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Background: Isorhapontigenin (ISO) has been shown to have antioxidant activity. This study aimed to investigate the antioxidant effects of ISO on cerebral ischemia/reperfusion (I/R) injury and its possible molecular mechanisms. Methods: Focal cerebral ischemia‐reperfusion injury (MCAO/R) model and primary cortical neurons were established an oxygen‐glucose deprivation (OGD / R) injury model. After 24 hr of reperfusion, the neurological deficits of the rats were analyzed and HE staining was performed, and the infarct volume was calculated by TTC staining. In addition, the reactive oxygen species (ROS) in rat brain tissue, the content of 4‐Hydroxynonenal (4‐HNE), and 8‐hydroxy2deoxyguanosine (8‐OHdG) were detected. Neuronal cell viability was determined by MTT assay. Western blot analysis was determined for protein expression. Results: ISO treatment significantly improved neurological scores, reduced infarct volume, necrotic neurons, ROS production, 4‐HNE, and 8‐OHdG levels. At the same time, ISO significantly increased the expression of Nrf2 and HO‐1. The neuroprotective effects of ISO can be eliminated by knocking down Nrf2 and HO‐1. In addition, knockdown of the PKCε blocked ISO‐induced nuclear Nfr2, HO‐1 expression. Conclusion: ISO protected against oxidative damage induced by brain I/R, and its neuroprotective mechanism may be related to the PKCε/Nrf2/HO‐1 pathway. [ABSTRACT FROM AUTHOR]

Objectives: Spontaneous intracerebral hemorrhage remains a major cause of death and disability throughout the world. We tried to establish accurate long‐term outcome prediction models for hypertensive intracerebral hemorrhage (HICH) using CT radiomics and machine learning. Methods: In a retrospective study of 270 patients with HICH between June 2013 and June 2018, CT images and patients' 6‐month outcome based on the modified Rankin Scale were collected. Hematomas on CT images were selected as volumes of interests (VOIs), and 1,029 radiomics features of the VOIs were extracted. Based on correlations with patients' outcome, radiomics features underwent dimensionality reduction analyses. Then, the support vector machine (SVM), k‐nearest neighbor (KNN), logistic regression (LR), decision tree (DT), random forest (RF), and XGBoost algorithms were applied with the screened features to establish prognostic prediction models of HICH. Accuracies of all models were compared. Results: Eighteen radiomics features were screened as prognosis‐associated radiomics signature of HICH based on the variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) regression models. Patients were randomly allocated into training (n = 215) and validation (n = 55) sets. Accuracies of all 6 machine learning algorithms in the validation set exceeded 80%. The sensitivity, specificity, and accuracy in the validation set were 93.3%, 92.5%, and 92.7% for the RF model and 92.3%, 88.1%, and 89.1% for the XGBoost model, respectively, which were the best two among all models. Conclusions: Taking advantage of radiomics and machine learning, we established accurate prognostic prediction models of HICH. The RF model and XGBoost model returned the best accuracies. [ABSTRACT FROM AUTHOR]

Abstract: Background: With rapid advances in technology, wearable devices as head‐mounted display (HMD) have been adopted for various uses in medical science, ranging from simply aiding in fitness to assisting surgery. We aimed to investigate the feasibility and practicability of a low‐cost multimodal HMD system in neuroendoscopic surgery. Methods: A multimodal HMD system, mainly consisted of a HMD with two built‐in displays, an action camera, and a laptop computer displaying reconstructed medical images, was developed to assist neuroendoscopic surgery. With this intensively integrated system, the neurosurgeon could freely switch between endoscopic image, three‐dimensional (3D) reconstructed virtual endoscopy images, and surrounding environment images. Using a leap motion controller, the neurosurgeon could adjust or rotate the 3D virtual endoscopic images at a distance to better understand the positional relation between lesions and normal tissues at will. Results: A total of 21 consecutive patients with ventricular system diseases underwent neuroendoscopic surgery with the aid of this system. All operations were accomplished successfully, and no system‐related complications occurred. The HMD was comfortable to wear and easy to operate. Screen resolution of the HMD was high enough for the neurosurgeon to operate carefully. With the system, the neurosurgeon might get a better comprehension on lesions by freely switching among images of different modalities. The system had a steep learning curve, which meant a quick increment of skill with it. Compared with commercially available surgical assistant instruments, this system was relatively low‐cost. Conclusions: The multimodal HMD system is feasible, practical, helpful, and relatively cost efficient in neuroendoscopic surgery. [ABSTRACT FROM AUTHOR]