Adult Ossabaw Pigs Prefer Fermented Sorghum Tea over Isocaloric Sweetened Water.

Ossabaw pigs (n = 11; 5-gilts, 6-barrows; age 15.6 ± 0.62 SD months) were exposed to a three-choice preference maze to evaluate preference for fermented sorghum teas (FSTs). After conditioning, pigs were exposed, in four sessions, to choices of white FST, sumac FST, and roasted sumac-FST. Then, pigs were exposed, in three sessions, to choices of deionized H2O (-control; avoidance), isocaloric control (+control; deionized H2O and sucrose), and blended FST (3Tea) (equal portions: white, sumac, and roasted sumac). When tea type was evaluated, no clear preference behaviors for tea type were observed (p > 0.10). When the 3Tea and controls were evaluated, pigs consumed minimal control (p < 0.01;18.0 ± 2.21% SEM), and they consumed great but similar volumes of +control and 3Tea (96.6 and 99.0 ± 2.21% SEM, respectively). Likewise, head-in-bowl duration was the least for -control, but 3Tea was the greatest (p < 0.01; 5.6 and 31.9 ± 1.87% SEM, respectively). Head-in-bowl duration for +control was less than 3Tea (p < 0.01; 27.6 vs. 31.9 ± 1.87% SEM). Exploration duration was the greatest in the area with the -control (p < 0.01; 7.1 ± 1.45% SEM), but 3Tea and +control exploration were not different from each other (1.4 and 3.0 ± 1.45% SEM, respectively). Regardless of tea type, adult pigs show preference for FST, even over +control. Adult pigs likely prefer the complexity of flavors, rather than the sweetness alone.

Machine Learning and Perturbation Theory Machine Learning (PTML) in Medicinal Chemistry, Biotechnology, and Nanotechnology.

Recently, different authors have reported Perturbation Theory (PT) methods combined with machine learning (ML) to obtain PTML (PT + ML) models. They have applied PTML models to the study of different biological systems. Here we present one state-of-art review about the different applications of PTML models in Organic Synthesis, Medicinal Chemistry, Protein Research, and Technology. The aim of the models is to find relations between the molecular descriptors and the biological characteristics to predict key properties of new compounds. An area where the ML has been very useful is the drug discovery process. The entire process of drug discovery leads to the generation of lots of data, and it is also a costly and time-consuming process. ML comes with the opportunity of analyzing significant amounts of chemical data obtaining outcomes to find potential drug candidates.

Coumarin-Rasagiline Hybrids as Potent and Selective hMAO-B Inhibitors, Antioxidants, and Neuroprotective Agents.

The frequency, complexity and morbidity of neurodegenerative diseases make them a great challenge for nowadays medicine. Most of the treatments currently used for Parkinson's disease - the second most prevalent - are only symptomatic. Therefore, it is urgent to develop drugs that are able to act simultaneously on different targets, being able to stop neuronal death and promote the recovery of neuronal populations already affected. In this work, we studied the activity of a series of hybrid molecules, which combine the structure of both coumarin and an alkynylamine group inspired on rasagiline, as MAO inhibitors, antioxidants and neuroprotective agents. Half of the studied hybrids turned out to be selective monoamine oxidase B (hMAO-B) inhibitors in the low micro/nanomolar range, demonstrating that positions 3 (compounds 1-3) and 7 (compounds 8 and 10) of the coumarin scaffold are the most suitable for the incorporation of the alkynylamine chain. All the studied compounds proved to be capable of neutralizing free radicals (DPPH). Finally, the 4-(but-2-yn-1-ylamino)coumarin (5) showed neuroprotective effects on glial cells and the 4-methyl-7-(pent-2-yn-1-ylamino)coumarin (8) inhibited intraneuronal ROS production as well.

Genome Characterization of a Pathogenic Porcine Rotavirus B Strain Identified in Buryat Republic, Russia in 2015.

An outbreak of enteric disease of unknown etiology with 60% morbidity and 8% mortality in weaning piglets occurred in November 2015 on a farm in Buryat Republic, Russia. Metagenomic sequencing revealed the presence of rotavirus B in feces from diseased piglets while no other pathogens were identified. Clinical disease was reproduced in experimentally infected piglets, yielding the 11 RVB gene segments for strain Buryat15, with an RVB genotype constellation of G12-P[4]-I13-R4-C4-M4-A8-N10-T4-E4-H7. This genotype constellation has also been identified in the United States. While the Buryat15 VP7 protein lacked unique amino acid differences in the predicted neutralizing epitopes compared to the previously published swine RVB G12 strains, this report of RVB in Russian swine increases our epidemiological knowledge on the global prevalence and genetic diversity of RVB.