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Record W2089788229 · doi:10.1093/jxb/ert313

FOUR LIPS and MYB88 conditionally restrict the G1/S transition during stomatal formation

2013· article· en· W2089788229 on OpenAlexafffund
EunKyoung Lee, Xuguang Liu, Yana Eglit, Fred D. Sack

Bibliographic record

VenueJournal of Experimental Botany · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGuard cellMitosisCell biologyBiologyCell divisionMutantBotanyGeneticsCellGene

Abstract

fetched live from OpenAlex

Consistent with their valve-like function in shoot-atmosphere gas exchange, guard cells are smaller than other epidermal cells and usually harbour 2C DNA levels in diploid plants. The paralogous Arabidopsis R2R3 MYB transcription factors, FOUR LIPS and MYB88, ensure that stomata contain just two guard cells by restricting mitosis. The loss of both FLP and MYB88 function in flp myb88 double mutants induces repeated mitotic divisions that lead to the formation of clusters of stomata in direct contact. By contrast, CYCLIN DEPENDENT KINASE B1 function is required for the symmetric division that precedes stomatal maturation. It was found that blocking mitosis by chemically disrupting microtubules or by the combined loss of FLP/MYB88 and CDKB1 function, causes single (undivided) guard cells (sGCs) to enlarge and attain mean DNA levels of up to 10C. The loss of both FLP and CDKB1 function also dramatically increased plastid number, led to the formation of multiple nuclei in GCs, altered GC and stomatal shape, and disrupted the fate of lineage-specific stem cells. Thus, in addition to respectively restricting and promoting symmetric divisions, FLP and CDKB1 together also conditionally restrict the G1/S transition and chloroplast and nuclear number, and normally maintain fate and developmental progression throughout the stomatal cell lineage.

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 score0.430
Threshold uncertainty score0.217

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 head0.016
GPT teacher head0.228
Teacher spread0.211 · 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

Citations27
Published2013
Admission routes2
Has abstractyes

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