Alteration of Blood–Brain Barrier Integrity by Retroviral Infection

The blood–brain barrier (BBB), which forms the interface between the blood and the cerebral parenchyma, has been shown to be disrupted during retroviral-associated neuromyelopathies. Human T Lymphotropic Virus (HTLV-1) Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP) is a slowly progressive neurodegenerative disease associated with BBB breakdown. The BBB is composed of three cell types: endothelial cells, pericytes and astrocytes. Although astrocytes have been shown to be infected by HTLV-1, until now, little was known about the susceptibility of BBB endothelial cells to HTLV-1 infection and the impact of such an infection on BBB function. We first demonstrated that human cerebral endothelial cells express the receptors for HTLV-1 (GLUT-1, Neuropilin-1 and heparan sulfate proteoglycans), both in vitro, in a human cerebral endothelial cell line, and ex vivo, on spinal cord autopsy sections from HAM/TSP and non-infected control cases. In situ hybridization revealed HTLV-1 transcripts associated with the vasculature in HAM/TSP. We were able to confirm that the endothelial cells could be productively infected in vitro by HTLV-1 and that blocking of either HSPGs, Neuropilin 1 or Glut1 inhibits this process. The expression of the tight-junction proteins within the HTLV-1 infected endothelial cells was altered. These cells were no longer able to form a functional barrier, since BBB permeability and lymphocyte passage through the monolayer of endothelial cells were increased. This work constitutes the first report of susceptibility of human cerebral endothelial cells to HTLV-1 infection, with implications for HTLV-1 passage through the BBB and subsequent deregulation of the central nervous system homeostasis. We propose that the susceptibility of cerebral endothelial cells to retroviral infection and subsequent BBB dysfunction is an important aspect of HAM/TSP pathogenesis and should be considered in the design of future therapeutics strategies

Optimization of Variable Cross-Sectional Area Thermoelectric Elements Through Multi-method Thermal-Electric Coupled Modeling

A well-posed thermal-electric coupled mathematical-numerical model to optimize the cross-sectional area per length of a thermoelectric (TE) leg is introduced to maximize thermal conversion efficiency (eta) or power output (Po). To employ such optimization, the p- or n-type leg was divided into uniform length segments, wherein the product of the electrical resistance (Rel) and thermal conductance (K) was minimized as to maximize the figure of merit (ZT) of each individual partition. The minimization of RelK was dependent upon the temperature difference established across each segment, which was resolved using a one-dimensional finite difference (FD) scheme of the TE general energy equation (GEQ). The TE GEQ included all pertinent phenomena - conduction, Joule, Peltier and Thomson effects - as well as temperature dependent properties. The boundary conditions of the FD scheme were provided via a one-dimensional thermal resistance network. The current output of the unicouple was determined by the temperature bounds across the junction and the internal resistance of the TE legs, and this was explicitly coupled to the TE GEQ to create a fully-coupled model. The proposed model was validated to a fully-coupled thermal-electric finite volume method model implemented in ANSYS CFX. The proposed optimization process yielded improvements in volumetric efficiency and volumetric power output of 4.60% and 3.75%, respectively, in comparison to conventional constant-area optimization processes

Mathematical Modeling of a Thermoelectric Generator Unicouple

To ascertain the simultaneous thermal and electrical performance of a thermoelectric (TE) unicouple with interconnectors, a thermal-electric coupled iterative mathematical model is introduced. The non-linear constitutive equations describing TE phenomena within the unicouple are linked to a thermal resistance network describing the interconnectors’ behavior. Thereupon, the thermal resistance of the interconnectors, and Joule heat generated within, are considered. Temperature dependent material properties are handled by integral-averaging techniques and an iterative solution methodology. Model form uncertainty is quantified by evaluating four unique analytic models. The first, the Implicit Thomson Model (ITM), considers the Thomson effect via integral averaging of the Seebeck coefficient. The second, the Explicit Thomson Model (ETM), decouples the Thomson effect from the Peltier effect; Thomson heat is explicitly solved using the Thomson coefficient. The third, the zT model, uses the figure of merit to describe the optimum efficiency-maximizing load resistance, and quantify device efficiency under maximum power scenarios. The last, the Differential Equation Model, does not assume distributions of Joule and Thomson heats to the cold- and hot-side interfaces as do the ITM, ETM and zT model. The predictive ability of each analytic model used within the unicouple-level model is compared to high-fidelity numeric results obtained from a three-dimensional, thermal-electric coupled model implemented in ANSYS CFX. Considering a range of hot-side unicouple temperatures, each analytic model exhibits agreement with one another, and with the numeric model. With increasing load resistance values, model form uncertainty and disagreement between analytic and numeric predictions decreases to a couple of percent at optimum operating points

Optimization Methods for Segmented Thermoelectric Generators

Future National Aeronautics and Space Administration deep-space missions are seeking radioisotope propulsion systems (RPS) to have specific powers above 8 [We/kg], while having thermal conversion efficiencies greater than 12%. The design and optimization of segmented thermoelectric unicouples used within RPS requires a multi-faceted approach to maximize device performance. The design space of a unicouple can span multiple dimensions, requiring immense computational resources to conduct parametric studies. These dimensions include, but are not limited to, the independent cross-sectional areas of the $n$- and $p$-type legs, the total height of the unicouple, the length of the high-temperature n- and p-type segments, the cold-side junction temperature and the load resistance applied to the couple, considering a fixed hot-side junction temperature, fixed per-couple heat input, and desired output voltage. To this end, computationally-inexpensive methods that optimize segmented unicouples are presented and compared. These methods include physics-based algorithms that dynamically reduce the design space when nonviable configurations are found, implementation of Golden Section Search (GSS) algorithm when uni-modal behavior is observed for a specific degree of freedom, and successive design space refinement. When using both GSS and successive design space refinement algorithms, an optimum geometry was found with 5,755 times fewer solver calls in comparison to the conventional parametric study without any loss of fidelity. This comparison indicates the proposed optimization methods are robust and accurate, while also drastically reducing the computation time to find the optimum unicouple configuration that maximizes system-level power output. These methods allow for exhaustive trade studies to be conducted of newly proposed heat sources, converter materials and designs, and heat exchange systems

Experimental Validation of Cryobot Thermal Models for the Exploration of Ocean Worlds

The tables in this repository represent the data used in the figures and analyses of the paper "Experimental Validation of Cryobot Thermal Models for the Exploration of Ocean Worlds", published in the Planetary Science Journal. The provided data was collected between 2020 and 2022.Work at the Jet Propulsion Laboratory, California Institute of Technology, was carried out under a contract (80NM0018D0004) with the National Aeronautics and Space Administration (NASA) and with funding from a NASA Scientific Exploration Subsurface Access Mechanism for Europa (SESAME) grant (80NM0018F0560). Work at the University of Washington was carried out under the same SESAME grant (80NM0018F0560). Work at Stone Aerospace and MIT was carried out under a separate NASA SESAME grant (80NSSC19K0612), as well as under the MIT TVML Fellowship