Phenolic composition of hydrophilic extract of manna from sicilian Fraxinus angustifolia vahl and its reducing, antioxidant and anti-inflammatory activity in vitro

Manna, a very singular vegetable product derived from the spontaneous solidification of the sap of some Fraxinus species, has long been known for its mild laxative and emollient properties. In this work, a hydro-alcoholic extract of manna (HME) from Sicilian Fraxinus angustifolia Vahl was investigated using HPLC-DAD to find phenol components and using chemical and biological in vitro assays to determine its reducing, antioxidant and anti-inflammatory capacity. We identified elenolic acid, tyrosol, hydroxytyrosol, catechin, fraxetin, verbascoside, gallic acid, procyanidin-B1, and luteolin 3,7 glucoside, in order of abundance. Measurements of total antioxidant activity by Folin-Ciocalteu reaction and ferric reducing ability (FRAP), as well as of scavenger activity towards ABTS•+, DPPH•, and perferryl-myoglobin radicals, showed that the phytocomplex effectively reduced oxidants with different standard potentials. When compared with vitamin E, HME also behaved as an efficient chain-breaking antioxidant against lipoperoxyl radicals from methyl linoleate. In cellular models for oxidative stress, HME counteracted membrane lipid oxidation of human erythrocytes stimulated by tert-butyl hydroperoxide and prevented the generation of reactive oxygen species, as well as the GSH decay in IL-1β–activated intestinal normal-like cells. Moreover, in this in vitro intestinal bowel disease model, HME reduced the release of the pro-inflammatory cytokines IL-6 and IL-8. These findings may suggest that manna acts as an antioxidant and anti-inflammatory natural product in humans, beyond its well-known effects against constipation

Characterization of two new alleles at the goat CSN1S2 locus.

Two novel alleles at the goat CSN1S2 locus have been identified: CSN1S2(F) and CSN1S2(D). Sequence analyses revealed that the CSN1S2(F) allele is characterized by a G --> A transition at the 13th nucleotide in exon 3 changing the seventh amino acid of the mature protein from Val to Ile. The CSN1S2(D) allele, apparently associated with a decreased synthesis of alpha s2-casein, is characterized by a 106-bp deletion, involving the last 11 bp of the exon 11 and the first 95 bp of the following intron. Methods (PCR-RFLP and PCR) for identification of carriers of these alleles have been developed

PRRT2 gene variant in a child with dysmorphic features, congenital microcephaly, and severe epileptic seizures: genotype-phenotype correlation?

BACKGROUND: Mutations in Proline-rich Transmembrane Protein 2 (PRRT2) have been primarily associated with individuals presenting with infantile epilepsy, including benign familial infantile epilepsy, benign infantile epilepsy, and benign myoclonus of early infancy, and/or with dyskinetic paroxysms such as paroxysmal kinesigenic dyskinesia, paroxysmal non-kinesigenic dyskinesia, and exercise-induced dyskinesia. However, the clinical manifestations of this disorder vary widely. PRRT2 encodes a protein expressed in the central nervous system that is mainly localized in the pre-synaptic neurons and is involved in the modulation of synaptic neurotransmitter release. The anomalous function of this gene has been proposed to cause dysregulation of neuronal excitability and cerebral disorders. CASE PRESENTATION: We hereby report on a young child followed-up for three years who presents with a spectrum of clinical manifestations such as congenital microcephaly, dysmorphic features, severe intellectual disability, and drug-resistant epileptic encephalopathy in association with a synonymous variant in PRRT2 gene (c.501C > T; p.Thr167Ile) of unknown clinical significance variant (VUS) revealed by diagnostic exome sequencing. CONCLUSION: Several hypotheses have been advanced on the specific role that PRRT2 gene mutations play to cause the clinical features of affected patients. To our knowledge, the severe phenotype seen in this case has never been reported in association with any clinically actionable variant, as the missense substitution detected in PRRT2 gene. Intriguingly, the same mutation was reported in the healthy father: the action of modifying factors in the affected child may be hypothesized. The report of similar observations could extend the spectrum of clinical manifestations linked to this mutation

Parallel pair-wise interaction for multi-agent immune systems modelling

Agent Based Modelling (ABM), is an approach for modelling dynamic systems and studying complex and emergent behaviour. ABM approach is a very common technique in biological domain due to high demand for a large scale analysis tool to collect and interpret information to solve biological problems. However, simulating large scale cellular level models (i.e. large number of agents/entities) require a high degree of computational power which is achievable through parallel computing methods such as Graphics Processing Units (GPUs). The use of parallel approaches in ABMs is growing rapidly specifically when modelling in continuous space system (particle based). Parallel implementation of particle based simulation within continuum space where agents contain quantities of chemicals/substances is very challenging. Pair-wise interactions are different abstraction to continuous space (particle) models which is commonly used for immune system modelling. This paper describes an approach to parallelising the key component of biological and immune system models (pair-wise interactions) within an ABM model. Our performance results demonstrate the applicability of this method to a broader class of biological systems with the same type of cell interactions and that it can be used as the basis for developing complete immune system models on parallel hardware

Biogeographical boundaries, functional group structure and diversity of rocky shore communities along the Argentinean coast

We investigate the extent to which functional structure and spatial variability of intertidal communities coincide with major biogeographical boundaries, areas where extensive compositional changes in the biota are observed over a limited geographic extension. We then investigate whether spatial variation in the biomass of functional groups, over geographic (10′s km) and local (10′s m) scales, could be associated to species diversity within and among these groups. Functional community structure expressed as abundance (density, cover and biomass) and composition of major functional groups was quantified through field surveys at 20 rocky intertidal shores spanning six degrees of latitude along the southwest Atlantic coast of Argentina and extending across the boundaries between the Argentinean and Magellanic Provinces. Patterns of abundance of individual functional groups were not uniformly matched with biogeographical regions. Only ephemeral algae showed an abrupt geographical discontinuity coincident with changes in biogeographic boundaries, and this was limited to the mid intertidal zone. We identified 3–4 main ‘groups’ of sites in terms of the total and relative abundance of the major functional groups, but these did not coincide with biogeographical boundaries, nor did they follow latitudinal arrangement. Thus, processes that determine the functional structure of these intertidal communities are insensitive to biogeographical boundaries. Over both geographical and local spatial scales, and for most functional groups and tidal levels, increases in species richness within the functional group was significantly associated to increased total biomass and reduced spatial variability of the group. These results suggest that species belonging to the same functional group are sufficiently uncorrelated over space (i.e. metres and site-to-site ) to stabilize patterns of biomass variability and, in this manner, provide a buffer, or “insurance”, against spatial variability in environmental conditions

Parallelisation strategies for agent based simulation of immune systems

Background In recent years, the study of immune response behaviour using bottom up approach, Agent Based Modeling (ABM), has attracted considerable efforts. The ABM approach is a very common technique in the biological domain due to high demand for a large scale analysis tools for the collection and interpretation of information to solve biological problems. Simulating massive multi-agent systems (i.e. simulations containing a large number of agents/entities) requires major computational effort which is only achievable through the use of parallel computing approaches. Results This paper explores different approaches to parallelising the key component of biological and immune system models within an ABM model: pairwise interactions. The focus of this paper is on the performance and algorithmic design choices of cell interactions in continuous and discrete space where agents/entities are competing to interact with one another within a parallel environment. Conclusions Our performance results demonstrate the applicability of these methods to a broader class of biological systems exhibiting typical cell to cell interactions. The advantage and disadvantage of each implementation is discussed showing each can be used as the basis for developing complete immune system models on parallel hardware

Improving the Quality of Hospital Antibiotic Use: Impact on Multidrug-Resistant Bacterial Infections in Children

Antimicrobial resistance (AMR) is considered a rapidly growing global public health emergency. Neonates and children are among patients for whom antibiotics are largely prescribed and for whom the risk of AMR development is high. The phenomenon of increasing AMR has led to the need to develop measures aimed at the rational and effective use of the available drugs also in children and antimicrobial stewardship (AS), which is one of the measures that in adults has showed the highest efficacy in reducing antibiotic abuse and misuse, appears as an attractive approach. The aim of this manuscript is to analyze the basic principles and strategies of pediatric AS. To this end, we searched in PubMed articles published in years 2000 to 2019 containing “antimicrobial resistance,” “antibiotic use,” “antimicrobial stewardship,” and “children” or “pediatric” as keywords. Our review showed that the balance between multi-resistant organisms and new antimicrobials is extremely precarious. The AS tools are the most important weapon at our disposal to stem the phenomenon. Careful monitoring of prescriptions, continuous training of prescribing physicians and collaboration with highly qualified multidisciplinary staff, creation of local and national guidelines, use of rapid diagnostic tests, technological means of support, and research activities by testing new broad-spectrum antibiotics are mandatory. However, all of these measures must be supported by adequate investment by national and international health organizations. Only by making AS daily practice, through the use of financial resources and dedicated staff, we can fight AMR to ensure safe and effective care for our young patients

Relationship between External and Internal Workloads in Elite Soccer Players : Comparison between Rate of Perceived Exertion and Training Load

The use of machine learning (ML) in soccer allows for the management of a large amount of data deriving from the monitoring of sessions and matches. Although the rate of perceived exertion (RPE), training load (S-RPE), and global position system (GPS) are standard methodologies used in team sports to assess the internal and external workload; how the external workload affects RPE and S-RPE remains still unclear. This study explores the relationship between both RPE and SRPE and the training workload through ML. Data were recorded from 22 elite soccer players, in 160 training sessions and 35 matches during the 2015/2016 season, by using GPS tracking technology. A feature selection process was applied to understand which workload features influence RPE and SRPE the most. Our results show that the training workloads performed in the previous week have a strong effect on perceived exertion and training load. On the other hand, the analysis of our predictions shows higher accuracy for medium RPE and S-RPE values compared with the extremes. These results provide further evidence of the usefulness of ML as a support to athletic trainers and coaches in understanding the relationship between training load and individual-response in team sports