Application of Raman Spectroscopy and Micro‐Indentation to Micro‐Map the Path and Boundary of NaOCI‐Induced Dentine Collagen Changes in an Ex‐Vivo Root Canal Irrigation Model
Bibliographic record
Abstract
OBJECTIVES: To apply Raman spectroscopy and micro-indentation to micro-map the path and boundary of NaOCl-induced dentine collagen changes in an ex-vivo root canal irrigation model. MATERIAL AND METHODS: Root canals of extracted single-rooted teeth were prepared and irrigated with NaOCl or saline. Four teeth (NaOCl = 3; saline = 1) embedded in epoxy resin and sectioned transversely into discs were Raman-analyzed on coronal surfaces from inter- and intra-tubular dentine in 4 quadrants over 12, 24, and 48 min-acquisition times. Eight additional teeth stratified by root maturity, irrigated with NaOCl (n = 7) or saline (n = 1), sectioned transversely and then embedded, were Raman-analyzed on apical surfaces at 18 equidistant (50 μm) points/quadrant for Amide bands. Micro-indentation of the corresponding facing sectioned surface was correlated with Amide band changes. Generalized linear and non-linear regression models were used for data analysis. RESULTS: Spectral quality at 24/48 min was similar and better than at 12 min. Inter-tubular but not intra-tubular spectra were masked by fluorescence. Spectral features near the canal lumen ( < 500 μm) showed more significant collagen alteration and varied by tooth/quadrant but decreasingly towards the cemento-dentinal junction (CDJ) without a clear boundary. Significant (p < 0.0001) changes in Amide I/III bands up to 300 μm from the canal and were accompanied by deeper corresponding indentations upto 200 μm. Canal instrumentation had a significant (p < 0.0001) effect on both Amide-I and Amide-III bands. CONCLUSIONS: NaOCl altered dentinal collagen and reduced microhardness but varied with quadrants/teeth, without a definable boundary; collagen changes were obvious within 300 μm of the canal and microhardness changes within 200 μm but evident to a decreasing extent up to the CDJ.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".