Dual Structural Role of Niobium in Bioactive Borate Glasses Modulates Bioactivity, Cytocompatibility, and Hemostatic Potential
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Designing bioactive glasses with tunable biological responses requires a precise understanding of how network modifiers influence structure–property relationships. This work investigates the effect of incorporating niobium pentoxide (Nb 2 O 5 ) into melt-derived borate glasses, aiming to uncover how Nb affects the glass structure and its multifunctional biological performance. Glasses with nominal compositions: 60B 2 O 3 –(19- x /2)CaO–(19- x /2)Na 2 O–2P 2 O 5 – x Nb 2 O 5 ( x = 0, 2.5, 5, 7.5, and 10 wt %) were synthesized and comprehensively characterized. A key finding is the dual structural role of Nb: it predominantly acts as a network former at ≤5 wt % and as a network modifier at higher contents. This transition directly influences the glass network connectivity, as supported by physical, thermal, and vibrational techniques, and reflected a conversion from BO 4 to BO 3 units with an increase in Nb content, correlating with a modification in hardness and elastic modulus. Structural changes also suppressed surface reactivity and ion release, leading to a modulation in hydroxycarbonate apatite formation in simulated body fluid. On the other hand, glasses containing Nb maintained or enhanced cytocompatibility with human adipose mesenchymal stem cells. In contrast, Nb-containing glasses demonstrated reduced hemostatic potential, likely due to Nb forming niobate complexes that may influence ion exchange and clotting pathways. Overall, these findings shed light on the potential of Nb incorporation as a strategy to tailor the multifunctional properties of bioactive borate glasses for targeted biomedical applications and offer a fresh perspective on how the dual structural role of niobium contributes to their overall performance within the context of biomaterials.
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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".