Microglial surveillance plays an essential role in clearing misfolded proteins such as amyloid-beta, tau, and α-synuclein aggregates in neurodegenerative diseases. However, due to the complex structure and ambiguous pathogenic species of the misfolded proteins, a universal approach to remove the misfolded proteins remains unavailable. Here, we found that a polyphenol, α-mangostin, reprogrammed metabolism in the disease-associated microglia through shifting glycolysis to oxidative phosphorylation, which holistically rejuvenated microglial surveillance capacity to enhance microglial phagocytosis and autophagy-mediated degradation of multiple misfolded proteins. Nanoformulation of α-mangostin efficiently delivered α-mangostin to microglia, relieved the reactive status and rejuvenated the misfolded-proteins clearance capacity of microglia, which thus impressively relieved the neuropathological changes in both Alzheimer's disease and Parkinson's disease model mice. These findings provide direct evidences for the concept of rejuvenating microglial surveillance of multiple misfolded proteins through metabolic reprogramming, and demonstrate nanoformulated α-mangostin as a potential and universal therapy against neurodegenerative diseases.

As an important branch of artificial intelligence, machine learning is widely used in various fields. Machine learning has similarity to classical statistical methods, but can solve many problems which are difficult for traditional statistics, so it is one of the important tools in epidemiological research. This paper introduced 9 common algorithms of machine learning and summarized their characteristics and applications in epidemiological research. Readers could choose appropriate machine learning method according to the research purpose for the better application of machine learning in epidemiological research.

With the accelerating globalization and the implementation of "Belt and Road" initiative proposed by our government, communication and exchanges between China and foreign countries have become more and more frequent than before, and much more international students have chosen to study in China's universities as candidates of master of public health (MPH). However, because China only launched the MPH program in recent years, with the training models being highly similar to the program of master of science in China but quite different from those of main international MPH programs, hindering China's MPH program to become an international one. This paper systematically evaluated existing training models of MPH programs both at home and abroad through literature review and identified major differences and deficiencies of China's MPH program compared to those from other countries: (1) requirement for medical background only; (2) comparatively longer period to complete the program; (3) incomplete curriculum; (4) overemphasizing scientific research competencies but somewhat neglecting practical abilities; and (5) limited career choices, and put forward some suggestions to improve the MPH program of China, including removing requirement for medical background only, shortening the period of MPH program, improving the curriculum of MPH program, and enhancing the training of practical abilities.

In prospective cohort study, multi follow up is often necessary for study subjects, and the observed values are correlated with each other, usually resulting in time-dependent confounding. In this case, the data generally do not meet the application conditions of traditional multivariate regression analysis. Sequential conditional mean model (SCMM) is a new approach that can deal with time-dependent confounding. This paper mainly summarizes the basic theory, steps and characteristics of SCMM.

The diagnosis of COVID-19 is based on the positive of etiological test. The current etiological test of COVID-19 cost long time, and have high false negative rate, may resulting delay the measures of disease treatment and prevention. We suggested that COVID-19 should be diagnosed as 3 types: suspected case, clinical diagnosed case, and definite diagnosed case.

Mediation analysis is mainly used to explore the causal mechanism between independent variable X and dependent variable Y. It determines whether mediator M plays a role and evaluate the role’s degree in the causal path by decomposing the causal path between the independent variable X and the dependent variable Y. However, the classical mediation analysis is generally used for single mediator. This paper introduces a new mediation analysis method for multiple mediators.

At present, traditional methods on statistics have limitations in controlling time- varying confounding. This paper introduces an analysis method, parametric g-formula, which would adjust time-varying confounding, and also exemplifies the steps of its implementation for purpose to provide a new reference for researchers to deal with long-term observational data.

Basal metabolic rate (BMR) is of great significance to the setting of daily energy requirements and the scientific diet guidance for the population. There are 3 kinds of measurement methods for BMR, including the direct calorimetry, the indirect calorimetry, and the equation estimation. The direct calorimetry method is difficult to implement and is only used in some special populations. The indirect calorimetry and the equation estimation are two methods that are currently used commonly. The indirect calorimetry is highly accurate and suitable for individual for basal metabolic measurement or datum collection via equation estimation. The equation estimation is simple and convenient, which is suitable for large samples.
Basal Metabolism ; physiology ; Biomedical Research ; Calorimetry, Indirect ; Energy Metabolism ; Humans

As a metabolic disorder during pregnancy,gestational diabetes mellitus (GDM) has an important effects on fetal development,neonatal health and maternal long-term health,and is one of the pregnancy complications with high incidence.It is of great significance that we have an accurate understanding of the etiology and risk factors of GDM for its prevention and control.GDM is a complex disease with multiple etiologies.Current studies have shown that the occurrence of GDM may be the result of combined effect of heredity and environment,but the exact etiology is still unclear.In this paper,we summarized the possible etiologies and risk factors of GDM,so as to understand the occurrence and development of GDM better and to provide possible references for prevention and further etiological studies of GDM.

Objective:To explore the prognosis of posttraumatic stress disorder (PTSD) in flood survivors 13 years after they had been diagnosed with PTSD symptoms,and investigate the relationship between their personality traits and the prognosis of PTSD.Method:In this cross-sectional study,the survivors of Dongting Lake flood in 1998-1999 in Hunan in China,who were investigated and screened as PTSD symptoms positive in 2000 were selected as the target population,from which a sample of 200subjects was drawn using amulti-stage random sampling method.The Posttraumatic Stress Disorder Scale Civilian Version (PCL-C) was used to examine and re-screen the participants of PTSD symptoms in order to explore the prognosis of PTSD.Participants whose PCL-C scores were equal to 44 or higher were classified as the PTSD symptoms positive group,while those with PCL-C scores less than 44 were classified as the recovered group.Personality traits were then assessed,using the Revised Eysenck Personality Questionnaire Short Scale for Chinese (EPQ-RSC),in both the recovered group and the PTSD symptoms positive group.Finally,the multivariate logistic regression analysis was used to investigate the relationship between the prognosis of PTSD and personality traits.Results:Totally 200 subjects were eligible for this study and completed the questionnaires,but 16 of them had their questionnaires excluded from data analysis because they provided incomplete information.Thus,the response rate was 92.0％.According to the PCL-C's cut-off score,22 participants were still screened as PTSD symptoms positive and were classified as the PTSD symptoms positive group,whereas the other 162 participants were screened as PTSD symptoms negative and were classified as the recovered group.Compared with the recovered group,the EPQ-RSC extroversion scores for the PTSD symptoms positive group were significantly lower [(51.8 ± 10.7) vs.(45.1 ± 13.2),P ＜ 0.05] and their neuroticism scores were significantly higher [(46.5 ± 10.1) vs.(58.3 ± 12.2),P ＜ 0.05].The multivariate logistic regression analysis showed,after adjusting for the variables such as gender and age,that higher neuroticism (OR ＝ 3.63,95％ CI:1.05 -12.54) was a risk factor for the persistent PTSD symptoms in the flood survivors.Conclusions:It suggests that neuroticism is associated with prognosis of PTSD in flood survivors,those with higher neuroticism scores appear to have problems to recover from PTSD.