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Abstract Background Treatment with immune-checkpoint inhibitors (ICI) may be associated with adverse cardiac events. Troponin elevation is part of the diagnostic criteria for ICI related myocarditis (ICIrM) and myocardial infarction (MI), however there is limited data for causes of troponin elevation independent of MI and ICIrM and their clinical outcomes with ICI therapy. Purpose To assess the diagnostic and prognostic value of high-sensitivity troponin T (hs-TnT) in patients treated with ICI based on different etiologies and association with cardiac events. Methods All patients treated with ICI who had hs-TnT measured at a multi-center institution from 2011 to 2022 were included. Medical records were reviewed for baseline characteristics and long-term outcomes, including cardiac death and MACE (MI, stroke, heart failure [HF]), and cause of hs-TnT elevation. Risk of cardiac events and mortality were compared for the different etiologies of hs-TnT elevation. Results Of 5,423 patients treated with ICI, 1669 had post-ICI hs-TnT measurement. Mean age was 68.7±11.3 years, 58.3% were male, with follow-up through one year from ICI first administration. Elevated hs-TnT was seen in 1136 patients, with the different causes for elevation depicted in Figure 1, panel A. ICIrM patients exhibited the highest median hs-TnT value of 364 ng/L (IQR 1096), followed by a median of 98 ng/L for MI/Type 2 ischemia, 61 ng/L for infection/sepsis, 51 ng/L for pulmonary embolus, 50 ng/L for HF and 27 ng/L for indeterminate causes, Figure 1, panel B. Additionally, median time from first ICI dose to hs-TnT elevation according to each of the diagnoses are depicted in Figure 1, panel C, with ICIrM showing the shortest median time of 44 days (IQR 74). Hs-TnT elevation in patients with ICIrM had the highest risk for cardiac death (HR 52.7, 95% CI 11.7-238.0, p<0.001), followed by hs-TnT elevation due to HF (HR 15.9, 95% CI 2.9-87.0, p=0.001), MI/type 2 ischemia (HR 11.6, 95% CI 2.4-56.1, p=0.002), and infection/sepsis (HR 5.7, 95% CI 1.0-31.0, p=0.045) compared to those with no hs-TnT elevation, Figure 2, panel A. Similarly, patients with ICIrM had highest risk for MACE (HR 8.2, 95% CI 4.4-15.3, p<0.001), followed by increased hs-TnT due to MI/type 2 ischemia (HR 8.1, 95% CI 5.0-13.1, p<0.001), HF (HR 7.6, 95% CI 4.2-13.7, p<0.001), pulmonary embolism (HR 5.1, 95% CI 2.5-10.8, p<0.001), infection/sepsis (HR 4.1, 95% CI 2.4-7.0, p<0.001), and indeterminate cause (HR 2.4, 95% CI 1.5-3.8, p<0.001), Figure 2, panel B. Conclusions Hs-TnT measurements have prognostic value for cardiac events in cancer patients receiving ICI therapy, including in those without ICIrM. Patients with ICIrM demonstrated the highest median hs-TnT levels and the poorest outcomes, with a graded response observed; the worst prognosis was seen in patients with hs-TnT elevation due to ICIrM, followed by other causes, and those without hs-TnT elevation had the best prognosis.Figure 1 Figure 2

Autism is a heritable neurodevelopmental condition marked by impaired social interaction, repetitive behavior, and co-occurring conditions. Sleep disturbances are common in autism. This study uses low-cost wearable devices to compare sleep, physical activity, and circadian behavior in autistic adults and their non-autistic relatives. We recruited 318 autistic individuals and 130 family members, collecting accelerometer data over 3 weeks (8249 days). Using a data-driven approach, we identified actimetry-derived features associated with autism. We examined 308 traits using the elastic net algorithm and linear mixed effects regressions. We identified 52 actimetry measures associated with autism (area under the curve: 0.812; confidence interval: 0.761–0.862), validated in a test set (area under the curve: 0.756; confidence interval: 0.700–0.813). Both mean and day-to-day variability in several measures (e.g., time spent sedentary, total light physical activity) were associated with autism. In autistic individuals, reduced physical activity during wake was more strongly associated with shorter sleep time than in non-autistic relatives (likelihood ratio: 41.6; p = 1.13e−10). Reduced physical activity in autistic individuals was linked to increased social impairment, as measured by the Social Responsiveness Scale. Long inactivity periods and lower physical activity levels were associated with autism, correlating with less sleep and later sleep onset. Interventional studies are needed to explore if improving sleep and physical activity can improve the quality of life for autistic individuals. Lay Abstract Autistic individuals frequently report problems with their sleep, though what aspects of sleep are most affected is not well understood. In this study, we recruited 318 adult autistic participants without intellectual disability and 130 of their non-autistic family members to measure their sleep, physical activity, and daily routines. Study participants wore accelerometer-based wrist-worn devices over 3 consecutive weeks to record their movement and activity. In total, 154 distinct physical activity, sleep, and behavioral traits were identified from the recordings, 52 of which were found to associate with autism. Many of these traits were related to physical activity, where autistic individuals were more likely to be less active for longer periods and have lower overall physical activity levels. Long periods of inactivity also associated with less sleep, with a stronger association in those with autism. For example, for every hour of inactivity, autistic participants had on average ~23 min less of sleep compared to ~17 min in their family members. Autistic individuals with lower levels of physical activity showed higher social impairment as measured by the Social Responsiveness Scale. Overall, lower physical activity may impair sleep and worsen the core features of autism. Interventional studies aimed to increase physical activity may improve the quality of life of autistic individuals.

Abstract When using real-world data to construct an external comparator arm for a single-arm trial, there may be differences in how and when patients are assessed for disease between trial and real-world settings. Such differences can generate outcome measurement error when comparing time-to-event endpoints and lead to biased findings. Recent methods have been developed to mitigate measurement error bias in real-world endpoints; however, they rely on the existence of a validation sample, ie, data on a set of patients where both the “true” trial-like and “mis-measured” real-world measures are collected. We demonstrate how novel statistical methods can be leveraged as quantitative bias analyses (QBA) to contextualize real-world evidence findings when outcome measurement error is of concern, but validation samples are infeasible to collect. Quantitative bias analyses allow researchers to set plausible ranges for the amount of error when not directly measurable. We highlight how to conduct QBA with two recent methods, cumulative incidence curve correction and survival regression calibration, and illustrate how to generate plausible parameter values through simulation. We provide an illustrative QBA example in a cohort of real-world patients with newly diagnosed multiple myeloma and provide practical guidance to apply QBA for outcome measurement error and interpret results.

Abstract Background Relapsed medulloblastoma remains a significant therapeutic challenge as it is near universally fatal. The tumor microenvironment of medulloblastoma plays a critical role in tumor progression, influencing tumor growth, immune evasion, and therapeutic resistance. We hypothesized that defining tumor-immune interactions in diagnostic and relapsed medulloblastoma may uncover mechanisms of immune evasion and identify novel therapeutic targets. Methods We analyzed paired primary and recurrent RNA-sequencing data from 140 medulloblastoma patients to profile immune cell composition and validate spatial relationships within the TME. To identify key tumor-immune interactions, we developed a novel algorithm to detect receptor-ligand pairs using single-cell RNA-sequencing data. These interactions were validated across RNA and proteomic datasets. Their functional significance was empirically demonstrated in newly developed immunocompetent models of recurrent medulloblastoma that closely recapitulate the human disease. Results We observed a shift toward a heightened immunosuppressive TME at relapse. Using our algorithm, we identified biologically significant receptor-ligand interactions, most notably MIF-CD74, constitutively expressed at RNA and protein levels across medulloblastoma subgroups, at diagnosis and relapse. Disrupting MIF-CD74 interactions led to significant alterations in the tumor microenvironment, highlighting its functional significance. Conclusions Our multifaceted approach identified key tumor-immune interactions in medulloblastoma. Among these, MIF-CD74 was validated as a targetable interaction, demonstrating the utility of our integrative approach for identifying novel therapeutic targets across multiple tumor types.

Purpose. Spontaneous coronary artery dissection (SCAD) has emerged as an important cause of acute coronary syndrome predominantly affecting women. Although the knowledge of SCAD has expanded over the past 2 decades, limited evidence exists to guide post-event management and prevention of future adverse events. This review aims to synthesize the current understanding of SCAD and outline considerations for exercise prescription and cardiac rehabilitation (CR) in this unique population. Review Methods. A comprehensive literature review was conducted, incorporating original research articles, systematic reviews, meta-analyses, and current clinical guidelines related to SCAD and CR. Summary. Current literature demonstrates that CR is safe in this population and is associated with improvement in measures of physical and mental health. Expert consensus supports reintroduction of exercise and an individualized multidisciplinary CR framework.This review highlights current evidence and expert recommendations for the multidisciplinary outpatient management of patients with SCAD.

Abstract Healthcare personnel (HCP) are at risk for occupational exposure to tuberculosis. Current guidelines for managing exposed HCP are broad and resource intensive. Based on review of our internal data, we propose a risk-based stratification approach to streamline exposure follow-up testing and optimize resource utilization.

Abstract INTRODUCTION Associations of short‐term use of menopausal hormone therapy (mHT) with Alzheimer's disease (AD) and structural magnetic resonance imaging (MRI) biomarkers were investigated 10 years after an mHT trial. METHODS Recently menopausal women with good cardiovascular health were randomized to oral conjugated equine estrogens (oCEE) or transdermal 17β‐estradiol (tE2) and micronized progesterone, or placebo for 4 years. Amyloid beta (Aβ) on positron emission tomography, hippocampal atrophy, and dorsolateral prefrontal cortex thickness on MRI were assessed 10 years after completion of the mHT trial ( n = 266). RESULTS Aβ and structural MRI biomarkers were not different in the oCEE and tE2 groups compared to placebo. Apolipoprotein E ε4 status did not modify the findings. DISCUSSION There was no evidence of adverse effects or benefits associated with 4 years of use of oral or transdermal mHT on Aβ and structural MRI biomarkers in relatively healthy women, 10 years after mHT. Findings support the long‐term safety of short‐term use of mHT on brain health. CLINICAL TRIALS REGISTRATION NCT00154180 Kronos Early Estrogen Prevention Study (KEEPS) Highlights There were no menopausal hormone therapy–related adverse effects or benefits on amyloid beta and magnetic resonance imaging biomarkers in the long term. Apolipoprotein E ε4 carrier status did not modify these findings. Findings align with neutral cognitive and cerebrovascular outcomes in this cohort.

ABSTRACT Background Li Fraumeni syndrome (LFS) is a hereditary multi‐cancer syndrome caused by alterations in TP53 (MIM# 151623). Next generation sequencing (NGS) allows for the detection of TP53 variants at lower variant allele frequencies (VAFs). A TP53 variant with a VAF < 50% may represent mosaic LFS, aberrant clonal expansion (ACE), or possible circulating tumor DNA. Differentiation among these conditions is important for optimal patient management. Methods Genetic testing was performed using a custom gene panel, with an average read depth of 350× (range 166–553×). DNA extracted from four different tissues (blood, saliva, cultured skin fibroblasts, and colon) was sequenced. Results Here, we describe an adult female patient with a history of an adrenocortical neoplasm and osteosarcoma, diagnosed at 2 and 16 years of age, respectively. Testing of peripheral blood identified a pathogenic TP53 variant, c.733G>A, p.(Gly245Ser) (NM_000546.6); however, subsequent in vitro fertilization with preimplantation genetic testing for monogenic disorders (PGT‐M) did not identify this TP53 variant in any of nine embryos tested. Testing for possible mosaicism in the proband was performed on four different specimens, revealing variable VAFs of the TP53 variant (saliva: 44%; blood: 31%; cultured skin fibroblasts: 18%; and colon tissue: 9%). These results suggest a post‐zygotic event, consistent with mosaic LFS rather than ACE. Conclusion This case highlights the complexity of interpreting mosaic variants in the TP53 gene, and we propose a testing algorithm to aid in the delineation of this phenomenon when relaying cancer and reproductive risk information in the context of mosaicism.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts (RHIs), characterized by tau tangles around small blood vessels at the depths of the sulci. Currently, CTE can be diagnosed only postmortem , but can present with an array of cognitive, behavioral, mood, and motor symptoms. However, traumatic brain injury is also associated with increased risk of Alzheimer’s disease (AD) and may lead to comorbid neuropathology. Characterization of the in vivo biomarkers of CTE is a necessary next step to facilitate accurate diagnoses. We examined the profile of cerebrospinal fluid (CSF) biomarkers of amyloid-β, total tau (tTau), and phospho-tau (pTau) in a cohort of former professional (PRO, n = 100) and college (COL, n = 40) football players at high risk of CTE compared to asymptomatic unexposed controls (UE, n = 43). CSF was collected under controlled conditions using collection, processing, and cryostorage kits provided by the DIAGNOSE CTE Research Project Biomarker Core, and concentrations of Aβ 40 , Aβ 42 , tTau, and pTau (pTau 181 , pTau 217 , pTau 231 ) were measured at the University of Gothenburg, Sweden, using immunoassays. Associations between CSF biomarker levels with football history, and diagnosis of traumatic encephalopathy syndrome (TES) were examined using linear regression, and corrected for age, education, APOE -ε4 allele status, race, and body mass index. Our analysis revealed that football exposure affected both CSF Aβ 40 ( p = 0.039) and Aβ 42 ( p = 0.038), particularly among those under 60 years of age in the PRO compared to the UE exposure group. Among former football players, estimates of RHI exposure were not generally associated with CSF Aβ, tTau, and pTau biomarker levels. CSF Aβ 40 ( p = 0.0041) and Aβ 42 ( p = 0.011) were lower in former football players with TES diagnosis compared to unexposed participants, although CSF Aβ, tTau, and pTau biomarker levels did not differ between former players with and without a TES diagnosis. Among former football players, reduced CSF Aβ 40 ( p = 0.011) and Aβ 42 (p = 6e-04) were observed in those with cognitive impairment compared to those with neurobehavioral dysregulation. The findings of significant associations of reduced CSF Aβ levels with RHI in elite football players are in line with recent postmortem studies; however, the lack of relationship with CSF tTau and pTau species observed to be altered in the setting of AD suggests that the pathological features of CTE reflected in fluid biomarkers are complex and require further study. The overlapping comorbid age-dependent features of neurodegeneration that occur in those at risk for CTE suggest that tau pathology in CTE is not reliably reflected by currently available fluid biomarkers and that the use of multiple biomarkers related to the compound characteristics of CTE may be required for early detection.

Acute kidney injury (AKI) affects thousands of hospitalized patients annually, yet early detection remains challenging as serum creatinine elevation lags behind clinical deterioration. Decreased urine output (UO) represents a key diagnostic criterion of AKI, sometimes manifesting hours before biochemical changes; however, current manual monitoring methods are labor-intensive and prone to error. Here, we developed and validated a simple, cost-effective automated urine flow meter using non-contact optical sensors, a peristaltic pump, and microcontroller-based automation for precise, real-time monitoring of urine output in clinical settings, named P-meter. Three successive prototypes (V1, V2, V3) were validated against gold-standard gravimetric measurements over 285 h of testing during animal experiments that required bladder catheterization. Iterative refinement addressed miniaturization challenges, fluid dynamics optimization, and sensor positioning to achieve progressively improved accuracy. The optimized V3 prototype demonstrated further enhanced volumetric precision, stability, and flow accuracy with near-unity linearity vs. reference method (R2 = 0.9889), minimal bias (mean error −0.1 mL), and 94.18% agreement within confidence limits (n = 86), outperforming the initial V1 prototype (R2 = 0.9971, mean error −1.69 mL, n = 207) and intermediate V2 design (R2 = 0.9941, mean error 3.63 mL, n = 390), primarily in terms of reduced bias and improved agreement. The P-meter offers accurate urine output monitoring at a lower cost than commercial systems, facilitating its use in early AKI detection and thereby improving patient outcomes.