Salivary and serum inflammatory mediators among pre-conception women with periodontal disease
Bibliographic record
Abstract
BACKGROUND: There have been inconsistent conclusions regarding the levels of inflammatory mediators in saliva and serum among people with or without periodontal disease. Although pre-conception has been put forward as the optimal time for the periodontal treatment in order to improving pregnancy outcomes, few studies have been conducted to examine inflammatory mediators in saliva and serum among pre-conception women. METHODS: Pre-conception women were recruited between January 2012 and December 2014. Women were provided with an oral health examination to detect periodontal disease. Salivary and serum samples were collected at the same of examination. Inflammatory mediators includinginterleukin-1 beta (IL-1β), IL-6, tumor necrosis factor alpha (TNF-α) and beta-glucuronidase (β-glucuronidase) were tested and analyzed among women with overall periodontal disease (n = 442) or moderate/severe periodontal disease (n = 247). Results were compared to that in women with a healthy periodontium (n = 91). RESULTS: Significantly increased concentrations of inflammatory mediators of IL-1β, IL-6, TNF-α and β-glucuronidase in saliva and IL-1β, β-glucuronidase and TNF-α in serum were found among pre-conception women with moderate/severe periodontal disease, compared with women without periodontal disease. Significantly increased levels were also found in all the above saliva inflammatory mediators and in serum IL-1β and TNF-α among women with overall periodontal disease. The levels of all inflammatory mediators in saliva and almost all inflammatory mediators except IL-6 in serum significantly increased with severity of periodontal disease. CONCLUSION: Periodontal disease is highly associated with the elevated levels of inflammatory mediators in saliva and some mediators in serum among pre-conception women.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".