2,281 research outputs found

    Anomaly and a QCD-like phase diagram with massive bosonic baryons

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    We study a strongly coupled Z2Z_2 lattice gauge theory with two flavors of quarks, invariant under an exact SU(2)×SU(2)×UA(1)×UB(1)\mathrm{SU}(2)\times \mathrm{SU}(2) \times \mathrm{U}_A(1) \times \mathrm{U}_B(1) symmetry which is the same as QCD with two flavors of quarks without an anomaly. The model also contains a coupling that can be used to break the UA(1)\mathrm{U}_A(1) symmetry and thus mimic the QCD anomaly. At low temperatures TT and small baryon chemical potential μB\mu_B the model contains massless pions and massive bosonic baryons similar to QCD with an even number of colors. In this work we study the T−μBT-\mu_B phase diagram of the model and show that it contains three phases : (1) A chirally broken phase at low TT and μB\mu_B, (2) a chirally symmetric baryon superfluid phase at low TT and high μB\mu_B, and (3) a symmetric phase at high TT. We find that the nature of the finite temperature chiral phase transition and in particular the location of the tricritical point that seperates the first order line from the second order line is affected significantly by the anomaly.Comment: 22 pages, 16 figures, 5 tables, references adde

    Reducing appointment lead-time in an outpatient department of gynecology and obstetrics through discrete-event simulation: A case study

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    Appointment lead-time is a critical variable in outpatient clinic services. In Gynecology and Obstetrics departments, longer appointment lead times are associated with lower patient satisfaction, the use of more complex healthcare services, development of long-term and severe complications and the increase of fetal, infant and maternal mortality rates. This paper aims to define and evaluate improvement alternatives through the use of Discrete-event simulation (DES). First, input data analysis is performed. Second, the simulation model is created; then, performance metrics are calculated and analyzed. Finally, improvement scenarios are designed and assessed. A case study of a mixed-patient type environment (Perinatology and Gynecobstetrics) in an outpatient department has been explored to verify the effectiveness of the proposed approach. Statistical analysis evidence that appointment lead times could be significantly reduced in both Perinatology and Gynecobstetrics appointments based on the proposed approaches in this paper

    Actin and myosin contribute to mammalian mitochondrial DNA maintenance.

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    Mitochondrial DNA maintenance and segregation are dependent on the actin cytoskeleton in budding yeast. We found two cytoskeletal proteins among six proteins tightly associated with rat liver mitochondrial DNA: non-muscle myosin heavy chain IIA and β-actin. In human cells, transient gene silencing of MYH9 (encoding non-muscle myosin heavy chain IIA), or the closely related MYH10 gene (encoding non-muscle myosin heavy chain IIB), altered the topology and increased the copy number of mitochondrial DNA; and the latter effect was enhanced when both genes were targeted simultaneously. In contrast, genetic ablation of non-muscle myosin IIB was associated with a 60% decrease in mitochondrial DNA copy number in mouse embryonic fibroblasts, compared to control cells. Gene silencing of β-actin also affected mitochondrial DNA copy number and organization. Protease-protection experiments and iodixanol gradient analysis suggest some β-actin and non-muscle myosin heavy chain IIA reside within human mitochondria and confirm that they are associated with mitochondrial DNA. Collectively, these results strongly implicate the actomyosin cytoskeleton in mammalian mitochondrial DNA maintenance.Medical Research Council; the European Union; the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development and National Heart; Lung and Blood Institute; National Institutes of Health and grants [CMRPG360491-2, 380651, NSC 97-2321-B-182A-002-MY2] from the Chang Gung Memorial Hospital, Lin-Kou, Taiwan (to C.C.M.). Funding for open access charge: Medical Research Council

    Robust estimation of microbial diversity in theory and in practice

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    Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

    Social interaction, noise and antibiotic-mediated switches in the intestinal microbiota

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    The intestinal microbiota plays important roles in digestion and resistance against entero-pathogens. As with other ecosystems, its species composition is resilient against small disturbances but strong perturbations such as antibiotics can affect the consortium dramatically. Antibiotic cessation does not necessarily restore pre-treatment conditions and disturbed microbiota are often susceptible to pathogen invasion. Here we propose a mathematical model to explain how antibiotic-mediated switches in the microbiota composition can result from simple social interactions between antibiotic-tolerant and antibiotic-sensitive bacterial groups. We build a two-species (e.g. two functional-groups) model and identify regions of domination by antibiotic-sensitive or antibiotic-tolerant bacteria, as well as a region of multistability where domination by either group is possible. Using a new framework that we derived from statistical physics, we calculate the duration of each microbiota composition state. This is shown to depend on the balance between random fluctuations in the bacterial densities and the strength of microbial interactions. The singular value decomposition of recent metagenomic data confirms our assumption of grouping microbes as antibiotic-tolerant or antibiotic-sensitive in response to a single antibiotic. Our methodology can be extended to multiple bacterial groups and thus it provides an ecological formalism to help interpret the present surge in microbiome data.Comment: 20 pages, 5 figures accepted for publication in Plos Comp Bio. Supplementary video and information availabl

    Mechanosensitive Enteric Neurons in the Myenteric Plexus of the Mouse Intestine

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    BACKGROUND: Within the gut the autonomous enteric nervous system (ENS) is able to sense mechanical stimuli and to trigger gut reflex behaviour. We previously proposed a novel sensory circuit in the ENS which consists of multifunctional rapidly adapting mechanosensitive enteric neurons (RAMEN) in the guinea pig. The aim of this study was to validate this concept by studying its applicability to other species or gut regions. METHODOLOGY/PRINCIPAL FINDINGS: We deformed myenteric ganglia in the mouse small and large intestine and recorded spike discharge using voltage sensitive dye imaging. We also analysed expression of markers hitherto proposed to label mouse sensory myenteric neurons in the ileum (NF145kD) or colon (calretinin). RAMEN constituted 22% and 15% of myenteric neurons per ganglion in the ileum and colon, respectively. They encoded dynamic rather than sustained deformation. In the colon, 7% of mechanosensitive neurons fired throughout the sustained deformation, a behaviour typical for slowly adapting echanosensitive neurons (SAMEN). RAMEN and SAMEN responded directly to mechanical deformation as their response remained unchanged after synaptic blockade in low Ca(++)/high Mg(++). Activity levels of RAMEN increased with the degree of ganglion deformation. Recruitment of more RAMEN with stronger stimuli may suggest low and high threshold RAMEN. The majority of RAMEN were cholinergic but most lacked expression of NF145kD or calretinin. CONCLUSIONS/SIGNIFICANCE: We showed for the first time that fundamental properties of mechanosensitive enteric neurons, such as firing pattern, encoding of dynamic deformation, cholinergic phenotype and their proportion, are conserved across species and regions. We conclude that RAMEN are important for mechanotransduction in the ENS. They directly encode dynamic changes in force as their firing frequency is proportional to the degree of deformation of the ganglion they reside in. The additional existence of SAMEN in the colon is likely an adaptation to colonic motor patterns which consist of phasic and tonic contractions

    Blockade of insulin-like growth factors increases efficacy of paclitaxel in metastatic breast cancer.

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    Breast cancer remains the leading cause of cancer death in women owing to metastasis and the development of resistance to established therapies. Macrophages are the most abundant immune cells in the breast tumor microenvironment and can both inhibit and support cancer progression. Thus, gaining a better understanding of how macrophages support cancer could lead to the development of more effective therapies. In this study, we find that breast cancer-associated macrophages express high levels of insulin-like growth factors 1 and 2 (IGFs) and are the main source of IGFs within both primary and metastatic tumors. In total, 75% of breast cancer patients show activation of insulin/IGF-1 receptor signaling and this correlates with increased macrophage infiltration and advanced tumor stage. In patients with invasive breast cancer, activation of Insulin/IGF-1 receptors increased to 87%. Blocking IGF in combination with paclitaxel, a chemotherapeutic agent commonly used to treat breast cancer, showed a significant reduction in tumor cell proliferation and lung metastasis in pre-clinical breast cancer models compared to paclitaxel monotherapy. Our findings provide the rationale for further developing the combination of paclitaxel with IGF blockers for the treatment of invasive breast cancer, and Insulin/IGF1R activation and IGF+ stroma cells as potential biomarker candidates for further evaluation
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