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Record W3035893400 · doi:10.1016/j.jid.2020.03.679

667 β3-tubulin knockdown interferes with microtubule dynamics, cell-cycle regulation, and microvesicle release in human melanoma cells

2020· article· en· W3035893400 on OpenAlexaff
Mohammed O. Altonsy, Philip Surmanowicz, Anutosh Ganguly, Gilles J. Lauzon, P. Régine Mydlarski

Bibliographic record

VenueJournal of Investigative Dermatology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiological Research and Disease Studies
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMicrovesicleTubulinCell biologyMicrotubuleMicrovesiclesCell cycleGene knockdownBiologyTransfectionMelanomaCarcinogenesisCancer researchCellChemistryCell cultureCancermicroRNABiochemistry

Abstract

fetched live from OpenAlex

Introduction: Microvesicles (MV), ranging in size from 100 nm to 1000 nm, play an important role in carcinogenesis by promoting angiogenesis and tumor metastasis, interfering with anti-tumor immunity, and inducing multidrug resistance. The release of MVs requires structural changes in microfilaments, intermediate filaments, and microtubules. Class III β-tubulin (β3-tubulin), one of seven β-tubulin isotypes, is a microtubule component involved in malignant transformation and cancer development. Herein, we characterize the effects of β3-tubulin knockdown on microtubule dynamics, cell cycle regulation, and microvesicle formation in human melanoma cells.

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 score0.004
Threshold uncertainty score0.486

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 studies0.0000.001
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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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
Published2020
Admission routes1
Has abstractyes

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