Pulmonology

Integrative multi-omics and machine learning reveal glycolysis-related biomarkers driving vascular remodeling in pulmonary arterial hypertension.

Metabolic reprogramming toward aerobic glycolysis, a phenomenon analogous to the Warburg effect, is increasingly recognized as a hallmark of pulmonary arterial hypertension (PAH). However, how glycolytic activation orchestrates pulmonary vascular remodeling and endothelial-mesenchymal transition (EndMT) remains poorly understood. To delineate the molecular determinants of glycolytic remodeling, we...

Multi-region proteomic mapping identifies FTL1 and SERPINA3K as protective factors in cardiac aging.

Aging is a well-recognized risk factor in cardiovascular diseases (CVDs), primarily due to its association with the gradual decline in cardiac function. This decline significantly influences the pathogenesis of common CVDs such as myocardial infarction and heart failure. Despite the existence of several proteomic atlases of the heart, the spatially resolved proteomic dynamics essential for underst...

Machine learning-based risk prediction of 28-day mortality for sepsis patients with augmented renal clearance.

Augmented renal clearance (ARC) frequently occurs in critically ill septic patients and is known to impact survival outcomes. To address this, we aime...

An automatic detection model for spread through air spaces in postoperative pathological sections based on deep learning in NSCLC.

Spread through air spaces (STAS) is recognized as an aggressive pattern of invasion in lung cancer and has been associated with poorer survival outcom...

Deep learning for visceral pleural invasion in non-small cell lung cancer.

BACKGROUND: To evaluate and compare the diagnostic performance of several commonly used deep learning (DL) models and a conventional clinical-radiolog...

Unraveling the molecular landscape of chronic radiation injury: From oxidative stress signaling to translational modeling (Review).

The expanding footprint of human radiation exposure, driven by advances in interventional diagnostics, the resurgence of the nuclear industry and the ...

Effect of a sports-medicine-guided football program on physical fitness in adolescents: A controlled school-based trial.

Integrating artificial intelligence (AI) with sports medicine principles into school-based physical education may enhance physical fitness and reduce ...

Risk Prediction Model for Critical Illness in Connective Tissue Disease-associated Interstitial Lung Disease.

OBJECTIVE: This study was to optimize the current methods for identifying and predicting the risk of critical illness in patients with connective tiss...

Longitudinal Plasma Proteomics Reveals an Immuno-thrombotic Signature that Predicts Radiation Pneumonitis in Lung Cancer.

PURPOSE: Radiation pneumonitis (RP) is a dose-limiting toxicity in lung cancer radiotherapy, often poorly predicted by static clinical and dosimetric ...

Pulmonary vascular volume heterogeneity in association with emphysema: a multicenter study based on non-contrast chest CT.

PURPOSE: To investigate the associations between emphysema and pulmonary vessels in patients with chronic obstructive pulmonary disease (COPD) and con...

Application of machine learning to predict bronchiolitis severity in children: a single-centre retrospective cohort study.

UNLABELLED: Several severity scores have been developed to assess disease severity in infants with bronchiolitis, but they often lack objectivity and ...

Effect of a Personalized Mobile Health Intervention Using Artificial Intelligence (the WARIFA App) Versus a Nonpersonalized Intervention on User-Defined Objectives, Healthy Lifestyles, and Management of Type 1 Diabetes (T1D): Protocol for a Randomized Controlled Trial.

BACKGROUND: Noncommunicable diseases are the leading cause of death worldwide. Cardiovascular and respiratory diseases, cancer, and type 2 diabetes sh...

Integrative transcriptomic analysis identifies immune-associated candidate genes and altered immune cell infiltration in pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a progressive vascular disease characterized by immune dysregulation and pulmonary vascular remod...

Decoding the role of polyamine metabolism in lung adenocarcinoma prognosis: A triangulated approach combining transcriptome, single-cell and Mendelian randomization analyses.

The progression of lung adenocarcinoma (LUAD) is influenced by polyamine metabolism, which modulates antitumor immunity, although the underlying mecha...

Lung Cancer Screening and Prevention: Beyond Conventional Strategies in a Rapidly Changing Global Milieu.

Lung cancer remains the leading cause of cancer-related mortality worldwide despite advances in early detection and treatment. Furthermore, its epidem...

Statistical Models Addressing Acute Respiratory Diseases: A Scoping Review.

This review highlights the application of statistical models in addressing respiratory diseases worldwide. A scoping review was conducted following Jo...

Effects of Non-IID Distributions in Lung Cancer Data on Survival Prediction with Federated Ensemble Learning.

A common challenge in Federated Learning (FL) is that distribution shifts between clients, or Non-IIDness, decrease global model performance. Non-IIDn...

Integrating ARIMA and Deep Learning Models for Counterfactual Evaluation of Nirsevimab's Early Impact on RSV Infant Admissions.

This study presents a hybrid modelling framework that integrates classical statistical methods (ARIMA) with deep learning architectures to enhance lon...

Integrating Causal Inference and Agent-Based Modelling to Assess the Impact of Clinicians' Guideline Adherence in Older Adults Hospitalized with Pneumonia.

This study integrates agent-based modeling (ABM) and causal machine learning (ML) to assess the impact of clinicians' adherence to antibiotic guidelin...

Automated Detection of Tuberculosis on Chest X-Rays Using Artificial Intelligence.

Detecting tuberculosis on X-rays remains complex and challenging for clinicians. In Burkina Faso, the scarcity of radiologists and their heavy workloa...