DNA‐nuclear protein interactions around‐224 A/G Single Nucleotide Polymorphism in the Neuropeptide Receptor Y2 ( <i>NPY2R</i> ) Gene in Predisposition to Hypertension
Bibliographic record
Abstract
Hypertension (HTN), is an important risk factor for cardiovascular and kidney diseases. Multiple genes as well as environmental and lifestyle factors influence the risk of developing high blood pressure. Previous work in animal models and human populations identified Neuropeptide Y receptor 2 ( NPY2R ) as a candidate gene for HTN. In two independent Japanese populations, the GG genotype single nucleotide polymorphism (SNP) located 224 bp upstream of the transcription start site was associated with an increased risk of HTN. The aim of this study was to assess the DNA‐nuclear protein interactions surrounding the NPY2R ‐224 A/G SNP. Two versions of double stranded oligonucleotide probes (50bp) corresponding to the sequence flanking NPY2R ‐224A/G were synthesized and incubated with different amounts nuclear extracts for an electrophoretic shift assay (EMSA). In addition, we used CTCF antibody for a gel supershift assay. The DNA/protein reactions were loaded on a 4% non‐denaturing polyacrylamide gel. Interestingly, the EMSA showed an allele‐specific binding with the oligonucleotide containing an A nucleotide in ‐224 position. However, the oligonucleotide containing the G nucleotide in ‐224 position shows no DNA/nuclear protein interaction. Also, we were able to detect a supershift using the CTCF antibody. The data provides strong evidence for a functional role of NPY2R in genetic predisposition to HTN.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".