715 research outputs found

    The effect of a dominant kinase-dead Csf1r mutation associated with adult-onset leukoencephalopathy on brain development and neuropathology

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    Amino acid substitutions in the kinase domain of the human CSF1R protein are associated with autosomal dominant adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP). To model the human disease, we created a disease-associated mutation (Glu631Lys; E631K) in the mouse Csf1r locus. Previous analysis demonstrated that heterozygous mutation (Csf1rE631K/+) had a dominant inhibitory effect on CSF1R signaling in vitro and in vivo but did not recapitulate the pathology of the human disease. We speculated that leukoencephalopathy in humans requires an environmental trigger and/or epistatic interaction with common neurodegenerative disease-associated alleles. Here we examine the impact of heterozygous Csf1r mutation on microglial phenotype, normal postnatal brain development, age-related changes in gene expression and on two distinct pathologies in which microgliosis is a prominent feature, prion disease and experimental autoimmune encephalitis (EAE). The heterozygous Csf1rE631K/+ mutation reduced microglial abundance and the expression of microglial-associated transcripts relative to wild-type controls at 12 weeks and 43 weeks of age but had no selective effect on homeostatic markers such as P2ry12. An epistatic interaction was demonstrated between Csf1rE631K/+ and Cxc3r1EGFP/+ genotypes leading to dysregulated microglial and neuronal gene expression in both hippocampus and striatum. Heterozygous Csf1rE631K mutation reduced the microgliosis associated with both diseases. There was no significant impact on disease severity or progression in prion disease. In EAE, induced expression of inflammation-associated transcripts in the hippocampus and striatum was suppressed in parallel with microglia-specific transcripts, but spinal cord demyelination was exacerbated. The results support a dominant-negative model of CSF1R-associated leukoencephalopathy and likely contributions of an environmental trigger and/or genetic background to neuropathology

    Extended Functional Connectivity of Convergent Structural Alterations Among Individuals with PTSD: A Neuroimaging Meta-Analysis

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    Background: Post-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated. Methods: Using emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional profiles of identified convergent structural regions utilizing resting-state functional connectivity (rsFC) and meta-analytic co-activation modeling (MACM) methods. Finally, we performed functional decoding to examine mental functions associated with our ALE, rsFC, and MACM brain characterizations. Results: We observed convergent structural alterations in a single region located in the medial prefrontal cortex. The resultant rsFC and MACM maps identified functional connectivity across a widespread, whole-brain network that included frontoparietal and limbic regions. Functional decoding revealed overlapping associations with attention, memory, and emotion processes. Conclusions: Consensus-based functional connectivity was observed in regions of the default mode, salience, and central executive networks, which play a role in the tripartite model of psychopathology. Taken together, these findings have important implications for understanding the neurobiological mechanisms associated with PTSD

    Neural Systems Underlying RDoC Social Constructs: An Activation Likelihood Estimation Meta-Analysis

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    Neuroscientists have sought to identify the underlying neural systems supporting social processing that allow interaction and communication, forming social relationships, and navigating the social world. Through the use of NIMH’s Research Domain Criteria (RDoC) framework, we evaluated consensus among studies that examined brain activity during social tasks to elucidate regions comprising the “social brain”. We examined convergence across tasks corresponding to the four RDoC social constructs, including Affiliation and Attachment, Social Communication, Perception and Understanding of Self, and Perception and Understanding of Others. We performed a series of coordinate-based meta-analyses using the activation likelihood estimate (ALE) method. Meta-analysis was performed on whole-brain coordinates reported from 864 fMRI contrasts using the NiMARE Python package, revealing convergence in medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, temporoparietal junction, bilateral insula, amygdala, fusiform gyrus, precuneus, and thalamus. Additionally, four separate RDoC-based meta-analyses revealed differential convergence associated with the four social constructs. These outcomes highlight the neural support underlying these social constructs and inform future research on alterations among neurotypical and atypical populations

    Open-label randomized trial of titrated disease management for patients with hypertension: Study design and baseline sample characteristics

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    Despite the availability of efficacious treatments, only half of patients with hypertension achieve adequate blood pressure (BP) control. This paper describes the protocol and baseline subject characteristics of a 2-arm, 18-month randomized clinical trial of titrated disease management (TDM) for patients with pharmaceutically-treated hypertension for whom systolic blood pressure (SBP) is not controlled (≥140mmHg for non-diabetic or ≥130mmHg for diabetic patients). The trial is being conducted among patients of four clinic locations associated with a Veterans Affairs Medical Center. An intervention arm has a TDM strategy in which patients' hypertension control at baseline, 6, and 12 months determines the resource intensity of disease management. Intensity levels include: a low-intensity strategy utilizing a licensed practical nurse to provide bi-monthly, non-tailored behavioral support calls to patients whose SBP comes under control; medium-intensity strategy utilizing a registered nurse to provide monthly tailored behavioral support telephone calls plus home BP monitoring; and high-intensity strategy utilizing a pharmacist to provide monthly tailored behavioral support telephone calls, home BP monitoring, and pharmacist-directed medication management. Control arm patients receive the low-intensity strategy regardless of BP control. The primary outcome is SBP. There are 385 randomized (192 intervention; 193 control) veterans that are predominately older (mean age 63.5 years) men (92.5%). 61.8% are African American, and the mean baseline SBP for all subjects is 143.6mmHg. This trial will determine if a disease management program that is titrated by matching the intensity of resources to patients' BP control leads to superior outcomes compared to a low-intensity management strategy

    A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses

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    Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

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    A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

    Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

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    An embedding technique to determine ττ backgrounds in proton-proton collision data

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    An embedding technique is presented to estimate standard model tau tau backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed mu mu events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique described in this paper was developed for CMS. Its validation and the inherent uncertainties are also discussed. The demonstration of the performance of the technique is based on a sample of proton-proton collisions collected by CMS in 2017 at root s = 13 TeV corresponding to an integrated luminosity of 41.5 fb(-1).Peer reviewe
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