Growth and bile tolerance of<i>Lactobacillus brevis</i>strains isolated from Japanese pickles in artificial digestive juices and contribution of cell-bound exopolysaccharide to cell aggregation
Bibliographic record
Abstract
Cell-bound exopolysaccharide (EPS) of the aggregable strain Lactobacillus brevis KB290 isolated from traditional Japanese pickles has been reported to protect against the effects of bile. However, there are no reports of bile tolerance mechanisms for other L. brevis strains that have aggregability. To elucidate the mechanism of bile tolerance of L. brevis KB290, we found 8 aggregable L. brevis strains out of 121 L. brevis strains isolated from traditional Japanese fermented pickles. We estimated their growth in artificial digestive juice and the amount of cell-bound EPS. We found 3 types of aggregation for these strains: filiform (<1 mm), medium floc (1-5 mm), or large floc (>5 mm). There was no significant difference in growth between nonaggregable and aggregable strains in the artificial digestive juice. The large floc strains selected from the aggregation strains showed significantly higher growth in the artificial digestive juice than nonaggregable strains. In medium and large floc strains, cell-bound EPS, mainly consisting of glucose, N-acetylglucosamine, and N-acetylmannosamine, were observed. The amount of EPS and each strain's growth index showed a positive correlation. We conclude that aggregable L. brevis strains were also protected by cell-bound EPS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".