Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 322

The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.

Recent progress in ferroptosis: inducers and inhibitors

Open access
Du, Yunxi, Guo, Zhong·2022·Cell Death Discovery

Abstract

Ferroptosis is a new iron-dependent form of programmed cell death characterized by iron accumulation and lipid peroxidation. In recent years, ferroptosis has garnered enormous interest in disease treatment research communities in pursuit to reveal the mechanism and key targets of ferroptosis because ferroptosis is closely related to the pathophysiological processes of many diseases. Recent studies have shown some key targets, such as glutathione peroxidase 4 (GPX4) and System Xc−, and several inducers and inhibitors have been developed to regulate these key targets. With the emergence of new ferroptosis targets, studies on inducers and inhibitors have made new developments. The selection and use of inducers and inhibitors are very important for related work. This paper briefly introduces important regulatory targets in the ferroptosis metabolic pathway, lists and categorizes commonly used and recently developed inducers and inhibitors, and discusses their medical application. The paper ends of with potential future research direction for ferroptosis.

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/s41420-022-01297-7

Cites

112 of 112 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 112 references

Cited by

See all 322

Metadata

Authors
Du, Y., & Guo, Z.
Venue
Cell Death Discovery
Published
2022-12-29
Volume
8
Issue
1
Pages
501-501
ISSN
2058-7716 (ISSN-L)
OpenAlex
W4313333110
Cited by
322
References
112
FWCI
38.90
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: Recent progress in ferroptosis: inducers and inhibitors. https://app.cochat.ai/papers/10.1038/s41420-022-01297-7
The paper
Du, Y., & Guo, Z. (2022). Recent progress in ferroptosis: inducers and inhibitors. Cell Death Discovery. https://doi.org/10.1038/s41420-022-01297-7

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.