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Record W2377383035

Screening, mutation breeding and medium optimization of glucan-producing lactic acid bacteria

2015· article· en· W2377383035 on OpenAlexaff
Hua Liu

Bibliographic record

VenueFood Science and Technology International · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsScience North
Fundersnot available
KeywordsLeuconostoc mesenteroidesGlucanStrain (injury)Lactic acidBacteriaFood scienceSucroseMutantChemistryBiologyMicrobiologyBiochemistryGenetics
DOInot available

Abstract

fetched live from OpenAlex

One lactic acid bacteria strain 2-17 with the glucan-producing capacity of(5.24±0.14) g/L was isolated from the commercial pickles and the pickles made in the laboratory. This strain was identifi ed as Leuconostoc mesenteroides subsp. mesenteroides by a series of physiological and biochemical tests and analysing the 16 SrDNA sequence. The glucan-producing capacity of the strain was improved by exposing the strain to nitrosoguanidine and UV irradiation successively, and the optimal mutagenic condition was determined as the following: the strain was first cultured in the MRS medium for 9h and then was exposed to 0.5 mg/m L nitrosoguanidine for 80 minutes followed by exposure to UV radiation(30 W) from distance of 45.0 cm for 30 s; then the culture was treated by the same nitrosoguanidine-UV complex mutation again. After that, one mutant UN2-18 with the glucan-producing capacity of(7.54±0.08) g/L was obtained and the glucan production of this mutant was 43.89% higher than that of its original strain. In addition, the strain obtained by continuous subculturing the mutant UN2-18 for 10 generations leveled out its glucan production by around 7.5 g/L. The optimal culture conditions of the cheap medium were determined for 2% soybean meal hydrolysised with degree of 10%, 10% sucrose and 2% K2HPO4. The glucan production of UN2-18 was(34.4±0.07) g/L, improving by 3.56 fold.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.010
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.258
Teacher spread0.241 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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