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Record W2166052896 · doi:10.1002/jcb.10686

Sphingosine 1‐phosphate effect on endothelial cell PAF synthesis: Role in cellular migration

2003· article· en· W2166052896 on OpenAlexaff
Pascal Bernatchez, François Tremblay, Simon Rollin, Paul‐Eduard Neagoe, Martin G. Sirois

Bibliographic record

VenueJournal of Cellular Biochemistry · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsSphingosine-1-phosphateCell biologySphingosineChemistryPhosphateEndothelial stem cellCell migrationCellBiophysicsBiochemistryBiologyReceptorIn vitro

Abstract

fetched live from OpenAlex

Sphingosine 1-phosphate (S1P) and vascular endothelial growth factor (VEGF) are two inflammatory mediators capable of promoting endothelial cell (EC) migration and angiogenesis. As VEGF inflammatory effect is mediated by the synthesis of endothelial platelet-activating factor (PAF) which is also contributing to VEGF chemotactic activity, we wanted to assess if S1P can trigger PAF synthesis in EC and if S1P-induced migration is PAF-dependent. Treatment of bovine aortic EC (BAEC) with S1P (10(-10)-10(-6) M) increased dose- and time-dependently the synthesis of PAF by up to 3.3-fold above the basal level, with a maximal amount of PAF detected at 20 min post-stimulation. This biological response was attenuated by inhibiting p38 mitogen-activated protein kinase (MAPK), cytosolic or secreted phospholipase A(2) (cPLA(2), sPLA(2)) activity, suggesting that p38 MAPK activation by S1P promotes the conversion of membrane phospholipids into PAF through the combined activation of cPLA(2) and sPLA(2). Interestingly, pretreatment of BAEC with extracellular PAF receptor antagonists (BN52021, 10(-5) M and CV3988, 10(-6) M) reduced by up to 42% the cellular migration induced by S1P (10(-6) M). These data demonstrate the capacity of S1P to induce PAF synthesis, which contributes in part to S1P chemotactic activity.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.003
GPT teacher head0.196
Teacher spread0.192 · 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.

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

Citations23
Published2003
Admission routes1
Has abstractyes

Explore more

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