Implications of Systemic Inflammation and Periodontitis for Major Depression
Bibliographic record
Abstract
Increasing evidence suggests that infection and persistent low-grade inflammation in peripheral tissues are important pathogenic factors in major depression. Major depression is frequently comorbid with systemic inflammatory diseases/conditions such as rheumatoid arthritis, allergies of different types, multiple sclerosis, cardiovascular disease, inflammatory bowel disease, chronic liver disease, diabetes, and cancer, in which pro-inflammatory cytokines are overexpressed. A number of animal studies demonstrate that systemic inflammation induced by peripheral administration of lipopolysaccharide increases the expression of pro-inflammatory cytokines in both the periphery and brain and causes abnormal behavior similar to major depression. Systemic inflammation can cause an increase in CNS levels of pro-inflammatory cytokines associated with glial activation, namely, neuroinflammation, through several postulated pathways. Such neuroinflammation can in turn induce depressive moods and behavioral changes by affecting brain functions relevant to major depression, especially neurotransmitter metabolism. Although various clinical studies imply a causal relationship between periodontitis, which is one of the most common chronic inflammatory disorders in adults, and major depression, the notion that periodontitis is a risk factor for major depression is still unproven. Additional population-based cohort studies or prospective clinical studies on the relationship between periodontitis and major depression are needed to substantiate the causal link of periodontitis to major depression. If such a link is established, periodontitis may be a modifiable risk factor for major depression by simple preventive oral treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".