Elevated numbers of infiltrating eosinophils accelerate the progression of Duchenne muscular dystrophy pathology in <i>mdx</i> mice
Bibliographic record
Abstract
Eosinophils, best known for their role in anti-parasitic responses, have recently been shown to actively participate in tissue homeostasis and repair. Their regulation must be tightly controlled, as their absence or hyperplasia is associated with chronic disease (e.g. asthma or inflammatory bowel disease). In the context of skeletal muscle, eosinophils play a supportive role after acute damage. Indeed, their depletion leads to strong defects in skeletal muscle regeneration and, in the absence of eosinophil-secreted interleukin (IL) 4 and IL13, fibro-adipogenic progenitors fail to support muscle stem cell proliferation. However, the role of eosinophils in muscular dystrophy remains elusive. Although it has been shown that eosinophils are present in higher numbers in muscles from mdx mice (a mouse model for Duchenne muscular dystrophy), their depletion does not affect muscle histopathology at an early age. Here, we evaluated the impact of hyper-eosinophilia on the development of fibrofatty infiltration in aged mdx mice and found that muscle eosinophilia leads to defects in muscle homeostasis, regeneration and repair, and eventually hastens death.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".