Microbial signatures predictive of short-term prognosis in severe pneumonia.

Objective: This retrospective cohort study aimed to investigate the composition and diversity of lung microbiota in patients with severe pneumonia and explore its association with short-term prognosis. Methods: A total of 301 patients diagnosed with severe pneumonia underwent bronchoalveolar lavage fluid metagenomic next-generation sequencing (mNGS) testing from February 2022 to January 2024. After applying exclusion criteria, 236 patients were included in the study. Baseline demographic and clinical characteristics were compared between survival and non-survival groups. Microbial composition and diversity were analyzed using alpha and beta diversity metrics. Additionally, LEfSe analysis and machine learning methods were employed to identify key pathogenic microorganism associated with short-term mortality. Microbial interaction modes were assessed through network co-occurrence analysis. Results: The overall 28-day mortality rate was 37.7% in severe pneumonia. Non-survival patients had a higher prevalence of hypertension and exhibited higher APACHE II and SOFA scores, higher procalcitonin (PCT), and shorter hospitalization duration. Microbial α and ß diversity analysis showed no significant differences between the two groups. However, distinct species diversity patterns were observed, with the non-survival group showing a higher abundance of Acinetobacter baumannii, Klebsiella pneumoniae, and Enterococcus faecium, while the survival group had a higher prevalence of Corynebacterium striatum and Enterobacter. LEfSe analysis identified 29 distinct terms, with 10 potential markers in the non-survival group, including Pseudomonas sp. and Enterococcus durans. Machine learning models selected 16 key pathogenic bacteria, such as Klebsiella pneumoniae, significantly contributing to predicting short-term mortality. Network co-occurrence analysis revealed greater complexity in the non-survival group compared to the survival group, with differences in central genera. Conclusion: Our study highlights the potential significance of lung microbiota composition in predicting short-term prognosis in severe pneumonia patients. Differences in microbial diversity and composition, along with distinct microbial interaction modes, may contribute to variations in short-term outcomes. Further research is warranted to elucidate the clinical implications and underlying mechanisms of these findings.

Functions and novel regulatory mechanisms of key glycolytic enzymes in pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) is a progressive vascular disease characterized by remodeling of the pulmonary vasculature and elevated pulmonary arterial pressure, ultimately leading to right heart failure and death. Despite its clinical significance, the precise molecular mechanisms driving PAH pathogenesis warrant confirmation. Compelling evidence indicates that during the development of PAH, pulmonary vascular cells exhibit a preference for energy generation through aerobic glycolysis, known as the "Warburg effect", even in well-oxygenated conditions. This metabolic shift results in imbalanced metabolism, increased proliferation, and severe pulmonary vascular remodeling. Exploring the Warburg effect and its interplay with glycolytic enzymes in the context of PAH has yielded current insights into emerging drug candidates targeting enzymes and intermediates involved in glucose metabolism. This sheds light on both opportunities and challenges in the realm of antiglycolytic therapy for PAH.