Citations

We performed 6-yr follow-up testing on a world record-breaking master marathon runner. We determined that his performance declined since his record-breaking marathon in 2018 primarily due to a reduction in V̇o2max. His max heart rate (HR) changed minimally, but his peak O2 pulse decreased, suggesting that his maximal stroke volume and/or arteriovenous O2 difference decreased. These changes likely reflect primarily age-related effects in the absence of an overt pathological disease process.

Context.— Generative artificial intelligence (AI) technologies are rapidly transforming numerous fields, including pathology, and hold significant potential to revolutionize educational approaches. Objective.— To explore the application of generative AI, particularly large language models and multimodal tools, for enhancing pathology education. We describe their potential to create personalized learning experiences, streamline content development, expand access to educational resources, and support both learners and educators throughout the training and practice continuum. Data Sources.— We draw on insights from existing literature on AI in education and the collective expertise of the coauthors within this rapidly evolving field. Case studies highlight practical applications of large language models, demonstrating both the potential benefits and unique challenges associated with implementing these technologies in pathology education. Conclusions.— Generative AI presents a powerful tool kit for enriching pathology education, offering opportunities for greater engagement, accessibility, and personalization. Careful consideration of ethical implications, potential risks, and appropriate mitigation strategies is essential for the responsible and effective integration of these technologies. Future success lies in fostering collaborative development between AI experts and medical educators, prioritizing ongoing human oversight and transparency to ensure that generative AI augments, rather than supplants, the vital role of educators in pathology training and practice.

AbstractThe emergence of the United States Food and Drug Administration (FDA)‐approved amyloid‐targeting therapies for Alzheimer's disease challenges clinicians and healthcare providers with a transformative landscape. Effectively communicating the risks, benefits, burdens, costs, and available support associated with these novel disease‐modifying treatments to patients, families, and other healthcare providers is essential but complex. In response, the Alzheimer's Association's Clinical Meaningfulness Workgroup has proposed language surrounding treatment eligibility, benefits, amyloid‐related imaging abnormalities (ARIA), apolipoprotein E (APOE) genotyping, and treatment costs, serving as a resource to healthcare professionals in navigating discussions with patients and their families. As the landscape evolves with the approval of new Alzheimer's therapies, this resource stands poised for updates, ensuring its continued relevance in facilitating informed and meaningful patient‐provider dialogues.Highlights Effective communication of risks, benefits, burdens, and costs of FDA‐approved amyloid‐targeting antibodies is essential to patients, families, and healthcare providers. The Alzheimer's Association's Clinical Meaningfulness Workgroup provides language for physicians and healthcare providers around treatment eligibility, benefits, ARIA, APOE genotyping, and treatment costs. This supplementary resource may be updated as new AD therapies become approved.

Humans with monogenic inborn errors responsible for extreme disease phenotypes can reveal essential physiological pathways. We investigated germline mutations in GNAI2 , which encodes G αi2 , a key component in heterotrimeric G protein signal transduction usually thought to regulate adenylyl cyclase–mediated cyclic adenosine monophosphate (cAMP) production. Patients with activating G αi2 mutations had clinical presentations that included impaired immunity. Mutant G αi2 impaired cell migration and augmented responses to T cell receptor (TCR) stimulation. We found that mutant G αi2 influenced TCR signaling by sequestering the guanosine triphosphatase (GTPase)–activating protein RASA2, thereby promoting RAS activation and increasing downstream extracellular signal–regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase (PI3K)–AKT S6 signaling to drive cellular growth and proliferation.

AbstractObjectiveThis study aims to compare the long‐term outcomes of Aquablation for small‐to‐moderate (30–80 cm3) prostates with the outcomes for large (80–150 cm3) prostates at 5‐year follow up.MethodsThe Waterjet Ablation Therapy for Endoscopic Resection of Prostate Tissue (WATER; NCT02505919) is a prospective, double‐blind, international clinical trial encompassing 116 patients, examining Aquablation versus transurethral resection of the prostate (TURP) for LUTS/BPH in prostates sized between 30 and 80 cm3. In parallel, WATER II (W‐II; NCT03123250), a prospective, multicentre, single‐arm international clinical trial, explores Aquablation outcomes in prostates ranging from 80 to 150 cm3. Baseline parameters and 60‐month outcomes were scrutinized using statistical analyses, including Students' t test, Wilcoxon tests for continuous variables, and Fisher's test for binary variables.ResultsThere is a significant improvement in International Prostate Symptom Score (IPSS) from baseline to 60 months in both WATER (22.9 to 7.0) and WATER II (23.2 to 6.8) (P = 0.852). Urinary flow rate (Qmax) increased in both groups from baseline to 60 months (WATER: 9.4 to 17.3 cc/s; WATER II: 8.7 to 17.1 cc/s) (P = 0.933). Immediate and sustained enhancements were observed in IPSS and Qmax. At 5 years, a notable percentage of patients in both groups were BPH medication‐free (WATER: 99%; WATER II: 94%) (P = 0.0517) and free from surgical retreatment (WATER: 95%; WATER II: 97%) (P = 0.508).ConclusionsThe 5‐year follow‐up affirms that Aquablation therapy exhibits sustained outcomes, minimal irreversible complications, and low retreatment rates for treating LUTS/BPH, irrespective of prostate volume ranging from 30 to 150 cm3.

Abstract There is increasing interest in Alzheimer’s disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ1–42 and Aβ1–40 (used as Aβ42/Aβ40 ratio), glial fibrillary acidic protein, and phosphorylated tau 181 (p-tau181). Participants’ brain health was evaluated through gray and white matter structural MRIs. The study also considered cardiovascular factors (hyperlipidemia, hypertension, stroke, diabetes, chronic kidney disease), lifestyle factors (area deprivation index, body mass index, cognitive and physical activities), and genetic factors (APOE, single nucleotide polymorphisms, and polygenic risk scores). An ML model was developed to predict cognitive outcomes at baseline and decline (slope). Three models were created: a base model with groups of risk factors as predictors, an enhanced model included socio-demographics, and a final enhanced model by incorporating plasma and socio-demographics into the base models. Models were explained for three age strata: younger than 65 years, 65–80 years, and older than 80 years, and further divided based on amyloid positivity status. Regardless of amyloid status the plasma biomarkers showed comparable performance (R² = 0.15) to MRI (R² = 0.18) and cardiovascular measures (R² = 0.10) when predicting cognitive decline. Inclusion of cardiovascular or MRI measures with plasma in the presence of socio-demographic improved cognitive decline prediction (R² = 0.26 and 0.27). For amyloid positive individuals Aβ42/Aβ40, glial fibrillary acidic protein and p-tau181 were the top predictors of cognitive decline while Aβ42/Aβ40 was prominent for amyloid negative participants across all age groups. Socio-demographics explained a large portion of the variance in the amyloid negative individuals while the plasma biomarkers predominantly explained the variance in amyloid positive individuals (21% to 37% from the younger to the older age group). Plasma biomarkers performed similarly to MRI and cardiovascular measures when predicting cognitive outcomes and combining them with either measure resulted in better performance. Top predictors were heterogeneous between cross-sectional and longitudinal cognition models, across age groups, and amyloid status. Multimodal approaches will enhance the usefulness of plasma biomarkers through careful considerations of a study population’s socio-demographics, brain and cardiovascular health.

Abstract BACKGROUND Few rare variants have been identified in genetic loci from genome‐wide association studies (GWAS) of Alzheimer's disease (AD), limiting understanding of mechanisms, risk assessment, and genetic counseling. METHODS Using genome sequencing data from 197 families in the National Institute on Aging Alzheimer's Disease Family Based Study and 214 Caribbean Hispanic families, we searched for rare coding variants within known GWAS loci from the largest published study. RESULTS Eighty‐six rare missense or loss‐of‐function (LoF) variants completely segregated in 17.5% of families, but in 91 (22.1%) families Apolipoprotein E ( APOE)‐ 𝜀4 was the only variant segregating. However, in 60.3% of families, APOE 𝜀4, missense, and LoF variants were not found within the GWAS loci. DISCUSSION Although APOE 𝜀4and several rare variants were found to segregate in both family datasets, many families had no variant accounting for their disease. This suggests that familial AD may be the result of unidentified rare variants. Highlights Rare coding variants from GWAS loci segregate in familial Alzheimer's disease. Missense or loss of function variants were found segregating in nearly 7% of families. APOE‐𝜀4 was the only segregating variant in 29.7% in familial Alzheimer's disease. In Hispanic and non‐Hispanic families, different variants were found in segregating genes. No coding variants were found segregating in many Hispanic and non‐Hispanic families.

AbstractINTRODUCTIONWe evaluated preliminary feasibility of a digital, culturally‐informed approach to recruit and screen participants for the Alzheimer's Disease Neuroimaging Initiative (ADNI4).METHODSParticipants were recruited using digital advertising and completed digital surveys (e.g., demographics, medical exclusion criteria, 12‐item Everyday Cognition Scale [ECog‐12]), Novoic Storyteller speech‐based cognitive test). Completion rates and assessment performance were compared between underrepresented populations (URPs: individuals from ethnoculturally minoritized or low education backgrounds) and non‐URPs.RESULTSOf 3099 participants who provided contact information, 654 enrolled in the cohort, and 595 completed at least one assessment. Two hundred forty‐seven participants were from URPs. Of those enrolled, 465 met ADNI4 inclusion criteria and 237 evidenced possible cognitive impairment from ECog‐12 or Storyteller performance. URPs had lower ECog and Storyteller completion rates. Scores varied by ethnocultural group and educational level.DISCUSSIONPreliminary results demonstrate digital recruitment and screening assessment of an older diverse cohort, including those with possible cognitive impairment, are feasible. Improving engagement and achieving educational diversity are key challenges.Highlights A total of 654 participants enrolled in a digital cohort to facilitate ADNI4 recruitment. Culturally‐informed digital ads aided enrollment of underrepresented populations. From those enrolled, 42% were from underrepresented ethnocultural and educational groups. Digital screening tools indicate > 50% of participants likely cognitively impaired. Completion rates and assessment performance vary by ethnocultural group and education.