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Record W2906915740 · doi:10.1073/pnas.1818099116

Ionic stress enhances ER–PM connectivity via phosphoinositide-associated SYT1 contact site expansion in <i>Arabidopsis</i>

2019· article· en· W2906915740 on OpenAlexafffund
EunKyoung Lee, Steffen Vanneste, Jessica Pérez‐Sancho, Francisco Benítez‐Fuente, M. Strelau, Alberto P. Macho, Miguel A. Botella, Jiřı́ Friml, Abel Rosado

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Reproductive Biology
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of HealthMinisterio de Economía y CompetitividadNatural Sciences and Engineering Research Council of CanadaMinisterio de Ciencia y TecnologíaGovernment of Canada
KeywordsEndoplasmic reticulumArabidopsisUnfolded protein responseCell biologyAdaptation (eye)BiologyChemistryNeuroscienceBiochemistryMutantGene

Abstract

fetched live from OpenAlex

Significance Interorganelle connectivity and nonvesicular information transfer are hallmarks of biological systems. These processes facilitate communication between organelles, allowing them to adapt to changing cellular environments. In plants, the endoplasmic reticulum (ER)–plasma membrane (PM) contact sites (EPCSs) physically connect the cortical ER and the PM, and act as general platforms for Ca 2+ homeostasis regulation and the cellular adaptation to environmental stresses. Our identification of ionic stress and PM phosphoinositides as enhancers of ER–PM connectivity advances our understanding of how stress influences interorganelle communication. Furthermore, our analyses of the spatiotemporal regulation of EPCS expansion highlights unique mechanisms that plants activate to maintain interorganelle communication during long-term exposure to environmental stress, not described in other eukaryotes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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 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

Citations101
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicPlant Reproductive BiologyFrench-language works237,207