Assessment of biofilm-forming ability of coagulase-negative staphylococci isolated from contaminated platelet preparations in Canada
Bibliographic record
Abstract
BACKGROUND: Coagulase-negative staphylococci (CoNS) are the most prevalent bacterial contaminants of platelet (PLT) preparations and have been implicated in adverse transfusion reactions worldwide. The most frequently identified contaminant is Staphylococcus epidermidis, which is noted for its ability to maintain chronic hospital-acquired infections by forming biofilms as a chief virulence mechanism. STUDY DESIGN AND METHODS: Strains of S. epidermidis isolated from contaminated PLT preparations in Canada were distinguished via gene-specific polymerase chain reaction (PCR) with divIVA as a marker. Biofilm-forming ability was assessed by the presence of the gene icaD, slime production on Congo red agar, and biofilm formation on polystyrene surfaces. Production of polysaccharide intercellular adhesin (PIA) was resolved by immunofluorescence. RESULTS: Eight of the 13 (62%) CoNS isolates under study were identified as S. epidermidis. Of these, four strains (50%) were classified as strong biofilm producers. Three of the four biofilm-positive strains (75%) produced slime, harbored the icaD gene, and had positive expression of PIA. CONCLUSIONS: Despite the presumable commensal origin of the CoNS isolates, a large proportion of S. epidermidis strains demonstrated a potential for enhanced virulence. Identification of contaminant staphylococci as biofilm producers is thus relevant and informative with regard to treatment approach in the circumstance of inadvertent infection of a PLT recipient.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".