Bibliographic record
Abstract
Atopic dermatitis (AD) is a chronic inflammatory disease caused by the complex interaction of genetic, immune and environmental factors. There have many recent discoveries involving the genetic and epigenetic studies of AD. A retrospective PubMed search was carried out from June 2009 to June 2016 using the terms “atopic dermatitis”, “association”, “eczema”, “gene”, “polymorphism”, “mutation”, “variant”, “genome wide association study”, “microarray” “gene profiling”, “RNA sequencing”, “epigenetics” and “microRNA”. A total of 132 publications in English were identified. To elucidate the genetic factors for AD pathogenesis, candidate gene association studies, genome-wide association studies (GWAS) and transcriptomic profiling assays have been performed in this period. Epigenetic mechanisms for AD development, including genomic DNA modification and microRNA posttranscriptional regulation, have been explored. To date, candidate gene association studies indicate that filaggrin ( FLG ) null gene mutations are the most significant known risk factor for AD, and genes in the type 2 T helper lymphocyte (Th2) signaling pathways are the second replicated genetic risk factor for AD. GWAS studies identified 34 risk loci for AD, these loci also suggest that genes in immune responses and epidermal skin barrier functions are associated with AD. Additionally, gene profiling assays demonstrated AD is associated with decreased gene expression of epidermal differentiation complex genes and elevated Th2 and Th17 genes. Hypomethylation of TSLP and FCER1G in AD were reported; and miR-155, which target the immune suppressor CTLA - 4 , was found to be significantly over-expressed in infiltrating T cells in AD skin lesions. The results suggest that two major biologic pathways are responsible for AD etiology: skin epithelial function and innate/adaptive immune responses. The dysfunctional epidermal barrier and immune responses reciprocally affect each other, and thereby drive development of AD.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".