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Record W1572632866 · doi:10.5539/jas.v7n8p156

Cloning and Expression of Cellulosome-Integrating Protein from Aspergillus niger H1 Improves Phosphate Solubilization

2015· article· en· W1572632866 on OpenAlexvenueno aff
Mingbo Gong, Chaoxi Tang

Bibliographic record

VenueJournal of Agricultural Science · 2015
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
Fundersnot available
KeywordsAspergillus nigerOpen reading frameComplementary DNACitric acidBiochemistryEscherichia coliExpression vectorMalic acidBiologyAmino acidGeneMolecular biologyCloning (programming)ChemistrycDNA libraryPeptide sequenceRecombinant DNA

Abstract

fetched live from OpenAlex

A primary cDNA library of Aspergillus niger H1 was constructed using SMART (switching mechanism at the 5' end of RNA transcript) technique. A total of 169 clones had halos on the insoluble phosphate medium, and clone H-47 had clear halos. The full-length cDNA of clone H-47 was 625 bp, with a complete open reading frame (ORF) of 390 bp, encoding a protein of 129 amino acids. Multiple alignment revealed a high degree of homology between the ORF of the clone and other fungi cellulosome-integrating protein (CipC-like). The expression vector of ORF was constructed and transformed into Escherichia coli DH-5a. The transformant (ORF-1) with the CipC-like gene secreted more organic acid when grown in tricalcium phosphate (TCP) medium, with TCP as the sole source of phosphate. E. coli DH5a containing the cipc-like gene secreted methanoic acid, acetic acid, malic acid, and citric acid reached 81.2, 93.3, 50.6, and 147.7 ug mL-1, respectively, within 28 h. These results showed that the expression of the A. niger H1 CipC-like gene in E. coli could enhance organic acid secretion and improve phosphate solubilizing ability.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.200
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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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