Sub-Diffusion Decays in Fluorescence Correlation Spectroscopy: Dye Photophysics or Protein Dynamics?
Bibliographic record
Abstract
Transitions between bright and dark fluorescent states of several rhodamine dyes were investigated by fluorescence correlation spectroscopy. We resolved two sub-diffusion exponential decays for free rhodamines in aqueous solutions, of which the slower component scales linearly with the viscosity of the solution. Correlation data for proteins and DNA labeled with tetramethylrhodamine were fitted with three to four exponential decays describing flickering dynamics on a time scale between 0.5 and 100 μs. We investigated the nature of these processes by performing experiments under different experimental conditions and for different samples. On the basis of how their population and lifetime change with viscosity, the oxygen content of the solution, the laser irradiance, and the detection geometry, we assigned these states, in the order of increasing lifetimes, to a triplet state, a hybrid between twisted-intramolecular-charge-transfer state and a ground state lactonic state, a lactonic state, and a photoionized state, respectively. Our data suggests that none of the observed sub-diffusion correlation decays can be directly assigned to the intramolecular dynamics of the labeled biomolecules. However, we found evidence that the intrinsic conformational dynamics of the biomolecule appears in the correlation curves as a modulation of the photophysics of the dye label. This shows the importance of accurate control measurements and appropriate modeling of the dye photophysics in fluorescence correlation studies, and it cautions against direct assignments of dark-state relaxation times to folding kinetics in proteins and nucleic acids.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".