Pediocin PA-1, a wide-spectrum bacteriocin from lactic acid bacteria

Pediocin PA-1 is a broad-spectrum lactic acid bacteria bacteriocin that shows a particularly strong activity against Listeria monocytogenes, a foodborne pathogen of special concern among the food industries. This antimicrobial peptide is the most extensively studied class IIa (or pediocin family) bacteriocin, and it has been sufficiently well characterized to be used as a food biopreservative. This review focuses on the progress that have been made in the elucidation of its structure, mode of action, and biosynthesis, and includes an overview of its applications in food systems. The aspects that need further research are also addressed. In the future, protein engineering, genetic engineering and/or chemical synthesis may lead to the development of new antimicrobial peptides with improved properties, based on some features of the pediocin PA-1 molecule

Asthma Prevalence, Knowledge, and Perceptions among Secondary School Pupils in Rural and Urban Costal Districts in Tanzania.

Asthma is a common chronic disease of childhood that is associated with significant morbidity and mortality. We aimed to estimate the prevalence of asthma among secondary school pupils in urban and rural areas of coast districts of Tanzania. The study also aimed to describe pupils' perception towards asthma, and to assess their knowledge on symptoms, triggers, and treatment of asthma. A total of 610 pupils from Ilala district and 619 pupils from Bagamoyo district formed the urban and rural groups, respectively. Using a modified International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire, a history of "diagnosed" asthma or the presence of a wheeze in the previous 12 months was obtained from all the studied pupils, along with documentation of their perceptions regarding asthma. Pupils without asthma or wheeze in the prior 12 months were subsequently selected and underwent a free running exercise testing. A >= 20% decrease in the post-exercise Peak Expiratory Flow Rate (PEFR) values was the criterion for diagnosing exercise-induced asthma. The mean age of participants was 16.8 (+/-1.8) years. The prevalence of wheeze in the past 12 months was 12.1% in Bagamoyo district and 23.1% in Ilala district (p < 0.001). Self-reported asthma was found in 17.6% and 6.4% of pupils in Ilala and Bagamoyo districts, respectively (p < 0.001). The prevalence of exercise-induced asthma was 2.4% in Bagamoyo, and 26.3% in Ilala (P < 0.002). In both districts, most information on asthma came from parents, and there was variation in symptoms and triggers of asthma reported by the pupils. Non-asthmatic pupils feared sleeping, playing, and eating with their asthmatic peers. The prevalence rates of self-reported asthma, wheezing in the past 12 months, and exercise-induced asthma were significantly higher among urban than rural pupils. Although bronchial asthma is a common disease, pupils' perceptions about asthma were associated with fear of contact with their asthmatic peers in both rural and urban schools

Metabolomic insights into the intricate gut microbial–host interaction in the development of obesity and type 2 diabetes

Gut microbiota has recently been proposed as a crucial environmental factor in the development of metabolic diseases such as obesity and type 2 diabetes, mainly due to its contribution in the modulation of several processes including host energy metabolism, gut epithelial permeability, gut peptide hormone secretion and host inflammatory state. Since the symbiotic interaction between the gut microbiota and the host is essentially reflected in specific metabolic signatures, much expectation is placed on the application of metabolomic approaches to unveil the key mechanisms linking the gut microbiota composition and activity with disease development. The present review aims to summarize the gut microbial-host co-metabolites identified so far by targeted and untargeted metabolomic studies in humans, in association with impaired glucose homeostasis and/or obesity. An alteration of the co-metabolism of bile acids, branched fatty acids, choline, vitamins (i.e. niacin), purines and phenolic compounds has been associated so far with the obese or diabese phenotype, in respect to healthy controls. Furthermore, anti-diabetic treatments such as metformin and sulfonylurea have been observed to modulate the gut microbiota or at least their metabolic profiles, thereby potentially affecting insulin resistance through indirect mechanisms still unknown. Despite the scarcity of the metabolomic studies currently available on the microbial-host crosstalk, the data-driven results largely confirmed findings independently obtained from in vitro and animal model studies, putting forward the mechanisms underlying the implication of a dysfunctional gut microbiota in the development of metabolic disorders

Finite-size and correlation-induced effects in Mean-field Dynamics

The brain's activity is characterized by the interaction of a very large number of neurons that are strongly affected by noise. However, signals often arise at macroscopic scales integrating the effect of many neurons into a reliable pattern of activity. In order to study such large neuronal assemblies, one is often led to derive mean-field limits summarizing the effect of the interaction of a large number of neurons into an effective signal. Classical mean-field approaches consider the evolution of a deterministic variable, the mean activity, thus neglecting the stochastic nature of neural behavior. In this article, we build upon two recent approaches that include correlations and higher order moments in mean-field equations, and study how these stochastic effects influence the solutions of the mean-field equations, both in the limit of an infinite number of neurons and for large yet finite networks. We introduce a new model, the infinite model, which arises from both equations by a rescaling of the variables and, which is invertible for finite-size networks, and hence, provides equivalent equations to those previously derived models. The study of this model allows us to understand qualitative behavior of such large-scale networks. We show that, though the solutions of the deterministic mean-field equation constitute uncorrelated solutions of the new mean-field equations, the stability properties of limit cycles are modified by the presence of correlations, and additional non-trivial behaviors including periodic orbits appear when there were none in the mean field. The origin of all these behaviors is then explored in finite-size networks where interesting mesoscopic scale effects appear. This study leads us to show that the infinite-size system appears as a singular limit of the network equations, and for any finite network, the system will differ from the infinite system

Effects of ocean acidification on invertebrate settlement at volcanic CO<inf>2</inf> vents

We present the first study of the effects of ocean acidification on settlement of benthic invertebrates and microfauna. Artificial collectors were placed for 1 month along pH gradients at CO2 vents off Ischia (Tyrrhenian Sea, Italy). Seventy-nine taxa were identified from six main taxonomic groups (foraminiferans, nematodes, polychaetes, molluscs, crustaceans and chaetognaths). Calcareous foraminiferans, serpulid polychaetes, gastropods and bivalves showed highly significant reductions in recruitment to the collectors as pCO2 rose from normal (336-341 ppm, pH 8.09-8.15) to high levels (886-5,148 ppm) causing acidified conditions near the vents (pH 7.08-7.79). Only the syllid polychaete Syllis prolifera had higher abundances at the most acidified station, although a wide range of polychaetes and small crustaceans was able to settle and survive under these conditions. A few taxa (Amphiglena mediterranea, Leptochelia dubia, Caprella acanthifera) were particularly abundant at stations acidified by intermediate amounts of CO2 (pH 7. 41-7.99). These results show that increased levels of CO2 can profoundly affect the settlement of a wide range of benthic organisms. © 2010 Springer-Verlag

Study protocol of cost-effectiveness and cost-utility of a biopsychosocial multidisciplinary intervention in the evolution of non-specific sub-acute low back pain in the working population: cluster randomised trial.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Low back pain (LBP), with high incidence and prevalence rate, is one of the most common reasons to consult the health system and is responsible for a significant amount of sick leave, leading to high health and social costs. The objective of the study is to assess the cost-effectiveness and cost-utility analysis of a multidisciplinary biopsychosocial educational group intervention (MBEGI) of non-specific sub-acute LBP in comparison with the usual care in the working population recruited in primary healthcare centres. Methods/design: The study design is a cost-effectiveness and cost-utility analysis of a MBEGI in comparison with the usual care of non-specific sub-acute LBP.Measures on effectiveness and costs of both interventions will be obtained from a cluster randomised controlled clinical trial carried out in 38 Catalan primary health care centres, enrolling 932 patients between 18 and 65 years old with a diagnosis of non-specific sub-acute LBP. Effectiveness measures are: pharmaceutical treatments, work sick leave (% and duration in days), Roland Morris disability, McGill pain intensity, Fear Avoidance Beliefs (FAB) and Golberg Questionnaires. Utility measures will be calculated from the SF-12. The analysis will be performed from a social perspective. The temporal horizon is at 3 months (change to chronic LBP) and 12 months (evaluate the outcomes at long term. Assessment of outcomes will be blinded and will follow the intention-to-treat principle. Discussion: We hope to demonstrate the cost-effectiveness and cost-utility of MBEGI, see an improvement in the patients' quality of life, achieve a reduction in the duration of episodes and the chronicity of non-specific low back pain, and be able to report a decrease in the social costs. If the intervention is cost-effectiveness and cost-utility, it could be applied to Primary Health Care Centres. Trial registration: ISRCTN: ISRCTN5871969

Density-dependence of functional development in spiking cortical networks grown in vitro

During development, the mammalian brain differentiates into specialized regions with distinct functional abilities. While many factors contribute to functional specialization, we explore the effect of neuronal density on the development of neuronal interactions in vitro. Two types of cortical networks, dense and sparse, with 50,000 and 12,000 total cells respectively, are studied. Activation graphs that represent pairwise neuronal interactions are constructed using a competitive first response model. These graphs reveal that, during development in vitro, dense networks form activation connections earlier than sparse networks. Link entropy analysis of dense net- work activation graphs suggests that the majority of connections between electrodes are reciprocal in nature. Information theoretic measures reveal that early functional information interactions (among 3 cells) are synergetic in both dense and sparse networks. However, during later stages of development, previously synergetic relationships become primarily redundant in dense, but not in sparse networks. Large link entropy values in the activation graph are related to the domination of redundant ensembles in late stages of development in dense networks. Results demonstrate differences between dense and sparse networks in terms of informational groups, pairwise relationships, and activation graphs. These differences suggest that variations in cell density may result in different functional specialization of nervous system tissue in vivo.Comment: 10 pages, 7 figure

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

The increasing importance of atmospheric demand for ecosystem water and carbon fluxes

Soil moisture supply and atmospheric demand for water independently limit—and profoundly affect—vegetation productivity and water use during periods of hydrologic stress1, 2, 3, 4. Disentangling the impact of these two drivers on ecosystem carbon and water cycling is difficult because they are often correlated, and experimental tools for manipulating atmospheric demand in the field are lacking. Consequently, the role of atmospheric demand is often not adequately factored into experiments or represented in models5, 6, 7. Here we show that atmospheric demand limits surface conductance and evapotranspiration to a greater extent than soil moisture in many biomes, including mesic forests that are of particular importance to the terrestrial carbon sink8, 9. Further, using projections from ten general circulation models, we show that climate change will increase the importance of atmospheric constraints to carbon and water fluxes in all ecosystems. Consequently, atmospheric demand will become increasingly important for vegetation function, accounting for >70% of growing season limitation to surface conductance in mesic temperate forests. Our results suggest that failure to consider the limiting role of atmospheric demand in experimental designs, simulation models and land management strategies will lead to incorrect projections of ecosystem responses to future climate conditions

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV