MétaCan
Menu
Back to cohort
Record W2104158570 · doi:10.1071/ch09112

Immobilized Whole Cells as Effective Catalysts for Chiral Alcohol Production

2009· article· en· W2104158570 on OpenAlexfundno aff
Jeck Fei Ng, Stephan Jaenicke

Bibliographic record

VenueAustralian Journal of Chemistry · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsBiocatalysisChemistryCatalysisAlcohol dehydrogenaseEnantiomeric excessContinuous stirred-tank reactorBioreactorEscherichia coliBatch reactorFermentationAlcoholChromatographyOrganic chemistryEnantioselective synthesisBiochemistryReaction mechanism

Abstract

fetched live from OpenAlex

Recombinant Escherichia coli overexpressing the gene LbADH, which encodes for an alcohol dehydrogenase from Lactobacillus brevis, was successfully transformed and cultured. The cells are able to catalyze the reduction of pro-chiral ketones, e.g. ethyl acetoacetate into R-(–)ethyl hydroxybutyrate (EHB) with high conversion and enantiomeric excess >99%. Immobilizing the whole cells in alginate beads leads to a catalyst with improved stability and ease of handling while maintaining the high activity of the free cells. The whole-cell catalyst was tested in a stirred batch reactor (CSTR) and in a continuously operated packed-bed reactor. An Mg2+ concentration of 2 mM was crucial for maintaining the activity of the biocatalyst. After a partial optimization of the process conditions, a productivity of 1.4 gEHB gwcw–1 h–1 could be maintained in a continuous flow reactor over a prolonged period of time.

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)0.000
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 score0.019
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.256
Teacher spread0.250 · 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

Citations11
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAustralian Journal of ChemistrySame topicMicrobial Metabolic Engineering and BioproductionFrench-language works237,207