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Record W2104622327 · doi:10.1093/treephys/21.6.359

Ascorbic acid changes the pattern of purine metabolism during germination of white spruce somatic embryos

2001· article· en· W2104622327 on OpenAlexafffund
Claudio Stasolla, Natalia Loukanina, Hiroshi Ashihara, Edward C. Yeung, Trevor A. Thorpe

Bibliographic record

VenueTree Physiology · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPurineAscorbic acidBiochemistryAdenosinePurine metabolismInosineEmbryoMetabolismChemistryBiologyEnzymeFood scienceCell biology

Abstract

fetched live from OpenAlex

It has previously been shown that exogenous applications of ascorbic acid (AA) increase the conversion frequency of somatic embryos of white spruce (Picea glauca (Moench) Voss). To determine whether ascorbic acid alters purine metabolism during the early phases of embryo germination, the relative rates of purine salvage and degradation were investigated by following the metabolic fates of exogenously applied [8-14C]adenine, [8-14C]adenosine, and [8-14C]inosine, and the activities of several key enzymes. We demonstrated that both the salvage and the degradation pathways operate during germination. Specifically, adenine and adenosine were mainly salvaged to nucleotides and nucleic acids, whereas an appreciable amount of inosine was degraded to CO2 and ureides. Comparisons of purine metabolism between control and AA-treated embryos showed that exogenous applications of ascorbic acid enhanced the ability of the embryos to take up adenine and adenosine throughout the germination period. Furthermore, the higher enzymatic activities of adenosine kinase and adenine phosphoribosyltransferase were responsible for the larger proportion of adenine and adenosine being salvaged in AA-treated embryos compared with control embryos. Thus, there was a positive correlation between the ability to anabolize purine precursors and successful embryo conversion.

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 score0.070
Threshold uncertainty score0.258

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 head0.228
Teacher spread0.218 · 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

Citations35
Published2001
Admission routes2
Has abstractyes

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