COMPARATIVE ANALYSIS OF SUBCUTANEOUS CONNECTIVE TISSUE RESPONSES TO CALCIUM ALUMINATE AND NANOSTRUCTURED TRICALCIUM SILICATE NANOMATERIALS IN MOUSE MODELS
Bibliographic record
Abstract
This study aimed o evaluate connective tissue reaction to experimental nanomaterial based on calcium aluminate (ALBO-CA) and commercial nanostructured tricalcium silicate DiaRoot Bioaggregate (DiaDent Group International, Burnaby, BC, Canada) in Wistar rats.The study included 36 rats aged from 10 to 11 weeks. In all animals, an incision took place on the back and two pockets of 15 mm in depth were made, in which sterile polyethylene tubes with test materials (ALBO-CA -Group F, Diaroot Bioaggregat- Group C) were implemented. The empty half of the tubes represented a negative control. After 7, 15, and 30 days (n=12), the animals were euthanized, and the tissues were processed for histological evaluation using hematoxylin-eosin (HiE) staining. Patohystological analysis included: inflammation, bleeding, fibrous capsule, and tissue integrity around the implanted material. Data were analyzed by the Mann -Whitney U test.ALBO-CA induced a statically significantly less inflammatory response after 15 (U=42.000, Z=-2.460, p=0.014) and after 30 days (U=42.000, Z=-2.198 p=0.028). At the end observation period significantly less vascular congestion (U=42.000, Z=-2.460, p=0.014) and significantly greater preservation of connective tissue integrity was noted (U =36.000, Z=-2.769, p=0.006) after ALBO-CA implantation compared to Diaroot Bioaggregate. There were no statistically significant difference in the fibrous capsule formation between the tested materials across all observation periods. The tested materials proved to be biologically acceptable, with the experimental nanostructured ALBO-CA showing a slightly better tissue response after subcutaneous implantation in rats.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".