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Record W4410309134 · doi:10.3390/plants14101433

Timing Is Everything: The Metabolic Partitioning of Suberin-Destined Carbon

2025· article· en· W4410309134 on OpenAlexafffund
Jessica L. Sinka, Mark A. Bernards

Bibliographic record

VenuePlants · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuberinMonomerChemistryBiopolymerCell wallCarbon fibersBiosynthesisBiochemistryMetabolismOrganic chemistryPolymerEnzyme

Abstract

fetched live from OpenAlex

Suberin is a cell wall-associated biopolymer that possesses both poly(phenolic) and poly(aliphatic) elements assembled into chemically and spatially distinct domains. Domain-specific monomers are formed via a branched pathway between phenolic and aliphatic metabolisms. Previous transcript accumulation data (RNAseq) from early stages of wound-induced suberization revealed highly coordinated, temporal changes in the regulation of these two branches. Notably, phenolic metabolism-associated transcripts accumulated first, indicating a preference toward phenolic production early on post-wounding. To better understand the dynamics of suberin monomer biosynthesis and assembly, we assessed carbon allocation between phenolic and aliphatic metabolisms during wound-induced suberization. To do so, [13C6]-glucose was administered to wound-healing potato tuber discs at different times post-wounding, and patterns of heavy carbon incorporation into (1) primary metabolites and (2) the suberin polymer were assessed. During early stages of wound-healing, carbon from glucose was rapidly incorporated into phenolic-destined metabolites, while at later stages it was shared between phenolic- and aliphatic-destined metabolites. Similarly, the pattern of labelled carbon incorporation into the poly(aliphatic) domain reflected a greater dedication of carbon towards 18:1 w-hydroxy fatty acid and 18:1 dioic acid (the two most abundant aliphatic monomers in potato suberin) later in the wound healing time course.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.192

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 head0.030
GPT teacher head0.220
Teacher spread0.190 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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