MétaCan
Menu
Back to cohort
Record W6976797233 · doi:10.60692/wnv7h-1c426

Darkness: A Crucial Factor in Fungal Taxol Production

2018· article· en· W6976797233 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2018
Typearticle
Languageen
FieldEnergy
TopicRenewable Energy and Sustainability
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFungusPlant use of endophytic fungi in defenseGeneAscomycotaFilamentous fungusGene expressionHost (biology)

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.215
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueGreater South Information SystemSame topicRenewable Energy and SustainabilityFrench-language works237,207