Vaccine is the most effective way to prevent the spread of communicable diseases, but the immune response induced by it varies greatly between individuals and populations in different regions of the world. Current studies have identified the composition and function of the gut microbiota as key factors in modulating the immune response to vaccination. This article mainly reviews the differences in gut microbiota among different groups of vaccinated people and animals, explores the possible mechanism of vaccine immunity affected by gut microbiota, and reviews the strategies for targeting gut microbiota to improve vaccine efficacy.

Objectives: This study aims to analyze gene expression in lung tissue and lung fibroblasts of patients with systemic sclerosis-associated interstitial lung disease (SSc-ILD) to identify potential biomarkers and therapeutic targets and to examine its possible role in the pathogenesis of SSc-ILD. Patients and methods: We obtained datasets from Gene Expression Omnibus (GEO) database, and used Robust Rank Aggregation to calculate the co-expressed differentially-expressed-genes (DEGs) in three chips, then analyzed the function, signaling pathways and the protein-protein interaction network of the DEGs. Finally, we verified the DEGs related to SSc-ILD by three databases of Comparative Toxicogenomics Database (CTD), GENE, and DisGeNET, respectively. Results: There were 16 co-expressed DEGs related to SSc-ILD in three GEO series, of which six genes were upregulated, and 10 genes were downregulated. The CTD included 29,936 genes related to SSc, and the GENE and DisGeNET databases had 429 genes related to SSc. Conclusion: The results of gene differential expression analysis suggest that interleukin-6, chemokine ligand 2, intercellular adhesion molecule 1, tumor necrosis factor alpha-induced protein 3, pentraxin 3, and cartilage oligomeric matrix protein may be implicated in the pathogenesis of SSc-ILD and are expected to be potential biomarkers and therapeutic targets for SSc-ILD.

DNA methylation age prediction from incomplete profiles requires evaluation under empirical and random missingness. We evaluated whole‐blood chronological‐age prediction using 524 development and 132 held‐out GSE40279 samples and an external GSE73103 cohort ( n = 355). Feature‐stability analysis across 750 prespecified perturbation conditions identified a 209‐CpG primary panel and a 52‐CpG stringent sensitivity subset. The primary predictor combined five‐nearest‐neighbor reconstruction (KNN5) with Ridge regression. In the internal holdout, intact‐profile prediction achieved a mean absolute error of 4.24 years, a root‐mean‐square error (RMSE) of 5.38 years, and Pearson r = 0.934. Under masks derived from 42 empirical templates of formalin‐fixed paraffin‐embedded detection failure, KNN5 reduced RMSE by 0.365 years relative to development‐set mean replacement (95% bootstrap interval for the difference, −0.546 to −0.205), with larger reductions at higher missingness burdens. The reconstruction advantage persisted in complementary development analyses after randomization preserving both sample‐level and CpG‐level failure counts. External predictions remained associated with chronological age ( r = 0.835), despite age‐dependent calibration bias. Mixture analyses showed that background accuracy was central to target recovery as mixture asymmetry increased. These findings support local reconstruction within a stability‐selected CpG panel for chronological‐age prediction under the evaluated empirical and random missingness conditions.

Our previous work identified several differentially expressed miRNAs (DEmiRNAs) in plasma exosomes from Takayasu’s arteritis (TAK) patients. This study aimed to validate these findings and explore the correlation between DEmiRNAs and clinical parameters in untreated TAK. Plasma exosomes were isolated from 30 untreated TAK patients and 20 healthy controls. qPCR was used to quantify miR-34a-5p, miR-143-3p, miR-22-3p, miR-200c-3p, and miR-21-5p expression. Correlations between miRNA levels, clinical data, inflammation markers, and T helper cell frequencies were analyzed. The target genes of validated DEmiRNAs were identified using mirDIP, and pathway enrichment analysis was performed using GO/KEGG. The effect of validated DEmiRNAs on the MAPK pathway and proliferation in human aortic endothelial cells (HAECs) was investigated in vitro. Only miR-200c-3p expression was validated as significantly downregulated in plasma exosomes from untreated TAK patients. Lower miR-200c-3p levels correlated negatively with ITAS-2010 scores and were associated with relapsed disease. MiR-200c-3p levels also negatively correlated with circulating Th17.1 cell frequencies. In vitro, the TAK exosome treatment activated ERK1/2 and JNK pathways and promoted HAEC proliferation, which was inhibited by the miR-200c-3p mimic. The pathway enrichment analysis showed that the MAPK pathway may be involved. This study confirms the reduced miR-200c-3p expression in plasma exosomes from TAK patients, suggesting its potential as a biomarker for vascular inflammation. MiR-200c-3p may exert protective effects in TAK by suppressing MAPK pathway activation and EC proliferation.