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Record W4313466225 · doi:10.1016/j.xpro.2022.101919

MATRIX platform to analyze translation machinery remodeling in glioblastoma cells

2022· article· en· W4313466225 on OpenAlexaff
J.J.David Ho, Tyler A. Cunningham, Jonathan R. Krieger, Jonathan H. Schatz, Stephen Lee

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsBioinformatics Solutions (Canada)
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Institutes of HealthSylvester Comprehensive Cancer Center, University of Miami Health Systems
KeywordsStable isotope labeling by amino acids in cell cultureTranslation (biology)RibosomeMass spectrometryProtein biosynthesisFractionationChemistryInternal ribosome entry siteCell fractionationMatrix (chemical analysis)Computational biologyGlioblastomaCell biologyProteomicsComputer scienceBiochemistryBiologyRNAMessenger RNAChromatographyEnzymeCancer research

Abstract

fetched live from OpenAlex

Here, we present a protocol using MATRIX (mass spectrometry analysis of active translation factors using ribosome density fractionation and isotopic labeling experiments) platform to investigate changes of the protein synthesis machinery in U87MG glioblastoma cells in response to the rocaglate silvestrol. This protocol describes steps to perform SILAC (stable isotope labeling by amino acids in cell culture), ribosome density fractionation, protein isolation, and mass spectrometry analysis. This approach can be applied to study any adaptive remodeling of protein synthesis machineries. For complete details on the use and execution of this protocol, please refer to Ho et al. (2021).1

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.298
Teacher spread0.278 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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