The mosaic disease in maize is caused by Sugarcane mosaic virus (SCMV), a member of the Potyviridae family. The best strategy to cope with viral infections is the use of disease-resistant maize lines. To better understand the resistance response to SCMV, we analyzed differentially expressed genes among a resistant line (CI-RL1), a susceptible line (B73), and the F1 progeny from a cross between both lines using RNA-Seq data. We also analyzed transcript expression pattern clustering to allocate previously reported resistance candidate genes. GO enrichment analysis of biological processes highlighted a strong regulation in ROS detoxification in both the susceptible and resistant lines. The enrichment of cellular components led to the identification of an integral component of the plasma membrane in the RL line. Transcript expression patterns provide evidence of the importance of host translation in virus response, showing the diverse and complex behavior of eIF4E homologs and the presence of eleven eEF1α factors in maize. In addition, we identified two genes putatively implied in long-distance movement: ZmPiezo and ZmPVIP1. Finally, we propose an ABC transporter to be associated with viral resistance.

The use of active video games or exergames has been booming recently, as they are motivating and promote exercise and healthy lifestyle habits for their users, and these immersive virtual reality (IVR) exercise programs could be compared to traditional physical exercise programs. A starting point for this would be to explore the physiological responses that can be generated by its use. Therefore, the main objective of this study was to evaluate the response across certain physiological parameters (heart rate, blood pressure and stress) after an IVR exergame exposure in a sample of healthy adults, and secondarily to explore its feasibility and usefulness as a tool to facilitate physical exercise. 37 healthy adults (22-54 years, 54.1% women) participated in the study. They carried out one exergaming session with the HTC Vive ProTM hardware. The primary outcome was evaluated using the concentration of cortisol, heart rate and blood pressure. Secondary outcomes were evaluated with safety using the Simulator Sickness Questionnaire (SSQ); usability evaluated with the System Usability Scale (SUS); personal experiences evaluated with Game Experience Questionnaire (GEQ) and perceived exertion through the Borg perceived effort scale. All participants completed the IVR session without significant adverse effects, and all physiological parameters analysed increased significantly in relation to pre-intervention levels. Perceived exertion corresponded to a moderate to intense exercise (6.30±0.50/10 on the modified Borg scale). All the sample considered the experience as good or very good and would recommend it. These findings support that our IVR session can be compared to a moderate to intense physical activity, as it involved similar perceived exertion with significant increases in heart rate, blood pressure and salivary cortisol levels.

Background: Chikungunya virus (CHIKV) diagnosis have become a challenge for primary care physicians in areas where zika virus and/or dengue virus are present. Case definitions for the three arboviral infections are overlapping. Methods: A cross-sectional analysis was carried out. A bivariate analysis was made using confirmed CHIKV infection as the outcome. Variables with significant statistical association were included in an agreement consensus. Agreed variables were analyzed in multiple regression model. The area under the receiver operating characteristic (ROC) curve was calculated to determine a cut-off value and performance. Results: 295 patients with confirmed CHIKV infection were included. A screening tool was made using symmetric arthritis (4 points), fatigue (3 points), rash (2 points) and ankle joint pain (1 point). The ROC curve identified a cut-off value and a score ≥ 5.5 was considered positive to identify CHIKV patients with a sensibility of 64.4% and a specificity of 87.4%, positive predictive value of 85.5%, negative predictive value of 67.7%, area under the curve of 0.72, and an accuracy of 75%. Conclusion: We developed a screening tool for CHIKV diagnosis using only clinical symptoms as well as proposed an algorithm to aid the primary care physician.