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Record W2087929887 · doi:10.3791/1333

<em>In utero</em> and <em>ex vivo</em> Electroporation for Gene Expression in Mouse Retinal Ganglion Cells

2009· article· en· W2087929887 on OpenAlexaff
Timothy J. Petros, Alexandra Rebsam, Carol A. Mason

Bibliographic record

VenueJournal of Visualized Experiments · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsColumbia College
FundersNational Institute of Neurological Disorders and StrokeNational Eye InstituteNational Institutes of Health
KeywordsElectroporationBiologyRetinaRetinal ganglion cellCell biologyEx vivoAxon guidanceNeuroscienceAxonIn vivoGeneticsGene

Abstract

fetched live from OpenAlex

The retina and its sole output neuron, the retinal ganglion cell (RGC), comprise an excellent model in which to examine biological questions such as cell differentiation, axon guidance, retinotopic organization and synapse formation. One drawback is the inability to efficiently and reliably manipulate gene expression in RGCs in vivo, especially in the otherwise accessible murine visual pathways. Transgenic mice can be used to manipulate gene expression, but this approach is often expensive, time consuming, and can produce unwanted side effects. In chick, in ovo electroporation is used to manipulate gene expression in RGCs for examining retina and RGC development. Although similar electroporation techniques have been developed in neonatal mouse pups, adult rats, and embryonic murine retinae in vitro, none of these strategies allow full characterization of RGC development and axon projections in vivo. To this end, we have developed two applications of electroporation, one in utero and the other ex vivo, to specifically target embryonic murine RGCs. With in utero retinal electroporation, we can misexpress or downregulate specific genes in RGCs and follow their axon projections through the visual pathways in vivo, allowing examination of guidance decisions at intermediate targets, such as the optic chiasm, or at target regions, such as the lateral geniculate nucleus. Perturbing gene expression in a subset of RGCs in an otherwise wild-type background facilitates an understanding of gene function throughout the retinal pathway. Additionally, we have developed a companion technique for analyzing RGC axon growth in vitro. We electroporate embryonic heads ex vivo, collect and incubate the whole retina, then prepare explants from these retinae several days later. Retinal explants can be used in a variety of in vitro assays in order to examine the response of electroporated RGC axons to guidance cues or other factors. In sum, this set of techniques enhances our ability to misexpress or downregulate genes in RGCs and should greatly aid studies examining RGC development and axon projections.

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 score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.010

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 head0.317
Teacher spread0.305 · 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

Citations30
Published2009
Admission routes1
Has abstractyes

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