Rare functional variants associated with antidepressant remission in Mexican-Americans: short title: antidepressant remission and pharmacogenetics in Mexican-Americans

Introduction: Rare genetic functional variants can contribute to 30-40% of functional variability in genes relevant to drug action. Therefore, we investigated the role of rare functional variants in antidepressant response. Method: Mexican-American individuals meeting the Diagnostic and Statistical Manual-IV criteria for major depressive disorder (MDD) participated in a prospective randomized, double-blind study with desipramine or fluoxetine. The rare variant analysis was performed using whole-exome genotyping data. Network and pathway analyses were carried out with the list of significant genes. Results: The Kernel-Based Adaptive Cluster method identified functional rare variants in 35 genes significantly associated with treatment remission (False discovery rate, FDR <0.01). Pathway analysis of these genes supports the involvement of the following gene ontology processes: olfactory/sensory transduction, regulation of response to cytokine stimulus, and meiotic cell cycleprocess. Limitations: Our study did not have a placebo arm. We were not able to use antidepressant blood level as a covariate. Our study is based on a small sample size of only 65 Mexican-American individuals. Further studies using larger cohorts are warranted. Conclusion: Our data identified several rare functional variants in antidepressant drug response in MDD patients. These have the potential to serve as genetic markers for predicting drug response. Trial Registration: ClinicalTrials.gov NCT00265291.Ma-Li Wong, Mauricio Arcos-Burgos, Sha Liu, Alice W. Licinio, Chenglong Yu, Eunice W.M. Chin, Wei-Dong Yao, Xin-Yun Lu, Stefan R. Bornstein, Julio Licini

Factors affecting horticultural and cleaning workers\u27 preference on cooling vests

Outdoor workers are at high risk of suffering from heat-related illness when they are exposed to a hot and humid environment under prolonged working time. Providing suitable cooling vests for these workers might help alleviate heat stress during summer time. However, whether workers are willing to wear cooling vests is still uncertain because of various personal preferences. To understand the determinants of worker preferences on two kinds of cooling vests, field studies were conducted in construction, horticulture and cleaning, and airport apron services industries, respectively. Workers were asked to rate 18 items of subjective attributes from a self-administrated questionnaire. Based on 17 items of subjective attributes, workers revealed four underlying factors; namely, thermal comfort, usability, tactile comfort, and fabric hand (feel), as the underlying factors affecting their preference. Multiple linear regression analysis was conducted between the four underlying factors derived from factor analysis and one dependent variable ‘dislike–like’ to find out the reasons why horticultural and cleaning workers preferred one type of cooling vest over the others. Results indicated that while male and female workers were influenced differently by different underlying factors, usability was the common and determining factor having the strongest correlation with their preference regardless of gender difference. Thermal comfort, tactile comfort, and fabric hand (feel) were also important factors affecting their preferences. However, the choices of male workers were influenced more by thermal comfort, whereas female workers paid more attention to tactile comfort and fabric hand (feel). Therefore, gender differences should be considered in designing and constructing suitable cooling vests

Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models