Staphylococcal enterotoxin <scp>B</scp> compromises the immune tolerant status in the airway mucosa
Bibliographic record
Abstract
BACKGROUND: The breakdown of immune tolerance plays a critical role in allergic disorders; the mechanism of breaching immune tolerance remains largely unknown. OBJECTIVE: The present study aimed to investigate the role of Staphylococcal enterotoxin B (SEB) in the interference of the immune tolerance in the nasal mucosa. METHODS: The immune tolerant components, tolerogenic dendritic cells (TolDC) and regulatory T cells (Treg), were assessed in the surgically removed nasal mucosa from patients with allergic rhinitis (AR) or non-AR chronic rhinitis. The contents of SEB and integrin alphavbeta6 (avb6) in the nasal epithelium were assessed using enzyme-linked immunoassay. The ability of avb6 on TolDC induction and the effect of SEB on suppression of avb6 in nasal epithelial cells were observed in cell culture. RESULTS: Compared with that in the non-AR nasal mucosa, the frequencies of TolDCs/Tregs were lower, the contents of SEB were higher and the contents of avb6 were lower in the AR nasal mucosa. Avb6 had the ability to induce the development of TolDCs in vitro; the latter had the ability to induce Treg development. The expression of avb6 was detected in nasal epithelial cells in culture that could be suppressed by SEB. CONCLUSIONS AND CLINICAL RELEVANCE: The components of immune tolerance machinery, TolDCs and Tregs were suppressed in the AR nasal mucosa. The increases in SEB and decreases in avb6 in nasal epithelium are associated with the compromises of immune tolerance in the nasal mucosa. SEB has the ability to suppress the expression of avb6 in nasal epithelial cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".