Presence of archaea and selected bacteria in infected root canal systems
Bibliographic record
Abstract
Infections of the root canal have polymicrobial etiology. The main group of microflora in the infected pulp is bacteria. There is limited data that archaea may be present in infected pulp tissue. The aim of this study was to check the prevalence of archaea in necrotic root canal samples obtained from patients with primary or post-treatment infection. The prevalence of selected bacteria species (Prevotella intermedia, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Synergistes sp.) in necrotic samples was evaluated as well. Sixty-four samples from root canal were collected for DNA and RNA extraction. A PCR assay based on the 16S rRNA gene was used to determine the presence of archaea and selected bacteria. Of the 64 samples, 6 were analyzed by semiquantitative reverse transcription PCR to estimate expression profiles of 16S rRNA, and another 9 were selected for direct sequencing. Archaea were detected in 48.4% samples. Statistical analysis indicated a negative association in coexistence between archaea and Treponema denticola (P < 0.05; Pearson’s χ2 test). The main representative of the Archaea domain found in infected pulp tissue was Methanobrevibacter oralis. Archaea 16S rRNA gene expression was significantly lower than Synergistes sp., Porphyromonas gingivalis, and Tannerella forsythia (P < 0.05; Student’s t test). Thus, it can be hypothesized that archaea may participate in the endodontic microbial community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".