Trametes meyenii possesses elevated dye degradation abilities under normal nutritional conditions compared to other white rot fungi
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
Several species of white-rot fungi were investigated for their utility in prolonged decolouration of the recalcitrant sulfonated azo dye, amaranth. Trametes pubescens, T. multicolor, T. meyenii and T. versicolor decoloured amaranth azo-dye best on low-nitrogen agar-solidified media whereas Bjerkandera adusta and Phlebia radiata were most effective in low nitrogen medium supplemented with manganese. Trametes cotonea did not decolour effectively under any condition. The decolouring Trametes species were also effective in liquid culture whereas B. adusta and P. radiata were not. Trametes meyenii, T. pubescens and T. multicolor were equal to or better than commonly employed T. versicolor at decolouring amaranth. This is the first study to show the dye decolouration potential of T. meyenii, T. pubescens, and T. multicolor. Supplementing with Mn(II) increased assayable manganese peroxidase activity, but not long-term decolouration, indicating that laccase is the main decolourizing enzyme in these Trametes species. This appears to be because of inadequate Mn(3+) chelation required by manganese peroxidase because adding relatively low amounts of malonate enhanced decolouration rates. The ability of Trametes meyenii to simultaneously decolour dye over prolonged periods of time while growing in relatively nutrient-rich medium appears to be unique amongst white-rot fungi, indicating its potential in wastewater bioremediation.
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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 | 0.000 |
| 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) | 0.001 | 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