A glycerol-inducible thermostable lipase from<i>Bacillus</i>sp.: medium optimization by a Plackett–Burman design and by response surface methodology
Why this work is in the frame
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Bibliographic record
Abstract
The production of a neutral lipase from a Bacillus sp. was improved tremendously (193-fold) following media optimization involving both the "one-at-a-time" and the statistical designing approaches. The present lipase was poorly induced by oils, instead its production was induced in the presence of sugars and sugar alcohols, mainly galactose, lactose, glycerol, and mannitol. A high inoculum density of 15% v/v (A550 = 0.8) led to maximum lipase production. Interestingly, the enzyme induction was growth independent, a property very different from most of the lipases investigated to date. The optimal composition of the growth medium to achieve maximum lipase production was determined to be as follows: NH4Cl, 35 g x L(-1); glycerol, 10 mL x L(-1); K2HPO4, 3 g x L(-1); KH2PO4, 1 g x L(-1); MgSO4.7H2O, 0.1 g x L(-1); glucose, 2 g x L(-1); MgCl2, 0.6 mmol x L(-1), with 15% inoculum density and an incubation period of 24 h. About 62 U x mL(-1) of enzyme production was achieved in the optimized medium.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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