Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,005

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Chelation in Metal Intoxication

Open access
Flora, Swaran J.S., Pachauri, Vidhu·2010·International Journal of Environmental Research and Public Health

Abstract

Chelation therapy is the preferred medical treatment for reducing the toxic effects of metals. Chelating agents are capable of binding to toxic metal ions to form complex structures which are easily excreted from the body removing them from intracellular or extracellular spaces. 2,3-Dimercaprol has long been the mainstay of chelation therapy for lead or arsenic poisoning, however its serious side effects have led researchers to develop less toxic analogues. Hydrophilic chelators like meso-2,3-dimercaptosuccinic acid effectively promote renal metal excretion, but their ability to access intracellular metals is weak. Newer strategies to address these drawbacks like combination therapy (use of structurally different chelating agents) or co-administration of antioxidants have been reported recently. In this review we provide an update of the existing chelating agents and the various strategies available for the treatment of heavy metals and metalloid intoxications.

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 · 10.3390/ijerph7072745

Cites

4 of 4 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 4 references

Cited by

See all 1,005

Metadata

Authors
Flora, S. J. S., & Pachauri, V.
Venue
International Journal of Environmental Research and Public Health
Publisher
MDPI AG
Published
2010-06-28
Volume
7
Issue
7
Pages
2745-2788
ISSN
1660-4601 (ISSN-L)
OpenAlex
W2166447472
Cited by
1,005
References
4
FWCI
16.25
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: Chelation in Metal Intoxication. https://app.cochat.ai/papers/10.3390/ijerph7072745
The paper
Flora, S. J. S., & Pachauri, V. (2010). Chelation in Metal Intoxication. International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph7072745

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.