Effect of Tacrine‐3‐caffeic Acid, A Novel Multifunctional Anti‐Alzheimer's Dimer, Against Oxidative‐Stress‐Induced Cell Death in <scp>HT</scp>22 Hippocampal Neurons: Involvement of Nrf2/<scp>HO</scp>‐1 Pathway
Bibliographic record
Abstract
AIMS: Oxidative stress (OS) plays an important role in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease (AD). This study was designed to uncover the cellular and biochemical mechanisms underlying the neuroprotective effects of tacrine-3-caffeic acid (T3CA), a novel promising multifunctional anti-Alzheimer's dimer, against OS-induced neuronal death. METHODS AND RESULTS: T3CA protected HT22 cells against high-concentration-glutamate-induced cell death in time- and concentration-dependent manners and potently attenuated glutamate-induced intracellular reactive oxygen species (ROS) production as well as mitochondrial membrane-potential (ΔΨ) disruption. Besides, T3CA significantly induced nuclear factor erythroid 2-related factor 2 (Nrf2) nuclear translocation and increased its transcriptional activity, which were demonstrated by Western blotting, immunofluorescence, and antioxidant response element (ARE)-luciferase reporter gene assay. Further studies showed that T3CA potently up-regulated heme oxygenase-1 (HO-1), an endogenous antioxidative enzyme and a downstream effector of Nrf2, at both mRNA and protein levels. The neuroprotective effects of T3CA were partially reversed by brusatol, which reduced protein level of Nrf2, or by inhibiting HO-1 with siRNA or ZnPP-IX, a specific inhibitor of HO-1. CONCLUSIONS: Taken together, these results clearly demonstrate that T3CA protects neurons against OS-induced cell death partially through Nrf2/ARE/HO-1 signaling pathway, which further supports that T3CA might be a promising novel therapeutic agent for OS-associated diseases.
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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".