The anti-biofilms effects of Thymus algeriensis on isolated strains of Bacillus cereus
Bibliographic record
Abstract
The ability of some microorganisms to form biofilms has been increasing in recent years. Indeed, biofilms are defined as a way of life that allows bacteria to survive and resist in hostile environments. Therefore, this form of survival represents a major problem for different food industries, including the dairy industry. The objective of this study is the isolation of Bacillus cereus strains from raw cow's milk and the study of their characterization, their ability to form biofilms, as well as the search for an inhibitory effect of the essential oil of 'Thymus algeriensis' on these formed biofilms. For this purpose, samples of cow's milk are collected from the region of Abu El Hassan (Chlef) and submitted to microbiological analyses. The preliminary identification of the isolated bacteria allowed the selection of 06 strains of Bacillus cereus. These strains in question have shown great potential for the formation of biofilm in the wells of a micro plate. The formation of biofilm in the micro plate was analyzed first by a simple observation with the naked eye of the wells after coloration with purple crystal, then using an ELISA device where the absorbance of the populations at 620 nm could be measured. Regarding the in vivo effect of the Thymus algeriensis essential oil, a complete inhibition of the biofilm formed was obtained after 24 hours of contact.
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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) | 0.000 | 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) | 0.001 | 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".