[Association between drinking and all-cause mortality in patients with ischemic stroke]

MiR-199a-5p inhibition protects cognitive function of ischemic stroke rats by AKT signaling pathway

To explore the effect of miR-199a-5p and AKT signal pathway on cognitive function and neuronal cells in rats with ischemic stroke. Sprague-Dawley rats were divided into 6 groups: Normal group (normal rats), Sham group (rats received sham operation), Model group (MCAO rats), miR-199a-5p inhibitor group (model rats treated with miR-199a-5p inhibitor), IGF-1 group (model rats treated with AKT signaling pathway activator), miR-199a-5p inhibitor + IGF-1 group (model rats treated by miR-199a-5p inhibitor and AKT signaling pathway activator). Rat behavior and cerebral infarction area were observed. TUNEL fluorescence staining was used to detect neuronal apoptosis in hippocampal CA1 region of rats. The dual luciferase reporter assay validated the targeting relationship between miR-199a-5p and AKT. qRT-PCR and WB were used to detect the expression level of miR-199a-5p, (p)-AKT and (p)-mTOR, apoptosis-related proteins Bax and Bcl-2. Compared with the normal group, the expression of miR-199a-5p was increased in the Model group, and the expression levels of AKT, mTOR, p-AKT, and p-mTOR were decreased (all P < 0.05); the cognitive function of the rats in the Model group was thereby significantly lower (P < 0.05). miR-199a-5p was targeted to inhibit AKT. Compared with the Model group, miR-199a-5p inhibition combined with IGF-1 showed more significant effects on improving cognitive function and protecting neuronal cells of rats. In conclusion, silencing miR-199a-5p can effectively improve cognitive function in ischemic stroke rats and decrease neuronal apoptosis in hippocampus by activating the AKT signaling pathway.

The Discriminative Efficacy of Retinal Characteristics on Two Traditional Chinese Syndromes in Association with Ischemic Stroke

We aimed to investigate the efficacy of an objective method using AI-based retinal characteristic analysis to automatically differentiate between two traditional Chinese syndromes that are associated with ischemic stroke. Inpatient clinical and retinal data were retrospectively retrieved from the archive of our hospital. Patients diagnosed with cerebral infarction in the department of acupuncture and moxibustion between 2014 and 2018 were examined. Of these, the patients with Qi deficiency blood stasis syndrome (QDBS) and phlegm stasis in channels (PSIC) syndrome were selected. Those without retinal photos were excluded. To measure and analyze the patients' retinal vessel characteristics, we applied a patented AI-assisted automated retinal image analysis system developed by the Chinese University of Hong Kong. The demographic, clinical, and retinal information was compared between the QDBS and PSIC patients. The t-test and chi-squared test were used to analyze continuous data and categorical data, respectively. All the selected clinical information and retinal vessel measures were used to develop different discriminative models for QDBS and PSIC using logistic regression. Discriminative efficacy and model performances were evaluated by plotting a receiver operating characteristic curve. As compared to QDBS, the PSIC patients had a lower incidence of insomnia problems (46% versus 29% respectively, p=0.023) and a higher tortuosity index (0.45 ± 0.07 versus 0.47 ± 0.07, p=0.027). Moreover, the area under the curve of the logistic model showed that its discriminative efficacy based on both retinal and clinical characteristics was 86.7%, which was better than the model that employed retinal or clinical characteristics individually. Thus, the discriminative model using AI-assisted retinal characteristic analysis showed statistically significantly better performance in QDBS and PSIC syndrome differentiation among stroke patients. Therefore, we concluded that retinal characteristics added value to the clinical differentiation between QDBS and PSIC.