Modulatory Role of Vitamin D in Stem Cell Factor‐Mediated Mast Cell TNF Expression
Bibliographic record
Abstract
Prevalence of allergic pathologies, such as atopic dermatitis (eczema), have been on the rise over the past few decades in developed nations, with approximately 10–30% of children suffering from atopic dermatitis alone. These pathologies are driven largely by mast cells, a sentinel immune cell enriched in tissues that interface with the external environment, including skin. Stem cell factor (SCF), an endogenous growth factor for hematopoietic stem cells, and required for mature mast cell survival in the periphery, is capable of activating mast cells through the c‐kit (CD117) receptor, either alone, or by playing a synergistic role in the IgE‐FcɛRI allergic inflammatory pathway. Vitamin D, a secosteroid synthesized in the skin and processed in organs including the liver, is largely responsible for increasing mineral absorption in the body, but has also been shown to impact mast cell activation through the IgE‐FcɛRI pathway. Mast cells have been found to express vitamin D receptor (VDR), and their ability to directly participate in the metabolism and activation of vitamin D to the active metabolite calcitriol has been characterized. The purpose of this study was to assess the role that vitamin D plays in SCF‐mediated mast cell activation. Primary mast cell cultures were established using bone marrow isolated from the tibias and femurs of female C57BL/6 mice and by differentiating progenitor cells into mature bone marrow‐derived mast cells (BMMC) under the direction of IL‐3 and PGE 2 . To condition mast cells, BMMCs were pre‐treated with 1 μM calcitriol for 48 hours prior to activation with 100 ng/mL of SCF across a 5‐hour time course accounting for the early (minutes) and late (hours) phase of the allergic response. SCF‐induced mast cell activation was assessed through gene expression by qPCR (n=3) for a variety of cytokines and transcription factors involved in the allergic inflammatory response. A decrease in gene expression level was seen in TNF , but not IL6 nor IL13 . This prompted the investigation of a transcriptional mechanism behind the reduction in TNF expression. Expression of various transcription factors was impacted with significant decreases at various time points for Egr1 (p<0.05), Egr2 (p<0.01), and NFκB subunit 2 (p<0.01). Gene expression for components of the heterodimeric vitamin D receptor retinoid X receptor complex remained unchanged across the activation time course. SCF‐induced mast cell degranulation, measured by β‐hexosaminidase release (n=4), a hallmark event of the early phase of an allergic reaction, was not impacted by the 48‐hour vitamin D pretreatment. These results suggest that vitamin D may modulate the late phase of mast cell activation through TNF production via reductions in induced Egr1, Egr2, and NF‐κB2 transcription factors. Further work will elucidate the interaction between these transcription factors and the vitamin D retinoid X receptor complex at the promotor region for TNF . Collectively, this work supports an anti‐inflammatory role for vitamin D in the activation of mast cells with relevance in allergy and host defence. Support or Funding Information Supported by the Natural Sciences and Engineering Research Council of Canada (NSERC); Canada Foundation for Innovation (CFI); Government of Ontario; and, Brock University. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.001 | 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 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".