Reductions of acetylcholine release and nerve growth factor expression are correlated with memory impairment induced by interleukin‐1β administrations: effects of omega‐3 fatty acid EPA treatment
Bibliographic record
Abstract
Interleukin (IL)-1beta may play an important role in Alzheimer's disease. However, the relationships between glucocorticoids and acetylcholine (ACh), and between neurotrophins and ACh in IL-1-induced memory deficits are unknown. While ethyl-eicosapentaenoate (E-EPA) has recently been reported to reduce inflammation and improve memory, cholinergic and neurotrophic mechanisms by which E-EPA improves memory is unclear. This study evaluated: (i) the correlation between ACh release and memory impairment; (ii) the effect of glucocorticoids on ACh release; (iii) the relationship between nerve growth factor (NGF) and inflammation; and (iv) the effects of E-EPA treatment on IL-1beta-induced changes. Intracerebroventricular IL-1beta administrations produced a significant reduction in hippocampal ACh release in rats fed control diet, which was partially attenuated by mifepristone (RU 486) and completely blocked by IL-1 receptor antagonist. In eight-arm radial maze, significantly less ACh release was correlated with the memory deficits after IL-1beta administrations. mRNA expression of hippocampal NGF was lower, whereas IL-1beta was higher when compared with controls. E-EPA treatment significantly improved the memory, which was correlated with normalizing ACh release, and expressions of NGF and IL-1beta. This study revealed important mechanisms by which IL-1beta impairs, while E-EPA improves memory through IL-1-glucocorticoid-ACh release and IL-1-NGF-ACh release pathways.
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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 | 0.000 | 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".