Background: Acute ischemic stroke (AIS) is a leading cause of disability and mortality worldwide. Prediction of penumbra existence after AIS is crucial for making decision on reperfusion therapy. Yet a fast, inexpensive, simple, and noninvasive predictive biomarker for the poststroke penumbra with clinical translational potential is still lacking. We aim to investigate whether the CircOGDH (circular RNA derived from oxoglutarate dehydrogenase) is a potential biomarker for penumbra in patients with AIS and its role in ischemic neuronal damage. Methods: CircOGDH was screened from penumbra of middle cerebral artery occlusion mice and was assessed in plasma of patients with AIS by quantitative polymerase chain reaction. Magnetic resonance imaging was used to examine the penumbra volumes. CircOGDH interacted with miR-5112 in primary cortical neurons was detected by fluorescence in situ hybridization, RNA immunoprecipitation, and luciferase reporter assay. ADV-mediated CircOGDH knockdown ameliorated neuronal apoptosis induced by COL4A4 (Gallus collagen, type VI, alpha VI) overexpression. Transmission electron microscope, nanoparticle tracking analysis, and Western blot were performed to confirm exosomes. Results: CircOGDH expression was dramatically and selectively upregulated in the penumbra tissue of middle cerebral artery occlusion mice and in the plasma of 45 patients with AIS showing a 54-fold enhancement versus noncerebrovascular disease controls. Partial regression analysis revealed that CircOGDH expression was positively correlated with the size of penumbra in patients with AIS. Sequestering of miR-5112 by CircOGDH enhanced COL4A4 expression to elevate neuron damage. Additionally, knockdown of CircOGDH significantly enhanced neuronal cell viability under ischemic conditions. Furthermore, the expression of CircOGDH in brain tissue was closely related to that in the serum of middle cerebral artery occlusion mice. Finally, we found that CircOGDH was highly expressed in plasma exosomes of patients with AIS compared with those in noncerebrovascular disease individuals. Conclusions: These results demonstrate that CircOGDH is a potential therapeutic target for regulating ischemia neuronal viability, and is enriched in neuron-derived exosomes in the peripheral blood, exhibiting a predictive biomarker of penumbra in patients with AIS.

BackgroundWe aimed to develop and validate a new nomogram for predicting the risk of intracranial hemorrhage (ICH) in patients with acute ischemic stroke (AIS) after intravenous thrombolysis (IVT).MethodsA retrospective study enrolled 553 patients with AIS treated with IVT. The patients were randomly divided into two cohorts: the training set (70%, n = 387) and the testing set (30%, n = 166). The factors in the predictive nomogram were filtered using multivariable logistic regression analysis. The performance of the nomogram was assessed based on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analysis (DCA).ResultsAfter multivariable logistic regression analysis, certain factors, such as smoking, National Institutes of Health of Stroke Scale (NIHSS) score, blood urea nitrogen-to-creatinine ratio (BUN/Cr), and neutrophil-to-lymphocyte ratio (NLR), were found to be independent predictors of ICH and were used to construct a nomogram. The AUC-ROC values of the nomogram were 0.887 (95% CI: 0.842–0.933) and 0.776 (95% CI: 0.681–0.872) in the training and testing sets, respectively. The AUC-ROC of the nomogram was higher than that of the Multicenter Stroke Survey (MSS), Glucose, Race, Age, Sex, Systolic blood Pressure, and Severity of stroke (GRASPS), and stroke prognostication using age and NIH Stroke Scale-100 positive index (SPAN-100) scores for predicting ICH in both the training and testing sets (p < 0.05). The calibration plot demonstrated good agreement in both the training and testing sets. DCA indicated that the nomogram was clinically useful.ConclusionsThe new nomogram, which included smoking, NIHSS, BUN/Cr, and NLR as variables, had the potential for predicting the risk of ICH in patients with AIS after IVT.

Background Because of multiple competing death outcomes and time-varying coefficients, using a Cox regression model to analyze the prognostic factors of low-grade gliomas (LGG) may lead to a possible bias. Therefore, we adopted time-dependent competing risk models to obtain accurate prognostic factors for LGG. Methods In this retrospective cohort study, data were extracted from patients enrolled in the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018. Univariate analysis was performed using the cumulative incidence function (CIF) and Kaplan-Meier (KM) function. Time-dependent competing risk and Cox regression models were used in the multivariable analysis. Results A total of 2581 patients were diagnosed with low-grade glioma, among whom 889 died from low-grade glioma, 114 died from other causes, and the rest were alive. The time-dependent competing risk models indicated that age, sex, marital status, primary tumor site, histological type, tumor diameter, surgery, and year of diagnosis were significantly associated with low-grade glioma-specific death, and the relative effect of age, tumor diameter, surgery, oligodendroglioma, and mixed glioma on low-grade glioma-specific death changed over time. Compared with the competing risk models, the Cox regression model misestimated the hazard ratio (HR) of covariates on the outcome and even produced false-negative results. Conclusions The time-dependent competing risk models were better than the Cox regression model for evaluating the impact of covariates on low-grade glioma-specific mortality in the presence of competing risks and time-varying coefficients. The models identified the prognostic factors of LGG more accurately than the Cox regression model.