Biofilm formation of <i>Staphylococcus aureus</i> from milk and expression of the adhesion genes <i>ebpS</i> and <i>cna</i> at different temperatures
Bibliographic record
Abstract
This study investigated the ability of Staphylococcus aureus isolates from milk to form biofilm, through detection of adhesion genes, investigating exopolysaccharide (EPS) production and biofilm formation on polystyrene (PS) and stainless steel (SS) surfaces, and by quantifying the expression of ebpS and cna genes under different temperatures and culture media. Among the 31 isolates, the adhesion genes ebpS and cna were found in 81% and 61% of the isolates, respectively. The screening tests for phenotype revealed that 58% of the isolates were EPS producers, and 45% showed the ability to produce biofilm on PS. Nine of the 31 isolates were selected to verify their ability to form biofilm on SS, of which 3 were non-biofilm producers, 3 were poor biofilm producers, and 3 were moderate biofilm producers. However, all nine isolates produced biofilm on SS, regardless of their phenotypic profile on PS. Reverse-transcriptase quantitative PCR (RT–qPCR) revealed no variation in the expression levels of ebpS and cna genes at different temperatures, except for isolate S24 at 10 °C, for both genes tested. Moreover, RT–qPCR assays revealed that the expression levels of the adhesion genes ebpS and cna are isolate- and temperature-dependent; however, they are independent of the phenotypic biofilm-formation profile.
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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".