Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,018

The DOI matches its Crossref record; 368 of the 368 references it cites were found in a registry or an index.

Free Fatty Acid Receptors in Health and Disease

Open access
Kimura, Ikuo, Ichimura, Atsuhiko, Ohue-Kitano, Ryuji, Igarashi, Miki·2020·Physiological Reviews

Abstract

Fatty acids are metabolized and synthesized as energy substrates during biological responses. Long- and medium-chain fatty acids derived mainly from dietary triglycerides, and short-chain fatty acids (SCFAs) produced by gut microbial fermentation of the otherwise indigestible dietary fiber, constitute the major sources of free fatty acids (FFAs) in the metabolic network. Recently, increasing evidence indicates that FFAs serve not only as energy sources but also as natural ligands for a group of orphan G protein-coupled receptors (GPCRs) termed free fatty acid receptors (FFARs), essentially intertwining metabolism and immunity in multiple ways, such as via inflammation regulation and secretion of peptide hormones. To date, several FFARs that are activated by the FFAs of various chain lengths have been identified and characterized. In particular, FFAR1 (GPR40) and FFAR4 (GPR120) are activated by long-chain saturated and unsaturated fatty acids, while FFAR3 (GPR41) and FFAR2 (GPR43) are activated by SCFAs, mainly acetate, butyrate, and propionate. In this review, we discuss the recent reports on the key physiological functions of the FFAR-mediated signaling transduction pathways in the regulation of metabolism and immune responses. We also attempt to reveal future research opportunities for developing therapeutics for metabolic and immune 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 · 10.1152/physrev.00041.2018

Cites

368 of 368 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

Items 201–368 of 368

Cited by

See all 1,018

Metadata

Authors
Kimura, I., Ichimura, A., Ohue-Kitano, R., & Igarashi, M.
Venue
Physiological Reviews
Published
2020-01-01
Volume
100
Issue
1
Pages
171-210
ISSN
  • 0031-9333 (ISSN-L)
  • 1522-1210
OpenAlex
W2971877727
Cited by
1,018
References
368
FWCI
5.50
Type
journal article
Language
en
Open access
hybrid

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

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.