Ceruloplasmin-Deficient Mice Show Dysregulation of Lipid Metabolism in Liver and Adipose Tissue Reduced by a Protein Replacement
Bibliographic record
Abstract
Ceruloplasmin is a ferroxidase that plays a role in iron homeostasis; its deficiency fosters inter alia iron accumulation in the liver, which expresses the soluble form of the protein secreted into the bloodstream. Ceruloplasmin is also secreted by the adipose tissue, but its role in adipocytes has been poorly investigated. We hypothesized that ceruloplasmin might have a role in iron/lipid interplay. We investigated iron/lipid dysmetabolism in the liver and adipose tissue of the ceruloplasmin-deficient mouse (CpKO) model of aceruloplasminemia and evaluated the effectiveness of ceruloplasmin replacement. We found that CpKO mice were overweight, showing adipose tissue accumulation, liver iron deposition and steatosis. In the adipose tissue of CpKO mice, iron homeostasis was not altered. Conversely, the levels of adiponectin and leptin adipokines behaved opposite to the wild-type. Increased macrophage infiltration was observed in adipose tissue and liver of CpKO mice, indicating tissue inflammation. The treatment of CpKO mice with ceruloplasmin limited liver iron accumulation and steatosis without normalizing the expression of iron homeostasis-related proteins. In the CpKO mice, the protein replacement limited macrophage infiltration in both adipose and hepatic tissues reduced the level of serum triglycerides, and partially recovered adipokines levels in the adipose tissue. These results underline the link between iron and lipid dysmetabolism in ceruloplasmin-deficient mice, suggesting that ceruloplasmin in adipose tissue has an anti-inflammatory role rather than a role in iron homeostasis. Furthermore, these data also indicate that ceruloplasmin replacement therapy may be effective at a systemic level.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".