The designer cytokine IC7Fc attenuates atherosclerosis development by targeting hyperlipidemia in mice
Bibliographic record
Abstract
The chimeric cytokine IC7Fc conveys the metabolic signaling properties of the glycoprotein 130 receptor cytokines interleukin-6 and ciliary neurotrophic factor via membrane-bound signaling. IC7Fc was previously shown to slow the progression of type 2 diabetes mellitus, and here, we demonstrate its effect on atherosclerotic development. In APOE*3-Leiden.CETP mice, an atherosclerosis-prone model with a humanized lipoprotein metabolism, IC7Fc markedly lowered plasma triglyceride and total cholesterol levels. This was mechanistically explained by an inhibition of de novo lipogenesis in the liver, increased synthesis of bile acids from cholesterol, and down-regulated apolipoprotein B synthesis, which resulted in decreased cholesterol secretion in very low-density lipoprotein particles. As a consequence, IC7Fc treatment considerably reduced atherosclerotic lesion formation and vascular inflammation compared with current antihyperlipidemic therapy. In conclusion, IC7Fc is a promising pharmacological treatment for cardiometabolic diseases targeting hyperlipidemia and inflammation.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".