62 research outputs found

    A novel, highly discriminatory risk model predicting acute severe right ventricular failure in patients undergoing continuous‐flow left ventricular assist device implant

    Full text link
    Various risk models with differing discriminatory power and predictive accuracy have been used to predict right ventricular failure (RVF) after left ventricular assist device (LVAD) placement. There remains an unmet need for a contemporary risk score for continuous flow (CF)‐LVADs. We sought to independently validate and compare existing risk models in a large cohort of patients and develop a simple, yet highly predictive risk score for acute, severe RVF. Data from the Mechanical Circulatory Support Research Network (MCSRN) registry, consisting of patients who underwent CF‐LVAD implantation, were randomly divided into equal‐sized derivation and validation samples. RVF scores were calculated for the entire sample, and the need for a right ventricular assist device (RVAD) was the primary endpoint. Candidate predictors from the derivation sample were subjected to backward stepwise logistic regression until the model with lowest Akaike information criterion value was identified. A risk score was developed based on the identified variables and their respective regression coefficients. Between May 2004 and September 2014, 734 patients underwent implantation of CF‐LVADs [HeartMate II LVAD, 76% (n = 560), HeartWare HVAD, 24% (n = 174)]. A RVAD was required in 4.5% (n = 33) of the patients [Derivation cohort, n = 15 (4.3%); Validation cohort, n = 18 (5.2%); P = 0.68)]. 19.5% of the patients (n = 143) were female, median age at implant was 59 years (IQR, 49.4–65.3), and median INTERMACS profile was 3 (IQR, 2–3). RVAD was required in 4.5% (n = 33) of the patients. Correlates of acute, severe RVF in the final model included heart rate, albumin, BUN, WBC, cardiac index, and TR severity. Areas under the curves (AUC) for most commonly used risk predictors ranged from 0.61 to 0.78. The AUC for the new model was 0.89 in the derivation and 0.92 in the validation cohort. Proposed risk model provides very high discriminatory power predicting acute severe right ventricular failure and can be reliably applied to patients undergoing placement of contemporary continuous flow left ventricular assist devices.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150536/1/aor13413_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150536/2/aor13413.pd

    The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

    Get PDF
    Background: The NORMAN Association (https://www.norman-.network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-.network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https:// zenodo.org/communities/norman-.sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox. epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-.network.com/nds/SLE/)

    Finishing the euchromatic sequence of the human genome

    Get PDF
    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∌99% of the euchromatic genome and is accurate to an error rate of ∌1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    The NORMAN Suspect List Exchange (NORMAN-SLE): Facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

    Get PDF
    Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/)

    The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

    Get PDF
    The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.The NORMAN-SLE project has received funding from the NORMAN Association via its joint proposal of activities. HMT and ELS are supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. ELS, PC, SEH, HPHA, ZW acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036756, project ZeroPM: Zero pollution of persistent, mobile substances. The work of EEB, TC, QL, BAS, PAT, and JZ was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). JOB is the recipient of an NHMRC Emerging Leadership Fellowship (EL1 2009209). KVT and JOB acknowledge the support of the Australian Research Council (DP190102476). The Queensland Alliance for Environmental Health Sciences, The University of Queensland, gratefully acknowledges the financial support of the Queensland Department of Health. NR is supported by a Miguel Servet contract (CP19/00060) from the Instituto de Salud Carlos III, co-financed by the European Union through Fondo Europeo de Desarrollo Regional (FEDER). MM and TR gratefully acknowledge financial support by the German Ministry for Education and Research (BMBF, Bonn) through the project “Persistente mobile organische Chemikalien in der aquatischen Umwelt (PROTECT)” (FKz: 02WRS1495 A/B/E). LiB acknowledges funding through a Research Foundation Flanders (FWO) fellowship (11G1821N). JAP and JMcL acknowledge financial support from the NIH for CCSCompendium (S50 CCSCOMPEND) via grants NIH NIGMS R01GM092218 and NIH NCI 1R03CA222452-01, as well as the Vanderbilt Chemical Biology Interface training program (5T32GM065086-16), plus use of resources of the Center for Innovative Technology (CIT) at Vanderbilt University. TJ was (partly) supported by the Dutch Research Council (NWO), project number 15747. UFZ (TS, MaK, WB) received funding from SOLUTIONS project (European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 603437). TS, MaK, WB, JPA, RCHV, JJV, JeM and MHL acknowledge HBM4EU (European Union’s Horizon 2020 research and innovation programme under the grant agreement no. 733032). TS acknowledges funding from NFDI4Chem—Chemistry Consortium in the NFDI (supported by the DFG under project number 441958208). TS, MaK, WB and EMLJ acknowledge NaToxAq (European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 722493). S36 and S63 (HPHA, SEH, MN, IS) were funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Project No. (FKZ) 3716 67 416 0, updates to S36 (HPHA, SEH, MN, IS) by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) Project No. (FKZ) 3719 65 408 0. MiK acknowledges financial support from the EU Cohesion Funds within the project Monitoring and assessment of water body status (No. 310011A366 Phase III). The work related to S60 and S82 was funded by the Swiss Federal Office for the Environment (FOEN), KK and JH acknowledge the input of Kathrin Fenner’s group (Eawag) in compiling transformation products from European pesticides registration dossiers. DSW and YDF were supported by the Canadian Institutes of Health Research and Genome Canada. The work related to S49, S48 and S77 was funded by the MAVA foundation; for S77 also the Valery Foundation (KG, JaM, BG). DML acknowledges National Science Foundation Grant RUI-1306074. YL acknowledges the National Natural Science Foundation of China (Grant No. 22193051 and 21906177), and the Chinese Postdoctoral Science Foundation (Grant No. 2019M650863). WLC acknowledges research project 108C002871 supported by the Environmental Protection Administration, Executive Yuan, R.O.C. Taiwan (Taiwan EPA). JG acknowledges funding from the Swiss Federal Office for the Environment. AJW was funded by the U.S. Environmental Protection Agency. LuB, AC and FH acknowledge the financial support of the Generalitat Valenciana (Research Group of Excellence, Prometeo 2019/040). KN (S89) acknowledges the PhD fellowship through Marie SkƂodowska-Curie grant agreement No. 859891 (MSCA-ETN). Exposome-Explorer (S34) was funded by the European Commission projects EXPOsOMICS FP7-KBBE-2012 [308610]; NutriTech FP7-KBBE-2011-5 [289511]; Joint Programming Initiative FOODBALL 2014–17. CP acknowledges grant RYC2020-028901-I funded by MCIN/AEI/1.0.13039/501100011033 and “ESF investing in your future”, and August T Larsson Guest Researcher Programme from the Swedish University of Agricultural Sciences. The work of ML, MaSe, SG, TL and WS creating and filling the STOFF-IDENT database (S2) mostly sponsored by the German Federal Ministry of Education and Research within the RiSKWa program (funding codes 02WRS1273 and 02WRS1354). XT acknowledges The National Food Institute, Technical University of Denmark. MaSch acknowledges funding by the RECETOX research infrastructure (the Czech Ministry of Education, Youth and Sports, LM2018121), the CETOCOEN PLUS project (CZ.02.1.01/0.0/0.0/15_003/0000469), and the CETOCOEN EXCELLENCE Teaming 2 project supported by the Czech ministry of Education, Youth and Sports (No CZ.02.1.01/0.0/0.0/17_043/0009632).Peer reviewe

    Circumferential slot virtual impactor for concentrating aerosols

    No full text
    A circumferential slot virtual impactor includes a disk-shaped housing with an endless circumferential slot for receiving aerosols. The slot forms an acceleration nozzle, and a receiver nozzle spaced apart radially inwardly from the acceleration nozzle exit. In an annular gap between the two nozzles, negative pressure is selectively applied to draw a major flow of the aerosol axially away from the nozzles, while a minor flow of the aerosol is drawn radially inward and enters the receiver nozzle. A portion of the larger particles leaves the major flow and merges with the minor flow due to particle momentum, thus increasing the large-particle concentration of the minor flow. The acceleration nozzle incorporates convex curvature along its opposed interior surfaces, for a smoother aerosol flow and reduced large-particle deposition.U

    Circumferential slot virtual impactor for concentrating aerosols

    No full text
    A circumferential slot virtual impactor includes a disk-shaped housing with an endless circumferential slot for receiving aerosols. The slot forms an acceleration nozzle, and a receiver nozzle spaced apart radially inwardly from the acceleration nozzle exit. In an annular gap between the two nozzles, negative pressure is selectively applied to draw a major flow of the aerosol axially away from the nozzles, while a minor flow of the aerosol is drawn radially inward and enters the receiver nozzle. A portion of the larger particles leaves the major flow and merges with the minor flow due to particle momentum, thus increasing the large-particle concentration of the minor flow. The acceleration nozzle incorporates convex curvature along its opposed interior surfaces, for a smoother aerosol flow and reduced large-particle deposition.U

    Circumferential slot virtual impactor for concentrating aerosols

    No full text
    A circumferential slot virtual impactor includes a disk-shaped housing with an endless circumferential slot for receiving aerosols. The slot forms an acceleration nozzle, and a receiver nozzle spaced apart radially inwardly from the acceleration nozzle exit. In an annular gap between the two nozzles, negative pressure is selectively applied to draw a major flow of the aerosol axially away from the nozzles, while a minor flow of the aerosol is drawn radially inward and enters the receiver nozzle. A portion of the larger particles leaves the major flow and merges with the minor flow due to particle momentum, thus increasing the large-particle concentration of the minor flow. The acceleration nozzle incorporates convex curvature along its opposed interior surfaces, for a smoother aerosol flow and reduced large-particle deposition.U

    Circumferential slot virtual impactor for concentrating aerosols

    No full text
    A circumferential slot virtual impactor includes a disk-shaped housing with an endless circumferential slot for receiving aerosols. The slot forms an acceleration nozzle, and a receiver nozzle spaced apart radially inwardly from the acceleration nozzle exit. In an annular gap between the two nozzles, negative pressure is selectively applied to draw a major flow of the aerosol axially away from the nozzles, while a minor flow of the aerosol is drawn radially inward and enters the receiver nozzle. A portion of the larger particles leaves the major flow and merges with the minor flow due to particle momentum, thus increasing the large-particle concentration of the minor flow. The acceleration nozzle incorporates convex curvature along its opposed interior surfaces, for a smoother aerosol flow and reduced large-particle deposition.U
    • 

    corecore