Bibliographic record
Abstract
Background: Periodontitis is associated with shifts in the balance of the microbial composition of subgingival biofilms. Many species that predominate in disease have not been isolated from healthy sites or are found in low abundance, raising questions as to the reservoir or origin of these putative pathogens. \nAims: This project aims to generate an in vitro model of dysbiosis to demonstrate whether it is possible to observe the outgrowth of low abundance disease-associated species from biofilms taken from healthy sites and subjects by mimicking a disease-promoting environment. \nMaterials and Methods: The Calgary Biofilm Device and several types of protein-rich media were used to culture five-species microbial communities. Then, the optimised model was used to culture complex biofilms using an inoculum of plaque and saliva from healthy young adult volunteers in media mimicking the nutritional status of the inflamed periodontal pocket. Later, three-week complex biofilms were cultured just in sterile human saliva to see whether changes in the enriched biofilms could be reversed. Metagenomics was used to characterise the taxonomy and functional potential of biofilms, and longitudinal comparisons were performed on biofilms and the inoculum. \nResults: The inoculum consisted mainly of health-associated genera, such as Streptococcus, Actinomyces and Haemophilus. After culture in various media for one or three weeks, the biofilm composition shifted and numerous fastidious and periodontal disease-associated species belonging to genera Bacteroidetes, Fretibacterium, Prevotella and Alloprevotella were enriched. These enriched biofilms, subsequently cultured solely in human saliva, showed a minor decrease in disease associated-species. There was a shift in functional activities, with cultured biofilms having a greater abundance of genes associated with virulence. \nConclusion: The results suggest that the source of the periodontal pathogens is the healthy human mouth, and that these species can be enriched at the expense of health-associated species in a nutritional environment resembling inflammation.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".