The alarming coincidence of toxin genes with staphylococcal cassette Chromosome mec (SCCmec) in clinical MRSA isolates
Bibliographic record
Abstract
Staphylococcus aureus is an opportunistic pathogen causing infections with high morbidity and mortality. MRSA isolates which harbor Staphylococcal Cassette Chromosome mec (SCCmec) and express various types of toxins are the most serious strains. Type of SCCmec and common toxin genes (TGs) among MRSA isolates were investigated in the current study. SCCmec and TGs were detected by multiplex-PCR. Possible correlations between SCCmec and TGs were elucidated statistically using IBM-SPSS software. Staphylococcus-enterotoxins (SEs) were sequenced to investigate their genetic relatedness using Sanger-sequencing, and MEGAX software. MRSA were detected in 124 isolates, 67 of MRSA isolates (54 %) were harboring a single SCCmec with 40, 21, 5 and 1 isolate for SCCmec II, SCCmec III, SCCmec IV, and SCCmec V, respectively. Furthermore, Four isolates (3.2 %) had both SCCmec II and SCCmec IV. The highest incidence of TGs was recorded for sea (40.3%) and etb (34.6%) genes. Statistically, moderate correlation between toxins and SCCmec type and between presence of toxin genes and severity of infections were detected. All SEs sequences were correlated, sea and see genes were more conserved. Isolates from serious cases revealed different degrees of nucleotide and amino acid substitution among seb, sec, and tsst genes, which might contribute to their increased virulence. This study improves our understanding of S. aureus toxin profile in relation to SCCmec type, and highlight their possible roles in virulence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".