The mosquito species Aedes aegypti (Linneaus) is the vector of multiple arboviruses, including dengue, Chikungunya, Zika, and yellow fever. Risk of infections associated with these arboviruses continues to expand as the geographical range of Ae. aegypti extends into temperate regions.
View Article and Find Full Text PDFAnim Sci J
November 2024
In this study, the inclusion of water fly (Notonecta sp., NT) meal was compared with conventional protein sources such as soybean meal (SBM) and fish meal (FM) in diets destined for sheep, with specific reference to growth performance, nutrient intake, nitrogen balance, and in vitro rumen fermentation parameters. For 21 days, 18 male Suffolk lambs were randomly assigned to three experimental diets fed: (1) SBM at 130 g/kg dry matter (DM), as a plant-based protein diet; (2) FM at 50 g/kg DM, as an animal-based protein diet; and (3) NT at 60 g/kg DM, as an insect-based protein diet, for ad libitum feed intake.
View Article and Find Full Text PDFAspiration pneumonia (AP) is the most severe complication of oropharyngeal dysphagia (OD). It is highly underdiagnosed and undertreated among older patients hospitalized with community-acquired pneumonia (CAP). Our aim is to review the state of the art in the diagnosis and treatment of swallowing disorders associated with AP.
View Article and Find Full Text PDFBackground: Data on long-term neurodevelopmental outcomes of normocephalic children (born with normal head circumference) exposed to Zika virus in utero are scarce. We aimed to compare neurodevelopmental outcomes in normocephalic children up to age 48 months with and without Zika virus exposure in utero.
Methods: In this prospective cohort study, we included infants from two cohorts of normocephalic children born in León and Managua, Nicaragua during the 2016 Zika epidemic.
Mathematical models of biomolecular networks are commonly used to study cellular processes; however, their usefulness to explain and predict dynamic behaviors is often questioned due to the unclear relationship between parameter uncertainty and network dynamics. In this work, we introduce PyDyNo (Python dynamic analysis of biochemical networks), a non-equilibrium reaction-flux based analysis to identify dominant reaction paths within a biochemical reaction network calibrated to experimental data. We first show, in a simplified apoptosis execution model, that despite the thousands of parameter vectors with equally good fits to experimental data, our framework identifies the dynamic differences between these parameter sets and outputs three dominant execution modes, which exhibit varying sensitivity to perturbations.
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