MétaCan
Menu
Back to cohort
Record W2534095088 · doi:10.1039/c6sm01184e

Effects of molecular crowding and confinement on the spatial organization of a biopolymer

2016· article· en· W2534095088 on OpenAlexaff
Chanil Jeon, Youngkyun Jung, Bae‐Yeun Ha

Bibliographic record

VenueSoft Matter · 2016
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBiopolymerCrowdingChemical physicsMonomerCompactionChain (unit)Excluded volumeFolding (DSP implementation)PolymerChemistryVolume fractionMacromolecular crowdingIsostructuralProtein foldingNanotechnologyCrystallographyMaterials sciencePhysicsPhysical chemistryOrganic chemistryBiologyBiochemistryComposite material

Abstract

fetched live from OpenAlex

A chain molecule can be entropically collapsed in a crowded medium in a free or confined space. Here, we present a unified view of how molecular crowding collapses a flexible polymer in three distinct spaces: free, cylindrical, and (two-dimensional) slit-like. Despite their seeming disparities, a few general features characterize all these cases, even though the ϕc-dependence of chain compaction differs between the two cases: a > ac and a < ac, where ϕc is the volume fraction of crowders, a is the monomer size, and ac is the crowder size. For a > ac (applicable to a coarse-grained model of bacterial chromosomes), chain size depends on the ratio aϕc/ac, and “full” compaction occurs universally at aϕc/ac ≈ 1; for ac > a (relevant for protein folding), it is controlled by ϕc alone and crowding has a modest effect on chain size in a cellular environment (ϕc ≈ 0.3). Also for a typical parameter range of biological relevance, molecular crowding can be viewed as effectively reducing the solvent quality, independent of confinement.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.003
GPT teacher head0.173
Teacher spread0.170 · 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

Citations50
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueSoft MatterSame topicMaterial Dynamics and PropertiesFrench-language works237,207