Human Oligodendrocyte Myelination Potential; Relation to Age and Differentiation
Bibliographic record
Abstract
OBJECTIVE: Myelin regeneration in the human central nervous system relies on progenitor cells within the tissue parenchyma, with possible contribution from previously myelinating oligodendrocytes (OLs). In multiple sclerosis, a demyelinating disorder, variables affecting remyelination efficiency include age, severity of initial injury, and progenitor cell properties. Our aim was to investigate the effects of age and differentiation on the myelination potential of human OL lineage cells. METHODS: We derived viable primary OL lineage cells from surgical resections of pediatric and adult brain tissue. Ensheathment capacity using nanofiber assays and transcriptomic profiles from RNA sequencing were compared between A2B5+ antibody-selected progenitors and mature OLs (non-selected cells). RESULTS: We demonstrate that pediatric progenitor and mature cells ensheathed nanofibers more robustly than did adult progenitor and mature cells, respectively. Within both age groups, the percentage of fibers ensheathed and ensheathment length per fiber were greater for A2B5+ progenitors. Gene expression of OL progenitor markers PDGFRA and PTPRZ1 were higher in A2B5+ versus A2B5- cells and in pediatric A2B5+ versus adult A2B5+ cells. The p38 MAP kinases and actin cytoskeleton-associated pathways were upregulated in pediatric cells; both have been shown to regulate OL process outgrowth. Significant upregulation of "cell senescence" genes was detected in pediatric samples; this could reflect their role in development and the increased susceptibility of pediatric OLs to activating cell death responses to stress. INTERPRETATION: Our findings identify specific biological pathways relevant to myelination that are differentially enriched in human pediatric and adult OL lineage cells and suggest potential targets for remyelination enhancing therapies. ANN NEUROL 2022;91:178-191.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".