Background Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to develop a clinical model to predict the outcome of patients with severe COVID-19 infection early. Methods Demographic, clinical and first laboratory findings after admission of 183 patients with severe COVID-19 infection (115 survivors and 68 non-survivors from the Sino-French New City Branch of Tongji Hospital, Wuhan) were used to develop the predictive models. Machine learning approaches were used to select the features and predict the patients’ outcomes. The area under the receiver operating characteristic curve (AUROC) was applied to compare the models’ performance. A total of 64 with severe COVID-19 infection from the Optical Valley Branch of Tongji Hospital, Wuhan, were used to externally validate the final predictive model. Results The baseline characteristics and laboratory tests were significantly different between the survivors and non-survivors. Four variables (age, high-sensitivity C-reactive protein level, lymphocyte count and d-dimer level) were selected by all five models. Given the similar performance among the models, the logistic regression model was selected as the final predictive model because of its simplicity and interpretability. The AUROCs of the external validation sets were 0.881. The sensitivity and specificity were 0.839 and 0.794 for the validation set, when using a probability of death of 50% as the cutoff. Risk score based on the selected variables can be used to assess the mortality risk. The predictive model is available at [https://phenomics.fudan.edu.cn/risk_scores/]. Conclusions Age, high-sensitivity C-reactive protein level, lymphocyte count and d-dimer level of COVID-19 patients at admission are informative for the patients’ outcomes.

Abstract:Dementia results in brain dysfunction, disability and dependency among affected people, causing an overwhelming burden for caregivers. China has the largest number of people with dementia worldwide and is facing severe challenges with respect to dementia care, including poor awareness of dementia in the public, inadequate knowledge of dementia for medical professionals and caregivers, an underdeveloped dementia service system, and high costs of dementia care. To address these challenges, China is taking action to increase dementia awareness and education among the public and care providers, and develop policies, services and resources for dementia care.

Oxidative damage, mitochondrial dysfunction, and neuroinflammation are strongly implicated in the pathogenesis of neurodegenerative diseases including Alzheimer's disease (AD) and Parkinson's disease (PD), and a substantial portion of elderly population at risk of these diseases requires nutritional intervention to benefit health due to lack of clinically relevant drugs. To this end, anti-inflammatory mechanisms of several phytochemicals such as curcumin, resveratrol, propolis, polyunsaturated fatty acids (PUFAs), and ginsenosides have been extensively studied. However, correlation of the phytochemicals with neuroinflammation or brain nutrition is not fully considered, especially in their therapeutic mechanism for neuronal damage or dysfunction. In this article, we review the advance in antioxidative and anti-inflammatory effects of phytochemicals and discuss the potential communication with brain microenvironment by improved gastrointestinal function, enhanced systemic immunity, and neuroprotective outcomes. These data show that phytochemicals may modulate and suppress neuroinflammation of the brain by several approaches: (1) reducing systemic inflammation and infiltration via the blood-brain barrier (BBB), (2) direct permeation into the brain parenchyma leading to neuroprotection, (3) enhancing integrity of disrupted BBB, and (4) vagal reflex-mediated nutrition and protection by gastrointestinal function signaling to the brain. Therefore, many phytochemicals have multiple potential neuroprotective approaches contributing to therapeutic benefit for pathogenesis of neurodegenerative diseases, and development of strategies for preventing these diseases represents a considerable public health concern and socioeconomic burden.