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Record W1971192728 · doi:10.1021/la7023204

Quantifying Blood Platelet Morphological Changes by Dissipation Factor Monitoring in Multilayer Shells

2008· article· en· W1971192728 on OpenAlexafffund
Julien Fatisson, Yahye Merhi, Maryam Tabrizian

Bibliographic record

VenueLangmuir · 2008
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversité de MontréalMcGill UniversityMontreal Heart Institute
FundersCanadian Institutes of Health ResearchFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsQuartz crystal microbalanceCytoskeletonAdhesionPolyelectrolyteSurface modificationBiophysicsCell adhesionDissipationChemistryPlateletNanotechnologyIntegrinMaterials scienceCellComposite materialPolymerBiochemistry

Abstract

fetched live from OpenAlex

The ability of electrostatically driven layer-by-layer (LbL) assembly to adapt to the morphological features of a template was explored. Subtle cytoskeletal changes in blood platelets became traceable through energy dissipation monitoring in multilayered shells using microgravimetric measurements. This LbL coating was sequentially deposited on protein-modified chips onto which platelets were adhered. In addition to consequently improving the signal sensitivity, the LbL shell acted in synergy with the cell, allowing the determination and quantification of cytoskeletal changes induced by the specific cell adhesion to the protein-modified chip surface used with a quartz crystal microbalance with dissipation. The difference in cell morphology, as a result of the optimization of specific interactions between the protein layer and cell membrane integrins induced viscoelastic changes in the polyelectrolyte shell, thereby providing quantitative data on platelet conformational changes upon their adhesion to protein-modified chip surface.

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 score0.053
Threshold uncertainty score0.455

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 head0.105
GPT teacher head0.330
Teacher spread0.224 · 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

Citations19
Published2008
Admission routes2
Has abstractyes

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