Citations

ABSTRACT Myelodysplastic syndrome (MDS) and chronic myelomonocytic leukemia (CMML) are clonal myeloid neoplasms shaped by genetic lesions and immune dysregulation, both of which contribute to disease progression and poor outcomes. Existing prognostic systems, such as IPSS‐R and IPSS‐M, do not incorporate immune alterations. We assessed the biological and clinical relevance of an immune dysfunction signature (IDS) across multi‐center MDS and CMML cohorts. IDS scores, derived from bulk transcriptomic data, were significantly associated with inferior leukemia‐free and overall survival. In multivariable analyses, IDS retained independent prognostic value alongside IPSS‐R, IPSS‐M, and bi‐allelic TP53 inactivation. Incorporation of IDS into existing models improved prognostic discrimination and time‐dependent predictive accuracy. Longitudinal analyses revealed that rising IDS scores paralleled disease progression and acute transformation, whereas declining scores were observed in remission. Biologically, IDS‐high cases demonstrated reduced cytotoxic T‐cell activity, expansion of regulatory T cells, enrichment of primitive progenitor signals, and increased expression of checkpoint pathway genes. These findings were validated across multiple independent MDS cohorts and consistently reproduced in CMML, where IDS also stratified risk and tracked disease evolution. Finally, integration with drug response signatures from the BeatAMLv2 cohort suggested potential therapeutic vulnerability of IDS‐high cases to multikinase and NF‐κB pathway inhibitors. These results establish IDS as a robust and dynamic biomarker in MDS and CMML, with applications in refined risk stratification, longitudinal disease monitoring, and guiding personalized therapeutic strategies targeting immune dysfunction. Trial Registration: #201709072RINC, #202109078RINB, #202207050RINB

Background: Hepatocellular carcinoma (HCC) has a poor long-term prognosis due to high recurrence and cirrhosis-related mortality, even after potentially curative treatments such as liver transplantation (LT), surgical resection, or ablation. This study aimed to identify factors associated with ≥10-year survival in HCC patients. Methods: A retrospective cohort study was conducted among HCC patients diagnosed between 2004 and 2022 using the National Cancer Database. Multivariable Cox regression was used to identify predictors of overall survival, and logistic regression was used to identify predictors of ≥10-year survival. Results: Among 249,600 HCC patients, 177,585 (71.2%) died within 5 years, 8613 (3.5%) died at 5–10 years, 54,988 (22.0%) were alive with <10 years of follow-up, and 8219 (3.3%) survived ≥10 years. LT, resection, and ablation were performed in 6.6%, 9.3%, and 11% of patients, respectively. Compared with ablation as the reference group, LT [adjusted odds ratio (aOR) 11.96, 95% confidence interval (CI): 11.27–13.29] and resection (aOR: 2.83, 95% CI: 2.57–3.08) increased the odds of ≥10-year survival, while non-curative treatments reduced the odds compared with ablation (aOR: 0.50, 95% CI: 0.47–0.55). Cox regression results were consistent with the logistic model, confirming the association. Decision tree analysis confirmed LT as the dominant determinant of long-term survival. Black individuals were associated with lower odds of ≥10-year survival (aOR: 0.88, 95% CI: 0.820–0.96) and decreased likelihood of receiving LT (aOR: 0.73, 95% CI: 0.55–0.96). Conclusions: LT offers the best chance of ≥10-year survival in HCC. Ensuring equitable access is essential, especially for Black patients who have lower transplant rates and worse outcomes.

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.

Chimeric antigen receptor (CAR) T-cell therapy is an effective treatment for hematologic malignancies. However, it is limited by high costs, risk of severe toxicities such as cytokine release syndrome and neurotoxicity, and heterogeneous patient responses. The current therapy monitoring depends largely on subjective symptom assessment, routine laboratory tests, and basic vital signs, without real-time, quantitative evaluation of CAR T-cell expansion or activation in clinical practice. This lack of timely immune monitoring hampers individualized care and contributes to increased treatment costs. To address this need, we present a proof-of-concept, label-free rapid optical imaging (ROI) biosensor with automated machine learning analysis for direct quantification of CAR T-cells from whole blood. This microfluidic platform integrates red blood cell (RBC) removal, CAR T-cell capture, and imaging-based quantification on a single chip, eliminating the need for centrifugation, staining, and operator-dependent interpretation. For validation, 50 μL whole blood samples spiked with Jurkat cells expressing CD19 CARs underwent RBC depletion by agglutination and microfiltration. The remaining blood components were then incubated on a sensor chip functionalized with recombinant CD19 protein. Captured CAR T-cells were imaged by brightfield microscopy and automatically enumerated using a machine learning algorithm trained on fluorescence-validated cells. The CD-19 cells’ capture performance was validated by flow cytometry and fluorescence imaging. The trained machine learning model validated at 88% sensitivity and 96% specificity. Buffer and whole blood calibration curves were established across clinically relevant concentrations (1–1000 cells/µL) with triple replicates. The results showed high correlation (0.975 and 0.990 R2) between the spiked concentration and the detected CAR T-cells, with a 95% certainty limit of detection (LOD) and quantification (LOQ) of 0.6 and 1.1 cells/µL for spiked buffer, and 14 and 67 cells/µL for spiked whole-blood, respectively.

Purpose To project the future utilization of open and arthroscopic rotator cuff repair (RCR) in the Medicare population through 2050, incorporating post‐COVID recovery data to provide insight into evolving surgical preferences, economic pressures, and implications for health care delivery. Methods We analyzed 2003‐2024 data from the Centers for Medicare and Medicaid Services Medicare Part‐B National Summary, which captures all Medicare beneficiaries undergoing open or arthroscopic RCR as identified by Current Procedural Terminology codes. Projections were based on 2003‐2019 and 2023‐2024 data, reflecting post‐COVID‐19 recovery and avoiding distortions from 2020 to 2022 pandemic‐related disruptions. Statistical models evaluated included log‐linear, Poisson, negative binomial, and autoregressive integrated moving average. Autoregressive integrated moving average was selected based on the lowest normalized root mean square error, reflecting superior predictive accuracy and its ability to capture time‐dependent trends, and was used to forecast RCR volumes through 2050. Results In 2024, there were 23,154 open and 188,700 arthroscopic RCR procedures, which served as the baseline for modeling. Open RCR is projected to decline on average by 5.91% annually, while arthroscopic RCR is projected to grow by 2.88% annually. By 2050, arthroscopic RCR volume is expected to reach 394,434 procedures (95% forecast interval: 363,424‐425,321), whereas open RCR is expected to decline to 4748 procedures (95% forecast interval: 1243‐43,747). Conclusions Autoregressive integrated moving average modeling projects that by 2050 arthroscopic RCR utilization will increase by 2‐fold and open RCR will decline to one‐fifth compared with 2024 baseline volumes. Level of Evidence Level III, retrospective cohort study.

Abstract Aims Pulsed field ablation for atrial fibrillation offers shorter procedural times and improved safety compared with thermal ablation, but the optimal anaesthesia strategy remains uncertain. Most centres in the USA use general anaesthesia with endotracheal intubation, whereas monitored anaesthesia care without endotracheal intubation may be a safe and efficient alternative. Objectives To compare procedural efficiency and safety between monitored anaesthesia care and general anaesthesia for pulsed field ablation. Methods and results Consecutive adults who underwent pulsed field ablation for atrial fibrillation between 2024 and 2025 at Marshfield Clinic Health System were included. The anaesthesia approach was determined by operator preference. Procedural times, medication use, complications, and patient tolerance were recorded prospectively. Among 200 patients, 100 received monitored anaesthesia care without endotracheal intubation, and 100 received general anaesthesia. The mean age was 67 years, 42% were female, and the mean body mass index was 33 kilograms per square metre. Monitored anaesthesia care shortened case duration (77 vs. 95 min; P &lt; 0.001) and laboratory time (118 vs. 153 min; P = 0.002) and required fewer adjunct medications (P &lt; 0.001). Twenty-five procedures (25%) were challenging due to cough or motion but were all completed safely. Complications occurred in one monitored anaesthesia care case and six general anaesthesia cases (P = 0.054). Pulmonary vein isolation was achieved in all patients. Conclusion Monitored anaesthesia care without endotracheal intubation was safe, efficient, and resource-sparing compared with general anaesthesia for pulsed field atrial fibrillation ablation.

The major barrier to clinical translation of αCD137 immunotherapy is separating antitumor efficacy from hepatotoxicity driven by IFN-γ–producing CD8 T cells. We propose a strategy to limit toxicity by promoting contraction of excessively expanded CD8 T cells. We identify CD11c + KLRG1 + effector CD8 T cells (CD11c + T E ) as the primary source of IFN-γ, recirculating between blood and secondary lymphoid organs (SLOs), where they undergo apoptosis during contraction. We show that lymphotoxin β receptor (LTβR) signaling restrains this contraction. Mechanistically, lymphotoxin-expressing B cells activate LTβR in fibroblastic reticular cells (FRCs), suppressing apoptosis of CD11c + T E cells in the spleen and sustaining their systemic circulation and liver infiltration. Pharmacological LTβR blockade abrogates hepatotoxicity by reducing the accumulation of IFN-γ–producing CD11c + T E cells while preserving tumor-specific CD8 T cell responses. These findings identify LTβR as a key regulator of effector CD8 T cell persistence and support the use of LTβR antagonists to improve the safety of αCD137-based immunotherapy.

Abstract Background Atypical hemolytic uremic syndrome (aHUS) is a rare, complement-mediated disorder. Disease-associated variants have been found in complement factor H-related genes and complement regulatory genes. Particularly, homozygous deletions of CFHR1, CFHR3, or CFHR4 have been associated with aHUS. Generally, multiplex ligation-dependent probe amplification (MLPA) is used to detect copy number changes in the CFH and CFHR regions. We have developed a cost-effective droplet digital PCR (ddPCR) method for measuring copy number variations (CNVs) in these genes. Methods A total of 41 DNA samples were analyzed using both ddPCR and MLPA to assess large deletions in the CFHR1, CFHR3, CFHR4 regions. The ddPCR primers were designed to avoid rare single nucleotide polymorphisms to enhance hybridization efficiency and accurate identification of deletions within the CFHR regions. The MLPA probe mix (Probemix P236 CFH Region) targeting CFHR regions was purchased from MRC Holland. Results Multiple heterozygous deletions were observed in the CFHR1, CFHR3, and CFHR4 genes. Homozygous deletions of CFHR1 and CFHR3 were seen in 2 cases, while 2 other cases showed homozygous CFHR1 and heterozygous CFHR3 deletions. All 41 samples demonstrated 100% concordance in copy number results between ddPCR and MLPA, as well as consistent reproducibility in both inter- and intratechnologist evaluations. Conclusions Our findings demonstrate that ddPCR is a robust platform to identify large deletions in the CFHR regions. Future studies are needed to evaluate its ability to distinguish full vs partial deletions and to further establish its clinical diagnostic value.

Abstract The hallmark of heparin-induced thrombocytopenia (HIT) is the presence of immunoglobulin G (IgG) antibodies against platelet factor 4/heparin (PF4/H) complexes, typically detected by PF4/H enzyme-linked immunosorbent assay (ELISA); thus, negative ELISA results are commonly used to exclude this diagnosis. Here, we report a prevalent yet previously unrecognized subset of antibodies that are undetectable by PF4/H ELISA (ELISA−) but activate platelets in the PF4-dependent P-selectin expression assay (PEA+). In 11 patients with clinically confirmed HIT who tested positive in both PF4/H ELISA and platelet activation assays, ELISA−PEA+ antibodies accounted for 65% ± 19% of total platelet-activating IgG activity and coexisted with ELISA+PEA+ antibodies. Consistent with this finding, single-cell cloning from 7 patients with HIT identified 23 PEA+ antibody-producing B-cell clones, of which 17 were ELISA−, outnumbering the ELISA+ clones. Functionally, ELISA−PEA+ antibodies closely resembled ELISA+PEA+ antibodies: platelet binding and activation required exogenous PF4 and were inhibited by FcγRIIA blockade, high-dose heparin, or Fab fragments made from ELISA+PEA+ antibodies. Importantly, these antibodies induced thrombocytopenia in a humanized mouse model of HIT. Despite lacking PF4/H reactivity in ELISAs, they recognize PF4 on platelets and showed no appreciable binding to neutrophil-activating peptide-2, interleukin-8, or PF4 alone. Structurally, these antibodies were heterogeneous, with a subset sharing heavy-chain features with ELISA+PEA+ antibodies. Collectively, our findings demonstrate that ELISA−PEA+ antibodies are a common, previously unrecognized feature of HIT, with functional relevance, supporting the possibility that they play an important, perhaps even central, role in HIT pathogenesis. Defining their prevalence, kinetics, and clinical impact deserves high priority for further investigation.