Our team has been a pioneer in harvesting extracellular vesicles (EVs) enriched for neuronal origin from peripheral blood and using them as a biomarker discovery platform for neurological disorders. This methodology has demonstrated excellent diagnostic and predictive performance for Alzheimer's and other neurodegenerative diseases in multiple studies, providing a strong proof of concept for this approach. Here, we describe our methodology in detail and offer further evidence that isolated EVs are enriched for neuronal origin. In addition, we present evidence that EVs enriched for neuronal origin represent a more sensitive and accurate base for biomarkers than plasma, serum, or non-enriched total plasma EVs. Finally, we proceed to investigate the protein content of EVs enriched for neuronal origin and compare it with other relevant enriched and non-enriched populations of plasma EVs. Neuronal-origin enriched plasma EVs contain higher levels of signaling molecules of great interest for cellular metabolism, survival, and repair, which may be useful as biomarkers and to follow response to therapeutic interventions in a mechanism-specific manner.

IMPORTANCE Blood biomarkers able to diagnose Alzheimer disease (AD) at the preclinical stage would enable trial enrollment when the disease is potentially reversible. Plasma neuronal-enriched extracellular vesicles (nEVs) of patients with AD were reported to exhibit elevated levels of phosphorylated (p) tau, Aβ42, and phosphorylated insulin receptor substrate 1 (IRS-1). OBJECTIVE To validate nEV biomarkers as AD predictors. DESIGN, SETTING, PARTICIPANTS This case-control study included longitudinal plasma samples from cognitively normal participants in the Baltimore Longitudinal Study of Aging (BLSA) cohort who developed AD up to January 2015 and age-and sex-matched controls who remained cognitively normal over a similar length of follow-up. Repeated samples were blindly analyzed over 1 year from participants with clinical AD and controls from the Johns Hopkins Alzheimer Disease Research Center (JHADRC). Data were collected from September 2016 to January 2018. Analyses were conducted in March 2019. MAIN OUTCOMES AND MEASURES Neuronal-enriched extracellular vesicles were immunoprecipitated; tau, Aβ42, and IRS-1 biomarkers were quantified by immunoassays; and nEV concentration and diameter were determined by nanoparticle tracking analysis. Levels and longitudinal trajectories of nEV biomarkers between participants with future AD and control participants were compared. RESULTS Overall, 887 longitudinal plasma samples from 128 BLSA participants who eventually developed AD and 222 age and sex-matched controls who remained cognitively normal were analyzed. Participants were followed up (from earliest sample to AD symptom onset) for a mean (SD) of 3.5 (2.31) years (range, 0-9.73 years). Overall, 161 participants were included in the training set, and 80 were in the test set. Participants in the BLSA cohort with future AD (mean [SD] age, 79.09 [7.02] years; 68 women [53.13%]) had longitudinally higher p-tau181, p-tau231, pSer312-IRS-1, pY-IRS-1, and nEV diameter than controls (mean [SD] age, 76.2 [7.36] years; 110 women [50.45%]) but had similar Aβ42, total tau, TSG101, and nEV concentration. In the training BLSA set, a model combining preclinical longitudinal data achieved 89.6% area under curve (AUC), 81.8% sensitivity, and 85.8% specificity for predicting AD. The model was validated in the test BLSA set (80% AUC, 55.6% sensitivity, 88.7% specificity). Preclinical levels of nEV xbiomarkers were associated with cognitive performance. In addition, 128 repeated samples over 1 year from 64 JHADRC participants with clinical AD and controls were analyzed. In the JHADRC cohort (35 participants with AD: mean [SD] age, 74.03 [8.73] years; 18 women [51.43%] and 29 controls: mean [SD] age, 72.14 [7.86] years; 23 women [79.31%]), nEV biomarkers achieved discrimination with 98.9% AUC, 100% sensitivity, and 94.7% specificity in the training set and 76.7% AUC, 91.7% sensitivity, and 60% specificity in the test set. CONCLUSIONS AND RELEVANCE We validated nEV biomarker candidates and further demonstrated that their preclinical longitud...

SummaryObesity, metabolic syndrome, and hyperleptinemia are associated with aging and age‐associated diseases including prostate cancer. One experimental approach to inhibit tumor growth is to reduce dietary protein intake and hence levels of circulating amino acids. Dietary protein restriction (PR) increases insulin sensitivity and suppresses prostate cancer cell tumor growth in animal models, providing a rationale for clinical trials. We sought to demonstrate that biomarkers derived from plasma extracellular vesicles (EVs) reflect systemic leptin and insulin signaling and respond to dietary interventions. We studied plasma samples from men with prostate cancer awaiting prostatectomy who participated in a randomized trial of one month of PR or control diet. We found increased levels of leptin receptor in the PR group in total plasma EVs and in a subpopulation of plasma EVs expressing the neuronal marker L1CAM. Protein restriction also shifted the phosphorylation status of the insulin receptor signal transducer protein IRS1 in L1CAM+ EVs in a manner suggestive of improved insulin sensitivity. Dietary PR modifies indicators of leptin and insulin signaling in circulating EVs. These findings are consistent with improved insulin and leptin sensitivity in response to PR and open a new window for following physiologic responses to dietary interventions in humans.

Background: Natural language processing models such as ChatGPT can generate text-based content and are poised to become a major information source in medicine and beyond. The accuracy and completeness of ChatGPT for medical queries is not known. Methods: Thirty-three physicians across 17 specialties generated 284 medical questions that they subjectively classified as easy, medium, or hard with either binary (yes/no) or descriptive answers. The physicians then graded ChatGPT-generated answers to these questions for accuracy (6-point Likert scale; range 1 – completely incorrect to 6 – completely correct) and completeness (3-point Likert scale; range 1 – incomplete to 3 - complete plus additional context). Scores were summarized with descriptive statistics and compared using Mann-Whitney U or Kruskal-Wallis testing. Results: Across all questions (n=284), median accuracy score was 5.5 (between almost completely and completely correct) with mean score of 4.8 (between mostly and almost completely correct). Median completeness score was 3 (complete and comprehensive) with mean score of 2.5. For questions rated easy, medium, and hard, median accuracy scores were 6, 5.5, and 5 (mean 5.0, 4.7, and 4.6; p=0.05). Accuracy scores for binary and descriptive questions were similar (median 6 vs. 5; mean 4.9 vs. 4.7; p=0.07). Of 36 questions with scores of 1-2, 34 were re-queried/re-graded 8-17 days later with substantial improvement (median 2 vs. 4; p<0.01). Conclusions: ChatGPT generated largely accurate information to diverse medical queries as judged by academic physician specialists although with important limitations. Further research and model development are needed to correct inaccuracies and for validation.

IMPORTANCE Diverse, representative enrollment in pivotal clinical trials is vital to sufficiently power subgroup analyses and ensure equity and validity of trial results. OBJECTIVE To evaluate the racial/ethnic representation, trends, and disparities in clinical trials leading to US Food and Drug Administration (FDA) ophthalmology drug approvals from 2000 to 2020. DESIGN, SETTING, AND PARTICIPANTSThis cohort study used data from participants in clinical trials of drugs for neovascular age-related macular degeneration (AMD), open-angle glaucoma (OAG), and expanded indications for diabetic retinopathy (DR) from January 1, 2000, to December 31, 2020. Trial data were sourced from FDA reviews, ClinicalTrials.gov, and relevant linked studies. National expected racial/ethnic proportions were sourced from public National Eye Institute prevalence data as well as published rates scaled using US Census Bureau data. MAIN OUTCOMES AND MEASURESThe primary outcome measures were the distribution of and change over time in the racial/ethnic proportion of participants in clinical trials leading to FDA approval of drugs for AMD, OAG, and DR. RESULTSDuring the 20-year period, 31 clinical trials were identified for 13 medications with 18 410 participants. The distribution of trial participants was different from the expected trial distribution for most approvals with regard to race/ethnicity (12 drugs) and sex (10 drugs). Compared with the first decade (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010), trials conducted in the second decade (2011-2020) showed increases in enrollment of Asian (odds ratio [OR], 2.30; 95% CI, 1.97-2.68; P < .001) and Hispanic or Latinx participants (OR, 1.74; 95% CI, 1.49-2.03; P < .001) for AMD, Asian participants (OR, 2.21; 95% CI, 1.46-3.42; P < .001) for DR, and Black (OR, 1.60; 95% CI, 1.43-1.78; P < .001) and Hispanic or Latinx participants (OR, 10.31; 95% CI, 8.05-13.35; P < .001) for OAG. There was a decrease in Black participants in DR trials (OR, 0.58; 95% CI, 0.42-0.79; P < .001). Based on these trends, the enrollment incidence ratio is expected to worsen by 2050, with overrepresentation of white participants vs underrepresentation of Black and Hispanic or Latinx participants in trials of drugs for AMD (1.08 vs 0.04 vs 0.77), DR (1.83 vs 0.87 vs 0.59), and OAG (1.62 vs 0.90 vs 0.37). CONCLUSIONS AND RELEVANCEIn this cohort study, Black, Hispanic or Latinx, and other non-White participants were underrepresented in clinical trials leading to FDA ophthalmology drug approvals compared with the expected disease burden and racial/ethnic distribution in the US. Although there was meaningful improvement from 2000 to 2020, further efforts to increase minority enrollment in clinical trials seem to be warranted.

System (MIPS) is intended to promote high-value health care through quality-related Medicare payment adjustments. OBJECTIVE To assess the economic evaluation of MIPS scoring and reporting on ophthalmologists. DESIGN, SETTING, AND PARTICIPANTSIn this retrospective, cross-sectional, multicenter economic evaluation conducted from October 10 to November 30, 2021, MIPS performance and related payment adjustments were evaluated using the US Centers for Medicare & Medicaid Service (CMS) public data files for ophthalmologists. Participants were stratified by reporting affiliation. Analysis of variance and summary statistics were used to characterize and compare total and subcategory MIPS scores and adjustments received by participants. Reported CMS methodology and performance year (PY) 2019 payment percentages were used to estimate payment adjustments for the following categories: positive MIPS adjustment plus potential additional adjustment for exceptional performance, positive MIPS adjustment, neutral payment adjustment, negative MIPS payment adjustment, and maximum negative MIPS payment adjustment. Study participants included ophthalmologists registered for Medicare Part B with participation in the Quality Payment Program (QPP) in PY 2019. MAIN OUTCOMES AND MEASURES Proportion of ophthalmologists qualifying for payment adjustments and payment adjustments.RESULTS For PY 2019, 76.5% of ophthalmologists (13 621) who registered for Medicare participated in the MIPS pathway of the QPP. Ophthalmologists practiced in a predominantly large metropolitan area (12 302; 90.3%). Roughly 99% of participants (11 182) received nonnegative reimbursement adjustments, and 92.6% (10 367) received positive adjustments. Ophthalmologists filing as individuals were less likely to achieve exceptional performance scores compared with those who had a filing category of advanced alternative payment model (APM; odds ratio [OR], 0.0003; 95% CI, 0.00002-0.00481) or group (OR, 0.21013; 95% CI, 0.19020-0.23215). When analyzing participating ophthalmologists with available Medicare payment data (11 193

transparency legislation is intended to reduce the ambiguity of hospital charges and the resultant financial stress faced by patients.OBJECTIVE To evaluate the availability, usability, and variability of standard reported prices for ophthalmologic procedures at academic hospitals. DESIGN, SETTING, AND PARTICIPANTSIn this multicenter economic evaluation study, publicly available price transparency web pages from Association of American Medical Colleges affiliate hospitals were parsed for standard charges and usability metrics. Price transparency data were collected from hospital web pages that met the inclusion criteria. Geographic practice cost indices for work, practice expense, and malpractice were sourced from the Centers for Medicare & Medicaid Services. Data were sourced from February 1 to April 30, 2021. Multiple regression was used to study the geographic influence on standard charges and assess the correlation between standard charges.MAIN OUTCOMES AND MEASURES Availability and variability of standard prices for Current Procedural Terminology (CPT) codes 66984 (removal of cataract with insertion of lens) and 66821 (removal of recurring cataract in lens capsule using laser). RESULTSOf 247 hospitals included, 191 (77.3%) provided consumer-friendly shoppable services, most commonly in the form of a price estimator or online tool. For CPT code 66984, 102 hospital (53.4%) provided discount cash pay estimates with a mean (SD) price of $7818.86 ($5407.91). For CPT code 66821, 71 hospital (37.2%) provided discount cash pay estimates with a mean (SD) price of $2041.72 ($2106.44). The top quartile of hospitals, prices wise, listed included prices higher than $10 400 for CPT code 66984 and $2324 for CPT code 66821. Usability issues were noted for 36 hospitals (18.8%), including requirements for personal information or web page navigability barriers. Multiple regression analysis found minimal explanatory value for geographic practice cost indices for cash discount prices for CPT codes 66984 (adjusted R 2 = 0.54; 95% CI, 0.41-0.67; P < .001) and 66821 (adjusted R 2 = 0.64; 95% CI, 0.51-0.77; P < .001).CONCLUSIONS AND RELEVANCE Despite recent legislature that codified price transparency requirements, some current standard charges remain ambiguous, with substantial interhospital variability not explained by geographic variability in costs. Given the potential for ambiguous pricing to burden vulnerable, uninsured patients, additional legislation might consider allowing hospitals to defer price estimates or rigorously define standards for actionable cash discount percentages with provisions for displaying relevant benchmark prices.

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