Bibliographic record
Abstract
Epigenetics of asthma and allergic disease is a field that has expanded greatly in the last decade. Previously thought only in terms of cell differentiation, it is now evident the epigenetics regulate many processes. With T cell activation, commitment toward an allergic phenotype is tightly regulated by DNA methylation and histone modifications at the Th2 locus control region. When normal epigenetic control is disturbed, either experimentally or by environmental exposures, Th1/Th2 balance can be affected. Epigenetic marks are not only transferred to daughter cells with cell replication but they can also be inherited through generations. In animal models, with constant environmental pressure, epigenetically determined phenotypes are amplified through generations and can last up to 2 generations after the environment is back to normal. In this review on the epigenetic regulation of asthma and allergic diseases we review basic epigenetic mechanisms and discuss the epigenetic control of Th2 cells. We then cover the transgenerational inheritance model of epigenetic traits and discuss how this could relate the amplification of asthma and allergic disease prevalence and severity through the last decades. Finally, we discuss recent epigenetic association studies for allergic phenotypes and related environmental risk factors as well as potential underlying mechanisms for these associations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".