Enhanced expression of hemoglobin scavenger receptor and heme oxygenase‐1 is associated with aortic valve stenosis in patients undergoing hemodialysis
Bibliographic record
Abstract
A high prevalence and a rapid progression of aortic valve stenosis (AS) in patients undergoing hemodialysis (HD) has been reported. In these circumstances, intraleaflet hemorrhage of aortic valve may be related to the development of AS in HD patients. We immunohistochemically examined the relationship among intraleaflet hemorrhage, neovascularization, hemoglobin scavenger receptor (CD163), and heme oxygenase-1 (HO-1) using surgically resected aortic valve specimens from AS patients undergoing HD. The study population consisted of 26 HD patients and 25 non-HD patients with severe AS who had undergone aortic valve replacement. Frozen aortic valve samples surgically obtained from AS patients were stained immunohistochemically with antibodies against smooth muscle cells, macrophages, glycophorin-A (a protein specific to erythrocyte membranes), CD31, CD163, and HO-1. Morphometric analysis demonstrated that the CD163-positive macrophage score, the number of CD31-positive microvessels, and the percentage of glycophorin-A and HO-1-positive area were significantly higher in HD patients than in non-HD patients (CD163-positive macrophage score, P < 0.0001; CD31-positive microvessels, P < 0.0001; glycophorin-A, P < 0.0001; HO-1, P < 0.0001). Double immunostaining for CD163 or HO-1 and macrophages revealed that the majority of CD163- or HO-1-positive cells were macrophages. Furthermore, CD163-positive macrophage score was positively correlated with glycophorin-A, HO-1-positive area, and the number of CD31-positive microvessels (glycophorin-A, R = 0.66, P < 0.0001; HO-1, R = 0.50, P < 0.0005; microvessels, R = 0.38, P < 0.01). These findings suggest a positive association among intraleaflet hemorrhage, neovascularization, and enhanced expression of CD163 and HO-1 as a response to intraleaflet hemorrhage in stenotic aortic valves in AS patients undergoing HD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".