Effects of chronic prenatal nicotine exposure on gene expression in neurotransmitter systems of the rat carotid body chemoafferent pathway
Bibliographic record
Abstract
Maternal smoking during pregnancy is a major risk factor for sudden infant death syndrome (SIDS) and nicotine is the key component implicated. Impaired ventilatory and arousal responses to low PO2 (hypoxia) during sleep are hallmarks of SIDS that have been observed in infants of smoking mothers and linked to prenatal nicotine exposure in animal models. Low PO2 stimulates the carotid body (CB), which receives afferent innervation from the petrosal ganglion (PG), initiating a chemoreflex that increases ventilation and can provoke wakefulness. Using a rat model, the objective of this study was to determine the effects of chronic prenatal nicotine exposure (1 mg / kg body weight / day) on gene expression within the cholinergic and dopaminergic neurotransmitter systems involved in the regulation of this reflex. After chronic nicotine, QPCR data revealed the upregulation of a2, a3, a6, b2, b3, and b4 nicotinic acetylcholine receptor (nAChR) subunits in the CB (a4, a5, a7, a9 unchanged, a10 downregulated) versus the downregulation of a2, a3, a4, a7, a9, a10, b2, b3 and b4 nAChR subunits in the PG (a5 absent, a6 unchanged). In the CB, tyrosine hydroxylase (TH) was upregulated and the dopamine transporter (DAT) was unchanged. In the PG, TH was upregulated and the DAT was downregulated. Future studies will determine whether changes in nAChR function correlate with observed changes in subunit expression. Supported by CIHR and NSERC.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".