Four-and-a-half LIM domain protein-2 (FHL-2) inhibition reduces atherosclerosis in apolipoprotein E-deficient mice
Bibliographic record
Abstract
Background: Four-and-a-half LIM domain protein-2 (FHL-2), a member of the FHL family of proteins, is expressed in vascular endothelial and smooth muscle cells and negatively regulates endothelial cell survival and migration. However, its role in atherogenesis is unknown. Methods and results: To investigate the role of FHL-2 in atherosclerosis, we crossed FHL-2 knockout (FHL-2-/-) with apolipoprotein E-deficient (ApoE-/-) mice, and fed them a high-cholesterol, high-fat diet for 7 weeks. FHL-2-/-ApoE-/- mice displayed significantly less atherosclerotic plaque formation, as assessed by oil red O staining, in the aortic sinus (0.14±0.02 vs. 0.29±0.04 mm2) and aorta (6.9±0.9 vs 10.3±1%), compared with ApoE-/- mice. This was associated with enhanced collagen (16±2 vs 8.6±3%) and smooth muscle cell (4.5±0.8 vs 1.8±0.5%) contents within the plaques in the aortic sinus of FHL-2-/-ApoE-/- mice, as determined by Sirius red and alpha-actin staining, respectively, compared with ApoE-/- mice. These results suggest that absence of FHL-2 promotes smaller and more stable plaques. However, relative monocyte/macrophage content within the atherosclerotic plaques, as determined by MOMA-2 immunostaining, and in spleens, as determined by FACS analysis, was equivalent in both animals groups. Decreased plaque formation in FHL-2-/-ApoE-/- mice was associated with significantly reduced aortic ICAM-1 mRNA levels by 40%. Moreover, FACS analysis of T cells in spleens showed a significant increase in CD4+CD25+Foxp3+ regulatory T cell numbers, in FHL-2-/-ApoE-/- compared with ApoE-/- mice (19.5±1.6 vs. 16.2±2% of CD3+CD4+ cells, respectively). Conclusions: These results suggest that FHL-2 may play an important role in atherogenesis by promoting plaque formation, involving upregulation of adhesion molecule expression and suppression of regulatory T cells.
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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 | 0.000 |
| 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".