62 research outputs found

    Effects of shear rate on propagation of blood clotting determined using microfluidics and numerical simulations

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    This paper describes microfluidic experiments with human blood plasma and numerical simulations to determine the role of fluid flow in the regulation of propagation of blood clotting. We demonstrate that propagation of clotting can be regulated by different mechanisms depending on the volume-to-surface ratio of a channel. In small channels, propagation of clotting can be prevented by surface-bound inhibitors of clotting present on vessel walls. In large channels, where surface-bound inhibitors are ineffective, propagation of clotting can be prevented by a shear rate above a threshold value, in agreement with predictions of a simple reaction-diffusion mechanism. We also demonstrate that propagation of clotting in a channel with a large volume-to-surface ratio and a shear rate below a threshold shear rate can be slowed by decreasing the production of thrombin, an activator of clotting. These in vitro results make two predictions, which should be experimentally tested in vivo. First, propagation of clotting from superficial veins to deep veins may be regulated by shear rate, which might explain the correlation between superficial thrombosis and the development of deep vein thrombosis (DVT). Second, nontoxic thrombin inhibitors with high binding affinities could be locally administered to prevent recurrent thrombosis after a clot has been removed. In addition, these results demonstrate the utility of simplified mechanisms and microfluidics for generating and testing predictions about the dynamics of complex biochemical networks

    Propagation of blood clotting in the complex biochemical network of hemostasis is described by a simple mechanism

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    Hemostasis is the complex biochemical network that controls blood clotting. We previously described a chemical model that mimicked the dynamics of hemostasis based on a simple regulatory mechanisma threshold response due to the competition between production and removal of activators. Here, we used human blood plasma in phospholipid-coated microfluidic channels to test predictions based on this mechanism. We demonstrated that, for a given geometry of channels, clot propagation from an obstructed channel into a channel with flowing blood plasma is dependent on the shear rate in the channel with flowing blood plasma. If confirmed in vivo, these results may explain clot propagation from a small vessel to a larger, clinically relevant vessel. In addition, these results would further validate the use of modular mechanisms, simplified chemical models, and microfluidics to study complex biochemical networks

    The Lunar Polar Hydrogen Mapper (LunaH-Map) CubeSat Mission

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    The Lunar Polar Hydrogen Mapper (LunaH-Map) is a 6U CubeSat mission recently selected by NASA\u27s Science Mission Directorate to fly as a secondary payload on first Exploration Mission (EM-1) of the Space Launch System (SLS), scheduled to launch in July 2018. LunaH-Map is led by a small team of researchers and students at Arizona State University, in collaboration with NASA centers, JPL, universities, and commercial space businesses. The LunaH-Map mission will reveal hydrogen abundances at spatial scales below 10 km in order to understand the relationship between hydrogen and permanently shadowed regions, particularly craters, at the Moon\u27s South Pole. The mission\u27s primary payload is designed to use the scintillator material Cs2YLiCl6:Ce, or CLYC to measure count rates of thermal and epithermal neutrons. Enabled by a low-thrust ion propulsion system, LunaH-Map will achieve lunar orbit insertion within ~12 months of SLS separation and maneuver into a highly elliptical, low-perilune (5-10 km) orbit centered around the South Pole of the Moon. In this orbit, LunaH-Map will achieve over 140 low-altitude fly-bys of the South Pole during its two month science phase. LunaH-Map and two fellow secondary payloads selected by NASA to fly on SLS EM-1 will be the first CubeSats to explore the Moon and interplanetary space

    Confidential Consortium Framework: Secure Multiparty Applications with Confidentiality, Integrity, and High Availability

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    Confidentiality, integrity protection, and high availability, abbreviated to CIA, are essential properties for trustworthy data systems. The rise of cloud computing and the growing demand for multiparty applications however means that building modern CIA systems is more challenging than ever. In response, we present the Confidential Consortium Framework (CCF), a general-purpose foundation for developing secure stateful CIA applications. CCF combines centralized compute with decentralized trust, supporting deployment on untrusted cloud infrastructure and transparent governance by mutually untrusted parties. CCF leverages hardware-based trusted execution environments for remotely verifiable confidentiality and code integrity. This is coupled with state machine replication backed by an auditable immutable ledger for data integrity and high availability. CCF enables each service to bring its own application logic, custom multiparty governance model, and deployment scenario, decoupling the operators of nodes from the consortium that governs them. CCF is open-source and available now at https://github.com/microsoft/CCF.Comment: 16 pages, 9 figures. To appear in the Proceedings of the VLDB Endowment, Volume 1

    Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

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    Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.Peer reviewe

    Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.

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    Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring
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