Investigation of a cyanine dye assay for the evaluation of the biocompatibility of magnesium alloys by direct and indirect methods
Bibliographic record
Abstract
Magnesium and its alloys are promising candidates for a new generation of biodegradable metals in orthopaedic applications due to their excellent biocompatibility, biodegradability, and mechanical properties that are similar to natural bone. However, direct in vitro assessment of these materials in the presence of cells is complicated by degradation products from the alloy that lead to a false positive for the most commonly used cell adhesion and cell proliferation assays. In this paper, a cyanine dye was used to quantitatively evaluate the in vitro biocompatibility of a Mg AZ31 alloy by both direct and indirect methods. The cytotoxicity of the corrosion products was evaluated via an indirect method; a 25% decrease in cell viability compared to control samples was observed. Moreover, direct assessment of cell adhesion and proliferation showed a statistically significant increase in cell number at the surface after 72 h. In addition, the degradation rate and surface characteristics of the Mg AZ31 alloy were evaluated for both direct and indirect tests. The degradation rate was unaffected by the presence of cells while evidence of an increase in calcium phosphate deposition on the magnesium alloy surface in the presence of cells was observed. This study demonstrates that a cyanine dye based assay provides a more accurate assessment of the overall in vitro biocompatibility of biodegradable metals than the more commonly used assays reported in the literature to date.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".