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Modification of the Adiponectin:Leptin Ratio May Underlie Obesity Dependent Prostate Cancer Progression

2010· article· en· W2299896665 on OpenAlexaff
Jordan Zeppieri, Michael K. Connor

Bibliographic record

VenueThe FASEB Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsYork University
Fundersnot available
KeywordsAdiponectinLNCaPProstate cancerAMPKEndocrinologyInternal medicineLeptinAdiponectin receptor 1Paracrine signallingProstateCancer researchBiologyMedicineCancerReceptorObesityPhosphorylationCell biologyInsulin resistanceProtein kinase A

Abstract

fetched live from OpenAlex

Obesity and prostate cancer exhibit a statistical link, which may be due to the paracrine/endocrine cell cycle effects of the adipocyte‐derived peptides leptin (LEP) and adiponectin (ADIPO). ADIPO induced AMPK–dependent phosphorylation of p27 on T198 (T198‐P) and increased total p27 protein and adiponectin receptor (ADIPOR1) protein levels in androgen‐receptor (AR) negative PC3 prostate cancer cells. Conversely, LEP induced the opposite effects on AMPK, T198‐P p27, total p27 and ADIPOR1 protein levels. LEP and ADIPO also had opposing effects in AR‐positive LNCaP cells. As observed in breast cancer cells, LEP treatment overcame the effects of ADIPO on all proteins examined in a concentration‐dependent manner. Furthermore, ADIPO administration was able to counteract the effects of LEP on all proteins measured. Our data suggest that ADIPO and LEP exert antagonistic effects on prostate epithelial cell cycle regulation, and modification of the ADIPO:LEP ratio may be one of the important factors that underlie the molecular link between obesity and prostate 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.302
Teacher spread0.280 · 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
Published2010
Admission routes1
Has abstractyes

Explore more

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