Endothelial protein C receptor–dependent antichemotactic effects of canine protein C
Bibliographic record
Abstract
OBJECTIVE To determine whether canine protein C (CnPC) had antichemotactic effects on canine neutrophils, whether endothelial protein C receptor (EPCR) was expressed on canine neutrophils, and the role of EPCR in neutrophil chemotaxis. SAMPLE Neutrophils isolated from blood samples from healthy dogs (n = 6) and sick dogs with (2) or without (3) an inflammatory leukogram. PROCEDURES Neutrophils were analyzed by reverse transcriptase PCR assay and flow cytometry for detection of EPCR mRNA and protein expression, respectively. Neutrophils were incubated with CnPC zymogen or canine activated protein C (CnAPC), with or without RCR-379 (an anti-human EPCR antibody). Neutrophils were then allowed to migrate through a filter membrane toward a chemokine. Untreated neutrophils served as positive control samples. Migration was quantified by fluorescence measurement, and chemotaxis index (Chx) values (fluorescence of test sample/fluorescence of positive control sample) were computed. RESULTS The cDNA for EPCR was amplified, and EPCR expression was detected on neutrophil surfaces. Obtained Chx values were significantly higher in cells treated with RCR-379 than in cells treated with CnPC or CnAPC alone. The Chx values for neutrophils treated with RCR-379 were not significantly different from 1, whereas those for neutrophils treated without RCR-379 were significantly less than 1. The effects of RCR-379 on neutrophil migration were independent of concentration or activation status of protein C. CONCLUSIONS AND CLINICAL RELEVANCE Canine neutrophils expressed EPCR, and inhibition of neutrophil chemotaxis by CnPC and CnAPC depended on EPCR. Interventions with EPCR signaling may have therapeutic application in dogs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".