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Record W2037819215 · doi:10.1254/jphs.fmj04005x2

Physiology and Pathophysiology of Proteinase-Activated Receptors (PARs): Proteinases as Hormone-Like Signal Messengers: PARs and More

2005· review· en· W2037819215 on OpenAlexafffund
Morley D. Hollenberg

Bibliographic record

VenueJournal of Pharmacological Sciences · 2005
Typereview
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsUniversity of CalgaryCanadian Institutes of Health Research
FundersCanadian Institutes of Health ResearchServierHeart and Stroke Foundation of Canada
KeywordsReceptorCell biologySignal transductionThrombinBiologyProtease-activated receptorG protein-coupled receptorBiochemistryImmunology

Abstract

fetched live from OpenAlex

Proteinases like thrombin and trypsin, long known for their ability to activate the coagulation cascade or to act as digestive enzymes for many protein targets, are now recognized as hormone-like regulators of cell function. These serine proteinases activate cell signaling by triggering a novel family of G-protein-coupled receptors, termed proteinase-activated receptors (PARs). This article summarizes the unique mechanisms involved in PAR activation and outlines the many different settings in which the PARs act to regulate tissue function. The PARs can be seen to play a role in inflammatory processes in large part via a neurogenic mechanism. Apart from activating PARs to cause their physiological effects in tissues, proteinases can also mediate cell signaling via a number of other mechanisms, including the activation of growth factor receptors, like the one for insulin. Thus, this article also points out the non-PAR mechanisms whereby proteinases can have hormone-like actions in cells and tissues.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.817
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.090
GPT teacher head0.399
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations37
Published2005
Admission routes2
Has abstractyes

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