Daily Respiratory Research Analysis

Acute respiratory distress syndrome (ARDS) remains a major challenge in critical care, with mortality exceeding 40%. Its diagnosis and management depend on multi-step procedures, invasive arterial blood gas analysis, and subjective CT interpretation, often leading to inconsistency, delayed intervention, and increased procedural burden. To address these limitations, we develop AutoARDS, an all-in-one foundation model that transforms routine chest CT into a quantitative platform, enabling integrated and reproducible assessment of diagnosis, progression, oxygenation, physiology, and prognosis within a single, non-invasive workflow, thereby supporting faster and more standardized critical-care decisions. Technically, AutoARDS proposes to employ a multi-task pretraining strategy with adversarial perturbation, distilling routine but unstructured clinical data into unified representations for fine-grained pathological learning. Trained on over 50,000 CT volumes and validated across six medical centers (6,153 individuals), AutoARDS (1) established a reproducible CT-derived biomarker linking morphological injury with disease severity, enabling standardized tracking of pulmonary progression; (2) accurately diagnosed acute respiratory failure and ARDS (AUCs = 0.97 and 0.87), facilitating early recognition and reducing diagnostic delay; (3) directly estimated the P/F ratio (PCC = 0.83), outperforming SpO

Coexisting strains of the same species within metagenomic data pose a substantial challenge to inferring transmission of pathogenic and commensal microbes. Here we present TRAnsmision Clustering of Strains (TRACS), a highly accurate algorithm for estimating genetic distances between strains at the level of individual single nucleotide polymorphisms, which is robust to intra-species diversity within the host. Analysis of faecal microbiota transplantation datasets and extensive simulations demonstrates that TRACS outperforms existing methods. We use TRACS to infer transmission networks in patients colonized with multiple strains, including severe acute respiratory syndrome coronavirus 2 amplicon sequencing data, deep population sequencing data of Streptococcus pneumoniae and single-cell genome sequencing data from patients infected with Plasmodium falciparum. Applying TRACS to gut metagenomic samples from a mother-infant cohort revealed species-specific transmission rates and identified increased the persistence of Bifidobacterium breve in infants, a finding previously missed owing to the presence of multiple strains. Our study shows that TRACS can be used across microbial kingdoms to uncover strain dynamics.

Pulmonary ischemia-reperfusion injury is a major cause of acute lung injury and primary graft dysfunction after lung transplantation, with few effective treatments available. In this study, we develop a macrophage-membrane-coated mesoporous polydopamine nanoparticle system loaded with ginsenoside Rg3 (Rg3@PACVs) and activated by near-infrared irradiation. This design enables precise targeting of injured lung tissue via chemokine-receptor- and integrin-mediated pathways, while allowing controllable, on-demand drug release. In vitro hypoxia-reoxygenation models and a rat pulmonary ischemia-reperfusion model demonstrate that Rg3@PACVs with mild photothermal therapy reduce reactive oxygen species accumulation, suppress inflammatory cytokines, preserve mitochondrial structure and tricarboxylic acid cycle metabolism, and alleviate tissue injury. The approach combines targeted delivery, multimodal protection against oxidative and inflammatory damage, and mitochondrial restoration. These findings suggest a promising therapeutic strategy for mitigating lung ischemia-reperfusion injury and potentially for other inflammation- and oxidative-stress-driven pulmonary diseases.