RESUMO
Objective Through the establishment of the model of mental fatigue which was induced by continuous mental workload,compare the changes in cognitive function before and after simulated flight and investigate the pattern of heart rate variability (HRV) during the period of simulated flight,thus providing the foundation of screening objective indices for monitoring mental fatigue.Methods A total of 30 participants were informed to take part in a simulated flight for 4 hours.They were arranged to complete the Stanford Sleepiness Scale (SSS) and two cognitive tests,including psychomotor vigilance task (PVT) and shifting attention test (SAT) before and after simulated flight severally.HRV was recorded continuously during the period of simulated flight.Results After simulated flight,the scores of SSS significantly increased (P＜0.05) and mean reaction times to PVT and SAT were longer compared with presimulated flight (P＜0.05).Heart rate (HR) and RMSSD considered as the time domain index of HRV showed significant difference during the period of simulated flight (F=9.81,F=4.75,respectively,both P＜0.05).The results indicate that HR declined and RMSSD of HRV increased significantly,while no significant differences were found in other time domain component and the frequency domain component of HRV.Conclusions The mean reaction times of cognitive tests are sensitive indices to monitor mental fatigue.However,when the time domain component and the frequency domain component of HRV are applied into monitoring mental fatigue,there are still some limitations in different conditions.
RESUMO
In Taiwan, the first human-infecting H6N1 avian influenza virus was isolated in 2013. To better understand the origin, evolutionary relationship and pathogenesis of the H6N1 virus, we studied the adaptive evolution and evolutionary dynamics of the hemagglutinin (HA) genes of the H6N1 virus in Taiwan. We felt that such studies woud contribute to the further study and control of the virus. Datasets were gained from the Flu and Global Initiative on Sharing All Influenza Data (GISAID) databases. Then, phylogenetic trees and evolutionary dynamics were reconstructed. The evolutionary rate and characterization of adaptive evolution were analyzed by bioinformatic methods. Results indicated that the HA genes of H6N1 in Taiwan were divided into at least five types, and that the new types that the infected human H6N1 belonged to could be local advantage type at present. Evolutionary dynamics revealed the viral population expanded first at the end of 1971, reduced sharply in 2008, and then increased slightly. Three sites were identified under positive selection, suggesting that various sites might increase the adaptive ability of the virus. Eighty-nine sites were under negative selection, revealing that these sites might play an important role in the replication and epidemiology of the virus. Interestingly, site 329 upstream from the cleavage site was also under negative selection, suggesting that this site might be associated with the virulence of H6N1. These data suggest that the HA genes of the Taiwanese H6N1 virus have been undergoing adaptive evolution, and that an outbreak may occur again. Hence, more attention should be paid to the identified sites, to enable timely monitoring and control of a future epidemic.