Cultures of Astroglia and Microglia from Primary Cultures of Mouse Neopallium
Bibliographic record
Abstract
Brains of newborn rats or mice are generally used as the source of tissue for glial cultures. Only about 1% of cells survive the cell disaggregation process and culture environment, and neurons that survive die within the first few days of culturing. Such cultures contain progenitor cells and glia cells in different stages of differentiation (; ; see also Chapter 14). Terminally differentiated glia cells, which can no longer divide, are overgrown by the proliferating, immature cells. How the cultures will develop, and which cell types (astroglia, oligodendroglia, ependymal cells, or microglia) will predominate, depend on the culture medium and the physical conditions under which the cells are grown (see also Chapters 12 and 14). The medium can be modified either by changing its chemically defined components or by adding or deleting serum. It is also possible to add growth factors and/or cytokines, either to the culture medium in pure recombinant form, or as medium conditioned by cells that produce and secrete growth factors/cytokines into the medium (the latter is considerably cheaper). The addition of cytokines to cultures can have a dramatic effect on the morphology and function of cells. It should be noted that cytokines and growth factors may affect more than one cell type, and may initiate variable effects in different cell types. The growth factors/cytokines may interact with other factors in the medium synergistically, additively, or in an inhibitory way. It is important to remember that the half-life of cytokines is short. However, the cytokines/growth factors can be added to ,the culture in microcapsules, which release the factors at a constant rate over a long period of time, thus assuring a constant concentration of a given factor to culture medium over long periods of time (; , ).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.010 |
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.
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".