Effects of Capillary Microsampling on Toxicological Endpoints in Juvenile Rats
Bibliographic record
Abstract
Blood sampling during juvenile rat toxicology studies is required to determine the toxicokinetic (TK) profile of compounds. Juvenile rats are too small to undergo repeated blood sampling using conventional methods, which collect 200-300 μl blood at each time point. Recently, capillary microsampling (CMS) gained interest because sample sizes are almost 10 times smaller enabling multi-sample collection from 1 rat. Here, we evaluated the use of CMS in juvenile rats in support of reduced animal usage. Juvenile rats at postnatal day (PND) 4, 10, and 17 underwent CMS via the submandibular, tail, and jugular veins. The CMS methods for pups at different ages were evaluated based on sample quality and technical practicality as well as on acute and chronic changes of toxicological parameters. The best location for CMS was the submandibular vein for PND 4 and 10 pups and the tail vein for PND 17 pups. No effects were found on clinical signs, body and organ weights and biochemistry parameters when 2 × 32 μl of blood was withdrawn from PND 4 pups or when 3 × 32 μl was taken from PND 10 and 17 pups within 24 h. Significant changes in several hematology parameters were observed 24 h after CMS due to a decrease of red blood cells and renewed production. These values had recovered to normal 7 days after CMS. CMS is feasible in juvenile rats for TK assessment. Utilizing this method could decrease the number of additional animals by 75%.
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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) | 0.001 | 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 | 0.001 |
| 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".