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Abstract Background Inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn’s disease (CD), is characterized by immune dysregulation1,2. Blood-based biomarkers in diagnosing patients with IBD are lacking. We tested the hypothesis that circulating immune cell types and immune repertoire could distinguish patients with IBD from controls. Methods We performed deep immunophenotyping with scRNA-seq with T-cell receptor (TCR) and B-cell receptor (BCR) sequencing on peripheral blood mononuclear cells (PBMCs) from patients with IBD and healthy controls (87 UC, 127 CD, 35 controls). We applied machine learning to quantify cell abundance (miloR3), construct diagnostic classifiers (immuneML4), and infer cell-cell ligand-receptor interactions (MultiNicheNet5) between patients with IBD and controls. Results A scRNA-seq atlas of over 1.1 million PBMCs consisting of 53 distinct cell types was generated (Fig1A). In classifying UC vs controls, support vector machine model had a balanced accuracy of 0.90, consisting of increased IgA and IgG plasma B cells, switched memory B cells, TRegs, and decreased CD16 monocytes, cDC1, non-switched B cells, and MAIT (Fig.1B). In classifying CD vs controls, K-nearest neighbors model had a balanced accuracy of 0.87, consisting of increased IgA plasma B cells, non-switched B cells, CD4 Th22, TReg cytotoxic, CD4 Th1/Th17, and pDC and decreased CD16 monocytes, gdT, CD4 Th17, CD4 Th2, and MAIT cells.Fig.1C). Inflammation was associated with increased IgG plasma B in patients with both UC and CD. Using 4-mer amino acid motif of the BCR complementary-determining region 3 (CDR3) logistic regression model, immuneML had a balanced accuracy of 0.82 (0.75-0.92) in classifying CD vs controls (Fig.1D with models showing top 25 BCR predictive features). Using 4-mer amino acid motif of the BCR CDR3 logistic regression model, immuneML had a balanced accuracy of 0.90 (0.70-1.00) in classifying UC vs controls (Fig.1E with models showing top 25 BCR predictive features). Using 3-mer amino acid motif of the TCR CDR3 logistic regression model, immuneML had a balanced accuracy of 0.76 (0.72-081) in classifying CD vs UC. (Fig.1F with models showing top 25 TCR predictive features). In UC vs controls, MultiNicheNet demonstrated increased signaling in ADAM10-NOTCH2 between TRegs and naïve B cells and IL15-IL2RA between CD14 monocytes and CD4 Th17 cells. In CD vs controls, there was increased signaling in IL15-IL2RA between CD14 monocytes and CD4 Th17 cells and ADAM10-TSPAN5 between CD14 monocytes and TRegs (Fig.1G). Conclusion Applying machine learning models to scRNA-seq and immune repertoire datasets enable blood-based deep immunophenotyping with diagnostic potential and reveals novel insights into cell signaling in IBD. References: 1.Kong L, Pokatayev V, Lefkovith A, Carter GT, Creasey EA, Krishna C, Subramanian S, Kochar B, Ashenberg O, Lau H, Ananthakrishnan AN, Graham DB, Deguine J, Xavier RJ. The landscape of immune dysregulation in Crohn’s disease revealed through single-cell transcriptomic profiling in the ileum and colon. Immunity. 2023 Feb 14;56(2):444-458.e5. doi: 10.1016/j.immuni.2023.01.002. Epub 2023 Jan 30. Erratum in: Immunity. 2023 Dec 12;56(12):2855. doi: 10.1016/j.immuni.2023.10.017. PMID: 36720220; PMCID: PMC9957882. 2.Smillie CS, Biton M, Ordovas-Montanes J, Sullivan KM, Burgin G, Graham DB, Herbst RH, Rogel N, Slyper M, Waldman J, Sud M, Andrews E, Velonias G, Haber AL, Jagadeesh K, Vickovic S, Yao J, Stevens C, Dionne D, Nguyen LT, Villani AC, Hofree M, Creasey EA, Huang H, Rozenblatt-Rosen O, Garber JJ, Khalili H, Desch AN, Daly MJ, Ananthakrishnan AN, Shalek AK, Xavier RJ, Regev A. Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis. Cell. 2019 Jul 25;178(3):714-730.e22. doi: 10.1016/j.cell.2019.06.029. PMID: 31348891; PMCID: PMC6662628. 3.Dann E, Henderson NC, Teichmann SA, Morgan MD, Marioni JC. Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat Biotechnol. 2022 Feb;40(2):245-253. doi: 10.1038/s41587-021-01033-z. Epub 2021 Sep 30. PMID: 34594043; PMCID: PMC7617075. 4.Pavlović M, Scheffer L, Motwani K, Kanduri C, Kompova R, Vazov N, Waagan K, Bernal FLM, Costa AA, Corrie B, Akbar R, Al Hajj GS, Balaban G, Brusko TM, Chernigovskaya M, Christley S, Cowell LG, Frank R, Grytten I, Gundersen S, Haff IH, Hovig E, Hsieh PH, Klambauer G, Kuijjer ML, Lund-Andersen C, Martini A, Minotto T, Pensar J, Rand K, Riccardi E, Robert PA, Rocha A, Slabodkin A, Snapkov I, Sollid LM, Titov D, Weber CR, Widrich M, Yaari G, Greiff V, Sandve GK. The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nat Mach Intell. 2021 Nov;3(11):936-944. doi: 10.1038/s42256-021-00413-z. Epub 2021 Nov 16. PMID: 37396030; PMCID: PMC10312379. 5.Browaeys, R., Gilis, J., Sang-Aram, C., De Bleser, P., Hoste, L., Tavernier, S., Lambrechts, D., Seurinck, R. and Saeys, Y., 2023. MultiNicheNet: a flexible framework for differential cell-cell communication analysis from multi-sample multi-condition single-cell transcriptomics data. BioRxiv, pp.2023-06. Conflict of interest: Dr. Gubatan, John Mark: No conflict of interest Jiayu, Ye: No conflict of interest Christin, Lund-Andersen: No conflict of interest Boye, Theresa: No conflict of interest Hoang, Jacqueline: No conflict of interest Sojwal, Raoul: No conflict of interest Fardeen, Touran: No conflict of interest Tran, Tracy: No conflict of interest Sokzini, Peacha: No conflict of interest Koh, Ally: No conflict of interest Gibson, Marielle: No conflict of interest Sinha, Sidhartha: No conflict of interest Rogalla, Stephan: No conflict of interest Rosen, Michael: No conflict of interest Nielsen, Ole Haagen: No conflict of interest Sandve, Geir Kjetil: No conflict of interest

Objective: To establish international benchmark values for relevant outcome parameters in robotic Whipple. Summary Background Data: For safe adoption of surgical innovation, robust quality control is essential. Benchmarking is a validated tool for assessing surgical performance. Recent international consensus identified establishing benchmark values for robotic Whipple as top priority. Methods: We analyzed consecutive patients undergoing robotic Whipple between 2020-2023 with a minimum one-year follow-up. Reference centers were required to perform ≥15 cases/year, be scientifically active in the field, and maintain a prospective database. Benchmark criteria included benign or resectable malignant disease without neoadjuvant therapy, arterial resection, major co-morbidities, or significant previous abdominal surgery. Benchmarks were established for 13 outcome parameters. Result: The benchmark cohort comprised 418 patients from 12 centers across four continents. Benchmark values were: conversion rate ≤4.3%, transfusion rate ≤2.1%, 6-month mortality ≤2.2%, major complications ≤23.2%, and CCI® ≤20.9. Clinically relevant pancreatic fistula (grade B/C) and hemorrhage (grade B/C) rates were ≤23.6% and ≤12.7%, respectively. For pancreatic ductal adenocarcinoma (n=123), the benchmark for lymph node yield was ≥20. Higher surgical difficulty was associated with increased overall postoperative morbidity (R 2 =0.38, P =0.019), higher center caseload with reduced pancreas-specific complications (R 2 =0.28, P =0.044). Independent POPF predictors included duct diameter ≤4 mm (OR 1.37, 95% CI: 1.03, 1.82), anticoagulation (OR 2.45, 95% CI: 1.47, 3.99), and indication other than PDAC (OR 2.33, 95% CI: 1.68, 3.27). Conclusions: This study establishes the first international benchmarks for robotic Whipple, demonstrating oncologic outcomes and morbidity comparable to open surgery with the benefits of minimally invasive surgery.

Abstract Objective To measure the relative levels of signal and noise in expert diagnosis of epilepsy. Methods Twenty multinational epileptologists independently reviewed 50 vignettes of adult and pediatric patients presenting with suspected seizure(s) on two separate occasions with a ≥30‐day washout period. Experts provided a diagnosis of epilepsy or non‐epilepsy based on clinical information and, if requested, routine EEG and neuroimaging data. Cases had an established clinical diagnosis of epilepsy or non‐epilepsy based on capture of habitual paroxysmal events on video‐EEG or long‐term clinical follow‐up. Experts' judgments were analyzed to decompose variability into different sources: signal (objective differences between cases), level noise (experts' bias toward over/under‐diagnosis), pattern noise (experts' idiosyncratic reactions to specific case features), and occasion noise (inconsistency across occasions). Results The probability of an expert making a different diagnosis for a given case on two different occasions was 16%. The probability of two different experts making a different diagnosis for the same case was 26%. Signal (case “difficulty”) accounted for 66–69% of total variation, with 31–34% attributable to noise. Level noise was the largest contributor in the absence of EEG/neuroimaging results (23%), while pattern noise dominated when test results were available (24%). Occasion noise contributed relatively little (1%) but was still sufficient to cause diagnostic reversals in 16–22% between occasions. Significance The degree of noise in expert diagnosis of epilepsy is substantial, stemming primarily from physicians' idiosyncratic interpretations of case features and variable dispositions toward over‐ or under‐diagnosis. Strategies to improve reliability are needed, including standardized data collection protocols and structured decision algorithms. For “difficult cases,” where expert reliability and accuracy are lowest, our findings support current clinical practice which favors early referral for video‐EEG monitoring over reliance on diagnostic anchoring. This diagnostic pathway may become more accessible with advances in EEG technology (e.g., wearable devices) and artificial intelligence.

Objective The objective of this study was to investigate the association between dual seropositive, single seropositive, and seronegative rheumatoid arthritis (RA) with radiographic erosions, disease flares, and death. Methods We performed a retrospective, population‐based study of residents in Southern Minnesota with incident RA who fulfilled criteria for RA in 2003 to 2019. Radiographic erosions and flares were evaluated within one year of incident RA. All‐cause mortality was obtained from medical records and death certificates. Cox models adjusted for age, sex, smoking status, year of incident RA, and comorbidities were used. Results The study included 1,373 patients with RA. At RA incidence, 37% were dual seropositive, 13% seropositive for anti–cyclic citrullinated protein (anti‐CCP) only, 12% seropositive for rheumatoid factor (RF) only, and 38% seronegative. The highest proportion of radiographic erosions before or within one year of RA incidence was in the dual seropositive (31%) and lowest in those seropositive for anti‐CCP only (13%). Flares occurred in 69% of the dual seropositive and 51% of the seropositive for anti‐CCP only within the first year of RA incidence. Those seropositive for RF only had over a two‐fold increase in mortality rates compared with the seronegatives (adjusted hazard ratio [aHR] 2.18, 95% confidence interval [CI] 1.47–3.24). In contrast, the dual seropositives had only a >50% increase in mortality rates (aHR 1.66, 95% CI 1.21–2.28), and those seropositive only for anti‐CCP had a >30% increase in mortality rates (aHR 1.32, 95% CI 0.83–2.11). Conclusion Patients with RA seropositive for RF only have an increase in mortality rates compared with patients who are dual seronegative. RF positivity could be an indicator of inflammation that requires pharmacologic treatment to decrease mortality rates.

Background: Rotator cuff tears are a common orthopaedic injury often resulting in shoulder pain and functional impairment. Despite the prevalence of rotator cuff tears, the incidence of retear after rotator cuff repair (RCR) remains high. There is growing interest in the use of structural augmentation in RCR to decrease retear rates and improve patient outcomes. Purpose: The purpose of this systematic review and meta-analysis was to compare the clinical and imaging outcomes of structural augmentation versus standard RCR in patients with full-thickness rotator cuff tears. The effectiveness of different augment subtypes was also assessed. Study Design: Meta-analysis; Level of evidence, 3. Methods: A comprehensive literature search was conducted in CENTRAL, Embase, and Medline from inception to November 13, 2024. Eligible studies included comparative trials evaluating structural augmentation in RCR for repairable full-thickness tears. Risk of bias was assessed using the Cochrane risk-of-bias tool for randomized controlled trials and the MINORS (Methodological Index for Non-randomized Studies) score for observational studies. Meta-analyses were performed via a random effects model, with subgroup analyses performed by study design and augment type. Results: Twenty-four studies (12 randomized controlled trials and 12 cohort studies) were included in this review, all of which evaluated biologic augments (xenograft, allograft, autograft). Structural augmentation significantly reduced the risk of retear by 35% as compared with standard RCR (risk ratio, 0.65; 95% CI, 0.48-0.89; P = .01). Retears were confirmed radiographically by magnetic resonance imaging or ultrasound. Subgroup analysis revealed the greatest reduction in retear rates with allograft augmentation (risk ratio, 0.34; 95% CI, 0.21-0.56). No significant differences were observed in patient-reported outcomes, including pain scores, American Shoulder and Elbow Surgeons scores, or Constant scores. Conclusion: Structural augmentation in RCR significantly reduces retear rates, particularly with allografts, but does not improve short-term patient-reported outcomes. Further research is needed to identify which patient and tear characteristics may influence the effectiveness of augmentation.

Abstract Background Measurement of cardiac troponin (cTn) using high-sensitivity assays is recommended for the diagnosis of myocardial infarction. We determined sex-specific and uniform 99th percentile upper reference limits (URLs) using the new Elecsys® Troponin T high-sensitivity Gen 6 assay in a global, healthy reference range cohort. Methods Lithium-heparin plasma and serum samples were prospectively collected from apparently healthy individuals aged ≥20 years across 34 global sites in the United States, Europe, China, and Japan. cTnT was measured using the Troponin T high-sensitivity Gen 6 assay on the Cobas® e 801 analyzer. Exclusion criteria were defined according to the 2022 IFCC guidance. Uniform and sex-specific 99th percentile URLs and nonparametric 95% CIs were determined in plasma and serum separately and combined. Results The final study population comprised 4147 participants (52.5% female) with a median (25th–75th percentiles) age of 48.0 (33.0–59.0) years; 45.8%, 47.9%, 5.2%, and 1.1% were White, Asian, Black, and other/unknown, respectively. For sample matrices combined (n = 8294), 81.0% and 99.2% of cTnT values were above the limit of detection in females and males, respectively. Sex-specific 99th percentile URLs (95% CI) were 18 (16–23) ng/L for females and 32 (28–35) ng/L for males; the uniform 99th percentile URL was 27 (24–31) ng/L. URLs were comparable in plasma and serum samples. Conclusions This study determined sex-specific and uniform 99th percentile URLs for the Troponin T high-sensitivity Gen 6 assay that were comparable irrespective of the matrix used in a large, global, healthy reference population.

Abstract Background Intracranial mesenchymal tumors, FET::CREB fusion-positive (ICMT), show fusions involving FET RNA-binding protein family genes (EWSR1 or FUS) and CREB family of transcription factors (ATF1, CREB1, or CREM). The methylation signature(s), gene expression characteristics, and clinical behavior of this important tumor type require further characterization. Methods We study the methylation profiles of 81 ICMT cases (61 newly profiled cases and 20 cases from publicly available sources). Clinicopathologic and genomic data were recorded for each case when available. Results ICMT showed a relatively distinct methylation signature compared to related tumors. Among the 65 cases where fusion types were documented, the identified fusions included EWSR1::ATF1 (25 cases), EWSR1::CREB1 (12 cases), EWSR1::CREM (21 cases), FUS::CREM (3 cases), and SMARCA2::CREM (4 cases). We confirmed the prior description of 2 distinct subgroups of ICMT (subclasses A and B). The majority of the cases belonged to subclass A (n = 69; 85%), which showed a higher median age compared to subclass B patients (26 years vs. 15 years). Subclass B cases (n = 12; 15%) showed shorter progression-free survival (P < 0.01). Gene expression analysis of ICMT showed key overexpressed markers in ICMT, with significant CREM overexpression regardless of fusion type, when compared to either meningioma alone or a larger group of CNS tumors. Conclusions This work provides further characterization of ICMT as an important CNS mesenchymal neoplasm that is prone to tumor recurrence, showing 2 prognostically relevant methylation subclasses and warranting diagnostic distinction from other epigenetically and histologically related tumors. ICMTs show substantial overexpression of the CREM gene, independent of fusion type.

Background: Knee injuries are among the most common injuries in female basketball players. Despite the growing popularity of professional women's basketball, particularly the Women's National Basketball Association (WNBA), there are limited recent data evaluating the incidence of and risk factors for knee injuries in WNBA athletes. Hypothesis: Older age, minutes played per game, number of games played, and player usage rate would be significantly associated with having a knee injury in WNBA players from the 2017 to 2022 seasons. Study Design: Descriptive epidemiology study. Methods: Publicly available data on the injury history and player records of active WNBA players between the 2017 and 2022 seasons were reviewed to identify players with a knee injury resulting in ≥1 games missed. The primary outcome was the incidence of knee injuries reported per 1000 minutes-exposures (MEs). Player demographics, statistics, and injury characteristics were recorded. Secondary analysis was conducted using bivariate and multivariable logistic regression to investigate risk factors associated with having a knee injury. Results: A total of 87 players (10.8% of all players) sustained a combined 104 knee injuries between the 2017 and 2022 seasons, indicating a rate of 6.03 knee injuries per 1000 MEs. Accounting for potential confounders, having a knee injury was significantly associated with older age (OR, 1.11; 95% CI, 1.05-1.18; P = .0002) and higher usage rate (OR, 1.06; 95% CI, 1.02-1.11; P = .02). Conclusion: This study showed that knee injuries occurred in 10.8% of players, with an overall rate of 6.03 injuries per 1000 MEs. The most significant risk factors associated with having a knee injury in WNBA athletes were older age and higher player usage rate. Implementing targeted load management strategies for players with higher usage rates or advanced age may help reduce the incidence of knee injuries among female basketball athletes.

Summary In adults with classic Hodgkin lymphoma (cHL), metabolic tumour volume (MTV) is valuable for risk stratification. This systematic review explored the role of volumetric parameters in children, adolescents and young adults (CAYA) with cHL. This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) method. Five databases were searched on 16 October 2024. Eligible studies were peer‐reviewed manuscripts, written in English, published since database inception that included patients ≤21 years of age with a diagnosis of cHL treated with chemotherapy ± radiotherapy with a baseline 18 F‐Fluorodeoxyglucose (F‐FDG) PET/CT scan for MTV quantification. The search strategy identified 3669 studies, of which 35 were eligible for inclusion. Fifteen studies (43%) evaluated a cohort exclusively ≤21 years of age. All eight studies that explored the association of baseline PET parameters with known risk factors identified a significant correlation. Nine of 12 papers (75%) demonstrated a statistically significant correlation with disease response to therapy on PET/CT. Fifteen of 20 papers (75%) demonstrated an independent statistically significant correlation with clinical outcomes. In the CAYAHL population, volumetric PET parameters are valuable for risk stratification despite heterogeneity in results. Future harmonization of the segmentation approach will facilitate incorporation of MTV into clinical practice.

Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPis) are an important therapy for high-grade serous ovarian cancer (HGSOC). However, PARPi resistance frequently emerges, necessitating previously unrecognized approaches to improve HGSOC responses. Here, we showed that the anaplastic lymphoma kinase (ALK) inhibitor brigatinib enhances PARPi activity in HGSOC cells by disrupting an adaptive survival mechanism orchestrated by Fos-related antigen 1 (FRA1) in response to PARPi. This effect of brigatinib occurred through an ALK-independent pathway, wherein brigatinib induced a dual blockade of focal adhesion kinase (FAK) and EPH receptor A2 (EPHA2) tyrosine kinases, leading to the suppression of protein kinase B (Akt) and extracellular-regulated kinase (ERK) signaling accompanied by disruption of a phosphorylation event crucial for FRA1 protein stability. Moreover, in HGSOC patient-derived xenograft (PDX) models, brigatinib and PARPi combination therapy induced tumor regression and improved overall survival compared with PARPi alone, particularly in models with high FAK and EPHA2. These findings support dual targeting of FAK and EPHA2 as a strategy to achieve effective and durable PARPi responses and identify a promising biomarker-based combinatorial approach using brigatinib and PARPi for HGSOC, particularly the subset characterized by high FAK and EPHA2.