Pulmonology

Subphenotypes in acute respiratory distress syndrome: A scoping review across clinical, biological, computational, imaging, omics, and artificial intelligence approaches.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome with high mortality. Subphenotyping may identify more homogeneous groups for prognostic enrichment and precision therapies. METHODS: We conducted a scoping review (January 2013-December 31, 2025) in PubMed, Embase, and the Cochrane Library, complemented by reference screening. We included original adult studies deri...

Highly efficient and durable Th1-biased protective immunity from a novel mRNA vaccine against RSV via AI-assisted antigen screening.

Respiratory syncytial virus (RSV) is a leading cause of severe respiratory illness, imposing a significant burden on global health and society. Here, we report a novel mRNA vaccine that can offer potent and enduring protection against RSV. We designed various vaccines based on mRNA that encoded the RSV prefusion F protein and established an AI screening model for the prediction of expression and i...

Machine learning-driven identification of shared and disease-specific mitochondria-related genes in COPD, NSCLC, and NSCLC with COPD.

Chronic obstructive pulmonary disease (COPD) and non-small-cell lung cancer (NSCLC) often coexist; here, the shared mitochondrial drivers were investi...

Water parks, vaping, COPD topics on team management, exacerbations, bronchoscopic therapies, lung transplantation, and artificial intelligence.

Liquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approach.

UNLABELLED: Pulmonary nodules are a common radiological finding that can be classified as either benign or Malignant, with significant clinical implic...

From inhibition to regulation: serpins in health and disease.

This issue of the Biomedical Journal highlights regulatory mechanisms that shape aging, disease progression, and biological complexity across molecula...

Double Graph Attention Network for predicting non-alcoholic fatty liver disease in patients with type 2 diabetes.

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease, while non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver di...

Multicenter Prospective Cohort Study on Clinical Outcomes and Fibrosis Patterns in Biopsy-Proven Steatotic Liver Disease Subtypes.

BACKGROUND & AIMS: Clinical outcomes and histological characteristics of biopsy-proven steatotic liver disease (SLD) subtypes remain understudied. We ...

Deep Learning Model with Nodule Indexing Tailored to Early-Stage Lung Cancer Detection.

OBJECTIVE: To evaluate whether a deep learning-based AI system with suspected nodule indexing and malignancy risk stratification improves radiologist ...

"Comprehensive multi-omics of age-respective plasma and matrix-bound extracellular vesicles identifies anti-fibrotic miRNAs validated on a heart-on-a-chip".

Aging is a major risk factor for cardiovascular disease, the leading cause of death worldwide, and numerous other diseases, but the mechanisms of thes...

Roof-dependent atrial tachycardia after pulsed field ablation-mechanistic insights and predictive modeling for optimized ablation strategies: an ultra-high-density mapping study.

BACKGROUND AND AIMS: Pulsed field ablation (PFA) has emerged to an innovative approach to achieve pulmonary vein isolation (PVI) in atrial fibrillatio...

Machine-learning-guided tungsten single atoms promote oxyhydroxides for noble-metal-free water electrolysis.

Lowering the overpotential of oxygen evolution reaction with electrocatalysts is essential for efficient renewable-electricity-driven electrolysis. Ac...

Bioinspired triboelectric droplet sensor for ammonia monitoring.

Gas sensors with fast response are in high demand for environmental and health applications. Conventional solid-state sensing materials are inherently...

Predicting postoperative delirium after lung cancer resection: the utility of synthetic data and LIME algorithm for model interpretation.

To construct an efficient predictive model for post-lung cancer resection delirium (POD) using artificial intelligence, with a focus on leveraging syn...

Integrated predictive model for visceral pleural invasion in small NSCLC with high clinical utility.

This study aims to develop and validate a multi-feature integrated imaging fusion (MIIF) model, incorporating deep learning, radiomics features, and c...

APOLLO11: a bio-data-driven model for clinical and translational research in lung cancer.

Identifying predictive and resistance biomarkers remains one of the most relevant unmet needs in clinical cancer research. Artificial Intelligence (AI...

Dynamic Vibration-Coupled Energy Transfer for Boosting ORR Catalysts in Fuel Cells.

We demonstrate here a promising yet challenging method to produce highly active catalysts by utilizing exothermic adsorption to spur endothermic desor...

Machine learning for identifying risk factors of nosocomial infection in cancer patients with immune checkpoint inhibitor-related pneumonia.

Assumption-light feature discovery outperforms Cox-based selection for PM2.5 constituent analysis in an open benchmark.

AI misapplications are widespread in environmental research, often arising from limited understanding of machine learning assumptions and their alignm...

Radiomics for Differentiating Autoimmune-Related Interstitial Lung Disease from Idiopathic Pulmonary Fibrosis: A Narrative Review.

Interstitial lung disease (ILD) represents a wide variety of lung diseases, commonly resulting in irreversible changes with worsening quality of life ...