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Record W3209642966 · doi:10.82308/15719

A rheometer-confocal platform for the study of cell deformation in three-dimensional environments

2019· article· en· W3209642966 on OpenAlexfundno aff
Yuanhang Wang

Bibliographic record

VenueeScholarship@McGill (McGill) · 2019
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsRheometerConfocalDeformation (meteorology)Computer visionArtificial intelligenceComputer scienceMaterials scienceRheologyOpticsComposite materialPhysics

Abstract

fetched live from OpenAlex

In vivo, cells undergo various external mechanical loadings. Mechanical forces have effects on cellular behavior and activities, including aspects such as cell morphology, migration, and protein expression. Such interactions between cells and their surroundings are essential, but not clearly understood. An in-depth understanding of external mechanical forces' impacts on cells requires advanced experimental approaches. Here I present a customized platform that combines two instruments: a rheometer and a confocal microscope. I then tested the platform with sub-micron sized fluorescent beads embedded in a homogeneous gel, by comparing optically measured strain with applied strain values. This rheometer-confocal platform is ideal for studying cellular interactions with surroundings, and cell activities specifically under shear load. With the calibrated system, I studied the relations between externally applied strain and internal cell strain. Cells were cultured within the three-dimensional hydrogel matrices and sheared by the rheometer. The internal strain was indicated by the fluorescent intensity ratio of a recombinant protein construct measured by the confocal microscope. The platform enables simultaneous observation and mechanical manipulation of the sample, providing a powerful tool to investigate the mechanical interactions between cells and their surroundings.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.227
Teacher spread0.203 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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