High Boron Content Enhances Bioactive Glass Biodegradation
Bibliographic record
Abstract
Derived Hench bioactive glass (BaG) containing boron (B) is explored in this work as it plays an important role in bone development and regeneration. B was also found to enhance BaG dissociation. However, it is only possible to incorporate a limited amount of B. To increase the amount of B in BaG, bioactive borosilicate glasses (BaG-Bx) were fabricated based on the use of the solution-gelation process (sol-gel). In this work, a high B content (20 wt.%) in BaG, respecting the conditions of bioactivity and biodegradability required by Hench, was achieved for the first time. The capability of BaG-Bx to form an apatite phase was assessed in vitro by immersion in simulated body fluid (SBF). Then, the chemical structure and the morphological changes in the fabricated BaG-Bx (x = 0, 5, 10 and 20) were studied. The formation of hydroxyapatite (HAp) layer was observed with X-ray diffraction (XRD) and infrared (IR) spectroscopy. The presence of HAp layer was confirmed using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Enhanced bioactivity and chemical stability of BaG-Bx were evaluated with an ion exchange study based on Inductively Coupled Plasma–Optical Emission Spectrometry (ICP-OES) and energy dispersive spectroscopy (EDS). Results indicate that by increasing the concentration of B in BaG-Bx, the crystallization rate and the quality of the newly formed HAp layer on BaG-Bx surfaces can be improved. The presence of B also leads to enhanced degradation of BaGs in SBF. Accordingly, BAG-Bx can be used for bone regeneration, especially in children, because of its faster degradation as compared to B-free glass.
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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".