Pulmonology

Identification of chemical features for improved outer membrane permeation in mycobacteria using machine learning.

The ability of compounds to permeate and accumulate in bacterial cells is a critical determinant of antibiotic efficacy. Better therapeutics are urgently needed for the human pathogen Mycobacterium tuberculosis, yet the cell envelope, including the mycobacterial outer membrane, represents a significant barrier for drug entry, and the chemical features governing permeation remain poorly understood....

Integrative Multi-Omics Analysis Elucidates the Progressive Disease Landscape and Reveals Dynamic Protein Biomarkers for MASLD Surveillance.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide, encompassing a continuum ranging from simple steatosis to steatohepatitis, hepatic fibrosis, and cirrhosis. Despite the complex and heterogeneous pathogenesis, effective therapeutic targets remain elusive. In this study, we sought to identify and validate critical genes implicate...

European Cancer Prevention Organization on cancer screening: an expert panel position paper.

BACKGROUND: Cancer screening is a cornerstone of cancer control in Europe yet marked disparities persist in access, implementation, and quality assura...

Machine learning-based cross-sectional exploration of depression-chronic pain associations in chronic respiratory disease patients.

BACKGROUND: Chronic respiratory diseases (CRD) are a leading global cause of death, with high comorbidity rates of depression and chronic pain forming...

Predicting 1-Year Renal Outcomes in Patients with Diabetic Kidney Disease in CKD Stages 3 to 4: A Multimodal Machine Learning Approach Fusing Clinical Composites and Pathology Images.

Patients with diabetic kidney disease (DKD) at chronic kidney disease (CKD) stages 3 to 4 are at high risk for rapid renal function decline within 1 y...

Discovery of biomarkers for primary Sj ögren's syndrome based on multi-omics data, construction of diagnostic models, and clinical correlation analysis.

OBJECTIVE: Primary Sjogren's syndrome(pSS) exhibits significant clinical heterogeneity, which poses challenges for accurately assessing disease activi...

Oxygen 1s photoelectron spectroscopy of gaseous alcohols and the σ-inductive properties of alkyl groups.

This study presents a comprehensive investigation of alcohol molecules in the gas phase using oxygen 1s X-ray photoelectron spectroscopy (O1s XPS), co...

From data mining to mechanistic prediction: a study on drug-induced lung injury integrating FAERS, machine learning, and network toxicology.

Drug-induced lung injury (DLI) is a serious and potentially fatal adverse drug reaction that remains difficult to detect early and continues to challe...

Harnessing Machine Learning and Electronic Health Record Data to Improve Asthma Management.

PURPOSE OF REVIEW: The review examines the application of machine learning (ML) and large language models (LLMs) to asthma management. We sought to id...

Integrating Machine Learning and Pharmacology Reveals NF-κB-Mediated Inflammatory Regulation by Shuanghuanglian Injection in Acute Lung Injury.

ETHNOPHARMACOLOGICAL RELEVANCE: Shuanghuanglian Injection (SHLI) is a traditional Chinese medicine formulation derived from Lonicerae Japonicae Flos, ...

Effects of Telerehabilitation Based on Motion Recognition Technology on Exercise Endurance of Patients With Non-Small Cell Lung Cancer After Surgery: Single-Center, Prospective, Open-Label, Randomized Controlled Trial.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for approximately 85% of primary pulmonary neoplasms. Complete surgical removal remains the co...

Underwater Suit-Wearing Cyborg Insect Capable of Hours-Long Diving and Terra-Aqua Travel.

The fundamental operational range of cyborg insects, which are hybrid robots that combine a living insect with an electronic controller, is inherently...

An attention-guided multimodal deep learning framework by integrating CT-PET imaging and clinical data for lung cancer detection.

The proposed multi-modal deep learning system for lung cancer diagnosis and characterisation uses structural (CT), functional (PET), and clinical (EHR...

Prediction of severe pediatric community-acquired pneumonia using multimodal fusion of chest radiographs and clinical data.

BACKGROUND: Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality in children, particularly in low-income countries. Severe...

Glycemic variability does not provide incremental prognostic value for in-hospital death in community-acquired pneumonia patients: conventional clinical variables dominate.

OBJECTIVES: This study aimed to systematically evaluate whether glycemic variability (GV) could provide independent incremental prognostic value for i...

Temporal deep learning for 28-day mortality prediction in critically ill ovarian cancer patients: a multicenter development and validation study using hourly vital signs.

BACKGROUND: Ovarian cancer patients requiring intensive care unit (ICU) admission face particularly grave prognosis, yet current prognostic models rel...

Deep learning for time-series segmentation of mechanical ventilator waveforms.

Accurate segmentation of ventilator waveforms is essential for detecting patient-ventilator asynchronies (PVAs), yet current heuristic methods can fai...

Decoding the Complexity of Tricuspid Regurgitation Prognostic Drivers Using Explainable Artificial Intelligence.

AIMS: Prognosis in tricuspid regurgitation (TR) is shaped by complex clinical and hemodynamic interactions, complicating risk stratification. We aimed...

Artificial intelligence-enhanced nurse navigation for monitoring and care of long COVID.

INTRODUCTION: Long COVID is a multisystem condition with challenging diagnosis. Nurse-navigation, a patient-centered intervention, can enhance educati...

Integrative machine learning and experimental validation reveal the molecular mechanisms of 2-bromo-4,6-dinitroaniline nephrotoxicity: CD45 and cyclophilin C as early response biomarkers of renal tubular injury.

2-Bromo-4,6-dinitroaniline (BDNA), a synthetic intermediate of brominated azo dyes, poses potential nephrotoxicity risks; however, its early molecular...