The suppression effects of Ratanasampil on oxidative stress-induced neuronal damage and microglia-mediated neuroinflammation
Bibliographic record
Abstract
Generation of reactive oxygen species (ROS) causes lipids, proteins and DNA damage, resulting in neuronal damage and neruoinflammation. Ratanasampil (RNSP), a traditional Tibetan medicine, clinically used for the mild-to moderate AD patients living at high altitude. In vivo, RNSP improved the learning and memory in an AD mouse model (Tg2576). However, mechanism underlying the effects of RNSP is unknown. In SH-SY5Y cells, RNSP significantly ameliorated the H2O2 –induced cytotoxicity. Furthermore, RNSP significantly reduced the H2O2-induced 8-oxo-2′-deoxyguanosine and attenuated the phosphorylation of p38 and ERK 1/2. In MG6 microglia, RNSP significantly ameliorated the cytotoxicity induced by hypoxia-reoxygenation. Furthermore, RNSP significantly suppressed the H6/R24-induced pro-inflammatory cytokines, ROS, DNA damage and phosphorylation of IκBα. These observations suggest that RNSP suppressed the H2O2-induced neuronal death through downregulation of p38-ERK activation and regulated the H/R-induced neuroinflammation through inhibition of oxidative stress and the activation of NFκB in MG6 cells. Therefore, RNSP may be beneficial for preventing oxidative stress-induced neuronal death and neuroinflammation.
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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) | 0.002 | 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".