👤 Bernardo Bertoni

Combined exercise training (CET) has been associated with positive responses in the clinical status of patients with heart failure (HF). Other nonpharmacological tools, such as amino acid supplementation, may further enhance its adaptation. The aim was to test whether CET associated with supplementing carnosine precursors could present better responses in the functional capacity and biochemical variables of rats with HF. Twenty-one male Wistar rats were subjected to myocardial infarction and allocated to three groups: sedentary (SED, n = 7), CET supplemented with placebo (CETP, n = 7), and CET with HF supplemented with β-alanine and L-histidine (CETS, n = 7). The trained animals were submitted to a strength protocol three times per week. Aerobic training was conducted twice per week. The supplemented group received β-alanine and L-histidine orally (250 mg/kg per day). Maximum oxygen uptake, running distance, time to exhaustion and maximum strength were higher in the CET-P group than that in the SED group and even higher in the CET-S group than that in the CET-P group (P < 0.01). CET-S showed lower oxidative stress and inflammation markers and higher heat shock protein 72 kDa content and mRNA expression for calcium transporters in the skeletal muscle compared to SED. CET together with β-alanine and L-histidine supplementation in rats with HF can elicit adaptations in both maximum oxygen uptake, running distance, time to exhaustion, maximum strength, oxidative stress, inflammation and mRNA expression. Carnosine may influence beneficial adjustments in the cell stress response in the skeletal muscle and upregulate the mRNA expression of calcium transporters. Show less

Chemical descriptors encode the physicochemical and structural properties of small molecules, and they are at the core of chemoinformatics. The broad release of bioactivity data has prompted enriched representations of compounds, reaching beyond chemical structures and capturing their known biological properties. Unfortunately, bioactivity descriptors are not available for most small molecules, which limits their applicability to a few thousand well characterized compounds. Here we present a collection of deep neural networks able to infer bioactivity signatures for any compound of interest, even when little or no experimental information is available for them. Our signaturizers relate to bioactivities of 25 different types (including target profiles, cellular response and clinical outcomes) and can be used as drop-in replacements for chemical descriptors in day-to-day chemoinformatics tasks. Indeed, we illustrate how inferred bioactivity signatures are useful to navigate the chemical space in a biologically relevant manner, unveiling higher-order organization in natural product collections, and to enrich mostly uncharacterized chemical libraries for activity against the drug-orphan target Snail1. Moreover, we implement a battery of signature-activity relationship (SigAR) models and show a substantial improvement in performance, with respect to chemistry-based classifiers, across a series of biophysics and physiology activity prediction benchmarks. Show less

In Mexico, the genetic mechanisms underlying childhood obesity are poorly known. We evaluated the effect of loci, known to be associated with childhood body mass index (BMI) in Europeans, in Mexican children from different ethnic groups. We performed linear and logistic analyses of BMI and obesity, respectively, in Mestizos and Amerindians (Seris, Yaquis and Nahuatl speakers) from Northern ( Show less