The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker
Open accessAbstract
Renal and urinary EGF can serve as biomarkers for prediction of outcomes in chronic kidney disease.
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
Toprak, O., Kurt, H., Sarı, Y., Şarkış, C., Us, H., & Kırık, A. (2017) · Kidney and Blood Pressure Research · doi:10.1159/000468530 · Cited by 29,627
Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V., Abraham, J., Adair, T., Aggarwal, R., Ahn, S. Y., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61728-0 · Cited by 14,070
Levey, A. S., Coresh, J., Bolton, K., Culleton, B. F., Harvey, K. S., Ikizler, T. A., Johnson, C. A., Kausz, A., Kimmel, P. L., Kusek, J. W., et al. (2002) · University of Groningen research database (University of Groningen / Centre for Information Technology) · Cited by 11,633
Sontrop, J. M., Dixon, S. N., Garg, A. X., Buendia-Jimenez, I., Dohein, O., Huang, S.-H. S., & Clark, W. F. (2013) · American Journal of Nephrology · doi:10.1159/000350377 · Cited by 5,871
Levey, A. S., Coresh, J., Greene, T., Stevens, L. A., Zhang, Y. (., Hendriksen, S., Kusek, J. W., & Van Lente, F. (2006) · Annals of Internal Medicine · doi:10.7326/0003-4819-145-4-200608150-00004 · Cited by 5,725
Chronic kidney disease: global dimension and perspectives
Jha, V., Garcia-Garcia, G., Iseki, K., Li, Z., Naicker, S., Plattner, B., Saran, R., Wang, A. Y.-M., & Yang, C.-W. (2013) · The Lancet · doi:10.1016/s0140-6736(13)60687-x · Cited by 4,383
Prevalence of chronic kidney disease in China: a cross-sectional survey
Zhang, L., Wang, F., Wang, L., Wang, W., Liu, B., Liu, J., Chen, M., He, Q., Liao, Y., Yu, X., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60033-6 · Cited by 2,091
Self-citationEpstein, F. H., Brenner, B. M., Meyer, T. W., & Hostetter, T. H. (1982) · New England Journal of Medicine · doi:10.1056/nejm198209093071104 · Cited by 2,075
Ma, Y.-C., Zuo, L., Chen, J.-H., Luo, Q., Yu, X.-Q., Li, Y., Xu, J.-S., Huang, S.-M., Wang, L.-N., Huang, W., et al. (2006) · Journal of the American Society of Nephrology · doi:10.1681/asn.2006040368 · Cited by 1,897
Self-citationLevey, A. S., Atkins, R., Coresh, J., Cohen, E. P., Collins, A. J., Eckardt, K.-U., Nahas, M. E., Jaber, B. L., Jadoul, M., Levin, A., et al. (2007) · Kidney International · doi:10.1038/sj.ki.5002343 · Cited by 1,516
Cited by
Opportunities and challenges in phenotypic drug discovery: an industry perspective
Moffat, J. G., Vincent, F., Lee, J. A., Eder, J., & Prunotto, M. (2017) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2017.111 · Cited by 939
Heerspink, H. J. L., Perco, P., Mulder, S., Leierer, J., Hansen, M. K., Heinzel, A., & Mayer, G. (2019) · Diabetologia · doi:10.1007/s00125-019-4859-4 · Cited by 457
Digital pathology and computational image analysis in nephropathology
Barisoni, L., Lafata, K. J., Hewitt, S. M., Madabhushi, A., & Balis, U. G. J. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0321-6 · Cited by 264
Self-citationFloege, J., Barbour, S. J., Cattran, D. C., Hogan, J. J., Nachman, P. H., Tang, S. C. W., Wetzels, J. F. M., Cheung, M., Wheeler, D. C., Winkelmayer, W. C., et al. (2019) · Kidney International · doi:10.1016/j.kint.2018.10.018 · Cited by 263
Self-citationMylonas, K. J., O’Sullivan, E. D., Humphries, D., Baird, D. P., Docherty, M.-H., Neely, S. A., Krimpenfort, P. J., Melk, A., Schmitt, R., Ferreira-Gonzalez, S., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abb0203 · Cited by 219
Metadata
- Authors
- Ju, W., Nair, V., Smith, S., Zhu, L., Shedden, K., Song, P. X. K., Mariani, L. H., Eichinger, F. H., Berthier, C. C., Randolph, A., Lai, J. Y.-C., Zhou, Y., Hawkins, J. J., Bitzer, M., Sampson, M. G., Thier, M., Solier, C., Duran-Pacheco, G. C., Duchateau-Nguyen, G., Essioux, L., Schott, B., Formentini, I., Magnone, M. C., Bobadilla, M., Cohen, C. D., Bagnasco, S. M., Barisoni, L., Lv, J., Zhang, H., Wang, H.-Y., Brosius, F. C., Gadegbeku, C. A., Kretzler, M., & for the ERCB, C.-P.
- Venue
- Science Translational Medicine
- Published
- 2015-12-02
- Volume
- 7
- Issue
- 316
- Pages
- 316ra193-316ra193
- ISSN
- 1946-6234 (ISSN-L)
- 1946-6242
- OpenAlex
- W2188526593
- Cited by
- 426
- References
- 43
- FWCI
- 24.44
- Type
- journal article
- Language
- en
- Open access
- green
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: Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. https://app.cochat.ai/papers/10.1126/scitranslmed.aac7071
- The paper
- Ju, W., Nair, V., Smith, S., Zhu, L., Shedden, K., Song, P. X. K., Mariani, L. H., Eichinger, F. H., Berthier, C. C., Randolph, A., Lai, J. Y.-C., Zhou, Y., Hawkins, J. J., Bitzer, M., Sampson, M. G., Thier, M., Solier, C., Duran-Pacheco, G. C., Duchateau-Nguyen, G., . . . for the ERCB, C.-P. (2015). Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. Science Translational Medicine. https://doi.org/10.1126/scitranslmed.aac7071
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.
