Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 190

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Activation of invariant natural killer T cells by lipid excess promotes tissue inflammation, insulin resistance, and hepatic steatosis in obese mice

Open access
Wu, Lan, Parekh, Vrajesh V., Gabriel, Curtis L., Bracy, Deanna P., Marks-Shulman, Pamela A., Tamboli, Robyn A., Kim, Sungjune, Mendez-Fernandez, Yanice V., Besra, Gurdyal S., Lomenick, Jefferson P., Williams, Brandon, Wasserman, David H., Van Kaer, Luc·2012·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.1200498109
Open this paper in CoChat — free account

Abstract

Obesity triggers a low-grade systemic inflammation, which plays an important role in the development of obesity-associated metabolic diseases. In searching for links between lipid accumulation and chronic inflammation, we examined invariant natural killer T (iNKT) cells, a subset of T lymphocytes that react with lipids and regulate inflammatory responses. We show that iNKT cells respond to dietary lipid excess and become activated before or at the time of tissue recruitment of inflammatory leukocytes, and that these cells progressively increase proinflammatory cytokine production in obese mice. Such iNKT cells skew other leukocytes toward proinflammatory cytokine production and induce an imbalanced proinflammatory cytokine environment in multiple tissues. Further, iNKT cell deficiency ameliorates tissue inflammation and provides protection against obesity-induced insulin resistance and hepatic steatosis. Conversely, chronic iNKT cell stimulation using a canonical iNKT cell agonist exacerbates tissue inflammation and obesity-associated metabolic disease. These findings place iNKT cells into the complex network linking lipid excess to inflammation in obesity and suggest new therapeutic avenues for obesity-associated metabolic disorders.

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 · 10.1073/pnas.1200498109

Cites

13 of 13 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 13 references

Cited by

See all 190

Metadata

Authors
Wu, L., Parekh, V. V., Gabriel, C. L., Bracy, D. P., Marks-Shulman, P. A., Tamboli, R. A., Kim, S., Mendez-Fernandez, Y. V., Besra, G. S., Lomenick, J. P., Williams, B., Wasserman, D. H., & Van Kaer, L.
Venue
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Published
2012-04-09
Volume
109
Issue
19
Pages
E1143-52
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.1200498109
OpenAlex
W2038904723
Cited by
190
References
13
FWCI
13.57
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: Activation of invariant natural killer T cells by lipid excess promotes tissue inflammation, insulin resistance, and hepatic steatosis in obese mice. https://app.cochat.ai/papers/10.1073/pnas.1200498109
The paper
Wu, L., Parekh, V. V., Gabriel, C. L., Bracy, D. P., Marks-Shulman, P. A., Tamboli, R. A., Kim, S., Mendez-Fernandez, Y. V., Besra, G. S., Lomenick, J. P., Williams, B., Wasserman, D. H., & Van Kaer, L. (2012). Activation of invariant natural killer T cells by lipid excess promotes tissue inflammation, insulin resistance, and hepatic steatosis in obese mice. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1200498109

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.