3,382 research outputs found

    Expandable and Rapidly Differentiating Human Induced Neural Stem Cell Lines for Multiple Tissue Engineering Applications

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    Limited availability of human neurons poses a significant barrier to progress in biological and preclinical studies of the human nervous system. Current stem cell-based approaches of neuron generation are still hindered by prolonged culture requirements, protocol complexity, and variability in neuronal differentiation. Here we establish stable human induced neural stem cell (hiNSC) lines through the direct reprogramming of neonatal fibroblasts and adult adipose-derived stem cells. These hiNSCs can be passaged indefinitely and cryopreserved as colonies. Independently of media composition, hiNSCs robustly differentiate into TUJ1-positive neurons within 4 days, making them ideal for innervated co-cultures. In vivo, hiNSCs migrate, engraft, and contribute to both central and peripheral nervous systems. Lastly, we demonstrate utility of hiNSCs in a 3D human brain model. This method provides a valuable interdisciplinary tool that could be used to develop drug screening applications as well as patient-specific disease models related to disorders of innervation and the brain

    Annotation of two large contiguous regions from the Haemonchus contortus genome using RNA-seq and comparative analysis with Caenorhabditis elegans

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    The genomes of numerous parasitic nematodes are currently being sequenced, but their complexity and size, together with high levels of intra-specific sequence variation and a lack of reference genomes, makes their assembly and annotation a challenging task. Haemonchus contortus is an economically significant parasite of livestock that is widely used for basic research as well as for vaccine development and drug discovery. It is one of many medically and economically important parasites within the strongylid nematode group. This group of parasites has the closest phylogenetic relationship with the model organism Caenorhabditis elegans, making comparative analysis a potentially powerful tool for genome annotation and functional studies. To investigate this hypothesis, we sequenced two contiguous fragments from the H. contortus genome and undertook detailed annotation and comparative analysis with C. elegans. The adult H. contortus transcriptome was sequenced using an Illumina platform and RNA-seq was used to annotate a 409 kb overlapping BAC tiling path relating to the X chromosome and a 181 kb BAC insert relating to chromosome I. In total, 40 genes and 12 putative transposable elements were identified. 97.5% of the annotated genes had detectable homologues in C. elegans of which 60% had putative orthologues, significantly higher than previous analyses based on EST analysis. Gene density appears to be less in H. contortus than in C. elegans, with annotated H. contortus genes being an average of two-to-three times larger than their putative C. elegans orthologues due to a greater intron number and size. Synteny appears high but gene order is generally poorly conserved, although areas of conserved microsynteny are apparent. C. elegans operons appear to be partially conserved in H. contortus. Our findings suggest that a combination of RNA-seq and comparative analysis with C. elegans is a powerful approach for the annotation and analysis of strongylid nematode genomes

    Gene therapy for carcinoma of the breast: Therapeutic genetic correction strategies

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    Gene therapy is a therapeutic approach that is designed to correct specific molecular defects that contribute to the cause or progression of cancer. Genes that are mutated or deleted in cancers include the cancer susceptibility genes p53 and BRCA1. Because mutational inactivation of gene function is specific to tumor cells in these settings, cancer gene correction strategies may provide an opportunity for selective targeting without significant toxicity for normal nontumor cells. Both p53 and BRCA1 appear to inhibit cancer cells that lack mutations in these genes, suggesting that the so-called gene correction strategies may have broader potential than initially believed. Increasing knowledge of cancer genetics has identified these and other genes as potential targets for gene replacement therapy. Initial patient trials of p53 and BRCA1 gene therapy have provided some indications of potential efficacy, but have also identified areas of basic and clinical research that are needed before these approaches may be widely used in patient care

    Does \u2018bigger\u2019mean \u2018better\u2019? Pitfalls and shortcuts associated with big data for social research

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    \u2018Big data is here to stay.\u2019 This key statement has a double value: is an assumption as well as the reason why a theoretical reflection is needed. Furthermore, Big data is something that is gaining visibility and success in social sciences even, overcoming the division between humanities and computer sciences. In this contribution some considerations on the presence and the certain persistence of Big data as a socio-technical assemblage will be outlined. Therefore, the intriguing opportunities for social research linked to such interaction between practices and technological development will be developed. However, despite a promissory rhetoric, fostered by several scholars since the birth of Big data as a labelled concept, some risks are just around the corner. The claims for the methodological power of bigger and bigger datasets, as well as increasing speed in analysis and data collection, are creating a real hype in social research. Peculiar attention is needed in order to avoid some pitfalls. These risks will be analysed for what concerns the validity of the research results \u2018obtained through Big data. After a pars distruens, this contribution will conclude with a pars construens; assuming the previous critiques, a mixed methods research design approach will be described as a general proposal with the objective of stimulating a debate on the integration of Big data in complex research projecting

    Jet Dipolarity: Top Tagging with Color Flow

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    A new jet observable, dipolarity, is introduced that can distinguish whether a pair of subjets arises from a color singlet source. This observable is incorporated into the HEPTopTagger and is shown to improve discrimination between top jets and QCD jets for moderate to high pT.Comment: 8 pages, 6 figures (updated to JHEP version

    Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

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    Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogs from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multi-band deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalog created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σΔz=0.007\sigma_{\Delta z} = 0.007, which is a 60% improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.Comment: 24 pages, 11 figures; matches version accepted to MNRA

    Search for first-generation scalar and vector leptoquarks

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    Intelligent data analysis to interpret major risk factors for diabetic patients with and without ischemic stroke in a small population

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    This study proposes an intelligent data analysis approach to investigate and interpret the distinctive factors of diabetes mellitus patients with and without ischemic (non-embolic type) stroke in a small population. The database consists of a total of 16 features collected from 44 diabetic patients. Features include age, gender, duration of diabetes, cholesterol, high density lipoprotein, triglyceride levels, neuropathy, nephropathy, retinopathy, peripheral vascular disease, myocardial infarction rate, glucose level, medication and blood pressure. Metric and non-metric features are distinguished. First, the mean and covariance of the data are estimated and the correlated components are observed. Second, major components are extracted by principal component analysis. Finally, as common examples of local and global classification approach, a k-nearest neighbor and a high-degree polynomial classifier such as multilayer perceptron are employed for classification with all the components and major components case. Macrovascular changes emerged as the principal distinctive factors of ischemic-stroke in diabetes mellitus. Microvascular changes were generally ineffective discriminators. Recommendations were made according to the rules of evidence-based medicine. Briefly, this case study, based on a small population, supports theories of stroke in diabetes mellitus patients and also concludes that the use of intelligent data analysis improves personalized preventive intervention

    Scaling Patterns for QCD Jets

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    Jet emission at hadron colliders follows simple scaling patterns. Based on perturbative QCD we derive Poisson and staircase scaling for final state as well as initial state radiation. Parton density effects enhance staircase scaling at low multiplicities. We propose experimental tests of our theoretical findings in Z+jets and QCD gap jets production based on minor additions to current LHC analyses.Comment: 36 pages, 16 figure

    Search for dark matter in association with a Higgs boson decaying to b-quarks in pp collisions at s=13 TeV with the ATLAS detector

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    A search for dark matter pair production in association with a Higgs boson decaying to a pair of bottom quarks is presented, using 3.2 fb−1 of pp collisions at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the LHC. The decay of the Higgs boson is reconstructed as a high-momentum bb¯ system with either a pair of small-radius jets, or a single large-radius jet with substructure. The observed data are found to be consistent with the expected backgrounds. Results are interpreted using a simplified model with a Z′ gauge boson mediating the interaction between dark matter and the Standard Model as well as a two-Higgs-doublet model containing an additional Z′ boson which decays to a Standard Model Higgs boson and a new pseudoscalar Higgs boson, the latter decaying into a pair of dark matter particles
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