Publications by authors named "M A Andrade-Navarro"

Background: Glioblastoma multiforme (GBM) is characterized by its cellular complexity, with a microenvironment consisting of diverse cell types, including oligodendrocyte precursor cells (OPCs) and neoplastic CD133 + radial glia-like cells. This study focuses on exploring the distinct cellular transitions in GBM, emphasizing the role of alternative polyadenylation (APA) in modulating microRNA-binding and post-transcriptional regulation.

Results: Our research identified unique APA profiles that signify the transitional phases between neoplastic cells and OPCs, underscoring the importance of APA in cellular identity and transformation in GBM.

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Homorepeats, specifically polyglutamine (polyQ) and polyalanine (polyA), are often implicated in protein-protein interactions (PPIs). So far, a method to predict the participation of homorepeats in protein interactions is lacking. We propose a machine learning approach to identify PPI-involved polyQ and polyA regions within the human proteome based on known interacting regions.

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Epigenetic aberration is one of the major driving factors in human cancer, often leading to acquired resistance to chemotherapies. Various small molecule epigenetic modulators have been reported. Nonetheless, outcomes from animal models and clinical trials have underscored the substantial setbacks attributed to pronounced on- and off-target toxicities.

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Article Synopsis
  • Skin inflammation and conditions like moist epitheliolysis and edema are common acute side effects of breast radiotherapy (RT).
  • The study aimed to evaluate the effectiveness of tissue-derived radiomics features compared to total breast volume (TBV) in predicting these side effects.
  • The best predictive model used a LASSO classifier based on TBV, achieving an AUROC of 0.74, similar to the AUROC of 0.75 for TBV alone, with mammary tissue showing greater predictive power than glandular tissue.
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Background: Reproducibility is a major concern in biomedical studies, and existing publication guidelines do not solve the problem. Batch effects and quality imbalances between groups of biological samples are major factors hampering reproducibility. Yet, the latter is rarely considered in the scientific literature.

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