Pulmonology

Materiobiology-guided regulation of mesenchymal stromal cell fate for aging-related diseases: From basic parameter design to clinical application.

Mesenchymal stromal cells (MSCs) possess potent immunomodulatory, pro-angiogenic, and regenerative capacities, offering broad clinical promise in regenerative medicine. However, clinical application is constrained by low in vivo survival, poor targeting, variable efficacy, replicative senescence and insufficiently characterized in vivo cell fate. The accelerating global aging trend further complic...

Effectiveness of natural language intelligence technology in chronic diseases nursing: A systematic review and meta-analysis.

BACKGROUND: Chronic diseases pose a heavy global burden, with challenges in utilizing unstructured data for continuous care. Natural language intelligence technology (NLIT) shows potential in addressing these issues. METHODS: This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, with its protocol register...

Integrating Clinical Modeling and Machine Learning for Risk Assessment of Paracetamol and Other Nonsteroidal Anti-Inflammatory Drug Hypersensitivity in Children.

BACKGROUND: Nonsteroidal anti-inflammatory drug (NSAID) hypersensitivity is a common cause of drug-related reactions in children. Pre-test risk strati...

Identification of key genes modules linking brain aging signatures and COVID-19-associated cognitive impairment.

BACKGROUND: Emerging evidence indicates that SARS-CoV-2 infection is associated with aging, particularly in memory-related domains. However, the molec...

An attention-driven framework for drug repurposing against human metapneumovirus: Integrating predictive modeling with docking validation.

Human metapneumovirus (HMPV) is a member of the Paramyxoviridae family of viruses and has been associated with significant morbidity and mortality in ...

Machine learning-enabled early risk stratification of β-Iactam-induced electrolyte imbalances.

AIMS: To estimate the incidence of β-lactam/β-lactamase inhibitor - associated electrolyte imbalances and develop an internally validated, interpretab...

An integrative omics-machine learning framework for predicting pulmonary responses to titanium dioxide nanoparticles.

We address the challenge of leveraging complex lung transcriptomic data for nanosafety by re-optimizing the Transcriptomic Response Index (TRI) as a s...

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure.

BACKGROUND: Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increa...

A device-invariant multi-modal learning framework for respiratory disease classification.

Recent advances in cough sound analysis using deep learning techniques enable smartphone-based respiratory disease screening suitable for self-managem...

A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data.

Computational blind challenges offer critical, unbiased opportunities to assess and accelerate scientific progress, as demonstrated by a breadth of br...

Mothers against decapentaplegic homolog 4 as a proteomic hub in vascular remodeling and residual cardiovascular risk.

Translational cardiovascular medicine increasingly relies on systems-level approaches to uncover therapeutic targets that bridge molecular mechanisms ...

Artificial Intelligence-Assisted Diagnosis of Pulmonary Nodules in Lung Cancer Screening: Point-An Evolving Capability That Will Strengthen Screening Practice.

Artificial Intelligence-Assisted Diagnosis of Pulmonary Nodules in Lung Cancer Screening: Counterpoint-False Positives, Workflow Disruption, and the Enduring Role of Radiologists.

Application research on surveillance and predictive modeling of respiratory diseases in Baise City based on meteorological big data analysis.

Respiratory diseases are increasingly influenced by meteorological variability, yet few studies have applied high-resolution environmental data and ad...

Machine learning approaches to predict the risk of tuberculosis among household contacts of index TB patients in Central Ethiopia.

Specific diagnostic model for bacterial pneumonia constructed by combining multiple omics and multi machine learning models.

Due to the difficulty in quickly discriminating bacterial pneumonia (BPs) from pneumonia caused by other pathogens in clinic, the research for new bio...

Antiviral drug discovery and development: challenges and future directions.

The coronavirus disease 2019 (COVID-19) pandemic has stimulated extensive endeavors toward the development of therapeutic interventions targeting seve...

AI based prediction of severe exacerbation in Asian bronchiectasis patients using the KMBARC registry.

Based on single-cell and transcriptome analysis of inflammatory pathway biomarkers and their molecular mechanisms in chronic obstructive pulmonary disease.

BACKGROUND: Systemic inflammation in chronic obstructive pulmonary disease (COPD) presents significant therapeutic challenges. Our study employs integ...

Inference of drowning sites of cases in the Pearl river based on microbial community profiling and random forest algorithm.

Accurate inference of drowning sites remains a critical challenge in forensic investigations, particularly for corpses recovered from dynamic aquatic ...