The coronavirus disease 2019 (COVID-19) is caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), having gradually developed into a pandemic and endangered global health. The continued use of angiotensin converting enzyme inhibitor (ACEIs) and angiotensin II receptor blockers (ARBs) which are part of renin-angiotensin-aldosterone system (RAAS) inhibitors in COVID-19 patients with hypertension has become controversial. We conducted a meta-analysis by searching Pubmed, Web of Science, Scopus and Embase up to 13 May 2020. Data analyses were performed by the Cochrane Collaboration's Review Manager 5.3 software. Finally, we included 9 studies comprising 3936 patients with hypertension and COVID-19 infection. Compared with non-ACEI/ARB treatment, ACEI/ARB treatment was not associated with disease severity (OR 0.71, 95 % CI 0.46-1.08, P 0.11, I 2 59%) but was related to lower mortality of COVID-19 in patients with hypertension (OR 0.57, 95 % CI 0.38-0.84, P 0.004, I 2 0). In summary, ACEI/ARB therapy did not aggravate disease severity of COVID-19. Besides, ACEI/ARB therapy can decrease the mortality of COVID-19. Current evidence suggested that RAAS inhibitors should be continued in COVID-19 patients with hypertension. Future well-designed randomized controlled trials are needed to confirm these findings.

Background The neuropathological hallmarks of Alzheimer’s disease (AD) are amyloid-β (Aβ) plaques and neurofibrillary tangles (NFTs). The amyloid cascade theory is the leading hypothesis of AD pathology. Aβ deposition precedes the aggregation of tau pathology and Aβ pathology precipitates tau pathology. Evidence also indicates the reciprocal interactions between amyloid and tau pathology. However, the detailed relationship between amyloid and tau pathology in AD remains elusive. Metformin might have a positive effect on cognitive impairments. However, whether metformin can reduce AD-related pathologies is still unconclusive. Methods Brain extracts containing tau aggregates were unilaterally injected into the hippocampus and the overlying cerebral cortex of 9-month-old APPswe/PS1DE9 (APP/PS1) mice and age-matched wild-type (WT) mice. Metformin was administrated in the drinking water for 2 months. Aβ pathology, tau pathology, plaque-associated microgliosis, and autophagy marker were analyzed by immunohistochemical staining and immunofluorescence analysis 2 months after injection of proteopathic tau seeds. The effects of metformin on both pathologies were explored. Results We observed tau aggregates in dystrophic neurites surrounding Aβ plaques (NP tau) in the bilateral hippocampi and cortices of tau-injected APP/PS1 mice but not WT mice. Aβ plaques promoted the aggregation of NP tau pathology. Injection of proteopathic tau seeds exacerbated Aβ deposits and decreased the number of microglia around Aβ plaques in the hippocampus and cortex of APP/PS1 mice. Metformin ameliorated the microglial autophagy impairment, increased the number of microglia around Aβ plaques, promoted the phagocytosis of NP tau, and reduced Aβ load and NP tau pathology in APP/PS1 mice. Conclusion These findings indicate the existence of the crosstalk between amyloid and NP tau pathology. Metformin promoted the phagocytosis of pathological Aβ and tau proteins by enhancing microglial autophagy capability. It reduced Aβ deposits and limited the spreading of NP tau pathology in APP/PS1 mice, which exerts a beneficial effect on both pathologies.

Objective: To assess the value of the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) during acute phase in predicting post-stroke cognitive impairment (PSCI) at 3-6 months. Methods: We prospectively recruited 229 patients who had suffered their first-ever ischemic stroke. PSCI was determined in 104 of these patients by a comprehensive neuropsychological battery performed at 3-6 months. Receiver operating characteristic (ROC) curve analysis was then performed to compare the discriminatory ability of the MMSE and MoCA. Also, we applied a decision tree generated by the classification and regression tree methodology. Results: In total, 66 patients had PSCI when evaluated 3-6 months after the onset of minor stroke. Logistic regression analysis revealed that education, body mass index (BMI), and baseline MoCA scores were independently associated with PSCI. ROC curve analysis showed that the ability to predict PSCI was similar when compared between baseline MoCA scores [area under curve (AUC), 0.821; 95% confidence interval (CI), 0.743-0.898] and baseline MMSE scores (AUC, 0.809; 95% CI, 0.725-0.892, P = 0.75). Both MMSE and MoCA exhibited similar predictive values at their optimal cutoff points (MMSE ≤27; sensitivity, 0.682; specificity, 0.816; MoCA ≤21; sensitivity, 0.636; specificity, 0.895). Classification and regression tree-derived analysis yielded an AUC of 0.823 (sensitivity, 0.803; specificity, 0.842). Conclusion: When applied within 2 weeks of stroke, the MMSE and MoCA are both useful and have similar predictive value for PSCI 3-6 months after the onset of minor stroke.

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