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Record W2604004670 · doi:10.1242/jcs.202275

Chloroplast behaviour and interactions with other organelles in <i>Arabidopsis thaliana</i> pavement cells

2017· article· en· W2604004670 on OpenAlexafffund
Kiah A. Barton, Michael R. Wozny, Neeta Mathur, Erica-Ashley Jaipargas, Jaideep Mathur

Bibliographic record

VenueJournal of Cell Science · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyArabidopsis thalianaChloroplastOrganelleArabidopsisCell biologyBotanyGeneticsGene

Abstract

fetched live from OpenAlex

ABSTRACT Chloroplasts are a characteristic feature of green plants. Mesophyll cells possess the majority of chloroplasts and it is widely believed that, with the exception of guard cells, the epidermal layer in most higher plants does not contain chloroplasts. However, recent observations on Arabidopsis thaliana have shown a population of chloroplasts in pavement cells that are smaller than mesophyll chloroplasts and have a high stroma to grana ratio. Here, using stable transgenic lines expressing fluorescent proteins targeted to the plastid stroma, plasma membrane, endoplasmic reticulum, tonoplast, nucleus, mitochondria, peroxisomes, F-actin and microtubules, we characterize the spatiotemporal relationships between the pavement cell chloroplasts (PCCs) and their subcellular environment. Observations on the PCCs suggest a source–sink relationship between the epidermal and the mesophyll layers, and experiments with the Arabidopsis mutants glabra2 (gl2) and immutans (im), which show altered epidermal plastid development, underscored their developmental plasticity. Our findings lay down the foundation for further investigations aimed at understanding the precise role and contributions of PCCs in plant interactions with the environment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), 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

Citations63
Published2017
Admission routes2
Has abstractyes

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