start-ver=1.4
cd-journal=joma
no-vol=17
cd-vols=
no-issue=16
article-no=
start-page=4108
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2024
dt-pub=20240819
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Effect of Scaffold Geometrical Structure on Macrophage Polarization during Bone Regeneration Using Honeycomb Tricalcium Phosphate
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The polarization balance of M1/M2 macrophages with different functions is important in osteogenesis and bone repair processes. In a previous study, we succeeded in developing honeycomb tricalcium phosphate (TCP), which is a cylindrical scaffold with a honeycomb arrangement of straight pores, and we demonstrated that TCP with 300 and 500 mu m pore diameters (300TCP and 500TCP) induced bone formation within the pores. However, the details of the influence of macrophage polarization on bone formation using engineered biomaterials, especially with respect to the geometric structure of the artificial biomaterials, are unknown. In this study, we examined whether differences in bone tissue formation due to differences in TCP geometry were due to the polarity of the assembling macrophages. Immunohistochemistry for IBA-1, iNOS, and CD163 single staining was performed. The 300TCP showed a marked infiltration of iNOS-positive cells, which are thought to be M1 macrophages, during the osteogenesis process, while no involvement of CD163-positive cells, which are thought to be M2 macrophages, was observed in the TCP pores. In addition, 500TCP showed a clustering of iNOS-positive cells and CD163-positive cells at 2 weeks, suggesting the involvement of M2 macrophages in the formation of bone tissue in the TCP pores. In conclusion, we demonstrated for the first time that the geometrical structure of the artificial biomaterial, i.e., the pore size of honeycomb TCP, affects the polarization of M1/2 macrophages and bone tissue formation in TCP pores.
en-copyright=
kn-copyright=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TsujigiwaHidetsugu
en-aut-sei=Tsujigiwa
en-aut-mei=Hidetsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=ChangAnqi
en-aut-sei=Chang
en-aut-mei=Anqi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=PiaoTianyan
en-aut-sei=Piao
en-aut-mei=Tianyan
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=InadaYasunori
en-aut-sei=Inada
en-aut-mei=Yasunori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=ArashimaTakuma
en-aut-sei=Arashima
en-aut-mei=Takuma
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=MorimatsuAyumi
en-aut-sei=Morimatsu
en-aut-mei=Ayumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=TanakaAyumi
en-aut-sei=Tanaka
en-aut-mei=Ayumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Life Science, Faculty of Science, Okayama University of Science
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=honeycomb TCP
kn-keyword=honeycomb TCP
en-keyword=bone formation
kn-keyword=bone formation
en-keyword=macrophages
kn-keyword=macrophages
en-keyword=polarization
kn-keyword=polarization
END
start-ver=1.4
cd-journal=joma
no-vol=14
cd-vols=
no-issue=1
article-no=
start-page=17591
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2024
dt-pub=20240730
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Training high-performance deep learning classifier for diagnosis in oral cytology using diverse annotations
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The uncertainty of true labels in medical images hinders diagnosis owing to the variability across professionals when applying deep learning models. We used deep learning to obtain an optimal convolutional neural network (CNN) by adequately annotating data for oral exfoliative cytology considering labels from multiple oral pathologists. Six whole-slide images were processed using QuPath for segmenting them into tiles. The images were labeled by three oral pathologists, resulting in 14,535 images with the corresponding pathologists' annotations. Data from three pathologists who provided the same diagnosis were labeled as ground truth (GT) and used for testing. We investigated six models trained using the annotations of (1) pathologist A, (2) pathologist B, (3) pathologist C, (4) GT, (5) majority voting, and (6) a probabilistic model. We divided the test by cross-validation per slide dataset and examined the classification performance of the CNN with a ResNet50 baseline. Statistical evaluation was performed repeatedly and independently using every slide 10 times as test data. For the area under the curve, three cases showed the highest values (0.861, 0.955, and 0.991) for the probabilistic model. Regarding accuracy, two cases showed the highest values (0.988 and 0.967). For the models using the pathologists and GT annotations, many slides showed very low accuracy and large variations across tests. Hence, the classifier trained with probabilistic labels provided the optimal CNN for oral exfoliative cytology considering diagnoses from multiple pathologists. These results may lead to trusted medical artificial intelligence solutions that reflect diverse diagnoses of various professionals.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TanakaFuta
en-aut-sei=Tanaka
en-aut-mei=Futa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OchiaiTakanaga
en-aut-sei=Ochiai
en-aut-mei=Takanaga
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=ShimadaKatsumitsu
en-aut-sei=Shimada
en-aut-mei=Katsumitsu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=InoueYuta
en-aut-sei=Inoue
en-aut-mei=Yuta
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TakiYoshihiro
en-aut-sei=Taki
en-aut-mei=Yoshihiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NakaiFumi
en-aut-sei=Nakai
en-aut-mei=Fumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NakaiYasuhiro
en-aut-sei=Nakai
en-aut-mei=Yasuhiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=IshihamaTakanori
en-aut-sei=Ishihama
en-aut-mei=Takanori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=MiyazakiRyo
en-aut-sei=Miyazaki
en-aut-mei=Ryo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=MurakamiSatoshi
en-aut-sei=Murakami
en-aut-mei=Satoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=14
ORCID=
en-aut-name=MiyakeMinoru
en-aut-sei=Miyake
en-aut-mei=Minoru
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=15
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=5
en-affil=Division of Oral Pathogenesis and Disease Control, Department of Oral Pathology, Asahi University School of Dentistry
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology, Graduate School of Oral Medicine, Matsumoto Dental University
kn-affil=
affil-num=7
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=8
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=9
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
affil-num=10
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
affil-num=12
en-affil=Stony Brook Cancer Center, Stony Brook University
kn-affil=
affil-num=13
en-affil=Department of Oral Pathology, Graduate School of Oral Medicine, Matsumoto Dental University
kn-affil=
affil-num=14
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=15
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
en-keyword=Deep learning
kn-keyword=Deep learning
en-keyword=Oral cytology
kn-keyword=Oral cytology
en-keyword=Classification
kn-keyword=Classification
en-keyword=Convolutional neural network
kn-keyword=Convolutional neural network
en-keyword=Probabilistic labeling
kn-keyword=Probabilistic labeling
END
start-ver=1.4
cd-journal=joma
no-vol=9
cd-vols=
no-issue=10
article-no=
start-page=e174618
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2024
dt-pub=20240522
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Double-faced CX3CL1 enhances lymphangiogenesis-dependent metastasis in an aggressive subclone of oral squamous cell carcinoma
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Because cancer cells have a genetically unstable nature, they give rise to genetically different variant subclones inside a single tumor. Understanding cancer heterogeneity and subclone characteristics is crucial for developing more efficacious therapies. Oral squamous cell carcinoma (OSCC) is characterized by high heterogeneity and plasticity. On the other hand, CX3C motif ligand 1 (CX3CL1) is a double-faced chemokine with anti- and pro -tumor functions. Our study reported that CX3CL1 functioned differently in tumors with different cancer phenotypes, both in vivo and in vitro. Mouse OSCC 1 (MOC1) and MOC2 cells responded similarly to CX3CL1 in vitro. However, in vivo, CX3CL1 increased keratinization in indolent MOC1 cancer, while CX3CL1 promoted cervical lymphatic metastasis in aggressive MOC2 cancer. These outcomes were due to double-faced CX3CL1 effects on different immune microenvironments indolent and aggressive cancer created. Furthermore, we established that CX3CL1 promoted cancer metastasis via the lymphatic pathway by stimulating lymphangiogenesis and transendothelial migration of lymph -circulating tumor cells. CX3CL1 enrichment in lymphatic metastasis tissues was observed in aggressive murine and human cell lines. OSCC patient samples with CX3CL1 enrichment exhibited a strong correlation with lower overall survival rates and higher recurrence and distant metastasis rates. In conclusion, CX3CL1 is a pivotal factor that stimulates the metastasis of aggressive cancer subclones within the heterogeneous tumors to metastasize, and our study demonstrates the prognostic value of CX3CL1 enrichment in long-term monitoring in OSCC.
en-copyright=
kn-copyright=
en-aut-name=EainHtoo Shwe
en-aut-sei=Eain
en-aut-mei=Htoo Shwe
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakayamaMasaaki
en-aut-sei=Nakayama
en-aut-mei=Masaaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OharaToshiaki
en-aut-sei=Ohara
en-aut-mei=Toshiaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=FukuharaYoko
en-aut-sei=Fukuhara
en-aut-mei=Yoko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=ShanQuisheng
en-aut-sei=Shan
en-aut-mei=Quisheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=SoeYamin
en-aut-sei=Soe
en-aut-mei=Yamin
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=OnoKisho
en-aut-sei=Ono
en-aut-mei=Kisho
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=MizukawaNobuyoshi
en-aut-sei=Mizukawa
en-aut-mei=Nobuyoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=IidaSeiji
en-aut-sei=Iida
en-aut-mei=Seiji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=14
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Microbiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Pathology and Experimental Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama Universit
kn-affil=
affil-num=6
en-affil=Department of Oral Morphology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral and Maxillofacial Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=12
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=13
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=14
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=23
cd-vols=
no-issue=1
article-no=
start-page=843
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2023
dt-pub=20231108
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Ligneous periodontitis exacerbated by Behçet’s disease in a patient with plasminogen deficiency and a stop-gained variant PLG c.1468C > T: a case report
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Background Plasminogen serves as the precursor to plasmin, an essential element in the fibrinolytic process, and is synthesized primarily in the liver. Plasminogen activation occurs through the action of plasminogen activator, converting it into plasmin. This conversion greatly enhances the fibrinolytic system within tissues and blood vessels, facilitating the dissolution of fibrin clots. Consequently, congenital deficiency of plasminogen results in impaired fibrin degradation. Patients with plasminogen deficiency typically exhibit fibrin deposits in various mucosal sites throughout the body, including the oral cavity, eyes, vagina, and digestive organs. Behcet's disease is a chronic recurrent systemic inflammatory disease with four main symptoms: aphthous ulcers of the oral mucosa, vulvar ulcers, skin symptoms, and eye symptoms, and has been reported worldwide. This disease is highly prevalent around the Silk Road from the Mediterranean to East Asia.
We report a case of periodontitis in a patient with these two rare diseases that worsened quickly, leading to alveolar bone destruction. Genetic testing revealed a novel variant characterized by a stop-gain mutation, which may be a previously unidentified etiologic gene associated with decreased plasminogen activity.
Case presentation This case report depicts a patient diagnosed with ligneous gingivitis during childhood, originating from plasminogen deficiency and progressing to periodontitis. Genetic testing revealed a suspected association with the PLG c.1468C > T (p.Arg490*) stop-gain mutation. The patient's periodontal condition remained stable with brief intervals of supportive periodontal therapy. However, the emergence of Behçet's disease induced acute systemic inflammation, necessitating hospitalization and treatment with steroids. During hospitalization, the dental approach focused on maintaining oral hygiene and alleviating contact-related pain. The patient's overall health improved with inpatient care and the periodontal tissues deteriorated.
Conclusions Collaborative efforts between medical and dental professionals are paramount in comprehensively evaluating and treating patients with intricate complications from rare diseases. Furthermore, the PLG c.1468C > T (p.Arg490*) stop-gain mutation could contribute to the association between plasminogen deficiency and related conditions.
en-copyright=
kn-copyright=
en-aut-name=Shinoda-ItoYuki
en-aut-sei=Shinoda-Ito
en-aut-mei=Yuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=HiraiAnna
en-aut-sei=Hirai
en-aut-mei=Anna
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=OmoriKazuhiro
en-aut-sei=Omori
en-aut-mei=Kazuhiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=IdeguchiHidetaka
en-aut-sei=Ideguchi
en-aut-mei=Hidetaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=YamamotoHideki
en-aut-sei=Yamamoto
en-aut-mei=Hideki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=KatoFumino
en-aut-sei=Kato
en-aut-mei=Fumino
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=ObataKyoichi
en-aut-sei=Obata
en-aut-mei=Kyoichi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=OgawaTatsuo
en-aut-sei=Ogawa
en-aut-mei=Tatsuo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NakadoiTakato
en-aut-sei=Nakadoi
en-aut-mei=Takato
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=KatsuyamaEri
en-aut-sei=Katsuyama
en-aut-mei=Eri
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=IbaragiSoichiro
en-aut-sei=Ibaragi
en-aut-mei=Soichiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=YamamotoTadashi
en-aut-sei=Yamamoto
en-aut-mei=Tadashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=14
ORCID=
en-aut-name=HirasawaAkira
en-aut-sei=Hirasawa
en-aut-mei=Akira
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=15
ORCID=
en-aut-name=TakashibaShogo
en-aut-sei=Takashiba
en-aut-mei=Shogo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=16
ORCID=
affil-num=1
en-affil=Department of Pathophysiology‑Periodontal Science, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Periodontics and Endodontics, Division of Dentistry, Okayama University Hospital
kn-affil=
affil-num=3
en-affil=Department of Pathophysiology‑Periodontal Science, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Periodontics and Endodontics, Division of Dentistry, Okayama University Hospital
kn-affil=
affil-num=5
en-affil=Department of Clinical Genomic Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Clinical Genomic Medicine, Okayama University Hospital
kn-affil=
affil-num=7
en-affil=Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=The Center for Graduate Medical Education (Dental Division), Okayama University Hospital
kn-affil=
affil-num=11
en-affil=Department of Nephrology, Rheumatology, Endocrinology and Metabolism, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=12
en-affil=Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=13
en-affil=The Center for Graduate Medical Education (Dental Division), Okayama University Hospital
kn-affil=
affil-num=14
en-affil=Department of Oral Pathology and Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=15
en-affil=Department of Clinical Genomic Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=16
en-affil=Department of Pathophysiology‑Periodontal Science, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=Ligneous periodontitis
kn-keyword=Ligneous periodontitis
en-keyword=Plasminogen deficiency
kn-keyword=Plasminogen deficiency
en-keyword=PLG
kn-keyword=PLG
en-keyword=Behcet's disease
kn-keyword=Behcet's disease
en-keyword=Gingival hyperplasia
kn-keyword=Gingival hyperplasia
END
start-ver=1.4
cd-journal=joma
no-vol=24
cd-vols=
no-issue=5
article-no=
start-page=382
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220913
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Investigation of bone invasion and underlying mechanisms of oral cancer using a cell line‑derived xenograft model
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The cancer stroma regulates bone invasion in oral squamous cell carcinoma (OSCC). However, data on normal stroma are limited. In the present study, the effects of gingival and periodontal ligament tissue‑derived stromal cells (G‑SCs and P‑SCs, respectively) and human dermal fibroblasts (HDFs) on bone resorption and osteoclast activation were assessed using hematoxylin and eosin and tartrate‑resistant acid phosphatase staining in a cell line‑derived xenograft model. The results demonstrated that G‑SCs promoted bone invasion and osteoclast activation and inhibited osteoclast proliferation following crosstalk with the human OSCC HSC‑3 cell line, whereas P‑SCs inhibited bone resorption and promoted osteoclast proliferation in vitro but had a minimal effect on osteoclast activation both in vitro and in vivo following crosstalk with HSC‑3 cells. Furthermore, the effects of G‑SCs, P‑SCs and HDFs on protein expression levels of matrix metalloproteinase (MMP)‑9, membrane type 1 MMP (MT1‑MMP), Snail, parathyroid hormone‑related peptide (PTHrP) and receptor activator of NF‑κB ligand (RANKL) in HSC‑3 cells in OSCC bone invasion regions were assessed using immunohistochemistry. The results demonstrated that G‑SCs had a more prominent effect on the expression of MMP‑9, MT1‑MMP, Snail, PTHrP, and RANKL, whereas P‑SCs only promoted RANKL and PTHrP expression and exerted a minimal effect on MMP‑9, MT1‑MMP and Snail expression. The potential genes underlying the differential effects of G‑SCs and P‑SCs on bone invasion in OSCC were evaluated using a microarray, which indicated that cyclin‑dependent kinase 1, insulin, aurora kinase A, cyclin B1 and DNA topoisomerase II alpha underlaid these differential effects. Therefore, these results demonstrated that G‑SCs promoted bone invasion in OSCC by activating osteoclasts on the bone surface, whereas P‑SCs exerted an inhibitory effect. These findings could indicate a potential regulatory mechanism for bone invasion in OSCC.
en-copyright=
kn-copyright=
en-aut-name=ShanQiusheng
en-aut-sei=Shan
en-aut-mei=Qiusheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=OmoriHaruka
en-aut-sei=Omori
en-aut-mei=Haruka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FujiiMasae
en-aut-sei=Fujii
en-aut-mei=Masae
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=InadaYasunori
en-aut-sei=Inada
en-aut-mei=Yasunori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=SanoSho
en-aut-sei=Sano
en-aut-mei=Sho
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=11
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
en-keyword=oral squamous cell carcinoma
kn-keyword=oral squamous cell carcinoma
en-keyword=bone invasion
kn-keyword=bone invasion
en-keyword=gingival ligament tissue‑derived stromal cell
kn-keyword=gingival ligament tissue‑derived stromal cell
en-keyword=periodontal ligament tissue‑derived stromal cell
kn-keyword=periodontal ligament tissue‑derived stromal cell
en-keyword=xenograft model
kn-keyword=xenograft model
en-keyword=microarray
kn-keyword=microarray
END
start-ver=1.4
cd-journal=joma
no-vol=47
cd-vols=
no-issue=4
article-no=
start-page=81
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220224
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Significance of cancer stroma for bone destruction in oral squamous cell carcinoma using different cancer stroma subtypes
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Stromal cells in the tumor microenvironment (TME) can regulate the progression of numerous types of cancer; however, the bone invasion of oral squamous cell carcinoma (OSCC) has been poorly investigated. In the present study, the effect of verrucous SCC‑associated stromal cells (VSCC‑SCs), SCC‑associated stromal cells (SCC‑SCs) and human dermal fibroblasts on bone resorption and the activation of HSC‑3 osteoclasts in vivo were examined by hematoxylin and eosin, AE1/3 (pan‑cytokeratin) and tartrate‑resistant acid phosphatase staining. In addition, the expression levels of matrix metalloproteinase (MMP)9, membrane‑type 1 MMP (MT1‑MMP), Snail, receptor activator of NF‑κB ligand (RANKL) and parathyroid hormone‑related peptide (PTHrP) in the bone invasion regions of HSC‑3 cells were examined by immunohistochemistry. The results suggested that both SCC‑SCs and VSCC‑SCs promoted bone resorption, the activation of osteoclasts, and the expression levels of MMP9, MT1‑MMP, Snail, RANKL and PTHrP. However, SCC‑SCs had a more prominent effect compared with VSCC‑SCs. Finally, microarray data were used to predict potential genes underlying the differential effects of VSCC‑SCs and SCC‑SCs on bone invasion in OSCC. The results revealed that IL1B, ICAM1, FOS, CXCL12, INS and NGF may underlie these differential effects. In conclusion, both VSCC‑SCs and SCC‑SCs may promote bone invasion in OSCC by enhancing the expression levels of RANKL in cancer and stromal cells mediated by PTHrP; however, SCC‑SCs had a more prominent effect. These findings may represent a potential regulatory mechanism underlying the bone invasion of OSCC.
en-copyright=
kn-copyright=
en-aut-name=ShanQiusheng
en-aut-sei=Shan
en-aut-mei=Qiusheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=InadaYasunori
en-aut-sei=Inada
en-aut-mei=Yasunori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FushimiShigeko
en-aut-sei=Fushimi
en-aut-mei=Shigeko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=6
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
en-keyword=oral squamous cell carcinoma
kn-keyword=oral squamous cell carcinoma
en-keyword=bone invasion
kn-keyword=bone invasion
en-keyword=osteoclast
kn-keyword=osteoclast
en-keyword=receptor activator of NF‑κB ligand
kn-keyword=receptor activator of NF‑κB ligand
en-keyword=parathyroid hormone‑related peptide
kn-keyword=parathyroid hormone‑related peptide
en-keyword=microarray
kn-keyword=microarray
en-keyword=cancer‑associated stromal cells
kn-keyword=cancer‑associated stromal cells
END
start-ver=1.4
cd-journal=joma
no-vol=11
cd-vols=
no-issue=10
article-no=
start-page=1730
end-page=1740
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20221027
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Lip pleomorphic adenomas: case series and literature review
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Background: Pleomorphic adenoma (PA) is the most frequent benign salivary gland tumor, but a lip PA is rare. Although this tumor may be definitively diagnosed by imaging or a tissue biopsy if it is reasonably large, PAs on the lip are relatively small, and they present findings that are similar to those of other lip lesions, which can make a preoperative diagnosis difficult.
Methods: We analyzed all PAs in the oral region and lesions on the lips treated in our department over the past 20 years, and we discuss them together with the relevant literature.
Results: We found that 11.8% (n=6) of the PAs occurred on a lip (upper lip: 9.8%, lower lip: 2.0%), and ~1% of all mass lesions of the lips were PAs. The average size of the lip PAs was 1.5±0.7 cm (range, 0.7–2.2 cm). For preoperative diagnostic assistance, ultrasonography (US) (n=4), magnetic resonance (MR) (n=3), or no imaging (n=2) was used. An excisional biopsy was performed in all cases, and to date, no recurrence or malignant transformation has been observed.
Conclusions: Lip PA is relatively rare. Because almost all of these lesions are small, a preoperative diagnosis is more difficult compared to palatal lesions. This tumor is also prone to long-term neglect and has the potential for recurrence and malignant transformation. It is thus necessary to perform an excision that includes the capsule and surrounding tissues, and careful postoperative follow-up should be continued.
en-copyright=
kn-copyright=
en-aut-name=UmemoriKoki
en-aut-sei=Umemori
en-aut-mei=Koki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=OnoKisho
en-aut-sei=Ono
en-aut-mei=Kisho
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=KanemotoHideka
en-aut-sei=Kanemoto
en-aut-mei=Hideka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=ObataKyoichi
en-aut-sei=Obata
en-aut-mei=Kyoichi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakamuraTomoya
en-aut-sei=Nakamura
en-aut-mei=Tomoya
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=IbaragiSoichiro
en-aut-sei=Ibaragi
en-aut-mei=Soichiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=SasakiAkira
en-aut-sei=Sasaki
en-aut-mei=Akira
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
affil-num=1
en-affil=Department of Oral and Maxillofacial Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Oral and Maxillofacial Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=3
en-affil=Department of Oral and Maxillofacial Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=4
en-affil=Department of Oral and Maxillofacial Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=6
en-affil=Department of Oral and Maxillofacial Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=Department of Oral and Maxillofacial Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=10
en-affil=Department of Oral and Maxillofacial Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
en-keyword=Pleomorphic adenoma (PA)
kn-keyword=Pleomorphic adenoma (PA)
en-keyword=upper lip
kn-keyword=upper lip
en-keyword=lower lip
kn-keyword=lower lip
en-keyword=minor salivary gland tumor
kn-keyword=minor salivary gland tumor
en-keyword=case series
kn-keyword=case series
END
start-ver=1.4
cd-journal=joma
no-vol=13
cd-vols=
no-issue=1
article-no=
start-page=11676
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2023
dt-pub=20230719
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Effectiveness of deep learning classifiers in histopathological diagnosis of oral squamous cell carcinoma by pathologists
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The study aims to identify histological classifiers from histopathological images of oral squamous cell carcinoma using convolutional neural network (CNN) deep learning models and shows how the results can improve diagnosis. Histopathological samples of oral squamous cell carcinoma were prepared by oral pathologists. Images were divided into tiles on a virtual slide, and labels (squamous cell carcinoma, normal, and others) were applied. VGG16 and ResNet50 with the optimizers stochastic gradient descent with momentum and spectral angle mapper (SAM) were used, with and without a learning rate scheduler. The conditions for achieving good CNN performances were identified by examining performance metrics. We used ROCAUC to statistically evaluate diagnostic performance improvement of six oral pathologists using the results from the selected CNN model for assisted diagnosis. VGG16 with SAM showed the best performance, with accuracy = 0.8622 and AUC = 0.9602. The diagnostic performances of the oral pathologists statistically significantly improved when the diagnostic results of the deep learning model were used as supplementary diagnoses (p-value = 0.031). By considering the learning results of deep learning model classifiers, the diagnostic accuracy of pathologists can be improved. This study contributes to the application of highly reliable deep learning models for oral pathological diagnosis.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TanakaFuta
en-aut-sei=Tanaka
en-aut-mei=Futa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=InoueYuta
en-aut-sei=Inoue
en-aut-mei=Yuta
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=KatsumitsuShimada
en-aut-sei=Katsumitsu
en-aut-mei=Shimada
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=NakaiFumi
en-aut-sei=Nakai
en-aut-mei=Fumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=NakaiYasuhiro
en-aut-sei=Nakai
en-aut-mei=Yasuhiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=MiyazakiRyo
en-aut-sei=Miyazaki
en-aut-mei=Ryo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
en-aut-name=MurakamiSatoshi
en-aut-sei=Murakami
en-aut-mei=Satoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=14
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=15
ORCID=
en-aut-name=MiyakeMinoru
en-aut-sei=Miyake
en-aut-mei=Minoru
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=16
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Pathology, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=3
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=4
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=5
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=6
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology, Graduate School of Oral Medicine, Matsumoto Dental University
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
affil-num=12
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
affil-num=13
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
affil-num=14
en-affil=Department of Oral Pathology, Graduate School of Oral Medicine, Matsumoto Dental University
kn-affil=
affil-num=15
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=16
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa University Faculty of Medicine
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=17
cd-vols=
no-issue=7
article-no=
start-page=e0269016
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220727
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Is attention branch network effective in classifying dental implants from panoramic radiograph images by deep learning?
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Attention mechanism, which is a means of determining which part of the forced data is emphasized, has attracted attention in various fields of deep learning in recent years. The purpose of this study was to evaluate the performance of the attention branch network (ABN) for implant classification using convolutional neural networks (CNNs). The data consisted of 10191 dental implant images from 13 implant brands that cropped the site, including dental implants as pretreatment, from digital panoramic radiographs of patients who underwent surgery at Kagawa Prefectural Central Hospital between 2005 and 2021. ResNet 18, 50, and 152 were evaluated as CNN models that were compared with and without the ABN. We used accuracy, precision, recall, specificity, F1 score, and area under the receiver operating characteristics curve as performance metrics. We also performed statistical and effect size evaluations of the 30-time performance metrics of the simple CNNs and the ABN model. ResNet18 with ABN significantly improved the dental implant classification performance for all the performance metrics. Effect sizes were equivalent to "Huge" for all performance metrics. In contrast, the classification performance of ResNet50 and 152 deteriorated by adding the attention mechanism. ResNet18 showed considerably high compatibility with the ABN model in dental implant classification (AUC = 0.9993) despite the small number of parameters. The limitation of this study is that only ResNet was verified as a CNN; further studies are required for other CNN models.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=TanakaFuta
en-aut-sei=Tanaka
en-aut-mei=Futa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=YamashitaKatsusuke
en-aut-sei=Yamashita
en-aut-mei=Katsusuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=KagayaTutaro
en-aut-sei=Kagaya
en-aut-mei=Tutaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Intelligence Science and Engineering, Graduate School of Natural Science and Technology, Gifu University
kn-affil=
affil-num=3
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=4
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=5
en-affil=Polytechnic Center Kagawa
kn-affil=
affil-num=6
en-affil=Department of Intelligence Science and Engineering, Graduate School of Natural Science and Technology, Gifu University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=10
cd-vols=
no-issue=11
article-no=
start-page=2729
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20221028
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=SOD3 Expression in Tumor Stroma Provides the Tumor Vessel Maturity in Oral Squamous Cell Carcinoma
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Tumor angiogenesis is one of the hallmarks of solid tumor development. The progressive tumor cells produce the angiogenic factors and promote tumor angiogenesis. However, how the tumor stromal cells influence tumor vascularization is still unclear. In the present study, we evaluated the effects of oral squamous cell carcinoma (OSCC) stromal cells on tumor vascularization. The tumor stromal cells were isolated from two OSCC patients with different subtypes: low invasive verrucous squamous carcinoma (VSCC) and highly invasive squamous cell carcinoma (SCC) and co-xenografted with the human OSCC cell line (HSC-2) on nude mice. In comparison, the CD34+ vessels in HSC-2+VSCC were larger than in HSC-2+SCC. Interestingly, the vessels in the HSC-2+VSCC expressed vascular endothelial cadherin (VE-cadherin), indicating well-formed vascularization. Our microarray data revealed that the expression of extracellular superoxide dismutase, SOD3 mRNA is higher in VSCC stromal cells than in SCC stromal cells. Moreover, we observed that SOD3 colocalized with VE-cadherin on endothelial cells of low invasive stroma xenograft. These data suggested that SOD3 expression in stromal cells may potentially regulate tumor vascularization in OSCC. Thus, our study suggests the potential interest in SOD3-related vascular integrity for a better OSCC therapeutic strategy.
en-copyright=
kn-copyright=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=EainHtoo Shwe
en-aut-sei=Eain
en-aut-mei=Htoo Shwe
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=SoeYamin
en-aut-sei=Soe
en-aut-mei=Yamin
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=SanouSho
en-aut-sei=Sanou
en-aut-mei=Sho
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=ShanQiusheng
en-aut-sei=Shan
en-aut-mei=Qiusheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=InadaYasunori
en-aut-sei=Inada
en-aut-mei=Yasunori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=FujiiMasae
en-aut-sei=Fujii
en-aut-mei=Masae
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=FukuharaYoko
en-aut-sei=Fukuhara
en-aut-mei=Yoko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=WangZiyi
en-aut-sei=Wang
en-aut-mei=Ziyi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=OnoMitsuaki
en-aut-sei=Ono
en-aut-mei=Mitsuaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=14
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=15
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Morphology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University,
kn-affil=
affil-num=11
en-affil=Department of Molecular Biology and Biochemistry, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=12
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=13
en-affil=Department of Molecular Biology and Biochemistry, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=14
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=15
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=oral squamous cell carcinoma
kn-keyword=oral squamous cell carcinoma
en-keyword=tumor microenvironment
kn-keyword=tumor microenvironment
en-keyword=tumor stroma
kn-keyword=tumor stroma
en-keyword=tumor vascularization
kn-keyword=tumor vascularization
en-keyword=extracellular superoxide dismutase (SOD3)
kn-keyword=extracellular superoxide dismutase (SOD3)
en-keyword=vascular endothelial cadherin (Ve-cadherin)
kn-keyword=vascular endothelial cadherin (Ve-cadherin)
END
start-ver=1.4
cd-journal=joma
no-vol=12
cd-vols=
no-issue=1
article-no=
start-page=16925
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20221008
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=In this study, the accuracy of the positional relationship of the contact between the inferior alveolar canal and mandibular third molar was evaluated using deep learning. In contact analysis, we investigated the diagnostic performance of the presence or absence of contact between the mandibular third molar and inferior alveolar canal. We also evaluated the diagnostic performance of bone continuity diagnosed based on computed tomography as a continuity analysis. A dataset of 1279 images of mandibular third molars from digital radiographs taken at the Department of Oral and Maxillofacial Surgery at a general hospital (2014-2021) was used for the validation. The deep learning models were ResNet50 and ResNet50v2, with stochastic gradient descent and sharpness-aware minimization (SAM) as optimizers. The performance metrics were accuracy, precision, recall, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). The results indicated that ResNet50v2 using SAM performed excellently in the contact and continuity analyses. The accuracy and AUC were 0.860 and 0.890 for the contact analyses and 0.766 and 0.843 for the continuity analyses. In the contact analysis, SAM and the deep learning model performed effectively. However, in the continuity analysis, none of the deep learning models demonstrated significant classification performance.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TanakaFuta
en-aut-sei=Tanaka
en-aut-mei=Futa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=YamashitaKatsusuke
en-aut-sei=Yamashita
en-aut-mei=Katsusuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=3
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=4
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=5
en-affil=Polytechnic Center Kagawa
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=12
cd-vols=
no-issue=1
article-no=
start-page=13281
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220802
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Effective deep learning for oral exfoliative cytology classification
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The use of sharpness aware minimization (SAM) as an optimizer that achieves high performance for convolutional neural networks (CNNs) is attracting attention in various fields of deep learning. We used deep learning to perform classification diagnosis in oral exfoliative cytology and to analyze performance, using SAM as an optimization algorithm to improve classification accuracy. The whole image of the oral exfoliation cytology slide was cut into tiles and labeled by an oral pathologist. CNN was VGG16, and stochastic gradient descent (SGD) and SAM were used as optimizers. Each was analyzed with and without a learning rate scheduler in 300 epochs. The performance metrics used were accuracy, precision, recall, specificity, F1 score, AUC, and statistical and effect size. All optimizers performed better with the rate scheduler. In particular, the SAM effect size had high accuracy (11.2) and AUC (11.0). SAM had the best performance of all models with a learning rate scheduler. (AUC = 0.9328) SAM tended to suppress overfitting compared to SGD. In oral exfoliation cytology classification, CNNs using SAM rate scheduler showed the highest classification performance. These results suggest that SAM can play an important role in primary screening of the oral cytological diagnostic environment.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TanakaFuta
en-aut-sei=Tanaka
en-aut-mei=Futa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=YamashitaKatsusuke
en-aut-sei=Yamashita
en-aut-mei=Katsusuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=5
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=6
en-affil=Polytechnic Center Kagawa
kn-affil=
affil-num=7
en-affil=Department of Pathology, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=10
cd-vols=
no-issue=7
article-no=
start-page=1332
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220718
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Incidence and Risk of Anti-Resorptive Agent-Related Osteonecrosis of the Jaw after Tooth Extraction: A Retrospective Study
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Bone-modifying agents (BMA) such as bisphosphonates and denosumab are frequently used for the treatment of bone metastases, osteoporosis, and multiple myeloma. BMA may lead to anti-resorptive agent-related osteonecrosis of the jaw (ARONJ). This study aimed to clarify the risk factors for and probabilities of developing ARONJ after tooth extraction in patients undergoing BMA therapy. In this study, the records of 505 target sites of 302 patients undergoing BMA who presented with mandibular fractures at the Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital, from March 2014 to January 2022, were retrospectively analyzed for the onset of ARONJ after tooth extraction. The following variables were investigated as attributes: anatomy, health status, and dental treatment. The correlation coefficient was calculated for the success or failure of endodontic surgery for each variable, the odds ratio was calculated for the upper variable, and the factors related to the onset of ARONJ were identified. The incidence rate of ARONJ was found to be 3.2%. Hypoparathyroidism was an important factor associated with ARONJ development. Thus, systemic factors are more strongly related to the onset of ARONJ after tooth extraction than local factors.
en-copyright=
kn-copyright=
en-aut-name=ShimizuRieko
en-aut-sei=Shimizu
en-aut-mei=Rieko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=SukegawaYuka
en-aut-sei=Sukegawa
en-aut-mei=Yuka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=HasegawaKazuaki
en-aut-sei=Hasegawa
en-aut-mei=Kazuaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakamuraTomoya
en-aut-sei=Nakamura
en-aut-mei=Tomoya
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FujimuraAi
en-aut-sei=Fujimura
en-aut-mei=Ai
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=FujisawaAyaka
en-aut-sei=Fujisawa
en-aut-mei=Ayaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
affil-num=1
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=4
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=5
en-affil=Department of Pathology, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=6
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=7
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=8
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=12
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=13
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=anti-resorptive agent-related osteonecrosis of the jaw
kn-keyword=anti-resorptive agent-related osteonecrosis of the jaw
en-keyword=bisphosphonate
kn-keyword=bisphosphonate
en-keyword=denosumab
kn-keyword=denosumab
en-keyword=retrospective study
kn-keyword=retrospective study
en-keyword=risk factor
kn-keyword=risk factor
en-keyword=tooth extraction
kn-keyword=tooth extraction
END
start-ver=1.4
cd-journal=joma
no-vol=10
cd-vols=
no-issue=7
article-no=
start-page=1348
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220720
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=The Effectiveness of Pre-Operative Screening Tests in Determining Viral Infections in Patients Undergoing Oral and Maxillofacial Surgery
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=We analyzed the rate of patients with hepatitis B virus (HBV), hepatitis C virus (HCV), or human immunodeficiency virus (HIV) infection diagnosed by pre-operative screening and estimated its cost. We retrospectively analyzed patients who underwent elective surgery at our maxillofacial surgery department between April 2014 and March 2022. We compared the number of patients with each infection identified by pre-operative screening and a pre-operative questionnaire. We also compared the prevalence of infections with varying age, sex, and oral diseases, and calculated the cost of screening per positive result. The prevalence of HBV, HCV, and HIV was 0.39% (62/15,842), 0.76% (153/15,839), and 0.07% (10/12,745), respectively. The self-reported rates were as follows: HBV, 63.4% (26/41); HCV, 50.4% (62/123); HIV, 87.5% (7/8). Differences in sex were statistically significant for all infectious diseases; age significantly affected HBV and HCV rates. There was no association between the odds ratio of oral disease and viral infections. The cost per positive result was $1873.8, $905.8, and $11,895.3 for HBV, HCV, and HIV, respectively. Although self-assessment using questionnaires is partially effective, it has inadequate screening accuracy. Formulating an auxiliary diagnosis of infectious diseases with oral diseases was challenging. The cost determined was useful for hepatitis, but not HIV.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=SukegawaYuka
en-aut-sei=Sukegawa
en-aut-mei=Yuka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=HasegawaKazuaki
en-aut-sei=Hasegawa
en-aut-mei=Kazuaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=NakamuraTomoya
en-aut-sei=Nakamura
en-aut-mei=Tomoya
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=FujimuraAi
en-aut-sei=Fujimura
en-aut-mei=Ai
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FujisawaAyaka
en-aut-sei=Fujisawa
en-aut-mei=Ayaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=MukainakaYumika
en-aut-sei=Mukainaka
en-aut-mei=Yumika
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Pathology, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=5
en-affil= Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=6
en-affil= Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=7
en-affil= Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=12
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=13
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=hepatitis B
kn-keyword=hepatitis B
en-keyword=hepatitis C
kn-keyword=hepatitis C
en-keyword=human immunodeficiency virus
kn-keyword=human immunodeficiency virus
en-keyword=pre-operative examination
kn-keyword=pre-operative examination
END
start-ver=1.4
cd-journal=joma
no-vol=15
cd-vols=
no-issue=9
article-no=
start-page=3353
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220507
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Prognostic Factors in Endodontic Surgery Using an Endoscope: A 1 Year Retrospective Cohort Study
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=This retrospective study clarified the success rate of endoscopic endodontic surgeries and identified predictors accounting for successful surgeries. In this retrospective study, 242 patients (90 males, 152 females) who underwent endoscopic endodontic surgery at a single general hospital and were diagnosed through follow-up one year later were included. Risk factors were categorized into attributes, general health, anatomy, and surgery. Then, the correlation coefficient was calculated for the success or failure of endodontic surgery for each variable, the odds ratio was calculated for the upper variable, and factors related to the surgical prognosis factor were identified. The success rate of endodontic surgery was 95.3%, showing that it was a highly predictable treatment. The top three correlation coefficients were post, age, and perilesional sclerotic signs. Among them, the presence of posts was the highest, compared with the odds ratio, which was 9.592. This retrospective study revealed the success rate and risk factors accounting for endoscopic endodontic surgeries. Among the selected clinical variables, the presence of posts was the most decisive risk factor determining the success of endodontic surgeries.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=ShimizuRieko
en-aut-sei=Shimizu
en-aut-mei=Rieko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=SukegawaYuka
en-aut-sei=Sukegawa
en-aut-mei=Yuka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=HasegawaKazuaki
en-aut-sei=Hasegawa
en-aut-mei=Kazuaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=FujimuraAi
en-aut-sei=Fujimura
en-aut-mei=Ai
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=YamamotoIzumi
en-aut-sei=Yamamoto
en-aut-mei=Izumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=3
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=4
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=5
en-affil=Department of Pathology, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=6
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=7
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=11
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=12
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=retrospective cohort study
kn-keyword=retrospective cohort study
en-keyword=endoscope
kn-keyword=endoscope
en-keyword=endodontic surgery
kn-keyword=endodontic surgery
en-keyword=prognostic factors
kn-keyword=prognostic factors
END
start-ver=1.4
cd-journal=joma
no-vol=12
cd-vols=
no-issue=1
article-no=
start-page=6088
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220412
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lack of discernible symptoms. Hence, screening for osteoporosis with widely used dental panoramic radiographs would be very cost-effective and useful. In this study, we investigate the use of deep learning to classify osteoporosis from dental panoramic radiographs. In addition, the effect of adding clinical covariate data to the radiographic images on the identification performance was assessed. For objective labeling, a dataset containing 778 images was collected from patients who underwent both skeletal-bone-mineral density measurement and dental panoramic radiography at a single general hospital between 2014 and 2020. Osteoporosis was assessed from the dental panoramic radiographs using convolutional neural network (CNN) models, including EfficientNet-b0, -b3, and -b7 and ResNet-18, -50, and -152. An ensemble model was also constructed with clinical covariates added to each CNN. The ensemble model exhibited improved performance on all metrics for all CNNs, especially accuracy and AUC. The results show that deep learning using CNN can accurately classify osteoporosis from dental panoramic radiographs. Furthermore, it was shown that the accuracy can be improved using an ensemble model with patient covariates.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=FujimuraAi
en-aut-sei=Fujimura
en-aut-mei=Ai
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TaguchiAkira
en-aut-sei=Taguchi
en-aut-mei=Akira
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=YamamotoNorio
en-aut-sei=Yamamoto
en-aut-mei=Norio
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=KitamuraAkira
en-aut-sei=Kitamura
en-aut-mei=Akira
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=GotoRyosuke
en-aut-sei=Goto
en-aut-mei=Ryosuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=3
en-affil=Department of Oral and Maxillofacial Radiology, School of Dentistry, Matsumoto Dental University
kn-affil=
affil-num=4
en-affil=Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Search Space Inc.
kn-affil=
affil-num=6
en-affil=Search Space Inc.
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=12
cd-vols=
no-issue=1
article-no=
start-page=684
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220113
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Evaluation of multi-task learning in deep learning-based positioning classification of mandibular third molars
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Pell and Gregory, and Winter's classifications are frequently implemented to classify the mandibular third molars and are crucial for safe tooth extraction. This study aimed to evaluate the classification accuracy of convolutional neural network (CNN) deep learning models using cropped panoramic radiographs based on these classifications. We compared the diagnostic accuracy of single-task and multi-task learning after labeling 1330 images of mandibular third molars from digital radiographs taken at the Department of Oral and Maxillofacial Surgery at a general hospital (2014-2021). The mandibular third molar classifications were analyzed using a VGG 16 model of a CNN. We statistically evaluated performance metrics [accuracy, precision, recall, F1 score, and area under the curve (AUC)] for each prediction. We found that single-task learning was superior to multi-task learning (all p < 0.05) for all metrics, with large effect sizes and low p-values. Recall and F1 scores for position classification showed medium effect sizes in single and multi-task learning. To our knowledge, this is the first deep learning study to examine single-task and multi-task learning for the classification of mandibular third molars. Our results demonstrated the efficacy of implementing Pell and Gregory, and Winter's classifications for specific respective tasks.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=MatsuyamaTamamo
en-aut-sei=Matsuyama
en-aut-mei=Tamamo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TanakaFuta
en-aut-sei=Tanaka
en-aut-mei=Futa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=YamashitaKatsusuke
en-aut-sei=Yamashita
en-aut-mei=Katsusuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Molecular Oral Medicine and Maxillofacial Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University
kn-affil=
affil-num=3
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=4
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=5
en-affil=Department of Intelligence Science and Engineering, Graduate School of Natural Science and Technology, Gifu University
kn-affil=
affil-num=6
en-affil=Polytechnic Center Kagawa
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=7
cd-vols=
no-issue=1
article-no=
start-page=e148960
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20220111
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Resident stroma-secreted chemokine CCL2 governs myeloid-derived suppressor cells in the tumor microenvironment
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Accumulating evidence has shown that cancer stroma and BM-derived cells (BMDCs) in the tumor microenvironment (TME) play vital roles in tumor progression. However, the mechanism by which oral cancer stroma recruits any particular subset of BMDCs remains largely unknown. Here, we sought to identify the subset of BMDCs that is recruited by cancer stroma. We established a sequential transplantation model in BALB/c nude mice, including (a) BM transplantation of GFP-expressing cells and (b) coxenografting of patient-derived stroma (PDS; 2 cases, designated PDS1 and PDS2) with oral cancer cells (HSC-2). As controls, xenografting was performed with HSC-2 alone or in combination with normal human dermal fibroblasts (HDF). PDS1, PDS2, and HDF all promoted BMDC migration in vitro and recruitment in vivo. Multicolor immunofluorescence revealed that the PDS coxenografts recruited Arginase-1(+)CD11b(+)GR1(+)GFP(+) cells, which are myeloid-derived suppressor cells (MDSCs), to the TME, whereas the HDF coxenograft did not. Screening using microarrays revealed that PDS1 and PDS2 expressed CCL2 mRNA (encoding C-C motif chemokine ligand 2) at higher levels than did HDF. Indeed, PDS xenografts contained significantly higher proportions of CCL2(+) stromal cells and CCR2(+)Arginase-1(+)CD11b(+)GR1(+) MDSCs (as receiver cells) than the HDF coxenograft. Consistently, a CCL2 synthesis inhibitor and a CCR2 antagonist significantly inhibited the PDS-driven migration of BM cells in vitro. Furthermore, i.p. injection of the CCR2 antagonist to the PDS xenograft models significantly reduced the CCR2(+)Arginase-1(+)CD11b(+)GR1(+) MDSC infiltration to the TME. In conclusion, oral cancer stroma-secreted CCL2 is a key signal for recruiting CCR2(+) MDSCs from BM to the TME.
en-copyright=
kn-copyright=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=TomidaShuta
en-aut-sei=Tomida
en-aut-mei=Shuta
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=EguchiTakanori
en-aut-sei=Eguchi
en-aut-mei=Takanori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=OnoKisho
en-aut-sei=Ono
en-aut-mei=Kisho
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=ShanQiusheng
en-aut-sei=Shan
en-aut-mei=Qiusheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=OharaToshiaki
en-aut-sei=Ohara
en-aut-mei=Toshiaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=YoshidaSaori
en-aut-sei=Yoshida
en-aut-mei=Saori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=OmoriHaruka
en-aut-sei=Omori
en-aut-mei=Haruka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
en-aut-name=OkamotoKuniaki
en-aut-sei=Okamoto
en-aut-mei=Kuniaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=13
ORCID=
en-aut-name=SasakiAkira
en-aut-sei=Sasaki
en-aut-mei=Akira
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=14
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=15
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Center for Comprehensive Genomic Medicine, Okayama University Hospital
kn-affil=
affil-num=5
en-affil=Department of Dental Pharmacology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral and Maxillofacial Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Pathology and Experimental Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=12
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=13
en-affil=Department of Dental Pharmacology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=14
en-affil=Department of Oral and Maxillofacial Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=15
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
END
start-ver=1.4
cd-journal=joma
no-vol=14
cd-vols=
no-issue=1
article-no=
start-page=137
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20211228
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Cancer-Associated Stromal Cells Promote the Contribution of MMP2-Positive Bone Marrow-Derived Cells to Oral Squamous Cell Carcinoma Invasion
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Simple Summary Based on its invasiveness, oral squamous cell carcinoma (OSCC) shows two different subtypes: less-invasive verrucous squamous carcinoma (VSCC) or highly invasive squamous cell carcinoma (SCC). The stromal component influences OSCC progression and invasion. On the other hand, bone marrow-derived cells (BMDCs) are recruited into tumors and involved in tumor development. We hypothesized that stromal factors might also affect the relation of BMDCs and tumor invasion. We established the OSCC models transplanted with stromal cells from VSCC and SCC, and we compared the potential stromal factors of VSCC and SCC for the involvement of BMDCs in tumor invasion. Our study showed that stromal factors IL6 and IL1B might promote the contribution of MMP-2 positive BMDCs to OSCC invasion. Tumor stromal components contribute to tumor development and invasion. However, the role of stromal cells in the contribution of bone marrow-derived cells (BMDCs) in oral squamous cell carcinoma (OSCC) invasion is unclear. In the present study, we created two different invasive OSCC patient-derived stroma xenografts (PDSXs) and analyzed and compared the effects of stromal cells on the relation of BMDCs and tumor invasion. We isolated stromal cells from two OSCC patients: less invasive verrucous OSCC (VSCC) and highly invasive conventional OSCC (SCC) and co-xenografted with the OSCC cell line (HSC-2) on green fluorescent protein (GFP)-positive bone marrow (BM) cells transplanted mice. We traced the GFP-positive BM cells by immunohistochemistry (IHC) and detected matrix metalloproteinase 2 (MMP2) expression on BM cells by double fluorescent IHC. The results indicated that the SCC-PDSX promotes MMP2-positive BMDCs recruitment to the invasive front line of the tumor. Furthermore, microarray analysis revealed that the expressions of interleukin 6; IL-6 mRNA and interleukin 1 beta; IL1B mRNA were higher in SCC stromal cells than in VSCC stromal cells. Thus, our study first reports that IL-6 and IL1B might be the potential stromal factors promoting the contribution of MMP2-positive BMDCs to OSCC invasion.
en-copyright=
kn-copyright=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=ShanQiusheng
en-aut-sei=Shan
en-aut-mei=Qiusheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=EainHtoo Shwe
en-aut-sei=Eain
en-aut-mei=Htoo Shwe
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=oral squamous cell carcinoma invasion
kn-keyword=oral squamous cell carcinoma invasion
en-keyword=patient-derived stromal cell xenograft (PDSX)
kn-keyword=patient-derived stromal cell xenograft (PDSX)
en-keyword=bone marrow-derived cells (BMDCs)
kn-keyword=bone marrow-derived cells (BMDCs)
en-keyword=MMP2
kn-keyword=MMP2
en-keyword=stromal factor IL-6
kn-keyword=stromal factor IL-6
en-keyword=stromal factor IL1B
kn-keyword=stromal factor IL1B
END
start-ver=1.4
cd-journal=joma
no-vol=22
cd-vols=
no-issue=22
article-no=
start-page=12392
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20211117
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Comparing the Osteogenic Potential and Bone Regeneration Capacities of Dedifferentiated Fat Cells and Adipose-Derived Stem Cells In Vitro and In Vivo: Application of DFAT Cells Isolated by a Mesh Method
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Background: We investigated and compared the osteogenic potential and bone regeneration capacities of dedifferentiated fat cells (DFAT cells) and adipose-derived stem cells (ASCs).
Method: We isolated DFAT cells and ASCs from GFP mice. DFAT cells were established by a new culture method using a mesh culture instead of a ceiling culture. The isolated DFAT cells and ASCs were incubated in osteogenic medium, then alizarin red staining, alkaline phosphatase (ALP) assays, and RT-PCR (for RUNX2, osteopontin, DLX5, osterix, and osteocalcin) were performed to evaluate the osteoblastic differentiation ability of both cell types in vitro. In vivo, the DFAT cells and ASCs were incubated in osteogenic medium for four weeks and seeded on collagen composite scaffolds, then implanted subcutaneously into the backs of mice. We then performed hematoxylin and eosin staining and immunostaining for GFP and osteocalcin.
Results: The alizarin red-stained areas in DFAT cells showed weak calcification ability at two weeks, but high calcification ability at three weeks, similar to ASCs. The ALP levels of ASCs increased earlier than in DFAT cells and showed a significant difference (p < 0.05) at 6 and 9 days. The ALP levels of DFATs were higher than those of ASCs after 12 days. The expression levels of osteoblast marker genes (osterix and osteocalcin) of DFAT cells and ASCs were higher after osteogenic differentiation culture.
Conclusion: DFAT cells are easily isolated from a small amount of adipose tissue and are readily expanded with high purity; thus, DFAT cells are applicable to many tissue-engineering strategies and cell-based therapies.
en-copyright=
kn-copyright=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=MatsubaraMasakazu
en-aut-sei=Matsubara
en-aut-mei=Masakazu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=YamachikaEiki
en-aut-sei=Yamachika
en-aut-mei=Eiki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=FujitaYuki
en-aut-sei=Fujita
en-aut-mei=Yuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=ArimuraYuki
en-aut-sei=Arimura
en-aut-mei=Yuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakatsujiKazuki
en-aut-sei=Nakatsuji
en-aut-mei=Kazuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=NagatsukaHistoshi
en-aut-sei=Nagatsuka
en-aut-mei=Histoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=IidaSeiji
en-aut-sei=Iida
en-aut-mei=Seiji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Okayama University Hospital
kn-affil=
affil-num=5
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=9
en-affil=Department of Oral and Maxillofacial Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=dedifferentiated fat cells (DFAT cells)
kn-keyword=dedifferentiated fat cells (DFAT cells)
en-keyword=adipose-derived stem cells (ASCs)
kn-keyword=adipose-derived stem cells (ASCs)
en-keyword=bone regeneration
kn-keyword=bone regeneration
en-keyword=mesh culture method
kn-keyword=mesh culture method
END
start-ver=1.4
cd-journal=joma
no-vol=4
cd-vols=
no-issue=3
article-no=
start-page=24
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210812
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Lymphoepithelial Carcinoma in the Lateral Tongue: The Case Report
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Lymphoepithelial carcinoma (LEC) of the tongue is a rare subtype of squamous cell carcinoma. Histologically, it is an undifferentiated carcinoma with rich lymphocyte and plasma cell infiltration. The most common location for LEC in the head and neck is the salivary glands, and LEC of the oral cavity is extremely rare. The second case report of LEC in the lateral tongue is presented. In addition, a review of the literature was performed, and the relationship between LEC and Epstein-Barr virus infection was considered.
en-copyright=
kn-copyright=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=MarunakaHidenori
en-aut-sei=Marunaka
en-aut-mei=Hidenori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=YanaiHiroyuki
en-aut-sei=Yanai
en-aut-mei=Hiroyuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NishidaKenji
en-aut-sei=Nishida
en-aut-mei=Kenji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=TojiTomohiro
en-aut-sei=Toji
en-aut-mei=Tomohiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=YoshinoTadashi
en-aut-sei=Yoshino
en-aut-mei=Tadashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
affil-num=1
en-affil=Department of Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Otolaryngology Head and Neck Surgery, Okayama University Hospital
kn-affil=
affil-num=3
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=7
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=Lymphoepithelial carcinoma
kn-keyword=Lymphoepithelial carcinoma
en-keyword=oral cavity
kn-keyword=oral cavity
en-keyword=lateral tongue
kn-keyword=lateral tongue
END
start-ver=1.4
cd-journal=joma
no-vol=57
cd-vols=
no-issue=8
article-no=
start-page=846
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210820
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Effect of Patient Clinical Variables in Osteoporosis Classification Using Hip X-rays in Deep Learning Analysis
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Background and Objectives: A few deep learning studies have reported that combining image features with patient variables enhanced identification accuracy compared with image-only models. However, previous studies have not statistically reported the additional effect of patient variables on the image-only models. This study aimed to statistically evaluate the osteoporosis identification ability of deep learning by combining hip radiographs with patient variables. Materials andMethods: We collected a dataset containing 1699 images from patients who underwent skeletal-bone-mineral density measurements and hip radiography at a general hospital from 2014 to 2021. Osteoporosis was assessed from hip radiographs using convolutional neural network (CNN) models (ResNet18, 34, 50, 101, and 152). We also investigated ensemble models with patient clinical variables added to each CNN. Accuracy, precision, recall, specificity, F1 score, and area under the curve (AUC) were calculated as performance metrics. Furthermore, we statistically compared the accuracy of the image-only model with that of an ensemble model that included images plus patient factors, including effect size for each performance metric. Results: All metrics were improved in the ResNet34 ensemble model compared with the image-only model. The AUC score in the ensemble model was significantly improved compared with the image-only model (difference 0.004; 95% CI 0.002-0.0007; p = 0.0004, effect size: 0.871). Conclusions: This study revealed the additional effect of patient variables in identification of osteoporosis using deep CNNs with hip radiographs. Our results provided evidence that the patient variables had additive synergistic effects on the image in osteoporosis identification.
en-copyright=
kn-copyright=
en-aut-name=YamamotoNorio
en-aut-sei=Yamamoto
en-aut-mei=Norio
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=YamashitaKazutaka
en-aut-sei=Yamashita
en-aut-mei=Kazutaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=ManabeMasaki
en-aut-sei=Manabe
en-aut-mei=Masaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=OzakiToshifumi
en-aut-sei=Ozaki
en-aut-mei=Toshifumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=KawasakiKeisuke
en-aut-sei=Kawasaki
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=YorifujiTakashi
en-aut-sei=Yorifuji
en-aut-mei=Takashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
affil-num=1
en-affil=Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Orthopedic Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=4
en-affil=Department of Radiation Technology, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Orthopaedic Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Orthopedic Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=12
en-affil=Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=patient variables
kn-keyword=patient variables
en-keyword=osteoporosis
kn-keyword=osteoporosis
en-keyword=deep learning
kn-keyword=deep learning
en-keyword=convolutional neural network
kn-keyword=convolutional neural network
en-keyword=ensemble model
kn-keyword=ensemble model
en-keyword=effect size
kn-keyword=effect size
END
start-ver=1.4
cd-journal=joma
no-vol=4
cd-vols=
no-issue=1
article-no=
start-page=5
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210222
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=A Case Report of Spindle Cell Carcinoma with Osteoid and Cartilage Formation in the Tongue
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Spindle cell carcinoma (SCSCC) with osteoid and/or cartilage formation in the head and neck is rare; only one case was reported in the tongue. Herein, we report an SCSCC with osteoid and cartilage formation of the tongue developed in an 85-year-old man, and then review the report.
en-copyright=
kn-copyright=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=MakinoTakuma
en-aut-sei=Makino
en-aut-mei=Takuma
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=YanaiHiroyuki
en-aut-sei=Yanai
en-aut-mei=Hiroyuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NishidaKenji
en-aut-sei=Nishida
en-aut-mei=Kenji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TaniguchiKohei
en-aut-sei=Taniguchi
en-aut-mei=Kohei
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=TojiTomohiro
en-aut-sei=Toji
en-aut-mei=Tomohiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=YoshinoTadashi
en-aut-sei=Yoshino
en-aut-mei=Tadashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
affil-num=1
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=2
en-affil=Department of Otolaryngology Head and Neck Surgery, Okayama University Hospital
kn-affil=
affil-num=3
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=8
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=9
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=11
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
en-keyword=spindle cell carcinoma
kn-keyword=spindle cell carcinoma
en-keyword=oral mucosa
kn-keyword=oral mucosa
en-keyword=tongue
kn-keyword=tongue
END
start-ver=1.4
cd-journal=joma
no-vol=4
cd-vols=
no-issue=1
article-no=
start-page=4
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210209
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=A Case Report of Primordial Odontogenic Tumor That Required Distinction from a Dentigerous Cyst
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Primordial odontogenic tumor (POT) is a rare odontogenic tumor characterized by a variably cellular loose fibrous tissue with areas similar to the dental papilla and covered by cuboidal to columnar epithelium. We herein report a case of POT in a 14-year-old boy. Computed tomography (CT) exhibited a round cavity with a defined cortical border circumscribing the tooth of the second molar. However, the gross finding was a solid mass, not a cyst. Histologically, the tumor consisted of dental papillalike myxoid connective tissue covered by columnar epithelium. Therefore, although the clinical diagnosis was dentigerous cyst (DC), we diagnosed POT based on histologic findings. Clinical findings of POT resemble DC, but the clinical behavior of POT is different to DC, such as cortical expansion and root resorption of teeth. Therefore, histological differentiation of POT from DC is critical for accurate diagnosis.
en-copyright=
kn-copyright=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=YoshinoTadashi
en-aut-sei=Yoshino
en-aut-mei=Tadashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
affil-num=1
en-affil=Department of Pathology, Okayama University Hospital
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=primordial odontogenic tumor
kn-keyword=primordial odontogenic tumor
en-keyword=dentigerous cyst
kn-keyword=dentigerous cyst
en-keyword=odontogenic tumor
kn-keyword=odontogenic tumor
END
start-ver=1.4
cd-journal=joma
no-vol=3
cd-vols=
no-issue=2
article-no=
start-page=6
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20200325
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Secretory Carcinoma of Salivary Gland with High-Grade Histology Arising in Hard Palate: A Case Report
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Secretory carcinoma (SC) is a recently described salivary gland tumor reported in the fourth edition of World Health Organization classification of head and neck tumors. SC is characterized by strong S-100 protein, mammaglobin, and vimentin immunoexpression, and harbors a t(12;15)(p13;q25) translocation which leads to ETV6-NTRK3 fusion product. Histologically, SC displays a lobulated growth pattern and is often composed of microcystic, tubular, and solid structures with abundant eosinophilic homogenous or bubbly secretion. SC is generally recognized as low-grade malignancy with low-grade histopathologic features, and metastasis is relatively uncommon. In this case, we described a SC of hard palate that underwent high grade transformation and metastasis to the cervical lymph node in a 54-year-old patient. In addition, this case showed different histological findings between primary lesion and metastasis lesion. Therefore, the diagnosis was confirmed by the presence of ETV6 translocation. Here, we report a case that occurred SC with high-grade transformation in the palate, and a review of the relevant literature is also presented.
en-copyright=
kn-copyright=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=YoshidaSaori
en-aut-sei=Yoshida
en-aut-mei=Saori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OmoriHaruka
en-aut-sei=Omori
en-aut-mei=Haruka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=QiushengShan
en-aut-sei=Qiusheng
en-aut-mei=Shan
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=UchidaKenichiro
en-aut-sei=Uchida
en-aut-mei=Kenichiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=MishimaKatsuaki
en-aut-sei=Mishima
en-aut-mei=Katsuaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral and Maxillofacial Surgery, Yamaguchi University Graduate School of Medicine
kn-affil=
affil-num=9
en-affil=Department of Oral and Maxillofacial Surgery, Yamaguchi University Graduate School of Medicine
kn-affil=
affil-num=10
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=secretory carcinoma
kn-keyword=secretory carcinoma
en-keyword=high-grade transformation
kn-keyword=high-grade transformation
en-keyword=ETV6-NTRK3 fusion
kn-keyword=ETV6-NTRK3 fusion
en-keyword=cervical lymph node metastasis
kn-keyword=cervical lymph node metastasis
END
start-ver=1.4
cd-journal=joma
no-vol=13
cd-vols=
no-issue=14
article-no=
start-page=3491
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210712
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=The Origin of Stroma Influences the Biological Characteristics of Oral Squamous Cell Carcinoma
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Simple Summary Normal stromal cells play a significant role in the progression of cancers but are poorly investigated in oral squamous cell carcinoma (OSCC). In this study, we found that stromal cells derived from the gingival and periodontal ligament tissues could inhibit differentiation and promote the proliferation, invasion, and migration of OSCC both in vitro and in vivo. Furthermore, microarray data suggested that genes, such as CDK1, BUB1B, TOP2A, DLGAP5, BUB1, and CCNB2, probably play a role in influencing the different effects of gingival stromal tissue cells (G-SCs) and periodontal ligament stromal cells (P-SCs) on the progression of OSCC. Therefore, both G-SCs and P-SCs could promote the progression of OSCC, which could be a potential regulatory mechanism in the progression of OSCC. Normal stromal cells surrounding the tumor parenchyma, such as the extracellular matrix (ECM), normal fibroblasts, mesenchymal stromal cells, and osteoblasts, play a significant role in the progression of cancers. However, the role of gingival and periodontal ligament tissue-derived stromal cells in OSCC progression is unclear. In this study, the effect of G-SCs and P-SCs on the differentiation, proliferation, invasion, and migration of OSCC cells in vitro was examined by Giemsa staining, Immunofluorescence (IF), (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) (MTS), invasion, and migration assays. Furthermore, the effect of G-SCs and P-SCs on the differentiation, proliferation, and bone invasion by OSCC cells in vivo was examined by hematoxylin-eosin (HE) staining, immunohistochemistry (IHC), and tartrate-resistant acid phosphatase (TRAP) staining, respectively. Finally, microarray data and bioinformatics analyses identified potential genes that caused the different effects of G-SCs and P-SCs on OSCC progression. The results showed that both G-SCs and P-SCs inhibited the differentiation and promoted the proliferation, invasion, and migration of OSCC in vitro and in vivo. In addition, genes, including CDK1, BUB1B, TOP2A, DLGAP5, BUB1, and CCNB2, are probably involved in causing the different effects of G-SCs and P-SCs on OSCC progression. Therefore, as a potential regulatory mechanism, both G-SCs and P-SCs can promote OSCC progression.
en-copyright=
kn-copyright=
en-aut-name=OmoriHaruka
en-aut-sei=Omori
en-aut-mei=Haruka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=ShanQiusheng
en-aut-sei=Shan
en-aut-mei=Qiusheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=TsujigiwaHidetsugu
en-aut-sei=Tsujigiwa
en-aut-mei=Hidetsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science
kn-affil=
en-keyword=gingival ligament tissue-derived stromal cells
kn-keyword=gingival ligament tissue-derived stromal cells
en-keyword=periodontal ligament tissue-derived stromal cells
kn-keyword=periodontal ligament tissue-derived stromal cells
en-keyword=oral squamous cell carcinoma
kn-keyword=oral squamous cell carcinoma
en-keyword=tumor microenvironment
kn-keyword=tumor microenvironment
en-keyword=biological character
kn-keyword=biological character
END
start-ver=1.4
cd-journal=joma
no-vol=11
cd-vols=
no-issue=6
article-no=
start-page=815
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210530
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Multi-Task Deep Learning Model for Classification of Dental Implant Brand and Treatment Stage Using Dental Panoramic Radiograph Images
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=It is necessary to accurately identify dental implant brands and the stage of treatment to ensure efficient care. Thus, the purpose of this study was to use multi-task deep learning to investigate a classifier that categorizes implant brands and treatment stages from dental panoramic radiographic images. For objective labeling, 9767 dental implant images of 12 implant brands and treatment stages were obtained from the digital panoramic radiographs of patients who underwent procedures at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2020. Five deep convolutional neural network (CNN) models (ResNet18, 34, 50, 101 and 152) were evaluated. The accuracy, precision, recall, specificity, F1 score, and area under the curve score were calculated for each CNN. We also compared the multi-task and single-task accuracies of brand classification and implant treatment stage classification. Our analysis revealed that the larger the number of parameters and the deeper the network, the better the performance for both classifications. Multi-tasking significantly improved brand classification on all performance indicators, except recall, and significantly improved all metrics in treatment phase classification. Using CNNs conferred high validity in the classification of dental implant brands and treatment stages. Furthermore, multi-task learning facilitated analysis accuracy.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=MatsuyamaTamamo
en-aut-sei=Matsuyama
en-aut-mei=Tamamo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=YamashitaKatsusuke
en-aut-sei=Yamashita
en-aut-mei=Katsusuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
affil-num=1
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=
affil-num=2
en-affil=Department of Intelligence Science and Engineering, Graduate School of Natural Science and Technology, Gifu University
kn-affil=
affil-num=3
en-affil=Department of Intelligence Science and Engineering, Graduate School of Natural Science and Technology, Gifu University
kn-affil=
affil-num=4
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=5
en-affil=Polytechnic Center Kagawa
kn-affil=
affil-num=6
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=
affil-num=7
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=
affil-num=8
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=
affil-num=9
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=
affil-num=10
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=multi-task learning
kn-keyword=multi-task learning
en-keyword=deep learning
kn-keyword=deep learning
en-keyword=artificial intelligence
kn-keyword=artificial intelligence
en-keyword=dental implant
kn-keyword=dental implant
en-keyword=classification
kn-keyword=classification
END
start-ver=1.4
cd-journal=joma
no-vol=14
cd-vols=
no-issue=12
article-no=
start-page=3286
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210614
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Biological Effects of Bioresorbable Materials in Alveolar Ridge Augmentation: Comparison of Early and Slow Resorbing Osteosynthesis Materials
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The purpose of this study was to investigate the bone healing properties and histological environment of a u-HA/PLLA/PGA (u-HA-uncalcined and unsintered hydroxyapatite, PLLA-Poly L-lactic acid, PGA-polyglycolic acid) composite device in humans, and to understand the histological dynamics of using this device for maxillofacial treatments. Twenty-one subjects underwent pre-implant maxillary alveolar ridge augmentation with mandibular cortical bone blocks using u-HA/PLLA or u-HA/PLLA/PGA screws for fixation. Six months later, specimens of these screws and their adjacent tissue were retrieved. A histological and immunohistochemical evaluation of these samples was performed using collagen 1a, ALP (alkaline phosphatase), and osteocalcin. We observed that alveolar bone augmentation was successful for all of the subjects. Upon histological evaluation, the u-HA/PLLA screws had merged with the bone components, and the bone was directly connected to the biomaterial. In contrast, direct bone connection was not observed for the u-HA/PLLA/PGA screw. Immunohistological findings showed that in the u-HA/PLLA group, collagen 1a was positive for fibers that penetrated vertically into the bone. Alkaline phosphatase was positive only in the u-HA/PLLA stroma, and the stroma was negative for osteocalcin. In this study, u-HA/PLLA showed a greater bioactive bone conductivity than u-HA/PLLA/PGA and a higher biocompatibility for direct bone attachment. Furthermore, u-HA/PLLA was shown to have the potential for bone formation in the stroma.
en-copyright=
kn-copyright=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Pathology, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=poly L-lactic acid
kn-keyword=poly L-lactic acid
en-keyword=uncalcined and unsintered hydroxyapatite
kn-keyword=uncalcined and unsintered hydroxyapatite
en-keyword=polyglycolic acid
kn-keyword=polyglycolic acid
en-keyword=alveolar ridge augmentation
kn-keyword=alveolar ridge augmentation
END
start-ver=1.4
cd-journal=joma
no-vol=14
cd-vols=
no-issue=12
article-no=
start-page=3409
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210620
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Preparation of Absorption-Resistant Hard Tissue Using Dental Pulp-Derived Cells and Honeycomb Tricalcium Phosphate
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=In recent years, there has been increasing interest in the treatment of bone defects using undifferentiated mesenchymal stem cells (MSCs) in vivo. Recently, dental pulp has been proposed as a promising source of pluripotent mesenchymal stem cells (MSCs), which can be used in various clinical applications. Dentin is the hard tissue that makes up teeth, and has the same composition and strength as bone. However, unlike bone, dentin is usually not remodeled under physiological conditions. Here, we generated odontoblast-like cells from mouse dental pulp stem cells and combined them with honeycomb tricalcium phosphate (TCP) with a 300 mu m hole to create bone-like tissue under the skin of mice. The bone-like hard tissue produced in this study was different from bone tissue, i.e., was not resorbed by osteoclasts and was less easily absorbed than the bone tissue. It has been suggested that hard tissue-forming cells induced from dental pulp do not have the ability to induce osteoclast differentiation. Therefore, the newly created bone-like hard tissue has high potential for absorption-resistant hard tissue repair and regeneration procedures.
en-copyright=
kn-copyright=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=InadaYasunori
en-aut-sei=Inada
en-aut-mei=Yasunori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=ShanQiusheng
en-aut-sei=Shan
en-aut-mei=Qiusheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FushimiShigeko
en-aut-sei=Fushimi
en-aut-mei=Shigeko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TsujigiwaHidetsugu
en-aut-sei=Tsujigiwa
en-aut-mei=Hidetsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
en-keyword=dental pulp
kn-keyword=dental pulp
en-keyword=mesenchymal stem cells
kn-keyword=mesenchymal stem cells
en-keyword=honeycomb TCP
kn-keyword=honeycomb TCP
en-keyword=matrix formation
kn-keyword=matrix formation
en-keyword=dentin formation
kn-keyword=dentin formation
en-keyword=osteodentin
kn-keyword=osteodentin
END
start-ver=1.4
cd-journal=joma
no-vol=18
cd-vols=
no-issue=8
article-no=
start-page=1824
end-page=1830
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210219
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Potential role of myeloid-derived suppressor cells in transition from reaction to repair phase of bone healing process
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of immature myeloid cells with immunosuppressive functions; these cells play a key role in infection, immunization, chronic inflammation, and cancer. Recent studies have reported that immunosuppression plays an important role in the healing process of tissues and that Treg play an important role in fracture healing. MDSCs suppress active T cell proliferation and reduce the severity of arthritis in mice and humans. Together, these findings suggest that MDSCs play a role in bone biotransformation. In the present study, we examined the role of MDSCs in the bone healing process by creating a bone injury at the tibial epiphysis in mice. MDSCs were identified by CD11b and GR1 immunohistochemistry and their role in new bone formation was observed by detection of Runx2 and osteocalcin expression. Significant numbers of MDSCs were observed in transitional areas from the reactionary to repair stages. Interestingly, MDSCs exhibited Runx2 and osteocalcin expression in the transitional area but not in the reactionary area. And at the same area, cllagene-1 and ALP expression level increased in osteoblast progenitor cells. These data is suggesting that MDSCs emerge to suppress inflammation and support new bone formation. Here, we report, for the first time (to our knowledge), the role of MDSCs in the initiation of bone formation. MDSC appeared at the transition from inflammation to bone making and regulates bone healing by suppressing inflammation.
en-copyright=
kn-copyright=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TsujigiwaHidetsugu
en-aut-sei=Tsujigiwa
en-aut-mei=Hidetsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Life Science, Faculty of Science, Okayama University of Science
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=myeloid-derived suppressor cells (MDSC)
kn-keyword=myeloid-derived suppressor cells (MDSC)
en-keyword=bone healing
kn-keyword=bone healing
en-keyword=transition period
kn-keyword=transition period
en-keyword=new bone formation
kn-keyword=new bone formation
END
start-ver=1.4
cd-journal=joma
no-vol=13
cd-vols=
no-issue=22
article-no=
start-page=5155
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20201116
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Geometrical Structure of Honeycomb TCP to Control Dental Pulp-Derived Cell Differentiation
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Recently, dental pulp has been attracting attention as a promising source of multipotent mesenchymal stem cells (MSCs) for various clinical applications of regeneration fields. To date, we have succeeded in establishing rat dental pulp-derived cells showing the characteristics of odontoblasts under in vitro conditions. We named them Tooth matrix-forming, GFP rat-derived Cells (TGC). However, though TGC form massive dentin-like hard tissues under in vivo conditions, this does not lead to the induction of polar odontoblasts. Focusing on the importance of the geometrical structure of an artificial biomaterial to induce cell differentiation and hard tissue formation, we previously have succeeded in developing a new biomaterial, honeycomb tricalcium phosphate (TCP) scaffold with through-holes of various diameters. In this study, to induce polar odontoblasts, TGC were induced to form odontoblasts using honeycomb TCP that had various hole diameters (75, 300, and 500 mu m) as a scaffold. The results showed that honeycomb TCP with 300-mu m hole diameters (300TCP) differentiated TGC into polar odontoblasts that were DSP positive. Therefore, our study indicates that 300TCP is an appropriate artificial biomaterial for dentin regeneration.
en-copyright=
kn-copyright=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TsujigiwaHidetsugu
en-aut-sei=Tsujigiwa
en-aut-mei=Hidetsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=InadaYasunori
en-aut-sei=Inada
en-aut-mei=Yasunori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=QiushengShan
en-aut-sei=Qiusheng
en-aut-mei=Shan
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=FushimiShigeko
en-aut-sei=Fushimi
en-aut-mei=Shigeko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
en-keyword=dental pulp
kn-keyword=dental pulp
en-keyword=honeycomb TCP
kn-keyword=honeycomb TCP
en-keyword=matrix formation
kn-keyword=matrix formation
en-keyword=dentin formation
kn-keyword=dentin formation
en-keyword=geometrical structure
kn-keyword=geometrical structure
en-keyword=scaffold
kn-keyword=scaffold
END
start-ver=1.4
cd-journal=joma
no-vol=10
cd-vols=
no-issue=11
article-no=
start-page=1534
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20201110
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 images from patients who underwent both skeletal bone mineral density measurement and hip radiography at a single general hospital between 2014 and 2019. Osteoporosis was assessed from the hip radiographs using five convolutional neural network (CNN) models. We also investigated ensemble models with clinical covariates added to each CNN. The accuracy, precision, recall, specificity, negative predictive value (npv), F1 score, and area under the curve (AUC) score were calculated for each network. In the evaluation of the five CNN models using only hip radiographs, GoogleNet and EfficientNet b3 exhibited the best accuracy, precision, and specificity. Among the five ensemble models, EfficientNet b3 exhibited the best accuracy, recall, npv, F1 score, and AUC score when patient variables were included. The CNN models diagnosed osteoporosis from hip radiographs with high accuracy, and their performance improved further with the addition of clinical covariates from patient records.
en-copyright=
kn-copyright=
en-aut-name=YamamotoNorio
en-aut-sei=Yamamoto
en-aut-mei=Norio
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=KitamuraAkira
en-aut-sei=Kitamura
en-aut-mei=Akira
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=GotoRyosuke
en-aut-sei=Goto
en-aut-mei=Ryosuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=NodaTomoyuki
en-aut-sei=Noda
en-aut-mei=Tomoyuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
en-aut-name=KawasakiKeisuke
en-aut-sei=Kawasaki
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=
en-aut-name=OzakiToshifumi
en-aut-sei=Ozaki
en-aut-mei=Toshifumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=
affil-num=1
en-affil=Department of Orthopaedic Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Search Space Inc.
kn-affil=
affil-num=4
en-affil=Search Space Inc.
kn-affil=
affil-num=5
en-affil=Department of Musculoskeletal Traumatology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=10
en-affil=Department of Orthopaedic Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=11
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=12
en-affil=Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
en-keyword=osteoporosis
kn-keyword=osteoporosis
en-keyword=deep learning
kn-keyword=deep learning
en-keyword=hip radiograph
kn-keyword=hip radiograph
en-keyword=ensemble model
kn-keyword=ensemble model
END
start-ver=1.4
cd-journal=joma
no-vol=13
cd-vols=
no-issue=21
article-no=
start-page=4761
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20201025
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Effect of Honeycomb β-TCP Geometrical Structure on Bone Tissue Regeneration in Skull Defect
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The effect of the geometric structure of artificial biomaterials on skull regeneration remains unclear. In a previous study, we succeeded in developing honeycomb beta-tricalcium phosphate (beta-TCP), which has through-and-through holes and is able to provide the optimum bone microenvironment for bone tissue regeneration. We demonstrated that beta-TCP with 300-mu m hole diameters induced vigorous bone formation. In the present study, we investigated how differences in hole directions of honeycomb beta-TCP (horizontal or vertical holes) influence bone tissue regeneration in skull defects. Honeycomb beta-TCP with vertical and horizontal holes was loaded with BMP-2 using Matrigel and Collagen gel as carriers, and transplanted into skull bone defect model rats. The results showed that in each four groups (Collagen alone group, Matrigel alone group, Collagen + BMP group and Matrigel + BMP-2), vigorous bone formation was observed on the vertical beta-TCP compared with horizontal beta-TCP. The osteogenic area was larger in the Matrigel groups (with and without BMP-2) than in the Collagen group (with and without BMP-2) in both vertical beta-TCP and horizontal beta-TCP. However, when BMP-2 was added, the bone formation area was not significantly different between the Collagen group and the Matrigel group in the vertical beta-TCP. Histological finding showed that, in vertical honeycomb beta-TCP, new bone formation extended to the upper part of the holes and was observed from the dura side to the periosteum side as added to the inner walls of the holes. Therefore, we can control efficient bone formation by creating a bone microenvironment provided by vertical honeycomb beta-TCP. Vertical honeycomb beta-TCP has the potential to be an excellent biomaterial for bone tissue regeneration in skull defects and is expected to have clinical applications.
en-copyright=
kn-copyright=
en-aut-name=WatanabeToshiyuki
en-aut-sei=Watanabe
en-aut-mei=Toshiyuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TsujigiwaHidetsugu
en-aut-sei=Tsujigiwa
en-aut-mei=Hidetsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=WatanabeSatoko
en-aut-sei=Watanabe
en-aut-mei=Satoko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=NakagiriRyoko
en-aut-sei=Nakagiri
en-aut-mei=Ryoko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=KimataYoshihiro
en-aut-sei=Kimata
en-aut-mei=Yoshihiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
affil-num=1
en-affil=Department of Plastic and Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=3
en-affil=Department of Life Science, Faculty of Science, Okayama University Science
kn-affil=
affil-num=4
en-affil=Department of Plastic and Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Plastic and Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=Department of Plastic and Reconstructive Surgery, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword= honeycomb β-TCP
kn-keyword= honeycomb β-TCP
en-keyword=bone tissue regeneration
kn-keyword=bone tissue regeneration
en-keyword=bone microenvironment
kn-keyword=bone microenvironment
en-keyword=Vertical and Horizontal holes
kn-keyword=Vertical and Horizontal holes
en-keyword=geometrical structure
kn-keyword=geometrical structure
END
start-ver=1.4
cd-journal=joma
no-vol=21
cd-vols=
no-issue=20
article-no=
start-page=7714
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20201018
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Impact of the Stroma on the Biological Characteristics of the Parenchyma in Oral Squamous Cell Carcinoma
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Solid tumors consist of the tumor parenchyma and stroma. The standard concept of oncology is that the tumor parenchyma regulates the tumor stroma and promotes tumor progression, and that the tumor parenchyma represents the tumor itself and defines the biological characteristics of the tumor tissue. Thus, the tumor stroma plays a pivotal role in assisting tumor parenchymal growth and invasiveness and is regarded as a supporter of the tumor parenchyma. The tumor parenchyma and stroma interact with each other. However, the influence of the stroma on the parenchyma is not clear. Therefore, in this study, we investigated the effect of the stroma on the parenchyma in oral squamous cell carcinoma (OSCC). We isolated tumor stroma from two types of OSCCs with different invasiveness (endophytic type OSCC (ED-st) and exophytic type OSCC (EX-st)) and examined the effect of the stroma on the parenchyma in terms of proliferation, invasion, and morphology by co-culturing and co-transplanting the OSCC cell line (HSC-2) with the two types of stroma. Both types of stroma were partially positive for alpha-smooth muscle actin. The tumor stroma increased the proliferation and invasion of tumor cells and altered the morphology of tumor cells in vitro and in vivo. ED-st exerted a greater effect on the tumor parenchyma in proliferation and invasion than EX-st. Morphological analysis showed that ED-st changed the morphology of HSC-2 cells to the invasive type of OSCC, and EX-st altered the morphology of HSC-2 cells to verrucous OSCC. This study suggests that the tumor stroma influences the biological characteristics of the parenchyma and that the origin of the stroma is strongly associated with the biological characteristics of the tumor.
en-copyright=
kn-copyright=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=OmoriHaruka
en-aut-sei=Omori
en-aut-mei=Haruka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=QiushengShan
en-aut-sei=Qiusheng
en-aut-mei=Shan
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=OoMay Wathone
en-aut-sei=Oo
en-aut-mei=May Wathone
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=TsujigiwaHidetsugu
en-aut-sei=Tsujigiwa
en-aut-mei=Hidetsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=8
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
affil-num=9
en-affil=Department of Oral Pathology and Medicine Graduate School of Medicine, Dentistry and Pharmaceutical Science, Okayama University
kn-affil=
en-keyword=tumor stroma
kn-keyword=tumor stroma
en-keyword=tumor parenchyma
kn-keyword=tumor parenchyma
en-keyword=tumor microenvironment
kn-keyword=tumor microenvironment
en-keyword=biological characteristics
kn-keyword=biological characteristics
END
start-ver=1.4
cd-journal=joma
no-vol=15
cd-vols=
no-issue=1
article-no=
start-page=107
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20200910
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Clinical study on primary screening of oral cancer and precancerous lesions by oral cytology
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Background This study was conducted to compare the histological diagnostic accuracy of conventional oral-based cytology and liquid-based cytology (LBC) methods. Methods Histological diagnoses of 251 cases were classified as negative (no malignancy lesion, inflammation, or mild/moderate dysplasia) and positive [severe dysplasia/carcinoma in situ (CIS) and squamous cell carcinoma (SCC)]. Cytological diagnoses were classified as negative for intraepithelial lesion or malignancy (NILM), oral low-grade squamous intraepithelial lesion (OLSIL), oral high-grade squamous intraepithelial lesion (OHSIL), or SCC. Cytological diagnostic results were compared with histology results. Results Of NILM cytology cases, the most frequent case was negative [LBCn = 50 (90.9%), conventionaln = 22 (95.7%)]. Among OLSIL cytodiagnoses, the most common was negative (LBCn = 34; 75.6%, conventionaln = 14; 70.0%). Among OHSIL cytodiagnoses (LBCn = 51, conventionaln = 23), SCC was the most frequent (LBCn = 31; 60.8%, conventionaln = 7; 30.4%). Negative cases were common (LBCn = 13; 25.5%, conventionaln = 14; 60.9%). Among SCC cytodiagnoses SCC was the most common (LBCn = 16; 88.9%, conventionaln = 14; 87.5%). Regarding the diagnostic results of cytology, assuming OHSIL and SCC as cytologically positive, the LBC method/conventional method showed a sensitivity of 79.4%/76.7%, specificity of 85.1%/69.2%, false-positive rate of 14.9%/30.7%, and false-negative rate of 20.6%/23.3%. Conclusions LBC method was superior to conventional cytodiagnosis methods. It was especially superior for OLSIL and OHSIL. Because of the false-positive and false-negative cytodiagnoses, it is necessary to make a comprehensive diagnosis considering the clinical findings.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Pathology, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=7
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=Cytology
kn-keyword=Cytology
en-keyword=Pathology
kn-keyword=Pathology
en-keyword=Liquid-based cytology
kn-keyword=Liquid-based cytology
en-keyword=Screening
kn-keyword=Screening
en-keyword=Inflammation
kn-keyword=Inflammation
END
start-ver=1.4
cd-journal=joma
no-vol=10
cd-vols=
no-issue=7
article-no=
start-page=984
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20200701
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Deep Neural Networks for Dental Implant System Classification
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=In this study, we used panoramic X-ray images to classify and clarify the accuracy of different dental implant brands via deep convolutional neural networks (CNNs) with transfer-learning strategies. For objective labeling, 8859 implant images of 11 implant systems were used from digital panoramic radiographs obtained from patients who underwent dental implant treatment at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2019. Five deep CNN models (specifically, a basic CNN with three convolutional layers, VGG16 and VGG19 transfer-learning models, and finely tuned VGG16 and VGG19) were evaluated for implant classification. Among the five models, the finely tuned VGG16 model exhibited the highest implant classification performance. The finely tuned VGG19 was second best, followed by the normal transfer-learning VGG16. We confirmed that the finely tuned VGG16 and VGG19 CNNs could accurately classify dental implant systems from 11 types of panoramic X-ray images.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=YamashitaKatsusuke
en-aut-sei=Yamashita
en-aut-mei=Katsusuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=YamamotoNorio
en-aut-sei=Yamamoto
en-aut-mei=Norio
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=3
en-affil=Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University
kn-affil=
affil-num=4
en-affil=Polytechnic Center Kagawa
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=6
en-affil=Department of Orthopaedic Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=
kn-affil=
en-keyword=dental implant
kn-keyword=dental implant
en-keyword=artificial intelligence
kn-keyword=artificial intelligence
en-keyword=classification
kn-keyword=classification
en-keyword=deep learning
kn-keyword=deep learning
en-keyword=convolutional neural networks
kn-keyword=convolutional neural networks
END
start-ver=1.4
cd-journal=joma
no-vol=16
cd-vols=
no-issue=5
article-no=
start-page=766
end-page=773
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2019
dt-pub=20190528
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Immunohistochemistry of YAP and dNp63 and survival analysis of patients bearing precancerous lesion and oral squamous cell carcinoma
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Background: Yes-associated protein (YAP) is a candidate oncogene in various human cancers, and recently, it has been reported that YAP expression and its activity was enhanced by Delta Np63. However, the role of YAP and Delta Np63 expression in carcinogenesis and progression of oral squamous cell carcinoma (OSCC) has been unknown. Therefore, we investigated how YAP and Delta Np63 influence carcinogenesis and progression of OSCC.
Methods: We performed immunohistochemical analyses in whole tissue samples to investigate YAP and Delta Np63 expression in normal oral mucosa, epithelial hyperplasia, oral epithelial dysplasia (OED; low/high grade), carcinoma in situ (CIS), and OSCC. Furthermore, in OSCC, we analyzed clinical significance by using Kaplan-Meier survival analysis.
Results: In normal oral mucosa and epithelial hyperplasia, YAP expression was primarily confined to the basal and parabasal layers, but YAP expression was elevated in OED, CIS, and OSCC. In OED, YAP and Delta Np63 expression levels were markedly higher in high grade than in low grade. In OSCC groups, YAP and Delta Np63 expression patterns tended to differ according to histopathological differentiation of OSCC. Furthermore, the YAP high expression group, which showed YAP staining in >50% positive cells with strong cytoplasmic staining or >10% positive cells with nuclear reactivity, showed a tendency to have a poor survival rate.
Conclusion: YAP and Delta Np63 expression levels correlated with grade of oral OED. Additionally, YAP expression was associated with OSCC survival rate. Our results suggested that YAP and Delta Np63 expression might serve as predictive markers to distinguish OSCC development and progression.
en-copyright=
kn-copyright=
en-aut-name=OnoSawako
en-aut-sei=Ono
en-aut-mei=Sawako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil= Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil= Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=YAP
kn-keyword=YAP
en-keyword=ΔNp63
kn-keyword=ΔNp63
en-keyword=oral epithelial dysplasia
kn-keyword=oral epithelial dysplasia
en-keyword=carcinoma in situ
kn-keyword=carcinoma in situ
en-keyword=oral squamous cell carcinoma
kn-keyword=oral squamous cell carcinoma
END
start-ver=1.4
cd-journal=joma
no-vol=12
cd-vols=
no-issue=22
article-no=
start-page=3681
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2019
dt-pub=20191108
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Advantage of Alveolar Ridge Augmentation with Bioactive/Bioresorbable Screws Made of Composites of Unsintered Hydroxyapatite and Poly-L-lactide
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=We studied human bone healing characteristics and the histological osteogenic environment by using devices made of a composite of uncalcined and unsintered hydroxyapatite (u-HA) and poly-L-lactide (PLLA). In eight cases of fixation, we used u-HA/PLLA screws for maxillary alveolar ridge augmentation, for which mandibular cortical bone block was used in preimplantation surgery. Five appropriate samples with screws were evaluated histologically and immunohistochemically for runt-related transcription factor 2 (RUNX2), transcription factor Sp7 (Osterix), and leptin receptor (LepR). In all cases, histological evaluation revealed that bone components had completely surrounded the u-HA/PLLA screws, and the bone was connected directly to the biomaterial. Inflammatory cells did not invade the space between the bone and the u-HA/PLLA screw. Immunohistochemical evaluation revealed that many cells were positive for RUNX2 or Osterix, which are markers for osteoblast and osteoprogenitor cells, in the tissues surrounding u-HA/PLLA. In addition, many bone marrow-derived mesenchymal stem cells were notably positive for both LepR and RUNX2. The u-HA/PLLA material showed excellent bioactive osteoconductivity and a highly biocompatibility with bone directly attached. In addition, our findings suggest that many bone marrow-derived mesenchymal stem cells and mature osteoblast are present in the osteogenic environment created with u-HA/PLLA screws and that this environment is suitable for osteogenesis.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=KannoTakahiro
en-aut-sei=Kanno
en-aut-mei=Takahiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil=Department of Oral and Maxillofacial Surgery, Shimane University Faculty of Medicine
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=7
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=poly-L-lactide
kn-keyword=poly-L-lactide
en-keyword=uncalcined and unsintered hydroxyapatite
kn-keyword=uncalcined and unsintered hydroxyapatite
en-keyword=biocompatibility
kn-keyword=biocompatibility
en-keyword=osteoconductivity
kn-keyword=osteoconductivity
en-keyword=mesenchymal stem cell
kn-keyword=mesenchymal stem cell
END
start-ver=1.4
cd-journal=joma
no-vol=12
cd-vols=
no-issue=9
article-no=
start-page=1557
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2019
dt-pub=20190513
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Biomechanical Loading Comparison between Titanium and Unsintered Hydroxyapatite/Poly-L-Lactide Plate System for Fixation of Mandibular Subcondylar Fractures
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Osteosynthesis absorbable materials made of uncalcined and unsintered hydroxyapatite (u-HA) particles, poly-l-lactide (PLLA), and u-HA/PLLA are bioresorbable, and these plate systems have feasible bioactive osteoconductive capacities. However, their strength and stability for fixation in mandibular subcondylar fractures remain unclear. This in vitro study aimed to assess the biomechanical strength of u-HA/PLLA bioresorbable plate systems after internal fixation of mandibular subcondylar fractures. Tensile and shear strength were measured for each u-HA/PLLA and titanium plate system. To evaluate biomechanical behavior, 20 hemimandible replicas were divided into 10 groups, each comprising a titanium plate and a bioresorbable plate. A linear load was applied anteroposteriorly and lateromedially to each group to simulate the muscular forces in mandibular condylar fractures. All samples were analyzed for each displacement load and the displacement obtained by the maximum load. Tensile and shear strength of the u-HA/PLLA plate were each approximately 45% of those of the titanium plates. Mechanical resistance was worst in the u-HA/PLLA plate initially loaded anteroposteriorly. Titanium plates showed the best mechanical resistance during lateromedial loading. Notably, both plates showed similar resistance when a lateromedially load was applied. In the biomechanical evaluation of mandibular condylar fracture treatment, the u-HA/PLLA plates had sufficiently high resistance in the two-plate fixation method.
en-copyright=
kn-copyright=
en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=KannoTakahiro
en-aut-sei=Kanno
en-aut-mei=Takahiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=YamamotoNorio
en-aut-sei=Yamamoto
en-aut-mei=Norio
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=
en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=
affil-num=1
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=2
en-affil=Department of Oral and Maxillofacial Surgery, Shimane University Faculty of Medicine
kn-affil=
affil-num=3
en-affil=Department of Orthopaedic Surgery, Kagawa Prefectural Central Hospital
kn-affil=
affil-num=4
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=5
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=6
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=7
en-affil=Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=
affil-num=8
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=mandibular condylar fracture
kn-keyword=mandibular condylar fracture
en-keyword=unsintered hydroxyapatite
kn-keyword=unsintered hydroxyapatite
en-keyword=poly-l-lactide composite plate
kn-keyword=poly-l-lactide composite plate
en-keyword=bioactive resorbable plate
kn-keyword=bioactive resorbable plate
en-keyword=biomechanical loading evaluation
kn-keyword=biomechanical loading evaluation
en-keyword=fracture fixation
kn-keyword=fracture fixation
END
start-ver=1.4
cd-journal=joma
no-vol=20
cd-vols=
no-issue=8
article-no=
start-page=1973
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2019
dt-pub=20190423
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Notch Signaling Affects Oral Neoplasm Cell Differentiation and Acquisition of Tumor-Specific Characteristics
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract= Histopathological findings of oral neoplasm cell differentiation and metaplasia suggest that tumor cells induce their own dedifferentiation and re-differentiation and may lead to the formation of tumor-specific histological features. Notch signaling is involved in the maintenance of tissue stem cell nature and regulation of differentiation and is responsible for the cytological regulation of cell fate, morphogenesis, and/or development. In our previous study, immunohistochemistry was used to examine Notch expression using cases of odontogenic tumors and pleomorphic adenoma as oral neoplasms. According to our results, Notch signaling was specifically associated with tumor cell differentiation and metaplastic cells of developmental tissues. Notch signaling was involved in the differentiation of the ductal epithelial cells of salivary gland tumors and ameloblast-like cells of odontogenic tumors. However, Notch signaling was also involved in squamous metaplasia, irrespective of the type of developmental tissue. In odontogenic tumors, Notch signaling was involved in epithelial-mesenchymal interactions and may be related to tumor development and tumorigenesis. This signaling may also be associated with the malignant transformation of ameloblastomas. Overall, Notch signaling appears to play a major role in the formation of the characteristic cellular composition and histological features of oral neoplasms, and this involvement has been reviewed here.
en-copyright=
kn-copyright=
en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=
en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=
en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=
en-aut-name=YoshidaSaori
en-aut-sei=Yoshida
en-aut-mei=Saori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=
en-aut-name=MaedaHatsuhiko
en-aut-sei=Maeda
en-aut-mei=Hatsuhiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=
en-aut-name=KawakamiToshiyuki
en-aut-sei=Kawakami
en-aut-mei=Toshiyuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=
en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=長塚仁
kn-aut-sei=長塚
kn-aut-mei=仁
aut-affil-num=7
ORCID=
affil-num=1
en-affil= Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=2
en-affil= Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=3
en-affil= Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=4
en-affil= Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
affil-num=5
en-affil= Department of Oral Pathology, School of Dentistry, Aichi Gakuin University,
kn-affil=
affil-num=6
en-affil= Hard Tissue Pathology Unit, Matsumoto Dental University Graduate School of Oral Medicine
kn-affil=
affil-num=7
en-affil= Department of Oral Pathology and Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=cell differentiation
kn-keyword=cell differentiation
en-keyword=epithelial-mesenchymal interaction
kn-keyword=epithelial-mesenchymal interaction
en-keyword=immunohistochemistry
kn-keyword=immunohistochemistry
en-keyword=malignant transformation
kn-keyword=malignant transformation
en-keyword=notch signaling
kn-keyword=notch signaling
en-keyword=odontogenic tumor
kn-keyword=odontogenic tumor
en-keyword=pleomorphic adenoma
kn-keyword=pleomorphic adenoma
END