Novel Methods for Surface EMG Analysis and Exploration Based on Multi-Modal Gaussian Mixture Models

<div><p>This paper introduces a new method for data analysis of animal muscle activation during locomotion. It is based on fitting Gaussian mixture models (GMMs) to surface EMG data (sEMG). This approach enables researchers/users to isolate parts of the overall muscle activation within locomotion EMG data. Furthermore, it provides new opportunities for analysis and exploration of sEMG data by using the resulting Gaussian modes as atomic building blocks for a hierarchical clustering. In our experiments, composite peak models representing the general activation pattern per sensor location (one sensor on the long back muscle, three sensors on the gluteus muscle on each body side) were identified per individual for all 14 horses during walk and trot in the present study. Hereby we show the applicability of the method to identify composite peak models, which describe activation of different muscles throughout cycles of locomotion.</p></div

Genetic Diversity of Drug-Related Genes in Native Americans of the Brazilian Amazon

Introduction: The genetic admixture of the Brazilian population has considerable relevance to the implementation of the principles of pharmacogenomics (PGx), as it may compromise the extrapolation of data obtained in more homogeneous world populations. Purpose: This study aims to investigate a panel of 117 polymorphisms in 35 pharmacogenes, which contains label recommendations or clinical evidence by international drug regulatory agencies, in Amazonian Native American populations, and compare the results obtained with continental population data from the 1000 Genomes Project Consortium. Patients and Methods: The study population is composed of 109 Native American individuals from three Brazilian Amazon groups. The genotyping of the PGx polymorphisms was performed by allelic discrimination using TagMan (R) OpenArray Genotyping with a panel of 120 customized assays on the QuantStudio (TM) 12K Flex Real-Time PCR System. Results: Statistical differences within the Native American populations were observed regarding both genotypes and phenotypes of some genes of the CYP family. The discriminant analysis of principal components (DAPC5) between the NAM group and the continental populations of the 1000 Genomes Project resulted in the clustering of the three Native American populations. Additionally, in general, the NAM group was determined to be closely situated between East Asia, America, and South Asia groups, which enabled us to infer a genetic similarity between these populations. The DAPC analysis further demonstrated that eight polymorphisms and six polymorphisms were more relevant in differentiating the NAM from the continental populations and the NAM populations among themselves, respectively. Conclusion: Some investigated polymorphisms show differences among world populations, particularly with populations of European origin, for whom precision medicine protocols are primarily designed. The accumulated knowledge regarding these variations may assist in the design of specific protocols for Native American populations and populations admixed with them