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Record W2344360731 · doi:10.1139/cjm-2015-0394

Investigating the expression of F10 and G11 xylanases in <i>Aspergillus niger</i> A09 with qPCR

2016· article· en· W2344360731 on OpenAlexvenueno aff
Cui Shixiu, Tianwen Wang, Hong Hu, Liangwei Liu, Andong Song, Hongge Chen

Bibliographic record

VenueCanadian Journal of Microbiology · 2016
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
Fundersnot available
KeywordsXylanaseXyloseAspergillus nigerXylanBiochemistryHydrolysisBiologyFood scienceChemistryEnzymeFermentation

Abstract

fetched live from OpenAlex

There exist significant differences between the 2 main types of xylanases, family F10 and G11. A clear understanding of the expression pattern of microbial F10 and G11 under different culture conditions would facilitate better production and industrial application of xylanase. In this study, the fungal xylanase producer Aspergillus niger A09 was systematically investigated in terms of induced expression of xylanase F10 and G11. Results showed that carbon and nitrogen sources could influence xylanase F10 and G11 transcript abundance, with G11 more susceptible to changes in culture media composition. The most favorable carbon and nitrogen sources for high G11 and low F10 production by A. niger A09 were xylan (2%) and (NH4)2C2O4 (0.3%), respectively. Following cultivation at 33 °C for 60 h, the highest xylanase activity (1132 IU per gram of wet mycelia) was observed. On the basis of differential gene expression of F10 and G11, as well as their different properties, we deduced that the F10 protein initially targeted xylan and hydrolyzed it into fragments including xylose, after which xylose acted as the inducer of F10 and G11 gene expression. These speculations also accounted for our failure to identify conditions favoring the high production of F10 but a low production of G11.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.168
Teacher spread0.160 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2016
Admission routes1
Has abstractyes

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