Evaluation of Rouxiella badensis Subsp Acadiensis (Canan SV-53) as a Potential Probiotic Bacterium
Bibliographic record
Abstract
The advent of omic platforms revealed the significant benefits of probiotics in the prevention of many infectious diseases. This led to a growing interest in novel strains of probiotics endowed with health characteristics related to microbiome and immune modulation. Therefore, autochthonous bacteria in plant ecosystems might offer a good source for novel next-generation probiotics. The main objective of this study was to analyze the effect of Rouxiella badensis acadiensis Canan (R. acadiensis) a bacterium isolated from the blueberry biota, on the mammalian intestinal ecosystem and its potential as a probiotic microorganism. R. acadiensis, reinforced the intestinal epithelial barrier avoiding bacterial translocation from the gut to deep tissues, even after feeding BALB/c mice for a prolonged period of time. Moreover, diet supplementation with R. acadiensis led to increases in the number of Paneth cells, well as an increase in the antimicrobial peptide α defensin. The anti-bacterial effect of R. acadiensis against Staphylococcus aureus and Salmonella enterica serovar Typhimurium was also reported. Importantly, R. acadiensis-fed animals showed better survival in an in vivo Salmonella enterica serovar Typhimurium challenge compared with those that received a conventional diet. These results demonstrated that R. acadiensis possesses characteristics of a probiotic strain by contributing to the reinforcement and maintenance of intestinal homeostasis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".