Low-Moderate Doses of Nicotine Decreased mRNA of NGF and BDNF and Their Receptors at 30 Min in the Frontal Cortex and Hippocampus of ApoE-KO Mice
Bibliographic record
Abstract
Background: Several studies have detected nicotine-associated increases in the mRNA and protein expression of NGF, BDNF and TrkA and TrkB receptors in multiple brain regions. Methods: We investigated the acute effects of different doses of nicotine (0.1, 0.5 and 1.0 mg/kg) on the mRNA levels of NGF, BDNF, TrkA and TrkB in the frontal cortex and hippocampus of ApoE-knockout (ApoE-KO) and wild-type (WT) mice. Results: The results demonstrated that in the frontal cortex and hippocampus, nicotine decreases NGF and BDNF mRNA levels in both ApoE-KO and WT mice. Nicotine also reduced TrkA in the frontal cortex and TrkB in both brain regions of WT mice, whereas no changes were observed in ApoE-KO mice. Interestingly, all of these effects were limited to low-intermediate doses (0.1 and 0.5 mg/kg) of nicotine, while 1.0 mg/kg of nicotine had no noticeable effect on the brain of either strain of mice. ApoE-KO mice showed a distinctly higher level of NGF mRNA expression versus the WT mice in both regions of the brain, whereas TrkA expression was lower only in the frontal cortex. Conclusions: These findings suggest that acute nicotine causes a decrease in the mRNA levels of NGF, BDNF and their receptors in the frontal cortex and hippocampus of mice depending on nicotine doses. A high level of NGF mRNA was observed in the brain of ApoE-KO mice, suggesting a role of ApoE in the expressions of neurotrophins in the hippocampus. doi: http://dx.doi.org/10.4021/jnr217e
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".