A Neurosphere Assay to Evaluate Endogenous Neural Stem Cell Activation in a Mouse Model of Minimal Spinal Cord Injury
Bibliographic record
Abstract
Neural stem cells (NSCs) in the adult mammalian spinal cord are a relatively mitotically quiescent population of periventricular cells that can be studied in vitro using the neurosphere assay. This colony-forming assay is a powerful tool to study the response of NSCs to exogenous factors in a dish; however, this can also be used to study the effect of in vivo manipulations with the proper understanding of the strengths and limitations of the assay. One manipulation of the clinical interest is the effect of injury on endogenous NSC activation. Current models of spinal cord injury provide a challenge to study this as the severity of common contusion, compression, and transection models cause the destruction of the NSC niche at the site of the injury where the stem cells reside. Here, we describe a minimal injury model that causes localized damage at the superficial dorsolateral surface of the lower thoracic level (T7/8) of the adult mouse spinal cord. This injury model spares the central canal at the level of injury and permits analysis of the NSCs that reside at the level of the lesion at various time points following injury. Here, we show how the neurosphere assay can be utilized to study the activation of the two distinct, lineally-related, populations of NSCs that reside in the spinal cord periventricular region - primitive and definitive NSCs (pNSCs and dNSCs, respectively). We demonstrate how to isolate and culture these NSCs from the periventricular region at the level of injury and the white matter injury site. Our post-surgical spinal cord dissections show increased numbers of pNSC and dNSC-derived neurospheres from the periventricular region of injured cords compared to controls, speaking to their activation via injury. Furthermore, following injury, dNSC-derived neurospheres can be isolated from the injury site - demonstrating the ability of NSCs to migrate from their periventricular niche to sites of injury.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".