The Effect of <i>Lactobacillus plantarum</i> BW2013 on The Gut Microbiota in Mice Analyzed by 16S rRNA Amplicon Sequencing
Bibliographic record
Abstract
Abstract Lactobacillus plantarum BW2013 was isolated from the fermented Chinese cabbage. This study aimed to test the effect of this strain on the gut microbiota in BALB/c mice by 16S rRNA amplicon sequencing. The mice were randomly allocated to the control group and three treatment groups of L. plantarum BW2013 (a low-dose group of 10 8 CFU/ml, a medium-dose group of 10 9 CFU/ml, and a high-dose group of 10 10 CFU/ml). The weight of mice was recorded once a week, and the fecal samples were collected for 16S rRNA amplicon sequencing after 28 days of continuous treatment. Compared with the control group, the body weight gain in the treatment groups was not significant. The 16S rRNA amplicon sequencing analysis showed that both the Chao1 and ACE indexes increased slightly in the medium-dose group compared to the control group, but the difference was not significant. Based on PCoA results, there was no significant difference in β diversity between the treatment groups. Compared to the control group, the abundance of Bacteroidetes increased in the low-dose group. The abundance of Firmicutes increased in the medium-dose group. At the genus level, the abundance of Alloprevotella increased in the low-dose group compared to the control group. The increased abundance of Ruminococcaceae and decreased abundance of Candidatus_Saccharimonas was observed in the medium-dose group. Additionally, the abundance of Bacteroides increased, and Alistipes and Candidatus_Saccharimonas decreased in the high-dose group. These results indicated that L. plantarum BW2013 could ameliorate gut microbiota composition, but its effects vary with the dose.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".