The Effects of Cyclosporine and Aspirin on Platelet Function in Normal Dogs
Bibliographic record
Abstract
BACKGROUND: Cyclosporine increases thromboxane synthesis in dogs, potentially increasing the thrombogenic properties of platelets. HYPOTHESIS/OBJECTIVES: Our hypothesis was that the concurrent administration of low-dose aspirin and cyclosporine would inhibit cyclosporine-associated thromboxane synthesis without altering the antiplatelet effects of aspirin. The objective was to determine the effects of cyclosporine and aspirin on primary hemostasis. ANIMALS: Seven healthy dogs. METHODS: A randomized, crossover study utilized turbidimetric aggregometry and a platelet function analyzer to evaluate platelet function during the administration of low-dose aspirin (1 mg/kg PO q24h), high-dose aspirin (10 mg/kg PO q12h), cyclosporine (10 mg/kg PO q12h), and combined low-dose aspirin and cyclosporine. The urine 11-dehydro-thromboxane-B2 (11-dTXB2 )-to-creatinine ratio also was determined. RESULTS: On days 3 and 7 of administration, there was no difference in the aggregometry amplitude or the platelet function analyzer closure time between the low-dose aspirin group and the combined low-dose aspirin and cyclosporine group. On day 7, there was a significant difference in amplitude and closure time between the cyclosporine group and the combined low-dose aspirin and cyclosporine group. High-dose aspirin consistently inhibited platelet function. On both days, there was a significant difference in the urinary 11-dTXB2 -to-creatinine ratio between the cyclosporine group and the combined low-dose aspirin and cyclosporine group. There was no difference in the urinary 11-dTXB2 -to-creatinine ratio among the low-dose aspirin, high-dose aspirin, and combined low-dose aspirin and cyclosporine groups. CONCLUSIONS AND CLINICAL IMPORTANCE: Low-dose aspirin inhibits cyclosporine-induced thromboxane synthesis, and concurrent use of these medications does not alter the antiplatelet effects of aspirin.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".