Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 172

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Proteomic Identification of Urinary Biomarkers of Diabetic Nephropathy

Rao, Paturi V., Lu, Xinfang, Standley, Melissa, Pattee, Patrick, Neelima, Gundupalle, Girisesh, Gudige, Dakshinamurthy, K.V., Roberts, Charles T., Nagalla, Srinivasa R.·2007·Diabetes Care

Abstract

OBJECTIVE—Diabetic nephropathy is a serious complication of both type 1 and type 2 diabetes, and, unless arrested, leads to end-stage renal disease. Current diagnosis consists of urine assays of microalbuminuria, which have inadequate specificity and sensitivity. RESEARCH DESIGN AND METHODS—We used proteomic analyses to identify novel biomarkers of nephropathy in urine from type 2 diabetic patients with demonstrated normo-, micro-, or macroalbuminuria. Samples were analyzed by fluorescence two-dimensional (2-D) differential in-gel electrophoresis (DIGE), and protein identification was performed by liquid chromatography-tandem mass spectrometry. RESULTS—2-D DIGE analysis of the urinary proteome in diabetes with nephropathy identified 195 protein spots representing 62 unique proteins. These proteins belonged to several functional groups, i.e., cell development, cell organization, defense response, metabolism, and signal transduction. Comparisons between control and diabetic subjects with different stages of renal dysfunction revealed the differential expression of several proteins. Spot volume quantification identified 7 proteins that were progressively upregulated with increasing albuminuria and 4 proteins that exhibited progressive downregulation. The majority of these potential candidate biomarkers were glycoproteins. CONCLUSIONS—These data demonstrate the ability of proteomic analyses to reveal potential biomarkers for diabetic nephropathy in urine, an important step forward in advancing accurate diagnosis and our understanding of disease mechanisms.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2337/dc06-2056

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 1 references

Cited by

See all 172

Metadata

Authors
Rao, P. V., Lu, X., Standley, M., Pattee, P., Neelima, G., Girisesh, G., Dakshinamurthy, K. V., Roberts, C. T., & Nagalla, S. R.
Venue
Diabetes Care
Published
2007-03-01
Volume
30
Issue
3
Pages
629-637
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
OpenAlex
W2045153875
Cited by
172
References
1
FWCI
13.02
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Proteomic Identification of Urinary Biomarkers of Diabetic Nephropathy. https://app.cochat.ai/papers/10.2337/dc06-2056
The paper
Rao, P. V., Lu, X., Standley, M., Pattee, P., Neelima, G., Girisesh, G., Dakshinamurthy, K. V., Roberts, C. T., & Nagalla, S. R. (2007). Proteomic Identification of Urinary Biomarkers of Diabetic Nephropathy. Diabetes Care. https://doi.org/10.2337/dc06-2056

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.