Citations

Abstract Histones variant composition and post-translational modifications (PTMs) of core and linker histones jointly orchestrate chromatin architecture and tissue-specific gene regulation. However, capturing the full complexity of the “histone code” in native human tissues remains challenging. Here we present a human cardiac histone proteoform atlas—comprising intact histone variants with combinatorial PTMs—enabled by a streamlined top‑down proteomics workflow. In a single one‑dimensional reversed‑phase liquid chromatography (LC)-mass spectrometry (MS) run, we achieve baseline separation of all four core histone families (H2A, H2B, H3, and H4) together with the linker histone H1 directly from human myocardium. Notably, this intact-protein analysis preserves the connectivity of co-occurring PTMs to individual histone molecules to reveal the combinatorial histone code, enabling proteoform‑level quantification of histone‑variant composition and PTM stoichiometry at the chromatographic scale. Targeted MS/MS directly resolves co-occurring PTM combinations and distinguishes highly homologous histone isoforms. Using this approach, we assemble the first comprehensive cardiac histone proteoform atlas and uncover previously unobserved histone proteoforms. More broadly, this top-down proteomics workflow provides a robust framework for proteoform-resolved analysis of histone variants and PTMs in complex biological systems.

INTRODUCTION: The American College of Gastroenterology assembled a multidisciplinary task force to evaluate the current state and future direction of artificial intelligence (AI) in gastroenterology, hepatology, and endoscopy leading to the development of consensus-based recommendations for responsible AI integration in clinical practice. METHODS: A total of 32 subject-matter experts and 12 industry partners, representing diverse practice settings and expertise, conducted subgroup literature reviews across 5 key areas (endoscopy, practice management clinical applications, training and education, inflammatory bowel disease and liver disease, ethics and equity). Draft statements were developed and rated on a 5-point Likert scale using a modified Delphi process. A consensus was set at ≥70% combined agreement. Nonconsensus items were revised and revoted electronically. RESULTS: A total of 43 statements, 40 (93%) reached consensus in round 1 and the remaining 3 achieved consensus after round 2. Evidence supports computer-aided detection improving adenoma detection rate and miss rate in controlled studies, with mixed real-world impact and insufficient long-term outcomes (e.g., interval colon cancer rate). Recommendations emphasize thorough validation and reduction of bias by heterogeneous Data sets. Outside endoscopy, ambient AI scribes, natural language processing (NLP)-enabled coding, workflow optimization, and previous authorization support show potential. Training recommendations endorse a structured AI curriculum while preserving independent procedural competence to avoid deskilling. In inflammatory bowel disease and hepatology, AI could help improve diagnostic accuracy, help predict risk of disease progression, and help guide therapy. Equity, governance, and reimbursement statements call for chain-of-custody data protections, specialty-society oversight, and payment models that reward quality and cost reduction. DISCUSSION: This consensus outlines how AI can augment rather than replace clinical expertise while promoting safety, transparency, interoperability, and equity. Priorities include pragmatic and prospective trials, multi-institutional data-sharing consortia, bias mitigation, and workforce training to enable trustworthy and clinically impactful AI adoption in gastroenterology, liver, and endoscopy care.

INTRODUCTION: High-quality colonoscopy requires accurate risk stratification for surveillance per the 2020 US Multi-Society Task Force guidelines and adherence to 2024 American College of Gastroenterology/American Society for Gastrointestinal Endoscopy quality benchmarks. Both are operationally challenging in clinical practice. We developed and validated Colon-Pilot, a large language model—powered clinical decision support system using GPT-4o to automate and standardize both functions. METHODS: The system was evaluated in 2 operational modes: (i) a human-in-the-loop clinical decision support validation of surveillance recommendations for 596 colonoscopies, comparing concordance with 2020 US Multi-Society Task Force guidelines against expert consensus, and (ii) an automated administrative audit applying Colon-Pilot to 42,632 colonoscopies across the Mayo Clinic Health System to calculate 2024 American College of Gastroenterology/American Society for Gastrointestinal Endoscopy priority quality indicators. Recommendations were autogenerated unless predefined safety criteria triggered manual review. RESULTS: Colon-Pilot issued recommendations for 522 of 596 cases (87.6%) and flagged 12.4% for manual review. For automated cases, guideline-concordant accuracy was 97.5% (Cohen κ = 0.970) versus 69.7% (κ = 0.781) for original endoscopist recommendations. Discordant artificial intelligence (AI) cases (n = 13) most often recommended longer-than-appropriate intervals (62%). Applied to the enterprise data set, Colon-Pilot calculated performance exceeding 2024 targets: adenoma detection rate 49.8% (≥35%), sessile serrated lesion detection rate 17.7% (≥6%), bowel preparation adequacy 91.8% (≥90%), and cecal intubation rate 97.4% (≥95%). DISCUSSION: Colon-Pilot demonstrated high fidelity in applying surveillance guidelines and automated quality benchmarking, outperforming unassisted endoscopists in guideline adherence. By combining safety protocols with large-scale automated reporting, it offers a scalable solution for improving both efficiency and quality in colorectal cancer prevention.

BACKGROUND AND OBJECTIVES: En bloc spondylectomies are essential for controlling malignant spinal tumors, but existing classification systems are often complex and impractical. This study introduces the Column, Line-of-Sight, Margins, Ring (CLiMR) framework, a novel system simplifying and standardizing en bloc spondylectomy planning and classification. METHODS: A retrospective review of patients who underwent single- or multistage en bloc spinal tumor resections was conducted at a single academic center (October 2019-December 2024). The CLiMR framework assigns scores to 4 components: Column (osteotomies/diskectomies for tumor release), Line-of-Sight (approach for circumferential access), Margin (adjacent structures sacrificed), and Ring (size of the vertebral ring window for safe delivery of neural tissue). Scores were applied using operative notes and imaging. RESULTS: Column scores ranged from 0.5 to 4.5. Of the patients included, 40.9% underwent sagittal split osteotomies, 22.7% radical diskectomies, 18.2% horizontal osteotomies, and the remaining 18.2% combinations of previous osteotomies . A posterior-only approach (Line-of-Sight score = 1) was used in 45.4% of cases, whereas 45.4% required a multistage approach (score = 2). Margin scores reflected increasing morbidity: 31.8% (n = 7) involving chest wall/pleura resection (grade 3), 40.9% (n = 9) requiring eloquent nerve sacrifice (grade 6), and 9.1% (n = 2) necessitating limb sacrifice (grade 7). The majority (86.4%, n = 19) of ring scores were grade 1, requiring laminectomies/facetectomies. The mean CLiMR score was 9.36 ± 2.43, with higher scores correlating with longer hospital stays (R = 0.64, P = .0012), longer case durations (R = 0.61, P = .0023), and increased blood loss (R = 0.40, P = .067). Patients with local recurrence, positive margins, or complications trended toward greater CLiMR scores. CONCLUSION: The CLiMR framework provides a novel, user-friendly method for planning and communicating en bloc spondylectomies. By addressing technical complexities and morbidity, CLiMR enables standardized assessment, facilitates surgical decision-making, and supports future research. This study demonstrates feasibility and lays the foundation for future validation studies.

Abstract Background Follow-up blood cultures (FUBCs) for streptococcal bacteremia are infrequently positive and may not provide sufficient clinical impact to justify the time and resources expended for their routine use. We aimed to evaluate the frequency of and risk factors for positive FUBCs in patients with streptococcal bacteremia and to compare clinical outcomes among patients with or without positive FUBCs. Methods We retrospectively reviewed hospitalized patients with streptococcal bacteremia from September 2023 to June 2024 within a multisite health system. Patients ≥18 years old with ≥1 positive blood culture for a Streptococcus species were included. Patients with polymicrobial bacteremia, those who died or were discharged to hospice within 48 hours of their index culture, and Minnesota residents who declined research authorization were excluded. Results We included 454 patients, with 48 (10.6%) having positive FUBCs. The rate of positivity ranged from 0% for Streptococcus pyogenes to 18.5% for Streptococcus anginosus. Endocarditis and osteomyelitis were more common in the positive than in the negative FUBC group (22.9% vs 12.1%, respectively, for endocarditis [P = .04] and 16.7% vs 5.4% [P = .005] for osteomyelitis). Positive FUBCs were associated with a higher incidence of infection relapse (8.5% vs 2.7%; P = .047) and longer duration of antibiotics (30 vs 16 days; P = .01), but no differences in mortality rate, length of stay, or infection-related readmission were observed. Conclusions Positive FUBCs were infrequent for S pyogenes, Streptococcus agalactiae, Streptococcus pneumoniae, and group C and G streptococci. It may be reasonable to forego FUBC for these streptococcal species if endocarditis or osteomyelitis are not clinically suspected.

Abstract In asthma, pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNFα) drive excessive mitochondrial fission in ASM cells through activating dynamin-related protein 1 (DRP1). Recently, we demonstrated that aryl hydrocarbon receptor (AhR) is expressed in human ASM and is upregulated during inflammation and asthma. This study explores the role of AhR in regulating mitochondrial fission in human ASM cells under pro-inflammatory and asthmatic conditions. Primary human nonasthmatic and asthmatic ASM cells were treated with 6-formylindolo[3,2-b]carbazole (FICZ: AhR agonist), with or without TNFα. Mitochondrial morphology was assessed using MitoTracker staining. DRP1 expression was evaluated in whole-cell and mitochondrial fractions. Loss- and gain-of-function studies (AhR inhibition, knockdown, and overexpression) were performed. AhR binding on the DRP1 promoter and promoter activity were assessed by ChIP-qPCR and luciferase reporter. The effects of AhR activation on oxygen consumption rate (OCR) were analyzed using seahorse XF-Pro. AhR activation significantly inhibited TNFα- and asthma-induced mitochondrial fission in ASM cells via inhibiting DRP1 in both inactive and active forms. In contrast, AhR inhibition or knockdown aggravated mitochondrial fission, while AhR overexpression failed to prevent TNFα-induced fission without ligand activation. Mechanistically, AhR bound the DRP1 promoter and suppressed its promoter activity, consistent with a genomic mode of action, while failing to alter ERK1/2 phosphorylation. Additionally, AhR activation also reduced TNFα- and asthma-induced increase in OCR. Collectively, this study shows that AhR activation prevents mitochondrial fission by inhibiting DRP1 in ASM during inflammation and highlights AhR as a promising therapeutic target for asthma and other airway diseases associated with mitochondrial dysfunction.

Abstract Background and Aims Women are underdiagnosed and undertreated for cardiovascular disease (CVD). Automatic quantification of breast arterial calcification (BAC) on screening mammography can identify women at risk for CVD. This study aimed to determine whether artificial intelligence–based automatic quantification of BAC from screening mammograms predicts CVD and mortality beyond PREVENT scores in a large, racially diverse, multi-institutional population. Methods This retrospective cohort study included 123 762 women from two healthcare systems who had screening mammograms. Breast arterial calcification was quantified using a transformer-based neural network for segmentation. Breast arterial calcification severity was categorized as zero (0 mm2), mild (>0–10 mm2), moderate (>10–25 mm2), and severe (>25 mm2). Kaplan–Meier analysis, Cox proportional hazards, and Fine–Gray competing event models were used to examine the association between BAC and major adverse cardiovascular events (MACE). Results Breast arterial calcification was detected in 16.1% (internal cohort) and 20.6% (external cohort) of women and provided significant prognostic value incremental to the PREVENT score. In PREVENT adjusted models, a clear dose–response was observed. Compared with zero BAC, mild [internal: hazard ratio (HR) 1.32, 95% confidence interval (CI) 1.10–1.59; external: HR 1.28, 95% CI 1.17–1.39], moderate (internal: HR 1.75, 95% CI 1.23–2.50; external: HR 1.79, 95% CI 1.55–2.06), and severe BAC (internal: HR 3.29, 95% CI 2.15–5.05; external: HR 2.80, 95% CI 2.36–3.32) were all prognostic for any MACE. Each 1 mm2 increase in BAC conferred an additional 2%–3% risk for MACE (P < .001). Conclusions Automatically quantified BAC is an independent predictor of MACE and mortality, adding prognostic value to the PREVENT score. This approach may provide an opportunistic cardiovascular risk assessment during routine mammography screening without additional radiation exposure to guide earlier and more effective preventive care for women.

Abstract Background Legionella pneumonia is an important cause of severe pneumonia, yet contemporary data describing its clinical phenotype, diagnostic patterns, and outcomes in the modern era are limited. Methods We conducted a retrospective multicenter cohort study of adults with laboratory-confirmed Legionella pneumonia across an integrated health system between January 2019 and September 2025. The primary outcome was 30-day mortality. Severe disease was defined as having a requirement for high-flow nasal cannula, noninvasive ventilation, mechanical ventilation, or extracorporeal membrane oxygenation (ECMO). Univariate and multivariable logistic regression were used to identify predictors of mortality and severe disease. Results There were 344 patients with laboratory-confirmed Legionella pneumonia during the study period. The median age was 66.6 years, and 45.1% were immunocompromised. Most patients required hospital admission (94.2%), with 36.1% admitted to the intensive care unit; 22.7% required mechanical ventilation and 1.5% ECMO. Thirty- and 90-day mortality were 11.9% and 16.6%, respectively. In multivariable analysis, cirrhosis (OR 10.2, 95% CI 2.15–48.3, P = .003), immunocompromised status (odds ratio [OR] 2.24, 95% CI 1.05–4.77, P = .036), age (OR 1.03, 95% CI 1.00–1.06, P = .031), and lymphopenia at presentation (OR 2.09, 95% CI 1.02–4.24, P = .043) were independently associated with increased 30-day mortality. Among patients who were polymerase chain reaction (PCR) or culture positive, urinary antigen testing was positive in only 25.6%. Conclusions Legionella pneumonia was associated with substantial short-term mortality. Cirrhosis, age, immunocompromised status, and lymphopenia at presentation emerged as independent predictors of 30-day mortality, underscoring the importance of host vulnerability in determining outcomes.

Abstract Purpose SARS-CoV-2 infection continues to impact global health, particularly among high-risk vulnerable individuals. With the loss of federal funding for SARS-CoV-2 management, hospitals will need to budget appropriately for antivirals like remdesivir, which has demonstrated effectiveness in reducing mortality. We evaluated the economic impact realized by hospitals for patients hospitalized for SARS-CoV-2 infection and initiated on remdesivir therapy. Methods We conducted a retrospective analysis using data compiled in the Premier Healthcare Database from January 2023 to February 2024. Propensity score matching was used to compare remdesivir-treated (RDV) and untreated (No RDV) groups. The mortality rate, hazard ratios associated with remdesivir use, and hospitalization costs were assessed overall and among the elderly (age ≥65 years). We also conducted a cost-effectiveness analysis to assess the economic value of remdesivir treatment. Results Among 25,498 hospitalized patients, the mortality rate in the RDV group was lower than in the No RDV group (6.2% versus 8.1%), with a greater reduction in the elderly (6.9% versus 9.0%). Remdesivir significantly reduced mortality risk by approximately 25% overall and among the elderly. Each life saved was realized at a minimal increase in average hospitalization costs ($18,329 in the RDV group versus $14,845 in the No RDV group). Remdesivir was a cost-effective treatment option at a willingness-to-pay threshold of $25,000 overall and among the elderly. Conclusions Our evaluation provides contemporaneous evidence of benefits and costs associated with management of individuals hospitalized for SARS-CoV-2 infection. Initiation of remdesivir was associated with minimal incremental hospitalization costs for lives saved as compared to not initiating remdesivir. Hospital pharmacy leadership can utilize this real-world evidence to appropriately budget for remdesivir treatment.

Background: Central cord syndrome (CCS) is the most common incomplete spinal cord injury, producing more severe motor deficits in the upper than lower extremities and impairing sensory and autonomic function. Although transcutaneous spinal cord stimulation (tSCS) has shown benefits in motor and sensory recovery after spinal cord injury, studies have not explicitly documented whether CCS subjects were included. The aim of this study was to assess the effects of tSCS over 12 weeks on motor and sensory outcomes in a subject with CCS. Methods: A 20-year-old male with a C7 injury was evaluated at baseline and after 12 weeks with the American Spinal Cord Injury Impairment scale, Modified Ashworth Scale, Penn and Spasm Frequency Scale, 3-Meter Walk Test and 6-Minute Walk Test, 9-Hole Peg Test, Box and Block Test, hand dynamometry, and lower-limb EMG. tSCS was applied between T9 and L1 at 30 Hz. Results: At 12 weeks, upper-limb motor and sensory scores improved, while spasm frequency and hand spasticity were reduced. Manual dexterity improved bilaterally in the 9-Hole Peg and Box and Block Tests, with a 2 kg gain in right-hand grip strength. In the 6-Minute Walk Test, the distance covered increased from 224.4 m to 295.2 m, and a 1.36 s reduction in 3-Meter walking time was achieved. Conclusions: tSCS improved motor and sensory function and reduced spasticity and spasms. These findings suggest that tSCS may serve as an effective complementary intervention for motor and sensory rehabilitation in individuals with mild cervical injuries, including CCS.