Gut microbiota and the periodontal disease: role of hyperhomocysteinemia
Bibliographic record
Abstract
Periodontal disease is one of the most common conditions resulting from poor oral hygiene and is characterized by a destructive process in the periodontium that essentially includes gingiva, alveolar mucosa, cementum, periodontal ligament, and alveolar bone. Notably, the destructive event in the alveolar bone has been linked to homocysteine (Hcy) metabolism; however, it has not been fully investigated. Therefore; the implication of Hcy towards initiation, progression, and maintenance of the periodontal disease remains incompletely understood. Higher levels of Hcy (also known as hyperhomocysteinemia (HHcy)) exerts deleterious effects on gum health and teeth in distinct ways. Firstly, increased production of proinflammatory cytokines such as TNF-α, IL-1β, IL-6, and IL-8 leads to an inflammatory cascade of events that affect methionine (Met) and Hcy metabolism (i.e., 1-carbon metabolism) leading to HHcy. Secondly, metabolic dysregulation during chronic medical conditions increases systemic inflammation leading to a decrease in vitamins, more specifically B6, B12, and folic acid, that play important roles as cofactors in Hcy metabolism. Also, given the folate level in the HHcy state that is important during dysbiosis, these two conditions appear to be intimately related, and in this context, HHcy-induced dysbiosis may be one of the potential causes of periodontal disease. This paper sums up the link between periodontitis and HHcy, with a special emphasis on the "oral-gut microbiome axis" and the potential probiotic intervention towards warding off some of the serious periodontal disease conditions.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".