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Record W2021053635 · doi:10.1139/w02-107

Tannic acid induces transcription of laccase gene<i>cglcc1</i>in the white-rot fungus<i>Coriolopsis gallica</i>

2002· article· en· W2021053635 on OpenAlexvenueno aff
José Ma Carbajo, Howard Junca, María C. Terrón, Tania González, Ernesto Zapico, Aldo E. González

Bibliographic record

VenueCanadian Journal of Microbiology · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsnot available
FundersComisión Interministerial de Ciencia y TecnologíaUniversidad Autónoma de MadridComunidad de Madrid
KeywordsLaccaseTannic acidFungusBiologyBotanyMicrobiologyAscomycotaGeneChemistryEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Laccase, a phenoloxidase enzyme secreted by white-rot fungi, has a significant role in the degradation of lignin and environmental pollutants. Coriolopsis gallica is a ligninolytic basidiomycete that produces high levels of this extracellular enzyme. A laccase gene cglcc1 from this fungus has been cloned and sequenced. The capacity of C. gallica to efficiently degrade polyphenols has been successfully applied in our laboratory to the biotreatment and decolorization of several industrial wastewaters. This study focused on the effect of tannic acid, a natural compound widely distributed in plants, on the production of laccase activity by C. gallica. Our results showed an evident increase of extracellular laccase levels when C. gallica was grown in the presence of tannic acid. Concentrations of 50 and 100 microM of this compound increased laccase activity when compared with control samples grown without tannic acid. In addition, we found an increase in laccase transcript levels in C. gallica grown in culture media supplemented with tannic acid. The role of tannic acid was shown to be an inductor of laccase activity in this fungus, due to the enhancement of expression of the laccase gene at the transcriptional level.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.938

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.189
Teacher spread0.163 · 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

Citations31
Published2002
Admission routes1
Has abstractyes

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