Mater Today Bio. 2026 Aug 18;40:103583. doi: 10.1016/j.mtbio.2026.103583. eCollection 2026 Oct.

ABSTRACT

TLR4 activation and the cascade of neutrophil extracellular trap (NET) formation exacerbate excessive inflammation and organ damage in the pathogenesis of acute lung injury (ALI), yet effective pharmacological interventions remain unavailable. Nanoaggregates derived from natural products offer promising avenue by leveraging synergistic anti-inflammatory effects. In this study, we surprisingly discovered that leonurine and ursolic acid spontaneously self-assemble into nanoparticles (LUNP) through non-covalent interactions, achieving a drug loading capacity of 100%. The LUNP platform exhibits superior biophysical properties, including enhanced mucus penetration, pH-responsive drug release, improved cellular uptake, and prolonged retention within inflamed lung tissue. Mechanistically, LUNP ameliorates ALI by dampening TLR4/MyD88/NF-κB-driven inflammatory activation, thereby remodeling the microenvironment to limit NOX4-PAD4-mediated NET formation. Notably, inhalational LUNP exhibits outstanding biosafety with minimal off-target distribution. Overall, this work introduces a synergistic self-assembled nanoplatform for precise pulmonary intervention in ALI, showcasing its ability to safely and effectively orchestrate the coordinated modulation of multiple pathological pathways. In summary, by inhibiting both TLR4 activation and NET formation, the synergistic LUNP platform offers an efficient, safe, and easily accessible therapeutic strategy for ALI, providing a promising solution for clinical translation.

PMID:42750707 | PMC:PMC13577835 | DOI:10.1016/j.mtbio.2026.103583

BMC Med. 2026 Apr 8. doi: 10.1186/s12916-026-04833-9. Online ahead of print.

ABSTRACT

Immunosenescence, the age-related decline in immune function, plays a crucial role in the pathogenesis and progression of lung diseases, including chronic obstructive pulmonary disease, lung cancer, pulmonary fibrosis, asthma, and respiratory tract infections. This comprehensive review examines the hallmarks of immunosenescence, and illustrates the association between immunosenescence and the pathogenesis of lung diseases. In addition, we discuss current and emerging therapeutic strategies that have been evaluated in human clinical trials for targeting immunosenescence in lung diseases. Specifically, this review provides in-depth insights into the therapeutic strategies, including senolytics and senomorphics, immunotherapy, stem cell therapy, thymic rejuvenation, probiotics, and lifestyle. We also highlight the potential of personalized approaches integrating multi-omics data and artificial intelligence to guide biomarker-driven interventions, enabling truly personalized therapeutic strategies. Finally, this review underscores the imperative for rigorously designed clinical trials to develop and validate interventions that specifically target immunosenescence, with the ultimate goal of improving clinical outcomes for the aged population with lung diseases.

PMID:41952158 | DOI:10.1186/s12916-026-04833-9

BMC Med. 2026 Apr 8. doi: 10.1186/s12916-026-04833-9. Online ahead of print.

ABSTRACT

Immunosenescence, the age-related decline in immune function, plays a crucial role in the pathogenesis and progression of lung diseases, including chronic obstructive pulmonary disease, lung cancer, pulmonary fibrosis, asthma, and respiratory tract infections. This comprehensive review examines the hallmarks of immunosenescence, and illustrates the association between immunosenescence and the pathogenesis of lung diseases. In addition, we discuss current and emerging therapeutic strategies that have been evaluated in human clinical trials for targeting immunosenescence in lung diseases. Specifically, this review provides in-depth insights into the therapeutic strategies, including senolytics and senomorphics, immunotherapy, stem cell therapy, thymic rejuvenation, probiotics, and lifestyle. We also highlight the potential of personalized approaches integrating multi-omics data and artificial intelligence to guide biomarker-driven interventions, enabling truly personalized therapeutic strategies. Finally, this review underscores the imperative for rigorously designed clinical trials to develop and validate interventions that specifically target immunosenescence, with the ultimate goal of improving clinical outcomes for the aged population with lung diseases.

PMID:41952158 | DOI:10.1186/s12916-026-04833-9

Gut. 2026 Mar 30:gutjnl-2025-337938. doi: 10.1136/gutjnl-2025-337938. Online ahead of print.

ABSTRACT

BACKGROUND: Survival outcomes after transarterial chemoembolisation (TACE) vary in hepatocellular carcinoma (HCC) patients, and existing prognostic scores and imaging models often lack generalisability and biological interpretability.

OBJECTIVE: To develop and validate a multimodal prognostication model for HCC that allows for a precise assessment of survival outcomes of HCC patients receiving TACE therapy.

DESIGN: This study enrolled 1448 HCC patients, including a TACE cohort (n=1349), a biomarker subset from a randomised trial (n=41), a single-cell RNA sequencing cohort and The Cancer Genome Atlas (TCGA) HCC cohort (n=50). Pre-treatment contrast-enhanced CT images were used to construct deep learning and conventional radiomic models. The early-fusion and late-fusion models (LFMs) were compared, and a clinical-radiologic model (CRM) was formed by integrating the better-performing LFM with clinical variables. Using TCGA data and single-cell transcriptomic profiles, the differences between high-score and low-score groups in tumour immune microenvironment, cellular functional states and key signalling pathways were investigated.

RESULTS: The CRM effectively stratified patients' survival across multiple independent cohorts and achieved more granular risk stratification than the existing clinical models. Multi-omic analyses revealed that in the LFM high-score group, myelocytomatosis oncogene was activated, epithelial-mesenchymal transition enhanced, glycolysis upregulated and hypoxia pathway activated. Single-cell transcriptomic data confirmed that virtually all cell types in high-risk patients scored high in hypoxia, and cytotoxic T cells had a reduced cytotoxic activity.

CONCLUSION: The CRM model can non-invasively predict the prognosis of HCC patients treated by TACE therapy.

PMID:41856522 | DOI:10.1136/gutjnl-2025-337938