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Record W1975795367 · doi:10.1515/bc.2010.038

Kallikrein-related peptidases: proteolysis and signaling in cancer, the new frontier

2010· review· en· W1975795367 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiological Chemistry · 2010
Typereview
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsKallikreinProteolysisProtease-activated receptorCell biologyReceptorProteasesSignal transductionProteomicsBiologyChemistryInflammationCell growthBiochemistryEnzymeImmunologyPlateletThrombin

Abstract

fetched live from OpenAlex

The exact mechanism(s) by which kallikrein-related peptidases (KLKs) function, their levels of activity and their potential endogenous targets in vivo have only recently begun to be revealed. Our group and others have shown that KLKs can have hormonal properties by signaling via proteinase-activated receptors (PARs), a family of G-protein-coupled receptors. Signals by PAR(1), PAR(2), and PAR(4) can regulate calcium release or mitogen-activated protein kinase activation and lead to platelet aggregation, vascular relaxation, cell proliferation, cytokine release, and inflammation. We have further documented the presence of active KLK6 and 10 (by activity-based ELISA or proteomics) and the presence of proteinase inhibitors, such as alpha(1)-antitrypsin, in cancer-derived fluids. We suggest that tumors and inflamed tissues can release active KLKs, which are under tight regulation by proteinase inhibitors. These enzymes can potentially control cell/tissue behavior by regulating PAR activation in specific settings and disease stages.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.056
GPT teacher head0.331
Teacher spread0.275 · 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