The Smad7 protein is negative regulator of the TGF-β signaling pathway, which is upregulated in patients with breast cancer. miRNAs regulate proteins expressions by arresting or degrading the mRNAs. The purpose of this work is to identify a miRNAs profile that regulates the expression of the mRNA coding for Smad7 in breast cancer using the data from patients with breast cancer obtained from the Cancer Genome Atlas Project. We develop an automatic search method based on genetic algorithms to find a predictive model based on deep neural networks (DNN) which fit the set of biological data and apply the Olden algorithm to identify the relative importance of each miRNAs. A computational model of non-linear regression is shown, based on deep neural networks that predict the regulation given by the miRNA target transcripts mRNA coding for Smad7 protein in patients with breast cancer, with R2 of 0.99 is shown and MSE of 0.00001. In addition, the model is validated with the results in vivo and in vitro experiments reported in the literature. The set of miRNAs hsa-mir-146a, hsa-mir-93, hsa-mir-375, hsa-mir-205, hsa-mir-15a, hsa-mir-21, hsa-mir-20a, hsa-mir-503, hsa-mir-29c, hsa-mir-497, hsa-mir-107, hsa-mir-125a, hsa-mir-200c, hsa-mir-212, hsa-mir-429, hsa-mir-34a, hsa-let-7c, hsa-mir-92b, hsa-mir-33a, hsa-mir-15b, hsa-mir-224, hsa-mir-185 and hsa-mir-10b integrate a profile that critically regulates the expression of the mRNA coding for Smad7 in breast cancer. We developed a genetic algorithm to select best features as DNN inputs (miRNAs). The genetic algorithm also builds the best DNN architecture by optimizing the parameters. Although the confirmation of the results by laboratory experiments has not occurred, the results allow suggesting that miRNAs profile could be used as biomarkers or targets in targeted therapies.

Gap junction (GJ) channels in invertebrates have been used to understand cell-to-cell communication in vertebrates. GJs are a common form of intercellular communication channels which connect the cytoplasm of adjacent cells. Dysregulation and structural alteration of the gap junction-mediated communication have been proven to be associated with a myriad of symptoms and tissue-specific pathologies. Animal models relying on the invertebrate nervous system have exposed a relationship between GJs and the formation of electrical synapses during embryogenesis and adulthood. The modulation of GJs as a therapeutic and clinical tool may eventually provide an alternative for treating tissue formation-related diseases and cell propagation. This review concerns the similarities between Hirudo medicinalis innexins and human connexins from nucleotide and protein sequence level perspectives. It also sets forth evidence of computational techniques applied to the study of proteins, sequences, and molecular dynamics. Furthermore, we propose machine learning techniques as a method that could be used to study protein structure, gap junction inhibition, metabolism, and drug development.

This research was carried out in the Mexican manufacturing industry, the second most important activity in the country's industrial sector, specifically in the transportation equipment manufacturing subsector, which generates 19% of the jobs in this industry. Thus, it is important to develop improvement strategies to strengthen the sector’s competitiveness. Currently, Lean Manufacturing projects are considered the most important strategy for manufacturing companies to achieve world-class performance. However, such projects yield different results, depending on the level of Critical Success Factor (CSFs) implementation during their development. This work proposes the design and validation of an instrument to evaluate the implementation of CSFs during the project-improvement phase in the production of transportation equipment in the Mexican manufacturing industry. The instrument is made up of six CSFs selected from the reviewed literature on Lean Manufacturing methodology and improvement projects and measured through 31 items. The instrument was verified and empirically validated through exploratory factor analysis, confirmatory factor analysis, and reliability analysis, using the SPSS Amos ® software program and a sample of 240 valid surveys applied to experienced developers of Lean Manufacturing improvement projects. The results show that the proposed instrument holds enough statistical validity to be used by the companies in the sector in order to assess the impact of critical success factors on the development of improvement projects. Additionally, the survey can help companies to identify areas of opportunity by adopting the Lean Manufacturing methodology and fit models, to assess the interaction of the FCEs in achieving the expected results of improvement projects.

The purpose of the this research work was to evaluate the impact of social support (through its two dimensions: co-worker support and supervisor support) on the reduction of the burnout syndrome (considering its three dimensions: emotional exhaustion, professional efficacy, and cynicism) from two proposed models that show clear differences. Social support was assessed using the Job Content Questionnaire instrument, and the burnout syndrome was measured through the Maslach Burnout Inventory - General Survey. A total of 467 middle and senior managers from the Mexican manufacturing industry participated in the research. Structural Equation Modeling was used to determine the relationships between the proposed variables. The results of model one show that social support helps mitigate the effects of burnout syndrome in its three dimensions. On the other hand, model two features better fit indices and specifically shows that co-worker support has a direct negative relationship with the dimension of emotional exhaustion, while supervisor support directly and negatively affects cynicism. These results show that, although social support helps in the mitigation of burnout syndrome in general, each type of support separately has a direct impact on a specific dimension of the burnout syndrome. Clarifying these relationships will help in the proposal of occupational hazard management policies in the Mexican industrial sector.