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Comparison of the preventive effect of ondansetron and dexamethasone on nausea and vomiting after orthognathic surgery between remimazolam and propofol anesthesia. - Comparison of the preventive effect of ondansetron and dexamethasone on nausea and vomiting after orthognathic surgery between remimazolam and propofol anesthesia.

开始日期2023-07-04

申办/合作机构

Tokyo Dental College

JPRN-UMIN000051727 / RecruitingN/AIIT

Elucidation of gene polymorphisms that contribute to nausea and vomiting after administration of ondansetron - Elucidation of gene polymorphisms that contribute to nausea and vomiting after administration of ondansetron

开始日期2023-05-03

申办/合作机构

Tokyo Dental College

100 项与 Tokyo Dental College 相关的临床结果

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0 项与 Tokyo Dental College 相关的专利（医药）

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6,128

项与 Tokyo Dental College 相关的文献（医药）

2024-12-31·Animal Cells and Systems

Unraveling the structure, chemical composition, and conserved signaling in leech teeth

作者: Min, Bong-Ki ; Yamamoto, Hitoshi ; Kim, Jae-Young ; Cho, Sung-Jin ; Kwon, Tae-Yub ; An, Chang-Hyeon ; Aryal, Yam Prasad ; Sohn, Wern-Joo ; Kwak, Hee-Jin ; Neupane, Sanjiv

2024-12-01·Japanese Dental Science Review

In vivo dynamics of hard tissue-forming cell origins: Insights from Cre/loxP-based cell lineage tracing studies

Review

作者: Mizoguchi, Toshihide

Bone tissue provides structural support for our bodies, with the inner bone marrow (BM) acting as a hematopoietic organ. Within the BM tissue, two types of stem cells play crucial roles: mesenchymal stem cells (MSCs) (or skeletal stem cells) and hematopoietic stem cells (HSCs). These stem cells are intricately connected, where BM-MSCs give rise to bone-forming osteoblasts and serve as essential components in the BM microenvironment for sustaining HSCs. Despite the mid-20th century proposal of BM-MSCs, their in vivo identification remained elusive owing to a lack of tools for analyzing stemness, specifically self-renewal and multipotency. To address this challenge, Cre/loxP-based cell lineage tracing analyses are being employed. This technology facilitated the in vivo labeling of specific cells, enabling the tracking of their lineage, determining their stemness, and providing a deeper understanding of the in vivo dynamics governing stem cell populations responsible for maintaining hard tissues. This review delves into cell lineage tracing studies conducted using commonly employed genetically modified mice expressing Cre under the influence of LepR, Gli1, and Axin2 genes. These studies focus on research fields spanning long bones and oral/maxillofacial hard tissues, offering insights into the in vivo dynamics of stem cell populations crucial for hard tissue homeostasis.

2024-10-01·British Journal of Ophthalmology

Deep learning model for extensive smartphone-based diagnosis and triage of cataracts and multiple corneal diseases

Article

作者: Oshika, Tetsuro ; Oda, Masahiro ; Miyake, Masahiro ; Fukuoka, Hideki ; Noma, Hisashi ; Shimazaki, Jun ; Kashiwagi, Kenji ; Akiyama, Masato ; Mori, Kensaku ; Miyata, Kazunori ; Yamaguchi, Takefumi ; Nejima, Ryohei ; Kitaguchi, Yoshiyuki ; Ueno, Yuta ; Maeda, Naoyuki

AimTo develop an artificial intelligence (AI) algorithm that diagnoses cataracts/corneal diseases from multiple conditions using smartphone images.MethodsThis study included 6442 images that were captured using a slit-lamp microscope (6106 images) and smartphone (336 images). An AI algorithm was developed based on slit-lamp images to differentiate 36 major diseases (cataracts and corneal diseases) into 9 categories. To validate the AI model, smartphone images were used for the testing dataset. We evaluated AI performance that included sensitivity, specificity and receiver operating characteristic (ROC) curve for the diagnosis and triage of the diseases.ResultsThe AI algorithm achieved an area under the ROC curve of 0.998 (95% CI, 0.992 to 0.999) for normal eyes, 0.986 (95% CI, 0.978 to 0.997) for infectious keratitis, 0.960 (95% CI, 0.925 to 0.994) for immunological keratitis, 0.987 (95% CI, 0.978 to 0.996) for cornea scars, 0.997 (95% CI, 0.992 to 1.000) for ocular surface tumours, 0.993 (95% CI, 0.984 to 1.000) for corneal deposits, 1.000 (95% CI, 1.000 to 1.000) for acute angle-closure glaucoma, 0.992 (95% CI, 0.985 to 0.999) for cataracts and 0.993 (95% CI, 0.985 to 1.000) for bullous keratopathy. The triage of referral suggestion using the smartphone images exhibited high performance, in which the sensitivity and specificity were 1.00 (95% CI, 0.478 to 1.00) and 1.00 (95% CI, 0.976 to 1.000) for ‘urgent’, 0.867 (95% CI, 0.683 to 0.962) and 1.00 (95% CI, 0.971 to 1.000) for ‘semi-urgent’, 0.853 (95% CI, 0.689 to 0.950) and 0.983 (95% CI, 0.942 to 0.998) for ‘routine’ and 1.00 (95% CI, 0.958 to 1.00) and 0.896 (95% CI, 0.797 to 0.957) for ‘observation’, respectively.ConclusionsThe AI system achieved promising performance in the diagnosis of cataracts and corneal diseases.

100 项与 Tokyo Dental College 相关的药物交易

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100 项与 Tokyo Dental College 相关的转化医学

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