ABSTRACT
BACKGROUND: As the global population ages, cognitive impairment (CI) becomes more prevalent. Tea has been one of the most popular drinks in the world. Several studies have demonstrated that tea consumption has an impact on cognitive function. OBJECTIVE: This study aims to examine the association between tea consumption and cognitive function and explore the potential effect of genetics on the relationship between tea consumption and CI risk in older adults. DESIGN: This is a prospective longitudinal study using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). SETTING: Six waves of data from CLHLS containing 76,270 subjects were analyzed. Generalized estimation equations (GEE) with a logit link function were adopted to estimate the effect of tea consumption on CI risk from a cross-sectional and longitudinal perspective. PARTICIPANTS: A population-based cohort of adults aged 65-105 years. MEASUREMENTS: The frequency and type of tea consumption were obtained by questionnaires. CI was measured based on MMSE. Polygenic risk was measured using the polygenic score approach described by the International Schizophrenia. RESULTS: The results showed that drinking green tea had a better protective effect on cognitive function than other types of tea, the incidence of CI gradually decreased with the increase of tea consumption frequency, and men were more likely to benefit from tea consumption. Additionally, we also found a significant interaction between tea consumption and genetic risk, measured by polygenic risk score (PRS). CONCLUSIONS: Based on current research evidence, tea consumption, may be a simple and important measure for CI prevention.
Subject(s)
Cognition , Cognitive Dysfunction , Tea , Humans , Male , Aged , Female , Longitudinal Studies , Cognition/physiology , Cognitive Dysfunction/genetics , Cognitive Dysfunction/epidemiology , Aged, 80 and over , Prospective Studies , Cross-Sectional Studies , China/epidemiologyABSTRACT
Microwave reflectometry diagnostics have been widely used to measure density profiles in fusion plasma. However, the high sensitivity of the diagnostics to plasma turbulence often results in large radial deviations in the edge density profile and causes difficulty in profile evaluation. To improve the performance of profile evaluation, a modified RANdom SAmple Consensus (RANSAC) method has been applied to fit the density profiles measured by reflectometry on the experimental advanced superconducting tokamak. Compared with the traditional least-squares method, the modified RANSAC method is much more efficient and robust in fitting the experimental profiles. Furthermore, a combination of RANSAC and a genetic algorithm (GA-RANSAC) is used to further optimize the profile evaluation procedure. The results show that this GA-RANSAC method yields better performance and stabler convergence than the modified RANSAC alone.
ABSTRACT
An ordinary-mode polarized multi-channel correlation reflectometer has been developed on the Experimental Advanced Superconducting Tokamak (EAST). The system with four different probing frequencies (i.e., 20.4 GHz, 24.8 GHz, 33 GHz, and 40 GHz) and two poloidally spaced receiving antennas can realize both the radial correlation measurement and the poloidal correlation measurement. These diagnostics focus on the measurement of density fluctuation in the pedestal region to investigate the turbulence transport and H-mode physics on EAST. In this article, the system hardware design, the key component tests, and the system performance are shown in detail.