Technological Implications of Modifying the Extent of Cell Wall-Proanthocyanidin Interactions Using Enzymes

The transference and reactivity of proanthocyanidins is an important issue that affects the technological processing of some fruits, such as grapes and apples. These processes are affected by proanthocyanidins bound to cell wall polysaccharides, which are present in high concentrations during the processing of the fruits. Therefore, the effective extraction of proanthocyanidins from fruits to their juices or derived products will depend on the ability to manage these associations, and, in this respect, enzymes that degrade these polysaccharides could play an important role. The main objective of this work was to test the role of pure hydrolytic enzymes (polygalacturonase and cellulose) and a commercial enzyme containing these two activities on the extent of proanthocyanidin-cell wall interactions. The results showed that the modification promoted by enzymes reduced the amount of proanthocyanidins adsorbed to cell walls since they contributed to the degradation and release of the cell wall polysaccharides, which diffused into the model solution. Some of these released polysaccharides also presented some reactivity towards the proanthocyanidins present in a model solution.     

Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system

Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. In this paper, a novel sampling-based algorithm is proposed which is able to plan in an unknown environment and provides solutions with lower cost in terms of path length, runtime and stability of the results. First, a fuzzy controller is designed which incorporates the heuristic rules of Tabu search to enable the planner for solving online navigation tasks. Then, an adaptive neuro-fuzzy inference system (ANFIS) is proposed such that it constructs and optimizes the fuzzy controller based on a set of given input/output data. Furthermore, a heuristic dataset generator is implemented to provide enough data for the ANFIS using a randomized procedure. The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. Finally, the proposed planner is compared to some of the similar motion planning algorithms to support the claim of superiority of its performance.

     

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.     

A mixed longitudinal and cross-sectional model to forecast the journal impact factor in the field of Dentistry

Scientometrics - In order to estimate the impact factor value for a journal in Dentistry, two sets of variables were considered in this study: the first takes in the longitudinal behavior of the...     

Neuroprotective Role of Liver Growth Factor “LGF” in an Experimental Model of Cerebellar Ataxia

Cerebellar ataxias (CA) comprise a heterogeneous group of neurodegenerative diseases characterized by a lack of motor coordination. They are caused by disturbances in the cerebellum and its associated circuitries, so the major therapeutic goal is to correct cerebellar dysfunction. Neurotrophic factors enhance the survival and differentiation of selected types of neurons. Liver growth factor (LGF) is a hepatic mitogen that shows biological activity in neuroregenerative therapies. We investigate the potential therapeutic activity of LGF in the 3-acetylpiridine (3-AP) rat model of CA. This model of CA consists in the lesion of the inferior olive-induced by 3-AP (40 mg/kg). Ataxic rats were treated with 5 µg/rat LGF or vehicle during 3 weeks, analyzing: (a) motor coordination by using the rota-rod test; and (b) the immunohistochemical and biochemical evolution of several parameters related with the olivo-cerebellar function. Motor coordination improved in 3-AP-lesioned rats that received LGF treatment. LGF up-regulated NeuN and Bcl-2 protein levels in the brainstem, and increased calbindin expression and the number of neurons receiving calbindin-positive projections in the cerebellum. LGF also reduced extracellular glutamate and GABA concentrations and microglia activation in the cerebellum. In view of these results, we propose LGF as a potential therapeutic agent in cerebellar ataxias.     

Macro- and microscale variables regulate stent haemodynamics,fibrin deposition and thrombomodulin expression

Drug eluting stents are associated with late stent thrombosis (LST), delayed healing and prolonged exposure of stent struts to blood flow. Using macroscale disturbed and undisturbed fluid flow waveforms, we numerically and experimentally determined the effects of microscale model strut geometries upon the generation of prothrombotic conditions that are mediated by flow perturbations. Rectangular cross-sectional stent strut geometries of varying heights and corresponding streamlined versions were studied in the presence of disturbed and undisturbed bulk fluid flow. Numerical simulations and particle flow visualization experiments demonstrated that the interaction of bulk fluid flow and stent struts regulated the generation, size and dynamics of the peristrut flow recirculation zones. In the absence of endothelial cells, deposition of thrombin-generated fibrin occurred primarily in the recirculation zones. When endothelium was present, peristrut expression of anticoagulant thrombomodulin (TM) was dependent on strut height and geometry. Thinner and streamlined strut geometries reduced peristrut flow recirculation zones decreasing prothrombotic fibrin deposition and increasing endothelial anticoagulant TM expression. The studies define physical and functional consequences of macro- and microscale variables that relate to thrombogenicity associated with the most current stent designs, and particularly to LST.