medRxiv - Dentistry and Oral Medicine最新文献

{"title":"Understanding Tooth Agenesis: A Multi-omics Insight into MicroRNA Regulation","authors":"Prashant Ranjan, Chandra Devi, Neha Verma, Rajesh Bansal, Vinay Kumar Srivastava, Parimal Das","doi":"10.1101/2024.09.02.24312916","DOIUrl":"https://doi.org/10.1101/2024.09.02.24312916","url":null,"abstract":"This study reveals novel microRNAs (miRNAs) implicated in congenital tooth agenesis (CTA), a common dental anomaly with a complex genetic basis. Through a multi-omics approach combining bioinformatics, whole exome sequencing, metabolite analysis, and gene expression profiling, we identified eight key miRNAs potentially involved in tooth development. Among these, four miRNAs viz. miR-218-5p, miR-15b-5p, miR-200b-3p, and let-7a-3p were validated as significant regulators in CTA, marking their first investigation in blood samples from CTA patients. Our analysis revealed that these miRNAs play critical roles in odontogenesis, influencing essential signaling pathways, including <em>Wnt, FGF</em>, and <em>PI3</em> kinase pathways. Among these four, miR-218-5p and let-7a-3p emerged as key players in dental tissue morphogenesis, each contributing to previously unidentified networks crucial for tooth development.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"729 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142201358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychological Contributors to Pain Before, During, and After Endodontic Procedures: A Scoping Review","authors":"Atieh Sadr, Ali Gholamrezaei, Amy G McNeilage, Cameron L Randall, Flavia P. Kapos, Christopher C. Peck, Claire E. Ashton-James","doi":"10.1101/2024.08.07.24311445","DOIUrl":"https://doi.org/10.1101/2024.08.07.24311445","url":null,"abstract":"Background: Despite an increasingly biopsychosocial approach to pain management in healthcare, the scope of research into the role of psychological factors in endodontic pain is unknown. Objectives:This study aimed to identify the scope of research into psychological contributors to pain associated with endodontic procedures, as a first step towards addressing psychological contributors to pain in clinical practice.\u0000Method: This scoping review was conducted and reported according to the JBI Manual for Evidence Synthesis and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (extension for scoping reviews). The data search was conducted in MEDLINE, EMBASE, PsycINFO, Web of Science, Scopus, Cochrane Database of Systematic Reviews, and CINAHL databases. For gray literature, we reviewed reference lists, medRxiv pre-prints, ProQuest and EBSCO theses, ClinicalTrials.gov and Cochrane trials (via Ovid), and conference materials via Web of Science and Scopus (from inception to July 2023). Each record was screened by two independent reviewers. Data were extracted by one reviewer and cross-verified by a second reviewer. Results: Forty studies were included in the review. Twelve broad psychological constructs were evaluated in relation to pain for pre-procedural, procedural and post-procedural endodontics: pain expectancies, positive treatment expectancies, depression, anxiety, positive and negative mood (affect), beliefs about pain, desire for control of dental treatments, perceptions of dentists, somatic focus or awareness, pain coping strategies, personality, and psychiatric diagnoses. Pre-procedural pain was most frequently associated with anxiety. Procedural pain was consistently associated with expected pain. Post-procedural pain was associated with expected pain, depression, beliefs about pain, positive treatment expectations, and personality characteristics.\u0000Conclusion: A variety of psychological factors have been investigated in relation to endodontic pain. Whilst associations between endodontic pain and psychological constructs were found, further research is needed to evaluate the strength of these associations, and the scope of evidence for interventions designed to address these psychological contributors to pain in dental practice. Registration: The search protocol was registered on Open Science Framework in 2021 (DOI number: 10.17605/OSF.IO/FSRJP).","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large Language Model Diagnose Facial Deformity","authors":"Jungwook Lee, Xuanang Xu, Daeseung Kim, Hannah H Deng, Tianshu Kuang, Nathan Lampen, Xi Fang, Jaime Gateno, Pingkun Yan","doi":"10.1101/2024.07.11.24310274","DOIUrl":"https://doi.org/10.1101/2024.07.11.24310274","url":null,"abstract":"Purpose: This study examines the application of Large Language Models (LLMs) in diagnosing jaw deformities, aiming to overcome the limitations of various diagnostic methods by harnessing the advanced capabilities of LLMs for enhanced data interpretation. The goal is to provide tools that simplify complex data analysis and make diagnostic processes more accessible and intuitive for clinical practitioners. Methods: An experiment involving patients with jaw deformities was conducted, where cephalometric measurements (SNB Angle, Facial Angle, Mandibular Unit Length) were converted into text for LLM analysis. Multiple LLMs, including LLAMA-2 variants, GPT models, and the Gemini-Pro model, were evaluated against various methods (Threshold-based, Machine Learning Models) using balanced accuracy and F1-score. Results: Our research demonstrates that larger LLMs efficiently adapt to diagnostic tasks, showing rapid performance saturation with minimal training examples and reducing ambiguous classification, which highlights their robust in-context learning abilities. The conversion of complex cephalometric measurements into intuitive text formats not only broadens the accessibility of the information but also enhances the interpretability, providing clinicians with clear and actionable insights. Conclusion: Integrating LLMs into the diagnosis of jaw deformities marks a significant advancement in making diagnostic processes more accessible and reducing reliance on specialized training. These models serve as valuable auxiliary tools, offering clear, understandable outputs that facilitate easier decision-making for clinicians, particularly those with less experience or in settings with limited access to specialized expertise. Future refinements and adaptations to include more comprehensive and medically specific datasets are expected to enhance the precision and utility of LLMs, potentially transforming the landscape of medical diagnostics.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141614722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OQA: A question-answering dataset on orthodontic literature","authors":"Maxime Rousseau, Amal Zouaq, Nelly Huynh","doi":"10.1101/2024.07.05.24309412","DOIUrl":"https://doi.org/10.1101/2024.07.05.24309412","url":null,"abstract":"Background: The near-exponential increase in the number of publications in orthodontics poses a challenge for efficient literature appraisal and evidence-based practice. Language models (LM) have the potential, through their question-answering fine-tuning, to assist clinicians and researchers in critical appraisal of scientific information and thus to improve decision-making.\u0000Methods: This paper introduces OrthodonticQA (OQA), the first question-answering dataset in the field of dentistry which is made publicly available under a permissive license. A framework is proposed which includes utilization of PICO information and templates for question formulation, demonstrating their broader applicability across various specialties within dentistry and healthcare. A selection of transformer LMs were trained on OQA to set performance baselines.\u0000Results: The best model achieved a mean F1 score of 77.61 (SD 0.26) and a score of 100/114 (87.72%) on human evaluation. Furthermore, when exploring performance according to grouped subtopics within the field of orthodontics, it was found that for all LMs the performance can vary considerably across topics.\u0000Conclusion: Our findings highlight the importance of subtopic evaluation and superior performance of paired domain specific model and tokenizer.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"366 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141567171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Caries status, caries severity, and oral health-related quality of life of preschool children in Kuantan","authors":"Muhammad Zaki Ramli, Nina Suhaity Azmi, Ahmad Faisal Ismail","doi":"10.1101/2024.07.04.24309980","DOIUrl":"https://doi.org/10.1101/2024.07.04.24309980","url":null,"abstract":"Dental caries among preschool children is prevalent and may affect their oral health-related quality of life (OHRQOL). The aim of this study was to assess the oral health-related quality of life (OHRQOL) of preschool children from Kuantan in relation to their dental caries status and severity. A cross-sectional survey using the Malay version of Early Childhood Oral Health Impact Scale (Malay-ECOHIS) involving preschool children aged three until six years old was conducted employing a convenience sampling. The dmft score of the preschool children was evaluated by a professional pediatric dentist, and the body mass index (BMI) was recorded. The caries status data was classified into either Absent (dmft = 0) or Present (dmft &gt;= 1), while caries severity data was categorized into No Caries (dmft = 0), Moderate (dmft = 1 or 2), and High (dmft &gt;= 3), depending on the caries experience. The Pearson Chi-square and Spearman correlation analyses were conducted. A high caries prevalence was recorded (89.1%), affecting 55 preschool children. They were more impacted than their family in terms of their OHRQOL, and those with high caries severity and those from low household income showed the lowest OHRQOL. However, since most of them were from high household income, their families were not financially impacted. It is important to not only assess the caries status of the preschool children when assessing their OHRQOL, but also their caries severity.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating adults’ dental caries burden through the DMFT index: results from the Tanzanian 5th national oral health survey","authors":"Kasusu Klint Nyamuryekung'e, Hawa Mbawalla, Matilda Mlangwa Mtaya","doi":"10.1101/2024.06.28.24309650","DOIUrl":"https://doi.org/10.1101/2024.06.28.24309650","url":null,"abstract":"Aim: Dental caries remains the most prevalent chronic disease worldwide, affecting adults and children across all regions. The DMFT index, representing the number of decayed, missing, and filled teeth, serves as a fundamental metric in oral epidemiology, providing an objective quantification of dental caries prevalence and severity. The aim of the current study is to evaluate the dental caries burden of the adult Tanzanian population through the DMFT index.\u0000Methods: A national pathfinder survey was conducted in mainland Tanzania using a cross-sectional design. The survey encompassed fourteen districts across thirteen regions. Site selection followed the World Health Organization’s (WHO) basic oral health survey methods, utilizing a modified stratified-cluster sampling approach. Electronic questionnaires were administered to all adult participants prior to their dental examinations. The questionnaires collected data on participants’ sociodemographic information, tooth brushing practices, and dentition status. Dental examinations were conducted in accordance with WHO standard criteria. Data cleaning and analysis were performed using SPSS version 23. Frequencies were calculated to determine the proportions of participants' mean and separate DMFT (Decayed, Missing, and Filled Teeth) components. Bivariate associations were examined using Student’s t-test and ANOVA to compare participants' DMFT components with their sociodemographic characteristics and oral health practices.\u0000Results: The study surveyed a total of 1,386 participants aged 30-34, 35-44 and 50+ comprising 713 females (51.4%) with most participants (49.1%) aged 50 years or older. The mean DMFT in the studied population was 4.63 (SD 5.4) with a dental caries experience of 76.6%. The Missing teeth component constituted the largest portion of the mean DMFT (52.4%), followed closely by the Decayed teeth component (45.8%). Tooth fillings were found in just 3.5% of those with dental caries experience. The mean DMFT score was significantly higher among females (5.31 ± 5.79), those aged 50 or more (5.93 ± 6.26) and with lowest level of education (5.78 ± 6.68). Brushing less than once daily (p&lt;0.001), not using toothpaste (p&lt;0.001) and not using a toothbrush daily (p&lt;0.05) were all associated with increased DMFT scores. Conclusions: Dental caries is a significant public health issue in Tanzania. The predominance of missing and decayed teeth highlights the critical gaps in treatment and dental care service accessibility. There is a pressing need for increased public health investment in preventive and restorative dental care and enhanced community education on the importance of maintaining dental health.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"112 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Adjunctive Intraoral Balance Appliance in the Usual Care of Patients with Chronic Temporomandibular Joint Disorders using Korean Medicine: Study Protocol for a Randomized Controlled Trial","authors":"Woo-Chul Shin, Se yun Kim, Whisung Cho, Jaehyun Park, Hyungsuk Kim, Won-Seok Chung, Mi-Yeon Song, Jae-Heung Cho","doi":"10.1101/2024.06.18.24309139","DOIUrl":"https://doi.org/10.1101/2024.06.18.24309139","url":null,"abstract":"Introduction Temporomandibular disorders (TMD) are a group of conditions that affect the temporomandibular joint, masticatory muscles, and associated structures, often leading to pain, dysfunction, and a significant impact on quality of life. Epidemiological studies have estimated that up to 75% of the population in the United States exhibit at least one sign of TMD. Although conservative treatments such as acupuncture and occlusal splints have been recommended, evidence for their effectiveness remains inconclusive, and the combined effects of these interventions are not well understood.\u0000This study aims to compare the efficacy of an intraoral balance appliance (IBA) combined with standard Korean medicine care versus Korean medicine care alone in patients with chronic, painful TMD with myalgia. Materials and Methods A single-center, two-arm, parallel, evaluator-blinded, randomized controlled trial (RCT) with a 1:1 allocation ratio will be designed to test the interventions. Seventy-six TMD patients with myalgia will be recruited and randomized. The Interventions will include manual acupuncture and physical therapy in both groups, with the addition of IBA in the treatment group. Discussion The outcomes will be measured using various scales such as the numeric rating scale for pain and bothersomeness, jaw functional limitation scale, and quality of life indicators. Conclusion The trial is expected to provide evidence of the efficacy of combining the usual Korean medicine care and IBA in managing chronic TMD myalgia. Despite certain limitations such as the short intervention period and lack of standardized splint therapy, this RCT will contribute valuable data to guide the future treatment of TMD with myalgia.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence in Periodontology: Performance Evaluation of ChatGPT, Claude, and Gemini on the In-service Examination","authors":"Bushra Ahmad, Khaled Saleh, Saleh Alharbi, Hend Alqaderi, Y. Natalie Jeong","doi":"10.1101/2024.05.29.24308155","DOIUrl":"https://doi.org/10.1101/2024.05.29.24308155","url":null,"abstract":"<strong>Background</strong> Artificial intelligence (AI) language models have shown potential as educational tools in healthcare, but their accuracy and reliability in periodontology education require further evaluation. In this study we aimed to assess and compare the performance of three prominent AI language models—ChatGPT-4o, Claude 3 Opus, and Gemini Advanced—with second-year periodontics residents across the United States on the American Academy of Periodontology 2024 in-service examination.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141257252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Converting dose-area product to effective dose in dental cone-beam computed tomography using organ-specific deep learning","authors":"Ruben Pauwels","doi":"10.1101/2024.05.28.24308014","DOIUrl":"https://doi.org/10.1101/2024.05.28.24308014","url":null,"abstract":"<strong>Objective</strong> To develop an accurate method for converting dose-area product (DAP) to patient dose for dental cone-beam computed tomography (CBCT) using deep learning.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141189634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychosocial Profiles of Older Adults by Dentition Status and Dental Utilization History","authors":"T.L. Finlayson, K. Moss, J.A. Jones, J.S. Preisser, J.A. Weintraub","doi":"10.1101/2024.05.05.24306865","DOIUrl":"https://doi.org/10.1101/2024.05.05.24306865","url":null,"abstract":"<strong>Objective</strong> Psychosocial factors can affect health. Patterns of psychosocial stressors and resources among older adults were examined for oral health status.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"249 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140935441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}