Manipulation of Innate and Adaptive Immunity by Staphylococcal Superantigens
Bibliographic record
Abstract
Staphylococcal superantigens (SAgs) constitute a family of potent exotoxins secreted by Staphylococcus aureus and other select staphylococcal species. SAgs function to cross-link major histocompatibility complex (MHC) class II molecules with T cell receptors (TCRs) to stimulate the uncontrolled activation of T lymphocytes, potentially leading to severe human illnesses such as toxic shock syndrome. The ubiquity of SAgs in clinical S. aureus isolates suggests that they likely make an important contribution to the evolutionary fitness of S. aureus. Although the apparent redundancy of SAgs in S. aureus has not been explained, the high level of sequence diversity within this toxin family may allow for SAgs to recognize an assorted range of TCR and MHC class II molecules, as well as aid in the avoidance of humoral immunity. Herein, we outline the major diseases associated with the staphylococcal SAgs and how a dysregulated immune system may contribute to pathology. We then highlight recent research that considers the importance of SAgs in the pathogenesis of S. aureus infections, demonstrating that SAgs are more than simply an immunological diversion. We suggest that SAgs can act as targeted modulators that drive the immune response away from an effective response, and thus aid in S. aureus persistence.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".