Deep Learning Estimation of Small Airways Disease from Inspiratory Chest CT: Clinical Validation, Repeatability, and Associations with Adverse Clinical Outcomes in COPD.

Rationale: Quantifying functional small airways disease (fSAD) requires additional expiratory computed tomography (CT) scan, limiting clinical applicability. Artificial intelligence (AI) could enable fSAD quantification from chest CT scan at total lung capacity (TLC) alone (fSAD).

Objectives: To evaluate an AI model for estimating fSAD, compare it with dual-volume parametric response mapping fSAD (fSAD), and assess its clinical associations and repeatability in chronic obstructive pulmonary disease (COPD).

Manual segmentation of opacities and consolidations on CT of long COVID patients from multiple annotators.

The field of supervised automated medical imaging segmentation suffers from relatively small datasets with ground truth labels. This is especially true for challenging segmentation problems that target structures with low contrast and ambiguous boundaries, such as ground glass opacities and consolidation in chest computed tomography images. In this work, we make available the first public dataset of ground glass opacity and consolidation in the lungs of Long COVID patients.

Mechanically Affected Lung and Progression of Emphysema.

Rationale: Most emphysema is believed to arise from small airways disease, but recent data suggest emphysema begets more emphysema and that its progression may be due to the mechanical stress experienced by normal lung regions adjacent to existing emphysema.

Objective: To determine whether new emphysema arises from this penumbra of mechanically affected lung (MAL) or from small airways disease.

Methods: We co-registered inspiratory chest computed tomography (CT) scans acquired at enrollment and 5 years later in 4,972 participants enrolled in a multicenter cohort.

Toward an integrated omics approach for plant biosynthetic pathway discovery in the age of AI.

Elucidating plant biosynthetic pathways is key to advancing a sustainable bioeconomy by enabling access to complex natural products through synthetic biology. Despite progress from genomic, transcriptomic, and metabolomic approaches, much multiomics data remain underutilized. This review highlights state-of-the-art multiomics strategies for discovering plant biosynthetic pathways, addressing challenges in data acquisition and interpretation with emerging computational tools.

Effect of perioperative remote ischemic conditioning on myocardial injury in patients with unstable angina undergoing percutaneous coronary intervention: protocol of a multicenter, randomized, double-blind clinical trial.

Background: Cardiovascular disease is a leading cause of death, with ischemic heart disease being a significant contributor. While percutaneous coronary intervention (PCI) effectively reduces mortality in myocardial infarction patients, its efficacy for unstable angina (UA) patients is controversial. Complications associated with PCI further limit application in UA.