To analyze the clinical phenotype and genetic etiology of patients with Dyggve-Melchior-Clausen syndrome (DMC syndrome). A child with DMC syndrome diagnosed at Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University in August 2020 was selected as study subject. A retrospective analysis was carried out to collect the proband's clinical data. Peripheral blood samples was collected from the proband and his parents. Following extraction of genomic DNA, whole exome sequencing (WES) was carried out. Candidate variants were validated within the family by Sanger sequencing. Pathogenicity of candidate variants was rated based on guidelines from the American College of Medical Genetics and Genomics (ACMG). This study was approved by the Medical Ethics Committee of the center (Ethics No.: SCMCIRB-K2023024-1). The proband, a 5-year-and-7-month-old girl, presented with short stature (height: -5.5 s) and intellectual disability. Physical examination revealed microcephaly (head circumference: -3.5 s), coarse facial features, long philtrum, pigeon chest, and brachydactyly of both hands. Laboratory findings revealed normal serum insulin-like growth factor-1 (IGF-1) levels (168 ng/mL). Imaging analysis demonstrated dysplasia of corpus callosum and spondyloepiphyseal dysplasia in the proband. WES revealed that she has harbored compound heterozygous variants of the DYM gene, namely c.312-313del (p.His104Glnfs*29) and c.1274A>T (p.Tyr425Phe). Both variants were unreported previously and inherited from her parents who were phenotypically normal. Based on guidelines from the ACMG, the DYM gene variant c.312-313del (p.His104Glnfs*29) was classified as pathogenic (PVS1+PM2_Supporting+PP3+PP4_supporting), while the c.1274A>T (p.Tyr425Phe) variant was classified as likely pathogenic (PM2_Supporting+PP3+PP1+PP4_supporting). By following the pre-set literature search strategy, a total of 20 articles were included, which involved a total of 73 cases of DYM gene variants leading to DMC syndrome. Among these, only one family case was documented in China. Together with proband from this study, a total of 74 DMC syndrome patients due DYM gene variants were included for a comprehensive analysis of clinical phenotypes and genetic characteristics. The age at the time of reporting ranged from 1 to 60 years. The main clinical manifestations included intellectual disability, short stature, and spondyloepiphyseal dysplasia, followed by microcephaly and coarse facial features. By genetic testing, c.1877delA variant was the most common mutation at the nucleotide level. The c.312-313del/c.1274A>T compound heterozygous variants of the DYM gene probably underlay the pathogenesis of DMC syndrome in this proband. Above finding has expanded the mutational and phenotypic spectra of the DMC syndrome.

To investigate epigenetic and transcriptional alterations in children with Wiedemann-Steiner syndrome (WDSTS) due to variants of KMT2A gene using genome-wide DNA methylation array and RNA sequencing (RNA-seq), and identify the key pathways and candidate genes. A retrospective study was carried out for 16 children with WDSTS and 10 healthy controls who visited Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine between November 2016 and December 2024. Peripheral blood samples were collected. Genomic DNA and total RNA were extracted using commercially made kits. Genome-wide DNA methylation profiling was conducted to identify differentially methylated positions (DMPs) and annotated genes, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. RNA-seq was performed to identify differentially expressed genes (DEGs) and conduct GO/KEGG functional annotation. Methylation and expression data were integrated to identify overlapping genes showing significant changes at both levels, followed by GO, KEGG and gene-pathway network analyses. This study was approved by the Ethics Committee of the hospital (Ethics No.: GKLW-A-2024-006-01). A total of 2 652 DMPs corresponding to 1 262 genes were identified, which included 833 hypermethylated genes (66%) and 429 hypomethylated genes (34%). Hypermethylated genes were mainly enriched for functions related to cell junctions, while hypomethylated genes were significantly involved in nervous system development and morphogenesis. RNA-seq identified 2 627 DEGs, including 765 up-regulated genes (29%) and 1 862 down-regulated genes (71%). Up-regulated genes were mainly associated with immune-related processes, and down-regulated genes were mainly related to substance transport. Integrative analysis identified 93 overlapping genes with significant changes in both methylation and expression. And these genes were enriched in extracellular matrix-related processes, calcium ion binding, neurodevelopment, and cell adhesion. Key candidate genes, including LAMB1, LAMB2 and NID1, were further prioritized. Integrated analysis of DNA methylation and transcriptome data reveals WDSTS-related epigenetic-transcriptional alterations and provides clues for exploring disease mechanisms and optimizing diagnostic strategies.

Objective: To compare the clinical, endoscopic, and histopathological features of pediatric inflammatory bowel disease (IBD) with IL-10 monogenic defects (IL-10 group) and those with non-IL-10 monogenic defects (non-IL-10 group). Methods: A total of 67 pediatric patients with monogenic IBD diagnosed from 2016 to 2021 were included. All patients were referred by the Children's Hospital of Fudan University, Shanghai, China and pathologically reviewed and genetically confirmed at Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, Hangzhou, China. A comparative analysis of the clinical presentation, endoscopic finding, pathological classification, and histopathological features was performed. A subgroup analysis was also carried out within the non-IL-10 group. Results: Among the 67 cases, 43 in the IL-10 group (predominantly IL10RA/B mutations) and 24 in the non-IL-10 group (CYBB, PIK3CD, LRBA mutations etc.). The median age at diagnosis was significantly younger in the IL-10 group (U=149.0, P<0.001). Endoscopically, the IL-10 group showed more colonic involvement and severe lesions. The IL-10 group more frequently exhibited a Crohn's disease-like pattern (χ2=8.841, P<0.001). Significantly higher rates of active inflammation (χ2=12.26, P<0.001) and transmucosal inflammation (χ2=6.847, P=0.009), moderate-to-severe crypt distortion (χ2=4.541, P=0.033) were also observed as the predominant histopathological features in the IL-10 group. Granulomas and increased intraepithelial lymphocytosis were observed only in the non-IL-10 group. Subgroup analysis of the IL-10 group showed that five patients with PIK3CD mutation had moderate-to-severe crypt distortion and transmural mucosal inflammation whereas three patients with CYBB mutations presented with granulomas, lymphocyte aggregation, and small intestinal villous blunting, without moderate-to-severe crypt distortion or transmucosal inflammation. Conclusions: IL-10-and non-IL-10-mediated monogenic IBD cases exhibit significantly different clinical, endoscopic, and pathological features. The IL-10 group often presents severe infantile/early-childhood colitis, while the non-IL-10 group shows later onset and greater phenotypic heterogeneity.

Objective: To investigate the clinicopathological characteristics, immunophenotype, molecular features, and differential diagnosis of low-grade eosinophilic renal tumors associated with FLCN mutations. Methods: Clinical and pathological data from 18 cases of FLCN-mutation-associated low-grade eosinophilic renal tumors were collected from the Department of Pathology of Nanjing Jinling Hospital, Nanjing University School of Medicine. Histological morphology and immunophenotyping were performed, and high-throughput targeted gene mutation sequencing was performed on all 18 cases. Results: Among the 18 patients, 13 were male and 5 were female, aged 55 (43, 62) years. Twelve cases were diagnosed with hereditary Birt-Hogg-Dubé (BHD) syndrome. Among patients with BHD syndrome, 10 had multifocal tumors and 7 had bilateral tumors. Of the 18 patients, 10 had typical hybrid eosinophilic/chromophobe tumors (HOCT), and 8 had unclassified eosinophilic tumors. Histologically, 10 cases of typical HOCT showed a characteristic "mosaic" pattern. The 8 cases of unclassified eosinophilic cell tumors were morphologically heterogeneous, including 4 cases resembling chromophobe renal cell carcinoma (ChRCC), 1 case resembling succinate dehydrogenase-deficient renal cell carcinoma (SDH-RCC), 2 cases rich in "histiocytic lakes," and 1 case with eosinophilic cell; all lacked the hybrid cell components and "mosaic" morphological features typical of HOCT. Immunophenotypically, in the 10 typical HOCT cases, L1CAM, E-cadherin, CD117, and CK7 predominantly showed "mosaic" -like immunohistochemical features, consistent with the histological morphology; Cathepsin K was diffusely moderate positive in 2 cases and focally positive in 3 cases; CD10 was positive in 2 cases. Eight cases of unclassified eosinophilic tumors partially lacked typical immunohistochemical features, and their immunophenotypes were inconsistent. Other commonly used immunohistochemical markers vimentin, CK20, Melan A, TFE3, and TFEB were all negative. Despite their heterogeneity, non-metastatic glycoprotein B (GPNMB) showed diffusely, strongly positive in both typical HOCT and unclassified eosinophilic cell tumors (18/18). Next-generation sequencing (NGS) confirmed the presence of pathogenic or likely pathogenic FLCN mutations in all 18 cases. Conclusions: FLCN-mutation-associated low-grade eosinophilic renal tumors show distinct histological morphology, immunophenotype, and molecular genetic characteristics. It is necessary to make differential diagnosis from morphologically similar renal tumors in clinical practice. GPNMB serves as an important auxiliary marker for diagnosis of FLCN-mutation-associated low-grade eosinophilic renal tumors. Clinical, molecular, and genetic testing should be integrated to assess potential association with BHD syndrome, for making a precise diagnosis.

Healthcare access varies dramatically across the United States, with rural and underserved populations facing notable barriers to timely, specialized care. The proximity of physician training affects the overall workforce distribution; however, this trend has not been assessed within orthopaedic surgery. This study investigates the impact birthplace and training location have on future practice location among US orthopaedic surgeons and characterizes the per-capita workforce distribution. Eight thousand, six hundred seventy-six orthopaedic surgeons who completed residency training between 2004 and 2017 were identified from the American Medical Association Physician Masterfile. Demographic and practice data were extracted, including birthplace, medical school, residency and attending practice as of January 1, 2023. Locations were stratified by state and census division. The cohort represented 94.84% of orthopaedic surgeons trained nationally during the study period. Attendings returning to their state of birth, medical school, or residency to practice were 21.7%, 31.8%, and 33.9%, respectively, with pronounced state-level variability (birthplace: 2.50% to 47.95%; medical school: 3.94% to 61.8%; residency: 11.71% to 63.95%). Indiana (pop:6,880,131) trained the fewest residents per capita (1:1.15 million), whereas neighboring Ohio (pop:11,824,034) ranked fifth nationally (1:191,000). Univariate logistic regression revealed notable associations ( P < 0.01) between practice location by census division at all career stages. Attending distribution per capita showed strong correlations by state (R 2 = 0.98) and census division (R 2 = 0.99), whereas birthplace (R 2 = 0.71), medical school (R 2 = 0.53), and residency (R 2 = 0.63) showed moderate association. This study demonstrates that birthplace and training location are strongly associated with practice location for US orthopaedic surgeons. Despite variation in trainee numbers by state, the distribution of practicing surgeons normalizes relative to state population, likely driven by economic incentives, local workforce demands, and market conditions. Given the strong statistical association for surgeons to practice near their training location, aligning local programs with underserved or high-need areas may offer a potential solution to reduce regional disparities and improve access to orthopaedic care.

A local needs assessment demonstrated deficits in direct observations, teaching, and written evaluations, which are required by training programs and accrediting bodies. We developed the Teaching Excellence Among Medical Providers (TEAM) Program to fill this gap and enhance the educational experience of learners and faculty in pediatric hospital medicine. Our objective was to evaluate this program's impact on our educational culture using a focused ethnographic approach. Informed by self-regulated learning theory, TEAM was created at our freestanding children's hospital in 2019. We conducted this qualitative study involving interviews of learners and faculty and field observations of TEAM shifts. We coded transcripts and field notes, organizing codes into themes through iterative group discussion until achieving information power. Prior research has described culture in medical education using 3 lenses: organizational, identity, and practice; we organized our analyzed data using these 3 cultural perspectives as a framework. Between May 2023 and August 2024, we completed 25 1:1 interviews and 10 field observations. Data analysis revealed 6 themes, each categorized in 1 of 3 cultural lenses. Our themes highlighted that TEAM represents shared values within our institution and increases cohesion and mentorship (organizational); fosters professional identify formation and a growth mindset (identity); and affects the workings of the clinical team while providing an appreciated, additional perspective (practice). TEAM has had a positive impact on our institution's educational culture through 3 unique lenses, as participants described prioritization of education, a professional development opportunity, and valuable support for the clinical team.

What makes a great urology sub-internship? A survey of medical students, residents, and faculty.

As AI integration in medicine becomes critical, this study evaluated medical students' attitudes and knowledge regarding AI and determined its impact on career specialization choices. This cross-sectional study used a voluntary, web-based convenience sample of 274 first- to fifth-year students at Gazi University Faculty of Medicine in Ankara, Türkiye (October-November 2025). Data were collected with a structured questionnaire incorporating the validated Perceptions on Artificial Intelligence in Medicine (PAIM) scale. Although 74.5% reported no formal AI training, 52.6% expected AI to influence their specialization choice. Students who expected AI to shape their careers reported higher "Knowledge and Trust" (p = 0.018); the "Disadvantages and Risks" subscale did not differ significantly between career-impact expectation groups (p = 0.131). Among the three PAIM dimensions, only "Informed Self-Control" differed significantly by training phase, with clinical-phase students scoring lower than pre-clinical peers (p = 0.027). In multivariable regression, expecting AI to influence specialization was the only positive predictor of "Knowledge and Trust" (B = 0.16, p = 0.018), and formal training predicted higher "Informed Self-Control" (B = 0.28, p = 0.015), while older age predicted lower scores (B = - 0.05, p = 0.015). Both models were statistically significant but explained only a small share of variance (adjusted R2 = 0.02 and 0.04). Overall, 94.2% supported integrating AI into the medical curriculum. The findings highlight a marked gap between students' strong demand for AI training and the limited formal instruction currently provided. Cross-sectional differences across training phases may reflect a shift from early optimism toward a more cautious stance, although the design cannot establish such a developmental trajectory. Because more than half of students expected AI to affect their specialty choice, curricula should move beyond technical instruction to integrate ethical and clinical reasoning alongside AI literacy. These associations are exploratory and require confirmation in larger, longitudinal studies. This study did not involve a clinical trial and therefore was not registered in a clinical trials registry.

Introduction: Local anesthetics (LAs) are commonly used to provide regional insensitivity in dentistry, minor surgical procedures, and general anesthesia but may rarely cause allergic reactions. Methods: The file data of 101 patients who were referred to the Department of Allergy and Immunology, Ege University Faculty of Medicine, with a suspected LA allergy between February 2020 and August 2024 were retrospectively reviewed. Patients included in the study were contacted by phone and asked whether they had used LAs after the test and whether any reactions had developed. Results: Female patients comprised 81% (n = 82) of the study cohort. Patients were predominantly referred from the departments of dentistry (45% [n = 46]) and anesthesiology (22% [n = 22]). Patients were referred due to reactions related to LAs alone (n = 51) and both LAs and other drugs (n = 50). The severity of LA reactions was mild (n = 47), moderate (n = 36), or severe (n = 18), with dyspnea being the most common symptom (n = 47). Prick-intradermal (P-ID) and provocation tests were performed on all the patients (suspected LAs [n = 32], alternative LAs [n = 23], random [n = 46]). Only one patient tested positive in the P-ID test, and a provocation test was performed on this patient with an alternative agent, with a negative result. Of the 80 patients reached by phone, 41 received LAs based on test results and did not develop an allergic reaction, whereas the other 39 patients did not receive LAs. Conclusion: Immunologically mediated reactions to LAs were exceedingly rare in this study. These findings highlight that most suspected reactions are not attributable to confirmed allergic mechanisms and underscore the importance of a careful clinical history and guideline-based evaluation to avoid unnecessary drug avoidance.

It all began, so they say, with Theodore Woodward, "Don't look for zebras on Greene Street." This aphorism has since been passed on to generations of residents and medical students at the University of Maryland School of Medicine and beyond. A zebra is a "medical condition whose appearance at a particular time and place, in a particular person, is both unexpected and astonishing. The 'condition' may be an item from the history, a physical finding, a laboratory test, or a diagnosis." This maxim nudges clinicians to consider competing or paradoxical hypotheses when assessing patients for common, unexpected, and rare diseases. Whereas errors are unavoidable, considering zebras (uncommon diagnoses) helps avoid "not-to-miss" diagnoses, patient harm, and the associated regret of failure. Perhaps there's also the tug to "bag the big one." On the one hand, pursuing zebras may result in overestimating probability assessments with the potential for harming patients and wasting resources, while applying the science of formal medical decision-analysis lessens the chances of overzealous workups. Unfortunately, conducting studies to evaluate the utility of clinical findings for rare diseases is difficult. The key is to identify symptoms and signs, preferably in combination, with high specificity and sensitivity. On the other hand, assuming horses (common diagnoses) for too long also has its risks. Both the failure to recognize when the current therapeutic plan is ineffective and to appreciate the diagnostic value of the history, physical, and routine laboratory tests can delay the search for alternative hypotheses and ultimately efficacious treatment. Sir William Osler admonished us over a century ago, "Use the knife and cautery to cure the moral necrosis which you will feel in the posterior parietal region, in Gall and Spurzheim's centre of self-esteem, where you will find a sore spot after you have made a mistake in diagnosis."

Efficacy of Short Course Cognitive Behavioral Therapy on Stress Reduction Among First-Year Surgical Residents.

Pediatric subspecialists in academic medicine earn less than adult subspecialists, but whether this disparity has changed over time is unclear. We compared the net present value (NPV) of lifetime earnings between pediatric and adult subspecialists in 2014 and 2024 and evaluated changes in the relative earnings differential. We conducted a retrospective economic analysis using Association of American Medical Colleges Faculty Salary Reports from 2014 and 2024. Salaries at the 25th, 50th, and 75th percentiles were extracted across academic ranks for pediatric and adult subspecialties and converted to 2024 dollars. Lifetime earnings were modeled through retirement at 67years old using a 3% real discount rate and 3 promotion pathways (baseline, plateaued, and no promotion). The relative earnings differential was defined as (Adult NPV - Pediatrics NPV)/Pediatrics NPV × 100. Across subspecialties, adult subspecialists in academic medicine had higher lifetime NPVs than pediatric subspecialists in both years. In 2024, lifetime NPVs for pediatric subspecialists ranged from $4.9 million to $7.6 million, compared with $5.3 million to $9.4 million for adult counterparts (50th percentile, baseline promotion pathway). The average relative earnings differential widened from 15.7% in 2014 to 20.2% in 2024. Disparities were amplified at higher salary percentiles and with plateaued or absent promotion, reaching 41.5% in a no-promotion pathway at the 75th percentile. From 2014 to 2024, the lifetime earnings gap between pediatric and adult subspecialists in academic medicine widened, with potential implications for pediatric workforce sustainability.

Prader-Willi syndrome (PWS) is highly associated with psychiatric comorbidity. This article investigates the prevalence of mental disorders in PWS, explores their association with neurobiological foundations, and outlines the resulting clinical recommendations. An evaluation of the scientific literature in the context of clinical experience from the special outpatient clinic for mental health in rare syndromic disorders at Hannover Medical School. Psychiatric manifestations are present in 44-89% of PWS patients, with disruptive behavior, skin picking, psychosis, compulsive symptoms, and affective disorders being the most common. PWS psychosis differs from schizophrenic psychosis and can be difficult to treat in some cases. Treatment approaches exist for disruptive behavior, affective symptoms, and compulsive symptoms. Knowledge of the neurobiological basis of PWS is necessary for the adequate treatment of psychiatric disorders. In addition to pharmacological therapies, behavioral interventions and environmental control should also be included.

The availability of mentorship for underrepresented minorities in surgery and surgical subspecialties: A systematic review.

What Are the Odds? Utilization of Artificial Intelligence to Predict Success in the Integrated Plastic Surgery Match.

Against the dual background of digital transformation and the development of New Medicine, traditional paper-based experiment reports increasingly show inherent limitations in efficiency, interactivity, archiving, and resource sharing. This study designed and developed an online electronic experiment report submission system tailored for medical universities, and further explored the application of artificial intelligence (AI) technology in automated grading and plagiarism detection. The system was built on the ThinkPHP 5.0 framework and MySQL database, with three role-based portals for administrators, teachers, and students. To meet the specific requirements of medical experiment teaching, core functions including copy-paste restriction, modular grading, a reusable comment library, one-click score aggregation, and batch PDF export were implemented. Furthermore, this study proposed a multi-algorithm similarity-based plagiarism detection scheme and an AI auto-grading concept based on a dual-layer evaluation model, providing a feasible path for the intelligent upgrade of experiment teaching. The application of this system is expected to effectively alleviate problems such as heavy grading workload, delayed feedback, and physical archiving difficulties, thereby improving the management efficiency and teaching quality of medical experiment education.

The rapid integration of artificial intelligence (AI) technologies in healthcare, ranging from diagnostic tools to clinical decision support systems, is transforming medical practice and education. However, without deliberate integration of ethics, there is a risk that medical education will reproduce a technosolutionist orientation by privileging efficiency and data-driven outputs over patient autonomy, justice and professional integrity. While AI-related courses are increasingly being introduced into medical curricula, ethical considerations often remain peripheral, with most frameworks emphasising technical skills over moral reasoning. As future clinicians will face complex ethical challenges related to autonomy, safety, bias, transparency and accountability in AI-integrated clinical settings, there is an urgent need to evaluate how ethics is incorporated into AI education. With AI curricula still in their formative stages, this moment presents a critical opportunity to proactively design ethical components, rather than introducing them after harms have emerged. This scoping review aims to systematically map the ethical-technical balance in AI-related medical education curricula, identifying current practices, gaps and opportunities for curriculum development. This scoping review will follow the Joanna Briggs Institute methodology and be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. The review will address how ethical considerations are integrated into AI-related curricula in medical education and examine the balance between ethical and technical content. A comprehensive search strategy will be employed across multiple databases, including MEDLINE, Web of Science, Google Scholar, EBSCO, the Virtual Health Library, the Bioethics Literature Database and PhilPapers, as well as grey literature sources such as institutional reports, curricula and policy documents. Publications from January 2020 to December 2025 will be included. Data will be charted and analysed using descriptive qualitative content analysis, followed by a theory-informed interpretive analysis drawing on the hidden curriculum theory of medical education. This review does not require ethics approval, as it involves analysis of publicly available data. Findings will be disseminated through a peer-reviewed publication and presented at relevant conferences and workshops focused on medical education or bioethics.

Skin disorders are among the most prevalent conditions encountered in primary care, yet dermatology remains underrepresented in medical curricula worldwide. Non-dermatologist physicians frequently manage these conditions with limited training and exposure, potentially compromising diagnostic accuracy and patient outcomes. This study aimed to assess the level of confidence among Palestinian physicians in diagnosing and managing skin disorders and to identify the training-related factors associated with higher diagnostic self-efficacy. A cross-sectional study was conducted among 246 licensed medical doctors practicing in the West Bank, Palestine. Participants were recruited through convenience sampling via professional networks and selected healthcare facilities, with the sample predominantly comprising younger and early-career physicians. Data were collected using a structured, validated self-administered questionnaire through mixed modes (electronic and paper-based). The instrument assessed sociodemographic and professional characteristics, dermatology exposure and training, and diagnostic self-efficacy using Likert-scale items. Diagnostic self-efficacy was dichotomized into below average versus average or above. Descriptive statistics, chi-square tests, and multivariable logistic regression were performed using SPSS version 22. Ethical approval was obtained from AlQuds University Institutional Review Board. Of 246 participating physicians, 74.4% were aged 30 years or younger and 58.9% were male. The majority were general practitioners (54.1%) working in hospital settings (79.7%). Most participants (58.9%) reported no formal dermatology training, and 42.3% encountered fewer than 10 dermatological cases in their careers. Most physicians rated their diagnostic skills as average (62.6%), with a mean diagnostic self-efficacy score of 2.92 ± 0.78. No meaningful associations were observed between most sociodemographic characteristics and diagnostic self- efficacy. Training-related factors significantly associated with higher self-efficacy included: dermatology training during medical school (81.2% vs. 64.3%; p = 0.038), exposure to more than three training methods (91.6% vs. 73.3%; p = 0.006), and confidence gained after training (85.6% vs. 63.9%; p = 0.003). In multivariable logistic regression, confidence after training remained an independent predictor of higher self-efficacy (OR = 3.21, 95% CI 1.29-8.11; p = 0.011). Dermatology rotations and lectures were identified as the most effective and most recommended training modalities. Palestinian physicians demonstrate only moderate diagnostic self-efficacy in dermatology, largely attributable to limited training and clinical exposure. Dermatology training, particularly when it meaningfully boosts confidence, is the most important predictor of diagnostic self-efficacy, irrespective of sociodemographic background. Integrating structured, multimodal dermatology education into undergraduate and postgraduate curricula is essential to improving physician competence and ultimately enhancing patient care in primary care settings.

This study examines trends in gender and racial/ethnic representation in academic psychiatry department chairs compared to faculty in the United States (U.S.). Using data from the American Association of Medical Colleges (AAMC) Faculty Roster (2012-2022), a total of 1722 psychiatric department chairs and 125,333 psychiatric faculty at U.S. academic medical centers were included. Trends in leadership representation by gender, race, and ethnicity were examined using the Leadership Parity Index (LPI). Individuals were categorized by self-identified race/ethnicity (American Indian or Alaska Native, Asian, Black/African American, Hispanic/Latino/Spanish origin, Native Hawaiian or Other Pacific Islander, White) and gender (female or male). An LPI of 1 suggests parity of department chair representation relative to a group's faculty representation, LPI > 1 suggests overrepresentation, and LPI < 1 suggests underrepresentation. White individuals (LPI range over 10-year period = 1.1 to 1.19), particularly white men (LPI range = 1.79 to 1.96), were consistently overrepresented as psychiatry department chairs. Women across all races/ethnicities were underrepresented as psychiatry department chairs (LPI range = 0.24 to 0.58). Men were overrepresented (LPI range = 1.54 to 1.70) in every racial/ethnic group, except Asian men. Of all racial/ethnic groups studied, Asian men and women were the most underrepresented (LPI range = 0.42 to 1.07 and 0.12 to 0.30, respectively). Academic psychiatry department chairs continue to be disproportionately overrepresented by white men. The persistent underrepresentation of women in all racial/ethnic groups and Asians as department chairs highlights the continued need to promote parity in academic psychiatry leadership.

Artificial intelligence (AI) is increasingly used in clinical medicine. Rheumatology is well-suited to AI applications due to diagnostic complexity of rheumatic diseases, variable disease presentations, and multisystem involvement. This cross-sectional study examines global AI research in rheumatology through bibliometric analysis of Scopus data. The Scopus database was searched on May 5, 2026, using the terms "artificial intelligence" AND "rheum*" in the title, abstract, and keyword fields. No temporal restrictions were applied, and all English documents were analyzed. Bibliometric data, including publication year, country, institution, author, journal, and keywords, were extracted. Retracted articles were identified using Scopus tags and were manually verified through related journal editorial notices. Disease-specific publication counts were determined through independent searches for rheumatic diseases. Survey-based studies were identified through manual review. Linear regression analysis was conducted to assess temporal trends. A total of 1,057 publications were identified. Annual output remained below 10 until 2018, then rose sharply to a peak of 282 in 2025. Linear regression confirmed a significant upward trend (p < 0.001). The United States produced the most publications (n = 249), followed by the United Kingdom (n = 141) and India (n = 138). Harvard Medical School was the leading institution (n = 33), and Knitza, J., was the most prolific author (n = 17). Rheumatology International published the most articles (n = 27). Osteoarthritis (n = 1,017) and rheumatoid arthritis (n = 646) dominated the field, while systemic vasculitis (n = 40), Behçet disease (n = 29), and familial Mediterranean fever (n = 16) were underrepresented. Eleven survey-based studies were identified, mostly published between 2024 and 2025. Two articles were retracted due to peer review irregularities. AI research in rheumatology has increased significantly, with research outputs stemming from a limited number of countries, institutions, and disease categories. Osteoarthritis and rheumatoid arthritis are the most frequently explored diseases in the field. The increasing number of survey-based studies indicates heightened attention to clinician and patient perspectives. Future research should focus on expanding international collaboration, addressing gaps in AI research on underrepresented diseases, and strengthening ethical and methodological standards to facilitate broader AI adoption in rheumatology.