Effects of Adult Neural Precursor-Derived Myelination on Axonal Function in the Perinatal Congenitally Dysmyelinated Brain: Optimizing Time of Intervention, Developing Accurate Prediction Models, and Enhancing Performance
Bibliographic record
Abstract
Stem cell repair shows substantial translational potential for neurological injury, but the mechanisms of action remain unclear. This study aimed to investigate whether transplanted stem cells could induce comprehensive functional remyelination. Subventricular zone (SVZ)-derived adult neural precursor cells (aNPCs) were injected bilaterally into major cerebral white matter tracts of myelin-deficient shiverer mice on postnatal day (P) 0, P7, and P21. Tripotential NPCs, when transplanted in vivo, integrated anatomically and functionally into local white matter and preferentially became Olig2+, Myelin Associated Glycoprotein-positive, Myelin Basic Protein-positive oligodendrocytes, rather than Glial Fibrillary Acidic Protein-positive astrocytes or Neurofiliment 200-positive neurons. Processes interacted with axons and transmission electron microscopy showed multilamellar axonal ensheathment. Nodal architecture was restored and by quantifying these anatomical parameters a computer model was generated that accurately predicted action potential velocity, determined by ex vivo slice recordings. Although there was no obvious phenotypic improvement in transplanted shi/shis, myelinated axons exhibited faster conduction, lower activation threshold, less refractoriness, and improved response to high-frequency stimulation than dysmyelinated counterparts. Furthermore, they showed improved resilience to ischemic insult, a promising finding in the context of perinatal brain injury. This study describes, for the first time mechanistically, the functional characteristics and anatomical integration of nonimmortalized donor SVZ-derived murine aNPCs in the dysmyelinated brain at key developmental time points.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".