MétaCan
Menu
Back to cohort
Record W1974687834 · doi:10.1007/s12284-010-9040-0

Folate Polyglutamylation is Required for Rice Seed Development

2010· article· en· W1974687834 on OpenAlexfundno aff
Nampeung Anukul, Riza Abilgos Ramos, Payam Mehrshahi, Anahi Santoyo Castelazo, Helen L. Parker, Anne Diévart, Nadège Lanau, Delphine Mieulet, Gregory A. Tucker, Emmanuel Guiderdoni, David A. Barrett, Malcolm J. Bennett

Bibliographic record

VenueRice · 2010
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsnot available
FundersNottingham Trent UniversityAgropolis FondationTrent UniversityFord Foundation
KeywordsBiologyGeneEnzymeGene expressionKnockout mouseGene expression profilingBiochemistry

Abstract

fetched live from OpenAlex

Abstract In plants, polyglutamylated folate forms account for a significant proportion of the total folate pool. Polyglutamylated folate forms are produced by the enzyme folylpolyglutamate synthetase (FPGS). The FPGS enzyme is encoded by two genes in rice, Os03g02030 and Os10g35940. Os03g02030 represents the major expressed form in developing seed. To determine the function of this FPGS gene in rice, a T-DNA knockout line was characterised. Disrupting Os03g02030 gene expression resulted in delayed seed filling. LC-MS/MS-based metabolite profiling revealed that the abundance of mono- and polyglutamylated folate forms was significantly decreased in seeds of the knockout line. RT-qPCR detected an increase in the transcript abundance of folate biosynthesis genes in seed of the knockout plant, whereas the folate deglutamating enzyme γ-glutamyl hydrolase mRNA level was reduced. Our study has uncovered a novel role for folate polyglutamylation during rice seed development and a potential feedback mechanism to maintain folate abundance.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.033
GPT teacher head0.327
Teacher spread0.295 · 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

Citations19
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueRiceSame topicFolate and B Vitamins ResearchFrench-language works237,207