Effect of tanshinone on the levels of nitric oxide synthase and acetylcholinesterase in the brain of Alzheimer’s disease rat model
Bibliographic record
Abstract
PURPOSE: To determine the influence of tanshinone on the levels of nitric oxide synthase (NOS) and acetylcholinesterase (AChE) in the brain of an Alzheimer's Disease (AD) rat model and on its potential therapeutic mechanism. METHODS: 100 Male Sprague Dawley rats were divided into three groups: control group, model group and tanshinone treatment group. 10 microg A beta 1-42 was injected bilaterally into the dorsal lateral region of the dentate gyrus in the hippocampus of rats in the model and tanshinone treatment groups to prepare the AD models. 24h after modeling, tanshinone, 50mg/kg, was administered by gastric perfusion to rats in the tanshinone treatment group. Later, immunohistochemical assay and Western blot analysis were used to detect expression of neuronal NOS (nNOS) and inducible NOS (iNOS) in the rat hippocampus. Activity of AChE in each subregion (CA1 approximately CA4) of rats' hippocampus was determined by a histochemical technique. RESULTS: Expression of nNOS in the model group was down-regulated whereas iNOS was up-regulated. After A beta 1-42 injection, the number of AChE positive fibers in each subregion (CA1 approximately CA4) of the hippocampus was decreased compared with controls. With tanshinone administration, the changes were improved to varying degrees. CONCLUSION: Tanshinone modulates AChE and NOS proteins concentrations in the hippocampus of AD rats. This may have therapeutic potential in AD rats.
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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) | 0.000 | 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) | 0.001 | 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".