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Record W2314477290 · doi:10.4161/adip.28308

Cross-tissue comparisons of leptin and adiponectin

2014· article· en· W2314477290 on OpenAlex
Andrée-Anne Houde, Cécilia Légaré, Frédéric‐Simon Hould, Stéfane Lebel, Picard Marceau, André Tchernof, Marie‐Claude Vohl, Marie‐France Hivert, Luigi Bouchard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdipocyte · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité LavalCentre hospitalier universitaire de QuébecUniversité du QuébecAluminium Refining, Degassing and Filtering (Canada)Institut universitaire de cardiologie et de pneumologie de QuébecCégep de ChicoutimiUniversité de Sherbrooke
Fundersnot available
KeywordsAdipose tissueDNA methylationAdiponectinEpigeneticsLeptinBiologyMethylationGeneDNAGene expressionAdipokineEndocrinologyInternal medicineGeneticsMedicineObesityInsulin resistance

Abstract

fetched live from OpenAlex

DNA methylation has been mostly studied in circulating blood cells. Although being readily accessible, metabolically active tissues such as adipose tissue would be more informative for the study of metabolic disorders. However, whether or not the blood DNA methylation profile correlates with that of adipose tissue remains unknown. In this study, DNA methylation patterns of variation at LEP and ADIPOQ gene loci were similar between individual CpGs across the different tissues. We also report that DNA methylation levels at biologically relevant CpGs are correlated between blood, subcutaneous, and visceral adipose tissue, and that these nearby CpGs are associated with LEP and ADIPOQ gene expression in adipose tissues. These results will be highly relevant for future epigenetic studies in metabolic disorders.

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.

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 score0.163
Threshold uncertainty score0.323

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 head0.288
Teacher spread0.277 · 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