Molecular detection and genotyping of Porphyromonas Gingivalis directly from oral rinse: Implications for Periodontitis pathogenesis
Bibliographic record
Abstract
Porphyromonas gingivalis is a Gram-negative anaerobe implicated as a primary etiological agent in chronic periodontitis, characterized by progressive inflammation and degradation of periodontal structures. The bacterium's pathogenicity is closely associated with its expression of distinct fimbrial subunits encoded by the fimA gene, which serves as a pivotal marker for strain differentiation and genotyping. Profiling the distribution of fimA genotypes in clinical specimens is vital for elucidating the pathogen's role in the etiology and progression of periodontitis. In this study, we developed a highly sensitive and specific real-time PCR assay utilizing TaqMan probe technology for the direct detection and genotyping of P. gingivalis fimA variants in oral rinse samples. The assay was designed to investigate both the prevalence and distribution of the six fimA genotypes (I, Ib, II, III, IV, and V) among individuals with periodontitis compared to periodontally healthy controls. A cohort of 30 participants, comprising 12 healthy individuals and 18 patients diagnosed with periodontitis, provided oral rinse samples for analysis. The real-time PCR assay, employing genotype-specific primers and TaqMan probes, demonstrated robust performance in discriminating the six recognized fimA genotypes. The assay achieved a detection rate of 94.4% in periodontitis samples, accurately identifying all fimA genotypes directly from the oral rinse specimens. The most prevalent fimA genotype identified was Ib, occurring in 33.33% of the samples. This was followed by genotype II, with a frequency of 27.78%. Genotype IV was found in 16.67% of samples, and genotype I was present in 5.56% of samples. Additionally, 16.67% of the samples contained combinations of two fimA types, including II,Ib; II,III; and II,IV. Among these, genotype II was the most frequently detected in combination with other genotypes. The linear regression analysis yielded a slope of -3.42, corresponding to an amplification efficiency of 94.5%, underscoring the assay's precision and reliability. The data indicate a potential contributory role of fimA genotypes Ib and II in periodontitis pathogenesis, establishing the developed PCR assay as a valuable diagnostic and epidemiological tool for monitoring P. gingivalis in clinical settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".