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Record W2839226594 · doi:10.1038/s41598-018-28717-y

Myosin X is required for efficient melanoblast migration and melanoma initiation and metastasis

2018· article· en· W2839226594 on OpenAlexfundno aff
Hiroshi Tokuo, Jag Bhawan, Lynne M. Coluccio

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesU.S. Department of Health and Human ServicesNational Institutes of HealthNational Institute of General Medical SciencesWellcome TrustInstitute of GeneticsSchool of Medicine, Boston University
KeywordsMelanomaCancer researchMetastasisCell migrationBiologyFilopodiaMicrophthalmia-associated transcription factorMyosinGene silencingCell biologyActinCell cultureCancerGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Myosin X (Myo10), an actin-associated molecular motor, has a clear role in filopodia induction and cell migration in vitro , but its role in vivo in mammals is not well understood. Here, we investigate the role of Myo10 in melanocyte lineage and melanoma induction. We found that Myo10 knockout (Myo10KO) mice exhibit a white spot on their belly caused by reduced melanoblast migration. Myo10KO mice crossed with available mice that conditionally express in melanocytes the BRAF V600E mutation combined with Pten silencing exhibited reduced melanoma development and metastasis, which extended medial survival time. Knockdown of Myo10 (Myo10kd) in B16F1 mouse melanoma cell lines decreased lung colonization after tail-vein injection. Myo10kd also inhibited long protrusion (LP) formation by reducing the transportation of its cargo molecule vasodilator-stimulated phosphoprotein (VASP) to the leading edge of migrating cells. These findings provide the first genetic evidence for the involvement of Myo10 not only in melanoblast migration, but also in melanoma development and metastasis.

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 score0.156
Threshold uncertainty score0.307

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 head0.016
GPT teacher head0.262
Teacher spread0.246 · 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

Citations47
Published2018
Admission routes1
Has abstractyes

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