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Record W2000402055 · doi:10.1073/pnas.1213603110

Microfluidic experiments reveal that antifreeze proteins bound to ice crystals suffice to prevent their growth

2013· article· en· W2000402055 on OpenAlexafffund
Yeliz Celik, Ran Drori, Natalya Pertaya-Braun, Aysun Altan, Tyler Barton, Maya Bar Dolev, Alex Groisman, Peter L. Davies, Ido Braslavsky

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsQueen's University
FundersCanadian Institutes of Health ResearchIsrael Science FoundationNational Science Foundation
KeywordsAntifreeze proteinIce crystalsAntifreezeFrost (temperature)ChemistryIce formationBiophysicsMaterials scienceBiochemistryBiologyOrganic chemistryGeologyPhysics

Abstract

fetched live from OpenAlex

Antifreeze proteins (AFPs) are a subset of ice-binding proteins that control ice crystal growth. They have potential for the cryopreservation of cells, tissues, and organs, as well as for production and storage of food and protection of crops from frost. However, the detailed mechanism of action of AFPs is still unclear. Specifically, there is controversy regarding reversibility of binding of AFPs to crystal surfaces. The experimentally observed dependence of activity of AFPs on their concentration in solution appears to indicate that the binding is reversible. Here, by a series of experiments in temperature-controlled microfluidic devices, where the medium surrounding ice crystals can be exchanged, we show that the binding of hyperactive Tenebrio molitor AFP to ice crystals is practically irreversible and that surface-bound AFPs are sufficient to inhibit ice crystal growth even in solutions depleted of AFPs. These findings rule out theories of AFP activity relying on the presence of unbound protein molecules.

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 score0.137
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.046
GPT teacher head0.279
Teacher spread0.233 · 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

Citations171
Published2013
Admission routes2
Has abstractyes

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