103 research outputs found
Hypoxia-enhanced Blood-Brain Barrier Chip recapitulates human barrier function and shuttling of drugs and antibodies
The high selectivity of the human blood-brain barrier (BBB) restricts delivery of many pharmaceuticals and therapeutic antibodies to the central nervous system. Here, we describe an in vitro microfluidic organ-on-a-chip BBB model lined by induced pluripotent stem cell-derived human brain microvascular endothelium interfaced with primary human brain astrocytes and pericytes that recapitulates the high level of barrier function of the in vivo human BBB for at least one week in culture. The endothelium expresses high levels of tight junction proteins and functional efflux pumps, and it displays selective transcytosis of peptides and antibodies previously observed in vivo. Increased barrier functionality was accomplished using a developmentally-inspired induction protocol that includes a period of differentiation under hypoxic conditions. This enhanced BBB Chip may therefore represent a new in vitro tool for development and validation of delivery systems that transport drugs and therapeutic antibodies across the human BBB
Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector
Measurements of electrons from interactions are crucial for the Deep
Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as
searches for physics beyond the standard model, supernova neutrino detection,
and solar neutrino measurements. This article describes the selection and
reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector.
ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and
operated at CERN as a charged particle test beam experiment. A sample of
low-energy electrons produced by the decay of cosmic muons is selected with a
purity of 95%. This sample is used to calibrate the low-energy electron energy
scale with two techniques. An electron energy calibration based on a cosmic ray
muon sample uses calibration constants derived from measured and simulated
cosmic ray muon events. Another calibration technique makes use of the
theoretically well-understood Michel electron energy spectrum to convert
reconstructed charge to electron energy. In addition, the effects of detector
response to low-energy electron energy scale and its resolution including
readout electronics threshold effects are quantified. Finally, the relation
between the theoretical and reconstructed low-energy electron energy spectrum
is derived and the energy resolution is characterized. The low-energy electron
selection presented here accounts for about 75% of the total electron deposited
energy. After the addition of lost energy using a Monte Carlo simulation, the
energy resolution improves from about 40% to 25% at 50~MeV. These results are
used to validate the expected capabilities of the DUNE far detector to
reconstruct low-energy electrons.Comment: 19 pages, 10 figure
Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment
A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is
to measure the MeV neutrinos produced by a Galactic
core-collapse supernova if one should occur during the lifetime of the
experiment. The liquid-argon-based detectors planned for DUNE are expected to
be uniquely sensitive to the component of the supernova flux, enabling
a wide variety of physics and astrophysics measurements. A key requirement for
a correct interpretation of these measurements is a good understanding of the
energy-dependent total cross section for charged-current
absorption on argon. In the context of a simulated extraction of
supernova spectral parameters from a toy analysis, we investigate the
impact of modeling uncertainties on DUNE's supernova neutrino
physics sensitivity for the first time. We find that the currently large
theoretical uncertainties on must be substantially reduced
before the flux parameters can be extracted reliably: in the absence of
external constraints, a measurement of the integrated neutrino luminosity with
less than 10\% bias with DUNE requires to be known to about 5%.
The neutrino spectral shape parameters can be known to better than 10% for a
20% uncertainty on the cross-section scale, although they will be sensitive to
uncertainties on the shape of . A direct measurement of
low-energy -argon scattering would be invaluable for improving the
theoretical precision to the needed level.Comment: 25 pages, 21 figure
Pseudoacromegaly
© 2018 Elsevier Inc. Individuals with acromegaloid physical appearance or tall stature may be referred to endocrinologists to exclude growth hormone (GH) excess. While some of these subjects could be healthy individuals with normal variants of growth or physical traits, others will have acromegaly or pituitary gigantism, which are, in general, straightforward diagnoses upon assessment of the GH/IGF-1 axis. However, some patients with physical features resembling acromegaly â usually affecting the face and extremities â, or gigantism â accelerated growth/tall stature â will have no abnormalities in the GH axis. This scenario is termed pseudoacromegaly, and its correct diagnosis can be challenging due to the rarity and variability of these conditions, as well as due to significant overlap in their characteristics. In this review we aim to provide a comprehensive overview of pseudoacromegaly conditions, highlighting their similarities and differences with acromegaly and pituitary gigantism, to aid physicians with the diagnosis of patients with pseudoacromegaly.PM is supported by a clinical fellowship by Barts and the London Charity. Our studies on pituitary adenomas and related conditions received support from the Medical Research Council, Rosetrees Trust and the Wellcome Trust
A local human VÎŽ1 T cell population is associated with survival in nonsmall-cell lung cancer
Murine tissues harbor signature γΎ T cell compartments with profound yet differential impacts on carcinogenesis. Conversely, human tissue-resident γΎ cells are less well defined. In the present study, we show that human lung tissues harbor a resident VÎŽ1 γΎ T cell population. Moreover, we demonstrate that VÎŽ1 T cells with resident memory and effector memory phenotypes were enriched in lung tumors compared with nontumor lung tissues. Intratumoral VÎŽ1 T cells possessed stem-like features and were skewed toward cytolysis and helper T cell type 1 function, akin to intratumoral natural killer and CD8+ T cells considered beneficial to the patient. Indeed, ongoing remission post-surgery was significantly associated with the numbers of CD45RAâCD27â effector memory VÎŽ1 T cells in tumors and, most strikingly, with the numbers of CD103+ tissue-resident VÎŽ1 T cells in nonmalignant lung tissues. Our findings offer basic insights into human body surface immunology that collectively support integrating VÎŽ1 T cell biology into immunotherapeutic strategies for nonsmall cell lung cancer
Highly-parallelized simulation of a pixelated LArTPC on a GPU
The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype
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