EXPERIMENTAL CARDIOVASCULAR AND LUNG RESEARCH Biological effects of anti-CD34-coated ePTFE vascular grafts. Early in vivo experimental results
Bibliographic record
Abstract
AIM OF THE STUDY: To assess the biological activity of anti-CD34 antibody-coated ePTFE vascular prostheses. MATERIAL AND METHODS: Indium(111)-labeled autologous thrombocytes were administered to 5 anesthetized pigs after the placement of femoral arterial and venous catheters. An arterio-venous fistula, created by the random interposition of 4 different ePTFE grafts (A = dry control, B = dry anti-CD34, C = wet control, D = wet anti-CD34), was blood perfused for 0, 10, 30, 60 and 120 minutes. Radioactivity of each graft was measured and expressed in cpm/mg. Morphological studies were performed to assess intraluminal deposition. RESULTS: The median radioactivity of graft B was significantly higher than that of graft A after 60 min (1074 vs. 18; p = 0.021) and 120 min (1990 vs. 25; p = 0.043) of perfusion. Similarly, graft D was significantly more active than graft C (60 min: 1388 vs. 26; p = 0.021 and 120 min: 2780 vs. 23; p = 0.021). Histological and SEM results confirmed the radio-labeling in-vivo studies by showing significantly more protein/cell and platelet depositions (p = 0.012). CONCLUSIONS: Anti-CD34-coated ePTFE grafts bound significantly more platelets/cells and proteins than their uncoated counterparts, confirming the bioactivity of the antibody. This process is time-dependent and matches the morphological results. The anti-CD34 coating may enhance temporal and spatial endothelialization of vascular grafts and, thus, possibly improve clinical results by providing direct endothelial progenitor cell (EPC) adhesion/entrapment or by creating a biocompatible protein-thrombocyte/cell layer that indirectly enhances migration and further proliferation of EPCs.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".