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Record W2460085209 · doi:10.1242/jcs.174623

Cell adhesion strength from cortical tension – an integration of concepts

2015· review· en· W2460085209 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Cell Science · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAdhesionBiologyCell adhesionCytoskeletonCell adhesion moleculeCell biologyCellMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

Morphogenetic mechanisms such as cell movement or tissue separation depend on cell attachment and detachment processes, which involve adhesion receptors as well as the cortical cytoskeleton. The interplay between the two components is of stunning complexity. Most strikingly, the binding energy of adhesion molecules is usually too small for substantial cell-cell attachment, pointing to a main deficit in our present understanding of adhesion. In this Opinion article, I integrate recent findings and conceptual advances in the field into a coherent framework for cell adhesion. I argue that active cortical tension is best viewed as an integral part of adhesion, and propose on this basis a non-arbitrary measure of adhesion strength - the tissue surface tension of cell aggregates. This concept of adhesion integrates heterogeneous molecular inputs into a single mechanical property and simplifies the analysis of attachment-detachment processes. It draws attention to the enormous variation of adhesion strengths among tissues, whose origin and function is little understood.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.613
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.044
GPT teacher head0.362
Teacher spread0.318 · 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