Hemoglobin and Its Scavenger Protein Haptoglobin Associate with ApoA-1-containing Particles and Influence the Inflammatory Properties and Function of High Density Lipoprotein
Bibliographic record
Abstract
Hemoglobin (Hb) uniquely associates with proinflammatory HDL in atherogenic mice and coronary heart disease (CHD) patients. In this paper, we report that Hb and its scavenger proteins, haptoglobin (Hp) and hemopexin (Hx) are significantly increased in apoA-1-containing particles of HDL both in mouse models of hyperlipidemia and in CHD patients, when compared with wild type mice and healthy donors, respectively. We further demonstrate that the association of Hb, Hp, and Hx proteins with HDL positively correlates with inflammatory properties of HDL and systemic inflammation in CHD patients. Interestingly, HDL from Hp(-/-) mice under atherogenic conditions does not accumulate Hb and is anti-inflammatory, suggesting that (i) Hp is required for the association of Hb with HDL and (ii) Hb x Hp complexes regulate the inflammatory properties of HDL. Moreover, treatment of apoE(-/-) mice with an apoA-1 mimetic peptide resulted in significant dissociation of Hb x Hp complexes from HDL and improvement of HDL inflammatory properties. Our data strongly suggest that HDL can become proinflammatory via the Hb x Hp pathway in mice and humans, and dissociation of Hb x Hp x Hx complexes from apoA-1-containing particles of HDL may be a novel target for the treatment of CHD.
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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) | 0.000 | 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 | 0.000 |
| 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".