Lipoprotein(a) in atherosclerotic plaques recruits inflammatory cells through interaction with Mac‐1 integrin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lipoprotein(a) [Lp(a)], consisting of LDL and the unique constituent apolipoprotein(a) [apo(a)], which contains multiple repeats resembling plasminogen kringle 4, is considered a risk factor for the development of atherosclerotic disorders. However, the underlying mechanisms for the atherogenicity of Lp(a) are not completely understood. Here, we define a novel function of Lp(a) in promoting inflammatory cell recruitment that may contribute to its atherogenicity. Through its apo(a) moiety Lp(a) specifically interacts with the beta2-integrin Mac-1, thereby promoting the adhesion of monocytes and their transendothelial migration in a Mac-1-dependent manner. Interestingly, the interaction between Mac-1 and Lp(a) was strengthened in the presence of proatherogenic homocysteine and was blocked by plasminogen/angiostatin kringle 4. Through its interaction with Mac-1, Lp(a) induced activation of the proinflammatory transcription factor NFkappaB, as well as the NFkappaB-related expression of prothrombotic tissue factor. In atherosclerotic coronary arteries Lp(a) was found to be localized in close proximity to Mac-1 on infiltrating mononuclear cells. Taken together, our data demonstrate that Lp(a), via its apo(a) moiety, is a ligand for the beta2-integrin Mac-1, thereby facilitating inflammatory cell recruitment to atherosclerotic plaques. These observations suggest a novel mechanism for the atherogenic properties of Lp(a).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 it