Citations

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.

Background/Objectives: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have emerged as a promising therapeutic option for women with polycystic ovary syndrome (PCOS). Clinical trials and data demonstrate significant improvements in body weight, insulin resistance, hyperandrogenism, and, in some studies, menstrual regularity and reproductive outcomes. However, the current evidence base remains disproportionately focused on short-term metabolic and anthropometric endpoints, while outcomes most relevant to patients—including treatment satisfaction, gastrointestinal tolerability, psychological well-being, body image, fertility planning, financial burden, and long-term adherence—remain inadequately characterized. Methods: We searched PubMed and Google Scholar for English-language literature published between 2021 and 2026, using structured keyword searches. This narrative review evaluates the literature on GLP-1RA use in PCOS beyond weight-focused outcomes, examining mechanisms of action, comparative tolerability across agents, and patient-centered domains including quality of life, eating behavior, and reproductive planning. Results: The published literature reveals a substantial gap between trial-reported completion rates and treatment success, and actual persistence and patient satisfaction. This discrepancy is particularly consequential in PCOS, where treatment decisions intersect with high baseline rates of depression, anxiety, and body image disturbance, and where ovulatory benefits must be weighed against mandatory discontinuation before conception. Conclusions: We identify a systematic absence of validated patient-reported outcome measures, standardized core outcome sets, and long-term follow-up data after treatment withdrawal. This review proposes a research agenda prioritizing patient-centered endpoints as co-primary outcomes, structured assessment of acceptability and persistence, qualitative and mixed-methods approaches, and a dedicated study of fertility planning and treatment interruption.

Abstract Glioblastoma (GBM) is a lethal, treatment-resistant brain cancer characterized by diffuse brain invasion, complex neuron-glioma signaling, and cellular, molecular, and spatial heterogeneity. Surgery is the current mainstay of treatment, aimed at maximizing tumor cytoreduction, decompressing the brain to improve neurological function, and providing material for analyses to inform prognostication and adjuvant treatment selection. To accurately model GBM surgical resection and tissue sampling in preclinical animal models, we developed the Maximal Safe Intracranial Surgery (MSIS) system. MSIS integrated a miniaturized neurosurgical resection device and enabled a safe, tunable, and reproducible approach for intracranial tumor resection, multi-regional biopsy, and longitudinal tissue sampling in murine models, with stereotactic, sterile, and high-viability tissue collection. MSIS was applied across five distinct orthotopic brain tumor models to reproducibly generate histologically and radiologically representative models of post-surgical GBM. Similar to humans, increasing the extent of resection correlated with improved animal survival, and recurrent growth patterns varied significantly by model type. Transcriptional profiles of matched primary vs. post-surgical recurrent tumors revealed enrichment of margin-associated transcriptional states consistent with neuron-glioma signaling. Overall, the MSIS system offers opportunities to model the standard-of-care, dissect the spatial and temporal dynamics of GBM, and pair therapeutic discovery with contextual tumor pathobiology.

Abstract Everolimus 10 mg daily is the standard dose for advanced neuroendocrine tumors (NETs), but adverse events frequently necessitate dose reduction. As a result, oncologists often adopt a dose‐escalation strategy starting at 5 mg and increasing the dose as tolerated. In this multicenter study, we evaluated the effect of reduced dose (RD) and standard dose (SD) everolimus on survival, progression, and toxicity in patients with advanced NETs. We conducted a multicenter retrospective cohort study of patients with advanced NETs treated with everolimus at Mayo Clinic and University Hospitals (Cleveland, OH). Patients were grouped by starting dose (5 mg vs. 10 mg). Primary endpoints were overall survival (OS), real‐world progression‐free survival (rwPFS), and adverse events. Multivariable Cox models, inverse probability of treatment weighting (IPTW), and time‐varying dose sensitivity analysis were used to account for confounding and dose crossover. Among 170 patients (48 started on 5 mg; 122 on 10 mg), the 5 mg cohort was older, had worse ECOG PS, and was more heavily pretreated. Median OS was 43.7 months (5 mg) versus 81.5 months (10 mg; log‐rank p = .02). However, after multivariable adjustment ( N = 124 G1–G2 patients; 51 events), the association was no longer statistically significant (adjusted HR, 0.59; 95% CI, 0.31–1.12; p = .11). Median rwPFS was 7.0 versus 12.4 months (log‐rank p = .05); the adjusted rwPFS difference was not statistically significant (HR, 0.95; 95% CI, 0.56–1.61; p = .84). Nearly half (46.7%) of 10 mg starters required dose reduction. Any‐grade toxicity was more common with 10 mg (89% vs. 75%; p = .05). The apparent survival advantage of standard‐dose everolimus was substantially attenuated after adjustment. These findings do not establish dose equivalence and should be interpreted in the context of limited statistical power. Given its more favorable observed tolerability profile, RD everolimus warrants prospective evaluation as a starting strategy for patients at increased risk of treatment‐related toxicity who may not tolerate SD.

Abstract Orthopaedic literature often establishes cutoffs when evaluating risk factors for an outcome of interest, whether patellar instability or most any other pathology. Although such cutoffs are intuitively easy to apply to clinical practice and testing situations, they leave much to be desired when it comes to nuanced patient care. As we increasingly recognize patient‐to‐patient differences, our approach to historic cutoffs such as tibial tubercle‐trochlear groove distance merits a revisit. A reasonable first step is to adjust for patient‐specific factors such as height and sex. However, as larger datasets and deeper mechanistic insights become available, we may ultimately move beyond simplistic thresholds altogether, advancing instead toward truly individualized precision medicine.

OBJECTIVE The 2023 American Diabetes Association (ADA) “Standards of Care in Diabetes” updated the recommended blood pressure (BP) goal to <130/80 mmHg for all people with diabetes, regardless of age, if it can be safely attained. We assessed whether this guideline change led to a change in BP control. RESEARCH DESIGN AND METHODS This retrospective, interrupted time series study from a large integrated health care delivery system assessed BP control from 1 January through 30 November 2022 (pre-guideline) compared with 1 December 2022 through 31 December 2023 (post-guideline). We assessed adults (aged ≥18 years) with comorbid diabetes and hypertension for the percentage of patients with a median BP of <130/80 mmHg, 130/80 to 139/89 mmHg, and ≥140/90 mmHg. Secondary outcomes examined prescribing rate trends of antihypertensive medication classes, sodium–glucose cotransporter 2 inhibitors (SGLT2is), glucagon-like peptide 1 (GLP-1) agonists, and dual GLP-1/glucose-dependent insulinotropic polypeptide (GIP) agonists. RESULTS We examined 24,211 median monthly BP measures before guideline publication and 28,889 after guideline publication. There was no significant difference in trend for meeting BP <130/80 mmHg pre- to post-guideline change after adjusting for differences in patient characteristics and seasonality (odds ratio 1.05, 95% CI 0.98–1.13, P = 0.16). Prescribing rates of SGLT-2i and GLP-1 or GLP-1/GIP medications increased both pre- and post-guideline release. There was a negative change in the trend of total number of antihypertensive classes prescribed pre- to post-guideline change (estimated difference −0.04, 95% CI −0.05 to 0.02, P < 0.001). CONCLUSIONS Updates to the ADA guidelines did not alter BP control and antihypertensive prescribing, suggesting therapeutic inertia.

Abstract The clonogenic assay is the foundational standard for evaluating cellular radiosensitivity, yet its manual quantification is limited by labor-intensive processing, high inter-observer variability, and a reductive binary scoring system. Here, we present and validate a deep learning-based segmentation pipeline for the automated, high-throughput quantification of mammalian cell survival across diverse radiation qualities (photons, protons, and carbon ions). By benchmarking against expert consensus using Bland-Altman analysis, we demonstrate that this AI framework consistently operates within natural human error margins. Crucially, transitioning to automated whole-well image-based analysis enables the extraction of continuous multidimensional data, including colony area, density, and cellularity. This phenotypic profiling successfully identified and quantified high-cellularity colonies formed by radioresistant BxPC-3 cells under particle irradiation. Coupled with rapid image acquisition platforms, this methodology significantly reduces processing bottlenecks while standardizing the derivation of relative biological effectiveness (RBE). By advancing beyond binary survival metrics to continuous morphological profiling, this framework provides a vital new analytical dimension for investigating structural mechanisms of radioresistance.