Establishing Mixed Neuronal and Glial Cell Cultures from Embryonic Mouse Brains to Study Infection and Innate Immunity
Bibliographic record
Abstract
Models of the central nervous system (CNS) must recapitulate the complex network of interconnected cells found in vivo. The CNS consists primarily of neurons, astrocytes, oligodendrocytes, and microglia. Due to increasing efforts to replace and reduce animal use, a variety of in vitro cell culture systems have been developed to explore innate cell properties, which allow the development of therapeutics for CNS infections and pathologies. Whilst certain research questions can be addressed by human-based cell culture systems, such as (induced) pluripotent stem cells, working with human cells has its own limitations with regard to availability, costs, and ethics. Here, we describe a unique protocol for isolating and culturing cells from embryonic mouse brains. The resulting mixed neural cell cultures mimic several cell populations and interactions found in the brain in vivo. Compared to current equivalent methods, this protocol more closely mimics the characteristics of the brain and also garners more cells, thus allowing for more experimental conditions to be investigated from one pregnant mouse. Further, the protocol is relatively easy and highly reproducible. These cultures have been optimized for use at various scales, including 96-well based high throughput screens, 24-well microscopy analysis, and 6-well cultures for flow cytometry and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. This culture method is a powerful tool to investigate infection and immunity within the context of some of the complexity of the CNS with the convenience of in vitro methods.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".