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Record W2033610915 · doi:10.1021/bm400466e

Thermal Reversal of Polyvalent Choline Phosphate, a Multivalent Universal Biomembrane Adhesive

2013· article· en· W2033610915 on OpenAlexafffund
Xifei Yu, Yuquan Zou, Sonja Horte, Johan Janzen, Jayachandran N. Kizhakkedathu, Donald E. Brooks

Bibliographic record

VenueBiomacromolecules · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsLower critical solution temperatureChemistryPolymerBiophysicsMacromoleculeBiological membraneBiomoleculeMembraneNanomedicinePolymer chemistryCopolymerNanotechnologyBiochemistryOrganic chemistryMaterials scienceNanoparticleBiology

Abstract

fetched live from OpenAlex

Multivalent macromolecular associations are widely observed in biological systems and are increasingly being utilized in bioengineering, nanomedicine, and biomaterial applications. Control over such associations usually demands an ability to reverse the multivalent binding. While in principle this can be done with binding site competitive inhibitors, dissociation is difficult in practice due to limited site accessibility when the macromolecule is bound. We demonstrate here efficient binding reversal of multivalent linear copolymers that adhere to any mammalian cell via the universal mechanism based on choline phosphate (CP) groups binding to phosphatidyl choline (PC)-containing biomembranes. Using a smart linear polymer exhibiting a lower critical solution temperature (LCST), we take advantage of the thermal contraction of the polymer above the LCST, which reduces accessibility of the CP groups to cell membrane PC lipids. The polymer construct can then desorb from the cell surface, reversing all effects of multivalent polymer adhesion on the cell.

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 score0.011
Threshold uncertainty score0.926

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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

Citations30
Published2013
Admission routes2
Has abstractyes

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