Increased nonHDL cholesterol levels cause muscle wasting and ambulatory dysfunction in the mouse model of LGMD2B
Bibliographic record
Abstract
Progressive limb and girdle muscle atrophy leading to loss of ambulation is a hallmark of dysferlinopathies, which include limb-girdle muscular dystrophy type 2B and Miyoshi myopathy. However, animal models fail to fully reproduce the disease severity observed in humans, with dysferlin-null (Dysf −/− ) mice exhibiting minor muscle damage and weakness without dramatic ambulatory dysfunction. As we have previously reported significant Dysf expression in blood vessels, we investigated the role of vascular function in development of muscle pathology by generating a Dysf-deficient mouse model with vascular disease. This was achieved by crossing Dysf −/− mice with ApoE −/− mice, which have high levels of nonHDL-associated cholesterol. Double-knockout Dysf −/− ApoE −/− mice exhibited severe ambulatory dysfunction by 11 months of age. In limb-girdle muscles, histology confirmed dramatic muscle wasting, fibrofatty replacement, and myofiber damage in Dysf −/− ApoE −/− mice without affecting the ratio of centrally nucleated myofibers. Although there were no major changes in ex vivo diaphragm and soleus muscle function, histological analyses revealed these muscles to be untouched by damage and remodelling. In all, these data suggest that cholesterol may be deleterious to dysferlinopathic muscle and lead to ambulatory dysfunction. Moreover, differences in plasma lipid handling between mice and humans could be a key factor affecting dysferlinopathy severity
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".