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Adiponectin receptor (ADIPOR1) signaling ameliorates obesity‐dependent cell cycle entry in MCF7 cells

2013· article· en· W262713318 on OpenAlexaff
Michael K. Connor, Christopher F. Theriau

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsYork University
Fundersnot available
KeywordsAdiponectin receptor 1AdipokineAdiponectinEndocrinologyInternal medicineLeptinAdipose tissueParacrine signallingAMPKReceptorBiologyChemistryCell biologyMedicineObesityInsulin resistanceProtein kinase A

Abstract

fetched live from OpenAlex

Adipose tissue produces and secretes hormones, termed adipokines, that have endocrine/paracrine effects on a wide variety of tissues. Two of these adipokines (adiponectin and leptin) have cell cycle effects on breast cancer cells and may underlie the molecular link between obesity and breast cancer. Adiponectin (ADIPO) and leptin (LEP) stoichiometrically antagonize each other in MCF7 cells. Stable 2.6‐fold over expression of ADIPOR1 inhibited LEP‐dependent antagonism of ADIPO in MCF7 cells. This effect of ADIPOR1 was also evident in MCF7 cells exposed to media conditioned by adipocytes from high fat diet fed animals (HFD‐CM). HFD‐CM inhibited AMPK, activated AKT, reduced p27 and ADIPOR1 protein levels in MCF7 cells compared to MCF7 cells exposed to CM from chow diet‐fed animals (CD‐CM). Stable overexpression prevented these HFD‐CM effects suggesting that maintenance of ADIPOR1 signaling may prevent obesity‐dependent breast cancer progression.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicAdipokines, Inflammation, and Metabolic Diseases→French-language works237,207→