VNN1 as a potential biomarker for sepsis diagnosis and its implications in immune infiltration and tumor prognosis.

Background: This study explored novel biomarkers for diagnosing sepsis, a severe disease prevalent in clinical settings, particularly threatening to elderly patients. Methods: Using microarray gene expression datasets and fatty acid metabolism signatures, we identified differentially expressed genes between sepsis and healthy control groups. Correlations between candidate genes, immune cells, and immune function were assessed. Logistic regression analysis and single-gene GSEA analysis were performed to identify potential biomarkers. The biomarkers' association with different types of tumors was investigated. Results: Twelve genes related to fatty acid metabolism were excluded. CA4, OLAN, and VNN1 were found relevant to immune cells and function. Among these, only VNN1 showed statistical significance (p < 0.05), with a strong area under the ROC curve (0.995). High VNN1 expression indicated activation of certain metabolic pathways, while low expression suggested potential autoimmune responses. VNN1 was up-regulated in eight tumors and down-regulated in eight others. High VNN1 expression was linked to poor prognosis in six types of tumors, and low expression was linked to poor prognosis in four types of tumors. VNN1 expression showed correlations with stromal scores, immune scores, and cancer purity in different types of tumors. Conclusion: VNN1 holds promise as a potential biomarker for sepsis diagnosis and is significant in identifying immune infiltration in tumor tissue and predicting tumor prognosis.

Exploring Influenza A Virus-Induced Lung Injury and Immune Response Based on Humanized Lung-on-Chip.

BACKGROUND: Influenza is an important respiratory tract pathogen that causes substantial seasonal and pandemic morbidity and mortality. The aim of this study was to systematically analyze the transcriptome characteristics of peripheral blood mononuclear cells (PBMCs) after influenza A virus infection by constructing a human lung microarray model composed of PBMCs to simulate the influenza A virus infection process. METHODS: A human lung microarray model was constructed using alveolar epithelial cells, vascular endothelial cells, alveolar macrophages and PBMCs, for simulation of the process of influenza A virus infection. The transcriptome characteristics of PBMCs after influenza A virus infection were analyzed by a single-cell RNA sequencing system. RESULTS: The study could realistically mimic the structure and physiological functions of the alveoli in vitro using immunofluorescence staining and expression of the specific marker. After the influenza A virus infected the upper lung chip channels, the epithelial cells underwent a high inflammatory response and spread to endothelial cells. Under experimental conditions, the Influenza A virus infection did not compromise the integrity of epithelial cells, but caused damage to endothelial cells and barrier dysfunction. Single-cell RNA sequencing of PBMCs showed that B and cluster of differentiation 4 (CD4) T cells played important immunomodulatory roles in response to influenza A virus infection, including significantly activating type I interferon signaling pathway, regulating cytokine and chemokine signaling pathway. Especially genes involved in cellular communication were significantly highly expressed post-infection. CONCLUSIONS: All these results suggested that the interactions among immune cells played a crucial role in endothelial cell injury and immune cell recruitment after influenza virus infection. This lung-on-chip infection model combined with single-cell RNA sequencing provided a unique platform that can closely investigate the lung immune response to influenza A virus infection and new therapeutic strategies for influenza.

Inosine and D-Mannose Secreted by Drug-Resistant Klebsiella pneumoniae Affect Viability of Lung Epithelial Cells.

The antibiotic resistance rates of Klebsiella pneumoniae have been steadily increasing in recent years. Nevertheless, the metabolic features of the drug-resistant Klebsiella pneumoniae and its associated benefits for bacterial pathogenicity are far from expounded. This study aims to unravel the unique physiological and metabolic properties specific to drug-resistant K. pneumoniae. Using scanning electron microscopy (SEM), we observed a thicker extracellular mucus layer around a drug-resistant K. pneumonia strain (Kp-R) than a drug-sensitive K. pneumonia strain (Kp-S). Kp-R also produced more capsular polysaccharide (CPS) and biofilm, and appeared to have a significant competitive advantage when co-cultured with Kp-S. Moreover, Kp-R was easier to adhere to and invade A549 epithelial cells than Kp-S but caused less cell-viability damage according to cell counting kit-8 (CCK-8) tests. Immunofluorescence revealed that both Kp-R and Kp-S infection destroyed the tight junctions and F-actin of epithelial cells, while the damage caused by Kp-S was more severe than Kp-R. We detected the extracellular metabolites secreted by the two strains with UHPLC-Q-TOF MS to explore the critical secretion products. We identified 16 predominant compounds that were differentially expressed. Among them, inosine increased the viability of epithelial cells in a dose-dependent manner, and an A2AR antagonist can abolish such enhancement. D-mannose, which was secreted less in Kp-R, inhibited the viability of A549 cells in the range of low doses. These findings provide potential targets and research strategies for preventing and treating drug-resistant K. pneumoniae infections.