Relationship between <i>Campylobacter rectus</i> and periodontal status during pregnancy
Bibliographic record
Abstract
INTRODUCTION: In a previous study, we showed that the growth of Campylobacter rectus is stimulated by the presence of female sex hormones in the culture medium. In the present study, we examined the relationship between C. rectus levels in the saliva and the periodontal status of pregnant women. METHODS: Unstimulated whole saliva was collected from 22 pregnant and 15 non-pregnant women. Periodontal pocket depth (PD) and bleeding on probing (BOP) were recorded. A quantitative real-time polymerase chain reaction was performed to determine the concentrations of suspected periodontopathogenic bacteria in the saliva samples. In addition, the concentration of estradiol in the saliva samples was measured by enzyme immunoassay. RESULTS: The average age, number of teeth, and total number of bacteria in the saliva of subjects in both groups were similar. The percentage of sites with a PD = 4 mm and the salivary estradiol concentrations were significantly higher in pregnant women than in non-pregnant women. In addition, the percentage of BOP sites and the C. rectus levels in the saliva of the pregnant women tended to be higher than in non-pregnant women, although these differences were not statistically significant. There were positive correlations between C. rectus levels and estradiol concentrations, and between C. rectus levels and the percentage of sites with PD = 4 mm in the pregnant women. CONCLUSION: These results indicate that C. rectus levels are higher in the oral flora of pregnant women and that this may be associated with increased salivary estradiol concentrations. This may contribute to periodontal disease progression during pregnancy.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".