Identification of epigenetic factor KAT2B gene variants for possible roles in congenital heart diseases
Bibliographic record
Abstract
Congenital heart disease (CHD) is a group of anatomic malformations in the heart with high morbidity and mortality. The mammalian heart is a complex organ, the formation and development of which are strictly regulated and controlled by gene regulatory networks of many signaling pathways such as TGF-β. KAT2B is an important histone acetyltransferase epigenetic factor in the TGF-β signaling pathway, and alteration in the gene is associated with the etiology of cardiovascular diseases. The aim of this work was to validate whether KAT2B variations might be associated with CHD. We sequenced the KAT2B gene for 400 Chinese Han CHD patients and evaluated SNPs rs3021408 and rs17006625. The statistical analyses and Hardy-Weinberg equilibrium tests of the CHD and control populations were conducted by the software SPSS (version 19.0) and PLINK. The experiment-wide significance threshold matrix of LD correlation for the markers and haplotype diagram of LD structure were calculated using the online software SNPSpD and Haploview software. We analyzed the heterozygous variants within the CDS region of the KAT2B genes and found that rs3021408 and rs17006625 were associated with the risk of CHD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".