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Record W2106763223 · doi:10.1002/cm.20391

Mechanical dynamics of single cells during early apoptosis

2009· article· en· W2106763223 on OpenAlexaff
Andrew E. Pelling, Farlan Veraitch, Carol Pui‐Kei Chu, Chris Mason, Michael A. Horton

Bibliographic record

VenueCell Motility and the Cytoskeleton · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of Ottawa
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilAgence Nationale pour la Gestion des Déchets Radioactifs
KeywordsCell biologyBiologyCytoskeletonMitosisApoptosisCellProgrammed cell deathBiochemistry

Abstract

fetched live from OpenAlex

Dynamic mechanical properties of cells are becoming recognized as indicators and regulators of physiological processes such as differentiation, malignant phenotypes and mitosis. A key process in development and homeostasis is apoptosis and whilst the molecular control over this pathway is well studied, little is known about the mechanical consequences of cell death. Here, we study the caspase-dependent mechanical kinetics of single cells during early apoptosis initiated with the general protein-kinase inhibitor staurosporine. This results in internal remodelling of the cytoskeleton and nucleus which is reflected in dynamic changes in the mechanical properties of the cell. Utilizing simultaneous confocal and atomic force microscopy (AFM), we measured distinct mechanical dynamics in the instantaneous cellular Young's Modulus and longer timescale viscous deformation. This allowed us to visualize time-dependent nuclear and cytoskeletal control of force dissipation with fluorescent fusion proteins throughout the cell. This work reveals that the cell death program not only orchestrates biochemical dynamics but also controls the mechanical breakdown of the cell. Importantly, the consequences of mechanical disregulation during apoptosis may be a contributing factor to several human pathologies through the poorly timed release of dead cells and cell debris.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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

Citations93
Published2009
Admission routes1
Has abstractyes

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