Using Quenching Kinetics and Thermodynamics of Amino-Fluorophores as Empirical Tools for Predicting Boronic Acid Sensors Suitable for Use in Physiological Conditions
Bibliographic record
Abstract
A series of water-soluble 1-amino-naphthalenes and 2-amino-fluorenes are prepared. These serve as model fluorophores for measuring the thermodynamics and kinetics of fluorescence quenching with phenylboronic acids and aliphatic amines. Steady-state and time-resolved fluorescence quenching kinetics are investigated using the Stern–Volmer method. Diffusion limited quenching constants and exergonic thermodynamics of electron transfer are derived for the 5-amino-1-napthol and 2-aminofluorene derivatives with phenylboronic acid and/or an aliphatic imine. No quenching and endergonic thermodynamics or electron transfer are observed for 5-sulfonamide, 5-sulfonic acid, or 5-hydroxy-7-sulfonic acid aminonaphthalene derivatives. Boronic acid sensors synthesized from these aminofluorophores by reductive amination with 2-formylphenylboronic acid undergo fluorescence revival in the presence of saccharides only when the fluorophore demonstrates diffusion limited quenching kinetics and exergonic thermodynamics of electron transfer with the boronic acid or imine quenchers. Thus, these two properties are suitable empirical tools for predicting saccharide-induced fluorescence revival of boronic acid sensors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".