Bibliographic record
Abstract
Hydroxyapatite (HA)-coated Ti6Al4V stems are currently used in total hip replacement (THR) surgeries. However, the residual stress in the HA coating due to mismatch in coefficient of thermal expansion (CTE) between HA and Ti6Al4V limits their application. Borate-based glasses can be promising alternatives to HA because of their similar CTEs to that of Ti6Al4V and excellent bioactivity that can promote bone repair. In this project, six borate-based glasses (Ly-B0, Ly-B1, Ly-B2, Ly-B3, Ly-B4, Ly-B5) from the B2O3-P2O5-CaO-Na2O-TiO2-SrO series were formulated by increasing the concentration of strontium oxide (SrO)from 0 to 25 in mol% at the expense of B2O3 in the glass series. Increased SrO content induced larger amounts of non-bridging oxygens and resulted in gradual increases in glass transition temperature (Tg). Discs of each glass powder were immersed in de-ionized water under 1, 7 and 30 days, and then the water extracts were used to determine the solubility and osteo-stimulatory effect of the glasses. Sr2+ doping retarded the dissolution rate of the glasses and the higher levels of Sr2+ doping (20 mol% and 25 mol%) promoted proliferation of osteoblasts. Except for Ly-B5 (containing 25 mol% SrO), discs of each glass powder exhibited bacteriostatic behavior against Staphylococcus aureus after 24 hours exposure. The glasses were enamelled onto Ti6Al4V substrates, and then bi-layer double cantilever beam (DCB) specimens were manufactured to measure the Mode I (GIC) and Mode II (GIIC) energy release rate of the glass coating/Ti6Al4V constructs. The mean GIC values increased from 6.56 ± 0.9 to 14.6 1 ± 2.1 J/m2 with increasing SrO content from Ly-B0 to Ly-B5, and the mean GIIC values increased from 36.07 ± 3.8 to 46.92 ± 3.3 J/m2 with increasing SrO content from Ly-B0 to Ly-B5, indicating that the incorporation of 15-25 mol% SrO significantly increased the fracture toughness of the construct. Moreover, the GIC and GIIC values of the coating/substrate system for all the six glasses significantly reduced (p ≤ 0.05) due to degradation in de-ionized water.
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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) | 0.000 | 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) | 0.001 | 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".