Citations

Peroxisome-proliferator–activated receptor delta (PPARδ) regulates metabolic, mitochondrial, and inflammatory pathways implicated in neurodegeneration, making it an attractive therapeutic target for amyotrophic lateral sclerosis (ALS). In this study, we evaluated two PPARδ agonists, KD3010 and T3D-959, in two established ALS/FTD mouse models: an AAV-mediated C9orf72 G4C2-repeat expansion model (C9-149R) and the TDP-43Q331K transgenic model. Drug treatment was initiated prior to the emergence of key disease features and continued for 9–10 months. Comprehensive behavioral, neuropathological, and biomarker analyses revealed marked differences between the two models. C9-149R mice exhibited reduced body weight and subtle behavioral alterations without robust motor deficits, whereas TDP-43Q331K mice developed pronounced, progressive motor and cognitive impairments accompanied by a ~7-fold elevation in plasma neurofilament light chain (NfL). Despite effective target engagement—particularly for T3D-959—neither PPARδ agonist improved motor performance, cognitive behavior, neuroanatomical measures, plasma NfL levels, or disease-associated molecular phenotypes in either model. Prolonged KD3010 treatment resulted in loss of target engagement, consistent with drug tolerance, while T3D-959 sustained PPARδ activation without therapeutic benefit. Together, these findings demonstrate that PPARδ agonism is insufficient to modify disease progression in these ALS/FTD mouse models and underscore the importance of publishing well-powered negative preclinical studies to refine therapeutic strategies for ALS.

BACKGROUND AND OBJECTIVES: Myelomeningocele is defined by the presence of a fluid-filled sac that contains the neural placode and cerebrospinal fluid (CSF) at the level of the spinal defect. Alternatively, the term myeloschisis is used when the neural placode is not contained within a CSF-filled sac. While both are eligible for prenatal closure, few studies have characterized the impact of the type of lesion on postnatal outcomes. This study compares the outcomes of these 2 types of open spinal dysraphism using data from the Fetal Myelomeningocele Consortium registry sponsored by the North American Fetal Therapy Network. METHODS: The prospective observational Fetal Myelomeningocele Consortium registry was used to extract deidentified data corresponding to patients who underwent fetal closure of myelomeningocele vs myeloschisis. Demographics, operative characteristics, perioperative complications, and postnatal outcomes were collected. RESULTS: A total of 1327 patients were identified, including 991 (74.7%) with myelomeningocele and 336 (25.3%) with myeloschisis. Compared with myelomeningocele, myeloschisis was associated with lower rates of prenatal talipes (11% vs 24%, P < .001) and higher rates of favorable prenatal movement (94% vs 86%, P < .001). Postnatally, myeloschisis conferred higher rates of leg movement (97% vs 90%, P = .002) and an increased likelihood of ambulation in the household (10.4% vs 4.1%, P = .009) and outside (7.2% vs 1.9%, P = .004) at 1 year. However, myeloschisis was also linked to greater use of skin patches during closure (49% vs 27%, P < .001), higher CSF leak rates among those with wound dehiscence (26% vs 8%, P = .014), and more frequent CSF diversion and tethered cord surgeries at follow-up. CONCLUSION: Myeloschisis and myelomeningocele demonstrate distinct clinical profiles. Although patients with myeloschisis may have favorable motor outcomes, they are also characterized by higher rates of CSF leakage, CSF diversion, and tethered cord surgery. These findings highlight the need for lesion-specific prognostication and may inform surgical planning and parental counseling in the context of prenatal spina bifida closure.

Abstract INTRODUCTION The vascular endothelial growth factor (VEGF) signaling family plays a role in neurodegenerative diseases, including Alzheimer's disease (AD). Previous work has shown widespread effects of the members FLT1 , FLT4 , and VEGFB on AD outcomes. However, these analyses have focused within the non‐Hispanic White (NHW) population. METHODS The goal of this study was to analyze the effects of the VEGF family in underrepresented populations, leveraging large and diverse bulk RNA sequencing and tandem mass tag–mass spectrometry (TMT‐MS) proteomic data. Outcomes included measures of AD pathology and diagnosis. RESULTS Within underrepresented populations, we replicated previously reported effects of FLT1 and FLT4 , whereby higher protein abundance was observed in the AD brain and was associated with higher neuropathology burden. In stratified analyses, these associations were largely consistent across race and ethnicity. DISCUSSION This multi‐omic study on the role of the VEGF family in AD emphasizes the need for more representative studies focused on therapeutic targets for AD. Highlights Vascular endothelial growth factor (VEGF) genes and proteins were quantified in four different brain regions. Samples included participants from four different populations. Previously observed effects were replicated in diverse populations. This study is the largest multi‐omic study of the vascular endothelial growth factor (VEGF) genes among Alzheimer's disease (AD) participants from diverse populations.

ABSTRACT Skeletal muscle (SM) is an integral organ component in the pathophysiology of many acute and chronic diseases. But is there a ‘gold’ standard or accepted reference method for quantifying the amount and composition of human SM mass? Exploring that question led us to recognize the existence of a SM measurement paradigm that divides methods into two broad categories, in vitro and in vivo. In vitro methods quantify SM mass, weighing intact muscles as part of whole cadaver evaluations, only 51 of which are reported in medical literature with no recent additions. In vivo methods are used to evaluate SM in vivo, and two tiers were revealed in our analyses. An upper tier that included three methods considered ‘reference’ approaches for their accuracy and precision: computed tomography, magnetic resonance imaging and dual‐energy X‐ray absorptiometry. A lower in vivo method tier included bioimpedance analysis, three‐dimensional imaging, several approaches involving creatine metabolism, ultrasound and anthropometry. A feature common to all of the lower tier methods is their need for calibration or validation against reference approaches in the upper in vivo method tier. A critical review of the three in vivo reference methods in the upper tier revealed widely variable SM volume/mass acquisition protocols, image analysis methods and applied terminology. Some reports espouse an upper tier reference method as the ‘gold’ standard while providing minimal details of exactly how and what was measured, thus making replication in follow‐up studies difficult. Any technical issues related to an in vivo reference method are propagated to the in vivo methods in the lower tier that are calibrated or validated against them. Our review of in vivo reference methods of quantifying SM mass and composition led us to two broad recommendations. First, published reports including these reference methods should provide enough details related to acquisition and analysis protocols so that readers can replicate their findings. Second, an effort should be made to apply precise terminology in published reports in order to avoid confusion on exactly what was measured; suggestions are made on definitions of commonly used terms when referring to body composition compartments. Lastly, because there is no consensus on what constitutes a ‘gold’ standard for SM measurement, we suggest expert groups convene in the future to recommend optimum approaches and working guidelines for quantifying muscle mass and composition in vivo.

Key Points Data were collected from a cohort of 759 patients with autosomal dominant polycystic kidney disease that were followed for a median of 10.2 years. Prognostic models were developed to predict kidney failure using routinely obtained clinical information and externally validated. Risk predictions had good discrimination and calibration over a time horizon of 15 years. Background Autosomal dominant polycystic kidney disease (ADPKD) is a common cause of kidney failure. Progression is highly variable, and accurate prognostic information is needed to guide early treatment decisions. The objective of this study was to develop a multivariable predictive model for progression to kidney failure. Methods We developed prognostic models using Cox regression for the outcome of kidney failure, defined as eGFR <15 ml/min per 1.73 m 2 , dialysis, or kidney transplantation. The development dataset consisted of participants in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) and Halt Progression of Polycystic Kidney Disease study A (HALT-A) studies. The validation dataset consisted of patients with ADPKD in the Mayo clinical registry aged 15–49 years, with eGFR ≥60 ml/min per 1.73 m 2 . Predictor variables in the base model were age, sex, creatinine or eGFR, ADPKD genotype, and Mayo Imaging Class. Clinical and laboratory data were evaluated in the full model. Results The development cohort included 759 patients with baseline eGFR of 91±29 ml/min per 1.73 m 2 (mean±SD), of whom 16% reached end point after median (interquartile range) follow-up of 10.2 (5.5–16.7) years. The validation cohort included 535 patients with baseline eGFR of 90±31 ml/min per 1.73 m 2 (mean±SD), of whom 11% reached end point after median (interquartile range) follow-up of 5.5 (1.5–13.7) years. The full model, including age, sex, serum creatinine, Mayo Imaging Class, total carbon dioxide, hemoglobin, diastolic BP, and body mass index, had a C-index of 0.81 (95% confidence interval, 0.72 to 0.90) in the validation cohort and 0.75 (95% confidence interval, 0.62 to 0.88) when ADPKD genotype was also included. Risk predictions from base and full models were well-calibrated out to 15 years. Conclusions In persons with early ADPKD and preserved eGFR, a model using routinely obtained clinical information quantified risk of kidney failure over 15 years.

Abstract Background Large language models (LLMs) are increasingly used in medication-related tasks despite limited evidence supporting their accuracy and safety. LLMs are vulnerable to adversarial attacks and may confabulate in response to fabricated information in the prompt. Given the substantial risk of harm from medication errors, the purpose of this study was to establish a benchmark task to evaluate LLM performance in distinguishing fabricated from real medications. Methods Two datasets (brand and generic), each consisting of 250 medication lists were developed, each including 4-6 medications and one fabricated medication (specifically a Pokémon character), with complete dosing information provided. Six LLMs were evaluated (GPT-5-Chat, GPT-4o-mini, DrugGPT, Gemma-3-27B-IT, Llama-3.3-70B-Instruct, and Qwen3-32B). For each medication list, models were queried for dosing information and disease indication across three experimental conditions: standard decoding, standard decoding with mitigation prompting, and deterministic decoding (temperature = 0). Each experiment was performed in triplicate. Outputs were deemed confabulations if the LLM failed to recognize and reject the fabricated medication. The primary outcome was the rate of confabulations. Exact paired-permutation tests were used to compare confabulation rates across LLMs and prompting approaches. Results Confabulation rates under standard conditions ranged from 2.7% to 99.6%. DrugGPT demonstrated the lowest baseline confabulation rates (2.7-6.4%), whereas other models demonstrated substantially higher rates (47.2-99.6%). Mitigation prompting significantly reduced confabulation rates compared to standard and deterministic decoding across all tasks and datasets (p < 0.001): GPT-5-Chat achieved confabulation rates of 0% with mitigation prompting from baseline rates of 66.4-88.5%. Deterministic decoding did not substantially impact confabulation rates. Conclusions LLMs performing medication-related tasks are susceptible to confabulation in response to invalid or fabricated inputs, raising important safety concerns for clinical use. While mitigation prompting reduced confabulation rates, this study underscores the importance of robust safeguards when deploying LLMs in medication-related decision-making.

Background/Objectives: Individuals with type 2 diabetes (T2D) achieve less total body weight loss (TBWL) with obesity medications compared to those without T2D. The individualized metabolic surgery (IMS) score, originally developed to predict T2D remission after bariatric surgery, inversely correlates with TBWL response to semaglutide. IMS reflects T2D severity, incorporating HbA1c and T2D duration and medication use. This study aims to evaluate TBWL with tirzepatide across IMS severity categories and identify predictors of response in a real-world cohort. Methods: This retrospective analysis included 717 adults with T2D using tirzepatide for overweight or obesity within the Mayo Clinic Health System. Patients were stratified by IMS severity (mild, moderate, severe) and quartiles. Primary endpoint: TBWL% at 15 months. Secondary endpoints: categorical thresholds (≥5%, ≥10%, ≥15%, ≥20%) and predictors of TBWL%. Linear mixed-effects models and regression models were employed. Results: At 15 months, TBWL was greater in mild versus severe IMS groups (14.8% vs. 11.0%, p = 0.015), with similar trends across quartiles. The proportion achieving ≥ 20% TBWL was nearly two-fold higher in mild versus severe IMS (27% vs. 14%, p = 0.03). Female sex independently predicted greater TBWL, whereas insulin use, higher T2D medication burden (particularly weight-promoting agents), and HbA1c > 7% were associated with less TBWL. Conclusions: Tirzepatide produced clinically meaningful TBWL across all IMS categories, although TBWL declined with increasing IMS severity. Glycemic control and T2D medication use emerged as strong predictors of TBWL. The IMS score may serve as a practical tool to anticipate weight-loss trajectories, guide personalized treatment decisions, and inform patient counseling.

Abstract Background Alzheimer's disease (AD) exhibits significant genetic heterogeneity, with no single model fully explaining its inheritance pattern. Structural variants (SVs) may contribute to the missing heritability of AD, particularly in disease pathology and familial AD, which remain largely unexplored. Method Structural variants (SVs) were analyzed in unrelated 1,162 individuals from the ROSMAP study (687 cognitively normal (CN), 475 AD patients), as well as 197 Non‐Hispanic White (NHW) families (926 individuals, 58.5% with AD) and 214 Caribbean Hispanic (CH) families (1,340 individuals, 59.17% with AD). Large insertions and deletions were identified using Manta, Absinthe, and MELT from whole‐genome sequencing, supplemented by Sniffles2 and external SV call sets. This approach generated a unified VCF file containing 45,251 insertions and 76,566 deletions. After filtering for missingness rate and allele counts, a total of 9,290 insertions and 9,529 deletions were retained for analysis. Genome‐wide SV analyses were performed with AD‐related metrics in ROSMAP, adjusting for age, sex, and principal components, and validated in an independent ADSP replication cohort comprising 29,055 unrelated individuals (17,110 CN and 11,945 AD patients). Result We identified nine SVs (one insertion and eight deletions) segregating in AD families. An insertion near PDCD10 in NHW families reached genome‐wide significance ( p <5×10 ‐8 ) for AD risk in the replication cohort. Two deletions in KIF26B and SPHKAP were found in both CH and NHW families, while five appeared only in NHW and one in CH. All eight deletions showed genome‐wide significance for AD risk. SV GWAS on AD pathologies in ROSMAP revealed an insertion in INPP4B with the strongest association to global brain pathology (β=0.19; p = 2.32×10 ‐5 ), also linked to pathological AD, diffuse plaques, and Braak staging. A deletion near ADGRB1 (β=1.53; p = 5.05×10 ‐6 ) was associated with neuritic plaques, and another near ARMC2 (β=1.66; p = 2.17×10 ‐6 ) was linked to diffuse plaques. All three SVs associated with AD ( p <5×10 ‐6 ) in replication. Conclusion Our findings reveal numerous SVs segregating in familial AD across both CH and NHW families, as well as additional SVs linked to sporadic AD. Prioritizing these SVs based on their potential effects on gene function and expression will provide deeper insight into their contributions to both familial and sporadic AD.

Abstract Geroscience research benefits from interdisciplinary approaches, team science, and collaborations, which collectively facilitate the discovery of aging mechanisms and their translation into tangible, clinical interventions. Since its inception in 2019, the Midwest Aging Consortium (MAC) has provided an engaging platform for aging researchers in the United States’ Midwest to connect, collaborate, and exchange ideas. The Sixth Annual Research Symposium of the MAC held at the Mayo Clinic in Rochester, Minnesota, in April 2025 highlighted the continued impact of the MAC in bringing together aging researchers, including many trainees and early career investigators, into a collaborative environment. This record-setting event featured interdisciplinary research on key aging mechanisms, including lipid metabolism, mitochondrial dysfunction, stress response, cellular senescence, and immune adaptations across organ systems. New therapeutic concepts and clinical trial approaches were presented. Cutting-edge methodologies including single-cell and spatial transcriptomics, metabolomics, and organoid cultures, to dissect aging process in tissue-specific and systemic contexts also were presented. Overall, the MAC symposium underscored the translational potential of geroscience and reinforced the MAC’s mission to accelerate aging research through regional collaborations and innovation.

Evidence-based practice is critical to providing high-quality hospice and palliative nursing care. Professional organizations, such as the Hospice and Palliative Nurses Association (HPNA), play a critical role in shaping the future of the hospice and palliative nursing field by identifying gaps in the science and fostering collaborative research efforts to inform evidence-based practices. One such driver is the tri-annual HPNA Research Agenda, which outlines key research priorities in hospice and palliative nursing, ultimately aiming to accelerate translation of research into practice and practice improvements. In this article, 6 emerging research scholars in the field and present and former co-chairs of the HPNA Emerging Research Scholar Special Interest Group reflect on the experiences that led them to pursue research careers in hospice and palliative nursing. Through a process of collective self-assessment, these scholars articulated their shared progress toward addressing the research priorities outlined in the 2023–2026 HPNA Research Agenda as a means of generating insights to direct future research efforts in the field.