Fluorescence Anisotropy of Cellular NADH as a Tool to Study Different Metabolic Properties of Human Melanocytes and Melanoma Cells
Bibliographic record
Abstract
In this study, we wanted to see if fluorescence anisotropy could be used to detect changes in metabolism in cells with significant light scattering and absorption properties. Fluorescence anisotropy measurements of nicotinamide adenine dinucleotide (NADH) were performed with human melanocytes and melanoma cell lines. To demonstrate the feasibility of using fluorescence anisotropy for detecting metabolic changes, the electron transport chain was blocked using rotenone, inducing an accumulation of intracellular NADH. Total fluorescence increased in all cells as a result of rotenone treatment. Fluorescence anisotropy decreased in the rotenone-treated cells relative to the controls, suggesting an increased ratio of free to protein-bound NADH in the treated cells. In general, the fluorescence anisotropy of the melanocytes was significantly higher than that of the melanoma cell lines. Reflectance spectroscopy showed that the differences in fluorescence anisotropy between the cell types were not due to differences in scattering and absorption properties. Intrinsic cellular NADH fluorescence was experimentally extracted by ratioing polarized fluorescence to polarized reflectance. NADH binding, measured as the ratio of fluorescence intensity at 430 and 465 nm, showed more protein-bound NADH in the melanocytes than in the melanoma cells, consistent with the fluorescence anisotropy measurements.
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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) | 0.001 | 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".