Identification of Prognostic Markers of Glioblastoma through Bioinformatics Analysis.

Objective: Glioblastoma is the most common and aggressive type of the central nervous system cancers. Although radiotherapy and chemotherapy are used in the treatment of glioblastoma, survival rates remain unsatisfactory. This study aimed to explore differentially expressed genes (DEGs) based on the survival prognosis of patients with glioblastoma and to establish a model for classifying patients into different risk groups for overall survival. Methods: DEGs from 160 tumor samples from patients with glioblastoma and 5 nontumor samples from other patients in The Cancer Genome Atlas database were identified. Functional enrichment analysis and a protein-protein interaction network were used to analyze the DEGs. The prognostic DEGs were identified by univariate Cox regression analysis. We split patient data from The Cancer Genome Atlas database into a high-risk group and a low-risk group as the training data set. Least absolute shrinkage and selection operator and multiple Cox regression were used to construct a prognostic risk model, which was validated in a test data set from The Cancer Genome Atlas database and was analyzed using external data sets from the Chinese Glioma Genome Atlas database and the GSE74187 and GSE83300 data sets. Furthermore, we constructed and validated a nomogram to predict survival of patients with glioblastoma. Results: A total of 3572 prognostic DEGs were identified. Functional analysis indicated that these DEGs were mainly involved in the cell cycle and focal adhesion. Least absolute shrinkage and selection operator regression identified 3 prognostic DEGs (EFEMP2, PTPRN, and POM121L9P), and we constructed a prognostic risk model. The receiver operating characteristic curve analysis showed that the areas under the curve were 0.83 for the training data set and 0.756 for the test data set. The predictive performance of the prognostic risk model was validated in the 3 external data sets. The nomogram showed that the prognostic risk model was reliable and that the accuracy of predicting survival in each patient was high. Conclusion: The prognostic risk model can effectively classify patients with glioblastoma into high-risk and low-risk groups in terms of overall survival rate, which may help select high-risk patients with glioblastoma for more intensive treatment.

Probiotics for the treatment of ulcerative colitis: a review of experimental research from 2018 to 2022.

Ulcerative colitis (UC) has become a worldwide public health problem, and the prevalence of the disease among children has been increasing. The pathogenesis of UC has not been elucidated, but dysbiosis of the gut microbiota is considered the main cause of chronic intestinal inflammation. This review focuses on the therapeutic effects of probiotics on UC and the potential mechanisms involved. In animal studies, probiotics have been shown to alleviate symptoms of UC, including weight loss, diarrhea, blood in the stool, and a shortened colon length, while also restoring intestinal microecological homeostasis, improving gut barrier function, modulating the intestinal immune response, and attenuating intestinal inflammation, thereby providing theoretical support for the development of probiotic-based microbial products as an adjunctive therapy for UC. However, the efficacy of probiotics is influenced by factors such as the bacterial strain, dose, and form. Hence, the mechanisms of action need to be investigated further. Relevant clinical trials are currently lacking, so the extension of animal experimental findings to clinical application requires a longer period of consideration for validation.

Pretreatment with Bifidobacterium longum BAA2573 ameliorates dextran sulfate sodium (DSS)-induced colitis by modulating gut microbiota.

Objectives: Inflammatory bowel disease (IBD) is a chronic lifelong inflammatory disease. Probiotics such as Bifidobacterium longum are considered to be beneficial to the recovery of intestinal inflammation by interaction with gut microbiota. Our goals were to define the effect of the exclusive use of BAA2573 on dextran sulfate sodium (DSS)-induced colitis, including improvement of symptoms, alleviation of histopathological damage, and modulation of gut microbiota. Methods: In the present study, we pretreated C57BL/6J mice with Bifidobacterium longum BAA2573, one of the main components in an over-the-counter (OTC) probiotic mixture BIFOTO capsule, before modeling with DSS. 16S rDNA sequencing and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomic profiling were performed with the collected feces. Results: We found that pretreatment of Bifidobacterium longum BAA2573 given by gavage significantly improved symptoms and histopathological damage in DSS-induced colitis mice. After the BAA2573 intervention, 57 genera and 39 metabolites were significantly altered. Pathway enrichment analysis demonstrated that starch and sucrose metabolism, vitamin B6 metabolism, and sphingolipid metabolism may contribute to ameliorating colitis. Moreover, we revealed that the gut microbiome and metabolites were interrelated in the BAA2573 intervention group, while Alistipes was the core genus. Conclusion: Our study demonstrates the impact of BAA2573 on the gut microbiota and reveals a possible novel adjuvant therapy for IBD patients.

Identification of key genes with prognostic value in gastric cancer by bioinformatics analysis.

Background: Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality. It is urgently required to identify genes to elucidate the underlying molecular mechanisms. The aim of this study is to identify the key genes which may affect the prognosis of GC patients and be a therapeutic strategy for GC patients by bioinformatic analysis. Methods: The significant prognostic differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. The protein-protein interaction (PPI) network was established by STRING and screening key genes by MCODE and CytoNCA plug-ins in Cytoscape. Functional enrichment analysis, construction of a prognostic risk model, and nomograms verify key genes as potential therapeutic targets. Results: In total, 997 genes and 805 genes were related to the prognosis of GC in the GSE84437 and TCGA datasets, respectively. We define the 128 genes shared by the two datasets as prognostic DEGs (P-DEGs). Then, the first four genes (MYLK, MYL9, LUM, and CAV1) with great node importance in the PPI network of P-DEGs were identified as key genes. Independent prognostic risk analysis found that patients with high key gene expression had a poor prognosis, excluding their age, gender, and TNM stage. GO and KEGG enrichment analyses showed that key genes may exert influence through the PI3K-Akt pathway, in which extracellular matrix organization and focal adhesion may play important roles in key genes influencing the prognosis of GC patients. Conclusion: We found that MYLK, MYL9, LUM, and CAV1 are potential and reliable prognostic key genes that affect the invasion and migration of gastric cancer.

Identification of an Immune-Related Prognostic Risk Model in Glioblastoma.

Background: Glioblastoma (GBM) is the most common and malignant type of brain tumor. A large number of studies have shown that the immunotherapy of tumors is effective, but the immunotherapy effect of GBM is not poor. Thus, further research on the immune-related hub genes of GBM is extremely important. Methods: The GBM highly correlated gene clusters were screened out by differential expression, mutation analysis, and weighted gene co-expression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and proportional hazards model (COX) regressions were implemented to construct prognostic risk models. Survival, receiver operating characteristic (ROC) curve, and compound difference analyses of tumor mutation burden were used to further verify the prognostic risk model. Then, we predicted GBM patient responses to immunotherapy using the ESTIMATE algorithm, GSEA, and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. Results: A total of 834 immune-related differentially expressed genes (DEGs) were identified. The five hub genes (STAT3, SEMA4F, GREM2, MDK, and SREBF1) were identified as the prognostic risk model (PRM) screened out by WGCNA and LASSO analysis of DEGs. In addition, the PRM has a significant positive correlation with immune cell infiltration of the tumor microenvironment (TME) and expression of critical immune checkpoints, indicating that the poor prognosis of patients is due to TIDE. Conclusion: We constructed the PRM composed of five hub genes, which provided a new strategy for developing tumor immunotherapy.

[Effects of astragalus polysaccharide on intestinal immune function of rats with severe scald injury].

OBJECTIVE: To observe the effects of astragalus polysaccharide (AP) on the intestinal mucosal morphology, level of secretory IgA (s-IgA) in intestinal mucus, and distribution of T lymphocyte subsets in Peyer's patch in rats with severe scald injury. METHODS: One hundred and thirty SD rats were divided into sham injury group (SI, sham injured, n = 10), scald group (S, n = 30), low dosage group (LD, n = 30), moderate dosage group (MD, n = 30), and high dosage group (HD, n = 30) according to the random number table. Rats in the latter 4 groups were inflicted with 30% TBSA full-thickness scald on the back. From post injury hour 2, rats in groups LD, MD, and HD were intraperitoneally injected with 0.5 mL AP solution with the dosage of 100, 200, and 300 mg/kg each day respectively, and rats in group S were injected with 0.5 mL normal saline instead. Ten rats from group SI immediately after injury and 10 rats from each of the latter 4 groups on post injury day (PID) 3, 7, 14 were sacrificed, and their intestines were harvested. The morphology of ileal mucosa was examined after HE staining; the level of s-IgA in ileal mucus was determined with double-antibody sandwich ELISA method; the proportions of CD3⁺, CD4⁺, CD8⁺ T lymphocytes in Peyer's patches of intestine were determined with flow cytometer, and the proportion of CD4⁺ to CD8⁺ was calculated. Data were processed with one-way analysis of variance, analysis of variance of factorial design, and SNK test. RESULTS: (1) Villi in normal form and intact villus epithelial cells were observed in rats of group SI immediately after injury, while edema of villi and necrosis and desquamation of an enormous amount of villi were observed in groups with scalded rats on PID 3, with significant infiltration of inflammatory cells. On PID 7, no obvious improvement in intestinal mucosal lesion was observed in groups with scalded rats. On PID 14, the pathology in intestinal mucosa of rats remained nearly the same in group S, and it was alleviated obviously in groups LD and MD, and the morphology of intestinal mucosa of rats in group HD was recovered to that of group SI. (2) On PID 3, 7, and 14, the level of s-IgA in intestinal mucus significantly decreased in groups S, LD, MD, and HD [(43 ± 5), (45 ± 5), (46 ± 5) µg/mL; (47 ± 5), (48 ± 5), (49 ± 6) µg/mL; (50 ± 6), (51 ± 5), (52 ± 5) µg/mL; (53 ± 6), (54 ± 5), (55 ± 5) µg/mL] as compared with that of rats in group SI immediately after injury [(69 ± 4) µg/mL, with P values below 0.05]. The level of s-IgA in intestinal mucus of rats in group MD was significantly higher than that in group S at each time point (with P values below 0.05), and that of group HD was significantly higher than that in groups S and LD at each time point (with P values below 0.05). (3) Compared with those of rats in group SI immediately after injury, the proportions of CD3⁺ T lymphocytes and CD4⁺ T lymphocytes significantly decreased in groups with scalded rats at each time point (with P values below 0.05), except for those in group HD on PID 14. The proportion of CD4⁺ T lymphocytes of rats in group LD was significantly higher than that in group S on PID 3 (P < 0.05). The proportions of CD3⁺ T lymphocytes and CD4⁺ T lymphocytes were significantly higher in groups MD and HD than in groups S and LD (except for the proportion of CD4⁺ T lymphocytes in group MD on PID 3 and 14) at each time point (with P values below 0.05). The proportion of CD3⁺ T lymphocytes on PID 7 and 14 and that of CD4⁺ T lymphocytes on PID 3 were significantly higher in group HD than in group MD (with P values below 0.05). Compared with that of rats in group SI immediately after injury, the proportion of CD8⁺ T lymphocytes significantly increased in the other 4 groups at each time point (with P values below 0.05). The proportion of CD8⁺ T lymphocytes was significantly lower in rats of group LD on PID 7 and 14 and groups MD and HD at each time point than in group S (with P values below 0.05). The proportion of CD8⁺ T lymphocytes was significantly lower in rats of group MD on PID 7 and 14 and group HD at each time point than in group LD (with P values below 0.05). The proportion of CD8⁺ T lymphocytes was significantly lower in rats of group HD on PID 7 and 14 than in group MD (with P values below 0.05). On PID 3, 7, and 14, the proportion of CD4⁺ to CD8⁺ was significantly lower in groups S, LD, MD, and HD (0.65 ± 0.11, 0.68 ± 0.13, 0.73 ± 0.22; 0.76 ± 0.15, 0.78 ± 0.14, 0.90 ± 0.10; 0.85 ± 0.21, 0.89 ± 0.18, 1.08 ± 0.19; 0.99 ± 0.20, 1.05 ± 0.21, 1.25 ± 0.23) as compared with that of rats in group SI immediately after injury (1.74 ± 0.20, with P values below 0.05). The proportion of CD4⁺ to CD8⁺ was significantly higher in rats of group HD than in group MD on PID 7 (P < 0.05), and the proportion was significantly higher in these two groups than in group S at each time point (with P values below 0.05). The proportion of CD4⁺ to CD8⁺ was significantly higher in rats of group MD on PID 14 and group HD at each time point than in group LD (with P values below 0.05). Compared within each group, the proportions of CD3⁺, CD4⁺, CD8⁺ T lymphocytes and the proportion of CD4⁺ to CD8⁺ of rats in groups LD, MD, and HD showed a trend of gradual elevation along with passage of time. CONCLUSIONS: AP can improve the injury to intestinal mucosa and modulate the balance of T lymphocyte subsets in Peyer's patch in a time- and dose-dependent manner, and it can promote s-IgA secretion of intestinal mucosa in a dose-dependent manner.