Transl Oncol. 2026 Sep 9;73:103020. doi: 10.1016/j.tranon.2026.103020. Online ahead of print.

ABSTRACT

BACKGROUND: The prognostic relevance of inflammatory bowel disease (IBD)-colorectal cancer (CRC) shared host-microbe signatures in non-intestinal epithelial malignancies remains unclear. This study aimed to evaluate the prognostic and biological significance of an IBD-CRC shared host-microbe interactome signature in bladder urothelial carcinoma (BLCA).

METHODS: Gene set variation analysis (GSVA) was used to assess the activity of the IBD-CRC shared signature across The Cancer Genome Atlas (TCGA) pan-cancer solid tumor cohorts, including lung, liver, colorectal, and urinary system tumors. In BLCA, weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO)-Cox regression were applied to construct a prognostic risk model, which was validated in independent transcriptomic cohorts. An attention-based multiple instance learning (MIL) model was developed to predict the LASSO-derived high- or low-risk group from H&E whole-slide images (WSIs), using TCGA cases for training and internal validation and an independent institutional cohort of 39 BLCA patients for external validation. Molecular subtype, immune infiltration, immunohistochemistry (IHC), machine learning, single nucleotide variation/copy number variation (SNV/CNV), single-cell/spatial transcriptomics, and WSI-based deep learning analyses were integrated to characterize the biological relevance of the signature.

RESULTS: High GSVA scores were significantly associated with poor prognosis in BLCA. The LASSO-derived high-risk group was enriched in basal/squamous molecular features and exhibited an immune-infiltrated but immunosuppressive tumor microenvironment, characterized by increased immunosuppressive cell infiltration and elevated immune checkpoint expression. Conventional IHC markers supported distinct subtype-related protein phenotypes between risk groups. Single-cell and spatial transcriptomic analyses revealed that malignant cells with high signature activity were enriched in Wnt, Hippo, and cell adhesion pathways. The WSI-based MIL model achieved an area under the curve (AUC) of 0.852 in the internal validation cohort. Machine learning and SNV/CNV analyses further characterized key molecular features associated with the LASSO risk score, including AKR1B1, LY6E, MEST, and others. Pan-cancer characterization of AKR1B1 across multiple malignancies, including lung adenocarcinoma (LUAD), liver hepatocellular carcinoma (LIHC), and kidney renal clear cell carcinoma (KIRC), revealed cancer-type-specific associations with immunosuppressive microenvironmental features and tumor stemness.

CONCLUSION: The IBD-CRC shared host-microbe signature has significant prognostic value in BLCA and is associated with basal/squamous differentiation, immunosuppressive microenvironmental features, genomic alteration patterns, and malignant cell functional heterogeneity. The integrated multi-omics framework and externally validated pathology AI model provide potential tools for BLCA risk stratification and biological interpretation.

PMID:42715652 | DOI:10.1016/j.tranon.2026.103020

J Vis Exp. 2026 Sep 8;(235). doi: 10.3791/71404.

ABSTRACT

Severe asthma is a difficult-to-control airway disease with pronounced heterogeneity in both clinical manifestations and underlying inflammatory mechanisms. This review examines the mechanisms, biomarkers, and biologic therapies of severe asthma, with a focus on biomarker-guided treatment selection and emerging precision strategies for type 2-high (T2-high) and type 2-low (T2-low) disease. The development of biologic therapies has changed the treatment paradigm, particularly for patients with T2-high inflammation. By targeting immunoglobulin E (IgE), interleukin-5 (IL-5), interleukin-4 receptor alpha (IL-4Rα), and thymic stromal lymphopoietin (TSLP)-related pathways, these agents can decrease exacerbations, improve lung function and symptom control, and enhance quality of life. Biomarkers, including blood eosinophils, fractional exhaled nitric oxide (FeNO), total IgE, and sputum eosinophils, have been incorporated into clinical decision-making to support patient stratification. Emerging markers such as periostin, epithelial alarmins, gene-expression patterns, microRNAs, and multi-omics signatures are under investigation for more accurate phenotyping and response prediction. Despite these advances, current biomarkers do not always provide sufficient predictive accuracy, targeted options for T2-low asthma remain limited, biologics are costly, and long-term outcome data remain incomplete. Overall, integrating biomarker findings with clinical phenotype, comorbidities, and treatment history remains central to individualized biologic selection.

PMID:42714006 | DOI:10.3791/71404

CA Cancer J Clin. 2026 Sep-Oct;76(5):e70100. doi: 10.3322/caac.70100.

ABSTRACT

The clinical landscape of early stage nonsmall cell lung cancer is at transformative crossroads. Driven by the widespread adoption of low-dose computed tomography screening, the frequent detection of ground-glass opacities, and a rising incidence among never-smokers, the diagnostic center of gravity has shifted toward earlier, potentially curable disease. This shift has been accompanied by equally important therapeutic advances, including parenchyma-sparing surgical techniques, minimally invasive platforms enhanced by digital navigation, and the transformative integration of perioperative immunotherapy and targeted agents. Concurrently, noninvasive monitoring approaches, such as liquid biopsy, have emerged as powerful tools to guide precision management. Despite this progress, substantial barriers to achieving a universal cure persist. Clinicians continue to face uncertainty in the management of ground-glass opacities, the anatomy-based TNM staging system fails to capture the biologic heterogeneity of early tumors, and global disparities in access to innovation remain unresolved. To address these challenges, the authors propose a shift toward a risk-adaptive management paradigm that harnesses artificial intelligence-driven analytics and multi-omics profiling to tailor treatment intensity according to each patient's biologic risk. Such an approach would enable appropriate escalation for high-risk individuals while permitting safe de-escalation for those at low risk. This holistic, lifespan-oriented strategy must be embraced to deliver equitable and durable cures for patients with early stage nonsmall cell lung cancer.

PMID:42713910 | PMC:PMC13555834 | DOI:10.3322/caac.70100

Front Immunol. 2026 Aug 25;17:1902981. doi: 10.3389/fimmu.2026.1902981. eCollection 2026.

ABSTRACT

BACKGROUND: Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome (MERS-CoV), cause respiratory infections with distinct clinical outcomes and case fatality rates. However, the molecular basis of these differences remains unclear. In this study, we sought to define virus-specific host metabolic programs by directly comparing multiomics profiles of the lungs of lethally infected mouse models.

METHODS: We performed integrated multiomics analyses, including untargeted metabolomics, transcriptomics, and targeted lipidomics, of lung tissues from human angiotensin-converting enzyme 2 (hiACE2)-human dipeptidyl peptidase 4 (hDPP4) double-knock-in (DKI) mice infected in SARS-CoV-2 or MERS-CoV. Data Integration Analysis and Biomarker discovery using Latent cOmponents (DIABLO) was applied across all three omics layers to identify key distinguishing molecular patterns. Additionally, in vitro lipid droplet kinetics were examined in infected Vero E6 cells to validate temporal differences in lipid remodeling.

RESULTS: We identified two distinct strategies for lipid utilization. SARS-CoV-2 infection showed strong activation of energy and amino acid metabolism at an early stage of infection (3 days post infection, DPI), whereas MERS-CoV infection was characterized by sustained alterations in lipid and nucleotide metabolism. Integrative DIABLO analysis of all three omics layers revealed that the key distinguishing features clustered into virus-specific molecular signatures: a triacylglycerol-lipid droplet-interferon axis for SARS-CoV-2 and a phospholipid-sphingolipid-membrane hub for MERS-CoV. In vitro lipid droplet kinetics in infected Vero E6 cells confirmed this temporal difference, with SARS-CoV-2 peaking earlier than MERS-CoV.

CONCLUSION: These findings show that β-CoVs exploit host lipid metabolism through virus-specific and time-dependent remodeling programs, providing a framework for understanding differential pathogenesis and developing host-directed antiviral strategies.

PMID:42712680 | PMC:PMC13550176 | DOI:10.3389/fimmu.2026.1902981

Transl Oncol. 2026 Sep 8;73:102990. doi: 10.1016/j.tranon.2026.102990. Online ahead of print.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) is a predominant and lethal subtype of non-small cell lung cancer, with a lack of reliable prognostic biomarkers to guide clinical management. Basigin (BSG) has been implicated in tumor progression across multiple cancers, yet its expression pattern, prognostic significance, and underlying mechanisms in LUAD remain incompletely elucidated.

METHODS: We integrated multi-omics data from TCGA, GTEx, CCLE, and GEO databases to analyze BSG expression profiles. Clinical correlations were assessed via Kruskal-Wallis tests. Prognostic value was determined using Kaplan-Meier survival analysis, univariate/multivariate Cox regression, and nomogram construction with calibration curves. Functional enrichment (GO/KEGG) and immune infiltration analyses were performed to explore BSG-related mechanisms, followed by immunohistochemical (IHC) validation in A549 cells and clinical LUAD tissue microarrays.

RESULTS: BSG was significantly upregulated in LUAD tissues versus normal/paired adjacent tissues, correlating with advanced T/N/pathologic stages. High BSG expression predicted worse survival outcomes in TCGA-LUAD, which was validated in GEO datasets. Multivariate Cox regression identified BSG as an independent prognostic factor, with a well-calibrated nomogram for survival prediction. Functional exploration indicated that BSG mainly participated in tumor-associated and immunological pathways. Immune infiltration analysis indicated that BSG was significantly correlated with the infiltration of various immune cells. Moreover, BSG exhibited a strong association with immune checkpoint proteins, chemokines, chemokine receptors, and MHC genes. IHC further confirmed its cytoplasmic/membranous localization and prognostic relevance.

CONCLUSION: BSG serves as an independent prognostic biomarker and potential therapeutic target in LUAD, shedding light on its regulatory roles in tumor progression and immune microenvironment remodeling.

PMID:42710246 | DOI:10.1016/j.tranon.2026.102990

Respirology. 2026 Sep 7. doi: 10.1002/resp.70309. Online ahead of print.

ABSTRACT

Multidisciplinary discussion remains the cornerstone of ILD diagnosis and management, with recent advances further strengthening the integration of clinical, radiological, pathological, and molecular information. Updated ILD nomenclature and classification better align disease terminology with underlying morphology and pathobiology. Growing emphasis is being placed on the early detection of ILD and on identifying individuals at high risk of progression among those with interstitial lung abnormalities (ILAs). Emerging multi-omic biomarkers and quantitative imaging techniques are enhancing prognostic stratification and may support future precision medicine approaches. Novel antifibrotic therapies and targeted treatments are expanding therapeutic options beyond IPF, although important unmet needs remain regarding patient selection, treatment response, and disease modification. The integration of clinical, radiological, functional, and molecular information will be fundamental to optimize individualized management and improve long-term outcomes in patients with ILDs.

PMID:42706010 | DOI:10.1002/resp.70309

Zhongguo Fei Ai Za Zhi. 2026 Jul 20;29(7):540-547. doi: 10.3779/j.issn.1009-3419.2026.101.17.

ABSTRACT

Immune checkpoint inhibitors (ICIs) have significantly improved the prognosis of patients with lung cancer. However, checkpoint inhibitor-related pneumonitis (CIP), as one of the most severe immune-related adverse events, lacks well-defined diagnostic criteria and reliable risk stratification tools. Radiomics enables high-throughput feature extraction from computed tomography images and provides a non-invasive technical approach for the early identification and risk stratification of CIP. This article systematically reviews the recent advances in the application of radiomics to risk prediction, diagnosis and differential diagnosis, and prognostic evaluation of CIP in lung cancer immunotherapy. Furthermore, it explores the value of integrating radiomics with multi-omics data in elucidating the pathogenesis of CIP, as well as the role of explainable artificial intelligence (XAI) in enhancing the clinical trustworthiness of models. .

PMID:42705857 | DOI:10.3779/j.issn.1009-3419.2026.101.17

Curr Probl Cancer. 2026 Sep 7;65:101333. doi: 10.1016/j.currproblcancer.2026.101333. Online ahead of print.

ABSTRACT

Heterogeneous tumor microenvironment (TME) in lung cancer plays a crucial role in disease progression and resistance to therapy. Despite advances in single-cell and bulk omics profiling, these methods often overlook spatial context, which is vital for understanding cell-cell interactions and regional heterogeneity. In recent years, spatial omics technologies-including spatial genomics, transcriptomics, proteomics, and metabolomics-have revolutionized the ability to map molecular landscapes while maintaining tissue architecture. These advancements have become essential components of next-generation lung cancer management. By providing unprecedented resolution in characterizing the lung cancer TME, spatial omics could reveal prognostic and predictive biomarkers and identify new therapeutic vulnerabilities. This review will provide the first critical evaluation of spatial multi-omics approaches for lung cancer prognosis. It will also assess various integration strategies for multi-omics data to explore the clinical translational potential of these tools for therapy selection and patient stratification. Therefore, a deeper understanding of spatial omics technologies and their application in lung cancer can significantly improve precision diagnostics and therapeutic decision-making.

PMID:42705130 | DOI:10.1016/j.currproblcancer.2026.101333

J Inflamm Res. 2026 Sep 2;19:633944. doi: 10.2147/JIR.S633944. eCollection 2026.

ABSTRACT

Lung inflammation and immune dysregulation are central to the pathogenesis of a broad spectrum of respiratory diseases, yet the cellular and molecular mechanisms underlying these processes remain incompletely understood. This review examines mechanisms of pulmonary inflammation across major respiratory diseases, including asthma, chronic obstructive pulmonary disease, acute lung injury/acute respiratory distress syndrome, and pulmonary fibrosis. We discuss the roles of dysregulated innate and adaptive immunity, persistent inflammation, tissue remodeling, and impaired resolution in the pathogenesis of respiratory diseases, thereby highlighting mechanisms that are broadly conserved across these conditions as well as those that diverge in a disease-specific manner. This synthesis offers a framework for understanding pulmonary immune dysregulation and identifying new biomarkers and therapeutic strategies to restore pulmonary immune homeostasis. We also discuss how endotyping, single-cell transcriptomics, spatial biology, and multi-omics approaches are refining mechanistic understanding and enabling precision immunomodulatory interventions.

PMID:42703518 | PMC:PMC13546649 | DOI:10.2147/JIR.S633944

Pediatr Res. 2026 Sep 5. doi: 10.1038/s41390-026-05417-2. Online ahead of print.

ABSTRACT

Bronchopulmonary dysplasia (BPD) is the most common chronic pulmonary complication of extreme prematurity in infants, now understood as a disorder of disrupted lung development rather than acute injury alone. Conventional clinical and functional criteria fail to capture the full heterogeneity of outcomes or the persistence of pulmonary morbidity into adulthood. Epigenetic mechanisms-including DNA methylation, histone modifications, and non-coding RNAs-provide a unifying biological framework linking perinatal exposures to long-term lung dysfunction. In the preterm lung, hyperoxia, inflammation, infection, pharmacologic interventions, and microbiome alterations durably influence gene expression without changing the DNA sequence, contributing to impaired alveolarization, pulmonary vascular growth, antioxidant defenses, immune regulation, and cellular senescence. Hyperoxia, specifically, has been associated with lasting epigenetic changes in redox-sensitive pathways, angiogenic signaling, and cell cycle control, while inflammatory stimuli may establish epigenetic "memory" that is consistent with the persistence of chronic inflammation and defective repair. Collectively, these processes support a model in which epigenetically programmed lung phenotypes may emerge, characterized by reduced pulmonary reserve, accelerated lung aging, and heightened vulnerability to respiratory disease across the lifespan. Although evidence for transgenerational inheritance in humans is limited, inherited susceptibility remains plausible, but unproven. Framing BPD as a disorder of biological memory emphasizes the need for epigenetic biomarkers, longitudinal cohort studies, and targeted preventive or therapeutic strategies to improve lifelong outcomes in survivors. IMPACT: This review reframes Bronchopulmonary Dysplasia as a disorder of developmental programming and biological memory, integrating hyperoxia, inflammation, and pharmacologic exposures within a DOHaD-based epigenetic framework to explain long-term pulmonary and systemic heterogeneity. It synthesizes experimental, translational, and clinical evidence-including redox epigenetics, trained immunity, sex-specific responses, and lung-brain-immune interactions-supporting a model in which early-life exposures shape lifelong respiratory and extra-pulmonary outcomes, while acknowledging that some mechanisms remain unproven. It identifies key translational priorities, including validation of epigenetic biomarkers, longitudinal multi-omics studies, and cautious development of epigenetic therapies, while emphasizing current methodological limitations and remaining evidence gaps.

PMID:42701161 | DOI:10.1038/s41390-026-05417-2

Cureus. 2026 Sep 3;18(9):e115698. doi: 10.7759/cureus.115698. eCollection 2026 Sep.

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disorder in which exacerbation susceptibility, persistent inflammation, disease progression, and treatment response are not fully explained by spirometry. Culture-independent studies have associated airway and gut microbial features with clinically relevant COPD phenotypes, but findings are highly sensitive to sampling site, low biomass, contamination control, sequencing depth and platform, bioinformatic workflow, microbial-load quantification, medication exposure, disease state, and host or environmental confounding. Methodological and clinical heterogeneity is therefore a central explanation for inconsistent results. This narrative review, a non-systematic synthesis using a prespecified focused PubMed/MEDLINE search (1 August 2021-1 August 2026), English-language eligibility, single-reviewer selection, structured data charting, and thematic appraisal without formal study-level risk-of-bias grading, evaluates recent human evidence on the airway bacteriome and mycobiome, gut microbiota and metabolites, host-microbe relationships, and the ecological effects of antibiotics and inhaled corticosteroids. Across cohorts, lower airway diversity, states dominated by potential pathobionts (normally resident organisms that may contribute to disease under altered host or ecological conditions), and altered microbial networks are recurrent but not universal associations; no disease-specific taxonomic signature has been validated. Gut microbial and metabolic differences may represent causes, consequences, treatment effects, shared determinants, or combinations of these mechanisms. Relative abundance is difficult to interpret without absolute microbial-load measurement. No microbiota-based diagnostic test, prognostic classifier, or intervention is ready for routine COPD care. Progress requires standardized longitudinal sampling, rigorous controls, absolute quantification, paired airway-gut multi-omics, diverse external validation, and randomized trials with prespecified patient-centered outcomes.

PMID:42699828 | PMC:PMC13544613 | DOI:10.7759/cureus.115698

Front Immunol. 2026 Aug 21;17:1878054. doi: 10.3389/fimmu.2026.1878054. eCollection 2026.

ABSTRACT

Viral burden or pathogen identity alone cannot adequately explain the progression of severe viral pneumonia from a compartmentalized respiratory infection to acute respiratory distress syndrome, multi-organ failure, and death. Maladaptive immunity, endothelial damage, and coagulation dysregulation are all functionally integrated in a host-driven pathological mechanism that mediates disease escalation. Systemic microvascular damage and pulmonary inflammation are linked by immune-endothelial-coagulation interaction. This review investigates the ways in which immunothrombosis and microcirculatory dysfunction are propagated by defective antiviral immunity, alveolar-capillary barrier failure, damage-associated molecular pattern and neutrophil extracellular trap release, endothelial glycocalyx degradation, complement-platelet interactions, coagulation cascade activation, and impaired fibrinolysis. Lung-derived inflammatory signals cause endothelial activation and procoagulant reprogramming in distal organs following systemic dissemination, resulting in organ-specific phenotypes such as acute kidney injury, secondary myocardial injury, ARDS in the lung, neurovascular unit dysfunction, and barrier-disruption-associated inflammatory amplification along the liver-gut axis. This framework may provide a rationale for exploring stage-adapted and phenotype-guided approaches to severe viral pneumonia, including early antiviral therapy, immunomodulation during disease progression, endothelial-coagulation axis targeting, and host-directed strategies. Further longitudinal cohorts, multi-omics analyses, mechanism-based stratification studies, and mechanism-embedded clinical trials will be needed to determine whether immune-endothelial-coagulation coupling can be translated from a mechanistic model into a clinically actionable framework for precision intervention.

PMID:42698821 | PMC:PMC13542883 | DOI:10.3389/fimmu.2026.1878054

J Proteome Res. 2026 Sep 4;25(9):4599-4613. doi: 10.1021/acs.jproteome.6c00120.

ABSTRACT

Microphysiological systems (MPSs) are gaining traction as a viable alternative model for toxicity studies. Further characterization is necessary to explore the full translational potential of MPSs to human physiology, along with the utility of these platforms to serve as a diagnostic tool. Multiomics analyses have emerged as a key means for identifying host biomarkers associated with chemical and drug exposure. Correlations between published human omics and MPS technology omics data will inform the potential of organ chips to accurately represent human responses and provide an alternative approach for improved biomarker discovery for toxicity assessment and exposure identification. To interrogate these potential overlaps, TissUse Chip3 multiorgan chips (MOCs) seeded with kidney organoids, liver organoids, and respiratory tract tissue were exposed to low, therapeutic, and toxic doses of acetaminophen (n = 4 for each condition) for 24 h and subjected to proteomic and metabolomic analysis. The data from our organ chips are largely consistent with biomarkers and dysregulations identified in published human omics data, in vitro and in vivo data, to include the identification of several known acetaminophen metabolites and biotransformation products. These data suggest that organ chips may be a suitable surrogate for human biomarker identification and drug or hazardous chemical exposure diagnosis.

PMID:42695873 | DOI:10.1021/acs.jproteome.6c00120

Front Immunol. 2026 Aug 20;17:1919864. doi: 10.3389/fimmu.2026.1919864. eCollection 2026.

ABSTRACT

Cholangiocarcinoma is an aggressive biliary tract malignancy in which metastatic relapse and primary or acquired resistance to immunotherapy remain major causes of mortality. Although immune checkpoint inhibitors have improved first-line treatment for advanced biliary tract cancer, most patients do not achieve durable benefit, indicating that immune failure is not explained by a single checkpoint pathway. In this Review, we propose a spatial immune-regulatory continuum for cholangiocarcinoma dissemination. Most direct single-cell and spatial evidence currently derives from intrahepatic cholangiocarcinoma, and its applicability to perihilar and distal disease remains to be established. This continuum begins in the tumor core and invasive front, where malignant cells, cancer-associated fibroblasts, tumor-associated macrophages, endothelial and lymphatic cells, regulatory T cells, immature neutrophils and excluded or dysfunctional cytotoxic T cells form a pro-invasive ecosystem. It then extends through extracellular vesicles, soluble mediators and lymphovascular routes that may educate organotropic pre-metastatic niches. Finally, lymph node, lung, liver, peritoneal and bone microenvironments provide organ-specific extracellular matrix, myeloid and stromal programs that enable immune evasion and metastatic colonization. By integrating clinical evidence, multi-omics studies, single-cell and spatial transcriptomics, extracellular vesicle biology, pre-metastatic niche concepts and emerging therapeutic strategies, we argue that cholangiocarcinoma metastasis should be targeted before overt dissemination whenever possible. In this Review, "metastasis-intercepting immunotherapy" is used as an author-defined conceptual framework for strategies intended to prevent or disrupt the immune-stromal conditions that enable dissemination and colonization, rather than merely shrink established metastatic lesions. Metastasis-intercepting immunotherapy will likely require rational combinations that reprogram the invasive front, restore dendritic-cell-mediated antigen presentation, block tumor-stroma-myeloid circuits, disrupt EV-mediated communication that may contribute to niche formation and select patients using spatial biomarkers rather than bulk immune markers alone.

PMID:42694469 | PMC:PMC13539491 | DOI:10.3389/fimmu.2026.1919864

Cell Rep. 2026 Sep 3;45(9):117943. doi: 10.1016/j.celrep.2026.117943. Online ahead of print.

ABSTRACT

Metabolic alterations are increasingly recognized during influenza virus infection, but how local lactate accumulation shapes antiviral immunity remains poorly characterized. By integrating time-series targeted energy metabolomics, single-cell RNA sequencing, flow cytometry, and functional perturbation, we show that influenza virus infection preferentially increases lactate within the lung microenvironment, where it restrains pulmonary CD8⁺ T cell response. Mechanistically, extracellular lactate enters dendritic cells through monocarboxylate transporter (MCT)-dependent transport and induces a tolerogenic-like state marked by impaired maturation, reduced costimulation, and diminished CD8⁺ T cell-priming capacity. Direct experimental evidence identifies H3K18la as a prominent lactate-responsive histone lactylation mark, while multi-omics integration links it to enhancer accessibility and NRF2 pathway activation. Functional studies further show that NRF2 promotes dendritic cell suppression by reinforcing tolerogenic programs and limiting mtROS-dependent XBP1 splicing. Together, these findings reveal a lactate-driven histone lactylation-NRF2 pathway that modulates antiviral immunity during influenza infection.

PMID:42690934 | DOI:10.1016/j.celrep.2026.117943