03086nas 2200709-a 450 991071734640332120241106213017.0(CKB)991042726136978(CONSER)---78615555-(EXLCZ)9999104272613697820760922b19582020 -a- aengtxtrdacontentcrdamediacrrdacarrierTidal current tablesAtlantic Coast of North AmericaWashington, D.C. U.S. Dept. of Commerce, Coast and Geodetic Survey[1958]-1 online resourceThe National Ocean Service ceased to distribute these tables in print format after 1995, and instead concurrently licenses various federal and commercial publishers to print and distribute, including: International Marine, <1996->; International Marine/McGraw-Hill, <2002->2008; North Wind Publishing, 2009- ; National Geospatial-Intelligence Agency, <2010->.Issues produced by the National Geospatial-Intelligence Agency (NGA) are intended for use aboard U.S. Navy vessels.Issues produced by the National Geospatial-Intelligence Agency (NGA) are distributed by GPO to regional depository libraries only.Print version: Tidal current tables. (DLC) 78615555 (OCoLC)2458466 0501-8234 Atlantic Coast of North AmericaTidal curr. tables, Atl. coast North Am.TidesAtlantic Coast (Canada)TablesPeriodicalsTidesAtlantic Coast (U.S.)TablesPeriodicalsTidesAtlantic Coast (North America)TablesPeriodicalsTidesGulf StatesTablesPeriodicalsTidal currentsAtlantic Coast (Canada)TablesPeriodicalsTidal currentsAtlantic Coast (U.S.)TablesPeriodicalsTidal currentsAtlantic Coast (North America)TablesPeriodicalsTidal currentsGulf StatesTablesPeriodicalsTidal currentsfast(OCoLC)fst01150760Tidesfast(OCoLC)fst01150792CanadaAtlantic CoastfastNorth AmericaAtlantic CoastfastUnited StatesAtlantic CoastfastUnited StatesGulf StatesfastTables (Data)fastPeriodicals.fastTables.fastTables (Data)lcgftTidesTidesTidesTidesTidal currentsTidal currentsTidal currentsTidal currentsTidal currents.Tides.623.89/49/091634U.S. Coast and Geodetic Survey.National Ocean Survey.NOAA National Ocean Service.United States.National Geospatial-Intelligence Agency.JOURNAL9910717346403321exl_impl conversionTidal current tables3275659UNINA03387nam 22005055 450 991029840710332120200702011749.03-319-98071-810.1007/978-3-319-98071-3(CKB)4100000007127536(MiAaPQ)EBC5592914(DE-He213)978-3-319-98071-3(PPN)232472556(EXLCZ)99410000000712753620181108d2018 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierFlow Cytometry Basics for the Non-Expert /by Christine Goetz, Christopher Hammerbeck, Jody Bonnevier1st ed. 2018.Cham :Springer International Publishing :Imprint: Springer,2018.1 online resource (xvii, 219 pages)Techniques in Life Science and Biomedicine for the Non-Expert,2367-11143-319-98070-X 1. Flow Cytometry: Definition, History, and Uses in Biotechnology -- 2. Physics of a Flow Cytometer -- 3. The Language of Flow Cytometry and Experimental Setup -- 4. Fluorochrome Choices for Flow Cytometry -- 5. Compensation -- 6. Primary and Seconardy Antibodies and Their Use in Flow Cytometry -- 7. Experimental Considerations with Data Sets as Examples -- 8. Cell Enrichment -- 9. Surface and Intracellular Staining Protocols for Flow Cytometry -- 10. Troubleshooting.Flow cytometry allows for the measurement of different aspects of a cell or particles in real time. Applications include quantifying various types of T cells to determine the presence of various immune disorders, such as whether HIV has progressed to AIDS, studying the dynamics of immune signaling in cells to detect the suppression of normal immune function, and analyzing biopsy specimens for tumors, to aid in cancer diagnosis and prognosis. In addition to simplifying the technique and using vocabulary accessible to those not trained in cell biology and immunology, the book includes the following 4 unqiue features: 1) Tips on how to set up an experiment for flow cytometry optimially 2) An expanded data set of flow staining including multiparameter flow cytometry 3) Detailed staining protocols for flow cytometry (ex. protocols optimized for transcription factors, secreted cytokines, phospho-antibodies, and surface antigens) 4) Section devoted to antibody development and conjugation.Techniques in Life Science and Biomedicine for the Non-Expert,2367-1114ImmunoglobulinsDiagnosis, LaboratoryAntibodieshttps://scigraph.springernature.com/ontologies/product-market-codes/B14010Laboratory Medicinehttps://scigraph.springernature.com/ontologies/product-market-codes/B15007Immunoglobulins.Diagnosis, Laboratory.Antibodies.Laboratory Medicine.574.87028Goetz Christineauthttp://id.loc.gov/vocabulary/relators/aut1059859Hammerbeck Christopherauthttp://id.loc.gov/vocabulary/relators/autBonnevier Jodyauthttp://id.loc.gov/vocabulary/relators/autBOOK9910298407103321Flow Cytometry Basics for the Non-Expert2508889UNINA07029nam 2201945z- 450 991055736750332120220111(CKB)5400000000042216(oapen)https://directory.doabooks.org/handle/20.500.12854/76447(oapen)doab76447(EXLCZ)99540000000004221620202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierClinical Studies, Big Data, and Artificial Intelligence in Nephrology and TransplantationBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (374 p.)3-0365-1134-2 3-0365-1135-0 In recent years, artificial intelligence has increasingly been playing an essential role in diverse areas in medicine, assisting clinicians in patient management. In nephrology and transplantation, artificial intelligence can be utilized to enhance clinical care, such as through hemodialysis prescriptions and the follow-up of kidney transplant patients. Furthermore, there are rapidly expanding applications and validations of comprehensive, computerized medical records and related databases, including national registries, health insurance, and drug prescriptions. For this Special Issue, we made a call to action to stimulate researchers and clinicians to submit their invaluable works and present, here, a collection of articles covering original clinical research (single- or multi-center), database studies from registries, meta-analyses, and artificial intelligence research in nephrology including acute kidney injury, electrolytes and acid-base, chronic kidney disease, glomerular disease, dialysis, and transplantation that will provide additional knowledge and skills in the field of nephrology and transplantation toward improving patient outcomes.Medicine and Nursingbicssc(cardiac) surgery16S rRNA sequencingacute kidney injuryacute rejectionallograftallograft steatosisanti-GBM diseasearea under the precision-recall curve (AUCPR)area under the receiver operating characteristic (AUROC)artificial intelligenceartificial neural network (ANN), clinical natural language processing (clinical NLP)big datablood pressurebone mineral densitybutyrate-producing bacteriaC/D ratiocardiovascular mortalitycellular crescentchronic kidney diseasechronic kidney disease (CKD)CKD-MBDCKD-Mineral and Bone Disorderclinical studiescollagen type VIcomorbidityconservative managementconversioncystatin Cdeathdeceased donordialysisdiarrheadischarge summariesdual-energy X-ray absorptiometryelderlyelectronic health record (EHR)epidemiologyeradicationerythropoietinestimated glomerular filtration rate (eGFR)ethnic disparityEurotransplant Senior Programeverolimusextracellular matrixFGF-23fibroblast growth factor 23fibrosisgeneralized linear model network (GLMnet)genetic polymorphismsglobal sclerosisglomerulosclerosisGoodpasture syndromeGoogle TrendsTMgraft failuregraft survivalgut microbiomegut microbiotahemodialysishepatitis C infectionhospitalizationhyperfiltrationICD-10 billing codesimmunosuppressed hostimmunosuppressionimmunosuppressive medicationin-hospital mortalityinflammationinflammatory cytokinesintensive careinterferon-free regimenkidney donorkidney injury molecule (KIM)-1kidney transplantkidney transplant recipientskidney transplantationklotholaboratory valueslaparoscopic surgeryLCPTlifestylelipopeliosislive donorsliver transplantationliving donationliving kidney donationliving-donor kidney transplantationlong-term outcomesmachine learningmachine learning (ML)MeltDose®metabolismmetabolomicsminimally-invasive donor nephrectomynephrologyNephrologyNLRno known kidney disease (NKD)organ donationoutcomeoutcomespatent ductus arteriosuspatient survivalphenotypingPLRpre-emptive transplantationpredictive valueprocurement kidney biopsyprolonged ischaemic timeProteobacteriapublic awarenessrandom forest (RF)renal functionrenal transplant recipientrenal transplantationrepeated kidney transplantationrisk predictionrisk stratificationrobot-assisted surgeryRPGNtacrolimustacrolimus metabolismtorquetenovirustransplant numberstransplantationtubular damageurinevascular calcificationweekend effectwithdrawalα-KlothoMedicine and NursingCheungpasitporn Wisitedt1277893Thongprayoon CharatedtKaewput WisitedtCheungpasitporn WisitothThongprayoon CharatothKaewput WisitothBOOK9910557367503321Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation3026967UNINA