179 research outputs found

    Tracking Cryptosporidium parvum by sequence analysis of small double-stranded RNA.

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    We sequenced a 173-nucleotide fragment of the small double-stranded viruslike RNA of Cryptosporidium parvum isolates from 23 calves and 38 humans. Sequence diversity was detected at 17 sites. Isolates from the same outbreak had identical double-stranded RNA sequences, suggesting that this technique may be useful for tracking Cryptosporidium infection sources

    Conceptual Design of a 10-Seater Electric Aircraft

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    With the increase in population, an increase of transportation needs is inevitable, especially in air travel. There is an underlying problem in this matter that is carbon pollutions. Air travel contributes around 2% of the global emissions. This paper contains the conceptual design of 10-seater electric aircraft that can serve as a cleaner alternative for air travel. The paper will discuss about our objectives and the results of configurations, backed with calculations of proof in all aspects that is needed. In conclusions, this paper presents a conceptual design of 10-seater electric aircraft that have range more than 450 km. The aircraft being designed has a mid-wing three surface configuration with a MTOW of 7250 kg

    Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction

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    We address the problem of causal effect estima-tion in the presence of unobserved confounding,but where proxies for the latent confounder(s) areobserved. We propose two kernel-based meth-ods for nonlinear causal effect estimation in thissetting: (a) a two-stage regression approach, and(b) a maximum moment restriction approach. Wefocus on the proximal causal learning setting, butour methods can be used to solve a wider classof inverse problems characterised by a Fredholmintegral equation. In particular, we provide a uni-fying view of two-stage and moment restrictionapproaches for solving this problem in a nonlin-ear setting. We provide consistency guaranteesfor each algorithm, and demonstrate that these ap-proaches achieve competitive results on syntheticdata and data simulating a real-world task. In par-ticular, our approach outperforms earlier methodsthat are not suited to leveraging proxy variables

    Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction

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    We address the problem of causal effect estimation in the presence of unobserved confounding, but where proxies for the latent confounder(s) are observed. We propose two kernel-based methods for nonlinear causal effect estimation in this setting: (a) a two-stage regression approach, and (b) a maximum moment restriction approach. We focus on the proximal causal learning setting, but our methods can be used to solve a wider class of inverse problems characterised by a Fredholm integral equation. In particular, we provide a unifying view of two-stage and moment restriction approaches for solving this problem in a nonlinear setting. We provide consistency guarantees for each algorithm, and we demonstrate these approaches achieve competitive results on synthetic data and data simulating a real-world task. In particular, our approach outperforms earlier methods that are not suited to leveraging proxy variables

    Electroconductive Hydrogel Based on Functional Poly(Ethylenedioxy Thiophene).

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    Poly(ethylene dioxythiophene) with functional pendant groups bearing double bonds is synthesized and employed for the fabrication of electroactive hydrogels with advantageous characteristics: covalently cross-linked porous 3D scaffolds with notable swelling ratio, appropriate mechanical properties, electroactivity in physiological conditions, and suitability for proliferation and differentiation of C2C12 cells. This is a new approach for the fabrication of conductive engineered constructs

    Pancreatic Mesenchyme Regulates Epithelial Organogenesis throughout Development

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    The developing pancreatic epithelium gives rise to all endocrine and exocrine cells of the mature organ. During organogenesis, the epithelial cells receive essential signals from the overlying mesenchyme. Previous studies, focusing on ex vivo tissue explants or complete knockout mice, have identified an important role for the mesenchyme in regulating the expansion of progenitor cells in the early pancreas epithelium. However, due to the lack of genetic tools directing expression specifically to the mesenchyme, the potential roles of this supporting tissue in vivo, especially in guiding later stages of pancreas organogenesis, have not been elucidated. We employed transgenic tools and fetal surgical techniques to ablate mesenchyme via Cre-mediated mesenchymal expression of Diphtheria Toxin (DT) at the onset of pancreas formation, and at later developmental stages via in utero injection of DT into transgenic mice expressing the Diphtheria Toxin receptor (DTR) in this tissue. Our results demonstrate that mesenchymal cells regulate pancreatic growth and branching at both early and late developmental stages by supporting proliferation of precursors and differentiated cells, respectively. Interestingly, while cell differentiation was not affected, the expansion of both the endocrine and exocrine compartments was equally impaired. To further elucidate signals required for mesenchymal cell function, we eliminated β-catenin signaling and determined that it is a critical pathway in regulating mesenchyme survival and growth. Our study presents the first in vivo evidence that the embryonic mesenchyme provides critical signals to the epithelium throughout pancreas organogenesis. The findings are novel and relevant as they indicate a critical role for the mesenchyme during late expansion of endocrine and exocrine compartments. In addition, our results provide a molecular mechanism for mesenchymal expansion and survival by identifying β-catenin signaling as an essential mediator of this process. These results have implications for developing strategies to expand pancreas progenitors and β-cells for clinical transplantation
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