The Effects of Paraquat Exposure on Serial Reaction Time Performance in Rats (Rattus norvegicus) and Neuroprotection by Water-Soluble COQ10
Bibliographic record
Abstract
Nissen and Bullemer (1987) developed the serial reaction time (SRT) task to measure attention in humans. The SRT task in rats is typically modeled after studies with humans and uses repeated or random sequences to test anticipatory reactions. In the current study, paraquat (PQ)-induced Parkinson's disease (PD) model in Long-Evans hooded rats was used to examine the rats' sequential learning. A water-soluble formulation of coenzyme Q10 (WS- CoQ10) was used as a therapeutic agent. Rats were induced with Parkinson's disease via the administration of paraquat. The aim of this study was to study the neuroprotective effects of CoQ10 using the SRT task to measure sequence performance in rats. The results indicated that the rats were much faster in responding to fixed sequences compared to random sequences. However, this study did not find significant results to indicate that exposure of paraquat with or without a neuroprotective agent, WS-CoQ10 affected serial reaction performance. The implications of these findings are discussed with suggestions for further research with this task.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".