Separation and determination of closely related lantibiotics by micellar electrokinetic chromatography
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A sensitive micellar electrokinetic chromatography (MEKC) method was developed for the separation and determination of four closely related lantibiotics: gallidermin, cinnamycin, duramycin and nisin. Factors affecting the separation of the lantibiotics such as pH, phosphate buffer concentration, SDS concentration and wavelength for UV detection were investigated. By optimizing these experimental conditions, successful separation was achieved between class 1A lantibiotics (nisin and gallidermin) and class 1B lantibiotics (duramycin and cinnamycin). The four lantibiotics were separated within 12 min in 50 mM phosphate buffer at pH 3.95 +/- 0.1 containing 80 mM SDS with UV detection of 214 nm. The LOD (S/N = 3) were 61 ng/mL for gallidermin, 57 ng/mL for cinnamycin, 55 ng/mL for duramycin and 58 ng/mL for nisin. The method was successfully applied to real samples such as fermentation broth, bovine colostrum and predrop beer. This method yielded satisfactory results, with quantitative recoveries of spiked lantibiotics in the three samples ranging from 86.1 to 99.6%.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it