Deletion of MCP-1 Impedes Pathogenesis of Acid Ceramidase Deficiency
Bibliographic record
Abstract
Farber Disease (FD) is an ultra-rare Lysosomal Storage Disorder caused by deficient acid ceramidase (ACDase) activity. Patients with ACDase deficiency manifest a spectrum of symptoms including formation of nodules, painful joints, and a hoarse voice. Classic FD patients will develop histiocytes in organs and die in childhood. Monocyte chemotactic protein (MCP-1; CCL2) is significantly elevated in both FD patients and a mouse model we previously generated. Here, to further study MCP-1 in FD, we created an ACDase;MCP-1 double mutant mouse. We show that deletion of MCP-1 reduced leukocytosis, delayed weight loss, and improved lifespan. Reduced inflammation and fibrosis were observed in livers from double mutant animals. Bronchial alveolar lavage fluid analyses revealed a reduction in cellular infiltrates and protein accumulation. Furthermore, reduced sphingolipid accumulation was observed in the lung and liver but not in the brain. The neurological and hematopoietic defects observed in FD mice were maintained. A compensatory cytokine response was found in the double mutants, however, that may contribute to continued signs of inflammation and injury. Taken together, targeting a reduction of MCP-1 opens the door to a better understanding of the mechanistic consequences of ceramide accumulation and may even delay the progression of FD in some organ systems.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".