Thrombospondin-1 and disease progression in dysferlinopathy
Bibliographic record
Abstract
The purpose of this study was to determine whether thrombospondin (TSP)-1 promotes macrophage activity and disease progression in dysferlinopathy. First, we found that levels of TSP-1 are elevated in blood of non-ambulant dysferlinopathy patients compared with ambulant patients and healthy controls, supporting the idea that TSP-1 levels are correlated with disease progression. We then crossed dysferlinopathic BlaJ mice with TSP-1 knockout mice and assessed disease progression longitudinally with magnetic resonance imaging (MRI). In these mice, deletion of TSP-1 ameliorated loss in volume and mass of the moderately affected gluteal muscle but not of the severely affected psoas muscle. T2 MRI parameters revealed that loss of TSP-1 modestly inhibited inflammation only in gluteal muscle of male mice. Histological assessment indicated that deletion of TSP-1 reduced inflammatory cell infiltration of muscle fibers, but only early in disease progression. In addition, flow cytometry analysis revealed that, in males, TSP-1 knockout reduced macrophage infiltration and phagocytic activity, which is consistent with TSP-1-enhanced phagocytosis and pro-inflammatory cytokine induction in cultured macrophages. In summary, TSP-1 appears to play an accessory role in modulating Mp activity in BlaJ mice in a gender, age and muscle-dependent manner, but is unlikely a primary driver of disease progression of dysferlinopathy.
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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) | 0.001 | 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".