Oxidative Stress Effect of Dopamine on α-Synuclein: Electroanalysis of Solvent Interactions
Bibliographic record
Abstract
The interaction of dopamine (DA) and α-synuclein (α-S) can lead to protein misfolding and neuronal death triggered by oxidative stress relevant to the progression of Parkinson's disease (PD). In this study, interfacial properties associated with DA-induced α-S aggregation under various solution conditions (i.e., pH, ionic strength) were investigated in vitro. The electrochemical oxidation of tyrosine (Tyr) residues in α-S was detected in the presence of DA. DA concentration dependence was analyzed and found to significantly affect α-S aggregation pathways. At low pH, DA was shown to be stable and produced no observable difference in interfacial properties. Between pH 7 and 11, DA promoted α-S aggregation. Significant differences in oxidation current signals in response to high pH and ionic strength suggested the importance of initial interactions in the stabilization of toxic oligomeric structures and subsequent off-pathways of α-S. Our results demonstrate the importance of solution interactions with α-S and the unique information that electrochemical techniques can provide for the investigation of α-S aggregation at early stages, an important step toward the development of future PD therapeutics.
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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 | 0.000 |
| 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 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".