Improved 3D Hydrogel Cultures of Primary Glial Cells for <em>In Vitro</em> Modelling of Neuroinflammation
Bibliographic record
Abstract
In the central nervous system, numerous acute injuries and neurodegenerative disorders, as well as implanted devices or biomaterials engineered to enhance function result in the same outcome: excess inflammation leads to gliosis, cytotoxicity, and/or formation of a glial scar that collectively exacerbate injury or prevent healthy recovery. With the intent of creating a system to model glial scar formation and study inflammatory processes, we have generated a 3D cell scaffold capable of housing primary cultured glial cells: microglia that regulate the foreign body response and initiate the inflammatory event, astrocytes that respond to form a fibrous scar, and oligodendrocytes that are typically vulnerable to inflammatory injury. The present work provides a detailed step-by-step method for the fabrication, culture, and microscopic characterization of a hyaluronic acid-based 3D hydrogel scaffold with encapsulated rat brain-derived glial cells. Further, protocols for characterization of cell encapsulation and the hydrogel scaffold by confocal immunofluorescence and scanning electron microscopy are demonstrated, as well as the capacity to modify the scaffold with bioactive substrates, with incorporation of a commercial basal lamina mixture to improved cell integration.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".