Injection of <i>Ortho</i>‐Functionalized Tetrafluorinated Azobenzene‐Containing siRNAs into Japanese Medaka Embryos for Photocontrolled Gene Silencing
Bibliographic record
Abstract
This article describes the detailed methodology of how to inject photoswitchable ortho-functionalized tetrafluorinated short interfering RNAs (F-siRNAs) into a single cell of stage-two Japanese medaka (Oryzias latipes) embryos and how to control gene silencing with different wavelengths of light. Many of the prior papers describing Japanese medaka embryo injections omit key information. As such, this article aims to give an in-depth explanation as to how the NanoJect III microinjector can be used for this purpose. To obtain the embryos for microinjection, adult medaka are housed under a 14-hr light, 10-hr dark cycle to mimic their natural breeding period. This induces mating at approximately the same time each day, when the lights turn on, so recently fertilized eggs can be obtained. Synthetic F-siRNAs are injected into transgenic stage-two single-cell Japanese medaka embryos expressing enhanced green fluorescent protein (eGFP). Our data demonstrate that our F-siRNAs can silence gene activity in Japanese medaka embryos expressing eGFP. Moreover, gene expression can be activated by exposing F-siRNA-injected embryos to blue light and deactivated a few days after exposure to green light. To the best of our knowledge, this marks the first reversible control of a gene-silencing oligonucleotide within an in vivo system. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Medaka maintenance and embryo collection Basic Protocol 2: Injection of stage-two one-cell medaka embryos Basic Protocol 3: Evaluation of the F-siRNA gene-silencing ability through light activation and inactivation using blue and green light by measuring enhanced green fluorescent protein fluorescence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".