Pulmonology

Linking ecological strategies to niche breadth: interpretable machine learning unravels community patterns of nirS-type aerobic denitrifiers along oxygen gradients in drinking water reservoirs.

Aerobic denitrifying bacteria are increasingly recognized for nitrogen removal in deep drinking-water reservoirs, yet how dissolved oxygen (DO) gradients relate to their ecological strategies, niche breadth, and co-occurrence networks remains unclear. We investigated nirS-type aerobic denitrifiers in 14 drinking-water reservoirs in North China using depth-stratified water-column samples, and class...

Identification of patients at risk for adverse events and poor symptom improvement after transcatheter aortic valve implantation.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) aims to improve symptoms and prognosis, while minimising adverse outcomes. Available prediction models focus on individual outcomes, but those combining adverse events and symptom improvement in a single prediction model are scarce, and include only few variables and lack external validation. Using machine learning, we developed a clinical...

Multi-omics integration in deciphering non-small cell lung cancer drug resistance: current status, challenges, and future prospects.

Lung cancer is the leading cause of cancer-related deaths globally. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung canc...

Integrative Analysis of Multi-omic Pathways Predict Cancer-Affected Lobes in Lung Cancer.

Lung cancer is the leading cause of cancer-related deaths. The human microbiome plays an important role in regulating response to cancer therapeutics,...

Multiscale Analysis of Deep Learning and Machine Learning: New Insights into the Adsorption Mechanism of VOCs Gas-Sensitive Materials.

Volatile organic compounds (VOCs) associated with lung cancer are key biomarkers for early noninvasive diagnosis, yet their adsorption behaviors on se...

Artificial Intelligence-Assisted Infrared Spectroscopy and Chemometrics for Enhanced Histopathology Screening of Micro- and Macrocancer Lesions.

Accurate detection of micro- and macrocancer lesions remains a critical challenge in histopathology, as conventional hematoxylin and eosin staining re...

A hybrid framework of feature selection and interpretability for dissolved oxygen prediction in drinking water treatment plants.

Accurate prediction of dissolved oxygen (DO) is essential for the sustainable operation of drinking water treatment plants. Conventional approaches of...

Interpretable machine learning unveils non-linear inflammatory thresholds and synergistic interactions in post-burn hypertrophic scarring: development of an intelligent clinical decision support system.

Hypertrophic scarring (HS) following severe burns remains a persistent rehabilitative challenge, yet traditional linear prediction models fail to capt...

Spectroscopic and machine learning approaches for clinical subtyping in systemic sclerosis.

Systemic sclerosis (SSc) is a heterogeneous autoimmune disease characterized by fibrosis, vascular damage, and immune dysregulation. In this study, we...

Explainable multi-modal approach for uncovering key predictors of stroke-risk from ECG, EMG, blood pressure, and respiratory signals.

Accurate and timely stroke-risk prediction is necessary to help patients at risk take guided measures, as stroke remains a leading cause of death and ...

Distinct serum metabolic profiles with supportive diagnostic value in differentiating tuberculosis and Mycobacterium avium complex pulmonary disease.

BACKGROUND: Pulmonary infectious diseases caused by Mycobacterium species, including Mycobacterium tuberculosis and Mycobacterium avium complex (MAC),...

Integrated network pharmacology and bioinformatics analysis reveals MME as key target of Notoginsenoside R1 in diabetic nephropathy.

BACKGROUND: Diabetic nephropathy (DN) is a major diabetes complication and a primary cause of end-stage renal failure. Notoginsenoside R1 (NGR1) is kn...

Machine learning-based prognostic model for local control prediction in lung cancer patients undergoing stereotactic body radiation therapy: a preliminary study.

PURPOSE: Predicting local recurrence after stereotactic body radiation therapy (SBRT) for lung cancer remains challenging. This study aims to develop ...

Deep Learning-based Estimated Pulmonary Biological Age from Chest CT Images in Healthy Adults: a model development and validation study.

BACKGROUND: Estimated pulmonary biological age (ePBA) has emerged as a more reliable indicator for disease progression and mortality than chronologica...

Molecular modelling assisted identification of novel Benzoxazole derivatives as hit molecules targeting Mycobacterial Membrane Protein Large 3 (MmpL3).

MmpL3 protein plays a vital role in cell wall synthesis in Mycobacterium. Novel benzoxazole carboxamide derivatives were designed to inhibit cell wall...

Pulmonary Obstruction and Age, Not Activity, Associate With Muscle Oxidative Impairment in Smokers With and Without COPD.

BACKGROUND: Low muscle oxidative capacity is an extrapulmonary manifestation of chronic obstructive pulmonary disease (COPD) with unclear aetiology. W...

Multi-omics predicts radiotherapy response in small cell lung cancer patients receiving whole brain irradiation.

OBJECTIVE: Dosiomics and radiomics elaborate the low-and high-order features extracted from images to predict clinical outcomes. Whole-brain radiother...

Evaluating the impact of deep learning-based image denoising on low-dose CT for lung cancer screening.

PURPOSE: Low-dose CT (LDCT) is increasingly being adopted as a preferred method for lung cancer screening. However, the accompanying rise in image noi...

The Immuno-Metabolic Crosstalk in Lung Squamous Cell Carcinoma: Prognostic Insights and Therapeutic Clues.

Lung squamous cell carcinoma (LUSC) has a poor prognosis due to the lack of effective targeted therapies, and its incidence has increased dramatically...

Artificial Intelligence-derived Measurements of Myosteatosis from Coronary Artery Calcium CT Scans to Predict COPD: The Multi-Ethnic Study of Atherosclerosis.

Purpose To evaluate the predictive value of myosteatosis as an opportunistic finding in coronary artery calcium (CAC) CT scans for clinically diagnose...