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Record W2072174138 · doi:10.1139/w07-080

Polar vineyard pruning extracts increase the activity of the main ligninolytic enzymes in Lentinula edodes cultures

2007· article· en· W2072174138 on OpenAlexvenueno aff
Citlalli Harris‐Valle, Martín Esqueda, Alfonso Sánchez, Miguel J. Beltrán-García, Elisa M. Valenzuela‐Soto

Bibliographic record

VenueCanadian Journal of Microbiology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsnot available
Fundersnot available
KeywordsLentinulaLaccaseMyceliumLigninManganese peroxidaseFood scienceBiomass (ecology)PeroxidaseEnzyme assayChemistryPleurotus eryngiiBotanyEnzymeLignin peroxidaseBiologyBiochemistryAgronomyMushroom

Abstract

fetched live from OpenAlex

Lentinula edodes is considered an alternative recycling agent for agricultural wastes, and there have been several studies to understand the relationship between its growth and ligninolytic activity. We tested the effect of wood from viticulture pruning, extracted with solvents of differing polarity, on the biomass production and activity pattern of ligninolytic enzymes. The analysis was done by measuring the mycelial dry mass and enzyme activity of liquid growth medium during the culture of L. edodes, adding either single extracts or a combination of extracts. Polar extracts enhanced mycelial production, and the activity patterns of lignin peroxidase, manganese peroxidase, aryl alcohol oxidase, and laccase were comparable to their activities predicted by ligninolysis models proposed for other fungi. We conclude that the polar extracts could be useful for enhancing fungal biomass production and for modifying lignin degradation because the regulation of ligninolytic enzyme activity is differentially influenced by the polarity of the extract.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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 designBench or experimental
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

Citations17
Published2007
Admission routes1
Has abstractyes

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