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Record W2027722054 · doi:10.3791/1106

Microinjection of Xenopus Laevis Oocytes

2009· article· en· W2027722054 on OpenAlexafffund
Sarah Cohen, Shelly Au, Nelly Pant eacute

Bibliographic record

VenueJournal of Visualized Experiments · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsXenopusMicroinjectionOocyteCell biologyAutographa californicaBiologyNuclear transportCytoplasmCell nucleusBiophysicsMolecular biologyGeneticsRecombinant DNAEmbryoGene

Abstract

fetched live from OpenAlex

Microinjection of Xenopus laevis oocytes followed by thin-sectioning electron microscopy (EM) is an excellent system for studying nucleocytoplasmic transport. Because of its large nucleus and high density of nuclear pore complexes (NPCs), nuclear transport can be easily visualized in the Xenopus oocyte. Much insight into the mechanisms of nuclear import and export has been gained through use of this system (reviewed by Panté, 2006). In addition, we have used microinjection of Xenopus oocytes to dissect the nuclear import pathways of several viruses that replicate in the host nucleus. Here we demonstrate the cytoplasmic microinjection of Xenopus oocytes with a nuclear import substrate. We also show preparation of the injected oocytes for visualization by thin-sectioning EM, including dissection, dehydration, and embedding of the oocytes into an epoxy embedding resin. Finally, we provide representative results for oocytes that have been microinjected with the capsid of the baculovirus Autographa californica nucleopolyhedrovirus (AcMNPV) or the parvovirus Minute Virus of Mice (MVM), and discuss potential applications of the technique.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.006

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 head0.012
GPT teacher head0.371
Teacher spread0.360 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations14
Published2009
Admission routes2
Has abstractyes

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