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Record W1980545405 · doi:10.1021/bi100468v

Kinetics and Morphology of Self-Assembly of an Elastin-like Polypeptide Based on the Alternating Domain Arrangement of Human Tropoelastin

2010· article· en· W1980545405 on OpenAlexaff
Judith T. Cirulis, Fred W. Keeley

Bibliographic record

VenueBiochemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsTropoelastinElastinCoacervateKineticsBiophysicsChemistryExtracellular matrixPhase (matter)NucleationCrystallographyMaterials scienceBiochemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Elastin is the polymeric extracellular matrix protein responsible for the properties of extensibility and elastic recoil in tissues such as arterial blood vessels, lung parenchyma, and skin. Both tropoelastin (TE), the full-length monomeric form of elastin, and elastin-like polypeptides (ELPs), based on sequences and domain arrangements of TE, have the intrinsic ability to undergo organized self-assembly into network structures through a process of temperature-induced phase separation or coacervation. It has been suggested that this property plays a role in in vivo formation of the extracellular elastic matrix. In general, the temperature at which phase separation takes place has been taken as the measure of propensity for self-assembly. However, this phase separation is only the first step in a more complex, multistep process of network formation. We have previously shown that analysis of spectrophotometric data allows extraction of kinetic parameters describing both early (coacervation) and later (maturation) steps of the self-assembly process. Here, using a well-characterized ELP containing three hydrophobic domains flanking two cross-linking domains, we describe the effects of temperature, polypeptide concentration, and solution conditions on the kinetics of self-assembly, providing insights into possible mechanisms for the spontaneous organization of such ELPs into extended networks.

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 score0.002
Threshold uncertainty score0.478

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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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

Citations51
Published2010
Admission routes1
Has abstractyes

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