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Record W2535036308 · doi:10.1016/j.celrep.2016.10.004

α/β-Hydrolase Domain 6 in the Ventromedial Hypothalamus Controls Energy Metabolism Flexibility

2016· article· en· W2535036308 on OpenAlexafffund
Alexandre Fisette, Stephanie W. Tobin, Léa Décarie-Spain, Khalil Bouyakdan, Marie‐Line Peyot, S.R. Murthy Madiraju, Marc Prentki, Stephanie Fulton, Thierry Alquier

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsEndocannabinoid systemMonoacylglycerol lipaseEndocrinologyInternal medicineBiologyEnergy homeostasisInsulin resistanceRegulatorObesityMedicineBiochemistryReceptor

Abstract

fetched live from OpenAlex

α/β-Hydrolase domain 6 (ABHD6) is a monoacylglycerol hydrolase that degrades the endocannabinoid 2-arachidonoylglycerol (2-AG). Although complete or peripheral ABHD6 loss of function is protective against diet-induced obesity and insulin resistance, the role of ABHD6 in the central control of energy balance is unknown. Using a viral-mediated knockout approach, targeted endocannabinoid measures, and pharmacology, we discovered that mice lacking ABHD6 from neurons of the ventromedial hypothalamus (VMH KO ) have higher VMH 2-AG levels in conditions of endocannabinoid recruitment and fail to physiologically adapt to key metabolic challenges. VMH KO mice exhibited blunted fasting-induced feeding and reduced food intake, energy expenditure, and adaptive thermogenesis in response to cold exposure, high-fat feeding, and dieting (transition to a low-fat diet). Our findings identify ABHD6 as a regulator of the counter-regulatory responses to major metabolic shifts, including fasting, nutrient excess, cold, and dieting, thereby highlighting the importance of ABHD6 in the VMH in mediating energy metabolism flexibility.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations37
Published2016
Admission routes2
Has abstractyes

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