Characterization of Nodal/TGF-Lefty Signaling Pathway Gene Variants for Possible Roles in Congenital Heart Diseases
Bibliographic record
Abstract
BACKGROUND: Nodal/TGF-Lefty signaling pathway has important effects at early stages of differentiation of human embryonic stem cells in directing them to differentiate into different embryonic lineages. LEFTY, one of transforming growth factors in the Nodal/TGF-Lefty signaling pathway, plays an important role in the development of heart. The aim of this work was to find evidence on whether Lefty variations are associated with congenital heart diseases (CHD). METHODS: We sequenced the Lefty gene for 230 Chinese Han CHD patients and evaluated SNPs rs2295418, rs360057 and g.G169A, which are located within the translated regions of the genes. The statistical analyses were conducted using Chi-Square Tests as implemented in SPSS (version 13.0). The Hardy-Weinberg equilibrium test of the population was carried out using online software OEGE, and multiple-sequence alignments of LEFTY proteins were carried out using the Vector NTI software. RESULTS: Two heterozygous variants in Lefty1 gene, g.G169A and g.A1035C, and one heterozygous variant in Lefty2 gene, g.C925A, were identified. Statistical analyses showed that the rs2295418 (g.C925A) variant in Lefty2 gene was obviously associated with the risk of CHD (P value = 0.016<0.05). The genotype frequency of rs360057 (g.A1035C) variant in Lefty1 gene was associated with the risk of CHD (P value = 0.007<0.05), but the allele frequency was not (P value = 0.317>0.05). CONCLUSIONS: The SNP rs2295418 in the Lefty2 gene is associated with CHD in Chinese Han populations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".