Data Mining Mycobacterium tuberculosis

Tuberculosis (TB) is one of the deadliest infectious diseases worldwide. In Mycobacterium tuberculosis, changes in gene expression are highly variable and involve many genes, so traditional single-gene screening of M. tuberculosis targets has been unable to meet the needs of clinical diagnosis. In this study, using the National Center for Biotechnology Information (NCBI) GEO Datasets, whole blood gene expression profile data were obtained in patients with active pulmonary tuberculosis. Linear model-experience Bayesian statistics using the Limma package in R combined with t-tests were applied for nonspecific filtration of the expression profile data, and the differentially expressed human genes were determined. Using DAVID and KEGG, the functional analysis of differentially expressed genes (GO analysis) and the analysis of signaling pathways were performed. Based on the differentially expressed gene, the transcriptional regulatory element databases (TRED) were integrated to construct the M. tuberculosis pathogenic gene regulatory network, and the correlation of the network genes with disease was analyzed with the DAVID online annotation tool. It was predicted that IL-6, JUN, and TP53, along with transcription factors SRC, TNF, and MAPK14, could regulate the immune response, with their function being extracellular region activity and protein binding during infection with M. tuberculosis

Preventive Effects of Collagen Peptide from Deer Sinew on Bone Loss in Ovariectomized Rats

Deer sinew (DS) has been used traditionally for various illnesses, and the major active constituent is collagen. In this study, we assessed the effects of collagen peptide from DS on bone loss in the ovariectomized rats. Wister female rats were randomly divided into six groups as follows: sham-operated (SHAM), ovariectomized control (OVX), OVX given 1.0 mg/kg/week nylestriol (OVX + N), OVX given 0.4 g/kg/day collagen peptide (OVX + H), OVX given 0.2 g/kg/day collagen peptide (OXV + M), and OVX given 0.1 g/kg/day collagen peptide (OXV + L), respectively. After 13 weeks of treatment, the rats were euthanized, and the effects of collagen peptide on body weight, uterine weight, bone mineral density (BMD), serum biochemical indicators, bone histomorphometry, and bone mechanics were observed. The data showed that BMD and concentration of serum hydroxyproline were significantly increased and the levels of serum calcium, phosphorus, and alkaline phosphatase were decreased. Besides, histomorphometric parameters and mechanical indicators were improved. However, collagen peptide of DS has no effect on estradiol level, body weight, and uterine weight. Therefore, these results suggest that the collagen peptide supplementation may also prevent and treat bone loss

Improved YOLOv7 Target Detection Algorithm Based on UAV Aerial Photography

With the rapid development of remote sensing technology, remote sensing target detection faces many problems; for example, there is still no good solution for small targets with complex backgrounds and simple features. In response to the above, we have added dynamic snake convolution (DSC) to YOLOv7. In addition, SPPFCSPC is used instead of the original spatial pyramid pooling structure; the original loss function was replaced with the EIoU loss function. This study was evaluated on UAV image data (VisDrone2019), which were compared with mainstream algorithms, and the experiments showed that this algorithm has a good average accuracy. Compared to the original algorithm, the mAP0.5 of the present algorithm is improved by 4.3%. Experiments proved that this algorithm outperforms other algorithms

Data Mining Mycobacterium tuberculosis Pathogenic Gene Transcription Factors and Their Regulatory Network Nodes

Tuberculosis (TB) is one of the deadliest infectious diseases worldwide. In Mycobacterium tuberculosis, changes in gene expression are highly variable and involve many genes, so traditional single-gene screening of M. tuberculosis targets has been unable to meet the needs of clinical diagnosis. In this study, using the National Center for Biotechnology Information (NCBI) GEO Datasets, whole blood gene expression profile data were obtained in patients with active pulmonary tuberculosis. Linear model-experience Bayesian statistics using the Limma package in R combined with t-tests were applied for nonspecific filtration of the expression profile data, and the differentially expressed human genes were determined. Using DAVID and KEGG, the functional analysis of differentially expressed genes (GO analysis) and the analysis of signaling pathways were performed. Based on the differentially expressed gene, the transcriptional regulatory element databases (TRED) were integrated to construct the M. tuberculosis pathogenic gene regulatory network, and the correlation of the network genes with disease was analyzed with the DAVID online annotation tool. It was predicted that IL-6, JUN, and TP53, along with transcription factors SRC, TNF, and MAPK14, could regulate the immune response, with their function being extracellular region activity and protein binding during infection with M. tuberculosis

Determination of eight lignans in <i>Schisandra chinensis</i> and <i>Schisandra sphenanthera</i>

A high performance liquid chromatography method for the determination of eight lignans contents in Schisandra chinensis and Schisandra sphenanthera was developed. The chromatographic column was Agilent ZORBAX 300SB-C18 column (4.6 mm × 250 mm?5 ?m). The mobile phase was methanol-water, a gradient elution was conducted and the detection wavelength was at 230 nm. The results showed that the recovery rate of eight lignans was 92.2-102.9% and RSD was 1.5-4.2%. The established content determination method was simple, sensitive, accurate and stable, and can be used to control the quality of S. chinensis and S. sphenanthera.

G Protein-Coupled Receptor 109A and Host Microbiota Modulate Intestinal Epithelial Integrity During Sepsis

The intestinal epithelial barrier is important to mucosal immunity, although how it is maintained after damage is unclear. Here, we show that G protein-coupled receptor 109A (GPR109A) supports barrier integrity and decreases mortality in a mouse cecum ligation and puncture (CLP) sepsis model. Data from 16S RNA sequencing showed that the intestinal microbiota of WT and Gpr109a−/− mice clustered differently and their compositions were disrupted after CLP surgery. GPR109A-deficient mice showed increased mortality, intestinal permeability, altered inflammation, and lower tight junction gene expression. After eliminating the intestinal flora with antibiotics, all experimental mice died within 48 h of CLP surgery. This demonstrates the critical role of the gut microbiota in CLP-induced sepsis. Importantly, mortality and other pathologies in the model were decreased after Gpr109a−/− mice received WT gut microbiota. These findings indicate that GPR109A regulates the gut microbiota, contributing to intestinal epithelial barrier integrity and decreased mortality in CLP-induced sepsis

Effect of α-Tocopherol on the Physicochemical Properties of Sturgeon Surimi during Frozen Storage

This study investigated the effects of &#945;-tocopherol (&#945;-TOH) on the physicochemical properties of sturgeon surimi during 16-week storage at &#8722;18 &#176;C. An aliquot of 0.1% (w/w) of &#945;-TOH was added into the surimi and subjected to frozen storage, and 8% of a conventional cryoprotectant (4% sorbitol and 4% sucrose, w/w) was used as a positive control. Based on total viable count, pH and whiteness, &#945;-TOH exhibited a better protection for frozen sturgeon surimi than cryoprotectant during frozen storage. According to soluble protein content, carbonyl content, total sulfhydryl content, and surface hydrophobicity, &#945;-TOH and cryoprotectant showed the same effects on retarding changes of proteins. The results of breaking force, deformation, gel strength, water-holding capacity and microstructure of sturgeon surimi indicated that the gel properties of frozen sturgeon surimi were retained by &#945;-TOH. Our results suggest that &#945;-TOH is an attractive candidate to maintain the quality of sturgeon surimi during frozen storage

Sodium Butyrate Inhibits Inflammation and Maintains Epithelium Barrier Integrity in a TNBS-induced Inflammatory Bowel Disease Mice Model

G Protein Coupled Receptor 109A (GPR109A), which belongs to the G protein coupled receptor family, can be activated by niacin, butyrate, and β-hydroxybutyric acid. Here, we assessed the anti-inflammatory activity of sodium butyrate (SB) on 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced colitis mice, an experimental model that resembles Crohn's disease, and explored the potential mechanism of SB in inflammatory bowel disease (IBD). In vivo, experimental GPR109a−/− and wild-type (WT) mice were administered SB (5 g/L) in their drinking water for 6 weeks. The mice were then administered TNBS via rectal perfusion to imitate colitis. In vitro, RAW246.7 macrophages, Caco-2 cells, and primary peritoneal macrophages were used to investigate the protective roles of SB on lipopolysaccharide (LPS)-induced inflammatory response and epithelium barrier dysfunction. In vivo, SB significantly ameliorated the inflammatory response and intestinal epithelium barrier dysfunction in TNBS-induced WT mice, but failed to provide a protective effect in TNBS-induced GPR109a−/− mice. In vitro, pre-treatment with SB dramatically inhibited the expression of TNF-α and IL-6 in LPS-induced RAW246.7 macrophages. SB inhibited the LPS-induced phosphorylation of the NF-κB p65 and AKT signaling pathways, but failed to inhibit the phosphorylation of the MAPK signaling pathway. Our data indicated that SB ameliorated the TNBS-induced inflammatory response and intestinal epithelium barrier dysfunction through activating GPR109A and inhibiting the AKT and NF-κB p65 signaling pathways. These findings therefore extend the understanding of GPR109A receptor function and provide a new theoretical basis for treatment of IBD. Keywords: GPR109A, SB, TNBS, IBD, Inflammation, Epithelium barrie

A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia

Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults, with an unfavourable outcome and a high rate of recurrence due to its heterogeneity. Dysregulation of fatty acid metabolism plays a crucial role in the development of several tumours. However, the value of fatty acid metabolism (FAM) in the progression of AML remains unclear. In this study, we obtained RNA sequencing and corresponding clinicopathological information from the TCGA and GEO databases. Univariate Cox regression analysis and subsequent LASSO Cox regression analysis were utilized to identify prognostic FAM-related genes and develop a potential prognostic risk model. Kaplan-Meier analysis was used for prognostic significances. We also performed ROC curve to illustrate that the risk model in prognostic prediction has good performance. Moreover, significant differences in immune infiltration landscape were found between high-risk and low-risk groups using ESTIMATE and CIBERSOT algorithms. In the end, differential expressed genes (DEGs) were analyzed by gene set enrichment analysis (GSEA) to preliminarily explore the possible signaling pathways related to the prognosis of FAM and AML. The results of our study may provide potential prognostic biomarkers and therapeutic targets for AML patients, which is conducive to individualized precision therapy