Extraction, Antibiofilm Activity and Characterization of Biosurfactant Produced by Limosilactobacillus reuteri IDCC 3701
Bibliographic record
Abstract
Aims: This study aimed to extract and characterize a biosurfactant produced by Limosilactobacillus reuteri IDCC 3701, assess its emulsifying activity against crude oil, and investigate its antibiofilm properties against major foodborne pathogens. Methodology: The biosurfactant, named I-BS, was extracted from the cell-free supernatant of Limosilactobacillus reuteri IDCC 3701 using acid precipitation. The emulsification index, emulsifying activity, oil spreading test, drop collapse test, and microplate distortion assay were performed to evaluate the surfactant properties of I-BS. The antibiofilm activity of I-BS against foodborne pathogens was assessed using the Calgary Biofilm Device. Finally, the cell-free supernatant of Limosilactobacillus reuteri IDCC 3701 was subjected to GC-MS analysis. Results: I-BS demonstrated an emulsification index of 49.4% and emulsifying activity of 400.67, indicating its potential as an effective emulsifier for oils. Positive results were observed in the oil spreading test and microplate distortion assay, confirming its surfactant properties. Additionally, I-BS exhibited significant antibiofilm activity against foodborne pathogens. GC-MS analysis of the I-BS structure revealed the presence of octanoic acid, a surfactant compound. Conclusion: The biosurfactant I-BS, derived from Limosilactobacillus reuteri IDCC 3701, displayed promising emulsifying activity and demonstrated notable antibiofilm properties against foodborne pathogens. These findings suggest that I-BS holds potential as a lead compound for the development of novel anti-biofilm agents and additives in the food industry.
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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 | 0.001 | 0.001 |
| 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".