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Record W2565403369 · doi:10.1111/pce.12889

Ice and anti‐nucleating activities of an ice‐binding protein from the annual grass, <i>Brachypodium distachyon</i>

2016· article· en· W2565403369 on OpenAlexaff
Melissa Bredow, Heather E. Tomalty, Lindsay Smith, Virginia K. Walker

Bibliographic record

VenuePlant Cell & Environment · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsQueen's University
Fundersnot available
KeywordsBrachypodium distachyonIce crystalsIce nucleusBrachypodiumNucleationChemistryCrystallographyBiophysicsBotanyMaterials scienceBiologyAstrobiologyCell biologyBiochemistryPhysicsMeteorologyOrganic chemistry

Abstract

fetched live from OpenAlex

Plants exposed to sub-zero temperatures face unique challenges that threaten their survival. The growth of ice crystals in the extracellular space can cause cellular dehydration, plasma membrane rupture and eventual cell death. Additionally, some pathogenic bacteria cause tissue damage by initiating ice crystal growth at high sub-zero temperatures through the use of ice-nucleating proteins (INPs), presumably to access nutrients from lysed cells. An annual species of brome grass, Brachypodium distachyon (Bd), produces an ice-binding protein (IBP) that shapes ice with a modest depression of the freezing point (~0.1 °C at 1 mg/mL), but high ice-recrystallization inhibition (IRI) activity, allowing ice crystals to remain small at near melting temperatures. This IBP, known as BdIRI, is unlike other characterized IBPs with a single ice-binding face, as mutational analysis indicates that BdIRI adsorbs to ice on two faces. BdIRI also dramatically attenuates the nucleation of ice by bacterial INPs (up to -2.26 °C). This 'anti-nucleating' activity is significantly higher than previously documented for any IBP.

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 score0.090
Threshold uncertainty score0.429

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 head0.009
GPT teacher head0.175
Teacher spread0.166 · 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

Citations27
Published2016
Admission routes1
Has abstractyes

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