Endodontic pathogens possess collagenolytic properties that degrade human dentine collagen matrix
Bibliographic record
Abstract
AIM: To measure collagenolytic protease activity from Enterococcus faecalis and Micrococcus luteus and their ability to degrade human dentinal collagen. METHODOLOGY: Proteases activity of E. faecalis ATCC 29212, ATCC 47077 and M. luteus towards generic and specific human matrix metalloproteinase (MMP) substrates was measured using a fluorimetric assay. The ability of the bacteria to degrade dentinal collagen was tested by quantifying the amount of hydroxyproline released into the media following incubation of the bacteria or heat-inactivated bacteria (HIN) with demineralized human dentine samples for 24 h and by scanning electron microscopy (SEM). Multifactorial anova and Tukey's post hoc test were used to analyse the data (P < 0.05). RESULTS: ). SEM revealed increased collagen network degradation after incubation with bacteria versus HIN. CONCLUSIONS: Endodontic pathogens possess collagenolytic protease properties that enable them to degrade dentinal collagen, potentially compromising the restoration-tooth and sealer-tooth interfaces. These collagenolytic protease properties could facilitate the migration of pathogenic bacteria into the root canal system and explain in part their role in root canal infections.
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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 | 0.001 |
| 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".