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Background: Valve-in-valve transcatheter aortic valve replacement (ViV-TAVR) is an increasingly preferred strategy for managing failed surgical bioprosthetic valves, especially in high-risk patients. However, limited data exist comparing outcomes between balloon-expandable (BE) and self-expandable (SE) transcatheter heart valves (THVs) in this setting. The influence of aortic annular area on outcomes by valve type remains poorly understood. This study evaluated the impact of annular area on clinical outcomes following ViV-TAVR with BE vs. SE valves. Methods: We conducted a retrospective, single-center analysis of 353 patients who underwent ViV-TAVR between 2012 and 2024. All had prior surgical bioprosthetic AVR and received either BE (n=267) or SE (n=86) valves. Preprocedural multidetector CT was used to quantify aortic annular area. Transthoracic echocardiography was performed before and after the procedure to assess transvalvular gradients and hemodynamics. The primary endpoint was all-cause mortality. Penalized spline regression was used to model the nonlinear relationship between annular area and mortality and assess interaction by valve type. Results: Median age was 79 (IQR: 72–83) in the BE group and 80 (IQR: 76–85) in the SE group (p=0.07). Female sex was more common in the SE group (32% vs. 22%, p=0.047). Median annular area was 374 mm2 (IQR: 316–440) for BE and 365 mm2 (IQR: 308–432) for SE (p=0.081). Preprocedural gradient and effective orifice area index were 36 mm Hg (IQR: 28–46) and 0.6 cm2/m2 (IQR: 0.5–0.9), respectively, with no significant differences. Median hospital stay was 2 vs. 3 days (p=0.68). Thirty-day mortality was low (1 per group, p=0.36). Median follow-up was 4.0 years (IQR: 1.6–6.4). One- and 5-year survival rates were 94.75% and 61.7%, respectively (p=0.20). Penalized spline analysis showed a nonlinear association between annular area and mortality. The hazard ratio for BE valves declined with increasing annular area and fell below SE valves beyond ~400 mm2. Conclusion: ViV-TAVR is a safe and effective treatment for failed surgical bioprostheses. Smaller annular areas were associated with higher mortality. Outcomes with BE valves improved in larger annuli, suggesting annular area could guide valve selection. Further studies are warranted to validate these observations.

Abstract Our understanding of Alzheimer's disease (AD) and related dementias (ADRD) has grown exponentially, thanks to significant investments by the National Institute on Aging (NIA). This article celebrates the 40th anniversary of the NIA's Alzheimer's Disease Research Centers, highlighting the pivotal role of neuropathology as the bedrock for neurodegeneration research. Neuropathology has championed the key principles of proteinopathy, selective vulnerability, and stereotypic spread. Furthermore, neuropathologic studies advanced our understanding of ADRD prevalence, heterogeneity, clinical–pathological correlations, and genetic underpinnings, spurring biomarker development for target engagement and disease monitoring. Disease‐modifying therapies for AD were inspired and informed by neuropathology. The neuropathology community is poised to refine diagnostics, leveraging digital pathology and integrating genetics and pathomics to enhance subtyping for novel precision medicine approaches. Despite some common misconceptions and logistical challenges, neuropathology continues to be a critical component of the ADRD research infrastructure, serving as a key bridge between allied basic and clinical sciences. Highlights We celebrate 40 years of NIA‐funded ADRCs and their contributions through neuropathology studies that have significantly advanced our understanding and treatment of ADRD. Neuropathology uncovers principles of neurodegenerative disease: proteinopathy, selective vulnerability, and stereotypic spread, informing diagnostics and therapies. Development of AD biomarkers with reference to neuropathology enhances accuracy in diagnosis and monitoring, paving the way for targeted disease‐modifying therapies. Integration of digital pathology, genetics, and novel tools in neurodegeneration research promises advanced precision medicine approaches and refined diagnostics. Misconceptions and logistical challenges to neuropathological research are addressed to improve understanding and collaboration.

Abstract eSource – particularly EHR-to-EDC – is an emerging paradigm in clinical research that enables automated transfer of electronic health record (EHR) data into electronic data capture (EDC) systems, with the potential to reduce site burden, improve data quality and accelerate oncology clinical trial workflows. However, widespread implementation remains limited due to technical, regulatory and operational barriers. To address these challenges, the European Institute for Innovation through Health Data (i~HD) launched the eSource Scale-Up Task Force in 2024. This multi-stakeholder initiative brings together leading oncology centres and pharmaceutical sponsors to establish a consensus-driven roadmap for eSource adoption. Central to this effort are three foundational resources: readiness criteria for early adopters, a performance indicator framework for monitoring success and an operational playbook to guide implementation. This article provides a structured overview of the Task Force’s objectives, collaborative model and outputs, with specific attention to its focus on interoperability, regulatory alignment and real-world validation. While initially developed for oncology, the Task Force’s framework is applicable across therapeutic areas characterized by data-intensive workflows.

Purpose: This study assesses intersurgeon variability in proptosis reduction after orbital decompression for thyroid eye disease. Methods: This multicenter retrospective study included patients with thyroid eye disease who underwent orbital decompression from 1 of 7 surgeons at 7 different institutions between January 2002 and December 2018. Data were included if a single decompression technique was performed on ≥10 patients by ≥2 surgeons. The primary outcome was postoperative change in proptosis with emphasis on comparison among surgeons utilizing similar surgical techniques. Statistical analysis was performed with χ 2 and ANOVA testing, and a multivariable logistic regression model was generated. Results: Six hundred thirty-three orbits that underwent orbital decompression were included. Five different decompression techniques were analyzed: medial wall (n = 29), fat + lateral wall (n = 113), medial wall + floor (n = 123), fat + lateral wall + medial wall (n = 140), and fat + lateral wall + medial wall + floor (n = 228), without significant difference in proptosis reduction among surgeons. Surgeons did not demonstrate significant differences in outcomes at different time points compared with each other or themselves. Outcomes when comparing endoscopic versus open medial wall decompression varied among surgery types. Multivariate modeling revealed a statistically significant association between postoperative change in proptosis with preoperative proptosis ( p < 0.001). Conclusions: Postoperative change in proptosis did not differ significantly between surgeons utilizing similar orbital decompression techniques for patients with thyroid eye disease. This study may strengthen the statistical validity of multicenter clinical trials assessing orbital decompression outcomes performed by surgeons employing uniform surgical techniques, thereby advancing our understanding of optimal surgical management strategies for thyroid eye disease.

Objectives Aircrew are subject to thermal stress and heat-related illness (HRI). Published screening methods and safety thresholds remain limited. The objective of this review was to evaluate the available evidence, approaches and guidelines regarding HRI screening tools in aircrew and analogue occupational and athletic cohorts to create a broad compendium of relevant tools for aviation safety decision-makers which establish risk stratification. Design A systematic literature review was conducted through 28 July 2025, of manuscripts and technical documents that reported HRI risk screening approaches. Pairs of independent reviewers selected studies and appraised risk of bias. Data sources Ovid MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews and Scopus were searched. Eligibility criteria Extrinsic and intrinsic factors checklists, protocols, diagrams, algorithms and screening approaches for HRI risk stratification and safety thresholds within occupational settings were included. Cohorts under 18 years of age and abstracts were excluded. Data extraction and synthesis 3472 reports were identified and 37 were included in the final analysis. Common approaches relied on wet bulb globe temperature (WBGT), workload assessment and personal protective equipment used. WBGT thresholds ranged 27–32°C for extreme risk and 23–31°C for high risk. Identified tools used 19 common domains to establish risk. Data were insufficient to identify a singular ideal screening approach. Conclusions This systematic review addresses knowledge gaps regarding occupational HRI risk screening protocols for use towards aviation workers. Limitations included lack of generalisability, risk definition variability and conflicting published author assumptions regarding intrinsic factors considered.

PURPOSE Recent studies reveal that 5%-18% of children with cancer harbor pathogenic variants in known cancer-predisposing genes. However, DNA damage repair (DDR) genes, which are frequently somatically altered in pediatric tumors, have not been systematically examined as a source of novel cancer-predisposing signals. METHODS To address this gap, we interrogated 189 DDR genes for presence of germline predisposing variants (PV) among 5,993 childhood cancer cases and 14,477 adult noncancer controls (discovery cohort). PV were determined using a tiered approach incorporating ClinVar annotations, InterVar classification, and in silico tools (REVEL, CADD, and MetaSVM). Using logistic and firth regression, we identified genes with PV statistically enriched in the germline of children with tumors and replicated findings among 1,497 additional childhood cancer cases across three independent cohorts. RESULTS Analysis across all cases with cancer revealed enrichment of TP53 PV. Cancer-specific analyses confirmed known associations including germline TP53 PV in adrenocortical carcinoma, high-grade glioma (HGG), and medulloblastoma (MB), PMS2 in HGG and non-Hodgkin lymphoma (NHL), MLH1 in HGG, BRCA2 in NHL, and BARD1 in neuroblastoma. In addition, four novel associations were uncovered, including BRCA1 in ependymoma, SPIDR in HGG, SMC5 in MB, and SMARCAL1 in osteosarcoma (OS). Importantly, the SMARCAL1 :OS association was significant in the discovery (6/230, 2.6%, false discovery rate [FDR] logistic = 0.0189) as well as all three replication cohorts (Childhood Cancer Survivor Study: 8/275, 2.9%; P Fisher < .0001; Cancer Predisposition Syndrome-German Childhood Cancer Registry: 4/135, 3%, P Fisher = .002; Individualized Therapy for Relapsed Malignancies in Childhood: 4/217, 1.8%, P Fisher = .012). The remaining wild-type SMARCAL1 allele was deleted in three of four OS tumors with available data. CONCLUSION Our study confirms the relevance DDR genetic variation in pediatric cancer risk and establishes SMARCAL1 as a novel OS predisposing gene, providing insights into tumor biology and creating opportunities to optimize care for patients with this challenging tumor.

Abstract Background Physical activity is associated with lower colorectal cancer (CRC) risk, but its association with molecular subtypes defined by genetic and epigenetic alterations of the disease is unclear. Such information may enhance the understanding of the mechanisms related to the benefits of physical activity. Methods Pooled observational (cases: n = 5386; controls: n = 6798; studies n = 5) and genome-wide association data (cases: n = 8178; controls: n = 10 472; studies n = 5) were used. We used multivariable logistic regression models and Mendelian randomization to assess the association between physical activity and the risk of CRC subtypes defined by individual tumor markers (and marker combinations), namely microsatellite instability status, CpG island methylator phenotype status, and BRAF and KRAS mutations. We used case-only analysis to test for differences between molecular subtypes. We applied Bonferroni correction to account for multiple tests. Results In the pooled observational analysis, higher levels of physical activity were associated with lower CRC risk (Obs-per 1SD, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.90 to 0.97), with an association that was stronger in males (Obs-per 1SD, OR = 0.91, 95% CI = 0.87 to 0.96) than in females (Obs-per 1SD, OR = 0.97, 95% CI = 0.91 to 1.03; Pinteraction = .04). Higher physical activity was associated with a lower risk of CRC across all molecular subtypes, especially in males. There was no difference in the associations by subtypes by pooled observational or Mendelian randomization analyses. The findings did not differ by study design, anatomical site, and early or late age onset of CRC. Conclusions Our findings suggest that physical activity is not differentially associated with the 4 major molecular subtypes involved in colorectal carcinogenesis, indicating that its benefits extend broadly across colorectal cancer pathogenesis.

Abstract Error analysis is a critical step in evaluating and improving clinical concept extraction models, the most common clinical natural language processing (NLP) task. Unlike corpus annotation, which follows standardized protocols for creating gold-standard datasets, error analysis requires nuanced judgment grounded in both clinical expertise and NLP knowledge. This is especially important given the heterogeneity of clinical text, where variations in documentation style, note structure, and terminology can substantially influence model behavior. Despite its importance, there is currently no standardized, user-level framework to support systematic error analysis in clinical concept extraction task. In this study, we developed and validated MedError, a machine-assisted, human-in-the-loop framework designed to standardize and enhance error analysis for clinical concept extraction tasks. We collected and manually curated a corpus of 1,187 unique errors from a total of 4,237 notes across three different distinct hospitals. The error categories were defined using our previously validated error taxonomy and included 480 false negatives and 707 false positives across 25 error types and 48 clinical concept categories. We evaluated the performance of three proprietary and three open-source large language models (LLMs) in automatically classifying these errors into 26 and 15 predefined categories. We further developed a machine-assisted framework, MedError, which integrates best practices in error analysis, LLM-assisted classification and reasoning, and a user-friendly interface to enable more efficient, reproducible, and context-aware error analysis. The framework supports both single-site and federated multisite error analysis, facilitating the effective translation of clinical NLP systems into real-world settings.

Abstract Objectives Neurofilament light (NfL) is an established biofluid marker of neuroaxonal injury for neurological diseases. Several high-throughput and sensitive immunoassays have been developed to quantify NfL in blood and cerebrospinal fluid (CSF), facilitating the use of NfL as a biomarker in research and clinical practice. However, because of the lack of rigorous comparisons of assays, it has been difficult to determine whether data are comparable and whether assay performance differs. Here, we compared the performance of five NfL immunoassays. Methods To assess the five NfL immunoassays (Fujirebio, ProteinSimple, Quanterix, Roche and Siemens), we used pooled plasma or pooled CSF, as well as unique samples from 20 healthy controls and 20 individuals with El Escorial defined probable or definite amyotrophic lateral sclerosis (ALS), to evaluate precision, parallelism and/or bias. We also examined correlations between plasma and CSF NfL concentrations within and across assays and evaluated their ability to differentiate healthy controls from individuals with ALS. Results Four of the five assays demonstrated exemplary performance based on our analyses of precision and parallelism. Across the five assays, NfL concentrations were lower in plasma than in CSF, although they displayed a high degree of correlation. We noted bias across assays; plasma NfL concentrations were lowest for the Roche assay and highest for the ProteinSimple assay. In addition, all assays reliably distinguished healthy controls from individuals with ALS using plasma or CSF NfL. Conclusions Four NfL assays demonstrated similar analytic performance. Alongside performance, other factors such as costs, accessibility, usability, footprint, and intended use, should be considered.

Abstract Background Physical activity (PA) is an established protective factor for colorectal cancer (CRC), but it is unclear if genetic variants modify this effect. To investigate this possibility, we conducted a genome-wide gene–PA interaction analysis. Methods Using logistic regression and two-step and joint tests, we analyzed interactions between common genetic variants across the genome and PA in relation to CRC risk. Self-reported PA levels were categorized as active (≥ 8.75 MET-h/wk) vs. inactive (< 8.75 MET-h/wk) and as study- and sex-specific quartiles of activity. Results PA had an overall protective effect on CRC (OR [active vs. inactive] = 0.85; 95%CI = 0.81–0.90). The two-step GxE method identified an interaction between rs4779584, an intergenic variant near the GREM1 and SCG5 genes, and PA for CRC risk (p-interaction = 2.6×10 − 8 ). Stratification by genotype at this locus showed a significant reduction in CRC risk by 20% in active vs. inactive participants with the CC genotype (OR = 0.80; 95%CI = 0.75–0.85), but no significant PA–CRC association among CT or TT carriers. When PA was modeled as quartiles, the 1-d.f. GxE test identified that rs56906466, an intergenic variant near the KCNG1 gene, modified the association between PA and CRC (p-interaction = 3.5×10 − 8 ). Stratification at this locus showed that increase in PA (highest vs. lowest quartile) was associated with a lower CRC risk solely among TT carriers (OR = 0.77; 95%CI = 0.72–0.82). Conclusions In summary, we identified two genetic variants that modified the association between PA and CRC risk. One of them, related to GREM1 and SCG5 , suggests that the bone morphogenetic protein (BMP)-related, inflammatory, and/or insulin signaling pathways may be associated with the protective influence of PA on colorectal carcinogenesis.