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Record W2588677334 · doi:10.1111/nph.14468

Sticking to cellulose: exploiting Arabidopsis seed coat mucilage to understand cellulose biosynthesis and cell wall polysaccharide interactions

2017· review· en· W2588677334 on OpenAlexaff
Jonathan S. Griffiths, Helen North

Bibliographic record

VenueNew Phytologist · 2017
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides and Plant Cell Walls
Canadian institutionsNational Research Council Canada
FundersFP7 People: Marie-Curie ActionsAgreenSkills
KeywordsCelluloseCell wallMucilageHemicellulosePolysaccharideSecondary cell wallArabidopsisXylanPectinXyloglucanBiochemistryBiosynthesisChemistryBiologyBotanyEnzymeGene

Abstract

fetched live from OpenAlex

The cell wall defines the shape of cells and ultimately plant architecture. It provides mechanical resistance to osmotic pressure while still being malleable and allowing cells to grow and divide. These properties are determined by the different components of the wall and the interactions between them. The major components of the cell wall are the polysaccharides cellulose, hemicellulose and pectin. Cellulose biosynthesis has been extensively studied in Arabidopsis hypocotyls, and more recently in the mucilage-producing epidermal cells of the seed coat. The latter has emerged as an excellent system to study cellulose biosynthesis and the interactions between cellulose and other cell wall polymers. Here we review some of the major advances in our understanding of cellulose biosynthesis in the seed coat, and how mucilage has aided our understanding of the interactions between cellulose and other cell wall components required for wall cohesion. Recently, 10 genes involved in cellulose or hemicellulose biosynthesis in mucilage have been identified. These discoveries have helped to demonstrate that xylan side-chains on rhamnogalacturonan I act to link this pectin directly to cellulose. We also examine other factors that, either directly or indirectly, influence cellulose organization or crystallization in mucilage.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.121
GPT teacher head0.312
Teacher spread0.191 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations70
Published2017
Admission routes1
Has abstractyes

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