Single oral dose study of two isosorbide-based aspirin prodrugs in the dog
Bibliographic record
Abstract
The objective of this study was to compare two aspirin prodrugs, isosorbide diaspirinate (ISDA) and a nitroaspirin (ISMNA), with aspirin in terms of effects on dog platelet function after administration of a single oral dose. Groups of six dogs were administered ISDA (2mg kg(-1)), ISMNA (4 mg kg(-1)) or aspirin (2mg kg(-1)). Blood was sampled at 1, 2, 4, 8, 12 and 24 h post-dosing and evaluated for capacity to generate post-clotting thromboxane (TX)B2. The aggregation response to arachidonic acid (AA) (100 microM), ADP (30 microM) or collagen (10 microg mL(-1)) was estimated at each time-point using the whole blood impedance method. Plasma ISMN following oral administration of ISMNA was also measured and compared with plasma ISMN following administration of a physical mixture of ISMN and aspirin. ISDA administration (2 mg kg(-1)) was associated with a significant reduction (P < 0.05) in serum TXB2 at 12 and 24 h (>90%) post-dosing and persistent inhibition of AA-induced platelet aggregation. ISDA administration caused a more marked depression of post-clotting TXB2 levels than aspirin in this study, although its ability to inhibit platelet aggregation was less consistent than that of aspirin. The nitroaspirin ISMNA was least effective at inhibiting platelet aggregation response or TXB2 production. The ISMN AUC(0-24 h) for the ISMNA-treated dogs was 77% of that for the physical mix-treated dogs and the tmax was delayed. This study indicates that the two aspirin esters cause aspirin-like effects on platelet function, probably through aspirin release, when administered orally to dogs.
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 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) | 0.001 | 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 | 0.001 |
| 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".