Characterization of the rat Acetylcholinesterase readthrough (AChE-R) splice variant: Implications for toxicological studies
Bibliographic record
Abstract
Exposure to chemicals and other environmental stressors can differentially impact the expression of Acetylcholinesterase (AChE) splice variants. Surprisingly, despite the widespread use of the rat model in toxicological studies and the wealth of literature on this important biomarker of neurotoxicity, AChE coding exons and splice variants are not yet fully annotated in this species. To address this knowledge gap, a short problematic region of the rat AChE genomic DNA present in GenBank was first re-sequenced. This revised genomic sequence was then aligned to rat AChE RefSeq mRNA and compared to orthologous mammalian sequences, in order to map the coding exon and intron boundaries of the rat AChE gene. Based on these bioinformatics analyses, a sequence was predicted for the yet-unannotated rat Acetylcholinesterase readthrough (AChE-R) splice variant. PCR primers designed to specifically amplify rat AChE-R were used to confirm its expression in rat PC12 cells. Compared to the canonical AChE-S splice variant, AChE-R was expressed at much lower levels but presented distinct regulation patterns in PC12 cells and rat primary cerebral granule cells (CGCs) following exposure to Chlorpyrifos (a well-known neurotoxic organophosphate pesticide). Taken together, these observations point to the evolutionary conservation of the AChE-R splicing event between rodents and human and to the distinct regulation of AChE splice variants in response to toxicological challenges.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".