👤 Francisco J Naya

Obesity is a highly prevalent disorder with complex aetiology. Therefore, studying its associated cellular and molecular pathways may be aided by analysing genetic tractable diseases. In this context, the study of ciliopathies such as Bardet-Biedl syndrome has highlighted the relevance of primary cilia in obesity, both in the central nervous system and peripheral tissues. Based on our previous Show less

The rapid spread of SARS-CoV-2 threatens global public health and impedes the operation of healthcare systems. Several studies have been conducted to confirm SARS-CoV-2 infection and examine its risk factors. To produce more effective treatment options and vaccines, it is still necessary to investigate biomarkers and immune responses in order to gain a deeper understanding of disease pathophysiology. This study aims to determine how cytokines influence the severity of SARS-CoV-2 infection. We measured the plasma levels of 48 cytokines in the blood of 87 participants in the COVID-19 study. Several Classifiers were trained and evaluated using Machine Learning and Deep Learning to complete missing data, generate synthetic data, and fill in any gaps. To examine the relationship between cytokine storm and COVID-19 severity in patients, the Shapley additive explanation (SHAP) and the LIME (Local Interpretable Model-agnostic Explanations) model were applied. Individuals with severe SARS-CoV-2 infection had elevated plasma levels of VEGF-A, MIP-1b, and IL-17. RANTES and TNF were associated with healthy individuals, whereas IL-27, IL-9, IL-12p40, and MCP-3 were associated with non-Severity. These findings suggest that these cytokines may promote the development of novel preventive and therapeutic pathways for disease management. In this study, the use of artificial intelligence is intended to support clinical diagnoses of patients to determine how each cytokine may be responsible for the severity of COVID-19, which could lead to the identification of several cytokines that could aid in treatment decision-making and vaccine development. Show less

The uneven spatial distribution of biodiversity is a defining feature of nature. In fact, the implementation of conservation actions both locally and globally has progressively been guided by the identification of biodiversity 'hotspots' (areas with exceptional biodiversity). However, different regions of the world differ drastically in the availability of fine-scale data on the diversity and distribution of species, thus limiting the potential to assess their local environmental priorities. Within South America-a megadiverse continent-Uruguay represents a peculiar area where multiple tropical and non-tropical eco-regions converge, creating highly heterogeneous ecosystems, but where the systematic quantification of biodiversity remains largely anecdotal. To investigate the constraints posed by the limited access to biodiversity data, we employ the most comprehensive database for tetrapod vertebrates in Uruguay (spanning 664 species) assembled to date, to identify hotspots of species-richness, endemism and threatened species for the first time. Our results reveal negligible spatial congruence among biodiversity hotspots, and that tetrapod sampling has historically concentrated in only a few areas. Collectively, our study provides a detailed account of the areas where urgent biodiversity monitoring efforts are needed to develop more accurate knowledge on biodiversity patterns, offering government and environmental bodies a critical scientific resource for future planning. Show less

To identify key oncogenes and proteins that are controlled by the microRNA miR-29 family (miR-29a, miR-29b and miR-29c) in renal cell carcinoma pathogenesis. Genome-wide gene expression and in silico database analyses were carried out. The Cancer Genome Atlas database was used to investigate the clinical significance of gene expression data in renal cell carcinoma patients. Loss-of-function assays were applied to investigate the function of target genes. We identified 47 possible target genes that might be regulated by the miR-29 family in renal cell carcinoma cells. Among the targets of the miR-29 family, high expression of 10 genes (ADAMTS14, TRIB13, SERPINH1, FCGR1B, COL1A1, LAIR2, WISP2, TREM1, TNKS1BP1 and GBP2) significantly predicted poor patient prognosis (P < 0.001). SERPINH1 was directly regulated by the miR-29 family, and its overexpression was detected in renal cell carcinoma surgical specimens and tyrosine kinase inhibitor failure autopsy specimens. High expression of SERPINH1 was significantly associated with tumor stage, pathological grade and poor prognosis (P < 0.0001). Knockdown assays showed that its expression enhanced cancer cell migration and invasive abilities. Genes regulated by the anti-tumor miR-29 family are closely involved in the molecular pathogenesis of renal cell carcinoma. Our approach based on anti-tumor microRNAs might contribute to the development of new diagnostic markers and therapeutic strategies. Show less