Design and evaluation of novel blood incubation systems for <i>in vitro</i> hemocompatibility assessment of planar solid surfaces
Bibliographic record
Abstract
Success in the development of hemocompatible biomaterials depends on adequate equipment and procedures for standardized analysis of blood-materials interactions in vitro. In view of the limited standard of knowledge on that important aspect, two novel incubation systems were designed, built, and evaluated for the in vitro assessment of the hemocompatibility of planar solid surfaces: A screening setup was introduced for the comparison of up to 12 different samples. A perfusion setup was developed to model the directed blood flow in the vascular system during incubation by a recirculation circuit, allowing the variation of the wall shear rate at the sample surface. The incubation procedures utilized freshly drawn, heparinized whole human blood. Hemocompatibility in terms of selected aspects of coagulation, thrombogenicity, and immune responses was quantified through plasma levels of characteristic molecules (immunoassays), cell counting, and analysis of adherent cells and fibrin formation (scanning electron microscopy), respectively. Prevention of blood-air contact and mechanical stress, constant temperature and blood pH during incubation, and the suitable choice of reference materials were found to be crucial for reliable testing. Considering those requirements, screening and perfusion system both provided sensitive discrimination between a given set of planar solid surfaces. In conclusion, the suggested methods for an in vitro hemocompatibility assessment permit versatile, sensitive, and efficient analysis of important blood-material interactions despite the unavoidable variability of blood characteristics in different experiments.
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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 | 0.001 |
| 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 | 0.000 | 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".