Mast Cells In Host Defense Against Cutaneous Staphylococcus aureus
Bibliographic record
Abstract
Staphylococcus aureus is an opportunistic pathogen implicated in skin and soft-tissue infections and chronic inflammatory skin diseases, such as atopic dermatitis. These infections can range from mild to potentially life-threatening systemic illnesses progressing to bacteremia, endocarditis, and sepsis. Mast cells, traditionally recognized for their role in allergies, are highly abundant within the skin and are gaining recognition for their contribution to bacterial defense. Here, we discuss the role of mast cells in three models of S. aureus skin infection according to skin depth: epicutaneous sensitization, intradermal injections, and subcutaneous injections. During S. aureus skin infection, mast cells become activated and accumulate in infected skin, recognize bacterial toxins, and modulate the activity of other immune cells, including neutrophils and dendritic cells. We discuss areas of research that should be the target of future studies, such as neuroimmunology, infected excisional wounds, quorum sensing, and risk of systemic illness. Our review aims to bring attention to the host-pathogen interaction between mast cells and S. aureus in the skin, both to encourage deeper investigation and inform the development of immunomodulatory based therapeutics.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".