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Exercise promotes recovery after motoneuron injury via hormonal mechanisms
No full textInjuries to spinal motoneurons manifest in a variety of forms, including damage to peripheral axons, neurodegenerative disease, or direct insult centrally. Such injuries produce a variety of negative structural and functional changes in both the directly affected and neighboring motoneurons. Exercise is a relatively simple behavioral intervention that has been demonstrated to protect against, and accelerate recovery from, these negative changes. In this article, we describe how exercise is neuroprotective for motoneurons, accelerating axon regeneration following axotomy and attenuating dendritic atrophy following the death of neighboring motoneurons. In both of these injury models, the positive effects of exercise have been found to be dependent on gonadal hormone action. Here we describe a model in which exercise, hormones, and brain-derived neurotrophic factor might all interact to produce neuroprotective effects on motoneuron structure following neural injury
Gains in health insurance coverage explain variation in Democratic vote share in the 2008-2016 presidential elections
No full textIn the last decade, health care reform has dominated U.S. public policy and political discourse. Double-digit rate increases in premiums in the Health Insurance Marketplaces established by the Affordable Care Act (ACA) in 2018 make this an ongoing issue that could affect future elections. A seminal event that changed the course of policy and politics around health care reform is the 2016 presidential election. The results of the 2016 presidential election departed considerably from polling forecasts. Given the prominence of the Affordable Care Act in the election, we test whether changes in health insurance coverage at the county-level correlate with changes in party vote share in the presidential elections from 2008 through 2016. We find that a one-percentage-point increase in county health insurance coverage was associated with a 0.25-percentage-point increase in the vote share for the Democratic presidential candidate. We further find that these gains on the part of the Democratic candidate came almost fully at the expense of the Republican (as opposed to third-party) presidential candidates. We also estimate models separately for states that did and did not expand Medicaid and find no differential effect of insurance gains on Democratic vote share for states that expanded Medicaid compared to those that did not. Our results are consistent with the hypothesis that outcomes in health insurance markets played a role in the outcome of the 2016 presidential election. The decisions made by the current administration, and how those decisions affect health insurance coverage and costs, may be important factors in future elections as well
Defect-Directed Growth of Symmetrically Branched Metal Nanocrystals
No full textBranched plasmonic nanocrystals (NCs) have attracted much attention due to electric field enhancements at their tips. Seeded growth provides routes to NCs with defined branching patterns and, in turn, near‐field distributions with defined symmetries. Here, a systematic analysis was undertaken in which seeds containing different distributions of planar defects were used to grow branched NCs in order to understand how their distributions direct the branching. Characterization of the products by multimode electron tomography and analysis of the NC morphologies at different overgrowth stages indicate that the branching patterns are directed by the seed defects, with the emergence of branches from the seed faces consistent with minimizing volumetric strain energy at the expense of surface energy. These results contrast with growth of branched NCs from single‐crystalline seeds and provide a new platform for the synthesis of symmetrically branched plasmonic NCs
Generating dynamical neuroimaging spatiotemporal representations (DyNeuSR) using topological data analysis
No full textIn this article, we present an open source neuroinformatics platform for exploring, analyzing, and validating distilled graphical representations of high-dimensional neuroimaging data extracted using topological data analysis (TDA). TDA techniques like Mapper have been recently applied to examine the brain’s dynamical organization during ongoing cognition without averaging data in space, in time, or across participants at the outset. Such TDA-based approaches mark an important deviation from standard neuroimaging analyses by distilling complex high-dimensional neuroimaging data into simple—yet neurophysiologically valid and behaviorally relevant—representations that can be interactively explored at the single-participant level. To facilitate wider use of such techniques within neuroimaging and general neuroscience communities, our work provides several tools for visualizing, interacting with, and grounding TDA-generated graphical representations in neurophysiology. Through Python-based Jupyter notebooks and open datasets, we provide a platform to assess and visualize different intermittent stages of Mapper and examine the influence of Mapper parameters on the generated representations. We hope this platform could enable researchers and clinicians alike to explore topological representations of neuroimaging data and generate biological insights underlying complex mental disorders
Researchers' Perceptions of Ethical Authorship Distribution in Collaborative Research Teams
No full textAuthorship is commonly used as the basis for the measurement of research productivity. It influences career progression and rewards, making it a valued commodity in a competitive scientific environment. To better understand authorship practices amongst collaborative teams, this study surveyed authors on collaborative journal articles published between 2011 and 2015. Of the 8364 respondents, 1408 responded to the final open-ended question, which solicited additional comments or remarks regarding the fair distribution of authorship in research teams. This paper presents the analysis of these comments, categorized into four main themes: (1) disagreements, (2) questionable behavior, (3) external influences regarding authorship, and (4) values promoted by researchers. Results suggest that some respondents find ways to effectively manage disagreements in a collegial fashion. Conversely, others explain how distribution of authorship can become a “blood sport” or a “horror story” which can negatively affect researchers’ wellbeing, scientific productivity and integrity. Researchers fear authorship discussions and often try to avoid openly discussing the situation which can strain team interactions. Unethical conduct is more likely to result from deceit, favoritism, and questionable mentorship and may become more egregious when there is constant bullying and discrimination. Although values of collegiality, transparency and fairness were promoted by researchers, rank and need for success often overpowered ethical decision-making. This research provides new insight into contextual specificities related to fair authorship distribution that can be instrumental in developing applicable training tools to identify, prevent, and mitigate authorship disagreement
Khuri-Treiman equations for decays of particles with spin
No full textKhuri-Treiman equations have proven to be a useful theoretical tool in the analysis of 3-body decays, specially into the final state. In this work we present in full detail the necessary generalization of the formalism to study the decays of particles with arbitrary spin, parity, and charge conjugation. To this extent, we find it most convenient to work with helicity amplitudes instead of the so-called invariant amplitudes, specially when dealing with the unitarity relations. The isobar expansions in the three possible (, , and ) final channels are related with the appropriate crossing matrices. We pay special attention to the kinematical singularities and constraints of the helicity amplitudes, showing that these can be derived by means of the crossing matrix
Algorithmic approaches to clonal reconstruction in heterogeneous cell populations
No full textBackground: The reconstruction of clonal haplotypes and their evolutionary history in evolving populations is a common problem in both microbial evolutionary biology and cancer biology. The clonal theory of evolution provides a theoretical framework for modeling the evolution of clones. Results: In this paper, we review the theoretical framework and assumptions over which the clonal reconstruction problem is formulated. We formally define the problem and then discuss the complexity and solution space of the problem. Various methods have been proposed to find the phylogeny that best explains the observed data. We categorize these methods based on the type of input data that they use (space-resolved or time-resolved), and also based on their computational formulation as either combinatorial or probabilistic. It is crucial to understand the different types of input data because each provides essential but distinct information for drastically reducing the solution space of the clonal reconstruction problem. Complementary information provided by single cell sequencing or from whole genome sequencing of randomly isolated clones can also improve the accuracy of clonal reconstruction. We briefly review the existing algorithms and their relationships. Finally we summarize the tools that are developed for either directly solving the clonal reconstruction problem or a related computational problem. Conclusions: In this review, we discuss the various formulations of the problem of inferring the clonal evolutionary history from allele frequeny data, review existing algorithms and catergorize them according to their problem formulation and solution approaches. We note that most of the available clonal inference algorithms were developed for elucidating tumor evolution whereas clonal reconstruction for unicellular genomes are less addressed. We conclude the review by discussing more open problems such as the lack of benchmark datasets and comparison of performance between available tools
Properties of Stationary Statistical Solutions of the Three-Dimensional Navier-Stokes Equations
No full textThe stationary version of a modified definition of statistical solution for the three-dimensional incompressible Navier–Stokes equations introduced in a previous work is investigated. Particular types of such stationary statistical solutions and their analytical properties are addressed. Results on the support and carriers of these stationary statistical solutions are also given, showing in particular that they are supported on the weak global attractor and are carried by a more regular part of the weak global attractor containing Leray–Hopf weak solutions which are locally strong solutions. Two recurrence-type results related to these measures are also proved
The role of lipocalin-2 in age-related macular degeneration (AMD)
No full textLipocalins are a family of secreted adipokines which play important roles in various biological processes. Lipocalin-2 (LCN-2) has been shown to be involved in acute and chronic inflammation. This particular protein is critical in the pathogenesis of several diseases including cancer, diabetes, obesity, and multiple sclerosis. Herein, we discuss the general molecular basis for the involvement of LCN-2 in acute infections and chronic disease progression and also ascertain the probable role of LCN-2 in ocular diseases, particularly in age-related macular degeneration (AMD). We elaborate on the signaling cascades which trigger LCN-2 upregulation in AMD and suggest therapeutic strategies for targeting such pathways