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Record W2782389490 · doi:10.1038/s41598-017-18529-x

MicroRNA-7 mediates cross-talk between metabolic signaling pathways in the liver

2018· article· en· W2782389490 on OpenAlexafffund
Ragunath Singaravelu, Curtis Quan, Megan H. Powdrill, Tyler A. Shaw, Prashanth Srinivasan, Rodney K. Lyn, Rhea C. Alonzi, Daniel M. Jones, Roxana Filip, Rodney S. Russell, John Paul Pezacki

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsMemorial University of NewfoundlandUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsOxysterolSterol regulatory element-binding proteinmicroRNARegulatorLiver X receptorCell biologySignal transductionBiologyNuclear receptorLipid metabolismPeroxisome proliferator-activated receptorLiver receptor homolog-1ReceptorSterolTranscription factorBiochemistryCholesterolGene

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) have emerged as critical regulators of cellular metabolism. To characterise miRNAs crucial to the maintenance of hepatic lipid homeostasis, we examined the overlap between the miRNA signature associated with inhibition of peroxisome proliferator activated receptor-α (PPAR-α) signaling, a pathway regulating fatty acid metabolism, and the miRNA profile associated with 25-hydroxycholesterol treatment, an oxysterol regulator of sterol regulatory element binding protein (SREBP) and liver X receptor (LXR) signaling. Using this strategy, we identified microRNA-7 (miR-7) as a PPAR-α regulated miRNA, which activates SREBP signaling and promotes hepatocellular lipid accumulation. This is mediated, in part, by suppression of the negative regulator of SREBP signaling: ERLIN2. miR-7 also regulates genes associated with PPAR signaling and sterol metabolism, including liver X receptor β (LXR-β), a transcriptional regulator of sterol synthesis, efflux, and excretion. Collectively, our findings highlight miR-7 as a novel mediator of cross-talk between PPAR, SREBP, and LXR signaling pathways in the liver.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.035
GPT teacher head0.289
Teacher spread0.254 · 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 designObservational
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

Citations39
Published2018
Admission routes2
Has abstractyes

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