Darkness: A Crucial Factor in Fungal Taxol Production
Bibliographic record
Abstract
Fungal Taxol acquired lots of attention in the last decades since it can be an easy method for manipulation and scaling up the production level of a valuable anticancer drug. Several researchers studied varieties of factors to enhance fungal Taxol production. However, up to date fungal Taxol production has never been enhanced to the commercial level. Thus it is assumed that optimization of fungal Taxol production could require clear understanding of the fungal habitat in its original host plant. One major sharing feature in the habitat of all fungal endophytes that they are located in the internal plant tissues where the dark is prominent; hence the effect of light on fungal Taxol production was tested. Incubation of Taxol-producing endophytic SSM001 fungus in light prior to inoculation for Taxol production showed dramatic loss of Taxol production, significant reduction in resin bodies and reduction in gene expression known to be involved in Taxol biosynthesis. The loss of Taxol production was accompanied with production of dark green pigments. Pigmentation is a fungal protection mechanism mediated by opsin receptor and induced by light. On the other hand, light induced the gene expression of opsin, a known photoreceptor involved in light perception and pigment production identified in SSM001 by genome sequencing. The results from this study indicated that the endophytic fungus SSM001 required the dark habitat of its host plant for Taxol production and hence behaved negative in response to light.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".