Differentiation block of oligodendroglial progenitor cells as a cause for remyelination failure in chronic multiple sclerosis
Bibliographic record
Abstract
Impaired function/differentiation of progenitor cells might provide an explanation for the limited remyelination observed in the majority of chronic multiple sclerosis lesions. Here, we establish that in the normal adult human CNS, the transcription factors Nkx2.2 and Olig2 are strongly expressed in progenitor cells while mature oligodendrocytes are characterized by low levels of Olig2 or Nkx2.2. In vitro studies confirmed the expression of Olig2 in oligodendroglial progenitor cells and mature oligodendrocytes while astrocytes, microglial cells and neurons were negative for Olig2. In early multiple sclerosis lesions, we found Olig2-positive progenitor cells throughout all lesion stages and in periplaque white matter (PPWM). The number of progenitors in PPWM was significantly increased compared with the white matter from controls. In chronic multiple sclerosis lesions progenitor cells were still present, however, in significantly lower numbers than in early multiple sclerosis lesions. A subpopulation of progenitor cells in early multiple sclerosis lesions and PPWM but not in control cases co-expressed NogoA, a marker of mature oligodendrocytes. The co-expression of these two markers suggested that these cells were maturing oligodendrocytes recently recruited from the progenitor pool. In contrast, in chronic multiple sclerosis lesions maturing progenitors were only rarely present. In summary, we provide evidence that a differentiation block of oligodendroglial progenitors is a major determinant of remyelination failure in chronic multiple sclerosis lesions.
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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) | 0.000 | 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".