Bioactive coatings for direct skeletal attachment applications for lower limb prostheses
Bibliographic record
Abstract
To tackle the current drawbacks with metallic implants used in direct skeletal attachment, novel bioactive glasses are considered as implant coatings in order to reduce bacterial infections and promote bone cell growth. Silica-based and borate-based glasses, with increasing amounts of titanium dioxide at the expense of either silica (for the silica-based glasses) or borate (for the borate-based glasses), respectively, were synthesized and characterized to determine the parameters that define a glass capable of inhibiting bacterial growth, stimulating cell proliferation and offering mechanical stability when enameled into a surgical alloy. The effect of substituting the glass backbone with titanium dioxide, in both glass series, is also investigated with respect to its effect on both biocompatibility and mechanical properties of the resultant glass/implant constructs. Borate-based glasses exhibited greater processing windows compared to the silica-based glasses, making them more desirable for coating applications. They also exhibited superior performance in terms of their in vitro bioactivity and biocompatibility, over their silica-based counterparts, due to their higher solubility and greater ability to inhibit S. epidermidis and E. coli bacteria. Specifically, glass BRT0 (control borate-based glass, with no titanium incorporated) exhibited an inhibition zone against S. epidermidis of 17.5 mm and a mass loss of 40% after 30 days, with BRT3 (borate-based glass, with 15 mol% titanium incorporated) exhibiting an inhibition zone against S. epidermidis of 7.6 mm and a mass loss of 34% after 30 days. Furthermore, borate-based glasses with greater titanium dioxide contents exhibited superior mechanical properties (e.g. bulk hardness, and critical strain energy release rates), which could be attributed to their more closely matched coefficients of thermal expansion with the titanium alloy substrate, Ti6Al4V, to which they were adhered. The critical strain energy release rates in mode I for the silica-based coating/substrate system ranged from 6.2 J/m2 (for SRT0, control silica-based glass with no titanium) to 12.08 J/m2 (for SRT3), whereas for the borate-based systems they ranged from 10.86 J/m2 (for BRT0) to 18.5 J/m2 (for BRT3), with the increase for the borate-based glasses being attributed to the presence of compressive residual stresses in the coating after application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 | 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".