Identification Of Genetic Variants In AGT Gene With Association With Increased Blood Pressure And The Risk Of Hypertension.
Bibliographic record
Abstract
The present research provides extensive research on the variants of the angiotensinogen (AGT) gene, which plays an essential role in the risk factors related to cardiovascular medical conditions and hypertension. The AGT gene is used in our body to regulate blood pressure, and it also provides equilibrium to various fluids in the human body. This research aims to identify the common variants that play an essential role in cardiovascular medical conditions. This research also included identifying the impact the variants and their mutation might have on developing essential hypertension. Kurdi, De Mello, and Booz (2005, pp. 1357-1367) stated that the renin-angiotensin-aldosterone system (RAAS) is responsible for the etiology of hypertension. The findings of this research were the focus on the nine SNPs which founded in AGT gene tow SNPs present in exon number 2 named rs699 and rs4762 and in the untranslated region found five SNPs named rs5046, rs5049, rs11568020, rs5050, and rs5051. Finally, the intron contains two SNPs named rs2148582 and rs3789679. It determined that AGT genes help us better understand the functions and processes of the different variants. Several studies have found a connection between enhanced AGT gene variants causing an increase in hypertension and AGT plasma. The following research touches on various aspects of angiotensinogen AGT, its system, and its impact on various functions in our body.
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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 | 0.001 |
| 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 | 0.001 |
| 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".