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Record W3000468850 · doi:10.3390/cells9010168

Disruption of Beta-Cell Mitochondrial Networks by the Orphan Nuclear Receptor Nor1/Nr4a3

2020· article· en· W3000468850 on OpenAlexafffund
Anne-Françoise Close, Nidheesh Dadheech, Hélène Lemieux, Qian Wang, Jean Buteau

Bibliographic record

VenueCells · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta Diabetes Foundation
KeywordsBeta cellGlucose homeostasisBiologyCell biologyMitochondrionEndocrinologyInternal medicineInsulinIsletInsulin resistanceMedicine

Abstract

fetched live from OpenAlex

Nor1, the third member of the Nr4a subfamily of nuclear receptor, is garnering increased interest in view of its role in the regulation of glucose homeostasis. Our previous study highlighted a proapoptotic role of Nor1 in pancreatic beta cells and showed that Nor1 expression was increased in islets isolated from type 2 diabetic individuals, suggesting that Nor1 could mediate the deterioration of islet function in type 2 diabetes. However, the mechanism remains incompletely understood. We herein investigated the subcellular localization of Nor1 in INS832/13 cells and dispersed human beta cells. We also examined the consequences of Nor1 overexpression on mitochondrial function and morphology. Our results show that, surprisingly, Nor1 is mostly cytoplasmic in beta cells and undergoes mitochondrial translocation upon activation by proinflammatory cytokines. Mitochondrial localization of Nor1 reduced glucose oxidation, lowered ATP production rates, and inhibited glucose-stimulated insulin secretion. Western blot and microscopy images revealed that Nor1 could provoke mitochondrial fragmentation via mitophagy. Our study unveils a new mode of action for Nor1, which affects beta-cell viability and function by disrupting mitochondrial networks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.215
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2020
Admission routes2
Has abstractyes

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