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Record W2111419555 · doi:10.1152/ajpendo.00125.2005

Leptin-mediated activation of human platelets: involvement of a leptin receptor and phosphodiesterase 3A-containing cellular signaling complex

2005· article· en· W2111419555 on OpenAlexaff
Hisham S. Elbatarny, Donald H. Maurice

Bibliographic record

VenueAmerican Journal of Physiology-Endocrinology and Metabolism · 2005
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsQueen's University
Fundersnot available
KeywordsLeptinLeptin receptorPlatelet activationJanus kinase 2Internal medicineEndocrinologyProtein kinase BPlateletSignal transductionPI3K/AKT/mTOR pathwayPhosphodiesteraseReceptorChemistryBiologyCell biologyMedicineBiochemistryEnzymeObesity

Abstract

fetched live from OpenAlex

An elevated circulating level of the adipocyte-derived satiety hormone leptin is an independent risk factor for cardiovascular disease. Because thrombus formation is a major cause of acute coronary events and leptin was shown previously to facilitate ADP-induced platelet aggregation, we chose to define the signaling events involved in leptin-mediated platelet activation. Using pharmacological, biochemical, and cell biological approaches, we show that leptin-induced platelet activation required activation of a signaling cascade that included the long form of the leptin receptor, three kinases [Janus kinase 2 (JAK2), phosphatidylinositol 3-kinase (PI3K), and protein kinase B (PKB/Akt)], the insulin receptor substrate-1 (IRS-1), and the major human platelet cAMP phosphodiesterase phosphodiesterase 3A (PDE3A). Moreover, we identify a role for an intraplatelet LEPR/JAK2/IRS-1/PI3K/PKB/PDE3A molecular complex that allows for the selective leptin-mediated activation of platelets. Our data demonstrate that leptin promotes platelet activation, provides a mechanistic basis for the prothrombotic effect of this hormone, and identifies a potentially novel therapeutic avenue to limit obesity-associated cardiovascular disease.

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 score0.042
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.266
Teacher spread0.240 · 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

Citations76
Published2005
Admission routes1
Has abstractyes

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