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Background: Asthma is a heterogeneous inflammatory disease with two main clinical endotypes: type 2 (T2) high and low asthma. The plasticity and autophagy in dendritic cells (DCs) influence T helper (Th)2 or Th17 differentiation to regulate asthma endotypes. Enhanced autophagy in DCs fosters Th2 differentiation in allergic environments, while reduced autophagy favors Th17 cell differentiation in sensitized and infected environments. Autophagy regulation in DCs involves interaction with various pathways like G protein‐coupled receptor (GPCR), mammalian target of rapamycin (mTOR), or phosphoinositide 3‐kinase (PI3K) pathway. However, specific molecules within DCs influencing asthma endotypes remain unclear. Methods: Gene expression data series (GSE) 64896, 6858, 2276, and 55247 were obtained from gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between CD103+ and CD11b+ DCs after induction by ovalbumin (OVA) and lipopolysaccharide (LPS) were analyzed using GEO2R. DEGs were examined through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) analyses. The hub gene network was construct with STRING database and Cytoscape. Autophagy differences in DCs and the selected hub gene in GSE6858, GSE2276, and GSE55247 were evaluated using student t tests. Results: Our analysis identified 635 upregulated and 360 downregulated genes in CD11b+ DCs, compared to CD103+ DCs. These DEGs were associated with "PI3K‐AKT signaling pathway," "Ras signaling pathway," and so forth. Thirty‐five hub genes were identified, in which G protein subunit gamma transduction protein 2 (Gngt2) in CD11b+ DCs exhibited a relatively specific increase in expression associated with autophagy defects under the induction environment similar to T2 low asthma model. No significant difference was found in lung Gngt2 expression between T2 high asthma model and control group. Conclusion: Our analysis suggested Gngt2 acted as an adapter molecule that inhibited autophagy, promoting Th17‐mediated airway inflammation via the GPCR pathway in a T2 low asthma mice model. Targeting this pathway provides new asthma treatment strategies in preclinical research. [ABSTRACT FROM AUTHOR]

Polyacrylamide (PAM)-glycerol (Gly)-lithium chloride (LiCl) hydrogel was prepared by salt solution immersion method, using PAM as the hydrogel matrix, Gly as the moisturizing factor and LiCl as the water absorption factor. The structure and performance of the hydrogel were characterized by scanning electron microscope, energy dispersive spectrometer, X-ray photoelectron spectrometer, Fourier infrared spectrometer, etc. Meanwhile, the effect of its application in a portable cigar moisturizing bag on the regulation of micro environment humidity was explored. The results showed that the PAM-Gly-LiCl hydrogel possessed excellent transparency and mechanical properties, with light transmittance of 90%, the maximum compression strain of 41%, compression strength of 1. 1 MPa, elongation breaking rate of 1100% and breaking strength of 0. 25 MPa. The hydrogel also displayed excellent water retention and humidity control performance. Owing to a high proportion of combined water, it could stably realize the humidity control process under different humidity environmental conditions. The humidity control range was 25%-95% of the relative humidity and kept for 500 h. The hydrogel could be applied to design as a portable cigar moisturizing bag. It could quickly sense changes in environmental humidity and make intelligent responses, stabilizing the microenvironment relative humidity inside the bag at around 65% and maintaining it for more than a week. [ABSTRACT FROM AUTHOR]

Mitochondrial DNA (mtDNA) somatic mutations play important roles in the initiation and progression of cancer. Although next‐generation sequencing (NGS) of paired tumor and control samples has become a common practice to identify tumor‐specific mtDNA mutations, the unique nature of mtDNA and NGS‐associated sequencing bias could cause false‐positive/‐negative somatic mutation calling. Additionally, there are clinical scenarios where matched control tissues are unavailable for comparison. Therefore, a novel approach for accurately identifying somatic mtDNA variants is greatly needed, particularly in the absence of matched controls. In this study, the ground truth mtDNA variants orthogonally validated by triple‐paired tumor, adjacent nontumor, and blood samples were used to develop mitoSomatic, a random forest‐based machine learning tool. We demonstrated that mitoSomatic achieved area under the curve (AUC) values over 0.99 for identifying somatic mtDNA variants without paired control in three tumor types. In addition, mitoSomatic was also applicable in nontumor tissues such as adjacent nontumor and blood samples, suggesting the flexibility of mitoSomatic's classification capability. Furthermore, analysis of triple‐paired samples identified a small group of variants with uncertain somatic/germline origin, whereas application of mitoSomatic significantly facilitated the prediction of their possible source. Finally, a control‐free evaluation of the public pan‐cancer NGS dataset with mitoSomatic revealed a substantial number of variants that were probably misclassified by conventional tumor‐control comparison, further emphasizing the usefulness of mitoSomatic in application. Taken together, our study demonstrates that mitoSomatic is valuable for accurately identifying somatic mtDNA variants in mtDNA NGS data without paired controls, applicable for both tumor and nontumor tissues. [ABSTRACT FROM AUTHOR]

Haplogroups and single‐nucleotide polymorphisms (SNP) of mitochondrial DNA (mtDNA) were associated with the prognosis of many types of cancer patients. However, whether mtDNA haplogroups contribute to clinical outcomes of colorectal cancer (CRC) in Chinese population remains to be determined. In this study, mtDNA of tissue samples from 445 CRC patients from Northwestern China was sequenced to evaluate the association between haplogroup and prognosis. The mtDNA sequencing data of 1015 CRC patients from Southern China were collected for validation. We found patients with mtDNA haplogroup M7 had a significantly higher death risk when compared with patients with other haplogroups in both Northwestern (Hazard ratio [HR] = 3.093, 95% CI = 1.768–5.411, p < 0.001) and Southern (HR = 1.607, 95% CI = 1.050–2.459, p = 0.029) China. Then, a haplogroup M7–based mtSNP classifier was selected by using LASSO Cox regression analysis. A nomogram comprising the mtSNP classifier and clinicopathological variables was developed to predict the prognosis of CRC patients (area under the curve [AUC] 0.735, 95% CI = 0.679–0.791). Furthermore, patients with high‐ and low‐risk scores calculated by the haplogroup M7–based mtSNP classifier exhibited significantly different overall survival (OS) and recurrence‐free survival (RFS) (all p < 0.001). Finally, RNA‐seq and immunohistochemical analyses indicated the poor prognosis of patients with haplogroup M7 may be related to mitochondrial dysfunction and immune abnormalities in CRC tissues. In conclusion, the haplogroup M7 and haplogroup M7–based mtSNP classifier seems to be a practical and reliable prognostic predictor for CRC patients, which provides a potential tool of clinical decision‐making for patients with haplogroup M7 in Chinese population. [ABSTRACT FROM AUTHOR]