MétaCan
Menu
Back to cohort
Record W2772192734 · doi:10.1063/1.5002145

Stability of the helical configuration of an intrinsically straight semiflexible biopolymer inside a cylindrical cell

2017· article· en· W2772192734 on OpenAlexafffund
Zicong Zhou, Béla Joós, Chen‐Xu Wu

Bibliographic record

VenueAIP Advances · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsCarleton UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Science and Technology of the People's Republic of China
KeywordsHelix (gastropod)BiopolymerProtein filamentTorqueMreBMaterials scienceCondensed matter physicsChemical physicsMechanicsClassical mechanicsPhysicsNanotechnologyChemistryPolymerThermodynamicsComposite materialCellCytoskeleton

Abstract

fetched live from OpenAlex

We examine the effects of the external force, torque, temperature, confinement, and excluded volume interactions (EVIs) on the stability of the helical configuration of an intrinsically straight semiflexible biopolymer inside a cylindrical cell. We find that to stabilize a helix, the confinement from both ends of the cell is more effective than a uniaxial force. We show that under a uniaxial force and in absence of confinement from bottom of the cell, a stable helix is very short. Our results reveal that to maintain a low pitch helix, a torque acting at both ends of the filament is a necessity, and the confinement can reduce the required torque to less than half making it much easier to form a stable helix. Moreover, we find that thermal fluctuations and EVIs have little impact on the stability of a helix. Our results can help understand the existence of the helix and ring configurations of some semiflexible biopolymers, such as MreB homologs, inside a rod-shaped bacteria.

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 score0.010
Threshold uncertainty score0.241

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 head0.268
Teacher spread0.259 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueAIP AdvancesSame topicProtein Structure and DynamicsFrench-language works237,207