Tanshinone I alleviates motor and cognitive impairments via suppressing oxidative stress in the neonatal rats after hypoxic-ischemic brain damage
Bibliographic record
Abstract
Neonatal hypoxia-ischemia is one of the main reasons that cause neuronal damage and neonatal death. Several studies have shown that tanshinone I (TsI), one of the major ingredients of Danshen, exerts potential neuroprotective effect in adult mice exposed to permanent left cerebral ischemia. However, it is unclear whether administration of TsI has neuroprotective effect on neonatal hypoxic-ischemic brain damage (HIBD), and if so, the potential mechanisms also remain unclear. Here, we reported that treatment with TsI (5 mg/kg, i.p.) significantly alleviated the deficits of myodynamia and motor functions as well as the spatial learning and memory in the rat model of HIBD. These behavioral changes were accompanied by a significant decrease in the number of neuronal loss in the CA1 area of hippocampus. Moreover, ELISA assay showed that TsI significantly increased the production of antioxidants including total antioxidant capacity (T-AOC), glutathione (GSH), total superoxide dismutase (T-SOD) and catalase (CAT), and reduced the production of pro-oxidants including hydrogen peroxide (H 2 O 2 ), total nitric oxide synthase (T-NOS) and inducible nitric oxide synthase (iNOS). Taken together, these results indicate that TsI presents potential neuroprotection against neuronal damage via exerting significantly antioxidative activity and against pro-oxidant challenge, thereby ameliorating hypoxia-ischemia-induced motor and cognitive impairments in the neonatal rats, suggesting that TsI may be a potential therapeutic agent against HIBD.
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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) | 0.001 | 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".