Spectroelectrochemical Reverse Engineering DemonstratesThat Melanin’s Redox and Radical Scavenging Activities Are Linked
Bibliographic record
Abstract
Melanins are ubiquitous in nature but their biological activities and functions have been difficult to discern. Conventional approaches to determine material function start by resolving structure and then characterize relevant properties. These approaches have been less successful for melanins because of their complex structure and insolubility, and because their relevant properties are not readily characterized by conventional methods. Here, we report a novel spectroelectrochemical reverse engineering approach that focuses on redox and radical scavenging activities. In this method, the melanin is immobilized in a permeable hydrogel film adjacent to an electrode and this immobilized melanin is probed using diffusible mediators and complex electrical inputs. Response characteristics are measured using two modalities, electrochemical currents associated with the reaction of diffusible mediators, and optical absorbance associated with the presence of diffusible free radicals. Using this method, we observed that both Sepia and fungal melanins are redox active and can repeatedly exchange electrons to be switched between oxidized and reduced states. Further, we observed that these melanins can quench radicals either by donating or accepting electrons. Finally, we demonstrate that the melanins' radical scavenging activities are dependent on their redox state such that a melanin must be reduced to have donatable electrons to quench oxidative free radicals, or must be oxidized to accept electrons from reductive free radicals. While the observation that melanin is redox-active is consistent with their well-accepted beneficial (radical-scavenging) and detrimental (pro-oxidant) activities, these observations may also support less well-accepted proposed functions for melanin in energy harvesting and redox communication.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 teacher head, 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".