Trained immunity as a potential target for therapeutic immunomodulation in Duchenne muscular dystrophy
Bibliographic record
Abstract
Dysregulated inflammation involving innate immune cells, particularly of the monocyte/macrophage lineage, is a key contributor to the pathogenesis of Duchenne muscular dystrophy (DMD). Trained immunity is an evolutionarily ancient protective mechanism against infection, in which epigenetic and metabolic alterations confer non-specific hyperresponsiveness of innate immune cells to various stimuli. Recent work in an animal model of DMD (mdx mice) has shown that macrophages exhibit cardinal features of trained immunity, including the presence of innate immune system "memory". The latter is reflected by epigenetic changes and durable transmissibility of the trained phenotype to healthy non-dystrophic mice by bone marrow transplantation. Mechanistically, it is suggested that a Toll-like receptor (TLR) 4-regulated, memory-like capacity of innate immunity is induced at the level of the bone marrow by factors released from the damaged muscles, leading to exaggerated upregulation of both pro- and anti-inflammatory genes. Here we propose a conceptual framework for the involvement of trained immunity in DMD pathogenesis and its potential to serve as a new therapeutic target.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".