Mediators of Inflammation

The current asthma therapies are inadequate for many patients with severe asthma. Pyrroloquinoline quinone (PQQ) is a naturally-occurring redox cofactor and nutrient that can exert a multitude of physiological effects, including anti-inflammatory and antioxidative effects. We sought to explore the effects of PQQ on allergic airway inflammation and reveal the underlying mechanisms. In vitro, the effects of PQQ on the secretion of epithelial-derived cytokines by house dust mite- (HDM-) incubated 16-HBE cells and on the differentiation potential of CD4+ T cells were investigated. In vivo, PQQ was administered to mice with ovalbumin- (OVA-) induced asthma, and lung pathology and inflammatory cell infiltration were assessed. The changes in T cell subsets and signal transducers and activators of transcription (STATs) were evaluated by flow cytometry. Pretreatment with PQQ significantly decreased HDM-stimulated thymic stromal lymphopoietin (TSLP) production in a dose-dependent manner in 16-HBE cells and inhibited Th2 cell differentiation in vitro. Treatment with PQQ significantly reduced bronchoalveolar lavage fluid (BALF) inflammatory cell counts in the OVA-induced mouse model. PQQ administration also changed the secretion of IFN-γ and IL-4 as well as the percentages of Th1, Th2, Th17, and Treg cells in the peripheral blood and lung tissues, along with inhibition the phosphorylation of STAT1, STAT3, and STAT6 while promoting that of STAT4 in allergic airway inflammation model mice. PQQ can alleviate allergic airway inflammation in mice by improving the immune microenvironment and regulating the JAK-STAT signaling pathway. Our findings suggest that PQQ has great potential as a novel therapeutic agent for inflammatory diseases, including asthma.

N6-methyladenosine (m6A) modification is the most prevalent chemical modification in eukaryotic mRNA and is associated with the development of various immune diseases. However, the role of m6A methylation in rheumatoid arthritis (RA) development is unclear. We preliminarily explored the role of m6A methylation-related mRNAs in RA for its clinical application. The discovery of m6A methylation-modifying genes in this study may provide a fresh perspective on the development of drugs for RA treatment. High-throughput sequencing combined with methylated RNA immunoprecipitation (MeRIP-seq) and RNA sequencing were used to assess whole-transcriptome m6A modifications in the synovium of patients with RA. The relationship between m6A-modified target genes and RA inflammation and macrophages was determined. The expression of the m6A-modified significant transcript-enriched inflammatory signaling pathway was assessed through animal experiments. Differentially expressed m6A genes were correlated with macrophage activation involved in immune response, vascular endothelium, MAPK signaling pathway, PI3K − Akt signaling pathway, and other inflammatory processes. Furthermore, combined analysis with m6A-seq and RNA-seq revealed 120 genes with significant changes in both m6A modification and mRNA expression. We selected the top 3 candidate mRNAs that were upregulated and downregulated simultaneously. The expression of phosphatase and tensin homolog deleted on chromosome ten (PTEN) mRNA and protein in RA patients was lower than that in healthy control (HC). SHC-binding protein 1 (SHCBP1) and neurexophilin-3 (NXPH3) mRNA expressions were increased in RA patients. The expression of M1 macrophages was increased in RA patients. RA markers are such as rheumatoid factor (RF) and peptide containing citrulline (CCP). Further animal experiments showed that the expression of synovial MAPK, PI3K, and Akt1 proteins in the RA model was increased, and the PTEN, p-PTEN protein expression was decreased. PI3K, Akt1, PTEN, and p-PTEN were correlated to RA joint inflammation. This study revealed a unique pattern of differential m6A methylation modifications in RA and concluded that m6A modification is related to the occurrence of RA synovial inflammation.

Head and neck cancer is the sixth most frequent cancer all over the world, with the majority of subtypes of head and neck squamous cell carcinoma (HNSCC). Cellular senescence-associated genes have been confirmed to play a critical role in cancer and have the potential to be prognostic biomarkers for cancer. Clinical information of HNSCC samples and expression data were acquired from public databases. Expression profiles of genes related to cellular senescence were used to identify molecular subtypes by consensus clustering. To screen differentially expressed genes (DEGs) between different subtypes, differential analysis was performed. We used the univariate Cox regression to identify prognostic DEGs and performed least absolute shrinkage and selection operator (LASSO) to optimize and construct a prognostic model. CIBERSORT, ESTIMATE, and TIDE tools were applied to estimate immune characteristics. Four molecular subtypes were established based on cellular senescence-associated genes. Differential prognosis was observed among different subtypes with C4 having the longest overall survival and C1 having the worst prognosis. C4 subtype also showed the highest immune infiltration. We screened a total of eight cellular senescence prognosis-related genes and established a cellular senescence-related signature score (CSRS.Score) that could stratify samples into high-CSRS.Score and low-CSRS.Score groups. The high-CSRS.Score group had worse prognosis, lower immune infiltration, and lower response to immunotherapy. We further improved the prognostic model and survival prediction by combining CSRS.Score with clinicopathological features using a decision tree model, which had high predictive accuracy and survival prediction. This study demonstrated an important role of cellular senescence in HNSCC. The identified eight cellular senescence-associated genes have the potential to provide ideas for adjuvant treatment and personalized treatment of HNSCC patients.

Objective. The alanine aminotransferase/aspartate aminotransferase (ALT/AST) ratio is thought to be related to metabolic disorders and insulin resistance. Type 2 diabetes mellitus (T2DM) is a high-risk population for low muscle mass. This study was performed to evaluate the association between ALT/AST and muscle mass in subjects with T2DM. Method. This cross-sectional study enrolled 1068 subjects (566 males and 502 females) with T2DM. General information, medical history, and blood samples were collected. Skeletal muscle index (SMI) was detected using dual-energy X-ray absorptiometry. Logistic regression analysis was utilized to determine the correlation of ALT/AST and low muscle mass in subjects with T2DM. Multiple linear regression analysis was utilized to evaluate the association between ALT/AST, SMI and other metabolic characteristics. Result. Of all subjects, 115 men (20.3%) and 71 women (14.1%) presented low muscle mass. ALT/AST was related to an increased risk for low muscle mass in both genders. Multiple linear regression analysis displayed that SMI was negatively associated with ALT/AST, age, glycosylated hemoglobin (HbA1c), and high-density lipoprotein cholesterol (HDL) in male group. While in female group, SMI was positively associated with systolic blood pressure (SBP) and negatively associated with ALT/AST and age. Furthermore, ALT/AST was associated with age and BMI in both genders. Conclusion. ALT/AST was negatively associated with muscle mass in subjects with T2DM.

Background. Melanomas, the most common human malignancy, are primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy, and histopathological examination. We aimed to systematically review the performance and quality of machine learning-based methods in distinguishing melanoma and benign nevus in the relevant literature. Method. Four databases (Web of Science, PubMed, Embase, and the Cochrane library) were searched to retrieve the relevant studies published until March 26, 2022. The Predictive model Deviation Risk Assessment tool (PROBAST) was used to assess the deviation risk of opposing law. Result. This systematic review included thirty researches with 114007 subjects and 71 machine learning models. The convolutional neural network was the main machine learning method. The pooled sensitivity was 85% (95% CI 82–87%), the specificity was 86% (82–88%), and the -index was 0.87 (0.84–0.90). Conclusion. The findings of our study showed that ML algorithms had high sensitivity and specificity for distinguishing between melanoma and benign nevi. This suggests that state-of-the-art ML-based algorithms for distinguishing melanoma from benign nevi may be ready for clinical use. However, a large proportion of the earlier published studies had methodological flaws, such as lack of external validation and lack of clinician comparisons. The results of these studies should be interpreted with caution.

Background. Polydatin (PD) is the primary active compound in Polygonum cuspidatum Sieb and has been demonstrated to exert anti-inflammatory and neuroprotective activities. In the present study, we aimed to explore the therapeutic mechanisms of PD against chemotherapy-induced neuropathic pain. Methods. The putative targets of PD were obtained from the CTD and SwissTargetPrediction databases. Neuropathic pain- and VIN-related targets were collected from the CTD and GeneCards databases. Subsequently, the intersection targets were obtained using the Venn tool, and the protein-protein interaction (PPI) was constructed by the STRING database. GO and KEGG enrichment analyses were performed to investigate the biological functions of the intersection targets. Further, a rat model of VIN-induced neuropathic pain was established to confirm the reliability of the network pharmacology findings. Results. A total of 46 intersection targets were identified as potential therapeutic targets, mainly related to neuroinflammation. KEGG pathway analysis indicated that the IL-17 signaling pathway was involved in the mechanism of the antinociceptive effect of PD. PPI network analysis indicated that RELA, IL-6, TP53, MAPK3, and MAPK1 were located at crucial nodes in the network. Additionally, PD exerted an antinociceptive effect by increasing the nociceptive threshold. The results of qRT-PCR, western blot, and immunohisochemistry indicated that PD inhibited the IL-6, TP53, and MAPK1 levels in VIN-induced neuropathic pain rats. Conclusions. Overall, this research provided evidence that suppressing inflammatory signaling pathways might be a potential mechanism action of PD’s antinociceptive effect against VIN-induced neuropathic pain.