The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Quantitative Urinary Proteome Analysis for Biomarker Evaluation in Chronic Kidney Disease
Abstract
A limitation of proteomic methods with respect to their clinical applicability is the lack of possibilities to directly deduce the amount of a protein or peptide from a particular mass spectrometry (MS) spectrum. For quantification of chronic kidney disease (CKD)-specific urinary polypeptides in capillary electrophoresis coupled with mass spectrometry (CE-MS), we compared signal intensity calibration methods based on either urinary creatinine or stable isotope labeled synthetic marker analogues (absolute quantification) with those based on ion counting using highly abundant collagen fragments as nonmarker references (relative quantification). Our results indicate that relative quantification of biomarker excretion based on ion counts in reference to endogenous "housekeeping" peptides is sufficient for the determination of urinary polypeptide levels. The calculation of absolute concentrations via exogenous stable isotope-labeled peptide standards is of no additional benefit.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Use of Single Voided Urine Samples to Estimate Quantitative Proteinuria
Ginsberg, J. M., Chang, B. S., Matarese, R. A., & Garella, S. (1983) · New England Journal of Medicine · doi:10.1056/nejm198312223092503 · Cited by 756
Discovery and validation of new protein biomarkers for urothelial cancer: a prospective analysis
Theodorescu, D., Wittke, S., Ross, M. M., Walden, M., Conaway, M., Just, I., Mischak, H., & Frierson, H. F. (2006) · The Lancet Oncology · doi:10.1016/s1470-2045(06)70584-8 · Cited by 410
Self-citationKolch, W., Neusüß, C., Pelzing, M., & Mischak, H. (2005) · Mass Spectrometry Reviews · doi:10.1002/mas.20051 · Cited by 290
Self-citationAdvances in Urinary Proteome Analysis and Biomarker Discovery
Fliser, D., Novak, J., Thongboonkerd, V., Argile[Combining Acute Accent]s, A. G. A., Jankowski, V., Girolami, M. A., Jankowski, J., & Mischak, H. (2007) · Journal of the American Society of Nephrology · doi:10.1681/asn.2006090956 · Cited by 286
Self-citationUrinary Proteomics in Diabetes and CKD
Rossing, K., Mischak, H., Dakna, M., Zürbig, P., Novak, J., Julian, B. A., Good, D. M., Coon, J. J., Tarnow, L., & Rossing, P. (2008) · Journal of the American Society of Nephrology · doi:10.1681/asn.2007091025 · Cited by 283
Self-citationDecramer, S., Wittke, S., Mischak, H., Zürbig, P., Walden, M., Bouissou, F., Bascands, J.-L., & Schanstra, J. P. (2006) · Nature Medicine · doi:10.1038/nm1384 · Cited by 274
Self-citationGood, D. M., Thongboonkerd, V., Novak, J., Bascands, J.-L., Schanstra, J. P., Coon, J. J., Dominiczak, A., & Mischak, H. (2007) · Journal of Proteome Research · doi:10.1021/pr070529w · Cited by 244
Self-citationBarnidge, D. R., Dratz, E. A., Martin, T., Bonilla, L. E., Moran, L. B., & Lindall, A. (2003) · Analytical Chemistry · doi:10.1021/ac026154+ · Cited by 227
Urinary Proteomic Biomarkers in Coronary Artery Disease
Zimmerli, L. U., Schiffer, E., Zürbig, P., Good, D. M., Kellmann, M., Mouls, L., Pitt, A. R., Coon, J. J., Schmieder, R. E., Peter, K. H., et al. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m700394-mcp200 · Cited by 226
Self-citationUrine Biomarkers Predict the Cause of Glomerular Disease
Varghese, S. A., Powell, T. B., Budisavljevic, M. N., Oates, J. C., Raymond, J. R., Almeida, J. S., & Arthur, J. M. (2007) · Journal of the American Society of Nephrology · doi:10.1681/asn.2006070767 · Cited by 221
DeLeo, J. M. (2002) · 1993 (2nd) International Symposium on Uncertainty Modeling and Analysis · doi:10.1109/isuma.1993.366750 · Cited by 213
Practical Points in Urinary Proteomics
Thongboonkerd, V. (2007) · Journal of Proteome Research · doi:10.1021/pr070328s · Cited by 208
CE‐MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics
Coon, J. J., Zürbig, P., Dakna, M., Dominiczak, A. F., Decramer, S., Fliser, D., Frommberger, M., Golovko, I., Good, D. M., Herget‐Rosenthal, S., et al. (2008) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.200800024 · Cited by 207
Self-citationConstancy of urinary creatinine excretion.
VESTERGAARD, P., & LEVERETT, R. (1958) · PubMed · Cited by 201
Neuhoff, N. V., Kaiser, T., Wittke, S., Krebs, R., Pitt, A., Burchard, A., Sundmacher, A., Schlegelberger, B., Kolch, W., & Mischak, H. (2004) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.1294 · Cited by 200
Self-citationProteomic analysis for the assessment of diabetic renal damage in humans
MISCHAK, H., KAISER, T., WALDEN, M., HILLMANN, M., WITTKE, S., HERRMANN, A., KNUEPPEL, S., HALLER, H., & FLISER, D. (2004) · Clinical Science · doi:10.1042/cs20040103 · Cited by 176
Self-citationCreatinine excretion: variability and relationships to diet and body size.
Bleiler, R. E., & Schedl, H. P. (1962) · PubMed · Cited by 173
Proteomic Identification of Urinary Biomarkers of Diabetic Nephropathy
Rao, P. V., Lu, X., Standley, M., Pattee, P., Neelima, G., Girisesh, G., Dakshinamurthy, K. V., Roberts, C. T., & Nagalla, S. R. (2007) · Diabetes Care · doi:10.2337/dc06-2056 · Cited by 172
Kaiser, T., Kamal, H., Rank, A., Kolb, H.-J., Holler, E., Ganser, A., Hertenstein, B., Mischak, H., & Weissinger, E. M. (2004) · Blood · doi:10.1182/blood-2004-02-0518 · Cited by 163
Self-citationWeissinger, E. M., Schiffer, E., Hertenstein, B., Ferrara, J. L. M., Holler, E., Stadler, M., Kolb, H., Zander, A. R., Zürbig, P., Kellmann, M., et al. (2007) · Blood · doi:10.1182/blood-2007-01-069757 · Cited by 149
Self-citationDiscovery and validation of urinary biomarkers for prostate cancer
Theodorescu, D., Schiffer, E., Bauer, H. W., Douwes, F. R., Eichhorn, F., Polley, R., Schmidt, T., Schöfer, W., Zürbig, P., Good, D. M., et al. (2008) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.200780082 · Cited by 144
Self-citationSharma, K., Lee, S., Han, S., Lee, S., Francos, B. B., McCue, P. A., Wassell, R. P., Shaw, M., & RamachandraRao, S. P. (2005) · PROTEOMICS · doi:10.1002/pmic.200401288 · Cited by 130
Wittke, S., Mischak, H., Walden, M., Kölch, W., Rädler, T., & Wiedemann, K. (2005) · Electrophoresis · doi:10.1002/elps.200410140 · Cited by 127
Self-citationQuantitative Proteomics: A Review of Different Methodologies
Righetti, P. G., Campostrini, N., Pascali, J. P., Hamdan, M. H., & Astner, H. (2004) · European Journal of Mass Spectrometry · doi:10.1255/ejms.600 · Cited by 103
Kaiser, T., Wittke, S., Just, I., Krebs, R., Bartel, S. J., Fliser, D., Mischak, H., & Weissinger, E. M. (2004) · Electrophoresis · doi:10.1002/elps.200305788 · Cited by 92
Self-citationChronic kidney disease: The distribution of health care dollars
Peter, W. L. S., Khan, S. S., Ebben, J. P., Pereira, B. J. G., & Collins, A. J. (2004) · Kidney International · doi:10.1111/j.1523-1755.2004.00733.x · Cited by 72
Recent progress in urinary proteomics
Thongboonkerd, V. (2007) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.200700035 · Cited by 66
Cell biology, development, physiology, hormones-peptides
(2005) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/20.suppl_5.v20 · Cited by 7
Cited by
Application of biomarkers in the development of drugs intended for the treatment of osteoarthritis
Kraus, V. B., Burnett, B., Coindreau, J., Cottrell, S., Eyre, D., Gendreau, M., Gardiner, J., Garnero, P., Hardin, J., Henrotin, Y., et al. (2011) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2010.08.019 · Cited by 328
Mischak, H., Coon, J. J., Novak, J., Weissinger, E. M., Schanstra, J. P., & Dominiczak, A. F. (2009) · Mass Spectrometry Reviews · doi:10.1002/mas.20205 · Cited by 193
Self-citationCE‐MS‐based proteomics in biomarker discovery and clinical application
Pontillo, C., Filip, S., Borràs, D. M., Mullen, W., Vlahou, A., & Mischak, H. (2015) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.201400115 · Cited by 77
Self-citation
Metadata
- Authors
- Jantos-Siwy, J., Schiffer, E., Brand, K., Schumann, G., Rossing, K., Delles, C., Mischak, H., & Metzger, J.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2008-11-14
- Volume
- 8
- Issue
- 1
- Pages
- 268-281
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2004799239
- Cited by
- 259
- References
- 28
- FWCI
- 6.25
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.