Crystal growth furnace safety system validation

The findings are reported regarding the safe operation of the NASA crystal growth furnace (CGF) and potential methods for detecting containment failures of the furnace. The main conclusions are summarized by ampoule leak detection, cartridge leak detection, and detection of hazardous species in the experiment apparatus container (EAC)

Connexin 36 Expression Regulates Neuronal Differentiation from Neural Progenitor Cells

Background: Gap junction communication has been shown in glial and neuronal cells and it is thought they mediate interand intra-cellular communication. Connexin 36 (Cx36) is expressed extensively in the developing brain, with levels peaking at P14 after which its levels fall and its expression becomes entirely neuronal. These and other data have led to the hypothesis that Cx36 may direct neuronal coupling and neurogenesis during development. Methodology/Principal Findings: To investigate Cx36 function we used a neurosphere model of neuronal cell development and developed lentiviral Cx36 knockdown and overexpression strategies. Cx36 knockdown was confirmed by western blotting, immunocytochemistry and functionally by fluorescence recovery after photobleaching (FRAP). We found that knockdown of Cx36 in neurosphere neuronal precursors significantly reduced neuronal coupling and the number of differentiated neurons. Correspondingly, the lentiviral mediated overexpression of Cx36 significantly increased the number of neurons derived from the transduced neurospheres. The number of oligodendrocytes was also significantly increased following transduction with Cx36 indicating they may support neuronal differentiation. Conclusions/Significance: Our data suggests that astrocytic and neuronal differentiation during development are governed by mechanisms that include the differential expression of Cx36

Microporous scaffolds loaded with immunomodulatory lentivirus to study the contribution of immune cell populations to tumor cell recruitment in vivo

Metastases are preceded by stochastic formation of a hospitable microenvironment known as the premetastatic niche, which has been difficult to study. Herein, we employ implantable polycaprolactone scaffolds as an engineered premetastatic niche to independently investigate the role of interleukin‐10 (IL10), CXCL12, and CCL2 in recruiting immune and tumor cells and impacting breast cancer cell phenotype via lentiviral overexpression. Lentivirus delivered from scaffolds in vivo achieved sustained transgene expression for 56 days. IL10 lentiviral expression, but not CXCL12 or CCL2, significantly decreased tumor cell recruitment to scaffolds in vivo. Delivery of CXCL12 enhanced CD45+ immune cell recruitment to scaffolds while delivery of IL10 reduced immune cell recruitment. CCL2 did not alter immune cell recruitment. Tumor cell phenotype was investigated using conditioned media from immunomodulated scaffolds, with CXCL12 microenvironments reducing proliferation, and IL10 microenvironments enhancing proliferation. Migration was enhanced with CCL2 and reduced with IL10‐driven microenvironments. Multiple linear regression identified populations of immune cells associated with tumor cell abundance. CD45+ immune and CD8+ T cells were associated with reduced tumor cell abundance, while CD11b+Gr1+ neutrophils and CD4+ T cells were associated with enhanced tumor cell abundance. Collectively, biomaterial scaffolds provide a tool to probe the formation and function of the premetastatic niche.Metastases are preceded by stochastic formation of a hospitable microenvironment known as the premetastatic niche, which has been difficult to study. Herein, we employ implantable polycaprolactone scaffolds as an engineered premetastatic niche to independently investigate the role of interleukin‐10 (IL10), CXCL12, and CCL2 in recruiting immune and tumor cells and impacting breast cancer cell phenotype via lentiviral overexpression.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153114/1/bit27179.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153114/2/bit27179_am.pd

Demes:A standard format for demographic models

Understanding the demographic history of populations is a key goal in population genetics, and with improving methods and data, ever more complex models are being proposed and tested. Demographic models of current interest typically consist of a set of discrete populations, their sizes and growth rates, and continuous and pulse migrations between those populations over a number of epochs, which can require dozens of parameters to fully describe. There is currently no standard format to define such models, significantly hampering progress in the field. In particular, the important task of translating the model descriptions in published work into input suitable for population genetic simulators is labor intensive and error prone. We propose the Demes data model and file format, built on widely used technologies, to alleviate these issues. Demes provide a well-defined and unambiguous model of populations and their properties that is straightforward to implement in software, and a text file format that is designed for simplicity and clarity. We provide thoroughly tested implementations of Demes parsers in multiple languages including Python and C, and showcase initial support in several simulators and inference methods. An introduction to the file format and a detailed specification are available at https://popsim-consortium.github.io/demes-spec-docs/

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Pandemic influenza has the epidemic potential to kill millions of people. While various preventive measures exist (i.a., vaccination and school closures), deciding on strategies that lead to their most effective and efficient use remains challenging. To this end, individual-based epidemiological models are essential to assist decision makers in determining the best strategy to curb epidemic spread. However, individual-based models are computationally intensive and it is therefore pivotal to identify the optimal strategy using a minimal amount of model evaluations. Additionally, as epidemiological modeling experiments need to be planned, a computational budget needs to be specified a priori. Consequently, we present a new sampling technique to optimize the evaluation of preventive strategies using fixed budget best-arm identification algorithms. We use epidemiological modeling theory to derive knowledge about the reward distribution which we exploit using Bayesian best-arm identification algorithms (i.e., Top-two Thompson sampling and BayesGap). We evaluate these algorithms in a realistic experimental setting and demonstrate that it is possible to identify the optimal strategy using only a limited number of model evaluations, i.e., 2-to-3 times faster compared to the uniform sampling method, the predominant technique used for epidemiological decision making in the literature. Finally, we contribute and evaluate a statistic for Top-two Thompson sampling to inform the decision makers about the confidence of an arm recommendation

A Current Mode Detector Array for Gamma-Ray Asymmetry Measurements

We have built a CsI(Tl) gamma-ray detector array for the NPDGamma experiment to search for a small parity-violating directional asymmetry in the angular distribution of 2.2 MeV gamma-rays from the capture of polarized cold neutrons by protons with a sensitivity of several ppb. The weak pion-nucleon coupling constant can be determined from this asymmetry. The small size of the asymmetry requires a high cold neutron flux, control of systematic errors at the ppb level, and the use of current mode gamma-ray detection with vacuum photo diodes and low-noise solid-state preamplifiers. The average detector photoelectron yield was determined to be 1300 photoelectrons per MeV. The RMS width seen in the measurement is therefore dominated by the fluctuations in the number of gamma rays absorbed in the detector (counting statistics) rather than the intrinsic detector noise. The detectors were tested for noise performance, sensitivity to magnetic fields, pedestal stability and cosmic background. False asymmetries due to gain changes and electronic pickup in the detector system were measured to be consistent with zero to an accuracy of $10^{-9}$ in a few hours. We report on the design, operating criteria, and the results of measurements performed to test the detector array.Comment: 33 pages, 20 figures, 2 table

Search for Matter-Dependent Atmospheric Neutrino Oscillations in Super-Kamiokande

We consider muon neutrino to tau neutrino oscillations in the context of the Mass Varying Neutrino (MaVaN) model, where the neutrino mass can vary depending on the electron density along the flight path of the neutrino. Our analysis assumes a mechanism with dependence only upon the electron density, hence ordinary matter density, of the medium through which the neutrino travels. Fully-contained, partially-contained and upward-going muon atmospheric neutrino data from the Super--Kamiokande detector, taken from the entire SK--I period of 1489 live days, are compared to MaVaN model predictions. We find that, for the case of 2-flavor oscillations, and for the specific models tested, oscillation independent of electron density is favored over density dependence. Assuming maximal mixing, the best-fit case and the density-independent case do not differ significantly.Comment: 6 pages, 1 figur

Polarized He-3 gas compression system using metastability-exchange optical pumping

Dense samples (10-100 bar cm) of nuclear spin polarized He-3 are utilized in high energy physics, neutron scattering, atomic physics, and magnetic resonance imaging. Metastability exchange optical pumping can rapidly produce high He-3 polarizations (≈ 80%) at low pressures (few mbar). We describe a polarized He-3 gas compressor system which accepts 0.26 bar l h(-1) of He-3 gas polarized to 70% by a 4 W neodymium doped lanthanum magnesium hexaluminate (Nd:LMA) laser and compresses it into a 5 bar cm target with final polarization of 55%. The spin relaxation rates of the system\u27s components have been measured using nuclear magnetic resonance and a model of the He-3 polarization loss based on the measured relaxation rates and the gas flow is in agreement with a He-3 polarization measurement using neutron transmission. © 2005 American Institute of Physics

Olanzapine-Induced Hyperphagia and Weight Gain Associate with Orexigenic Hypothalamic Neuropeptide Signaling without Concomitant AMPK Phosphorylation

The success of antipsychotic drug treatment in patients with schizophrenia is limited by the propensity of these drugs to induce hyperphagia, weight gain and other metabolic disturbances, particularly evident for olanzapine and clozapine. However, the molecular mechanisms involved in antipsychotic-induced hyperphagia remain unclear. Here, we investigate the effect of olanzapine administration on the regulation of hypothalamic mechanisms controlling food intake, namely neuropeptide expression and AMP-activated protein kinase (AMPK) phosphorylation in rats. Our results show that subchronic exposure to olanzapine upregulates neuropeptide Y (NPY) and agouti related protein (AgRP) and downregulates proopiomelanocortin (POMC) in the arcuate nucleus of the hypothalamus (ARC). This effect was evident both in rats fed ad libitum and in pair-fed rats. Of note, despite weight gain and increased expression of orexigenic neuropeptides, subchronic administration of olanzapine decreased AMPK phosphorylation levels. This reduction in AMPK was not observed after acute administration of either olanzapine or clozapine. Overall, our data suggest that olanzapine-induced hyperphagia is mediated through appropriate changes in hypothalamic neuropeptides, and that this effect does not require concomitant AMPK activation. Our data shed new light on the hypothalamic mechanism underlying antipsychotic-induced hyperphagia and weight gain, and provide the basis for alternative targets to control energy balance