Brown rice attenuates iron-induced Parkinson’s disease phenotypes in male wild-type <i>drosophila</i>: insights into antioxidant and iron metabolism modulation
Bibliographic record
Abstract
Parkinson's disease (PD) is a progressive movement disorder associated with brain iron (Fe) accumulation and free radicals. Brown rice (BR) is antioxidant-rich and has been shown to ameliorate oxidative stress-induced damage. The aim of this study was to investigate the effects of BR compared to white rice (WR) on Fe-induced PD in a fruit fly model. Three-day-old male adult flies were divided into two groups: one on a normal diet and the other on Fe-diet (1 mmol/L) for 10 days to induce PD. After 10 days, the Fe-fed flies were redistributed into four groups: one on normal diet (Fe group), while the others were treated with BR (Fe + BR group), WR (Fe + WR group), or L-3,4-dihydroxyphenylalanine (L-dopa) (Fe + L-dopa group) for 5 days. Similarly, the flies initially on a normal diet were separated into four groups: one on normal diet (Control group), while the others were treated with BR (BR group), WR (WR group), or L-dopa (L-dopa group) for 5 days. Finally, Fe levels, dopamine, malonaldehyde (MDA), and antioxidant enzymes were measured, and the mRNA levels of antioxidant and Fe metabolism genes were assessed. BR significantly improved motor and cognitive functions, decreased fly head MDA and Fe levels, and increased antioxidant enzyme levels in comparison to the Fe and WR groups. Similarly, BR upregulated the mRNA levels of antioxidant genes: catalase, GPx, Nrf2, and DJ-1. The results suggest that BR could potentially reduce morbidities associated with PD possibly due to its bioactive compounds compared to WR.
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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 | 0.000 | 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".