Citations

Abstract Emotional experiences during focal seizures are often misinterpreted as psychiatric disorders. We aimed to evaluate symptoms involving affective symptoms at seizure onset. We aimed to identify the most prevalent affective symptoms at seizure onset and characterize their localizing and lateralizing value. We performed a scoping review based on Preferred Reporting Items for Systematic reviews and Meta‐Analyses–extension for Scoping Reviews guidelines. A systematic search identified records from 4 databases: PubMed, Embase, CINAHL (via EBSCOhost), and Web of Science. Two reviewers independently screened titles/abstracts and full texts; discrepancies were resolved by consensus. This review focused on patients with focal seizures, as affective symptoms may occur in generalized epilepsies. The affective symptoms: fear, anxiety, panic, sadness, mystic, ecstatic, sexual, and mirth were identified, and semiology was evaluated in accordance with ILAE guidelines. Symptom onset, frequency, brain localization, and video‐EEG monitoring technique were evaluated to assess localization and lateralization of regional networks. Scalp EEG, invasive EEG recordings, and electrical stimulation were analyzed. A total of 1276 documents were identified, with 98 studies included for review. Fear was the most frequently reported ictal emotion, identified in 274 patients (66%), predominantly in temporal lobe epilepsy. Sadness and sexual, ecstatic symptoms were also consistently associated with temporal networks. Mirth was more frequently reported with frontal onset seizures. Evidence, primarily from Class IV studies, reported right hemispheric predominance for ecstasy, mystic, and sexual symptoms at seizure onset. Ictal affective symptoms at seizure onset yield localizing information. The limbic system, especially the temporal lobe, followed by the frontal lobe, was the most common site of origin. Fear was the most common spontaneous and electrically elicited symptom, followed by anxiety. While bi‐hemispheric lateralization occurred, right lateralization predominated. Recognizing paroxysmal affective symptoms as ictal phenomena may reduce misdiagnosis and aid presurgical evaluation in drug‐resistant focal epilepsy.

Background Microsurgery is a critical component of plastic and reconstructive surgery. However, the high cost of training and equipment pose significant barriers, particularly in resource-limited settings. To address this challenge, the Microsurgery and Regenerative Medicine Lab within the Division of Plastic Surgery at the University of Wisconsin developed a low-cost, 3D-printed surgical microscope. This study qualitatively appraised the use of this novel microscope for microsurgery training by surveying surgeons about their experiences using this tool relative to traditional magnification methods. Methods In this prospective, multi-institutional appraisal study, surgical residents, fellows, and attending surgeons with varying microsurgical experience performed a single end-to-end microsurgical anastomosis on chicken thigh femoral arteries using the 3D-printed microscope. Participants then completed a survey assessing ease of use, adequacy for microsurgical training, educational value, and perceived impact on teaching capacity in local and global settings. Results Over 80% of participants reported that performing an end-to-end anastomosis was easier or equivalent using the 3D-printed microscope compared to surgical loupes. All respondents expressed willingness to use the device for microsurgery teaching and practice. Additionally, 91.7% (33/36) believed access to the microscope would enhance microsurgical teaching at their home institutions, and 97.1% (34/35) felt it would improve teaching capacity in globally. Qualitative feedback was overwhelmingly positive, with suggestions primarily related to ergonomics and lighting. Conclusion This study supports that this low-cost, 3D-printed microscope is an effective microsurgical training tool. Ongoing design refinements informed by user feedback may further optimize its role in expanding access to microsurgery education worldwide.

AI skill development is essential in health professions education (HPE), yet this type of faculty development is complex to design and implement. While competency frameworks and AI education programs are emerging, many faculty developers are themselves still building AI literacy and confidence, and practical guidance for how to design a faculty development program on AI that is accessible, skill-oriented, and responsive to rapid technological change remains limited. Although webinars and workshops can only do so much, a well-planned faculty development program can provide a great introduction to AI, alleviate fears, and inspire participants to keep growing and learning. Drawing on our experience designing and hosting the AAMC GEA AI Skill-Building Webinar Series and the current literature in AI, this article offers twelve practical tips for faculty developers who are creating AI-focused learning opportunities for everyone involved in HPE. These tips will help readers create robust AI skill-building sessions that move participants beyond awareness of AI and shift their perspectives toward applied, reflective, and responsible use of AI in HPE.

Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.

Importance Recent case reports suggest that B antigen–containing blood products may be associated with anaphylactic transfusion reactions in recipients with preformed immunoglobulin E to galactose- α -1,3-galactose (alpha-gal). Objective To test the association of local alpha-gal syndrome (AGS) prevalence and allergic transfusion reaction (ATR) in patients with blood type O. Design, Setting, and Participants In this international, multicenter, retrospective cohort study at academic medical centers, sites were assigned to AGS high- or low-prevalence clusters based on the known geographic distribution of AGS. Data were collected on platelet or plasma transfusions and ATRs during 2020 to 2024. Consecutive patients receiving platelet or plasma transfusions were included. Exposures Patients with blood type O who received B or AB units and patients with blood type O who received O units (reference group) in AGS high- and low-prevalence clusters were compared. Main Outcomes and Measures Before data collection, the hypothesis was that if transfusion-related alpha-gal syndrome (TRAGS) is a true clinical entity, excess ATRs to group B or AB units would be detected in AGS high-prevalence regions exclusively. The main measure was the overall risk ratio (RR) for ATRs to B or AB plasma or platelets in AGS high- vs low-prevalence clusters. Results In total, 558 823 platelet and plasma transfusions at 40 sites in 5 countries were analyzed, of which ATRs occurred in 1744 transfusions (0.3%). In the US AGS high-prevalence cluster (9 sites), significantly more ATRs of any severity occurred among patients with blood type O who received B or AB units vs patients with blood type O who received O units (overall RR, 3.93; 95% CI, 2.96-5.21; P &amp;lt; .001). In contrast, in the primary analysis of the AGS low-prevalence cluster (15 sites), excess ATRs to B or AB units were not detected. In subgroup analyses among patients with blood type O receiving B units, the RR for moderate to severe ATRs was 9.14 (95% CI, 5.39-15.52; P &amp;lt; .001) in the AGS high-prevalence cluster vs 2.15 (95% CI, 1.34-3.47; P = .002) in the AGS low-prevalence cluster. Outside the US, a signal consistent with TRAGS was not detected. Conclusions and Relevance This cohort study provides provocative epidemiologic evidence that TRAGS may be a unique manifestation of AGS and a previously unrecognized risk associated with transfusion. In AGS high-prevalence regions, blood collectors and hospital transfusion services should consider approaches to preventing severe ATRs from B or AB plasma or platelet units.

Objective Epidemiologic estimates for age of systemic lupus erythematosus (SLE) diagnosis are limited, particularly for men and racial and ethnic subpopulations in the United States. Leveraging the Centers for Disease Control and Prevention (CDC) National Lupus Registry network of population‐based SLE registries, meta‐analyses were performed estimating age‐specific incidence of SLE by sex, race, and ethnicity. Methods The CDC network of SLE registries includes five state‐based registries, plus a sixth Indian Health Service registry. Incidence periods spanned calendar years 2002‐2018. Registries provided age‐specific incidence of SLE, fulfilling the American College of Rheumatology (ACR) SLE classification criteria, per 100,000 person‐years, stratified by sex, race, and ethnicity for the meta‐analyses. Results Incidence rates among women were highest for those aged 30‐39 (12.7, 95%CI: 9.5‐16.8), while rates among men were highest for those aged 60‐69 (2.1, 95%CI: 1.3‐3.4). Black women aged 20‐39 had the highest SLE incidence rates (23.6, 95%CI: 20.7‐26.8). Among women diagnosed with SLE before age 20, incidence was highest among Asian (6.5, 95%CI: 2.8‐15.2) individuals. Among women diagnosed with SLE after age 60, incidence was highest among American Indian/Alaska Native (9.4, 95%CI: 3.4‐15.4) individuals. Weighted percentages show 10.0% of those with SLE were diagnosed before age 20, while 15.1% were diagnosed after age 60. The largest proportion of individuals with SLE, 22.1%, were diagnosed between 30‐39 years. Conclusions This study provides comprehensive sex‐ and race‐specific estimates of age at SLE diagnosis. The substantial later in life SLE incidence among men and disease burden in pediatric and older populations should raise awareness in considering SLE in the differential diagnosis in previously underrecognized groups.

Adult optic nerve axon regeneration has traditionally been framed as a problem of limited intrinsic growth capacity in central nervous system neurons. However, growing evidence suggests that intrinsic factors alone cannot account for regenerative failure: restrictive extrinsic environmental factors largely govern optic nerve regeneration, dictating the intrinsic capacity axons can express. In this review, we frame the extrinsic optic nerve environment as a dynamic regenerative niche, in which vascular, immune, glial, matrix, and metabolic compartments are spatially co-localized and temporally coordinated rather than acting as independent barriers. These compartments follow a shared trajectory, broadly protective in the acute phase, then inhibitory once the underlying response fails to resolve, while also actively driving one another, such as reactive astrocytes promoting the matrix remodeling that subsequently restricts axon regrowth. Consequently, the niche’s overall permissiveness for regeneration reflects the aggregate and interdependent state of these compartments rather than the action of any single barrier. This review integrates current evidence on extrinsic barriers, intervention opportunities, and disease-specific variability relevant to RGC axon regeneration after injury. These interventions must incorporate the spatial, temporal, and metabolic factors that shape the goal of functional recovery and vision restoration.

Background: Several breast cancer (BC) risk prediction models have been developed to provide personal risk assessments. Though individually validated, their performance has not been systematically evaluated across a wide range of populations or ages. Methods: We harmonized individual-level baseline questionnaire data and incident BC diagnoses from 21 cohorts from North America, Europe, and Australia participating in the Breast Cancer Risk Prediction Project. Five-year absolute risk of invasive BC was estimated for five established risk prediction models using classical risk factors only. Discrimination was evaluated by area under the curve (AUC). Calibration was assessed using average and risk-decile specific expected to observed (E/O) ratios. Performance metrics were meta-analyzed across cohorts and models. Metaregression tested associations between cohort characteristics and performance metrics. Results: This analysis included 1,595,977 women aged 20-75 years, enrolled in studies between 1976-2015, with 19,062 (1.2%) invasive BC cases ascertained within 5 years from exposure assessment. Age-adjusted AUCs were similar across models and cohorts (pooled AUCs by model: 0.57-0.58), while E/O ratios varied substantially (pooled E/O ratios by model: 0.83-1.25). Overestimation was common among predicted high-risk individuals (>3%). No appreciable differences in model performance by cohort age, birth year, race, and variable missingness emerged. Calibration improved after assigning race-specific incidence rates. Conclusion: Existing BC risk prediction models provided similar risk discrimination across multiple cohorts, although there was overestimation of risk for high-risk individuals. Performance variation across cohorts was not driven by specific characteristics, which supports development of a unified risk model for diverse populations that leverages appropriate incidence rates.