An inhalation anaesthesia approach for neonatal mice allowing streamlined stereotactic injection in the brain
Bibliographic record
Abstract
BACKGROUND: Investigating brain function requires tools and techniques to visualise, modify and manipulate neuronal tissue. One powerful and popular method is intracerebral injection of customised viruses, allowing expression of exogenous transgenes. This technique is a standard procedure for adult mice, and is used by laboratories worldwide. Use of neonatal animals in scientific research allows investigation of developing tissues and enables long-term study of cell populations. However, procedures on neonatal mice are more challenging, due to the lack of reliable methods and apparatus for anaesthesia of these animals. NEW METHOD: Here, we report an inhalation-based protocol for anaesthesia of neonatal (P0-2) mice and present a custom 3D-printed apparatus for maintenance of anaesthesia during surgical procedures. Our optimised method of anaesthesia enables a rapid method of stereotactic injection in neonatal mice for transduction of brain tissue. RESULTS AND COMPARISON WITH EXISTING METHODS: This approach significantly enhances animal welfare and facilitates wider and simpler use of neonatal rodents in scientific research. We demonstrate this procedure for targeted labelling of specific brain regions, and in vivo modification of tissue prior to organotypic culture. CONCLUSIONS: Our protocol for reliable delivery of inhalational anaesthetics can be readily adopted by any laboratory and will enable safer use of neonatal rodents across a diverse spectrum of scientific disciplines. Application to stereotactic injections allows a rapid and efficient method for modification of brain tissue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".