Physiological and Biochemical Effects of Echium Amoenum Extract on Mn2+-Imposed Parkinson Like Disorder in Rats
Bibliographic record
Abstract
Purpose: Manganism is a cognitive disorder take places in peoples are exposed to environmental manganese pollution. Overexposure to manganese ion (Mn2+) mainly influences central nervous system and causes symptoms that increase possibility of hippocampal damages. Methods: In this study rats were administrated by two different doses of MnCl2 and behavioral and physiological consequences were evaluated. We also investigated effects of E. Amoenum on Mn2+-imposed toxicity by behavioral, biochemical, immunoblotting and histological studies on hippocampus tissue. Results: Results showed metal overexposure increases oxidative stress mainly by lipid peroxidation and reactive oxygen species overproduction. Histological studies and caspase 3 analyses by immunoblotting revealed Mn2+ induced apoptosis from mitochondrial-dependent pathway in the presence of low metal dose. This study provides evidence that oral administration of E. amoenum extract inhibited manganese neurotoxicity by oxidative stress attenuation and apoptosis reduction that lead to improved depression like behavior. Plant extract also increased catecholamine content in Mn2+ treated hippocampus. Conclusion: As molecular and pathophysiological effects of E. amoenum, it could be considered as a pre-treatment for Parkinson and Parkinson like disorders in high-risk people.
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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 | 0.001 |
| 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".