Atopy affects LPS responsiveness and TLR-4 expression in children peripheral mononuclear cells
Bibliographic record
Abstract
Lipopolysaccharide (LPS) exposure in early life is associated with a lower incidence of atopy. We sought to determine whether atopy regulates TLR-4 expression and LPS-induced signal transduction on peripheral immune cells e.g. CD4 T ‘helper’ T cells, monocytes and B cells of a large pediatric cohort. Over 350 subjects were recruited from the Pediatric Test Center of the Montreal Children’s Hospital and a questionnaire was administered to determine presence of a history of atopic diseases. 3-5cc of anti-coagulated blood was taken and peripheral blood mononuclear cells were cultured for up to 24h with IL-4 (13.5ng/ml) and/or LPS (up to 5µg/ml). We conducted flow cytometric analysis for surface TLR-4 expression, along with T ‘helper’ lymphocyte marker CD4, pan-B lymphocyte marker CD19, monocyte marker CD14, and for intracellular phosphorylated p44/p42 and p38 signaling molecules. Non-atopic monocytes prominently internalize TLR-4 and trigger signal transduction (e.g. phosphorylation of p44/p42 and of p38) upon LPS exposure. Such LPS responsiveness was strikingly impaired in monocytes from atopic children. Compared with monocytes, reduced proportions of CD4+ T ‘helper’ lymphocytes and CD19+ B cells express TLR-4. In T cells, TLR-4 expression varies with age (it peaks between 7-17 years of age) and atopy; atopic children display reduced TLR-4 expression compared with controls. Recombinant IL-4 also interferes with LPS signaling, and was found to differentially modulate TLR-4 expression in T ‘helper’, B lymphocytes and monocytes. Peripheral TLR-4+ CD14+ CD4+ monocytes may be used to discriminate between atopic and non-atopic children based on reduced LPS-induced signaling in atopic subjects. TLR-4 expression greatly varies with age and appears to be affected by both atopic status and IL-4. Our data suggest that atopy and Th2-type immune bias may impair TLR-4-mediated innate immune function during childhood and, therefore influence allergic disease manifestations.
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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 | 0.000 | 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".