Biochemical parameters and oxidative stress markers in Tunisian patients with periodontal disease
Bibliographic record
Abstract
BACKGROUND: Oxidative stress is involved in many diseases including diabetes and cancer. Numbers of studies have suggested its involvement in the pathogenesis of periodontal diseases. The aim of this study was to evaluate the levels of biochemical parameters and oxidative stress markers in plasma of healthy and chronic periodontitis patients. METHODS: One hundred thirty subjects were divided into two groups; patients (mean age = 42 ± 13.6 y.o) and control (mean age = 44.8 ± 12.6 y.o). Patients and healthy subjects were free from any infection, coronary or heart disease, diabetes or liver failure. Total cholesterol, LDLc, HDLc, Triglycerides (TG), creatinine, uric acid (UA), glucose and urea levels as well as the activities of enzymatic antioxidants such as catalase, glutathione reductase (GR) and total antioxidant capacity (TAOC), were measured in plasma samples using colorimetric assays. Statistical differences between groups were determined by Student's t-test and p ≤ 0.05 was considered as significant. RESULTS: Periodontitis patients exhibited significant decrease in the activities of catalase, TAOC, GR and TG, cholesterol, LDLc, glucose, HDLc, uric acid levels in plasma samples in comparison with healthy subjects. However, no statistically significant differences in the levels of creatinine and urea were observed between the two groups. CONCLUSION: The reduction of plasma antioxidant activities (Catalase, TAOC, GR) may have a role in the pathogenesis of periodontal diseases. Our findings suggest a decrease in the host capacity to control the damage caused by oxidative stress. Therefore, therapeutic strategies, aiming at modulating the oxidative stress could be considered as potential tools for the prevention or treatment of periodontal diseases and their potential systemic effects on the general health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".