Hydrogen peroxide-induced oxidative stress, acetylcholinesterase inhibition, and mediated brain injury attenuated by <i>Thymus algeriensis</i>
Bibliographic record
Abstract
The aim of the current study was to evaluate acetylcholinesterase (AChE) inhibition, antioxidant enzyme activities, and malondialdehyde (MDA) levels induced by hydrophobic fractions of Thymus algeriensis (HFTS) growing in Tunisia. The results showed that hydrogen peroxide (H2O2), an oxidative stress inducer, acts by decreasing the body mass and brain mass of rats. Moreover, we found higher MDA levels in the group treated with H2O2 (P < 0.05) and a significantly lower activity of catalase, glutathione peroxidase, glutathione S-transferase, and superoxide dismutase, as well as a reduction in reduced glutathione activity in the brain tissues of H2O2-treated rats when compared with those of the control group (P < 0.05); however, rats that received HFTS with H2O2 experienced a decrease in MDA levels in the brain. In contrast, HFTS demonstrated neuroprotective effects in rat brain. Overall, exposure to HFTS prior to H2O2 induced a marked dose-dependent increase in reactive oxygen species scavenger levels (P < 0.05) accompanied by a statistically significant decrease in MDA levels (P < 0.05) when compared with no exposure. Notably, the activity of AChE was affected by exposure to natural compounds; levels were significantly lower in HFTS-treated rats and in those treated with the combination of HFTS and a low or high dose of H2O2. Furthermore, histopathological analysis showed that brain injuries occurred with high doses of H2O2 administered alone or with a low dose of HFTS, whereas a high dose of essential oil markedly alleviated neurone degeneration. The results suggest that HFTS alleviates neuroinflammation by acting as an AChE inhibitor and attenuates H2O2-induced brain toxicity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".