Evidence of oxidative stress in temporomandibular disorders: a pilot study
Bibliographic record
Abstract
Oxidative stress is involved in the pathogenesis of many conditions and is caused by free radicals in concentrations that overwhelm the natural scavenging mechanisms and cause pain and inflammation. This investigation sought to determine whether pain from temporomandibular disorders was associated with increased oxidative stress as measured by biomarkers in saliva and serum. Both salivary and serum levels of the oxidative stress biomarkers including 8-hydroxydeoxyguanosine, malondialdehyde and total antioxidant status were compared in patients with mild and severe TMJD pain and with healthy controls. These biomarkers were determined spectrophotometrically in saliva and serum from 10 high TMJD pain patients, 10 low TMJD pain patients, and 10 healthy control subjects from National Institute of Dental Research's TMJ Implant Registry and Repository. Linear and logistic regression analyses were used to evaluate the association between each biomarker and TMJD pain. The mean levels of log 8-hydroxydeoxyguanosine (saliva P < 0·0001, serum P = 0·0008), malondialdehyde (saliva P = 0·002, serum P = 0·004) and total antioxidant status (saliva P = 0·005; serum P = 0·001) achieved statistically significant differences between groups. In linear regression analysis, both salivary and serum levels of each biomarker were associated with TMJD pain. In a multivariable analysis, again, both salivary levels and serum levels were also different between groups. Salivary levels of oxidative stress ratios of 8-hydroxydeoxyguanosine, malondialdehyde and total antioxidant status were significantly different between patients with TMJD pain and controls and was comparable to that in serum. These biomarkers hold promise as a potential diagnostic and therapeutic strategy.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".