Expression of Bone Morphogenetic Proteins in Multiple Sclerosis Lesions
Bibliographic record
Abstract
Bone morphogenetic proteins (BMPs) are secreted proteins that belong to the transforming growth factor-β superfamily. In the adult brain, they modulate neurogenesis, favor astrogliogenesis, and inhibit oligodendrogenesis. Because BMPs may be involved in the failure of remyelination in multiple sclerosis (MS), we characterized the expression of BMP-2, BMP-4, BMP-5, and BMP-7; BMP type II receptor (BMPRII); and phosphorylated SMAD (pSMAD) 1/5/8 in lesions of MS and other demyelinating diseases. A total of 42 MS lesions, 12 acute ischemic lesions, 8 progressive multifocal leukoencephalopathy lesions, and 10 central nervous system areas from four nonneuropathological patients were included. Lesions were histologically classified according to the inflammatory activity. The expression of BMP-2, BMP-4, BMP-5, BMP-7, BMPRII, and pSMAD1/5/8 was quantified by immunostaining, and colocalization studies were performed. In MS lesions, astrocytes, microglia/macrophages, and neurons expressed BMP-2, BMP-4, BMP-5, and BMP-7; BMPRII; and pSMAD1/5/8. Oligodendrocytes expressed BMP-2 and BMP-7 and pSMAD1/5/8. The percentage of cells that expressed BMPs, BMPRII, and pSMAD1/5/8 correlated with the inflammatory activity of MS lesions, and changes in the percentage of positive cells were more relevant in MS than in other white matter-damaging diseases. These data indicate that BMPs are increased in active MS lesions, suggesting a possible role in MS pathogenesis.
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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 | 0.001 | 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) | 0.002 | 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".