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Characterization of transgenic poplar with ectopic expression of pine cytosolic glutamine synthetase under conditions of varying nitrogen availability

2005· article· en· W2097530439 on OpenAlexaff
Hui‐Min Man, Randall Boriel, Rami T. El‐Khatib, Edward G. Kirby

Bibliographic record

VenueNew Phytologist · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGlutamine synthetaseNitrogen assimilationGlutamineTransgeneEctopic expressionAmmoniumBiologyAmino acidGenetically modified cropsCytosolBiochemistryNitrogenSalicaceaeBotanyHorticultureChemistryEnzymeWoody plantGene

Abstract

fetched live from OpenAlex

The present study addresses the hypothesis that enhanced expression of glutamine synthetase (GS) in transgenic poplar, characterized by the ectopic expression of pine cytosolic GS, results in an enhanced efficiency of nitrogen (N) assimilation and enhanced growth. Transgenic and control poplar were supplied with low and high N levels and the role of ectopic expression of the pine GS in growth and N assimilation was assessed by using amino acid analysis, (15)N enrichment, biochemical analyses, and growth measurements. While leaves of transgenic poplar contained 85% less (P < 0.01) free ammonium than leaves of nontransgenic control plants, leaves of transgenics showed increases in the levels of free glutamine and total free amino acids. Transgenic poplar lines also displayed significant increases in growth parameters when compared with controls grown under both low (0.3 mm) and high (10 mm) nitrate conditions. Furthermore, (15)N-enrichment experiments showed that 27% more (P < 0.05) (15)N was incorporated into structural compounds in transgenic lines than in nontransgenic controls. Using the methods described here, we present direct evidence for increased N assimilation efficiency and growth in GS transgenic lines.

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 score0.096
Threshold uncertainty score0.315

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 head0.022
GPT teacher head0.226
Teacher spread0.204 · 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

Citations94
Published2005
Admission routes1
Has abstractyes

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