Differential and cooperative actions of Olig1 and Olig2 transcription factors on immature proliferating cells after contusive spinal cord injury
Bibliographic record
Abstract
Spontaneous remyelination after spinal cord injury (SCI) is limited probably due to inadequate signaling to generate sufficient OLs from progenitor cells. The present study tested a hypothesis that introduction of olig genes, critical regulators of OL development, into immature proliferating cells could increase oligodendrogenesis after contusive SCI in adult rats. Recombinant retroviruses encoding Olig1 and Olig2 transcription factors, separately or in combination, with green fluorescent protein (GFP) were injected into the injured spinal cord. Unexpectedly, introduction of Olig2-GFP retroviruses led to a marked hyperplasia of GFP+ cells at 1 week, and soft agar colony forming assay of isolated GFP+ cells confirmed Olig2-induced tumorous transformation. In contrast, Olig1 did not alter the number of GFP+ cells. Simultaneous expression of Olig1 and Olig2 (Olig1/2) led to a marked increase in the number of GFP+ cells without tumor formation. The proportion of GFP+ cells with OL progenitor markers was increased by Olig1/2. Moreover, Olig1/2 robustly increased the proportion of mature OLs and expression of myelin related proteins, while Olig1 alone exhibited only modest effects. Olig1/2 upregulated Sox10, which drives terminal OL differentiation, implicating Sox 10 as a mediator of Olig1/2 effects on the maturation. Finally, injection of Olig1/2 retroviruses significantly improved a quality of hindpaws locomotion and increased the total number of OLs after SCI. Activation of both Olig1 and Olig2 may be beneficial by both increasing the progenitor cell proliferation and enhancing OL differentiation in the injured spinal cord.
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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) | 0.000 | 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".