Hexarelin exerts neuroprotective and antioxidant effects against hydrogen peroxide-induced toxicity through the modulation of MAPK and PI3K/Akt patways in Neuro-2A cells
Bibliographic record
Abstract
Abstract Hexarelin, a synthetic hexapeptide, protects cardiac and skeletal muscles by inhibiting apoptosis, both in vitro and in vivo . Moreover, evidence suggests that hexarelin could have important neuroprotective bioactivity. Oxidative stress and the generation of free radicals has been implicated in the etiologies of several neurodegenerative diseases, including amyotrophic lateral sclerosis, Parkinson’s disease, Alzheimer’s disease, Huntington’s disease and multiple sclerosis. In addition to direct oxidative stress, exogenous hydrogen peroxide (H 2 O 2 ) can penetrate biological membranes and enhance the formation of other reactive oxygen species. The aim of this study was to examine the inhibitory influence of hexarelin on H 2 O 2 -induced apoptosis in Neuro-2A cells, a mouse neuroblastoma cell line. Our results indicate that H 2 O 2 reduced the viability of Neuro-2A cells in a dose-related fashion. Furthermore, H 2 O 2 induced significant changes in the morphology of Neuro-2A cells, reflected in the formation of apoptotic cell bodies, and an increase of nitric oxide (NO) production. Hexarelin effectively antagonized H 2 O 2 oxidative damage to Neuro-2A cells as indicated by improved cell viability, normal morphology and reduced nitrite (NO 2 − ) release. Hexarelin treatment of Neuro-2A cells also reduced mRNA levels of caspases−3 and −7 and those of the pro-apoptotic molecule Bax; by contrast, hexarelin treatment increased anti-apoptotic Bcl-2 mRNA levels. Hexarelin also reduced MAPKs phosphorylation induced by H 2 O 2 and concurrently increased p-Akt protein expression. In conclusion, our results identify several neuroprotective and anti-apoptotic effects of hexarelin. These properties suggest that further investigation of hexarelin as a neuroprotective agent in an investigational and therapeutic context are merited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".