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Record W3088122987 · doi:10.1016/j.xpro.2020.100112

Quantitative Imaging of MS2-Tagged hTR in Cajal Bodies: Photobleaching and Photoactivation

2020· article· en· W3088122987 on OpenAlexafffund
Michael J. Smith, Emmanuelle Querido, Pascal Chartrand, Agnel Sfeir

Bibliographic record

VenueSTAR Protocols · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversité de Montréal
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health Research
KeywordsPhotobleachingCajal bodyBiophysicsCell biologyChemistryFluorescence recovery after photobleachingInterstitial cell of CajalRNAGreen fluorescent proteinNanotechnologyBiologyFluorescenceGeneBiochemistryPhysicsMaterials scienceOpticsRNA splicing

Abstract

fetched live from OpenAlex

Advances in imaging technologies, gene editing, and fluorescent molecule development have made real-time imaging of nucleic acids practical. Here, we detail methods for imaging the human telomerase RNA template, hTR via the use of three inserted MS2 stem loops and cognate MS2 coat protein (MCP) tagged with superfolder GFP or photoactivatable GFP. These technologies enable tracking of the dynamics of RNA species through Cajal bodies and offer insight into their residence time in Cajal bodies through photobleaching and photoactivation experiments. For complete details on the use and execution of this protocol, please refer to Laprade et al. (2020).

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 score0.015
Threshold uncertainty score0.440

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 head0.031
GPT teacher head0.306
Teacher spread0.275 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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