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A role for caleosin in degradation of oil‐body storage lipid during seed germination

2006· article· en· W2007053023 on OpenAlexaff
Marianne K. Poxleitner, Sally W. Rogers, Lacey Samuels, John Browse, John C. Rogers

Bibliographic record

VenueThe Plant Journal · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsUniversity of British Columbia
FundersU.S. Department of AgricultureNational Science Foundation
KeywordsVacuoleGerminationMutantInternalizationCell biologyWild typeStorage proteinBiologyBiochemistryChemistryBiophysicsBotanyCellCytoplasmGene

Abstract

fetched live from OpenAlex

Caleosin is a Ca(2+)-binding oil-body surface protein. To assess its role in the degradation of oil-bodies, two independent insertion mutants lacking caleosin were studied. Both mutants demonstrated significant delay of breakdown of the 20:1 storage lipid at 48 and 60 h of germination. Additionally, although germination rates for seeds were not affected by the mutations, mutant seedlings grew more slowly than wild type when measured at 48 h of germination, a defect that was corrected with continued growth for 72 and 96 h in the light. After 48 h of germination, wild-type central vacuoles had smooth contours and demonstrated internalization of oil bodies and of membrane containing alpha- and delta-tonoplast intrinsic proteins (TIPs), markers for protein storage vacuoles. In contrast, mutant central vacuoles had distorted limiting membranes displaying domains with clumps of the two TIPs, and they contained fewer oil bodies. Thus, during germination caleosin plays a role in the degradation of storage lipid in oil bodies. Its role involves both the normal modification of storage vacuole membrane and the interaction of oil bodies with vacuoles. The results indicate that interaction of oil bodies with vacuoles is one mechanism that contributes to the degradation of storage lipid.

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 score0.083
Threshold uncertainty score0.179

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations182
Published2006
Admission routes1
Has abstractyes

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