Evidence map›Paper›PMID 40581369›Full record

ReviewJournal of biochemistry2025

Transcriptional control of brown adipocyte differentiation and function by NFIA: recent perspectives on deciphering metabolic diseases.

Yuta Hiraike

Abstract readReview
In one paragraph

Review in Journal of biochemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Yuta HiraikeLaboratory for Advanced Research on Pathophysiology of Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.

Funding

a grant for front runner of future diabetes research (FFDR) from the Japan Foundation for Applied Enzymology 17F005a grant from MSD Life Science Foundation; a life science research grant from Takeda Science Foundationa Kishimoto research grant from Senri Life Science Foundationa life science research grant from the Mitsubishi Foundationan Inamori research grant from the Inamori Foundationa Samuro Kakiuchi memorial research award for young scientists from the Japanese Biochemical Society; by a grant from Lotte FoundationJapan Agency for Medical Research and Development (AMED) 25ek0210204h0002Japan Society for the Promotion of Science (JSPS) KAKENHI grant-in-aid for scientific research (B) 25K03025
6 · The paper itself

Abstract

Brown adipocytes dissipate chemical energy as heat and confer protection against type 2 diabetes and obesity. Nuclear factor I-A (NFIA) is a transcription factor that orchestrates the brown fat gene programme by activating cell type-specific enhancers and facilitating the genomic binding of PPARγ, the master regulator of adipogenesis, to these enhancers. NFIA promotes mitochondrial oxidative phosphorylation and thermogenesis, while reciprocally suppressing adipose tissue inflammation, thereby contributing to the maintenance of glucose and body weight homeostasis in mice. Here the author provides an overview of the identification of NFIA as a pivotal regulator of brown adipocyte biology, elucidates its underlying mechanisms of action, examines its implications for systemic metabolism and outlines future perspectives for research in this field.

Indexed as

Adipocytes, BrownCell DifferentiationMetabolic DiseasesNFI Transcription FactorsTranscription, GeneticAdipogenesisAdipose Tissue, BrownAnimalsHumansThermogenesisNFI Transcription Factorsadipose tissue inflammationbrown adipocytesdiabetesobesitytranscriptional regulation

Identifiers

PMID40581369
PMCPMC12372464

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.