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Exposure to particulate matter (PM) is associated with increased incidence of respiratory diseases. The present study aimed to investigate the roles of fibroblast growth factor 10 (FGF10) in PM-induced lung injury. Mice were intratracheally instilled with FGF10 or phosphate-buffered saline at one hour before instillation of PM for two consecutive days. In addition, the anti-inflammatory impact of FGF10 in vitro and its effect on the high-mobility group box 1 (HMGB1)-toll-like receptor 4 (TLR4) pathway was investigated. It was found that PM exposure is associated with increased inflammatory cell infiltration into the lung and increased vascular protein leakage, while FGF10 pretreatment attenuated both of these effects. FGF10 also decreased the PM-induced expression of interleukin (IL)-6, IL-8, tumor necrosis factor-α and HMGB1 in murine bronchoalveolar lavage fluid and in the supernatants of human bronchial epithelial cells exposed to PM. FGF10 exerted anti-inflammatory and cytoprotective effects by inhibiting the HMGB1-TLR4 pathway. These results indicate that FGF10 may have therapeutic values for PM-induced lung injury.

Background The BOLA gene family, comprising three members, is mainly involved in regulating intracellular iron homeostasis. Emerging evidence suggests that BolA family member 2 plays a vital role in tumorigenesis and hepatic cellular carcinoma progression. However, there was less known about its role in ovarian cancer. Methods In the present study, we investigated the expression profiles, prognostic roles, and genetic alterations of three BolA family members in patients with ovarian cancer through several public databases, containing Oncomine and Gene Expression Profiling Interactive Analysis, Human Protein Atlas, Kaplan–Meier plotter and cBioPortal. Then, we constructed the protein-protein interaction networks of BOLA proteins and their interactors by using the String database and Cytoscape software. In addition, we performed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment by the Annotation, Visualization, and Integrated Discovery database. Finally, we explored the mechanisms underlying BolA family members’ involvement in OC by using gene set enrichment analysis. Results The mRNA and protein expression levels of BOLA2 and BOLA3 were heavily higher in ovarian cancer tissues than in normal ovarian tissues. Dysregulated mRNA expressions of three BolA family members were significantly associated with prognosis in overall or subgroup analysis. Moreover, genetic alterations also occurred in three BolA family members in ovarian cancer. GO analysis indicated that BolA family members might regulate the function of metal ion binding and protein disulfide oxidoreductase activity. Gene set enrichment analysis indicated that BolA family members were mainly associated with oxidative phosphorylation, proteasome, protein export, and glutathione metabolism in ovarian cancer. Conclusion In brief, our finding may contribute to increasing currently limited prognostic biomarkers and treatment options for ovarian cancer.

Objective Development of biofluid‐based biomarkers is attractive for the diagnosis of chronic obstructive pulmonary disease (COPD) but still lacking. Thus, here we aimed to identify serum metabolic biomarkers for the diagnosis of COPD. Methods In this study, we investigated serum metabolic features between COPD patients (n = 54) and normal individuals (n = 74) using a 1H NMR‐based metabolomics approach and developed an integrated method of least‐squares support vector machine (LS‐SVM) and serum metabolic biomarkers to assist COPD diagnosis. Results We observed a hypometabolic state in serum of COPD patients, as indicated by decreases in N‐acetyl‐glycoprotein (NAG), lipoprotein (LOP, mainly LDL/VLDL), polyunsaturated fatty acid (pUFA), glucose, alanine, leucine, histidine, valine, and lactate. Using an integrated method of multivariable and univariate analyses, NAG and LOP were identified as two important metabolites for distinguishing between COPD patients and controls. Subsequently, we developed a LS‐SVM classifier using these two markers and found that LS‐SVM classifiers with linear and polynomial kernels performed better than the classifier with RBF kernel. Linear and polynomial LS‐SVM classifiers can achieve the total accuracy rates of 80.77% and 84.62% and the AUC values of 0.87 and 0.90 for COPD diagnosis, respectively. Conclusions This study suggests that artificial intelligence integrated with serum metabolic biomarkers has a great potential for auxiliary diagnosis of COPD., Development of biofluid‐based biomarkers is of great importance and interest for the diagnosis of chronic obstructive pulmonary disease (COPD) but still lacking. Here, we identified N‐acetyl‐glycoprotein (NAG) and lipoprotein (LOP) as two important metabolic biomarkers for distinguishing between COPD patients and healthy subjects. Then, we developed a LS‐SVM classifier based on NAG and LOP and found that LS‐SVM classifiers with linear and polynomial kernels performed better than the classifier with RBF kernel. Linear and polynomial LS‐SVM classifiers can achieve the total accuracy rates of 80.77% and 84.62% and the AUC values of 0.87 and 0.90 for COPD diagnosis, respectively. Thus, our study suggests that artificial intelligence with serum metabolic biomarkers might be a promising tool for auxiliary diagnosis of COPD.

Here, a fully integrated multicolor immunosensor was developed for sensitive and reliable semiquantitative analysis of HIV-1 p24, which integrates the multistep reactions of horseradish peroxidase (HRP)-linked immunoassay and gold nanorod (AuNR)-based multicolor assay into a single microfluidic chip. The HRP-linked immunoassay functions by moving magnetic beads bound to a capture antibody through different aqueous phases containing immunoassay reagents. HRP-catalyzed oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) is used to mediate AuNRs etching for producing various color changes. Multiple etching processes can be activated by simple mixing of the reagents from the reagent storage reservoir. The fully integrated strategy with sample-in answer-out capability is initiated by simple chip manipulation and finally concluded by converting recognition of antigen-antibody into a vivid color variation for direct visualization and semiquantitative analysis. By bare eye observation, our integrated multicolor immunosensor allows sensitive and reliable semiquantitative analysis of HIV-1 p24 within 1 h. The microfluidic chip device demonstrated here simplifies the operation significantly and thus allows broader application of a multicolor immunosensor for point of care (POC) testing in low-resource settings.

Central nervous system (CNS) diseases are some of the most difficult to treat because the blood-brain barrier (BBB) almost entirely limits the passage of many therapeutic drugs into the CNS. Gene therapy based on the adeno-associated virus (AAV) vector has the potential to overcome this problem. For example, an AAV serotype AAV9 has been widely studied for its ability to cross the BBB to transduce astrocytes, but its efficiency is limited. The emergence of AAV directed evolution technology provides a solution, and the variants derived from AAV9 directed evolution have been shown to have significantly higher crossing efficiency than AAV9. However, the mechanisms by which AAV crosses the BBB are still unclear. In this review, we focus on recent advances in crossing the blood-brain barrier with AAV vectors. We first review the AAV serotypes that can be applied to treating CNS diseases. Recent progress in possible AAV crossing the BBB and transduction mechanisms are then summarized. Finally, the methods to improve the AAV transduction efficiency are discussed.

There has been significant progress in gene and microRNA (miRNA) research with regard to the morbidity of Hodgkin's lymphoma (HL). However, the regulatory mechanisms of genes and miRNAs have yet to be determined. In the current study, the regulatory association between genes, miRNAs and transcription factors (TFs) was investigated to gain an understanding of the mechanisms and key pathways of HL. The association between TFs and miRNAs, miRNAs and target genes and miRNA and its host gene was examined. To show the regulatory correlation clearly, three regulatory networks were hierarchically constructed: Differentially expressed, associated and global networks. Following comparison and analysis of the similarities and differences among the three networks, a number of key pathways, which showed self-adaptation associations were identified. This included NFκB1 and hsa-miR-9, hsa-miR-196a-1 and its host gene HOXB7, which separately forms a self-adaptation association. The differentially expressed network illuminated the pathogenesis of HL. In addition, the associated network further described the regulatory mechanism associated with HL, including prevention, diagnosis, development and therapy. The current study systematically explains the regulatory mechanisms of HL and supplies comprehensive data associated with HL for further studies. With increasing knowledge of the occurrence, mechanism, improvement, metastasis and treatment, an increased understanding of HL may be achieved.