Luteolin offers novel therapeutic regimen in rotenone-induced Parkinson disease via modulation of TNF-α/FXMRP/serotonin/tyrosine hydroxylase signaling pathway.
Bibliographic record
Abstract
Exposure of pesticide and complex I inhibitor, rotenone has been shown to reproduce features of Parkinson's disease, including selective nigrostriatal dopaminergic degeneration and α-synuclein-positive cytoplasmic inclusions. Sixty mice were randomly divided into six groups (n=10) and orally treated for 28 consecutive days as follows; group 1: vehicle (10 mL/kg), group 2- vehicle + rotenone (10 mg/kg p.o. in 0.5% carboxymethyl cellulose (CMC), group 3 - rotenone + 100 mg/kg Luteolin, group 4 - rotenone + 200 mg/kg Luteolin, group 5 - 100 mg/kg Luteolin and group 6 - 200 mg/kg Luteolin, respectively. At the end of the experiment, brain tissues were harvested for biomarkers of oxidative stress, neurobehavioural studies, histology, and immunohistochemistry of Tumour Necrosis Factor alpha (TNF-α), Fragile X Mental Retardation Protein (FXMRP), serotonin, and tyrosine hydroxylase were evaluated. Rotenone toxicity significantly enhanced biomarkers of oxidative stress, acetylcholinesterase activity, and declined antioxidant defense system. Significant reduction in motor coordination and movement disorder together with vacuolation (demyelination) and atrophy of neurons were observed in ROT-untreated mice. Treatment of mice with Luteolin lowered oxidative stress biomarkers, neuroinflammation, Fragile X Mental Retardation Protein expression, improved expression of serotonin and tyrosine hydroxylase production, and restored neuronal ultrastructure anarchy.
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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 | 0.001 |
| 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".