Mediators of Inflammation最新文献

Leprosy continues to be an important public health problem, particularly in endemic regions such as Brazil, India, and Indonesia. Household contacts of multibacillary (MB) patients represent a high-risk group for subclinical infection due to prolonged exposure and high bacillary load. Host biomarkers have emerged as promising tools for identifying early infections and guiding prophylactic interventions. This systematic review aimed to identify and synthesize evidence on inflammatory and immune biomarkers associated with susceptibility to leprosy and disease progression among contacts of index cases, evaluating their potential predictive and diagnostic value. The study followed the Preferred Reporting Items for Systematic Reviews (PRISMA) 2020 guidelines and was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD420251111469). We searched CAPES, SciELO, PubMed, ScienceDirect, EMBASE, Scopus, and EBSCO databases for original studies published between 2012 and 2025, with no language restrictions. Two review authors independently selected studies using the Rayyan software, and methodological quality was assessed using the ROBIS tool. The biomarkers most frequently investigated in the studies were particularly tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-10, which play regulatory roles in the host. Elevated levels of TNF-α, interferon-γ (IFN-γ), IL-6, and IL-4 were associated with a higher risk of subclinical infection among contacts of MB patients, indicating a polyfunctional immune profile. On the other hand, paucibacillary (PB) contacts exhibited lower cytokine activation, suggesting partial protection. Additional promising markers included anti-Mce1A, PGL-I IgM, and CCL4, detected primarily by enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) methods. In summary, inflammatory and immune biomarkers-especially TNF-α, IL-10, IFN-γ, and anti-Mce1A-demonstrate potential as predictive indicators of subclinical leprosy infection. Their combined use may increase risk stratification and allow early therapeutic intervention in endemic settings. However, longitudinal validation studies are required prior to clinical application.

Background: Mitochondrial-related pathways (MRPs) play a crucial role in cancer metabolism and progression; however, their prognostic value in breast cancer (BC) is still poorly understood.

Methods: We integrated multiomics data to investigate the landscape of MRPs in BC. A mitochondria pathways-associated signature (MPAS) was established using multimachine learning framework and interpreted by SHAP analysis across independent BC cohorts. Additionally, a series of functional experiments were employed to explore the role of RNA exonuclease 2 (REXO2) in BC cells.

Results: MRPs are extensively activated in BC at multiomics level. MPAS demonstrates outstanding predictive performance across multiple BC cohorts, with high scores indicating poor clinical outcomes. Moreover, it was observed that high MPAS scores are closely associated with immunosuppressive states and inflammatory microenvironments. SHAP analysis identified REXO2 as a hub factor of MPAS. Cell-based work confirmed that silencing REXO2 greatly inhibited cell proliferation and induced apoptosis in BC.

Conclusions: Our proposed MPAS could effectively evaluate the prognosis and treatment response of BC patients, providing new reference for clinical decision-making. Furthermore, REXO2 regulates cell proliferation and apoptosis, making it a promising potential therapeutic target for inhibiting BC progression.

[This corrects the article DOI: 10.1155/mi/4954551.].

Background: Bone fracture healing is a multifaceted process that involves different stages and intercellular interactions. In this study, we aimed to investigate the effect of Taohong Siwu decoction (TSD) on bone fracture healing and the underlying mechanisms.

Methods: First, a mouse model of femur fracture was constructed, and TSD intervention was administered for durations of 7, 14, and 21 days. Following this, immunofluorescence (IF) was employed to evaluate the expression of CD90 (a marker for mesenchymal stem cells [MSCs]), endomucin (Emcn), and CD31. We also treated MSCs with normal serum and 10% TSD-containing serum to investigate the effects of TSD. Molecular docking was applied to verify the binding of active compounds in TSD to pVon Hippel-Lindau (VHL). Additionally, MSCs were treated with paeoniflorin and 2-methoxyestradiol (2-ME2) to explore the effects of paeoniflorin. Subsequently, mouse aortic endothelial cells were extracted and identified. Furthermore, normally cultured MSCs were cocultured with endothelial cells. MSCs were exposed to control serum, 10% TSD-containing serum, and a combination of 10% TSD-containing serum with 2-ME2. Finally, we administered a combination of 2-ME2 over 21 days to evaluate its effects on the fractured mice.

Results: TSD significantly influenced H-type angiogenesis during the healing process of fractured mice. Compared to the sham group, the model group exhibited lower levels of Emcn, CD90, hypoxia-inducible factor-1 alpha (HIF-1α), and vascular endothelial growth factor (VEGF), while there was an increase in pVHL expression. After 7, 14, and 21 days of TSD intervention, the levels of Emcn, CD90, HIF-1α, VEGF, and pVHL gradually increased, whereas HIF-1α expression decreased. In vitro experiments revealed that TSD enhanced the proliferation and migration of MSCs while inhibiting the ubiquitination of pVHL/HIF-1α. Moreover, ferulic acid, amygdalin, hydroxysafflor yellow A, and paeoniflorin demonstrated a strong affinity for binding with pVHL. Notably, paeoniflorin promoted the proliferation and migration of MSCs through the pVHL/HIF-1α pathway to promote angiogenesis. Furthermore, TSD was found to enhance endothelial angiogenesis in MSCs. In summary, TSD affects H-type angiogenesis and MSCs homing during the healing process of fractured mice through the HIF-1α axis.

Conclusions: TSD regulated MSC-mediated H-type angiogenesis to accelerate fracture healing through VHL/HIF-1α ubiquitination.

Objective: This study, utilising bibliometric analysis combined with bioinformatics approaches, systematically analysed research trends in the fields of osteoporosis (OP) and autophagy (ATG) over the past two decades, with a focus on the emerging frontier of lipid peroxidation (LP). The aim was to reveal its independent role in the OP network, distinct from the ferroptosis framework.

Methods: CiteSpace.6.4.R1 was utilised to perform visualisation analysis on 588 relevant articles from the Web of Science Core Collection, examining countries, institutions, authors, and keywords. Common targets between OP and key burst terms were screened via the Gene Expression Omnibus (GEO) database, followed by the construction of a protein-protein interaction (PPI) network and gene ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Subsequently, we constructed 113 models using 12 machine learning algorithms to screen for feature genes, and the diagnostic value of key targets was validated using receiver operating characteristic (ROC) curves.

Results: Bibliometric analysis indicated that the field entered a period of rapid development from 2018, with China dominating in terms of publication volume and the United States leading in academic influence. Keyword burst detection identified 'LP' as an emerging frontier since 2023. Bioinformatics analysis identified 127 common OP-LP targets, which are enriched in pathways such as NF-κB, eestrogen signalling, and mitophagy. Through machine learning and MCODE module analysis, five key targets were ultimately screened: Amyloid beta precursor protein (APP), Forkhead Box O1 (FOXO1), Forkhead Box O3 (FOXO3), Jun Proto-Oncogene (JUN), and Synuclein Alpha (SNCA). ROC curves demonstrated their good diagnostic efficacy.

Conclusion: This study is the first to integrate bibliometric and bioinformatics methods, revealing the macro-level trends in OP-ATG research and the molecular mechanisms underlying OP-LP crossover. It successfully identified five key OP-LP targets, providing a new perspective for understanding OP mechanisms and developing targeted therapies.

Background: Lung cancer, particularly the non-small cell lung cancer (NSCLC) subtypes lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD), exhibits high heterogeneity and high mortality. This study aimed to explore their tumor microenvironment (TME) features, cellular interactions, and potential therapeutic targets.

Methods: Using scRNA-seq datasets (GSE200972, GSE117570, and GSE127465) and TCGA bulk RNA-seq data, we performed cell clustering, pseudotime trajectory, cell-cell communication, and survival analyses. Batch correction and quality control were applied first, followed by cell type annotation with SingleR, copy number variation inference with InferCNV, and intercellular signaling investigation with CellChat.

Results: Four epithelial signatures (S1-S4) with distinct gene expression profiles were identified, with S3 specific to LUSC and correlated with high malignancy. Pseudotime analysis revealed distinct differentiation trajectories: S2→S1→S3/S4 in LUSC and S4→S1→S2 in LUAD. In LUSC, S3 interacted with macrophages via the SPP1 and MIF ligand-receptor pairs, involving the PI3K-Akt pathways; in LUAD, S4 communicated with neutrophils through MIF, linked to interferon-related pathways. Macrophages played a central role in the TME, with SPP1-CD44 as a key ligand-receptor pair in LUSC and RESISTIN-CAP1 in LUAD. Additionally, CD44 and CD74 expression correlated with prognosis in LUSC and LUAD, respectively.

Conclusion: This study highlights subtype-specific epithelial signatures, identifies key signaling pathways (e.g., MIF), and pinpoints candidate therapeutic targets (CD44, CD74). These discoveries shed new light on the distinct pathogenic mechanisms of LUSC and LUAD and provide actionable insights to facilitate the clinical translation of subtype-specific personalized immunotherapies.

Background: Sepsis-associated acute kidney injury (SA-AKI) is a common and severe complication in critically ill patients, yet the prognostic value of longitudinal white blood cell (WBC) dynamics remains underexplored. Most studies rely on single-timepoint measurements, potentially overlooking important dynamic information for risk stratification.

Objectives: This study aimed to identify distinct WBC trajectory patterns during the first 7 days of ICU admission and evaluate their associations with mortality and secondary AKI in sepsis patients.

Methods: This retrospective cohort study analyzed 15,328 adult sepsis patients from the MIMIC-IV database (version 3.1) between 2008 and 2019. Group-based trajectory modeling (GBTM) was applied to daily WBC counts to identify trajectory subgroups. The primary outcome was 28-day mortality, with secondary outcomes including 90-day mortality and secondary AKI occurring after day 7. Cox proportional hazards regression was used to estimate hazard ratios with 95% confidence intervals. Subgroup analyses evaluated effect consistency across clinically relevant characteristics.

Results: Four distinct WBC trajectory groups were identified: high (n = 812, 5.3%), medium-high (n = 2,830, 18.5%), medium-low (n = 7,121, 46.5%), and low (n = 4,565, 29.8%), with overall mean WBC counts of 24.13, 16.60, 11.24, and 6.64 × 10⁹/L, respectively. The 28-day mortality rates were 31.2%, 20.7%, 14.8%, and 12.9% for high, medium-high, medium-low, and low groups, respectively (log-rank p  < 0.001). Compared with the high group, the low trajectory demonstrated significantly reduced mortality risk (HR: 0.36, 95% CI: 0.31-0.42, p  < 0.001). The high-trajectory group exhibited higher secondary AKI incidence (21.8% vs. 13.0%, p  < 0.001) and greater disease severity. A significant interaction was observed for AKI status (P for interaction = 0.003).

Conclusions: Longitudinal WBC trajectory patterns provide superior prognostic information compared to single-timepoint measurements in sepsis patients, with persistently high WBC levels associated with increased mortality and secondary AKI risk.

Background: Bisphenol A (BPA), a widespread environmental endocrine-disrupting chemical, has been associated with the development and progression of Crohn's disease (CD), yet its precise molecular mechanisms remain unclear. We aimed to systematically elucidate the potential molecular mechanisms by which BPA exacerbates CD and to identify key biomarkers and therapeutic targets.

Methods: BPA-related targets and CD transcriptomic datasets (GSE36807, GSE75214, and GSE95095) were retrieved from public databases. Overlapping genes were identified and subjected to functional enrichment and protein-protein interaction (PPI) network analysis. Multiple machine learning algorithms were employed to screen for core genes, and molecular docking was used to validate the binding affinity between BPA and core proteins. Immune infiltration analysis and regulatory network construction were performed to explore the roles of core genes in the immune microenvironment and post-translational regulation.

Results: A total of 65 overlapping genes between BPA and CD were identified, primarily enriched in pathways related to inflammation, apoptosis, and immune regulation. Machine learning screened five core genes (HGF, IL1R1, MMP1, MMP2, and NTRK2), which demonstrated strong diagnostic performance in independent datasets. Molecular docking revealed strong binding affinity between BPA and these proteins, with the lowest binding energy observed for MMP2 (-8.4 kcal/mol). Immune infiltration analysis indicated significant correlations between core genes and immune cell subsets such as Tr1, Th17, and Tfh cells. Regulatory network analysis identified key transcription factors (e.g., STAT3) and E3 ubiquitin ligases (e.g., SYVN1) involved in gene regulation.

Conclusion: BPA may exacerbate CD progression by dysregulating core genes, such as HGF, IL1R1, MMP1, MMP2, and NTRK2, thereby disrupting inflammatory balance, extracellular matrix remodeling, and immune homeostasis.

Background and objective: Diabetic retinopathy (DR) is a leading cause of vision loss in patients with diabetes mellitus (DM), and its pathogenesis is closely associated with aberrant microglial activation. Although bone marrow mesenchymal stem cell-derived exosomes (BMSC-Exo) and the miRNAs that they carry show therapeutic potential for DR, the specific roles and molecular mechanisms through which let-7b-5p regulates microglial activation after it is delivered by BMSC-Exo remain unclear. This study aimed to elucidate the function and underlying mechanism of BMSC-Exo let-7b-5p in DR.

Methods: A DR mouse model was established by intraperitoneal injection of streptozotocin (STZ), and BV-2 microglia were stimulated with high glucose (HG) to induce activation in vitro. The morphological characteristics of the BMSC-Exo were identified using transmission electron microscopy (TEM). Protein and gene expression levels, as well as microglial activation, were assessed by Western blot, RT-qPCR, and immunofluorescence, respectively. Retinal tissue damage and apoptosis were evaluated using HE staining and TUNEL assays.

Results: BMSC-Exo treatment significantly suppressed the expression of activation markers (Iba1 and TSPO) and inflammatory cytokines (TNF-α, IL-1β, and IL-6) in HG-induced BV-2 cells and DR mouse retinas while alleviating retinal tissue damage and apoptosis. Bioinformatics analysis revealed the downregulation of let-7b-5p in DR. Functional experiments demonstrated that let-7b-5p overexpression enhanced the inhibitory effects of BMSC-Exo on microglial activation, inflammation, and retinal damage, whereas let-7b-5p knockdown attenuated these therapeutic benefits. Mechanistically, BMSC-Exo let-7b-5p inhibited excessive microglial activation and inflammatory responses by targeting the TLR4/ATF4 signaling pathway.

Conclusion: BMSC-Exo deliver let-7b-5p to suppress the TLR4/ATF4 pathway, thereby mitigating microglial activation and inflammation and ultimately delaying DR progression. These findings support the potential of this novel therapeutic strategy for targeted DR treatment.

Background: Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, closely associated with neuroinflammation, immune dysregulation, and gut microbiota imbalance. Gut microbiota-derived metabolites may modulate key targets involved in MS pathogenesis.

Methods: This study integrated network pharmacology, machine learning (ML), and single-cell transcriptome analysis to identify MS-related differentially expressed genes (DEGs) and potential targets of gut microbial metabolites. Feature contributions were evaluated using the SHapley Additive exPlanations (SHAP) method, and causal relationships were validated via Mendelian randomization (MR). Single-cell analysis, molecular docking, and assessments of drug-likeness and toxicity were also performed.

Results: Caspase-3 (CASP3) was identified as a core target interacting with multiple gut microbial metabolites, including L-isoleucine, aromatic lactic acid derivatives, 3-hydroxyphenethyl alcohol, and D-xylose, potentially regulating neuroimmune responses via TNF, MAPK, IL-17, and galectin pathways. Specific microbial taxa, such as Akkermansia, Bacteroides, and Bifidobacterium, were closely associated with these metabolites. The metabolites exhibited favorable drug-likeness and low predicted toxicity, indicating potential therapeutic value.

Conclusion: Gut microbial dysbiosis and its metabolites play a significant role in MS onset and progression, providing a theoretical basis for identifying therapeutic targets and gut-CNS axis interventions. Experimental validation is needed to confirm mechanisms and translational potential.