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Record W2121787089 · doi:10.1111/nph.12084

<scp><i>SHORT INTERNODES/STYLISH</i></scp> genes, regulators of auxin biosynthesis, are involved in leaf vein development in <i><scp>A</scp>rabidopsis thaliana</i>

2013· article· en· W2121787089 on OpenAlexaff
Tammy Baylis, Izabela Cierlik, Eva Sundberg, Jim Mattsson

Bibliographic record

VenueNew Phytologist · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsSimon Fraser University
FundersVetenskapsrådetTel Aviv UniversitySvenska Forskningsrådet Formas
KeywordsPrimordiumAuxinMutantBiologyCell biologyPlant stemTranscription factorArabidopsis thalianaBotanyGeneGenetics

Abstract

fetched live from OpenAlex

Leaves depend on highly developed venation systems to collect fixed carbon for transport and to distribute water. We hypothesized that local regulation of auxin biosynthesis plays a role in vein development. To this effect, we assessed the role of the SHORT INTERNODES/STYLISH (SHI/STY) gene family, zinc-finger transcription factors linked to regulation of auxin biosynthesis, in Arabidopsis thaliana leaf vein development. Gene functions were assessed by a combination of high-resolution spatio-temporal expression analysis of promoter-marker lines and phenotypic analysis of plants homozygous for single and multiple mutant combinations. The SHI/STY genes showed expression patterns with variations on a common theme of activity in incipient and developing cotyledon and leaf primordia, narrowing to apices and hydathode regions. Mutant analysis of single to quintuple mutant combinations revealed dose-dependent defects in vein patterning affecting multiple vein traits, most notably in cotyledons. Here we demonstrate that local regulation of auxin biosynthesis is an important aspect of leaf vein development. Our findings also support a model in which auxin synthesized at the periphery of primordia affects vein development.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.029
GPT teacher head0.236
Teacher spread0.207 · 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 designObservational
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

Citations68
Published2013
Admission routes1
Has abstractyes

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