Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 781

The DOI matches its Crossref record; 364 of the 364 references it cites were found in a registry or an index.

Kidney fibrosis: from mechanisms to therapeutic medicines

Open access
Huang, Rongshuang, Fu, Ping, Ma, Liang·2023·Signal Transduction and Targeted Therapy

Abstract

Chronic kidney disease (CKD) is estimated to affect 10–14% of global population. Kidney fibrosis, characterized by excessive extracellular matrix deposition leading to scarring, is a hallmark manifestation in different progressive CKD; However, at present no antifibrotic therapies against CKD exist. Kidney fibrosis is identified by tubule atrophy, interstitial chronic inflammation and fibrogenesis, glomerulosclerosis, and vascular rarefaction. Fibrotic niche, where organ fibrosis initiates, is a complex interplay between injured parenchyma (like tubular cells) and multiple non-parenchymal cell lineages (immune and mesenchymal cells) located spatially within scarring areas. Although the mechanisms of kidney fibrosis are complicated due to the kinds of cells involved, with the help of single-cell technology, many key questions have been explored, such as what kind of renal tubules are profibrotic, where myofibroblasts originate, which immune cells are involved, and how cells communicate with each other. In addition, genetics and epigenetics are deeper mechanisms that regulate kidney fibrosis. And the reversible nature of epigenetic changes including DNA methylation, RNA interference, and chromatin remodeling, gives an opportunity to stop or reverse kidney fibrosis by therapeutic strategies. More marketed (e.g., RAS blockage, SGLT2 inhibitors) have been developed to delay CKD progression in recent years. Furthermore, a better understanding of renal fibrosis is also favored to discover biomarkers of fibrotic injury. In the review, we update recent advances in the mechanism of renal fibrosis and summarize novel biomarkers and antifibrotic treatment for 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.

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

Integrity signals

Registry

Crossref · 10.1038/s41392-023-01379-7

Cites

364 of 364 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 364 references

Cited by

See all 781

Metadata

Authors
Huang, R., Fu, P., & Ma, L.
Venue
Signal Transduction and Targeted Therapy
Published
2023-03-17
Volume
8
Issue
1
Pages
129-129
ISSN
2059-3635 (ISSN-L)
OpenAlex
W4327811820
Cited by
781
References
364
FWCI
129.26
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: Kidney fibrosis: from mechanisms to therapeutic medicines. https://app.cochat.ai/papers/10.1038/s41392-023-01379-7
The paper
Huang, R., Fu, P., & Ma, L. (2023). Kidney fibrosis: from mechanisms to therapeutic medicines. Signal Transduction and Targeted Therapy. https://doi.org/10.1038/s41392-023-01379-7

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.