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Record W2065715836 · doi:10.1002/ddr.10302

Proteinase‐activated receptor domains and signaling

2003· article· en· W2065715836 on OpenAlexafffund
Morley D. Hollenberg, Steven J. Compton

Bibliographic record

VenueDrug Development Research · 2003
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchServierKidney Foundation of Canada
KeywordsG protein-coupled receptorSignal transductionCell biologyReceptorBiologyExtracellularIntracellularPalmitoylationPhosphorylation5-HT5A receptorG proteinG protein-coupled receptor kinaseEnzyme-linked receptorProtease-activated receptorBiochemistryImmunologyEnzyme

Abstract

fetched live from OpenAlex

Abstract Given that the proteinase‐activated receptors (PARs) are activated by a “tethered ligand mechanism,” an important question to answer is: Which other extracellular domains of the receptors are involved in this novel signaling mechanism? Further, as for other G‐protein‐coupled receptors (GPCRs), it is of importance to know about the intracellular receptor domains that are involved in coupling receptor activation to signal transduction. Studies summarized in this article have singled out the importance of extracellular loop‐2 of PAR 1 and PAR 2 for tethered‐ligand signaling. In human PAR 1 , but not in PAR 2 , a short sequence in the extracellular N‐terminal domain (Q 83 to G 94 ) is also important for receptor activation. As for other GPCRs, intracellular loops 2 and 3 mediate receptor‐G‐protein coupling, and the C‐terminal sequence, with a putative “palmitoylation” site and target residues for kinase C phosphorylation, plays a role in receptor signaling and desensitization. This article provides an overview of the experiments leading to the current understanding of the PAR domains involved in signal transduction. Drug Dev. Res. 59:344–349, 2003. © 2003 Wiley‐Liss, Inc.

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)0.002
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 score0.061
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.073
GPT teacher head0.351
Teacher spread0.278 · 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

Citations4
Published2003
Admission routes2
Has abstractyes

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