Neuroprotective effect of Chunghyuldan from amyloid beta oligomer induced neuroinflammation in vitro and in vivo
Bibliographic record
Abstract
Microglia-mediated inflammation is a major pathological mechanism contributing to Alzheimer's disease (AD), and has been proposed as a potential therapeutic target. Chunghyuldan (CHD; Qingxue-dan in Chinese and Daio-Orengedokuto in Japanese) possesses wide-ranging biological effects, including anti-hyperlipidemic, anti-stroke, anti-inflammatory, and antioxidant activities that could affect neurological functions. In this study, we examined the effects of CHD in in-vitro and in-vivo models of AD induced by the oligomeric form of amyloid-beta (Aβ oligomer), which acts directly on microglia-mediated neuroinflammation to result in neuronal damage and cognitive impairment. CHD at 0.1-100 μg·mL(-1) significantly protected PC12 cells and rat primary hippocampal cells from Aβ oligomer1-42 toxicity. In addition, CHD at 1-10 μg·mL(-1) inhibited Aβ oligomer1-42 induced production of nitric oxide, tumor necrosis factor-α, and interleukin-1β in microglial cells. In an in-vivo AD model, administration of CHD (50 mg·(kg body mass)(-1), for 5 days, per oral) inhibited the activation of astrocytes and microglia in the dentate gyrus and neuronal damage in the CA1 of the ipsilateral hippocampus. Moreover, CHD ameliorated cognitive impairment induced by Aβ oligomer1-42 toxicity. These results demonstrate the neuroprotective effects of CHD through inhibition of microglia-mediated neuroinflammation in in-vitro and in-vivo AD-like models induced by Aβ oligomer1-42 toxicity.
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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 | 0.000 |
| 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".