Isolation and characterization of lactobacilli from human faeces and indigenous fermented foods for their potential application as probiotics
Bibliographic record
Abstract
This study was conducted to select Lactobacillus strains from various sources on the basis of their probiotic attributes, such as acid and bile tolerance, binding to intestinal cells, and antimicrobial activity. Twelve isolates were obtained from human and food sources and were evaluated against standard probiotic Lactobacillus rhamnosus GG (LGG). Isolates were also studied for their antibiotic susceptibility. Isolate Lactobacillus fermentum GPI-6 showed the best survival profile at 0.3% and 1% bile salt, as compared with LGG. Isolates Lactobacillus plantarum GRI-2 and Lactobacillus salivarius GPI-4 showed no reduction in survival rate at pH 2.5. As expected, isolates showed strain-specific differences when comparing various attributes. Isolates GPI-4, GPI-7, and FA-5 showed better adhesion to HT-29, while isolate GPI-4 adhered better to Caco-2 cells than did LGG. However, when studying their ability to compete with Escherichia coli O26:H11, isolates GPI-6 and GPI-7 significantly inhibited E. coli adhesion to both HT-29 and Caco-2 cells compared with LGG. In conclusion, isolates GPI-4, GPI-7, and FA-5 showed excellent binding ability and antagonistic activity and better tolerance to acidic pH (pH 2.5) and to different bile salt concentrations in comparison with LGG, and hence, they could be considered as potential probiotic candidates.
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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) | 0.000 | 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) | 0.000 | 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".