Background:Neuropathic pain is one of the common complications after spinal cord injury (SCI), affecting individuals’ quality of life. The molecular mechanism for neuropathic pain after SCI is still unclear. We aimed to discover potential genes and microRNAs (miRNAs) related to neuropathic pain by the bioinformatics method.Methods:Microarray data of GSE69901 were obtained from Gene Expression Omnibus (GEO) database. Peripheral blood samples from individuals with or without neuropathic pain after SCI were collected. Twelve samples from individuals with neuropathic pain and 13 samples from individuals without pain as controls were included in the downloaded microarray. Differentially expressed genes (DEGs) between the neuropathic pain group and the control group were detected using the GEO2R online tool. Functional enrichment analysis of DEGs was performed using the DAVID database. Protein-protein interaction network was constructed from the STRING database. MiRNAs targeting these DEGs were obtained from the miRNet database. A merged miRNA-DEG network was constructed and analyzed with Cytoscape software.Results:In total, 1134 DEGs were identified between individuals with or without neuropathic pain (case and control), and 454 biological processes were enriched. We identified 4 targeted miRNAs, including mir-204-5p, mir-519d-3p, mir-20b-5p, mir-6838-5p, which may be potential biomarkers for SCI patients.Conclusion:Protein modification and regulation of the biological process of the central nervous system may be a risk factor in SCI. Certain genes and miRNAs may be potential biomarkers for the prediction of and potential targets for the prevention and treatment of neuropathic pain after SCI.

Purpose Propofol is one of the most commonly used intravenous sedatives in general anesthesia, while the individual variations of propofol are apparent. The objective of this study was to investigate the influence of genetic variations in GABAergic neurons and glutamatergic neurons on time to loss of consciousness (LOC) and the incidence of hypotension during anesthesia induction. Patients and Methods A total of 140 Chinese patients undergoing thyroid surgery or breast surgery were recruited. Genotyping of candidate genes was carried out using the Agena Bioscience MassARRAY system. Anesthesia induction was initiated with a propofol target plasma concentration (Cp) of 4.0 μg mL −1 . The LOC latency, systolic blood pressure, diastolic blood pressure, mean arterial pressure were documented. Results We found that GABRA2 rs35496835, GABRB1 rs1372496, GABRG2 rs11135176, GABRG2 rs209358, GAD1 rs3791878, SLC1A3 rs1049522 and gender were significant determinants of the patient’s LOC latency following propofol administration. GABRA2 rs11503014 was highly correlated with blood pressure reduction during anesthesia induction. Multiple linear regression analysis revealed that GABRB1 rs1372496, GABRG2 rs11135176, and SLC1A3 rs1049522 accounted for 35.3% variations in LOC latency following propofol administration. Conclusion Our findings indicate that genetic variants of GABRA2, GABRB1, GABRG2, GAD1 and SLC1A3 may have influence on propofol susceptibility, which would be an important guidance towards building clinical models that can precisely predict the efficacy of propofol with various populations before surgery.

Objective We aimed to explore potential microRNAs (miRNAs) and target genes related to atrial fibrillation (AF). Methods Data for microarrays GSE70887 and GSE68475, both of which include AF and control groups, were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between AF and control groups were identified within each microarray, and the intersection of these two sets was obtained. These miRNAs were mapped to target genes in the miRNet database. Functional annotation and enrichment analysis of these target genes was performed in the DAVID database. The protein-protein interaction (PPI) network from the STRING database and the miRNA-target-gene network were merged into a PPI-miRNA network using Cytoscape software. Modules of this network containing miRNAs were detected and further analyzed. Results Ten differentially expressed miRNAs and 1520 target genes were identified. Three PPI-miRNA modules were constructed, which contained miR-424, miR-15a, miR-542-3p, and miR-421 as well as their target genes, CDK1, CDK6, and CCND3. Conclusion The identified miRNAs and genes may be related to the pathogenesis of AF. Thus, they may be potential biomarkers for diagnosis and targets for treatment of AF.

Aim Propofol and opioids are commonly used in anaesthesia, but are highly susceptible to haemodynamic instability, thereby threatening the patient's surgical safety and prognosis. The purpose of this study was to investigate the predictors of haemodynamic instability and establish its predictive model. Methods A total of 150 Chinese patients undergoing thyroid or breast surgery participated in the study, with target‐controlled infusion concentrations of propofol, opioids dosage, heart rate (HR), mean arterial pressure (MAP) and Narcotrend Index recorded at key points throughout the procedure. The Agena MassARRAY system was used to genotype candidate single nucleotide polymorphisms related to pharmacodynamics and pharmacokinetics of propofol and opioids. Results Among nongenetic factors, baseline HR (R = −.579, P < .001) and baseline MAP (R = −.725, P < .001) had a significant effect on the haemodynamic instability. Among genetic factors, the CT/CC genotype of GABRB1 rs4694846 (95% confidence interval [CI]: −11.309 to −3.155), AA/AG of OPRM1 rs1799971 (95%CI: 0.773 to 10.290), AA of CES2 rs8192925 (95%CI: 1.842 to 9.090) were associated with higher HR instability; the AA/GG genotype of NR1I2 rs6438550 (95%CI: 0.351 to 7.761), AA of BDNF rs2049046 (95%CI: −9.039 to −0.640) and GG of GABBR2 rs1167768 (95%CI: −10.146 to −1.740) were associated with higher MAP instability. The predictive models of HR and MAP fluctuations were developed, accounting for 45.0 and 59.2% of variations, respectively. Conclusion We found that cardiovascular fundamentals and genetic variants of GABRB1, GABBR2, OPRM1, BDNF, CES2 and NR1I2 are associated with cardiovascular susceptibility, which can provide a reference for haemodynamic management in clinical anaesthesia.

No abstract