549 research outputs found

    Dynamics of direct inter-pack encounters in endangered African wild dogs

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    Aggressive encounters may have important life history consequences due to the potential for injury and death, disease transmission, dispersal opportunities or exclusion from key areas of the home range. Despite this, little is known of their detailed dynamics, mainly due to the difficulties of directly observing encounters in detail. Here, we describe detailed spatial dynamics of inter-pack encounters in African wild dogs (Lycaon pictus), using data from custom-built high-resolution GPS collars in 11 free-ranging packs. On average, each pack encountered another pack approximately every 7 weeks and met each neighbour twice each year. Surprisingly, intruders were more likely to win encounters (winning 78.6% of encounters by remaining closer to the site in the short term). However, intruders did tend to move farther than residents toward their own range core in the short-term (1 h) post-encounter, and if this were used to indicate losing an encounter, then the majority (73.3%) of encounters were won by residents. Surprisingly, relative pack size had little effect on encounter outcome, and injuries were rare (<15% of encounters). These results highlight the difficulty of remotely scoring encounters involving mobile participants away from static defendable food resources. Although inter-pack range overlap was reduced following an encounter, encounter outcome did not seem to drive this, as both packs shifted their ranges post-encounter. Our results indicate that inter-pack encounters may be lower risk than previously suggested and do not appear to influence long-term movement and ranging

    Unique and conserved MicroRNAs in wheat chromosome 5D revealed by next-generation sequencing

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    MicroRNAs are a class of short, non-coding, single-stranded RNAs that act as post-transcriptional regulators in gene expression. miRNA analysis of Triticum aestivum chromosome 5D was performed on 454 GS FLX Titanium sequences of flow sorted chromosome 5D with a total of 3,208,630 good quality reads representing 1.34x and 1.61x coverage of the short (5DS) and long (5DL) arms of the chromosome respectively. In silico and structural analyses revealed a total of 55 miRNAs; 48 and 42 miRNAs were found to be present on 5DL and 5DS respectively, of which 35 were common to both chromosome arms, while 13 miRNAs were specific to 5DL and 7 miRNAs were specific to 5DS. In total, 14 of the predicted miRNAs were identified in wheat for the first time. Representation (the copy number of each miRNA) was also found to be higher in 5DL (1,949) compared to 5DS (1,191). Targets were predicted for each miRNA, while expression analysis gave evidence of expression for 6 out of 55 miRNAs. Occurrences of the same miRNAs were also found in Brachypodium distachyon and Oryza sativa genome sequences to identify syntenic miRNA coding sequences. Based on this analysis, two other miRNAs: miR1133 and miR167 were detected in B. distachyon syntenic region of wheat 5DS. Five of the predicted miRNA coding regions (miR6220, miR5070, miR169, miR5085, miR2118) were experimentally verified to be located to the 5D chromosome and three of them : miR2118, miR169 and miR5085, were shown to be 5D specific. Furthermore miR2118 was shown to be expressed in Chinese Spring adult leaves. miRNA genes identified in this study will expand our understanding of gene regulation in bread wheat

    A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

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    The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE

    Optimal free descriptions of many-body theories

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    Interacting bosons or fermions give rise to some of the most fascinating phases of matter, including high-temperature superconductivity, the fractional quantum Hall effect, quantum spin liquids and Mott insulators. Although these systems are promising for technological applications, they also present conceptual challenges, as they require approaches beyond mean-field and perturbation theory. Here we develop a general framework for identifying the free theory that is closest to a given interacting model in terms of their ground-state correlations. Moreover, we quantify the distance between them using the entanglement spectrum. When this interaction distance is small, the optimal free theory provides an effective description of the low-energy physics of the interacting model. Our construction of the optimal free model is non-perturbative in nature; thus, it offers a theoretical framework for investigating strongly correlated systems

    School, peer and family relationships and adolescent substance use, subjective wellbeing and mental health symptoms in Wales: a cross sectional study

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    Positive relationships with family, friends and school staff are consistently linked with health and wellbeing during adolescence, though fewer studies explore how these micro-systems interact to influence adolescent health. This study tests the independent and interacting roles of family, peer and school relationships in predicting substance use, subjective wellbeing and mental health symptoms among 11–16 year olds in Wales. It presents cross-sectional analyses of the 2013 Health Behaviour in School-aged Children survey, completed by 9055 young people aged 11–16 years. Multilevel logistic regression analyses are used to test associations of family communication, family support, relationships with school staff, school peer connectedness, and support from friends, with tobacco use, cannabis use, alcohol use, subjective wellbeing and mental health symptoms. Positive relationships with family and school staff were consistently associated with better outcomes. Support from friends was associated with higher use of all substances, while higher school peer connectedness was associated with better subjective wellbeing and mental health. Better relationships with school staff were most strongly associated with positive subjective wellbeing, and fewer mental health symptoms where pupils reported less family support. Support from friends was associated with higher cannabis use and worse mental health among pupils with lower family support. Relationships with family and school staff may be important in protecting young people against substance use, and improving wellbeing and mental health. Interventions focused on student-staff relationships may be important for young people with less family support. Interventions based on peer support should be mindful of potential harmful effects for pupils with less support from family

    Identification of metabolic pathways influenced by the G-protein coupled receptors GprB and GprD in Aspergillus nidulans

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    Heterotrimeric G-protein-mediated signaling pathways play a pivotal role in transmembrane signaling in eukaryotes. Our main aim was to identify signaling pathways regulated by A. nidulans GprB and GprD G-protein coupled receptors (GPCRs). When these two null mutant strains were compared to the wild-type strain, the DeltagprB mutant showed an increased protein kinase A (PKA) activity while growing in glucose 1% and during starvation. In contrast, the DeltagprD has a much lower PKA activity upon starvation. Transcriptomics and (1)H NMR-based metabolomics were performed on two single null mutants grown on glucose. We noted modulation in the expression of 11 secondary metabolism gene clusters when the DeltagprB and DeltagprD mutant strains were grown in 1% glucose. Several members of the sterigmatocystin-aflatoxin gene cluster presented down-regulation in both mutant strains. The genes of the NR-PKS monodictyphenone biosynthesis cluster had overall increased mRNA accumulation in DeltagprB, while in the DeltagprD mutant strain the genes had decreased mRNA accumulation. Principal component analysis of the metabolomic data demonstrated that there was a significant metabolite shift in the DeltagprD strain. The (1)H NMR analysis revealed significant expression of essential amino acids with elevated levels in the DeltagprD strain, compared to the wild-type and DeltagprB strains. With the results, we demonstrated the differential expression of a variety of genes related mainly to secondary metabolism, sexual development, stress signaling, and amino acid metabolism. We propose that the absence of GPCRs triggered stress responses at the genetic level. The data suggested an intimate relationship among different G-protein coupled receptors, fine-tune regulation of secondary and amino acid metabolisms, and fungal development

    Comparative Live-Cell Imaging Analyses of SPA-2, BUD-6 and BNI-1 in Neurospora crassa Reveal Novel Features of the Filamentous Fungal Polarisome

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    A key multiprotein complex involved in regulating the actin cytoskeleton and secretory machinery required for polarized growth in fungi, is the polarisome. Recognized core constituents in budding yeast are the proteins Spa2, Pea2, Aip3/Bud6, and the key effector Bni1. Multicellular fungi display a more complex polarized morphogenesis than yeasts, suggesting that the filamentous fungal polarisome might fulfill additional functions. In this study, we compared the subcellular organization and dynamics of the putative polarisome components BUD-6 and BNI-1 with those of the bona fide polarisome marker SPA-2 at various developmental stages of Neurospora crassa. All three proteins exhibited a yeast-like polarisome configuration during polarized germ tube growth, cell fusion, septal pore plugging and tip repolarization. However, the localization patterns of all three proteins showed spatiotemporally distinct characteristics during the establishment of new polar axes, septum formation and cytokinesis, and maintained hyphal tip growth. Most notably, in vegetative hyphal tips BUD-6 accumulated as a subapical cloud excluded from the Spitzenkörper (Spk), whereas BNI-1 and SPA-2 partially colocalized with the Spk and the tip apex. Novel roles during septal plugging and cytokinesis, connected to the reinitiation of tip growth upon physical injury and conidial maturation, were identified for BUD-6 and BNI-1, respectively. Phenotypic analyses of gene deletion mutants revealed additional functions for BUD-6 and BNI-1 in cell fusion regulation, and the maintenance of Spk integrity. Considered together, our findings reveal novel polarisome-independent functions of BUD-6 and BNI-1 in Neurospora, but also suggest that all three proteins cooperate at plugged septal pores, and their complex arrangement within the apical dome of mature hypha might represent a novel aspect of filamentous fungal polarisome architecture

    Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

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    Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

    Ultrasonic Evaluation of in-Plane and out-of-Plane Elastic Properties of Composite Materials

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    Evaluation of elastic properties of composite materials using ultrasound is important for the generation of output data for the design of composites. It is also extremely important as a nondestructive tool for quality evaluation of the composites after manufacturing. The problem was addressed in the seventies [1–3] when Markham [1] suggested using the time-delay through transmission technique with obliquely incident ultrasonic waves from water onto a composite plate. The full set of elastic constants was measured later by Kriz and Stinchcomb [4] on samples cut out in different directions from a composite plate. Recently several works have appeared where the set of elastic constants was measured by using Markham’s technique [5–7]
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