Beneficial microbes for the oral cavity: time to harness the oral streptococci?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Indigenous microbes are known to influence human health outcomes and various approaches are now being made to positively modulate these microbe-induced outcomes via the administration of probiotics. The application of probiotics that are specific to the oral cavity is a relatively undeveloped field, and their emergence has largely occurred as a reasoned follow-up to initial studies in which probiotics that had already been developed and obtained regulatory approval for intestinal applications were then also evaluated for their putative influence on oral microbiota functionality. These attempts to extend the application of existing probiotics were probably at least in part motivated by recognition of the substantial safety and regulatory hurdles that must be overcome prior to the introduction of a novel probiotic agent. Nevertheless, from an efficacy perspective it appears more logical to develop microbes of oral origin as the specific providers of probiotic solutions for oral diseases, rather than attempting to adapt intestinally-derived strains for this role. Oral bacteria and their bioactive molecules have evolved to operate optimally in this environment and in some cases are known to persist only in oral sites. Amongst the bacteria of more than 700 species now identified within the human oral microbiota, it is the streptococci that are numerically predominant. Although this review highlights the development of the oral cavity bacterium Streptococcus salivarius as an oral probiotic, a number of other streptococcal species have also been shown to have considerable potential as probiotic candidates.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.011 |
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 it