The Association Between Onset of Staphylococcal Non-menstrual Toxic Shock Syndrome With Inducibility of Toxic Shock Syndrome Toxin-1 Production
Bibliographic record
Abstract
Non-menstrual toxic shock syndrome (non-mTSS) is a life-threatening disease caused by Staphylococcus aureus strains producing superantigens, such as staphylococcal enterotoxins A, B, C, and toxic shock syndrome toxin-1 (TSST-1). However, little is known about why the TSS cases are rare, although S. aureus strains frequently carry a tst gene, which encodes TSST-1. To answer this question, the amount of TSST-1 produced by 541 clinical isolates was measured in both the presence and absence of serum supplementation to growth media. Then a set of S. aureus strains with similar genetic backgrounds isolated from patients presenting with non-mTSS and those with clinical manifestations other than non-mTSS was compared for their TSST-1 inducibility by human serum, and their whole-genome sequences were determined. Subsequently, the association of mutations identified in the tst promoter of non-mTSS strains with TSST-1 inducibility by human serum was evaluated by constructing promoter replacement mutants and green fluorescent protein (GFP) reporter recombinants. Results showed that 39 out of 541 clinical isolates (7.2%), including strains isolated from non-mTSS patients, had enhanced production of TSST-1 in the presence of serum. TSST-1 inducibility by human serum was more clearly seen in non-mTSS strains of clonal complex (CC)-5. Moreover, the whole-genome sequence analysis identified a set of sequence variations at a putative SarA-binding site of the tst promoter. This sequence variation was proven to be partially responsible for the induction of TSST-1 production by human serum. We conclude that the onset of staphylococcal toxic shock syndrome caused by TSST-1-producing CC-5 strains seem at least partially initiated by serum induction of TSST-1, which is regulated by the mutation of putative SarA-binding site at the tst promoter.
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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 | 0.000 |
| 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) | 0.002 | 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".