Investigating long-term stability of sulfur and fluorine based adlayers on stainless steel stent models
Bibliographic record
Abstract
N continues to be an emerging discipline, providing novel solutions to diseases that otherwise could not be treated effectively. The development and use of self-assembled monolayers and adlayers for biomedical applications has allowed bioincompatible materials such as stainless steel and cobalt-chromium, to be used as effective medical devices. In terms of stainless steel, this material has been widely used to develop stent implants. Stents are expandable tubes used to open up a restricted artery. Conventional implantation of a bare metal stent can cause renarrowing of the artery over time restenosis, due to an immune response launched by the body towards the “foreign” stent. As a result, improving the biocompatibility of stainless steel is thought to be critical for creating a stent that is not rejected by the body. Benzothiosulfonate (BTS) and Pentafluorophenyl Ester (PFP) are two chemical molecules that have previously been used as surface modifiers of stainless steel and quartz. BTS was recently used as a surface coating on stainless steel to bind antibodies, which could then in principle be used to bind specific biomarkers on circulating endothelial cells. For this stent application, it is important that the surface coatings show minimal chemical change over time, when placed in a physiological environment. This investigation involved assessing the long-term stability of BTS and PFP coatings on stainless steel. Surface characterization techniques like X-ray photoelectron spectroscopy, contact angle goniometry and atomic force microscopy were used to analyze the integrity and composition of the adlayers upon immersion in physiological buffer solution.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".