Publications by authors named "Claudia G Penuelas-Rivas"

Medium-scale pig production systems, which make up 30 % of Mexico's pig farms, face two key obstacles impacting their economic and financial performance. The first is the absence of a sales plan based on pigs' weight, which negatively affects both profitability and resource management. The second obstacle is inadequate waste management, which hampers efforts to mitigate environmental impacts generated by pig farms.

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To estimate the economic and financial viability of a pig farm in central sub-tropical Mexico within a 5-year planning horizon, a Monte Carlo simulation model was utilized. Net returns were projected using simulated values for the distribution of input and product processes, establishing 2021 as base scenario. A stochastic modelling approach was employed to determine the economic and financial outlook.

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Unbalanced uptake of Omega 6/Omega 3 (ω-6/ω-3) ratios could increase chronic disease occurrences, such as inflammation, atherosclerosis, or tumor proliferation, and methylation methods for measuring the ruminal microbiome fatty acid (FA) composition/distribution play a vital role in discovering the contribution of food components to ruminant products (e.g., meat and milk) when pursuing a healthy diet.

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Quantitative Structure-Activity (mt-QSAR) techniques may become an important tool for prediction of cytotoxicity and High-throughput Screening (HTS) of drugs to rationalize drug discovery process. In this work, we train and validate by the first time mt-QSAR model using TOPS-MODE approach to calculate drug molecular descriptors and Linear Discriminant Analysis (LDA) function. This model correctly classifies 8258 out of 9000 (Accuracy = 91.

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Entropy measures are universal parameters useful to codify biologically-relevant information in many systems. In our previous work, (Gonzalez-Diaz, H., et al.

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Bibliometric methods for analyzing and describing research output have been supported internationally by the establishment and operation of organizations such as the Institute for Scientific Information (ISI) or Scimago Ranking Institutions (SRI). This study provides an overview of the research performance of major World countries in the field cytokines, Citometric bead assays and QSAR, the most important journals in which they published their research articles, and the most important academic institutions publishing them. The analysis was based on Thomson Scientific's Web of Science (WoS), and Scimago group calculated bibliometric indicators of publication activity and actual citation impact.

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Article Synopsis
  • Multiplexed biological assays allow for multiple cellular measurements in a single test, and this study explores the use of an Artificial Neural Network (ANN) model to predict the effects of drugs on macrophage populations.
  • The research identified the best ANN model as a Linear Neural Network (LNN), which achieved a 93.0% accuracy in classifying drug effects across 6900 drug endpoints.
  • Additionally, experimental findings demonstrated the cytotoxicity of drug G1 on mouse macrophages and utilized the LNN model to predict G1's activity in numerous untested multiplex assays, paving the way for innovative 'in silico' drug screening methods.
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