The DOI matches its Crossref record; 95 of the 95 references it cites were found in a registry or an index.
Molecular characterization of the transition from acute to chronic kidney injury following ischemia/reperfusion
Open accessAbstract
Though an acute kidney injury (AKI) episode is associated with an increased risk of chronic kidney disease (CKD), the mechanisms determining the transition from acute to irreversible chronic injury are not well understood. To extend our understanding of renal repair, and its limits, we performed a detailed molecular characterization of a murine ischemia/reperfusion injury (IRI) model for 12 months after injury. Together, the data comprising RNA-sequencing (RNA-seq) analysis at multiple time points, histological studies, and molecular and cellular characterization of targeted gene activity provide a comprehensive profile of injury, repair, and long-term maladaptive responses following IRI. Tubular atrophy, interstitial fibrosis, inflammation, and development of multiple renal cysts were major long-term outcomes of IRI. Progressive proximal tubular injury tracks with de novo activation of multiple Krt genes, including Krt20, a biomarker of renal tubule injury. RNA-seq analysis highlights a cascade of temporal-specific gene expression patterns related to tubular injury/repair, fibrosis, and innate and adaptive immunity. Intersection of these data with human kidney transplant expression profiles identified overlapping gene expression signatures correlating with different stages of the murine IRI response. The comprehensive characterization of incomplete recovery after ischemic AKI provides a valuable resource for determining the underlying pathophysiology of human CKD.
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
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
De Rosa, S., Samoni, S., Villa, G., & Ronco, C. (2017) · Blood Purification · doi:10.1159/000452650 · Cited by 5,007
Targeting the KEAP1-NRF2 system to prevent kidney disease progression
Nezu, M., Suzuki, N., & Yamamoto, M. (2017) · American Journal of Nephrology · doi:10.1159/000475890 · Cited by 3,447
Genomic responses in mouse models poorly mimic human inflammatory diseases
Seok, J., Warren, H. S., Cuenca, A. G., Mindrinos, M. N., Baker, H. V., Xu, W., Richards, D. R., McDonald-Smith, G. P., Gao, H., Hennessy, L., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1222878110 · Cited by 3,005
Chronic kidney disease after acute kidney injury: a systematic review and meta-analysis
Coca, S. G., Singanamala, S., & Parikh, C. R. (2012) · Kidney International · doi:10.1038/ki.2011.379 · Cited by 2,256
Acute Kidney Injury and Chronic Kidney Disease as Interconnected Syndromes
Chawla, L. S., Eggers, P. W., Star, R. A., & Kimmel, P. L. (2014) · New England Journal of Medicine · doi:10.1056/nejmra1214243 · Cited by 1,977
A census of human transcription factors: function, expression and evolution
Vaquerizas, J. M., Kummerfeld, S. K., Teichmann, S. A., & Luscombe, N. M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2538 · Cited by 1,573
Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury
Kashani, K., Al-Khafaji, A., Ardiles, T., Artigas, A., Bagshaw, S. M., Bell, M., Bihorac, A., Birkhahn, R., Cely, C. M., Chawla, L. S., et al. (2013) · Critical Care · doi:10.1186/cc12503 · Cited by 1,362
Cited by
Cell profiling of mouse acute kidney injury reveals conserved cellular responses to injury
Kirita, Y., Wu, H., Uchimura, K., Wilson, P. C., & Humphreys, B. D. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2005477117 · Cited by 650
Immune cells and inflammation in AKI to CKD progression
Sato, Y., & Yanagita, M. (2018) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00195.2018 · Cited by 273
GDF15: a hormone conveying somatic distress to the brain
Lockhart, S. M., Saudek, V., & O’Rahilly, S. (2020) · Endocrine Reviews · doi:10.1210/endrev/bnaa007 · Cited by 256
FOXM1 drives proximal tubule proliferation during repair from acute ischemic kidney injury
Chang-Panesso, M., Kadyrov, F. F., Lalli, M., Wu, H., Ikeda, S., Kefaloyianni, E., Abdelmageed, M. M., Herrlich, A., Kobayashi, A., & Humphreys, B. D. (2019) · Journal of Clinical Investigation · doi:10.1172/jci125519 · Cited by 158
Myofibroblast YAP/TAZ activation is a key step in organ fibrogenesis
He, X., Tolosa, M. F., Zhang, T., Goru, S. K., Ulloa Severino, L., Misra, P. S., McEvoy, C. M., Caldwell, L., Szeto, S. G., Gao, F., et al. (2022) · JCI Insight · doi:10.1172/jci.insight.146243 · Cited by 106
Metadata
- Authors
- Liu, J., Kumar, S., Dolzhenko, E., Alvarado, G. F., Guo, J., Lu, C., Chen, Y., Li, M., Dessing, M. C., Parvez, R. K., Cippà, P. E., Krautzberger, A. M., Saribekyan, G., Smith, A. D., & McMahon, A. P.
- Venue
- JCI Insight
- Published
- 2017-09-21
- Volume
- 2
- Issue
- 18
- ISSN
- 2379-3708 (ISSN-L)
- OpenAlex
- W2755721550
- Cited by
- 285
- References
- 95
- FWCI
- 14.25
- Type
- journal article
- Language
- en
- Open access
- gold
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: Molecular characterization of the transition from acute to chronic kidney injury following ischemia/reperfusion. https://app.cochat.ai/papers/10.1172/jci.insight.94716
- The paper
- Liu, J., Kumar, S., Dolzhenko, E., Alvarado, G. F., Guo, J., Lu, C., Chen, Y., Li, M., Dessing, M. C., Parvez, R. K., Cippà, P. E., Krautzberger, A. M., Saribekyan, G., Smith, A. D., & McMahon, A. P. (2017). Molecular characterization of the transition from acute to chronic kidney injury following ischemia/reperfusion. JCI Insight. https://doi.org/10.1172/jci.insight.94716
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.