Blaschke, Sabine

[["dc.bibliographiccitation.firstpage","806"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","Clinical Toxicology"],["dc.bibliographiccitation.lastpage","812"],["dc.bibliographiccitation.volume","57"],["dc.contributor.author","Müller, Dieter"],["dc.contributor.author","Neurath, Hartmud"],["dc.contributor.author","Neukamm, Merja A."],["dc.contributor.author","Wilde, Maurice"],["dc.contributor.author","Despicht, Caroline"],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Grapp, Marcel"],["dc.date.accessioned","2020-12-10T18:15:18Z"],["dc.date.available","2020-12-10T18:15:18Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1080/15563650.2018.1554187"],["dc.identifier.eissn","1556-9519"],["dc.identifier.issn","1556-3650"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/74806"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","New synthetic opioid cyclopropylfentanyl together with other novel synthetic opioids in respiratory insufficient comatose patients detected by toxicological analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","076002"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Journal of Biomedical Optics"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Montejo, Ludguier D."],["dc.contributor.author","Jia, Jingfei"],["dc.contributor.author","Kim, Hyun K."],["dc.contributor.author","Netz, Uwe J."],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Mueller, Georg Anton"],["dc.contributor.author","Hielscher, Andreas H."],["dc.date.accessioned","2018-11-07T09:22:50Z"],["dc.date.available","2018-11-07T09:22:50Z"],["dc.date.issued","2013"],["dc.description.abstract","This is the second part of a two-part paper on the application of computer-aided diagnosis to diffuse optical tomography (DOT) for diagnosing rheumatoid arthritis (RA). A comprehensive analysis of techniques for the classification of DOT images of proximal interphalangeal joints of subjects with and without RA is presented. A method for extracting heuristic features from DOT images was presented in Part 1. The ability of five classification algorithms to accurately label each DOT image as belonging to a subject with or without RA is analyzed here. The algorithms of interest are the k-nearest-neighbors, linear and quadratic discriminant analysis, self-organizing maps, and support vector machines (SVM). With a polynomial SVM classifier, we achieve 100.0% sensitivity and 97.8% specificity. Lower bounds for these results (at 95.0% confidence level) are 96.4% and 93.8%, respectively. Image features most predictive of RA are from the spatial variation of optical properties and the absolute range in feature values. The optimal classifiers are low-dimensional combinations (<7 features). These results underscore the high potential for DOT to become a clinically useful diagnostic tool and warrant larger prospective clinical trials to conclusively demonstrate the ultimate clinical utility of this approach. (c) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)"],["dc.identifier.doi","10.1117/1.JBO.18.7.076002"],["dc.identifier.isi","000323030400010"],["dc.identifier.pmid","23856916"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/29438"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Spie-soc Photo-optical Instrumentation Engineers"],["dc.relation.issn","1083-3668"],["dc.title","Computer-aided diagnosis of rheumatoid arthritis with optical tomography, Part 2: image classification"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Ritter, Zully"],["dc.contributor.author","Vogel, Stefan"],["dc.contributor.author","Schultze, Frank"],["dc.contributor.author","Pischek-Koch, Kerstin"],["dc.contributor.author","Schirrmeister, Wiebke"],["dc.contributor.author","Walcher, Felix"],["dc.contributor.author","Röhrig, Rainer"],["dc.contributor.author","Kesztyüs, Tibor"],["dc.contributor.author","Krefting, Dagmar"],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.editor","Séroussi, Brigitte"],["dc.contributor.editor","Weber, Patrick"],["dc.contributor.editor","Dhombres, Ferdinand"],["dc.contributor.editor","Grouin, Cyril"],["dc.contributor.editor","Liebe, Jan-David"],["dc.contributor.editor","Pelayo, Sylvia"],["dc.contributor.editor","Pinna, Andrea"],["dc.contributor.editor","Rance, Bastien"],["dc.contributor.editor","Sacchi, Lucia"],["dc.contributor.editor","Ugon, Adrien"],["dc.contributor.editor","Benis, Arriel"],["dc.contributor.editor","Gallos, Parisis"],["dc.date.accessioned","2022-06-01T09:39:49Z"],["dc.date.available","2022-06-01T09:39:49Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.3233/SHTI220529"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/108571"],["dc.notes.intern","DOI-Import GROB-572"],["dc.publisher","IOS Press"],["dc.relation.crisseries","Studies in Health Technology and Informatics"],["dc.relation.eisbn","9781643682853"],["dc.relation.isbn","9781643682846"],["dc.relation.ispartof","Challenges of Trustable AI and Added-Value on Health : Proceedings of MIE 2022"],["dc.title","Using Explainable Artificial Intelligence Models (ML) to Predict Suspected Diagnoses as Clinical Decision Support"],["dc.type","book_chapter"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","32"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Kidney and Blood Pressure Research"],["dc.bibliographiccitation.lastpage","35"],["dc.bibliographiccitation.volume","29"],["dc.contributor.author","Benöhr, P."],["dc.contributor.author","Grenz, A."],["dc.contributor.author","Hartmann, J. T."],["dc.contributor.author","Müller, G. A."],["dc.contributor.author","Blaschke, Sabine"],["dc.date.accessioned","2018-11-07T10:37:54Z"],["dc.date.available","2018-11-07T10:37:54Z"],["dc.date.issued","2006"],["dc.description.abstract","Background. Cystatin C has recently been proposed as an ideal marker for glomerular filtration rate (GFR). In this study, cystatin C serum levels were evaluated in comparison to serum creatinine concentrations and inulin clearances in patients with normal kidney function receiving cisplatin-based chemotherapy to assess the validity of cystatin C as an alternative endogenous marker of GFR. Methods: Blood samples for the assessment of cystatin C, creatinine and inulin clearances were collected in patients before and after application of cisplatin in a clinical trial. Overall, 41 patients were included in the study, 35 of them were eligible receiving cisplatin in two different cisplatin-based chemotherapy schedules. Results: A 21% increase of cystatin C serum levels was demonstrated in the placebo group after application of cisplatin. Analysis of inulin clearances revealed a 23% loss of inulin clearance in patients of the placebo arm. In contrast, significant changes could not be detected by analysis of serum creatinine levels. Conclusions: Cystatin C represents a more sensitive clinical marker than serum creatinine for the early assessment of GFR damage caused by cisplatin. Changes in cystatin C serum concentrations correlate well to GFR decrease as measured by inulin clearance. Copyright D 2006 S. Karger AG, Basel"],["dc.identifier.doi","10.1159/000092485"],["dc.identifier.isi","000238189000005"],["dc.identifier.pmid","16582575"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/45679"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","Najko"],["dc.relation.issn","1420-4096"],["dc.title","Cystatin C - A marker for assessment of the glomerular filtration rate in patients with cisplatin chemotherapy"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Clinical Research in Cardiology"],["dc.contributor.author","Slagman, Anna"],["dc.contributor.author","Pigorsch, Mareen"],["dc.contributor.author","Greiner, Felix"],["dc.contributor.author","Behringer, Wilhelm"],["dc.contributor.author","Bernhard, Michael"],["dc.contributor.author","Bienzeisler, Jonas"],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Burst, Volker"],["dc.contributor.author","Dechant, Katharina"],["dc.contributor.author","Dommasch, Michael"],["dc.contributor.author","Möckel, Martin"],["dc.date.accessioned","2022-09-01T09:51:30Z"],["dc.date.available","2022-09-01T09:51:30Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract\n \n Background\n In this retrospective routine data analysis, we investigate the number of emergency department (ED) consultations during the COVID-19 pandemic of 2020 in Germany compared to the previous year with a special focus on numbers of myocardial infarction and acute heart failure.\n \n \n Methods\n Aggregated case numbers for the two consecutive years 2019 and 2020 were obtained from 24 university hospitals and 9 non-university hospitals in Germany and assessed by age, gender, triage scores, disposition, care level and by ICD-10 codes including the tracer diagnoses myocardial infarction (I21) and heart failure (I50).\n \n \n Results\n A total of 2,216,627 ED consultations were analyzed, of which 1,178,470 occurred in 2019 and 1,038,157 in 2020. The median deviation in case numbers between 2019 and 2020 was − 14% [CI (− 11)–(− 16)]. After a marked drop in all cases in the first COVID-19 wave in spring 2020, case numbers normalized during the summer. Thereafter starting in calendar week 39 case numbers constantly declined until the end of the year 2020. The decline in case numbers predominantly concerned younger [− 16%; CI (− 13)–(− 19)], less urgent [− 18%; CI (− 12)–(− 22)] and non-admitted cases [− 17%; CI (− 13)–(− 20)] in particular during the second wave. During the entire observation period admissions for chest pain [− 13%; CI (− 21)–2], myocardial infarction [− 2%; CI (− 9)–11] and heart failure [− 2%; CI (− 10)–6] were less affected and remained comparable to the previous year.\n \n \n Conclusions\n ED visits were noticeably reduced during both SARS-CoV-2 pandemic waves in Germany but cardiovascular diagnoses were less affected and no refractory increase was noted. However, long-term effects cannot be ruled out and need to be analysed in future studies.\n \n \n Graphical abstract"],["dc.identifier.doi","10.1007/s00392-022-02074-3"],["dc.identifier.pii","2074"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/113983"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-597"],["dc.relation.eissn","1861-0692"],["dc.relation.issn","1861-0684"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Medical and cardio-vascular emergency department visits during the COVID-19 pandemic in 2020: is there a collateral damage? A retrospective routine data analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","076001"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Journal of Biomedical Optics"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Montejo, Ludguier D."],["dc.contributor.author","Jia, Jingfei"],["dc.contributor.author","Kim, Hyun K."],["dc.contributor.author","Netz, Uwe J."],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Mueller, Georg Anton"],["dc.contributor.author","Hielscher, Andreas H."],["dc.date.accessioned","2018-11-07T09:22:51Z"],["dc.date.available","2018-11-07T09:22:51Z"],["dc.date.issued","2013"],["dc.description.abstract","This is the first part of a two-part paper on the application of computer-aided diagnosis to diffuse optical tomography (DOT). An approach for extracting heuristic features from DOT images and a method for using these features to diagnose rheumatoid arthritis (RA) are presented. Feature extraction is the focus of Part 1, while the utility of five classification algorithms is evaluated in Part 2. The framework is validated on a set of 219 DOT images of proximal interphalangeal (PIP) joints. Overall, 594 features are extracted from the absorption and scattering images of each joint. Three major findings are deduced. First, DOT images of subjects with RA are statistically different (p < 0.05) from images of subjects without RA for over 90% of the features investigated. Second, DOT images of subjects with RA that do not have detectable effusion, erosion, or synovitis (as determined by MRI and ultrasound) are statistically indistinguishable from DOT images of subjects with RA that do exhibit effusion, erosion, or synovitis. Thus, this subset of subjects may be diagnosed with RA from DOT images while they would go undetected by reviews of MRI or ultrasound images. Third, scattering coefficient images yield better one-dimensional classifiers. A total of three features yield a Youden index greater than 0.8. These findings suggest that DOT may be capable of distinguishing between PIP joints that are healthy and those affected by RA with or without effusion, erosion, or synovitis. (c) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)"],["dc.identifier.doi","10.1117/1.JBO.18.7.076001"],["dc.identifier.isi","000323030400009"],["dc.identifier.pmid","23856915"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/29439"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Spie-soc Photo-optical Instrumentation Engineers"],["dc.relation.issn","1083-3668"],["dc.title","Computer-aided diagnosis of rheumatoid arthritis with optical tomography, Part 1: feature extraction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","432"],["dc.bibliographiccitation.issue","05"],["dc.bibliographiccitation.journal","Aktuelle Rheumatologie"],["dc.bibliographiccitation.lastpage","441"],["dc.bibliographiccitation.volume","42"],["dc.contributor.author","Sewerin, Philipp"],["dc.contributor.author","Klein, Sabine"],["dc.contributor.author","Brinks, Ralph"],["dc.contributor.author","Hoyer, Annika"],["dc.contributor.author","Schleich, Christoph"],["dc.contributor.author","Miese, Falk"],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Edelmann, Edmund"],["dc.contributor.author","Gao, Ino"],["dc.contributor.author","Georgi, Joachim"],["dc.contributor.author","Kellner, Herbert"],["dc.contributor.author","Keyßer, Gernot"],["dc.contributor.author","Lorenz, Hanns-Martin"],["dc.contributor.author","Müller-Ladner, Ulf"],["dc.contributor.author","Pott, Hans-Georg"],["dc.contributor.author","Schulze-Koops, Hendrik"],["dc.contributor.author","Walther, Marisa"],["dc.contributor.author","Schmidt, Wolfgang"],["dc.contributor.author","Schneider, Matthias"],["dc.contributor.author","Ostendorf, Benedikt"],["dc.date.accessioned","2020-12-10T18:12:21Z"],["dc.date.available","2020-12-10T18:12:21Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1055/s-0042-124184"],["dc.identifier.eissn","1438-9940"],["dc.identifier.issn","0341-051X"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/74341"],["dc.language.iso","de"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","REMISSIONPLUS eine Initiative zur Integration moderner Bildgebung in die rheumatologische Versorgung Rückblick, Einblick, Ausblick: Auswertung der Niederfeld-MRT Daten"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1477"],["dc.bibliographiccitation.issue","16"],["dc.bibliographiccitation.journal","AIDS Research and Human Retroviruses"],["dc.bibliographiccitation.lastpage","1485"],["dc.bibliographiccitation.volume","15"],["dc.contributor.author","Buske, Christian"],["dc.contributor.author","Hannig, Horst"],["dc.contributor.author","Schneider, Eva-Maria"],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Hunsmann, Gerhard"],["dc.contributor.author","Bodemer, Walter"],["dc.contributor.author","Hiddemann, Wolfgang"],["dc.date.accessioned","2022-10-06T13:34:40Z"],["dc.date.available","2022-10-06T13:34:40Z"],["dc.date.issued","1999"],["dc.identifier.doi","10.1089/088922299309991"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/115967"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-602"],["dc.relation.eissn","1931-8405"],["dc.relation.issn","0889-2229"],["dc.relation.orgunit","Deutsches Primatenzentrum"],["dc.title","Transforming Growth Factor beta Is a Growth-Inhibitory Cytokine of B Cell Lymphoma in SIV-Infected Macaques"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","10"],["dc.bibliographiccitation.journal","Arthritis & Rheumatism"],["dc.bibliographiccitation.volume","64"],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Trautmann, Sandra"],["dc.contributor.author","Beham, Alexander W."],["dc.contributor.author","Mai, Burkhard"],["dc.contributor.author","Koelling, Sebastian"],["dc.contributor.author","Breysach, Caroline"],["dc.contributor.author","Wolf, Gabriele"],["dc.contributor.author","Mueller, Georg Anton"],["dc.contributor.author","Miosge, Nicolai"],["dc.date.accessioned","2018-11-07T09:04:58Z"],["dc.date.available","2018-11-07T09:04:58Z"],["dc.date.issued","2012"],["dc.format.extent","S517"],["dc.identifier.isi","000309748302284"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/25220"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.publisher.place","Hoboken"],["dc.relation.conference","Annual Scientific Meeting of the American-College-of-Rheumatology (ACR) and Association-of-Rheumatology-Health-Professionals (ARHP)"],["dc.relation.eventlocation","Washington, DC"],["dc.relation.issn","0004-3591"],["dc.title","Functional Role of Chondrogenic Progenitor Cells in Rheumatoid Arthritis."],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Journal of Arthritis"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Vasko, Radovan"],["dc.contributor.author","Blaschke, Sabine"],["dc.contributor.author","Streich, Jan-Hendrik"],["dc.contributor.author","Müller, Gerhard A."],["dc.contributor.author","Korsten, Peter"],["dc.contributor.author","Dihazi, Hassan"],["dc.date.accessioned","2020-05-04T07:22:22Z"],["dc.date.available","2020-05-04T07:22:22Z"],["dc.date.issued","2016"],["dc.description.abstract","Background: To identify differentially regulated serum proteins, we compared proteome profiles of sera from patients with rheumatoid arthritis (RA) and healthy controls using proteomics. Methods: Sera were collected from 43 patients with RA and 48 healthy volunteers. The samples were cleared of the most abundant major proteins by immunoaffinity chromatography. Serum protein profiles between the two groups were compared by two-dimensional differential gel electrophoresis (2D-DIGE) and differentially regulated proteins were studied using mass spectrometry. Results: We identified 26 differentially expressed serum proteins between patients with RA and healthy controls. A quantitatively significant change of protein levels was defined as at least 1.5-fold upregulation or 0.6-fold downregulation respectively. Using these criteria, patients with RA exhibited significantly higher levels of leucine-rich alpha-2-glycoprotein (p<0.01), apolipoprotein A-IV (p<0.001), clusterin (p<0.001), haptoglobin (p<0.001), Ig alpha-1 chain C region (p<0.05), retinol-binding protein 4 (p<0.001), serum amyloid A (p<0.01) and alpha-1-antichymotrypsin (p<0.01). The levels of serotransferrin were significantly decreased in RA patients (p<0.01). Conclusion: We identified eight proteins with significantly increased and one protein with significantly decreased serum levels in RA patients compared to healthy controls. Several of these proteins may be implicated in the pathogenesis of RA and may have potential in diagnostics and activity assessment of RA."],["dc.identifier.doi","10.4172/2167-7921.1000201"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/64544"],["dc.language.iso","en"],["dc.relation.issn","2167-7921"],["dc.title","Comparative Serum Proteomic Analysis of Differentially Regulated Proteins in Patients with Rheumatoid Arthritis and Healthy Volunteers"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]