Circulating undercarboxylated osteocalcin and gingival crevicular fluid tumour necrosis factor‐<i>α</i> in children
Bibliographic record
Abstract
BACKGROUND: Osteocalcin, a protein secreted by osteoblasts during bone formation, is negatively associated with adult periodontal disease. Little is known about this association in children. AIM: To examine the extent to which plasma undercarboxylated osteocalcin (ucOC) is associated with gingival crevicular fluid tumour necrosis factor-alpha (GCF TNF-α) - a potential marker of gingival inflammation - in children. METHODS: We used data from the Quebec Adipose and Lifestyle InvesTigation in Youth cohort, an ongoing longitudinal study on the natural history of obesity among Caucasian children with a family history of obesity in Quebec, Canada. This cross-sectional analysis from the baseline visit includes 120 children aged 8-10 years. Plasma ucOC and GCF TNF-α levels were determined by enzyme-linked immunosorbent assay. Linear regression analyses, adjusting for age, gender, family income, sexual maturity stage, daily physical activity, obesity, and fasting glucose were conducted, with TNF-α level as the dependent variable. RESULTS: A 1-ng/ml increase in ucOC was associated with a 0.96% decrease (95% confidence interval (CI): -1.69, -0.23) in GCF TNF-α level. CONCLUSION: A negative association between a marker of bone formation and a marker of gingival inflammation was observed as early as childhood among Caucasian children with a family history of obesity.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".