Objective To establish a dynamic spatiotemporal spread modes of influenza A(H7N9) virus by using discrete geographic information and explore the spatiotemporal transmission of the virus.Methods The gene sequences of H7N9 virus isolated from human in China,which were available from Global Initiative on Sharing Avian Influenza Data (GISAID),were used in alignment by using software BioEdit 7.0.Spatiotcmporal spread model of H7N9 virus was established in a Bayesian statistical framework by using software BEAST 1.8.2.The symmetric substitution model and Bayesian stochastic search variable selection (BSSVS) were used to infer and verify the historical transmission route of H7N9 virus.Finally the spatiotemporal transmission route was presented by Google Earth software.Results The transmission of avian influenza A (H7N9) virus originated in Shanghai and Hangzhou,and can be dated back to October 2012.In March and April 2013,it began to spread to the neighboring provinces.The transmission speed up in August and September and affected more than ten geographic positions within 3 months.Conclusion Based on gene sequences and spatial geographic information,the transmission route of H7N9 virus was traced,which would support the avian influenza prevention and control as well as avian influenza virus tracing.

Objective To establish a multi-regression workload model based on surgical related factors.Methods The routine surgery workload was measured by the RBRVS development process of Hsiao WC,and multiple regression models were established for the operative factors from the surgical project specifications,pricing regulations and the operative workload.Results Top workload factors of an operation were technical difficulty,surgical classification and time cost.Multiple regression equation R2=0.699.One degree increase of technical difficulty would push up workload by 0.034;one level of operation grade would raise workload by 0.793;and every one hour longer of the operation time would increase workload by 1.025. Conclusions Operations of higher level, technical difficulty and longer time cost should deserve more reimbursement in consideration of both pricing and income distribution.

Objective: To explore the cognitive functions of the elderly aged 60 years and above in Xiamen, and whether TV watching time would affect those functions. Methods: We conducted a cross-sectional study on 3 230 registered individuals aged 60 years and above in Xiamen from July to October in 2016 with a multi-stage random sampling method. Montreal Cognitive Assessment (MoCA) was used to measure cognitive functions and ordinal logistic regression was used to quantify their associations with TV watching time. Results: A total of 2 944 respondents were included in this study. The overall age of them was (70.14±7.81) years. 51.49% (n=1 516) of all participants were men. Overall, the mean scores of MoCA in general and each subdomain cognitive function were 18.65±6.43 (general), 5.43±1.17 (orientation), 2.33±1.95 (memory), 1.80±1.52 (visuospatial), 1.66±1.20 (executive), 4.54±1.71 (attention), and 4.09±1.64 (language). Compared to those who watched TV no more than 2 hours per day, the elderly who did not watch TV had a worse performance in general, orientation, memory, visuospatial, executive, attention, language function, with OR (95%CI) values about 0.50 (0.35-0.71), 0.52 (0.37-0.73), 0.68 (0.48-0.96), 0.67 (0.47-0.96), 0.48 (0.34-0.67), 0.56 (0.41-0.77) and 0.45 (0.33-0.62), respectively. As to respondents who watched TV more than 2 hours but no more than 4 hours per day, they had a better performance in general, executive, attention, language, and orientation function with respective OR (95%CI) values about 1.24 (1.05-1.47), 1.20 (1.02-1.41), 1.41 (1.19-1.67), 1.51 (1.28-1.77) and 1.33 (1.08-1.64). Conclusion The elderly aged 60 years and above in Xiamen City with TV watching time between 2 and 4 hours per day had a good performance in cognitive functions compared to those with more or less TV watching time.

Mild cognitive impairment(MCI)is a prodromal phase of dementia with heterogeneity in etiology, clinical presentation, disease progression, outcome, and prognosis.The number of studies on MCI subtypes is increasing each year.This article discussed the subtypes of MCI from the perspectives of phenotypic characteristics, etiology, progression, outcome, and data-driven approaches, and further summarizes the epidemiological characteristics, influencing factors, and risk of progression to dementia of each subtype.Despite the increasing number of studies on MCI subtyping, research remains limited on the correlation between MCI subtypes from different perspectives, indicating a need for further investigation in order to achieve more accurate and effective diagnosis and treatment of MCI and obtain evidence for dementia prevention.