Variable Immunogenic Potential of Wheat: Prospective for Selection of Innocuous Varieties for Celiac Disease Patients via in vitro Approach
Bibliographic record
Abstract
Celiac Disease is a multifactorial, autoimmune enteropathy activated by cereal proteins in genetically predisposed individuals carrying HLA DQ2/8 genes. A heterogenous gene combination of the cereal prolamins is documented in different wheat genotypes, which is suggestive of their variable immunogenic potential. In the current study, four wheat varieties (C591, C273, 9D and K78) identified via in silico analysis were analyzed for immunogenicity by measuring T-cell proliferation rate and levels of inflammatory cytokines (Interferon-γ and Tumor Necrosis Factor-α). Peripheral Blood Mononuclear Cells and biopsy derived T-cell lines isolated from four celiac disease patients in complete remission and two controls were stimulated and cultured in the presence of tissue transglutaminase activated pepsin-trypsin digest of total gliadin extract from test varieties. The immunogenicity was compared with PBW 621, one of the widely cultivated wheat varieties. Phytohaemagglutinin-p was taken as positive control, along with unstimulated cells as negative control. Rate of cell proliferation (0.318, 0.482; 0.369, 0.337), concentration of IFN- γ (107.4, 99.2; 117.9, 99.7pg/ml) and TNF- α (453.8, 514.2; 463.8, 514.2pg/ml) was minimum in cultures supplemented with wheat antigen from C273, when compared with other test varieties and unstimulated cells. Significant difference in toxicity levels among different wheat genotypes to stimulate celiac mucosal T-cells and PBMC’s was observed; where C273 manifested least immunogenic response amongst the test varieties analyzed.
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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".