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Record W2175471743 · doi:10.3791/53386

Isolation and Compositional Analysis of Plant Cuticle Lipid Polyester Monomers

2015· article· en· W2175471743 on OpenAlexafffund
Seamus Jenkin, Isabel Molina

Bibliographic record

VenueJournal of Visualized Experiments · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsEssar Steel Algoma (Canada)Algoma University
FundersInstitute of GeneticsNatural Sciences and Engineering Research Council of CanadaUniversities Space Research Association
KeywordsCutinSuberinPolyesterCuticle (hair)EndodermisChemistryPlant cuticleCell wallMonomerBiochemistryBotanyPolymerBiologyOrganic chemistryWaxAnatomy

Abstract

fetched live from OpenAlex

Terrestrial plants produce extracellular aliphatic biopolyesters that modify cell walls of specific tissues. Epidermal cells synthesize cutin, a polyester of glycerol and modified fatty acids that constitutes the framework of the cuticle that covers aerial plant surfaces. Suberin is a related lipid polyester that is deposited on the cell walls of certain tissues, including the root endodermis and the periderm of tubers, tree bark and roots. These lipid polymers are highly variable in composition among plant species, and often differ among tissues within a single species. Here, we describe a detailed protocol to study the monomer composition of cutin in Arabidopsis thaliana leaves by sodium methoxide (NaOMe)-catalyzed depolymerisation, derivatization, and subsequent gas chromatography-mass spectrometry (GC/MS) analysis. This method can be used to investigate the monomers of insoluble polyesters isolated from whole delipidated plant tissues bearing either cutin or suberin. The method can by applied not only to characterize the composition of lipid polymers in species not previously analyzed, but also as an analytical tool in forward and reverse genetic approaches to assess candidate gene function.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.105

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 head0.058
GPT teacher head0.348
Teacher spread0.291 · 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

Citations32
Published2015
Admission routes2
Has abstractyes

Explore more

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