Protective effects of Dioscorea bulbifera and Zingiber officinale mixed extracts against glutamate-induced cell death in HT22 cells
Bibliographic record
Abstract
Abstract This study aimed to evaluate the neuroprotective effects of mixed extracts from Dioscorea bulbifera and Zingiber officinale (DBZO) against glutamate-induced excitotoxicity in HT-22 cells and to elucidate the associated molecular mechanisms. Neurotoxicity and protective effects were assessed using MTT and LDH assays, while cellular morphology was analyzed via microscopy. DBZO extract significantly restored axonal integrity disrupted by glutamate exposure. A DCFDA assay confirmed that DBZO reduced reactive oxygen species (ROS) generation in a concentration-dependent manner, underscoring its antioxidant capacity. Western blot analysis demonstrated that DBZO markedly decreased glutamate-induced neuronal death at 0.25 and 0.5 mg/mL. The observed neuroprotection was associated with the inhibition of the MAPK signaling cascade and the downregulation of apoptotic markers, including Caspase-3 and PARP. Moreover, DBZO activated the PI3K/Akt/mTOR survival pathway, enhancing neuronal viability. It also boosted antioxidant defenses by modulating Keap1 and NQO1 expression, thereby reducing oxidative damage. Collectively, these findings suggest that DBZO confers neuroprotection by regulating oxidative stress and apoptosis through NRf2/NQO-1 signaling. Due to its strong antioxidant and antiapoptotic properties. Graphical Abstract
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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 | 0.001 | 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) | 0.002 | 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".