Beckwith-Wiedemann syndrome demonstrates a role for epigenetic control of normal development
Bibliographic record
Abstract
The Beckwith-Wiedemann syndrome (BWS) is characterized by somatic overgrowth and a predisposition to pediatric embryonal tumors. It is associated with genetic or epigenetic abnormalities in a cluster of imprinted genes found within a genomic region of approximately one megabase on human chromosome 11p15. Imprinted genes are expressed preferentially or exclusively from either the paternal or maternal allele. The 11p15 region is organized into two imprinted domains in which genomic imprinting is controlled by separate 'imprinting control regions'. Twenty-five to 50% of BWS patients have biallelic rather than monoallelic expression of the insulin-like growth factor 2 (IGF2) gene. Another 50% of patients have an epigenetic mutation resulting in loss of imprinting of a transcript called KCNQ1OT1. Each of these genes resides in one of the two imprinted domains that appear to be subject to developmental dysregulation in BWS. In this review, we discuss the insights that the study of BWS have contributed to our understanding of the mechanisms of growth control, oncogenesis and genomic imprinting. Specifically, methylation and chromatin modification may coordinate the expression of closely linked imprinted genes. Finally, we discuss how knowledge of epigenetic mechanisms associated with the early stages of embryogenesis suggest caution in the current debate surrounding assisted reproductive and cloning technologies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".