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Record W2555974282 · doi:10.1242/dev.146464

Localized translation regulates cell adhesion and transendothelial migration

2016· article· en· W2555974282 on OpenAlexafffund
Jonathan Bergeman, Alexia Caillier, François Houle, Laurence M. Gagné, Marc‐Étienne Huot

Bibliographic record

VenueDevelopment · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsHôtel-Dieu de QuébecUniversité Laval
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsBiologyCell biologyTranslation (biology)Cell adhesionAdhesionCell migrationCellGeneticsGeneMessenger RNA

Abstract

fetched live from OpenAlex

Epithelial-to-mesenchymal transition (EMT) is a process by which cancer cells gain the ability to leave the primary tumor site and invade surrounding tissues.These metastatic cancer cells can further increase their plasticity by adopting an amoeboid-like morphology, by undergoing mesenchymal-to-amoeboid transition (MAT).We found that adhering cells produce spreading initiation centers (SICs), transient structures that are localized above nascent adhesion complexes, and share common biological and morphological characteristics associated with amoeboid cells.Meanwhile, spreading cells seem to return to a mesenchymal-like morphology.Thus, our results indicate that SIC-induced adhesion recapitulates events that are associated with amoeboid-to-mesenchymal transition (AMT).We found that polyadenylated RNAs are enriched within SICs, blocking their translation decreased adhesion potential of metastatic cells that progressed through EMT.These results point to a so-farunknown checkpoint that regulates cell adhesion and allows metastatic cells to alter adhesion strength to modulate their dissemination.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.202

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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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
Published2016
Admission routes2
Has abstractyes

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