Hyperhomocysteinemia: an instigating factor for periodontal disease
Bibliographic record
Abstract
Hyperhomocysteinemia (HHcy) affects bone remodeling, since a destructive process in cortical alveolar bone has been linked to it; however, the mechanism remains at large. HHcy increases proinflammatory cytokines viz. TNF-α, IL-1b, IL-6, and IL-8 that leads to a cascade that negatively impacts methionine metabolism and homocysteine cycling. Further, chronic inflammation decreases vitamins B12, B6, and folic acid that are required for methionine homocysteine homeostasis. This study aims to investigate a HHcy mouse model (cystathionine β-synthase deficient, CBS+/–) for studying the potential pathophysiological changes, if any, in the periodontium (gingiva, periodontal ligament, cement, and alveolar bone). We compared the periodontium side-by-side in the CBS+/– model with that of the wild-type (C57BL/6J) mice. Histology and histomorphometry of the mandibular bone along with gene expression analyses were carried out. Also, proangiogenic proteins and metalloproteinases were studied. To our knowledge, this research shows, for the first time, a direct connection between periodontal disease during CBS deficiency, thereby suggesting the existence of disease drivers during the hyperhomocysteinemic condition. Our findings offer opportunities to develop diagnostics/therapeutics for people who suffer from chronic metabolic disorders like HHcy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".