The Subgingival Microbiota of Papillon‐Lefèvre Syndrome
Bibliographic record
Abstract
BACKGROUND: There is little information about the microbiologic profiles of periodontal lesions in Papillon-Lefèvre syndrome (PLS) and the significance of bacteria in the pathogenesis of periodontitis in these patients. This comprehensive analysis of the subgingival microbiota in patients with PLS used 16S ribosomal RNA (rRNA) clonal analysis and the 16S rRNA-based Human Oral Microbe Identification Microarray (HOMIM). METHODS: Thirteen patients with PLS from seven unrelated families volunteered for this microbiologic study. Subgingival plaque was collected with sterile paper points from multiple sites with ≥5 mm probing depth, and whole genomic DNA was extracted. The 16S rRNA genes were amplified, cloned, and sequenced. The samples were then probed for ≈300 predominant oral bacterial species using the HOMIM. RESULTS: The most commonly detected phylotypes in the clonal analysis were Gemella morbillorum, Gemella haemolysans, Granulicatella adiacens, Lachnospiraceae OT 100 (EI074), Parvimonas micra, Selenomonas noxia, and Veillonella parvula. As a group, streptococci were commonly detected in these individuals. In the HOMIM analysis, a total of 170 bacterial species/phylotypes were detected, with a range of 40 to 80 species per patient with PLS. Of these, 12 bacterial species were detected in medium to high levels in ≥50% of the individuals. The high-frequency strains were clustered into eight groups: Aggregatibacter actinomycetemcomitans, Campylobacter spp., Capnocytophaga granulosa, G. morbillorum, P. micra, Porphyromonas endodontalis, Streptococcus spp., and Tannerella forsythia. CONCLUSIONS: The subgingival microbiota in PLS is diverse. Periodontal pathogens commonly associated with chronic and aggressive periodontitis and opportunistic pathogens may be associated with the development of severe periodontitis in patients with PLS.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".