419 research outputs found

    Analysis of Short Tandem Repeats by Parallel DNA Threading

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    The majority of studies employing short tandem repeats (STRs) require investigation of several of these genetic markers. As such, we demonstrate the feasibility of the trinucleotide threading (TnT) approach for scalable analysis of STRs. The TnT method represents a parallel amplification alternative that addresses the obstacles associated with multiplex PCR. In this study, analysis of the STR fragments was performed with capillary gel electrophoresis; however, it should be possible to combine our approach with the massive 454 sequencing platform to considerably increase the number of targeted STRs

    Muscle Fatigue Analysis Using OpenSim

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    In this research, attempts are made to conduct concrete muscle fatigue analysis of arbitrary motions on OpenSim, a digital human modeling platform. A plug-in is written on the base of a muscle fatigue model, which makes it possible to calculate the decline of force-output capability of each muscle along time. The plug-in is tested on a three-dimensional, 29 degree-of-freedom human model. Motion data is obtained by motion capturing during an arbitrary running at a speed of 3.96 m/s. Ten muscles are selected for concrete analysis. As a result, the force-output capability of these muscles reduced to 60%-70% after 10 minutes' running, on a general basis. Erector spinae, which loses 39.2% of its maximal capability, is found to be more fatigue-exposed than the others. The influence of subject attributes (fatigability) is evaluated and discussed

    Exhausted CD8 T Cells Downregulate the IL-18 Receptor and Become Unresponsive to Inflammatory Cytokines and Bacterial Co-infections

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    During many chronic infections virus-specific CD8 T cells succumb to exhaustion as they lose their ability to respond to antigenic activation. Combinations of IL-12, IL-18, and IL-21 have been shown to induce the antigen-independent production of interferon (IFN)-γ by effector and memory CD8 T cells. In this study we investigated whether exhausted CD8 T cells are sensitive to activation by these cytokines. We show that effector and memory, but not exhausted, CD8 T cells produce IFN-γ and upregulate CD25 following exposure to certain combinations of IL-12, IL-18, and IL-21. The unresponsiveness of exhausted CD8 T cells is associated with downregulation of the IL-18-receptor-α (IL-18Rα). Although IL-18Rα expression is connected with the ability of memory CD8 T cells to self-renew and efflux rhodamine 123, the IL-18Rαlo exhausted cells remained capable of secreting this dye. To further evaluate the consequences of IL-18Rα downregulation, we tracked the fate of IL-18Rα-deficient CD8 T cells in chronically infected mixed bone marrow chimeras and discovered that IL-18Rα affects the initial but not later phases of the response. The antigen-independent responsiveness of exhausted CD8 T cells was also investigated following co-infection with Listeria monocytogenes, which induces the expression of IL-12 and IL-18. Although IL-18Rαhi memory cells upregulated CD25 and produced IFN-γ, the IL-18Rαlo exhausted cells failed to respond. Collectively, these findings indicate that as exhausted T cells adjust to the chronically infected environment, they lose their susceptibility to antigen-independent activation by cytokines, which compromises their ability to detect bacterial co-infections

    Angular and Current-Target Correlations in Deep Inelastic Scattering at HERA

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    Correlations between charged particles in deep inelastic ep scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4 pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation.Comment: 26 pages including 10 figures (submitted to Eur. J. Phys. C

    RNA-Seq Analysis Reveals Different Dynamics of Differentiation of Human Dermis- and Adipose-Derived Stromal Stem Cells

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    Tissue regeneration and recovery in the adult body depends on self-renewal and differentiation of stem and progenitor cells. Mesenchymal stem cells (MSCs) that have the ability to differentiate into various cell types, have been isolated from the stromal fraction of virtually all tissues. However, little is known about the true identity of MSCs. MSC populations exhibit great tissue-, location- and patient-specific variation in gene expression and are heterogeneous in cell composition.Our aim was to analyze the dynamics of differentiation of two closely related stromal cell types, adipose tissue-derived MSCs (AdMSCs) and dermal fibroblasts (FBs) along adipogenic, osteogenic and chondrogenic lineages using multiplex RNA-seq technology. We found that undifferentiated donor-matched AdMSCs and FBs are distinct populations that stay different upon differentiation into adipocytes, osteoblasts and chondrocytes. The changes in lineage-specific gene expression occur early in differentiation and persist over time in both AdMSCs and FBs. Further, AdMSCs and FBs exhibit similar dynamics of adipogenic and osteogenic differentiation but different dynamics of chondrogenic differentiation.Our findings suggest that stromal stem cells including AdMSCs and dermal FBs exploit different molecular mechanisms of differentiation to reach a common cell fate. The early mechanisms of differentiation are lineage-specific and are similar for adipogenic and osteogenic differentiation but are distinct for chondrogenic differentiation between AdMSCs and FBs

    Optimization of Muscle Activity for Task-Level Goals Predicts Complex Changes in Limb Forces across Biomechanical Contexts

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    Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3) across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2×) compared to individual muscle control. Our results are consistent with the idea that hierarchical, task-level neural control mechanisms previously associated with voluntary tasks may also be used in automatic brainstem-mediated pathways for balance

    Sexually Dimorphic Serotonergic Dysfunction in a Mouse Model of Huntington's Disease and Depression

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    Depression is the most common psychiatric disorder in Huntington's disease (HD) patients. In the general population, women are more prone to develop depression and such susceptibility might be related to serotonergic dysregulation. There is yet to be a study of sexual dimorphism in the development and presentation of depression in HD patients. We investigated whether 8-week-old male and female R6/1 transgenic HD mice display depressive-like endophenotypes associated with serotonergic impairments. We also studied the behavioral effects of acute treatment with sertraline. We found that only female HD mice exhibited a decreased preference for saccharin as well as impaired emotionality-related behaviors when assessed on the novelty-suppressed feeding test (NSFT) and the forced-swimming test (FST). The exaggerated immobility time displayed by female HD in the FST was reduced by acute administration of sertraline. We also report an increased response to the 5-HT1A receptor agonist 8-OH-DPAT in inducing hypothermia and a decreased 5-HT2A receptor function in HD animals. While tissue levels of serotonin were reduced in both male and female HD mice, we found that serotonin concentration and hydroxylase-2 (TPH2) mRNA levels were higher in the hippocampus of males compared to female animals. Finally, the antidepressant-like effects of sertraline in the FST were blunted in male HD animals. This study reveals sex-specific depressive-related behaviors during an early stage of HD prior to any cognitive and motor deficits. Our data suggest a crucial role for disrupted serotonin signaling in mediating the sexually dimorphic depression-like phenotype in HD mice

    In Vivo Dynamics of the Musculoskeletal System Cannot Be Adequately Described Using a Stiffness-Damping-Inertia Model

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    Background: Visco-elastic properties of the (neuro-)musculoskeletal system play a fundamental role in the control of posture and movement. Often, these properties are described and identified using stiffness-damping-inertia (KBI) models. In such an approach, perturbations are applied to the (neuro-)musculoskeletal system and subsequently KBI-model parameters are optimized to obtain a best fit between simulated and experimentally observed responses. Problems with this approach may arise because a KBI-model neglects critical aspects of the real musculoskeletal system. Methodology/Principal Findings: The purpose of this study was to analyze the relation between the musculoskeletal properties and the stiffness and damping estimated using a KBI-model, to analyze how this relation is affected by the nature of the perturbation and to assess the sensitivity of the estimated stiffness and damping to measurement errors. Our analyses show that the estimated stiffness and damping using KBI-models do not resemble any of the dynamical parameters of the underlying system, not even when the responses are very accurately fitted by the KBI-model. Furthermore, the stiffness and damping depend non-linearly on all the dynamical parameters of the underlying system, influenced by the nature of the perturbation and the time interval over which the KBI-model is optimized. Moreover, our analyses predict a very high sensitivity of estimated parameters to measurement errors. Conclusions/Significance: The results of this study suggest that the usage of stiffness-damping-inertia models t

    Identification and Visualization of CD8+ T Cell Mediated IFN-γ Signaling in Target Cells during an Antiviral Immune Response in the Brain

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    CD8+ T cells infiltrate the brain during an anti-viral immune response. Within the brain CD8+ T cells recognize cells expressing target antigens, become activated, and secrete IFNγ. However, there are no methods to recognize individual cells that respond to IFNγ. Using a model that studies the effects of the systemic anti-adenoviral immune response upon brain cells infected with an adenoviral vector in mice, we describe a method that identifies individual cells that respond to IFNγ. To identify individual mouse brain cells that respond to IFNγ we constructed a series of adenoviral vectors that contain a transcriptional response element that is selectively activated by IFNγ signaling, the gamma-activated site (GAS) promoter element; the GAS element drives expression of a transgene, Cre recombinase (Ad-GAS-Cre). Upon binding of IFNγ to its receptor, the intracellular signaling cascade activates the GAS promoter, which drives expression of the transgene Cre recombinase. We demonstrate that upon activation of a systemic immune response against adenovirus, CD8+ T cells infiltrate the brain, interact with target cells, and cause an increase in the number of cells expressing Cre recombinase. This method can be used to identify, study, and eventually determine the long term fate of infected brain cells that are specifically targeted by IFNγ. The significance of this method is that it will allow to characterize the networks in the brain that respond to the specific secretion of IFNγ by anti-viral CD8+ T cells that infiltrate the brain. This will allow novel insights into the cellular and molecular responses underlying brain immune responses
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