Nutrient media optimization for simultaneous enhancement of the laccase and peroxidases production by coculture of <i><scp>D</scp>ichomitus squalens</i> and <i><scp>C</scp>eriporiopsis subvermispora</i>
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
Coculturing of two white-rot fungi, Dichomitus squalens and Ceriporiopsis subvermispora, was explored for the optimization of cultivation media for simultaneous augmentation of laccase and peroxidase activities by response surface methodology (RSM). Nutrient parameters chosen from our previous studies with the monocultures of D. squalens and C. subvermispora were used to design the experiments for the cocultivation study. Glucose, arabinose, sodium nitrate, casein, copper sulfate (CuSO4 ), and manganese sulfate (MnSO4 ) were combined according to central composite design and used as the incubation medium for the cocultivation. The interaction of glucose and sodium nitrate resulted in laccase and peroxidase activities of approximately 800 U/g protein. The addition of either glucose or sodium nitrate to the medium also modifies the impact of other nutrients on the ligninolytic activity. Both enzyme activities were cross-regulated by arabinose, casein, CuSO4 , and MnSO4 as a function of concentrations. Based on RSM, the optimum nutrient levels are 1% glucose, 0.1% arabinose, 20 mM sodium nitrate, 0.27% casein, 0.31 mM CuSO4 , and 0.07 mM MnSO4 . Cocultivation resulted in the production of laccase of 1,378 U/g protein and peroxidase of 1,372 U/g protein. Lignin (16.9%) in wheat straw was degraded by the optimized enzyme mixture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 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