Mounting ground sections of teeth: Cyanoacrylate adhesive versus Canada balsam
Bibliographic record
Abstract
INTRODUCTION: Hard tissues can be studied by either decalcification or by preparing ground sections. Various mounting media have been tried and used for ground sections of teeth. However, there are very few studies on the use of cyanoacrylate adhesive as a mounting medium. AIMS: The aim of our study was to evaluate the efficacy of cyanoacrylate adhesive (Fevikwik™) as a mounting medium for ground sections of teeth and to compare these ground sections with those mounted with Canada balsam. MATERIALS AND METHODS: Ground sections were prepared from twenty extracted teeth. Each section was divided into two halves and mounted on one slide, one with cyanoacrylate adhesive (Fevikwik™) and the other with Canada balsam. Scoring for various features in the ground sections was done by two independent observers. STATISTICAL ANALYSIS USED: Statistical analysis using Student's t-test (unpaired) of average scores was performed for each feature observed. RESULTS: No statistically significant difference was found between the two for most of the features. However, cyanoacrylate was found to be better than Canada balsam for observing striae of Retzius (P < 0.0205), enamel lamellae (P < 0.036), dentinal tubules (P < 0.0057), interglobular dentin (P < 0.0001), sclerotic dentin - transmitted light (P < 0.00001), sclerotic dentin - polarized light (P < 0.0002) and Sharpey's fibers (P < 0.0004). CONCLUSIONS: This initial study shows that cyanoacrylate is better than Canada balsam for observing certain features of ground sections of teeth. However, it remains to be seen whether it will be useful for studying undecalcified sections of carious teeth and for soft tissue sections.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".