Biocompatible Carbohydrate-Functionalized Stainless Steel Surfaces: A New Method For Passivating Biomedical Implants
Bibliographic record
Abstract
A convenient method for passivating and functionalizing stainless steel is described. Several methods of coating stainless steel (SS) samples with silica were investigated and of these methods, a thin (less than 15 nm thick) layer of silica created by atomic layer deposition (ALD) was found to give superior performance in electrochemical testing. These interfaces were then used as a platform for further functionalization with molecules of biological interest. Specifically, the SS samples were functionalized with biologically significant carbohydrates [N-acetyl-D-glucosamine (GlcNAc) and D-galactose (Gal)] that contain trialkoxysilane derivatives as chemical handles for linking to the surface. The presence and biological availability of these moieties on the silica coated SS were confirmed by XPS analysis and an enzyme-linked lectin assay (ELLA) using complementary lectins that specifically recognize the surface-bound carbohydrate. This method has the potential of being adapted to the functionalization of stainless steel biomedical implants with other biologically relevant carbohydrates.
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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) | 0.001 | 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 | 0.000 |
| 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".