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Record W2795062686 · doi:10.1101/292292

Nonlinear calcium ion waves along actin filaments control active hair–bundle motility

2018· preprint· en· W2795062686 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldComputer Science
TopicNonlinear Dynamics and Pattern Formation
Canadian institutionsUniversity of Alberta
FundersSerbian Academy of Sciences and ArtsMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsCalciumBundleMotilityNonlinear systemActinMyosinBiophysicsHair cellChemistryMaterials sciencePhysicsInner earAnatomyBiologyCell biologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Actin filaments are highly dynamic semiflexible cellular biopolymers with diverse functions, such as cell motility. They also play the role of conduits for propagation of calcium ion waves. In this paper, we propose a new biophysical model that describes how actin filaments with their polyelectrolyte properties serve as pathways for calcium ion flows in hair cells. We show this can be utilized for the tuning of force–generating myosin motors. In this model, we unify the calcium nonlinear dynamics involved in the control of the myosin adaptation motors with mechanical displacements of hair– bundles. The model shows that the characteristic time scales fit reasonably well with the available experimental data for spontaneous oscillations in the inner ear. This model offers promises to fill a gap in our understanding of the role of calcium ion nonlinear dynamics in the regulation of processes in the auditory cells of the inner ear.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.237
Teacher spread0.220 · 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