Optimization of a Fluorescence-based Lysozyme Activity Assay for Contact Lens Studies
Bibliographic record
Abstract
PURPOSE: To optimize a fluorescence-based lysozyme activity assay to investigate the conformational state of lysozyme in solution and to determine the impact of extraction and evaporation procedures and the possible interference of contact lens materials on lysozyme activity. METHODS: The fluorescence-based lysozyme activity assay, Enzchek (Molecular Probes Inc, Eugene, OR) which utilizes fluorescently quenched Micrococcus lysodeikticus, was compared to the gold standard, classical lysozyme turbidity assay, using four differently concentrated lysozyme samples (20, 10, 5.0 and 2.0 ng/µL). Furthermore, six differently concentrated lysozyme samples (2.0, 1.0, 0.5, 0.25, 0.125 and 0.01 µg/µL) were quantified using the fluorescence-based assay in the presence of extraction solvents consisting of 0.2% and 0.02% trifluroacetic acid/acetonitrile and following evaporation procedures. RESULTS: A standard curve was generated by the fluorescence-based assay ranging from 2 to 150 ng. The total active lysozyme quantified in the four lysozyme samples was not significantly different between the two assays (p > 0.05) and the concordance correlation coefficient was determined to be 0.995. However an average discrepancy between the two assays was found to be 0.474 ng, with the turbidity assay typically reporting higher active lysozyme measurements. The sensitivity of the fluorescence-based assay was higher than the classical turbidity assay when quantifying 20 ng or less active lysozyme. Following the extraction and evaporation procedures and the addition of lens extracts, the total active lysozyme recovered was 95% or greater. CONCLUSIONS: In comparison to the classical turbidity assay, the fluorescence-based assay is a very sensitive method, making it a favorable technique, particularly when studying contact lens materials that deposit relatively low levels of lysozyme.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".