Application of tail vein serial microsampling for plasma or dried plasma spots in toxicokinetic assessment in rats using acetaminophen as the model compound
Bibliographic record
Abstract
In the current study, two groups of rats (five per group) were administered a single oral dose of 500 mg/kg acetaminophen. For toxicokinetic assessment, the Group 1 animals were bled via conventional sparse (two animals/time point) sublingual vein bleeding (~0.5 ml) with anesthesia, while the Group 2 animals were bled via serial tail vein microsampling (~0.075 ml) without anesthesia. All collected blood was processed for plasma. Each Group 2 plasma sample (~30 μl) was divided into 'wet' and 'dried' (dried plasma spots). All plasma samples were analyzed by LC-MS/MS for acetaminophen and its major metabolites acetaminophen glucuronide and acetaminophen sulfate. In addition, plasma and urine samples were collected for analysis of corticosterone and creatinine to assess stress levels. Comparable plasma exposure to acetaminophen and its two metabolites was observed in the plasma obtained via conventional sparse sublingual vein bleeding and serial tail vein microsampling and between the 'wet' and 'dried' plasma obtained by the latter. Furthermore, comparable corticosterone levels or corticosterone/creatinine ratios between the two groups suggested that serial microsampling without anesthesia did not increase the levels of stress as compared with conventional sampling with anesthesia, confirming the utility of microsampling for plasma or dried plasma spots in rodent toxicokinetic assessment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".