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Record W2149198535 · doi:10.1093/jxb/erm287

Over-expression of UDP-glucose pyrophosphorylase in hybrid poplar affects carbon allocation

2007· article· en· W2149198535 on OpenAlexafffund
Heather D. Coleman, Thomas Canam, Kyu‐Young Kang, David Ellis, Shawn D. Mansfield

Bibliographic record

VenueJournal of Experimental Botany · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of British Columbia
FundersCanadian Forest ServiceU.S. Forest Service
KeywordsMetaboliteSugarBiochemistryBiologyLigninStarchSalicylic acidCelluloseShootBotanyChemistry

Abstract

fetched live from OpenAlex

The effects of the over-expression of the Acetobacter xylinum UDP-glucose pyrophosphorylase (UGPase) under the control of the tandem repeat Cauliflower Mosaic Virus promoter (2x35S) on plant metabolism and growth were investigated in hybrid poplar (Populus albaxgrandidentata). Transcript levels, enzyme activity, growth parameters, leaf morphology, structural and soluble carbohydrates, and soluble metabolite levels were quantified in both transgenic and wild-type trees. Transgenic 2x35S::UGPase poplar showed impaired growth rates, displaying reduced height growth and stem diameter. Morphologically, 2x35S::UGPase trees had elongated axial shoots, and leaves that were substantially smaller in size when compared with wild-type trees at equivalent developmental stages. Biochemical analysis revealed significant increases in soluble sugar, starch, and cellulose contents, and concurrent decreases in lignin content. Lignin monomer composition was altered in favour of syringyl moieties. Detailed soluble metabolite analysis revealed that 2x35S::UGPase trees had as much as a 270-fold increase in the salicylic acid 2-O-beta-D-glucoside (SAG), a compound typically associated with the stress response. These data suggest that while it is possible to alter the allocation of carbon in favour of cellulose biosynthesis, whole plant changes result in unexpected decreases in growth and an increase in defence metabolites.

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 score0.023
Threshold uncertainty score0.331

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 head0.252
Teacher spread0.246 · 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

Citations76
Published2007
Admission routes2
Has abstractyes

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