31 research outputs found

    Compressive stress enhances coordinated migration of mammary carcinoma cells

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    Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references.Cancer research has traditionally focused on genetic and biochemical changes during tumor progression. Uncontrolled cell proliferation of a solid tumor in a confined space not only creates well-studied oxidative stress (hypoxia), but also generates growth-induced mechanical stress (compression). However, the importance of such compressive stress in tumor biology has been largely ignored. Our lab has previously shown that compressive stress influences tumor spheroid growth and stimulates production of extracellular matrix molecules. Others have also demonstrated the importance of matrix rigidity in tumor development and enhanced tumor cell adhesion by hydrostatic pressure. Yet whether growth-induced compressive stress can enhance caner cell migration and invasion remains unclear. The focus of this thesis is to evaluate the effect of anisotropic compressive stress on cancer cell motility. To mimic growth-induced compressive stress experienced by cancer cells in vivo, we developed an in vitro compression device for compressing a monolayer of cancer cells with precisely-defined normal forces. Here we show, for the first time, that externally-applied compressive stress resulted in faster migration of some mammary carcinoma cell lines. Independent of multi-cellular micro-organization, compression induced migration of mammary carcinoma cells in a coordinated sheet, initiated by "leader cells" -- single cells at the leading edge of the sheet, extending long filopodia.(cont.) Accompanied by redistribution of fibronectin deposition, compression enhanced cell-matrix adhesion and stabilized cell distension, thereby promoting coordinated cell migration. Using a stochastic model to simulate 2-D collective cell migration, cell distension and uniform cell migration were found to be crucial factors for effective collective migration. Our finding on compression-induced coordinated migration of mammary carcinoma cells has significant implications for in vivo situations where epithelial cancer cells form a "coordinated" invading mass guided by "leader" cells. Our work suggests that compressive stress generated by proliferating cancer cells can distort their shape, enhance cell-substrate adhesion and stimulate formation of leader cells responsible for collective cell migration. This discovery could open the door to characterization of novel pathways driven by mechanical-stress and improved strategies for cancer treatment.by Janet M. Tse.Sc.D

    High-energy neutrino follow-up search of gravitational wave event GW150914 with ANTARES and IceCube

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    We present the high-energy-neutrino follow-up observations of the first gravitational wave transient GW150914 observed by the Advanced LIGO detectors on September 14, 2015. We search for coincident neutrino candidates within the data recorded by the IceCube and Antares neutrino detectors. A possible joint detection could be used in targeted electromagnetic follow-up observations, given the significantly better angular resolution of neutrino events compared to gravitational waves. We find no neutrino candidates in both temporal and spatial coincidence with the gravitational wave event. Within ±500  s of the gravitational wave event, the number of neutrino candidates detected by IceCube and Antares were three and zero, respectively. This is consistent with the expected atmospheric background, and none of the neutrino candidates were directionally coincident with GW150914. We use this nondetection to constrain neutrino emission from the gravitational-wave event.by Anand Sengupta et al

    Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack:a pooled analysis of individual patient data from cohort studies

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    BACKGROUND Cerebral microbleeds are a neuroimaging biomarker of stroke risk. A crucial clinical question is whether cerebral microbleeds indicate patients with recent ischaemic stroke or transient ischaemic attack in whom the rate of future intracranial haemorrhage is likely to exceed that of recurrent ischaemic stroke when treated with antithrombotic drugs. We therefore aimed to establish whether a large burden of cerebral microbleeds or particular anatomical patterns of cerebral microbleeds can identify ischaemic stroke or transient ischaemic attack patients at higher absolute risk of intracranial haemorrhage than ischaemic stroke. METHODS We did a pooled analysis of individual patient data from cohort studies in adults with recent ischaemic stroke or transient ischaemic attack. Cohorts were eligible for inclusion if they prospectively recruited adult participants with ischaemic stroke or transient ischaemic attack; included at least 50 participants; collected data on stroke events over at least 3 months follow-up; used an appropriate MRI sequence that is sensitive to magnetic susceptibility; and documented the number and anatomical distribution of cerebral microbleeds reliably using consensus criteria and validated scales. Our prespecified primary outcomes were a composite of any symptomatic intracranial haemorrhage or ischaemic stroke, symptomatic intracranial haemorrhage, and symptomatic ischaemic stroke. We registered this study with the PROSPERO international prospective register of systematic reviews, number CRD42016036602. FINDINGS Between Jan 1, 1996, and Dec 1, 2018, we identified 344 studies. After exclusions for ineligibility or declined requests for inclusion, 20 322 patients from 38 cohorts (over 35 225 patient-years of follow-up; median 1·34 years [IQR 0·19-2·44]) were included in our analyses. The adjusted hazard ratio [aHR] comparing patients with cerebral microbleeds to those without was 1·35 (95% CI 1·20-1·50) for the composite outcome of intracranial haemorrhage and ischaemic stroke; 2·45 (1·82-3·29) for intracranial haemorrhage and 1·23 (1·08-1·40) for ischaemic stroke. The aHR increased with increasing cerebral microbleed burden for intracranial haemorrhage but this effect was less marked for ischaemic stroke (for five or more cerebral microbleeds, aHR 4·55 [95% CI 3·08-6·72] for intracranial haemorrhage vs 1·47 [1·19-1·80] for ischaemic stroke; for ten or more cerebral microbleeds, aHR 5·52 [3·36-9·05] vs 1·43 [1·07-1·91]; and for ≥20 cerebral microbleeds, aHR 8·61 [4·69-15·81] vs 1·86 [1·23-1·82]). However, irrespective of cerebral microbleed anatomical distribution or burden, the rate of ischaemic stroke exceeded that of intracranial haemorrhage (for ten or more cerebral microbleeds, 64 ischaemic strokes [95% CI 48-84] per 1000 patient-years vs 27 intracranial haemorrhages [17-41] per 1000 patient-years; and for ≥20 cerebral microbleeds, 73 ischaemic strokes [46-108] per 1000 patient-years vs 39 intracranial haemorrhages [21-67] per 1000 patient-years). INTERPRETATION In patients with recent ischaemic stroke or transient ischaemic attack, cerebral microbleeds are associated with a greater relative hazard (aHR) for subsequent intracranial haemorrhage than for ischaemic stroke, but the absolute risk of ischaemic stroke is higher than that of intracranial haemorrhage, regardless of cerebral microbleed presence, antomical distribution, or burden. FUNDING British Heart Foundation and UK Stroke Association

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

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    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 10310^3 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

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

    No full text
    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 10310^3 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

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

    No full text
    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 10310^3 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

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

    No full text
    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 10310^3 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

    Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment

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    International audienceA primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the O(10)  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 νe 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 σ(Eν) for charged-current νe absorption on argon. In the context of a simulated extraction of supernova νe spectral parameters from a toy analysis, we investigate the impact of σ(Eν) modeling uncertainties on DUNE’s supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on σ(Eν) must be substantially reduced before the νe 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 σ(Eν) 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 σ(Eν). A direct measurement of low-energy νe-argon scattering would be invaluable for improving the theoretical precision to the needed level

    Supernova Pointing Capabilities of DUNE

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    International audienceThe determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on 40^{40}Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called ``brems flipping'', as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE's burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage

    Supernova Pointing Capabilities of DUNE

    No full text
    International audienceThe determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on 40^{40}Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called ``brems flipping'', as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE's burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage
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