Pulmonology

Right Ventricular Metrics as End Points in Clinical Trials: A Review.

IMPORTANCE: Clinical trials in cardiovascular medicine aim to deliver high-quality evidence with greater efficiency, including smaller sample sizes and shorter timelines. The selection of sensitive and reliable end points is central to this goal. Right ventricular (RV) structure and function play a critical role in many cardiovascular conditions; however, RV-specific parameters remain underused an...

Human donor liver viability evaluation with polarization-sensitive optical coherence tomography.

Human liver transplantation is constrained by a critical shortage of viable donor livers. In response to this shortage, marginal livers from extended criteria donors are increasingly used to expand the donor pool. Donor liver viability assessment remains limited by invasive, biopsy-based pathological sampling, and there is a need for more comprehensive and noninvasive evaluation techniques to meet...

Decoding fibrosis: Transcriptomic and clinical insights via AI-derived collagen deposition phenotypes in MASLD.

Histological assessment is foundational to multi-omics studies of liver disease, yet conventional fibrosis staging lacks resolution, and quantitative ...

Stochastic Expansion of Radionuclide Inhalation Dosimetry for Consequence Management Application: Uncertainty and Sensitivity Analysis in the ICRP 130 Human Respiratory Tract Model.

Releases from nuclear or radiological security events can result in significant internal radiation contamination through inhalation of particulate con...

Inflammation-mediated diabetes-liver disease cross-organ crosstalk: From molecular mechanisms to precision therapeutic strategies.

The rising global prevalence of diabetes mellitus and its liver complications presents a significant public health challenge. Inflammation-driven cros...

A hybrid LLM and machine learning framework for early fire detection in subway tunnels.

Fire detection is vital in subway tunnels where confined geometries and ventilation complicate safety monitoring. Existing approaches, including class...

Multimodal PET/CT-based PD-L1 status prediction in lung cancer via semi-supervised and unsupervised deep learning.

Deep learning (DL) techniques have been applied in lung cancer screening, assessing drug effectiveness, and enhancing prognosis prediction. Within thi...

Interpretable machine learning for preoperative prediction of ground-glass nodules invasiveness in lung adenocarcinoma: a multicenter study.

Accurate, noninvasive prediction of invasiveness in ground-glass nodules (GGNs) is important for surgical planning in lung adenocarcinoma. This multic...

Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.

Cough is a common and physiologically informative component of respiratory morbidity, but its potential for diagnosing and monitoring disease is not t...

Urbanization compound pathways of global lung cancer incidence risk under proximal and distal interactions.

Lung cancer burden varies across countries undergoing different stages of urbanization, but the interacting roles of behavioral and macro-environmenta...

Using machine learning algorithms based on laboratory indicators to establish a diagnostic model for lung cancer.

BACKGROUND: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Current diagnostic strategies rely primarily on imagi...

Detecting and measuring respiratory events in horses during exercise with a microphone: deep learning vs. standard signal processing.

BACKGROUND: Monitoring respiration parameters such as respiratory rate could be beneficial to understand the impact of training on equine health and p...

Real-Time and Non-Invasive Detection of Respiratory Viral Infections Using an Intelligent Odor Monitoring System (IOMS).

Real-time monitoring of infection-associated volatile organic compounds (VOCs) offers a non-invasive pathway for early respiratory infection detection...

Multi-omics investigation of per- and polyfluoroalkyl substances in lung adenocarcinoma: comprehensive network toxicology, machine learning and molecular docking experiments.

Growing concerns regarding per- and polyfluoroalkyl substances (PFAS) as pervasive environmental contaminants have prompted increasing scrutiny regard...

Toward next-generation biosurfactants: Engineering rhamnolipid production from safe chassis design to scalable bioprocessing.

Rhamnolipid manufacturing is transitioning from empirical cultivation to programmable, multi-scale molecular bioengineering. This review highlights th...

Objective dyspnea measurement in real time using a forehead wearable and artificial intelligence.

Dyspnea is a complex symptom measured using subjective patient-reported ratings. Continuous, automated dyspnea measurements are needed, especially in ...

Metabolic pathway signatures define prognostic subtypes of lung adenocarcinoma.

Metabolic reprogramming is a core hallmark of cancer, yet how it contributes to the clinical heterogeneity of lung adenocarcinoma (LUAD) remains poorl...

Detection, localization, and measurement of endotracheal tube positioning on adults' chest X-ray: developing a prediction model.

Accurate placement of the endotracheal tube (ETT) is critical for ensuring optimal care for patients requiring mechanical ventilation and preventing p...

Innovative screening for OSAS in patients with head and neck cancer using the apneal application: Protocol for a prospective single-centre study.

INTRODUCTION: OSAS is a common yet underdiagnosed condition, particularly among patients with head and neck cancers (HNC). Anatomical changes caused b...

Transformer-accelerated discovery of inhibitors targeting the RpsAΔ438 deletion in PZA-resistant tuberculosis.

Tuberculosis is a major global public health problem caused by Mycobacterium tuberculosis. Pyrazinamide (PZA), a key first-line drug, is activated to ...