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Record W2409989654 · doi:10.1139/cjm-2016-0248

Efficient production of nonactin by <i>Streptomyces griseus</i> subsp. <i>griseus</i>

2016· article· en· W2409989654 on OpenAlexvenueno aff
Yulian Zhan, Shaolun Zheng

Bibliographic record

VenueCanadian Journal of Microbiology · 2016
Typearticle
Languageen
FieldChemistry
TopicSynthetic Organic Chemistry Methods
Canadian institutionsnot available
Fundersnot available
KeywordsStreptomyces griseusStreptomycetaceaeFermentationActinomycetalesIonophoreStreptomycesYield (engineering)BiologyBiochemistryAmberliteChemistryBacteriaOrganic chemistry

Abstract

fetched live from OpenAlex

Here we report the production of the cyclic macrotetrolide nonactin from the fermentation culture of Streptomyces griseus subsp. griseus. Nonactin is a member of a family of naturally occurring cyclic ionophores known as the macrotetrolide antibiotics. Our fermentation procedure of Streptomyces griseus was performed at 30 °C and 200 rev·min(-1) for 5 days on a rotary shaker. Diaion HP-20 and Amberlite XAD-16 were added to the fermentation medium. Isolated yield of nonactin was up to 80 mg·L(-1) using our methodology. Nonactin is commonly known as an ammonium ionophore and also exhibits antibacterial, antiviral, and antitumor activities. It is also widely used for the preparation of ion-selective electrodes and sensors. Chemical synthesis of nonactin has been achieved by some groups; however, overall yields are very low, making efficient biosynthesis an attractive means of production.

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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