MétaCan
Menu
Back to cohort
Record W2606334150 · doi:10.1007/s11745-017-4251-4

Acute Fasting Induces Expression of Acylglycerophosphate Acyltransferase (AGPAT) Enzymes in Murine Liver, Heart, and Brain

2017· article· en· W2606334150 on OpenAlexafffund
Ryan M. Bradley, Emily B. Mardian, Katherine A. Moes, Robin E. Duncan

Bibliographic record

VenueLipids · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPhosphatidic acidLysophosphatidic acidAcyltransferasesAcyltransferaseLipidologyClinical chemistryInternal medicineEndocrinologyEnzymeNEFABiochemistryBiologyChemistryFatty acidPhospholipidBiosynthesisMedicine

Abstract

fetched live from OpenAlex

During fasting, cells increase uptake of non-esterified fatty acids (NEFA) and esterify excess into phosphatidic acid (PtdOH), the common precursor of both triacylglycerols and phospholipids, using acylglycerophosphate acyltransferases/lysophosphatidic acid acyltransferases (AGPAT/LPAAT). Knowledge of the regulation of AGPAT enzymes is important for understanding fasting adaptations. Total RNA was isolated from liver, heart, and whole brain tissue of C57BL/6J mice fed ad libitum, or fasted for 16 h. Following fasting, induction of Agpat2, 3, 4, and 5 was observed in the liver, Agpat2 and 3 in heart tissue, and Agpat1, 2, and 3 in whole brain tissue. As a result, the relative abundance profile of the individual homologues within specific tissues was found to be significantly altered depending on the nutritive state of the animal. These data demonstrate tissue-specific effects of fasting on the regulation of different Agpat that are implicated in supporting unique downstream glycerolipid synthesis pathways.

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 categoriesnone
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 score0.040
Threshold uncertainty score0.527

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)0.0000.000

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 head0.011
GPT teacher head0.253
Teacher spread0.241 · 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 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

Citations12
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueLipidsSame topicLipid metabolism and biosynthesisFrench-language works237,207