Comparison of cell viabilityand cytotoxicity of MTA,45S5 and niobiophosphatebioactive glass
Bibliographic record
Abstract
Aim: This current in vitro study investigated the cytotoxicity and the ability to maintain cell viability of two bioglasses, the commercial 45S5 (Sylc®, OSspray Ltd, London, UK) and the experimental NbG (niobiophosphate bioactive glass), in comparison to MTA (MTA Angelus®, Parana, Brazil). Methods: In the cell viability assay, human gingival fibroblasts were exposed to the bioactive materials/cements (NbG; 45S5; and MTA) diluted in the cell culture medium. According to ISO 10993-5, a cytotoxic effect was considered when there was a decrease in cell viability of more than 30%. The three bioactive materials were also analyzed under SEM (TM 3030, Hitachi, Tokyo, Japan) to assess the mean particle size, and under EDX analysis (EDX-720, Shimadzu, Tokyo, Japan) to verify composition and the presence of contaminants. Results: Human gingival fibroblasts had the highest cell viability when exposed to NbG (p<0.001). The control group and the MTA group had similar values (p=0.2341). The lowest cell viability occurred for the 45S5 group (p<0.001). The average particle size of the materials tested was 5.2μm for 45S5; 54.0μm for NbG; and 4.0μm for MTA. 45S5 and NbG showed the presence of Si, Ca, and P. Conclusion: The 45S5 bioglass was cytotoxic to fibroblasts, while MTA was not. The addition of niobium into the bioglass composition is advantageous.
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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) | 0.001 | 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".