Citations

Emerging evidence suggests that systemic physiological factors may influence plasma biomarker concentrations of Alzheimer’s disease (AD) and related neurodegenerative processes, potentially affecting their specificity for central nervous system pathology. This study examined the relationship of demographic factors and medical comorbidities with plasma biomarkers of AD and neurodegeneration in a community-dwelling cohort of Black/African American (B/AA) older adults (N = 141). Participants underwent plasma assessment of phosphorylated tau at threonine 217 (p-Tau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). Results showed associations between plasma p-Tau217 and amyloid PET positivity, and significant intercorrelations among p-Tau217, GFAP, and NfL. Stepwise regression models incorporated demographics, amyloid PET status, and laboratory measures of renal, metabolic, and lipid function as predictors for each biomarker. p-Tau217 was primarily predicted by amyloid PET and renal function; GFAP by age and sex; and NfL by renal function, age, and sex. Findings indicate plasma biomarker concentrations in B/AA older adults reflect both central AD-related pathology and systemic physiological factors, particularly renal function, and demographic influences. Results underscore the importance of accounting for comorbid medical conditions and demographic characteristics when interpreting blood-based biomarkers and highlight the need for comprehensive medical phenotyping to improve diagnostic specificity and clinical utility.

ABSTRACT Background Anemia is an established marker of cardiovascular disease severity and risk which leads to elevations in resting myocardial blood flow (MBF) and impaired myocardial flow reserve (MFR) in patients without obstructive coronary artery disease (CAD). Anemia can potentially be detected opportunistically from blood pool density changes on computed tomography (CT) imaging. Objectives We evaluated relationships between chamber density measurements with hemoglobin, positron emission tomography (PET) findings, and cardiovascular events. Methods We included 33460 patients from 13 sites in the REFINE-PET who underwent PET and 24368 patients undergoing lung cancer screening chest CT. A deep learning model segmented cardiac chambers from CT images, then quantified chamber density. We evaluated the relationship between chamber density measures with resting MBF and MFR, as well as associations with death or myocardial infarction (MI). Results We included a total of 57,828 patients. A higher density in myocardium compared to left ventricle blood pool was associated with reduced MFR (adjusted odds ratio 3.02 per SD increase, 95% confidence interval[CI] 2.72 – 3.38) and an increased risk of death or MI in (adjusted hazard ratio[HR] 1.38 per SD increase, 95% CI 1.26-1.51). Having myocardial density higher than blood pool density was also associated with cardiovascular death in patients undergoing low-dose chest CT (adjusted HR 1.73, 95% CI 1.20-2.52). Conclusions In a large multimodality dataset, lower cardiac chamber density is associated with impaired MFR and independently associated with cardiovascular events. These biomarkers can be automatically extracted from CT to provide physiologic insights and potentially guide patient care. CONDENSED ABSTRACT Anemia is an important marker of cardiovascular disease severity and predictor of cardiovascular events. We utilized deep learning to measure cardiac chamber density on computed tomography imaging as a surrogate for anemia in 57,828 patients from two large multicenter studies. A higher density in myocardium compared to left ventricle blood pool was associated with reduced MFR and an increased risk of death or MI in patients undergoing positron emission tomography, and an increased risk of cardiovascular death in patients undergoing low-dose computed tomography. These biomarkers can provide additionally physiologic insights which could be used to guide patient care.

Abstract Rationale Fungal infections remain a major cause of morbidity and mortality post lung transplant due to unique exposure of the allograft to the external environment and the intensity of immunosuppression. Single-center studies have described variable rates of fungal infections. Contemporary population-level data with temporal trends, pathogen distribution, and associated outcomes are limited. Leveraging a large multicenter real-world dataset, we aimed to characterize incidence, prevalence and clinical outcomes of fungal infections among adult lung-transplant recipients. Methods Data were obtained from the TriNetX Global Collaborative Network (160 HCOs). Adult lung-transplant recipients (≥18 years) were identified between 2005 and 2024, using ICD and CPT procedure codes. Patients with solid organ transplants other than lung, combined-organ transplant or stem-cell transplant and HIV patients were excluded. Patients with pre transplant fungal infections were also excluded. Pre-transplant characteristics included demographics, comorbidities within a year, laboratory values within seven days, and medication within 90 days before transplantation. Post-transplant fungal infections were identified using ICD-10 codes for Aspergillus, Candida, Cryptococcus, Mucorales, Histoplasma, Blastomyces, Coccidioides, and Pneumocystis. TriNetX platform was utilized for statistical analysis. Incidence and prevalence of infections, all-cause mortality and transplant rejection were analyzed. Results A total of 12,857 adult lung-transplant recipients were identified. The mean age at transplantation was 57.6 ± 13.4 years, with a male predominance of (57%) and majority were white (65%). Average BMI was 26.8 ± 5.7 kg/m². The most common pulmonary conditions were COPD (15%), pulmonary fibrosis (17%), pulmonary hypertension (9%), bronchiectasis (3%), and cystic fibrosis (3%). Pre-transplant fungal and viral screening assays were rarely available (<1%). Medication exposure within 90 days prior to transplant demonstrated prednisone prescription (17%) methylprednisolone (7%), tacrolimus (6%), and mycophenolate mofetil (7%). Azathioprine and basiliximab were used in 2% each. Systemic antifungals (voriconazole, posaconazole, or fluconazole) in approximately 1% each.The overall incidence of post-transplant fungal infection was 3 % across full study period, rising to 7% in the modern era (2015-2024). Most frequently identified pathogens were Candida spp. (4.8%) and Aspergillus spp. (2.9%), followed by Pneumocystis Jirovecii (0.5%). Infection rates increased from 22 per 1,000 (2005-2014) to 75 per 1,000 (2015-2024) suggestive of improved diagnostic sensitivity and data capture, and longer post-transplant survival. All-cause mortality 5-year post transplant was 22.1%, and rejection rate was 22.5%. Conclusion Our study highlights a rising burden of fungal infections among lung-transplant recipients with potential implications for early post-transplant surveillance and antifungal prophylaxis strategies. This abstract is funded by: None

Abstract Rationale Fungal infections are common after lung transplantation and may adversely affect graft function and survival, but long-term outcomes remain incompletely defined. Using a large multicenter real-world dataset, we aimed to study the impact of post-transplant fungal infections on clinical outcomes of lung transplant recipients. Methods We conducted a retrospective, cohort study using the TriNetX Global Collaborative Network, which aggregates de-identified electronic health records from >160 healthcare organizations across North America, Europe, and Asia. Adult lung transplant recipients (≥18 years) between 2005 and 2024 were identified using ICD-10 and CPT codes. Patients with post-transplant fungal infection (aspergillosis, candidiasis, mucormycosis, histoplasmosis, coccidioidomycosis, blastomycosis) and matched controls without fungal infection within one year before or any time after transplant were identified. The index date was the date of transplantation. Propensity-score matching was performed on demographics, comorbidities, laboratory values, procedures and immunosuppressive medications. Outcomes included all-cause mortality (primary), allograft rejection, and chronic lung allograft dysfunction (CLAD) at 6 months, 1 year, 3 years, and 5 years. Kaplan-Meier and Cox proportional hazards models were used to estimate risk ratios (RRs), hazard ratios (HRs), and 95% confidence intervals (CIs). Analyses were conducted in TriNetX Analytics (v25.0, Cambridge, MA). Results A total of 3,083 patients with post-transplant fungal infection and 11,625 patients without infection were identified. Mean age was 58 ± 13 years, and 56% were male. The most common pulmonary comorbidities were chronic obstructive pulmonary disease, unspecified pulmonary fibrosis, idiopathic pulmonary fibrosis and bronchiectasis. Immunosuppression exposure was similar across groups. After propensity score matching across 56 clinical variables, both groups (1,790 per group) were well balanced. Mortality was higher in the fungal infection cohort at all follow-up points: 13.% vs 9% at 6 months (RR 1.45, 95% CI 1.2-1.75, p = 0.001), 17.8% vs 13% at 1 year (RR 1.36, p = 0.0001), 27.7% vs 21% at 3 years (RR 1.28, p < 0.0001), and 33 % vs 25% at 5 years (RR 1.32, p < 0.0001). Allograft rejection remained consistently higher (46-61% vs 22-34%), while CLAD occurred two- to three-fold more frequently (1.8-5.7% vs 0.7-2%). Conclusion Post-transplant fungal infection is independently associated with significantly increased mortality, acute rejection, and CLAD following lung transplantation. These findings underscore the need for early fungal surveillance, optimized antifungal prophylaxis, and individualized immunosuppression strategies to improve long-term patient outcomes. This abstract is funded by: None

Background SGLT2 (sodium‐glucose cotransporter 2) inhibitors reduce major adverse cardiovascular events (MACE) in type 2 diabetes. However, no direct comparison of individual SGLT2 inhibitor drugs has been conducted, particularly among adults with moderate cardiovascular risk who comprise most people with type 2 diabetes. Methods We used data for commercial, Medicare Advantage, and Medicare fee‐for‐service beneficiaries to emulate a target trial of adults (≥21 years) with type 2 diabetes and moderate cardiovascular risk who started canagliflozin, dapagliflozin, or empagliflozin between 2015 and 2020. We estimated propensity scores using the super learner ensemble method and incorporated them as inverse probability of treatment weights into Cox models, estimating risk of MACE, expanded MACE, and hyperglycemic and hypoglycemic crises through December 31, 2022. Results The weighted cohort, balanced on all baseline covariates, included 137 232 patients (mean age 65.7 years [SD, 8.1], 75.3% non‐Hispanic White, 57.0% male, 81.9% on metformin, 11.4% on glucagon‐like peptide‐1 receptor agonists) starting canagliflozin (N=42 877), dapagliflozin (N=17 871), or empagliflozin (N=7648). The risk of MACE was lower among patients starting empagliflozin versus canagliflozin (hazard ratio [HR], 0.92 [95% CI, 0.87–0.97]), driven by reduced risk of all‐cause mortality (HR, 0.86 [95% CI, 0.80–0.94]). There was no difference in MACE between empagliflozin versus dapagliflozin or dapagliflozin versus canagliflozin therapy. There was no difference in remaining outcomes between the three drugs. Conclusions The 3 most used SGLT2 inhibitor medications demonstrate similar effectiveness on cardiovascular outcomes among patients with type 2 diabetes at moderate cardiovascular risk, with differences between these drugs small in magnitude. Clinicians and health systems should prioritize enhancing access to these cardioprotective therapies.

Abstract Background Previous studies evaluated large language model (LLM) performance on the American Society of Nuclear Cardiology (ASNC) Board Preparation Exam. Without domain-specific context, the best model (GPT-4o) achieved 63.1%, below the estimated 65% passing threshold and the 78% mean score of human fellows-in-training (FITs). Providing textbook context improved GPT-4o to 73.8% on text-only questions, but still fell short of human trainees. Whether next-generation LLMs with retrieval-augmented generation (RAG) can exceed this gap is unknown. Methods Claude Opus 4.7 and GPT-5.5 were administered all 168 questions (141 text-only, 27 image-based) from the 2023 ASNC Board Preparation Exam across 5 iterations each, using RAG with a nuclear cardiology textbook, companion atlas, and ASNC clinical guidelines. Claude used local FAISS-based semantic retrieval; GPT-5.5 used Azure’s cloud-hosted vector store. Performance was compared to prior LLM results and 13 human FITs. Results Across 5 iterations, Claude Opus 4.7 achieved a mean accuracy of 86.3% ± 1.4% (text 88.8%, image 73.3%). GPT-5.5 achieved 86.7% ± 2.2% (text 88.5%, image 77.0%) but refused a mean of 12.2 questions (7.3%) per iteration due to safety filters. Both models surpassed the human FIT mean (78.0%) and the estimated passing threshold. Compared to GPT-4o without context (63.1%), this represents a 23-percentage-point improvement in 18 months. Conclusion Next-generation LLMs with RAG now surpass average human trainee performance on nuclear cardiology board preparation questions, suggesting significant potential as educational tools and knowledge-reference aids in cardiovascular imaging. Condensed Abstract Across 5 iterations each, Claude Opus 4.7 and GPT-5.5 with retrieval-augmented generation achieved mean accuracies of 86.3% and 86.7% on the 2023 ASNC Board Preparation Exam (168 questions), both surpassing the mean human fellow-in-training score of 78%. GPT-5.5 refused a mean of 12.2 questions (7.3%) per iteration due to safety filters. These results represent a 23-percentage-point improvement over the best prior LLM without context (63.1%), demonstrating that RAG-enhanced LLMs have reached human-level proficiency in nuclear cardiology knowledge. Graphical Abstract Overview of the three-study research arc evaluating LLM performance on the 2023 ASNC Board Preparation Exam. Study 1 (2024) tested four LLMs without context (best: GPT-4o, 63.1%). Study 2 (2025) added textbook context to GPT-4o (73.8%). Study 3 (2026, current) evaluated Claude Opus 4.7 and GPT-5.5 with retrieval-augmented generation across 5 iterations each (mean 86.3% and 86.7%, respectively), both surpassing the human fellow-in-training mean of 78%. Right panel shows the performance scale with key thresholds.

Background: Spontaneous coronary artery dissection (SCAD) is a common type of myocardial infarction in females under the age of 50 years, caused by sudden separation between the coronary arterial wall layers and/or hematoma. The SCAD patient population is mostly females (~80%) with few or no traditional cardiovascular disease risk factors (e.g., obesity, hypertension). Common triggers for SCAD include sympathoexcitatory stimuli, such as intense physical and emotional stress. This implicates the sympathetic nervous system in the pathophysiology of SCAD. Thus, we aimed to investigate sympathetic nervous system responses to mental stress in patients with a history of SCAD. We hypothesized that females with a history of SCAD exhibit a greater increase in muscle sympathetic nerve activity (MSNA) with acute exposure to mental stress compared to healthy females. Methods: Seven females with a history of SCAD (age: 48±9 yrs, BMI: 29±6 kg/m 2 ) and seven age- and BMI-matched healthy female controls (CON, age: 49±9 yrs, BMI: 26±6 kg/m 2 ) participated in the study (both p>0.05). MSNA was measured via peroneal microneurography during a 2-minute rest, a 5-minute Stroop Color Word Test aimed at inducing mental stress, and a 2-minute recovery. Heart rate (HR, 3-lead electrocardiography) and BP (finger photoplethysmography) were continuously recorded during each stage. Data are presented as an absolute change from rest (Δmean±SD). Two-way independent t-tests were used for statistical analyses. Results: Resting mean blood pressure (MBP, SCAD: 96±14 vs CON: 89±7 mmHg, p=0.27), heart rate (HR, SCAD: 56±11vs CON: 65±16 bpm, p=0.25), MSNA burst frequency (SCAD: 22±9 vs CON: 18±7 bursts/minute, p=0.40) and total MSNA (SCAD: 1135±471 vs CON: 951±245 au/min, p=0.41) were not different between the groups. During the Stroop Color Word Test, average changes in MBP (SCAD: Δ10±9 vs CON: Δ8±5 mmHg, p=0.67) and HR (SCAD: Δ11±7 vs CON: Δ14±5 bpm, p=0.35) were not different between the groups. Similarly, average changes in MBP (SCAD: Δ3±4 vs CON: Δ-2±5 mmHg, p=0.13) and HR (SCAD: Δ3±4 vs CON: Δ3±2 bpm, p=0.62) were not different during the recovery. Changes in MSNA burst frequency with the Stroop Color Word Test (SCAD: Δ1±7 vs CON: Δ6±7 bursts/minute, p=0.22) and recovery (SCAD: Δ0±5 vs CON: Δ4±4 bursts/minute, p=0.13) were not different between the groups. Total MSNA changes were also not different during the Stroop Color Word Test (SCAD: Δ267±335 vs CON: Δ606±432 au/min, p=0.15) and recovery (SCAD: Δ68±666 vs CON: Δ217±217 au/min, p=0.61) between the two groups. Conclusion: These preliminary data suggest that contrary to our hypothesis, sympathetic nervous system responses to acute mental stress exposure are not different between females with a history of SCAD and healthy females. Further investigation is needed to understand MSNA association with chronic stress exposure in females with a history of SCAD. Funding: NIH K23 HL155506 This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Alzheimer’s disease (AD) is characterized by profound metabolic dysfunction and disturbances in gut–brain axis signaling. Ketogenic diet (KD) has demonstrated metabolic and cognitive benefits in both preclinical and clinical studies. However, factors that determine individual responsiveness or non-responsiveness to KD interventions remain poorly understood. Emerging evidence suggests that gut microbiome composition plays a critical role in modulating these factors. This study examined how KD responsiveness, determined by fecal microbiota transplantation (FMT) derived from human KD responders (RES) or non-responders (nRES)- influences cognition, gut barrier function, neuroinflammation, and microbial structure in 3xTg-AD mice. We further evaluated whether supplementing KD with a novel Synbiotic Yogurt (SY) formulated by our team could augment or restore responsiveness. We hypothesized that RES microbiota would confer superior KD-driven benefits and that KD-SY would synergistically improve metabolic and neurobiological outcomes, particularly among nRES recipients. Adult 3xTg-AD mice were antibiotic-cleansed and randomized to receive Control-, RES-, or nRES – FMT, while maintained on KD for four weeks. A second cohort received KD supplemented with SY or non-fat milk along with RES- or nRES-FMT. Behavioral tests, gut permeability assay, serum inflammatory markers, brain amyloid beta (Aβ), intestinal morphology, gene expression, and 16S rRNA microbial profiling were measured. RES-FMT recipients showed early improvements in spatial memory (Y-maze and novel object recognition) and consistently lower Aβ accumulation in cortex and hippocampus. They also showed higher synaptophysin and IL-10 expression. In contrast, nRES-FMT mice exhibited distinct microbiome clustering, lower microbial diversity, enrichment of Proteobacteria, and impaired gut barrier function relative to RES-FMT recipients. Functionally, specific taxa like Enterococcus, Enterobacter, and Paenibacillus were associated with greater vulnerability to AD-related pathology, while Akkermansia, Bifidobacterium, and Muribaculum were linked with lower vulnerability. SY supplementation improved metabolic and gut barrier indices across groups characterized by increased circulating ketone levels, lowered fasting glucose and glucose-ketone index, and decreased gut permeability. nRES-SY mice showed the strongest gains in recognition memory and reductions in brain Aβ1–42 burden. SY increased expression of barrier- and inflammation-modulating genes, including occludin, APLP2, and IL-10. Microbiome analysis demonstrated higher microbial diversity and enrichment of beneficial genera such as Paralactobacillus, Eubacterium, and Muribaculum. These findings show that KD responsiveness is strongly determined by gut microbiota composition and that SY supplementation can enhance or rescue metabolic, cognitive, and microbial outcomes, particularly in nonresponders. This supports a precision-microbiome strategy combining metabolic and Synbiotic interventions to improve gut–brain axis function in AD. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Abstract Inflammatory bowel disease (IBD) is a chronic immune-mediated disorder of the gastrointestinal tract whose genetic basis is only partly resolved because most risk variants identified by genome-wide association studies (GWAS) lie in non-coding regions, limiting direct gene assignment and biological interpretation 1,2 . Here we analysed whole-exome and whole-genome sequencing data from 86,213 IBD cases and 478,363 controls of European ancestry. We identified 68 IBD genes directly implicated by conditionally independent protein-coding associations across the allele frequency spectrum. Many newly implicated IBD genes are supported by orthogonal genomic or pleiotropic evidence, pointing to disease-related pathways and nominating targets with therapeutic relevance. We further identified allelic series and non-additive effects at key loci such as NOD2 and TYK2. These results show that large-scale sequencing can resolve disease genes and pathways that remain ambiguous from non-coding association alone, providing a more direct route from human genetics to biological insight and therapeutic hypotheses.