Effects of fibroblast growth factor 21 on cell damage in vitro and atherosclerosis in vivo
Bibliographic record
Abstract
Fibroblast growth factor 21 (FGF-21), which is a modulator of glucose and lipid homeostasis, acts as a novel therapeutic reagent for many metabolic perturbations. However, its potential as a treatment for cardiovascular disease, especially atherosclerosis (AS) has not been fully explored. Here, we report that recombinant FGF-21 improves resistance to cell damage from oxidative stress in vitro, and from atherosclerosis in vivo. Human umbilical vein endothelial cells (HUVECs) were induced with H2O2, followed by treatment with high purity recombinant FGF-21. The results indicated that FGF-21 significantly enhanced cell viability and decreased the degree of DNA fragmentation in HUVECs, as caused by H2O2 stress induction. Further studies revealed that FGF-21 inhibited H2O2-induced cell apoptosis by preventing the activation of mitogen-activated protein kinase (MAPK) signaling pathways. In an established rat model, FGF-21 dramatically improved the condition of atherosclerotic rats by decreasing serum levels of total triglyceride (TG), low density lipoprotein cholesterol (LDL-C), and total cholesterol (TC), and by increasing the serum levels of high density lipoprotein cholesterol (HDL-C). FGF-21 also has antioxidant effects in the atherosclerotic rat, such that increased levels of superoxide dismutase, reduced glutathione, and reduced malondialdehyde were observed. These data provide novel insight into the potential use of FGF-21 in the prevention and treatment of human cardiovascular diseases.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".