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Record W1993778572 · doi:10.1002/bit.20737

The expression of a <i>Pichia stipitis</i> xylose reductase mutant with higher <i>K</i><sub>M</sub> for NADPH increases ethanol production from xylose in recombinant <i>Saccharomyces cerevisiae</i>

2005· article· en· W1993778572 on OpenAlexaff
Marie Jeppsson, Oskar Bengtsson, Katja Franke, Hung Lee, Bärbel Hahn‐Hägerdal, Marie F. Gorwa‐Grauslund

Bibliographic record

VenueBiotechnology and Bioengineering · 2005
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPichia stipitisXyloseXylitolBiochemistryChemistryFermentationYeastXylose metabolismNAD+ kinaseCofactorZymomonas mobilisEthanol fuelEnzyme

Abstract

fetched live from OpenAlex

Xylose fermentation by Saccharomyces cerevisiae requires the introduction of a xylose pathway, either similar to that found in the natural xylose-utilizing yeasts Pichia stipitis and Candida shehatae or similar to the bacterial pathway. The use of NAD(P)H-dependent XR and NAD(+)-dependent XDH from P. stipitis creates a cofactor imbalance resulting in xylitol formation. The effect of replacing the native P. stipitis XR with a mutated XR with increased K(M) for NADPH was investigated for xylose fermentation to ethanol by recombinant S. cerevisiae strains. Enhanced ethanol yields accompanied by decreased xylitol yields were obtained in strains carrying the mutated XR. Flux analysis showed that strains harboring the mutated XR utilized a larger fraction of NADH for xylose reduction. The overproduction of the mutated XR resulted in an ethanol yield of 0.40 g per gram of sugar and a xylose consumption rate of 0.16 g per gram of biomass per hour in chemostat culture (0.06/h) with 10 g/L glucose and 10 g/L xylose as carbon source.

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 score0.003

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)0.0010.000

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 head0.181
Teacher spread0.175 · 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

Citations151
Published2005
Admission routes1
Has abstractyes

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