Neuroprotective Effect of Dexmedetomidine on Cerebral Ischemia-Reperfusion Injury in Rats.

Background: The number of patients having ischemic stroke is increasing year on year. The anesthetic adjuvant dexmedetomidine is neuroprotective in rats and has potential for use in the treatment of ischemic stroke. Objective: The neuroprotective mechanism of dexmedetomidine in cerebral ischemia-reperfusion injury was studied in relation to its regulation of the oxidative stress response, astrocyte response, microglia overactivation, and apoptosis-related protein expression. Methods: We randomly and equally divided 25 male Sprague-Dawley rats into 5 groups: a sham-operation group, an ischemia-reperfusion injury group, and low-, medium-, and high-dose dexmedetomidine groups. A rat model of focal cerebral ischemia-reperfusion injury was established by embolization of the right middle cerebral artery for 60 minutes and reperfusion for 2 hours. The volume of cerebral infarction was calculated by triphenyl tetrazolium chloride staining. The protein expression levels of caspase-3, methionyl aminopeptidase 2 (MetAP2 or MAP2), glial fibrillary acidic protein, and allograft inflammatory factor 1 (AIF-1) in the cerebral cortex were determined by Western blot and immunohistochemistry. Results: The volume of cerebral infarction in rats decreased with increasing dose of dexmedetomidine (P = .039, 95% CI = .027 to .044). The expression levels of caspase-3, glial fibrillary acidic protein, and allograft inflammatory factor 1 and the amount of 4-hydroxynonenal decreased with increasing doses of dexmedetomidine (P = .033, 95% CI = .021 to .037). Methionyl aminopeptidase 2 (MetAP2 or MAP2) expression increased with increasing doses of dexmedetomidine (P = .023, 95% CI = .011 to .028). Conclusion: Dexmedetomidine has a dose-dependent protective effect on cerebral ischemic injury in rats. The neuroprotective effects of dexmedetomidine are achieved, in part, by reducing the oxidative stress response, inhibiting glial overactivation, and inhibiting expression levels of apoptosis-related proteins.

Construction and validation of a novel prognostic model for thyroid cancer based on N7-methylguanosine modification-related lncRNAs.

BACKGROUND: To construct and verify a novel prognostic model for thyroid cancer (THCA) based on N7-methylguanosine modification-related lncRNAs (m7G-lncRNAs) and their association with immune cell infiltration. METHODS: In this study, we identified m7G-lncRNAs using co-expression analysis and performed differential expression analysis of m7G-lncRNAs between groups. We then constructed a THCA prognostic model, performed survival analysis and risk assessment for the THCA prognostic model, and performed independent prognostic analysis and receiver operating characteristic curve analyses to evaluate and validate the prognostic value of the model. Furthermore, analysis of the regulatory relationship between prognostic differentially expressed m7G-related lncRNAs (PDEm7G-lncRNAs) and mRNAs and correlation analysis of immune cells and risk scores in THCA patients were carried out. RESULTS: We identified 29 N7-methylguanosine modification-related mRNAs and 116 differentially expressed m7G-related lncRNAs, including 87 downregulated and 29 upregulated lncRNAs. Next, we obtained 8 PDEm7G-lncRNAs. A final optimized model was constructed consisting of 5 PDEm7G-lncRNAs (DOCK9-DT, DPP4-DT, TMEM105, SMG7-AS1 and HMGA2-AS1). Six PDEm7G-lncRNAs (DOCK9-DT, DPP4-DT, HMGA2-AS1, LINC01976, MID1IP1-AS1, and SMG7-AS1) had positive regulatory relationships with 10 PDEm7G-mRNAs, while 2 PDEm7G-lncRNAs (LINC02026 and TMEM105) had negative regulatory relationships with 2 PDEm7G-mRNAs. Survival curves and risk assessment predicted the prognostic risk in both groups of patients with THCA. Forest maps and receiver operating characteristic curves were used to evaluate and validate the prognostic value of the model. Finally, we demonstrated a correlation between different immune cells and risk scores. CONCLUSION: Our results will help identify high-risk or low-risk patients with THCA and facilitate early prediction and clinical intervention in patients with high risk and poor prognosis.