MétaCan
Menu
Back to cohort
Record W2050332780 · doi:10.1002/btpr.302

Doubling the catabolic reducing power (NADH) output of <i>Escherichia coli</i> fermentation for production of reduced products

2009· article· en· W2050332780 on OpenAlexfundno aff
Shengde Zhou, Andrew Iverson, W. Scott Grayburn

Bibliographic record

VenueBiotechnology Progress · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsnot available
FundersCanadian Association for the Study of the Liver
KeywordsFermentationEscherichia coliOperonBiochemistryCatabolismAnaerobic exerciseChemistryPyruvate dehydrogenase complexFormateDehydrogenaseBiologyMetabolismEnzymeCatalysisGene

Abstract

fetched live from OpenAlex

Homofermentative production of reduced products requires additional reducing power output (NADH) from glucose catabolism. Anaerobic expression of the pyruvate dehydrogenase complex (PDH, encoded by aceEF-lpd, a normal aerobic operon) is able to provide the additional NADH required for production of reduced products in Escherichia coli fermentation. The multiple promoters (pflBp(1-7)) of pyruvate formate lyase (pflB) were evaluated for anaerobic expression of the aceEF-lpd operon. Four chromosomal constructs, pflBp(1-7)-aceEF-lpd, pflBp(1-6)-aceEF-lpd, pflBp(6,7)-aceEF-lpd, and pflBp6-aceEF-lpd efficiently expressed the PDH complex in anaerobically grown cells. Doubling the reducing power output was achieved when glucose was oxidized to acetyl-CoA through glycolysis and pyruvate oxidation by the anaerobically expressed PDH complex (glucose -->2 acetyl-CoA + 4 NADH). This additional reducing power output can be used for production of reduced products in anaerobic E. coli fermentation.

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 score0.013
Threshold uncertainty score0.468

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 head0.010
GPT teacher head0.248
Teacher spread0.238 · 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

Citations25
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueBiotechnology ProgressSame topicMicrobial Metabolic Engineering and BioproductionFrench-language works237,207