Citations

Background COVID‐19 and other respiratory viral infections can cause cardiovascular complications. SARS‐CoV‐2 virions are found in the blood, and circulating viral RNA levels are associated with death. We hypothesized that viremia can induce thrombotic endotheliopathy that contributes to death and studied this relationship in patients hospitalized for COVID‐19 and enrolled in the ACTIV‐4a (Accelerating COVID‐19 Therapeutic Interventions and Vaccines) randomized trial of antithrombotic therapy. Methods We quantified SARS‐CoV‐2 nucleocapsid RNA and protein in plasma and measured their associations with clinical outcomes and biomarkers of thromboinflammation and endotheliopathy. We used Cox regression and Fine–Gray competing risk models to analyze survival and thrombosis. We conducted causal mediation analysis to explore whether thrombotic endotheliopathy mediates the relationship between viral RNA and death. Results In 93 patients, SARS‐CoV‐2 RNA and N‐antigen were higher in nonsurvivors. Baseline viral RNA levels were associated with increased 90‐day death (hazard ratio [HR], 1.31 [95% CI, 1.17–1.46]) and thrombosis (HR, 1.35 [95% CI, 1.24–1.47]). Viral RNA more effectively predicted survivorship than N‐antigen levels. Soluble thrombomodulin, a biomarker of thrombotic endotheliopathy, positively correlated with viral RNA levels. Mediation analysis revealed that soluble thrombomodulin accounts for 12.2% (95% CI, 0.1%–32.3%; P =0.048) after adjustment for age and sex of the relationship between viral RNA and the 90‐day mortality rate. Conclusions Elevated plasma SARS‐CoV‐2 RNA levels are associated with death in ACTIV‐4a, which is causally mediated in part by soluble thrombomodulin. We propose that lung–blood viral dissemination is a potential mechanism for cardiovascular complications of respiratory viruses. Registration URL: https://www.clinicaltrials.gov ; Unique Identifier: NCT04505774.

Abstract Background and aims Rural communities have a high incidence of stroke driven by high prevalence of risk factors. We hypothesize that patient centric stroke prevention education can be delivered in rural communities. Methods High risk patients defined as Atherosclerotic Cardiovascular Disease (ASCVD) 10-year risk of ≥ 20% cardio-cerebrovascular events were identified through electronic medical records receiving primary care in Greenville and Lakeview (intervention sites) and Muskegon (control site) were included. Education material included lifestyle modification and stroke signs-symptoms information. Patients completed a pre-intervention survey, recieved standardized stroke education, and were assessed for knowledge retention through quarterly telephone follow-ups and completed a 12-month post-intervention survey. Total study cost is 130,000$ over 18 months. Results High ASCVD score was identified in 758 (Intervention) and 1128 (Control) patients. 70 intervention and 73 control patients were enrolled. Time spent consenting patients and delivering education is 5 minutes with additional 10-15 minutes at each 3-month follow-up call. 65 intervention patients completed 12 month follow up. Intervention vs. Control; Median: IQR: Age [74 (68-76) vs. 73(68-75) years; p=0.20]; Initial ASCVD [24.5 (22-30) vs. 28.6 (26-37); p<0.001], 12-month ASCVD [25(21-30) vs. 30(24-39); p=0.002). Post-intervention survey showed significant improvement in recognition of stroke risk factors (p<0.001) and stroke signs-symptoms (p<0.001). 49 (75%) patients adopted healthy lifestyle at 12-month follow up. Conclusions A primary stroke prevention cost-effective education program can be successfully implemented in a high-risk rural population, demonstrating improved stroke literacy and healthy lifestyle adoption. Conflict of interest

Background: Several special tests for detecting medial ulnar collateral ligament (MUCL) injuries of the elbow have been described, but data on the clinical utility of these tests are limited. Purpose: To determine the clinical utility of selected elbow special tests to detect MUCL injuries in an athletic population. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 84 consecutive patients with sports-related elbow pain underwent a standardized clinical examination. Overall, 6 special tests (moving valgus stress test, static valgus stress test, modified valgus stress test, milking maneuver, pronation flexion resistance test, and temple/cheek press test) were performed. Sensitivity, specificity, accuracy, positive/negative predictive value, and positive/negative likelihood ratio (LR+ and LR–, respectively) were calculated for individual tests and combinations of tests to detect MUCL injuries. Higher values for the LR+ and lower values for the LR– represent stronger clinical utility. Results: For detecting MUCL injuries, the moving valgus stress test resulted in the highest sensitivity (98%) and accuracy (93%) with the lowest LR– (2%). The milking maneuver had the highest LR+ (5.1) with the second highest sensitivity (77%) and accuracy (79%). The pronation flexion resistance test and the temple/cheek press test had the lowest LR+ (1.5 and 1.8, respectively) and highest LR– (94% and 95%, respectively) in addition to the lowest sensitivity (16% and 9%, respectively) and accuracy (33% and 30%, respectively). No combination of tests resulted in increased clinical utility. Conclusion: The moving valgus stress test and milking maneuver demonstrated acceptable clinical utility in which the moving valgus stress test was better for ruling out MUCL injuries and the milking maneuver was better at ruling in MUCL injuries. There was no added value when combining the 2 tests together or with other maneuvers.

ABSTRACT Objective To evaluate intracochlear electrocochleography (ECochG) amplitude parameters during cochlear implantation (CI) using a novel multi‐frequency ECochG algorithm. Methods A multi‐institutional, prospective cohort study was performed at 18 high‐volume CI centers. The inclusion criteria were adults with sensorineural hearing loss and audiometric thresholds of ≤ 90 dB hearing level at 500 Hz undergoing CI with Advanced Bionics (Valencia, CA) Ultra 3D devices between 2024 and 2025. ECochG recordings were performed with simultaneous multi‐frequency stimulation of four frequencies between 125 and 4000 Hz during cochlear implant insertion. Concurrent multi‐frequency recording allowed extraction of amplitude and phase of each frequency individually. Post hoc analysis was performed to determine the difference in the number of drop alarms between single‐ and multi‐frequency ECochG. An ECochG amplitude drop of 6 dB was defined as a drop alarm. Insertion track patterns were compared between single‐ and multi‐frequency ECochG. Results One hundred ninety‐five ears were included. Mean number of drop alarms for the single‐frequency algorithm was 1.72 (95% CI: 1.52, 1.92; median 1) compared to 0.42 (95% CI: 0.31, 0.53; median 0) for multi‐frequency; p < 0.001. The number of Type C patterns (rise in amplitude during insertion followed by a drop) decreased with the multi‐frequency ECochG algorithm compared to the single‐frequency ECochG algorithm. The number of Type D patterns (no‐response) decreased, indicating that multi‐frequency ECochG generated more responses across the cochlea than single‐frequency ECochG. Conclusions A novel multi‐frequency ECochG algorithm during CI is associated with fewer drop alarms and altered insertion track patterns, which may provide a more accurate assessment of the cochlear microenvironment. Level of Evidence 3.

Introduction/Objective: Immune checkpoint inhibitors (ICIs) have limited efficacy in prostate cancer. Radiation therapy (RT) combined with ICIs and PI3K inhibition may enhance anti-tumor immune activity. Methods: RT-induced cytosolic double-stranded DNA (dsDNA) was measured in human and mouse prostate cancer cell lines as the surrogate upstream marker consistent with cGAS–STING engagement. In a syngeneic mouse model for castration-resistant prostate cancer (Myc-CaP in FVB mice), triple therapies were studied: (1) anti-CTLA-4, anti-PD-1, and RT, and (2) PIM kinase inhibitor PIM447, anti-PD-1, and RT. Mass cytometry (CyTOF) was used to measure the tumor-immune profile. Results: The peak induction of cytosolic dsDNA was at an RT dose of 13 Gy. In the mouse model, triple therapy with anti-CTLA-4, anti-PD-1, and RT doubled the median survival compared to monotherapy (32 days vs 11 to 22 days, p<0.006). Triple therapy with the PIM kinase inhibitor PIM447, anti-PD-1, and RT nearly tripled the median survival compared to PIM447 monotherapy (82 days vs 29 days, p=0.002). Mass cytometry analysis revealed that the combination of anti-PD-1 and RT reduced myeloid-derived suppressor cells and tissue-associated macrophages and enhanced CD8+ T-cell infiltration. Discussion: Although prostate cancer is an immunocold entity, RT can trigger immune activation, consistent with engagement of the cGAS–STING signaling pathway (cytosolic dsDNA serving as a surrogate upstream marker). In triple therapy, RT can enhance the efficacy of ICI and PI3K-targeted drug therapy, significantly improving overall survival in a mouse model of CRPC. Conclusions: A combination of RT, ICIs, and PIM kinase inhibition may help overcome immune resistance in prostate cancer. This combination therapy approach supports further preclinical validation and careful clinical evaluation and warrants further clinical investigation to optimize treatment strategies for CRPC.

Abstract Neurosurgical and neuromodulation therapies such as deep brain stimulation (DBS) require millimeter-level accuracy to effectively target functional brain regions. Yet, many neuroanatomical boundaries remain invisible to current imaging and electrophysiology methods, limiting precision and contributing to suboptimal patient outcomes. Here, we introduce a self-supervised artificial intelligence (AI) framework that learns to delineate functional subregions directly from the spectral content of intraoperative local field potential (LFP) recordings, without the need for predefined biomarkers or anatomical labels. The framework identifies physiologic structure across the full spectrum of the signal and, through explainable AI (XAI), reveals the specific frequency components underlying these distinctions. Validated in the subthalamic nucleus (STN), the model aligned with clinically defined borders and rediscovered known beta oscillations. Applied to the motor thalamus in tremor patients, it consistently identified functional transitions corresponding to the ventral oralis posterior (Vop) and ventral intermediate (Vim) nuclei—regions where conventional methods fail to provide reliable boundaries. To assess clinical relevance, physiologically defined clusters were functionally evaluated using monopolar review data at their first DBS clinic postoperative visit, demonstrating distinct stimulation-response profiles across clusters and linking electrophysiologic segmentation to clinically meaningful programming outcomes. These findings demonstrate that intraoperative LFP recordings can be transformed into both a real-time guidance resource and a data-driven platform for biomarker discovery, establishing a foundation for more precise, individualized neuromodulation therapies and advancing our understanding of functional brain organization.

Abstract The intestinal epithelium harbors a large population of microbiota-dependent CD8αβ + T cells whose antigen specificity and regulation are ill-defined. By identifying MHCIa-restricted TCRs and generating tetramers against the gut commensal Segmented Filamentous Bacteria, we demonstrate that a single commensal species drives a clonally expanded, antigen-specific CD8αβ + T cell within the intraepithelial lymphocyte compartment. Mechanistically, the intestinal epithelium coordinates coincident signals governing this population: peptide:MHC-dependent TCR engagement drives pIEL accumulation, while αvβ6-mediated TGFβ activation restraints effector cell differentiation. Perturbation of epithelial cell-mediated TGFβ activation diverts commensal-specific CD8 + T cells toward inflammatory differentiation states transcriptionally convergent with those observed in ulcerative colitis. The intestinal epithelium thus functions as a dual-signal organizer of commensal-specific CD8 + T cell responses, coupling differentiation to restraint through spatially coincident molecular cues.

Abstract Glioblastoma (GBM), isocitrate dehydrogenase wild-type (IDHwt) and central nervous system diffuse large B-cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. Deep learning on T1 postcontrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study design was utilized. Model development was performed on 146 patients with CNS-DLBCL and 146 age-matched, sex-matched, and MRI year–matched patients with GBM diagnosed at Mayo Clinic between 1998 and 2019. Models were tested on independent temporal test cohorts. Initial testing included 240 independent GBM diagnosed at Mayo Clinic between 1998 and 2019. The prospective test cohort included 37 patients with CNS-DLBCL and 256 patients with GBM diagnosed at Mayo Clinic after January 1, 2020, and 36 patients with CNS-DLBCL diagnosed at an external institution. Of the patients diagnosed at Mayo Clinic, 47% had MRIs generated from non-Mayo institutions. Two different model approaches were compared: (i) ensemble approach using area under the receiver operating characteristic curve (AUC) and cross-validation for model selection and (ii) loss approach minimizing cross-entropy loss and cross-validation to evaluate prediction performance. The AUCs on the prospective test cohort were 0.84 [95% confidence interval (CI), 0.78–0.90] and 0.83 (95% CI, 0.77–0.88) for the ensemble and loss approaches, respectively. Stability of ensemble prediction improved with the increasing number of models. Stratified AUC analysis demonstrated consistent performance across sex and age. We utilized a robust temporal study design and applied 2 different analytic approaches to develop a classification model. The findings confirm the feasibility of using MRI-based deep learning models to differentiate GBM from CNS-DLBCL. Significance: GBM, IDHwt and CNS-DLBCL are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. We developed MRI-based deep learning models to differentiate GBM, IDHwt from CNS-DLBCL using a rigorous three-stage temporal design that included prospective validation. The model AUC on a prospective cohort was 0.84.

Abstract Background Postoperative spinal implant infections (PSIIs) are a serious complication of instrumented spinal fusion. Although debridement with implant retention is standard for early infection, the optimal duration of antimicrobial therapy remains uncertain. Methods We conducted a multicenter retrospective cohort study across 10 US academic centers, including adults with early PSII (≤90 days after fusion surgery) from 2017 to 2021. We excluded patients who experienced treatment failure within 6 weeks of debridement. The primary outcome was treatment failure. Antibiotic therapy effect was analyzed as a time-varying exposure using adjusted Cox proportional hazards models. Secondary analyses included 12-week landmark and clone-censor-weighted models to compare durations ≤ 12 weeks versus &gt;12 weeks. Results A total of 116 patients out of 499 (23.2%) experienced treatment failure during a median follow-up of 3.2 years. Among patients who remain failure-free 6 weeks from debridement, being on antibiotics was not associated with treatment failure (adjusted hazard ratio [aHR] 0.71; 95% CI .48–1.07; P = .10). In a 12-week landmark analysis limited to 359 patients who were not on indefinite suppressive antibiotic therapy, treatment durations &gt; 12 weeks did not significantly reduce the risk of failure (aHR 1.01; 95% CI .62–1.64; P = .99). Results were consistent in the clone-censor-weight sensitivity analysis (aHR 0.85; 95% CI .62–1.16; P = .30). Conclusions Prolonged antibiotic therapy was not associated with improved outcomes in early PSII managed with debridement and implant retention. These results support shorter, individualized antibiotic courses in patients with adequate surgical source control.

Background: Mindfulness-based interventions may improve cardiovascular health (CVH) by supporting behavioral change across multiple risk factors. This study evaluated the impact of Mindfulness-Based Blood Pressure Reduction (MB-BP), a mindfulness program targeting hypertension-related behaviors ( Image 1 ), on CVH using the American Heart Association’s Life’s Essential 8 framework. Methods: This secondary analysis of parallel-group, phase 2 randomized clinical trial evaluated the effects of MB-BP on CVH in 201 participants with elevated office BP (≥120/80 mmHg). The MB-BP group (n=101) received an 8-week program focused on mindfulness training and education targeting diet, physical activity, medication adherence, alcohol use, and stress, whereas the control group (n=100) received enhanced usual care ( Image 2 ). CVH was assessed using available Life’s Essential 8 components: systolic blood pressure, body mass index (BMI), diet (DASH adherence), physical activity, smoking, and sleep duration. Generalized estimating equations evaluated intervention effects through six months. Results: At six months follow-up, MB-BP participants significantly improved composite CVH scores compared to controls (standardized mean difference: 0.144; 95% CI: 0.023, 0.266) ( Image 3 ). MB-BP influenced most CVH components in healthier directions at trend levels, with the strongest responses for physical activity (47.9 MET min/week; 95% CI: -16.5, 112.3), sleep (0.34 hours/night; 95% CI: -0.10, 0.78), systolic blood pressure (-4.95 mmHg; 95% CI: -10.34, 0.44) and DASH diet score (0.27, 95% CI: -0.15, 0.69). Conclusions: MB-BP led to modest but clinically significant improvements in CVH, driven by multiple Life’s Essential 8 components. These findings suggest that MB-BP may be an effective behavioral intervention to support CVH and reduce risk for cardiovascular disease. ClinicalTrials.gov Preregistration Identifiers: NCT03256890, NCT03859076