Mechanism of Collagen Activation in Human Platelets
Bibliographic record
Abstract
The mechanism of collagen-induced human platelet activation was examined using Ca2+, Na+, and the pH-sensitive fluorescent dyes calcium green/fura red, sodium-binding benzofuran isophthalate, and 2',7'-bis(2-carboxyethyl)-5(6)-carboxyfluorescein. Administration of a moderate dose of collagen (10 microg/ml) to human platelets resulted in an increase in [Ca2+](i) and platelet aggregation. The majority of this increase in [Ca2+](i) resulted from the influx of calcium from the extracellular milieu via the Na+/Ca2+ exchanger (NCX) functioning in the reverse mode and was reduced in a dose-dependent manner by the NCX inhibitors 5-(4-chlorobenzyl)-2',4'-dimethylbenzamil (KD(50) = 4.7 +/- 1.1 microm) and KB-R7943 (KD(50) = 35.1 +/- 4.8 microm). Collagen-induced platelet aggregation was dependent on an increase in [Ca2+](i) and could be inhibited by chelation of intra- and extracellular calcium through the administration of 1,2-bis(2-aminophenoxy)ethane-N,N,N',N'-tetraacetic acid tetrakis(acetoxymethyl ester) (BAPTA-AM) and EGTA, respectively, or via the administration of BAPTA-AM to platelets suspended in no-Na+/HEPES buffer. Collagen induced an increase in [Ca2+](i) (23.2 +/- 7.6 mm) via the actions of thromboxane A(2) and, to a lesser extent, of the Na+/H+ exchanger. This study demonstrates that the collagen-induced increase in [Ca2+](i) is dependent on the concentration of Na+ in the extracellular milieu, indicating that the collagen-induced increase in [Ca2+](i) causes the reversal of the NCX, ultimately resulting in an increase in [Ca2+](i) and platelet aggregation.
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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) | 0.001 | 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".