Cocoa beans improve mitochondrial biogenesis via PPARγ/PGC1α dependent signalling pathway in MPP<sup>+</sup>intoxicated human neuroblastoma cells (SH-SY5Y)
Bibliographic record
Abstract
Polyphenols are shown to protect from or delay the progression of chronic neurodegenerative diseases. Mitochondrial dysfunction plays a key role in the pathogenesis of Parkinson’s disease (PD). This study was aims to gain insight into the role of ahydroalcoholic extract of cocoa (standardised for epicatechin content) on mitochondrial biogenesis in MPP+ intoxicated human neuroblastoma cells (SHSY5Y). The effects of cocoa on PPARγ, PGC1α, Nrf2 and TFAM protein expression and mitochondrial membrane potential were evaluated. A pre-exposure to cocoa extract decreased reactive oxygen species formation and restored mitochondrial membrane potential. The cocoa extract was found to up-regulate the expression of PPARγ and the downstream signalling proteins PGC1α, Nrf2 and TFAM. It increased the expression of the anti-apoptotic protein BCl2 and increased superoxide dismutase activity. Further, the cocoa extract down-regulated the expression of mitochondria fission 1 (Fis1) and up-regulated the expression of mitochondria fusion 2 (Mfn2) proteins, suggesting an improvement in mitochondrial functions in MPP+ intoxicated cells upon treatment with cocoa. Interestingly, cocoa up-regulates the expression of tyrosine hydroxylase, the rate limiting enzyme in dopamine synthesis. No change in the expression of PPARγ on treatment with cocoa extract was observed when the cells were pre-treated with PPARγ antagonist GW9662. This data suggests that cocoa mediates mitochondrial biogenesis via a PPARγ/PGC1α dependent signalling pathway and also has the ability to improve dopaminergic functions by increasing tyrosine hydroxylase expression. Based on our data, we propose that a cocoa bean extract and products thereof could be used as potential nutritional supplements for neuroprotection in PD.
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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".