Cardioprotective role of oleanolic acid in patients with type 2 diabetes mellitus.

Background: Patients with type 2 diabetes mellitus (T2DM) experience a decline in cardiac function, resulting in poor prognosis. Therefore, restoration of cardiac function and improvement of myocardial fibrosis is an important treatment goal for patients with T2DM. Material and methods: The chemical structure of oleanolic acid(OA) was downloaded from PubChem and uploaded to PharmMapper. GeneCards and OMIM databases were searched for genes related to OA and disease and plotted into a Venn diagram. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using R software. Then, a mouse model of diabetes mellitus was established, and ELISA, echocardiographic analysis of cardiac function, TUNEL assay, and reactive oxygen species assay were performed. Results: Network pharmacology analysis identified the related targets and potential molecular mechanisms underlying the effects of OA in T2DM. ELISA, echocardiographic analysis of cardiac function, and TUNEL assay results showed that OA inhibits apoptosis and improves apoptotic indexes in mice with T2DM-induced myocardial injury. Conclusion: The results demonstrate the myocardial protective effect of OA in this mouse model.

Identification of the Hub Genes Involved in Stem Cell Treatment for Intervertebral Disc Degeneration: A Conjoint Analysis of Single-Cell and Machine Learning.

Intervertebral disc degeneration (IDD), which is distinguished by a variety of pathologic alterations, is the major cause of low back pain (LBP). Nonetheless, preventative measures or therapies that may delay IDD are scarcely available. In this study, we sought to identify new diagnostic biological markers for IDD. In this first-of-a-kind study combining machine learning, stem cell treatment samples and single-cell sequencing data were collected. Differentially expressed genes (DEGs) were detected from the treatment group and clusters. To filter potential markers, support vector machine analysis and LASSO were performed. LAPTM5 was found to be the hub gene for IDD. In addition, the results of single-cell sequencing demonstrated the critical function of stem cells in IDD. Finally, we found that aging is significantly associated with the rate of stem cells. In general, our results may offer fresh insights that may be used in the investigation of innovative markers for diagnosing IDD. The critical genes identified by the machine learning algorithm could provide new perspectives on IDD.

Upregulation of EMID1 Accelerates to a Favorable Prognosis and Immune Infiltration in Lung Adenocarcinoma.

Lung cancer is a difficult-to-treat cancer. Lung adenocarcinoma (LUAD) is the main subtype of lung cancer. Although there are many ways to treat lung cancer, the survival rate of patients is low. Therefore, novel molecules need to be identified to diagnose and treat LUAD. This study utilized The Cancer Genome Atlas (TCGA) LUAD data to analyze and validate the value of EMID1 as a LUAD diagnostic surface marker and overall survival prognostic marker. Differential expression analysis formally confirmed that decreased EMID1 expression was significantly associated with advanced stage and metastasis of lung cancer. Kaplan-Meier survival analysis showed that the patients with low EMID expression are dismal. The relationship between clinicopathological features and EMID1 was scored using Wilcoxon signed-rank test and R (v.3.5.1) logistic regression and suggested that patients with low EMID1 expression had a worse prognosis than patients with high EMID1 expression. (Gene Ontology) GO, Kyoto Encyclopedia of Genes and Genomes(KEGG), and gene set enrichment analysis (GSEA) were performed to investigate the potential mechanism of EMID1 expression on the prognosis of LUAD and suggested that Notch signaling pathway may be an important biological pathway for EMID1 to play a role in LUAD. Further, combined with univariate and multivariate Cox regression analysis, it was speculated that high and low levels of EMID1 expression and the logistic regression analysis of related clinical variables had significant clinical significance to verify the underlying mechanism of LUAD focus and prognosis. EMID1 plays an important role in the immune milieu of LUAD. Meanwhile, the correlation between tumor-infiltrating immune cells and genes was assessed using CIBERSORT, and it was found that the level of B cell infiltration was positively correlated with the expression of EMID1, all of which were validated in the GEO and GEPIA databases. In all, this study helps to understand the immune microenvironment of LUAD and improve the survival of patients with LUAD. Thus, EMID1 may be a novel immune-related prognostic marker of LUAD.

Effect of bilateral paravertebral nerve block on cognitive function in elderly patients undergoing radical gastrectomy for gastric cancer: a prospective randomized double-blind controlled trial.

OBJECTIVE: To investigate the effect of a bilateral paravertebral block (PVB) on cognitive function in elderly patients undergoing radical gastrectomy for gastric cancer. METHODS: Sixty patients (40 men and 20 women) aged 65-80 undergoing radical gastrectomy surgery under general anaesthesia were included and randomly assigned to either the PVB group or the control group. Patients in the PVB group had before incision a single-shot ultrasound-guided bilateral PVB at the T8 level with 20 mL of ropivacaine 0.375%, while patients in the control group had no block. Patients in both groups had a BIS-guided total intravenous anaesthesia with propofol and remifentanil infusions. Postoperative cognitive function assessed by the mini-mental state examination (MMSE) and NSE (neuron-specific enolase) was the primary outcome. RESULTS: The awareness time in group PVB was shorter than that in the group C, and the propofol and remifentanil dosages were less than that in group C (P<0.001, P = 0.007, respectively). Furthermore, the change of the MMSE score and the NSE concentration was significant from day0 to day1 and day1 to day2. (P<0.001). CONCLUSION: A single-shot bilateral PVB active throughout radical gastrectomy for gastric cancer reduces the needs for general anaesthetic agents and improve postoperative recovery, along with a surrogate evidence for neuroprotective effects. TRIAL REGISTRATION: ChiCTR2200060088 . Registered 18 May 2022.

Promising novel biomarkers and candidate small-molecule drugs for lung adenocarcinoma: Evidence from bioinformatics analysis of high-throughput data.

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer associated with an unstable prognosis. Thus, there is an urgent demand for the identification of novel diagnostic and prognostic biomarkers as well as targeted drugs for LUAD. The present study aimed to identify potential new biomarkers associated with the pathogenesis and prognosis of LUAD. Three microarray datasets (GSE10072, GSE31210, and GSE40791) from the Gene Expression Omnibus database were integrated to identify the differentially expressed genes (DEGs) in normal and LUAD samples using the limma package. Bioinformatics tools were used to perform functional and signaling pathway enrichment analyses for the DEGs. The expression and prognostic values of the hub genes were further evaluated by Gene Expression Profiling Interactive Analysis and real-time quantitative polymerase chain reaction. Furthermore, we mined the "Connectivity Map" (CMap) to explore candidate small molecules that can reverse the tumoral of LUAD based on the DEGs. A total of 505 DEGs were identified, which included 337 downregulated and 168 upregulated genes. The PPI network was established with 1,860 interactions and 373 nodes. The most significant pathway and functional enrichment associated with the genes were cell adhesion and extracellular matrix-receptor interaction, respectively. Seven DEGs with high connectivity degrees (ZWINT, RRM2, NDC80, KIF4A, CEP55, CENPU, and CENPF) that were significantly associated with worse survival were chosen as hub genes. Lastly, top 20 most important small molecules which reverses the LUAD gene expressions were identified. The findings contribute to revealing the molecular mechanisms of the initiation and progression of LUAD and provide new insights for integrating multiple biomarkers in clinical practice.

Effect of Intravenous Lidocaine on Serum Interleukin-17 After Video-Assisted Thoracic Surgery for Non-Small-Cell Lung Cancer: A Randomized, Double-Blind, Placebo-Controlled Trial.

PURPOSE: Surgical stress promotes tumor metastasis. Interleukin (IL)-17 plays a pivotal role in cancer progression, and high IL-17 expression predicts poor prognosis of non-small-cell lung cancer (NSCLC). Lidocaine may exert tumor-inhibiting effects. We hypothesize that intravenous lidocaine attenuates surgical stress and reduces serum IL-17 levels during video-assisted thoracic surgery (VATS) for NSCLC. METHODS: This randomized, double-blind, placebo-controlled trial included 60 early-stage NSCLC patients undergoing VATS, into a lidocaine group (n = 30; intravenous lidocaine bolus 1.0 mg/kg, and 1.0 mg/kg/h until the end of surgery) or a normal saline control group (n = 30). The primary outcome was serum IL-17 level at 24 hours postoperatively. The secondary outcomes included serum IL-17 level at the time of post-anesthesia care unit (PACU) discharge, serum cortisol level at PACU discharge and postoperative 24 hours, pain scores (0-10) from PACU discharge to 48 hours postoperatively, incidences of postoperative nausea and vomiting, dizziness, and arrhythmia during 0-48 hours postoperatively, and 30-day mortality. Long-term outcomes included chemotherapy, cancer recurrence, and mortality. RESULTS: The lidocaine group had lower serum IL-17 at 24 hours postoperatively compared with the control group (23.0 ± 5.8 pg/mL vs 27.3 ± 8.2 pg/mL, difference [95% CI] = -4.3 [-8.4 to -0.2] pg/mL; P = 0.038). The lidocaine group also had reduced serum IL-17 (difference [95% CI] = -4.6 [-8.7 to -0.5] pg/mL), serum cortisol (difference [95% CI] = -37 [-73 to -2] ng/mL), and pain scores (difference [95% CI] = -0.7 [-1.3 to -0.1] points) at PACU discharge. During a median follow-up of 10 (IQR, 9-13) months, 2 patients in the lidocaine group and 6 patients in the control group received chemotherapy, one patient in the control group had cancer recurrence, and no death event occurred. CONCLUSION: Intravenous lidocaine was associated with reduced serum IL-17 and cortisol following VATS procedures in early-stage NSCLC patients. TRIAL REGISTRATION: ChiCTR2000030629.

Bioinformatics analysis of high-throughput data to validate potential novel biomarkers and small molecule drugs for glioblastoma multiforme.

OBJECTIVE: There have been no recent improvements in the glioblastoma multiforme (GBM) outcome, with median survival remaining 15 months. Consequently, the need to identify novel biomarkers for GBM diagnosis and prognosis, and to develop targeted therapies is high. This study aimed to establish biomarkers for GBM pathogenesis and prognosis. METHODS: In total, 220 overlapping differentially expressed genes (DEGs) were obtained by integrating four microarray datasets from the Gene Expression Omnibus database (GSE4290, GSE12657, GSE15824, and GSE68848). Then a 140-node protein-protein interaction network with 343 interactions was constructed. RESULTS: The immune response and cell adhesion molecules were the most significantly enriched functions and pathways, respectively, among DEGs. The designated hub genes ITGB5 and RGS4, which have a high degree of connectivity, were closely correlated with patient prognosis, and GEPIA database mining further confirmed their differential expression in GBM versus normal tissue. We also determined the 20 most appropriate small molecules that could potentially reverse GBM gene expression, Prestwick-1080 was the most promising and had the highest negative scores. CONCLUSIONS: This study identified ITGB5 and RGS4 as potential biomarkers for GBM diagnosis and prognosis. Insights into molecular mechanisms governing GBM occurrence and progression will help identify alternative biomarkers for clinical practice.

Identification of novel biomarkers and candidate small molecule drugs in non-small-cell lung cancer by integrated microarray analysis.

Background: Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC. Methods: The microarray datasets of GSE18842, GSE30219, GSE31210, GSE32863 and GSE40791 from Gene Expression Omnibus database were downloaded. The differential expressed genes (DEGs) between NSCLC and normal samples were identified by limma package. The construction of protein-protein interaction (PPI) network, module analysis and enrichment analysis were performed using bioinformatics tools. The expression and prognostic values of hub genes were validated by GEPIA database and real-time quantitative PCR. Based on these DEGs, the candidate small molecules for NSCLC were identified by the CMap database. Results: A total of 408 overlapping DEGs including 109 up-regulated and 296 down-regulated genes were identified; 300 nodes and 1283 interactions were obtained from the PPI network. The most significant biological process and pathway enrichment of DEGs were response to wounding and cell adhesion molecules, respectively. Six DEGs (PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5) which significantly up-regulated in NSCLC tissues, were selected as hub genes according to the results of module analysis. The GEPIA database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. Additionally, CMap predicted the 20 most significant small molecules as potential therapeutic drugs for NSCLC. DL-thiorphan was the most promising small molecule to reverse the NSCLC gene expression. Conclusions: Based on the gene expression profiles of 696 NSCLC samples and 237 normal samples, we first revealed that PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5 could act as the promising novel diagnostic and therapeutic targets for NSCLC. Our work will contribute to clarifying the molecular mechanisms of NSCLC initiation and progression.

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gastric cancer.

BACKGROUND AND OBJECTIVE: The underlying molecular mechanisms of gastric cancer (GC) have yet not been investigated clearly. In this study, we aimed to identify hub genes involved in the pathogenesis and prognosis of GC. METHODS: We integrated five microarray datasets from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between GC and normal samples were analyzed with limma package. Gene ontology (GO) and KEGG enrichment analysis were performed using DAVID. Then we established the protein-protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING). The prognostic analysis of hub genes were performed through Gene Expression Profiling Interactive Analysis (GEPIA). Additionally, we used real-time quantitative PCR to validate the expression of hub genes in 5 pairs of tumor tissues and corresponding adjacent tissues. Finally, the candidate small molecules as potential drugs to treat GC were predicted in CMap database. RESULTS: Through integrating five microarray datasets, a total of 172 overlap DEGs were detected including 79 up-regulated and 93 down-regulated genes. Biological process analysis of functional enrichment showed these DEGs were mainly enriched in digestion, collagen fibril organization and cell adhesion. Signaling pathway analysis indicated that these DEGs played an vital in ECM-receptor interaction, focal adhesion and metabolism of xenobiotics by cytochrome P450. Protein-protein interaction network among the overlap DEGs was established with 124 nodes and 365 interactions. Three DEGs with high degree of connectivity (NID2, COL4A1 and COL4A2) were selected as hub genes. The GEPIA database confirmed that overexpression levels of hub genes were significantly associated with worse survival of patients. Finally, the 20 most significant small molecules were obtained based on CMap database and spiradoline was the most promising small molecule to reverse the GC gene expression. CONCLUSIONS: Our results indicated that NID2, COL4A1 and COL4A2 could be the potential novel biomarkers for GC diagnosis prognosis and the promising therapeutic targets. The present study may be crucial to understanding the molecular mechanism of GC initiation and progression.

The promising novel biomarkers and candidate small molecule drugs in lower-grade glioma: Evidence from bioinformatics analysis of high-throughput data.

Overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty-eight nodes with 603 interactions were obtained from the establishment of protein-protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients' prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS-275 (enrichment score = -0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.