Neuroprotective effects of Shaoyao Gancao decoction against excitatory damage in PC12 cells based on the Src-NR2-nNOS pathway
Bibliographic record
Abstract
To explore the neuroprotective effects of the Shaoyao Gancao decoction (SGD) against excitatory damage in PC12 cells and the role of the Src-NR2-nNOS pathway mediation by SGD in regulating γ-aminobutyric acid (GABA)-glutamate (Glu) homeostasis. N-Methyl-d-aspartic acid (NMDA) was used to establish a PC12 cell excitability injury model. To investigate the neuroprotective effect of SGD, a Cell Counting Kit-8 (CCK-8) assay was used to determine PC12 cell viability, Annexin V/Propidium Iodide (Annexin V/PI) double staining was used to determine PC12 cell apoptosis, and Ca2+ concentration was observed using laser confocal microscopy. GABA receptor agonists and antagonists were used to analyze the neuroprotective interactions between γ-aminobutyric acid (GABA) and NMDA receptors. Additionally, molecular biology techniques were used to determine mRNA and protein expression in the Src-NR2-nNOS pathway. We analyzed the correlations between the regulatory sites of GABA and NMDA interactions, excitatory neurotoxicity, and brain damage at the molecular level. NMDA excitotoxic injury manifested as a significant decrease in cell activity, increased apoptosis and caspase-3 protein expression, and a significant increase in intracellular Ca2+ concentration. Administration of SGD, a GABAA receptor agonist (muscimol), or a GABAB receptor agonist (baclofen) decreased intracellular Ca2+ concentrations, attenuated apoptosis, and reversed NMDA-induced upregulation of caspase-3, Src, NMDAR2A, NMDAR2B, and nNOS. Unexpectedly, a GABAA receptor antagonist (bicuculline) and a GABAB receptor antagonist (saclofen) failed to significantly increase excitatory neurotoxicity. Taken together, these results not only provide an experimental basis for SGD administration in the clinical treatment of central nervous system injury diseases, but also suggest that the Src-NR2A-nNOS pathway may be a valuable target in excitotoxicity treatment.
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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 | 0.000 |
| 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".