Citations

Abstract Concerns about declining gray fox (Urocyon cinereoargenteus) populations in the Midwest, United States, prompted a petition to list the prairie gray fox subspecies (Urocyon cinereoargenteus ocythous) under the US Endangered Species Act. Although previous studies identified a deep phylogenetic break between eastern and western lineages of the gray fox at the Great Plains Suture Zone, population structure within the Midwest remains poorly understood, complicating subspecies classification. To address this, we genotyped 339 individuals from the eastern lineage of the gray fox using single nucleotide polymorphisms (SNPs) generated from 2bRAD genomic sequencing to assess genetic diversity and structure. Bayesian clustering and principal component analysis supported three genetic clusters (K = 3), revealing a cryptic break within Missouri that subdivides the morphologically defined range of U. c. ocythous and a secondary break coinciding with the Mississippi River and the currently accepted subspecies boundary. However, low pairwise FST values and admixture indicate weak overall genetic differentiation with ongoing gene flow, whereas declining genetic diversity at northern latitudes is reflective of founder effects from post-glacial population expansion. Consistent with prior mitochondrial DNA (mtDNA) results, nuclear SNP data suggest that U. c. ocythous and Urocyon cinereoargenteus cinereoargenteus are unlikely to represent distinct evolutionary units. However, because 2bRAD detects primarily neutral variation, whole-genome sequencing will be needed to test for adaptive divergence that might persist despite gene flow. Our findings provide an important step toward a comprehensive understanding of population structure and refining subspecies boundaries within the eastern lineage of the gray fox.

Background: Noninvasive tests are well validated in metabolic dysfunction–associated steatotic liver disease, but evidence in metabolic dysfunction and alcohol-associated liver disease (MetALD) and alcohol-associated liver disease (ALD) is limited. We evaluated noninvasive test–based clinical care pathways for fibrosis risk stratification in MetALD and ALD. Methods: This is a multinational, multicenter, cross-sectional study across 35 centers in 16 countries (2013–2025), including adults with MetALD or ALD. Fibrosis was assessed by liver biopsy and/or vibration-controlled transient elastography (VCTE). In biopsy-proven participants, we analyzed the sequential pathway (Fibrosis-4 [FIB-4] first, followed by VCTE for indeterminate FIB-4) to identify advanced fibrosis (≥F3). Diagnostic accuracy was assessed using the AUC. Results: Among 893 participants (41.3% MetALD and 58.7% ALD), the median age was 52 [43.0–61.0] years, and 79.4% were male. The estimated prevalence of advanced fibrosis was 45% (32.2% in MetALD and 54.0% in ALD). Participants with MetALD had a more dysmetabolic profile but lower fibrosis stages than ALD. Among biopsy-proven participants, FIB-4 AUC was 0.720, and VCTE AUC was 0.833. FIB-4 performed better in MetALD than ALD (AUC 0.773 vs. 0.540), while VCTE accuracy was similar across groups. In the sequential pathways, the false-negative rate for advanced fibrosis (misclassified as low risk) was 6.8% (4.9% MetALD and 11.3% ALD). Conclusions: In biopsy-proven patients, FIB-4 performance was acceptable in MetALD but substantially weaker in ALD. The standard 2-step pathway performed adequately in MetALD but missed a clinically meaningful proportion of advanced fibrosis in ALD.

Abstract Polygenic risk scores (PRSs), which quantify inherited susceptibility to complex traits and diseases, have emerged as valuable tools for risk stratification and precision medicine. Despite their promise, PRS developed on European cohorts often demonstrate substantially reduced predictive accuracy in non-European populations, due to differences in genetic architecture. The disproportionate representation of European ancestry cohorts in genome-wide association studies (GWAS) leads to inequitable deployment of PRS technologies across diverse populations. Here, we introduce PRANA (Polygenic Risk Adaptation via Neural-network Architecture), a deep learning framework that adapts an existing PRS developed on one population to other ancestries. Unlike methods that require large-scale GWAS in the target population, PRANA leverages pre-trained PRS models derived from European cohorts and adapts them using modestly sized cohorts from the target population. We evaluated PRANA on seven complex traits in South Asian, East Asian and Ashkenazi Jewish populations, as well as in selected smaller East Asian subpopulations where the scarcity of training data poses a particular challenge. PRANA mostly improved predictive performance of the baseline PRS models by 5%-20% in terms of effect size (β) and Nagelkerke’s R², and, in most cases, outperformed existing cross-ancestry multi-PRS approaches. These results highlight PRANA as a scalable and practical strategy to reduce disparities in genomic risk prediction and advance the equitable application of PRS in diverse populations.

Abstract Severe neuropathies with predominant involvement of motor fibres can resemble lower motor neuron disease (LMND) phenotypes. Given the fatal prognosis of LMND, identifying underlying autoimmune syndromes is crucial to provide treatment options to patients. We investigated a novel autoantibody binding pattern observed on murine teased sciatic nerve fibres. Target antigens were identified using immunoprecipitation combined with mass spectrometry. Target specificity of these autoantibodies was validated in cell-based assays, neutralization assays and knock-out models. A retrospective study cohort consisting of different neuropathies (chronic inflammatory demyelinating polyradiculopathy n = 86, Guillain–Barré syndrome n = 37, multifocal motor neuropathy n = 18, diabetic neuropathy n = 30, other inflammatory neuropathies n = 10), amyotrophic lateral sclerosis (n = 50), multiple sclerosis (n = 50) and healthy controls (n = 50) was negative for septin multimer autoantibodies. Histopathological analysis of skin and the sural nerve including electron microscopy was performed in one seropositive patient, and autoantibody binding was characterized in vitro. Extensive immunotherapy was initiated in one patient, with clinical and serological follow-up over 4 years. Among 3543 total samples tested, three patients (two male, one female)—diagnosed with the LMND variant of amyotrophic lateral sclerosis (aged 65, 72 and 79 years, respectively)—showed a novel and distinct autoantibody binding pattern of indirect immunofluorescence staining on peripheral nerves, targeting Schmidt–Lanterman incisures (SLIs), paranodes and the abaxonal myelin. Target identification and validation revealed septin multimers as autoantibody epitopes. Despite the primarily intracellular location of septins, autoantibody binding was evident in living myelinated dorsal root ganglia, primarily at SLIs (‘incisuropathy’). Septin multimer autoantibodies further initiated complement deposition on fixed and permeabilized cell-based assays. Sural nerve and skin biopsies showed inflammation, myelin and axonal pathology. Extensive immunotherapy in one patient was followed by disease stabilization over 3 years. The other two patients died of rapid disease progression: one of them received no immunotherapy while the other had ineffective treatments with single administrations of intravenous immunoglobulin and rituximab. Our data suggest that septin multimer autoimmunity occurs in severe motor-predominant neuropathies which can clinically resemble a neurodegenerative LMND. Screening for septin multimer autoantibodies should be considered in patients presenting with this phenotype. Follow-up studies need to determine the direct pathogenicity of septin multimer autoantibodies, their potential as a biomarker of an autoimmune syndrome and responses to immunotherapy in larger cohorts.

8519 Background: Non-classical mutations (NCM) of epidermal growth factor receptor (EGFR) represent a broad group of oncogenic mutations in non-small cell lung cancer (NSCLC), often associated with resistance to osimertinib (e.g., P-loop and αC-helix compressing [PACC] mutations). Patients (pts) with NCM have inferior clinical outcomes with a high incidence of CNS metastases (CNSm). Silevertinib (BDTX-1535) is a fourth-generation, covalent EGFR TKI with high CNS penetrance targeting both EGFR classical mutations and NCM. The antitumor activity and safety of silevertinib in pts with advanced NSCLC were evaluated in a Phase 2 trial (NCT05256290). Methods: Pts with advanced EGFR NCM NSCLC who received no prior systemic therapy were enrolled (Cohort 3) based on a local molecular test. Silevertinib 200 mg was administered orally once daily. The primary endpoint of objective response rate (ORR) was assessed using RECIST v1.1. CNS ORR was assessed using Response Assessment in Neuro-Oncology for Brain Metastases (RANO-BM) in pts with no prior CNS therapy. Secondary endpoints include progression-free survival (PFS), duration of response (DOR), disease control rate (DCR), and safety. Results: From February 2024 to July 2025, 43 pts with 35 unique NCMs (including 25 pts with PACC mutations) were enrolled in Cohort 3: median age 70.0 years, 72% female, 74% white, and 42% never smoked cigarettes. As of November 3, 2025, median follow-up was 7.2 months. ORR by RECIST v1.1 is shown in the table. Sixteen pts (37%) had CNSm, including 7 pts (16%) with measurable CNS disease. RANO-BM CNS response was 86% (n=6/7). Complete clearance of EGFR VAF ctDNA was observed in 21/26 (81%) evaluable pts. Serious treatment-related adverse events (TRAEs) were reported in 5 pts (12%), and 4 pts (9%) discontinued treatment due to TRAEs. The most common TRAEs included rash (19%, grade 3), diarrhea (19%, grade 3), stomatitis (9%, grade 3), and paronychia (5%, grade 3). While 77% of pts had a dose reduction, 19/22 (86%) patients with a radiographic response maintained or deepened their response after dose reduction, including all patients with CNS response. Conclusions: Silevertinib demonstrated robust antitumor activity in treatment-naïve pts with a broad spectrum of NCM EGFR driver mutations with high intracranial activity in pts with brain metastases. The safety profile was consistent with the known AEs of the EGFR TKI class. Clinical trial information: NCT05256290 . Data as of November 3, 2025 N ORR n (%) 95% CI DCR n (%) 95% CI ITT Population * 43 26 (60) (44.4, 75.0) 39 (91) (77.9, 97.4) PACC mutations 25 14 (56) (34.9, 75.6) 22 (88) (68.8, 97.5) Compound mutations † 16 11 (69) (41.3, 89.0) 15 (94) (69.8, 99.8) *No pts with classical (E746_A750del or L858R) mutations were enrolled. † Presence of ≥ 2 NCMs. As of December 27, 2025, the 6-month PFS rate was 86% overall and 80% in pts with CNSm; available PFS and DOR data will be presented.

Lactococcosis has emerged as an economically and ecologically significant disease in aquatic animals worldwide. This study employed multilocus sequence typing (MLST) to investigate the genetic diversity of Lactococcus spp. strains from Brazilian fish species and evaluate their phylogenetic relationships with global isolates to elucidate potential epidemiological connections involving multiple host species and distinct geographic regions. A total of 55 isolates from different laboratories had their DNA extracted, followed by the amplification and sequencing of the internal fragments of seven housekeeping genes (als, atpA, tuf, gapC, gyrB, rpoC and galP). Sequence types (STs) and clonal complexes (CCs) were defined. An unrooted neighbor-joining phylogenetic tree was generated using allele profiles from this study and those previously reported from other aquatic animal species. The isolates comprised 29 STs (11 previously reported, 18 novel ones), which were grouped into species-specific CCs: CC5 (L. formosensis); CC4, CC17, CC62 (L. garvieae); CC24, CC29, CC97 (L. petauri). Considerable genetic divergence was observed, with L. formosensis and L. garvieae forming heterogeneous populations, while L. petauri was more homogeneous. These findings describe the MLST structure of the sampled isolates and should be interpreted as hypothesis-generating rather than population-level estimates of genotype prevalence. Phylogenetics confirmed groupings within the CCs and revealed additional phylogenetic clustering patterns. In conclusion, the Brazilian Lactococcus spp. strains analyzed in this study constitute a genetically diverse population based on their STs. MLST and phylogenetic analysis demonstrated genetic relatedness between the L. garvieae and L. formosensis isolates from this study and those from other aquatic animal species. In contrast, all the STs identified for L. petauri in this study were unrelated to the MLST lineages responsible for outbreaks in Brazilian Nile tilapia (Oreochromis niloticus) and North American rainbow trout (Oncorhynchus mykiss). This suggests that piscine L. petauri populations in the Americas evolved from distinct ancestral origins.

Abstract Background and aims Reversible cerebral vasoconstriction syndrome (RCVS) is characterized by recurrent thunderclap headaches and reversible multifocal cerebral arterial narrowing. Although prognosis is generally favorable, a subset of patients develops cerebrovascular complications that may drive long-term disability; this study aims to identify factors associated with these complications. Methods We retrospectively reviewed 348 patients with probable or definite RCVS evaluated at Mayo Clinic between 2010-2023. Diagnostic criteria were adapted from RCVS2 and ICHD-3. The primary outcome was a composite of ischemic stroke, non-aneurysmal subarachnoid hemorrhage, and intracerebral hemorrhage; secondary outcome was poor functional status (modified Rankin Scale ≥2 within one year). Univariable and multivariable logistic regression identified predictors of these outcomes. Results Cerebrovascular complications occurred in 37.6% of patients and were the strongest determinant of poor functional outcome (aOR 5.05, 95% CI 2.04–12.51). On multivariable analysis, older age (aOR per year 1.02, 95% CI 1.00–1.04) and angiographically visible vasoconstriction (aOR 3.14, 95% CI 1.85–5.33) were independently associated with higher risk of cerebrovascular complications, whereas male sex (aOR 0.55, 95% CI 0.30–0.99), thunderclap headache at presentation (aOR 0.30, 95% CI 0.11–0.86), and sexual activity as a trigger (aOR 0.19, 95% CI 0.08–0.42) were associated with lower risk of these complications. Conclusions Cerebrovascular complications are common and strongly predict disability. Angiographic vasoconstriction and older age identify patients at higher risk, whereas thunderclap headache and sexual activity as a trigger mark a more benign phenotype. These findings may guide early risk stratification and help tailored monitoring strategies. Conflict of interest Name of author: nothing to disclose.

INTRODUCTION: Nosocomial infections (NIs) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have failed to identify high-risk patients. We aimed to develop machine learning (ML) models to predict NI. METHODS: The CLEARED consortium consists of prospectively enrolled cirrhosis inpatients from >120 centers. Using day-of-admission clinical data, 3 ML approaches (random forest [RF], extreme gradient boosting, and neural networks [NNs]) were used to predict NI. Data were split 80:20 for training and testing stratified by the outcome. Models were compared using area under the receiver operating characteristic curve (AUC). RESULTS: In total, 8,263 patients (55.90 ± 13.34 years; 64.1% men) from 127 centers in 37 countries were included. NI developed in 869 (10.5%), a median of 6 (4–11) days of postadmission. Major NIs were respiratory (29.6%) and urinary tract infection (15.7%), and spontaneous bacterial peritonitis (13.5%). NIs occurred more frequently in patients from low/low-middle income countries and those with severe liver disease, alcohol etiology, and admission infections. NIs were associated with inpatient mortality (31.9% vs 8.1%, P < 0.001) and liver transplantation (4.8% vs 1.9%, P < 0.001). Although the RF model (AUC 0.69) showed good calibration (Brier score 0.09), outperforming extreme gradient boosting, neural network, and LR models (AUC 0.66 for all; LR comparison P = 0.043), no model achieved AUC ≥0.80 for clinical utility. At 10% predicted probability threshold, the RF model demonstrated only 75.4% sensitivity, 52.9% specificity, and 15.9% positive predictive value (PPV). DISCUSSION: NIs cannot be accurately predicted from day-of-admission data using ML models, even in a large, prospective, global cirrhosis cohort. Every hospitalized patient with cirrhosis should receive protocolized infection control measures.

Abstract Introduction: Pathological complete response (pCR) is a strong prognostic marker, but survival outcomes comparing treatment to control do not reliably align with treatment-control differences in pCR rates in breast cancer. A novel Bayesian hierarchical framework models treatments within trials, allowing us to predict treatment effects on distant recurrence-free survival (DRFS) from pCR with greater accuracy. Methods: We analyzed 12 neoadjuvant breast cancer trials (6,000 patients, all HR/HER2 subtypes; including I-SPY2). The framework of Burzykowski, Molenberghs & Buyse (2005) is extended to a novel arm-based hierarchical structure providing a distribution of pCR and DRFS treatment effects controlling for subtype (HR/HER2), N and T stage, grade, and calendar year. Three held-out trials (877 patients; 26 regimens; med follow-up &gt;4 years) validate predictions of DRFS treatment benefit from pCR. All data was used to estimate treatment-effect correlation and the surrogate threshold effect (STE). Analyses were repeated for Residual Cancer Burden Index (binary RCB01, continuous RCB). Results: Predicted probability of DRFS benefit closely matched actual DRFS follow-up (mean absolute error 0.06; Pearson r = 0.9). Across all trials, pCR showed moderate surrogacy (ρ = 0.82, R2 = 0.67). A 60% increase in pCR odds achieves ≥95% probability of DRFS benefit (STE = OR of 1.60). RCB outperforms pCR across all metrics, with 92% sensitivity and 93% specificity for detecting DRFS benefit in 26 validation regimens (Table 1). Conclusion: This novel Bayesian meta-analytic framework reveals that pCR, RCB01 and continuous RCB reliably predict survival benefit across heterogeneous trials, with RCB performing the best in an external validation. This provides a statistical foundation for accelerated approval decisions using robust early biomarkers in modern neoadjuvant trial designs by accurately predicting survival at the treatment arm level. Citation Format: Keli S. Santos-Parker, Jessica R. Santos-Parker, W. Fraser Symmans, Laura J. Esserman, Christina Yau, Angie DeMichele, Laura van't Veer, Doug Yee, Fabien Reyal, Helena Earl, Jean Abraham, David Cameron, Peter Hall, Judy Boughey, Matthew Goetz, Gabe Sonke, Miguel Martín, Sara López-Tarruella, Priyanka Sharma, Rachel Freiberg, Jane Perlmutter, Aditya Bardia, Martin Eklund, Rachel Freiberg, Lajos Pusztai. A novel statistical framework for surrogate endpoint prediction of survival in neoadjuvant breast cancer trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1401.

Abstract Background Automated phlebotomy has the potential to improve patient outcomes and address phlebotomist workforce challenges. The Autonomous Blood Drawing Optimization and Performance Testing trial (ADOPT, ClinicalTrials.gov NCT05878483) assesses performance, safety, and patient experience of an autonomous robotic phlebotomy device (ARPD) that utilizes multimodal imaging. Methods Patients were recruited from outpatient phlebotomy departments in the Netherlands. In cohort 1, analytical equivalence was assessed by comparing within-subject test results from ARPD-collected and manually collected samples using Passing–Bablok regression analysis. In cohort 2, the ARPD was assessed in routine use. The primary performance endpoint was first-stick success rate; the primary safety endpoint was the rate of adverse events. Exploratory endpoints assessed pain and patient preference. Results One hundred fifty-three patients were enrolled in cohort 1. No statistically significant differences were observed in activated partial thromboplastin time, prothrombin time, lactate dehydrogenase, aspartate transaminase, or platelet count, indicating analytical equivalence. A total of 1633 patients were enrolled in cohort 2. The overall first-stick success rate, in patients where the ARPD could identify a suitable vein, was 94.5% (95% CI, 93.3–95.5) and remained high in patients with difficult venous access (92.7%), obesity (97.4%), and age ≥65 years (93.4%). Adverse events, all mild, occurred at a rate of 0.6%. Ninety percent of patients reported far less (19%), less (32%), or similar pain (39%) compared with manual phlebotomy. Eighty-two percent indicated they would strongly prefer (16%) or prefer (31%) use of the ARPD in the future or had no preference (35%). Conclusions Automated phlebotomy using the ARPD shows a favorable performance and safety profile and may improve patient experience. ClinicalTrials.gov Registration Number: NCT05878483