Sesamin Modulates Tyrosine Hydroxylase, Superoxide Dismutase, Catalase, Inducible No Synthase and Interleukin‐6 Expression in Dopaminergic Cells Under Mpp+‐Induced Oxidative Stress
Why this work is in the frame
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Bibliographic record
Abstract
Oxidative stress is regarded as a mediator of nerve cell death in several neurodegenerative disorders, such as Parkinson's disease. Sesamin, a lignan mainly found in sesame oil, is currently under study for its anti-oxidative and possible neuroprotective properties. We used 1-methyl-4-phenyl-pyridine (MPP(+)) ion, the active metabolite of the potent parkinsonism-causing toxin 1-methyl-4-phenyl-1,2,5,6-tetrahydropyridine, to produce oxidative stress and neurodegeneration in neuronal PC12 cells, which express dopamine, as well as neurofilaments. Our results show that picomolar doses of sesamin protected neuronal PC12 cells from MPP(+)-induced cellular death, as revealed by colorimetric measurements and production of reactive oxygen species. We also demonstrated that sesamin acted by rescuing tyrosine hydroxylase levels from MPP(+)-induced depletion. Sesamin, however, did not modulate dopamine transporter levels, and estrogen receptor-alpha and -beta protein expression. By examining several parameters of cell distress, we found that sesamin also elicited a strong increase in superoxide dismutase activity as well as protein expression and decreased catalase activity and the MPP(+) stimulated inducible nitric oxide synthase protein expression, in neuronal PC12 cells. Finally, sesamin possessed significant anti-inflammatory properties, as disclosed by its potential to reduce MPP(+)-induced interleukin-6 mRNA levels in microglia. From these studies, we determined the importance of the lignan sesamin as a neuroprotective molecule and its possible role in complementary and/or preventive therapies of neurodegenerative diseases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it