Knockdown of Inhibitory Guanine Nucleotide Binding Protein Giα‐2 by Antisense Oligodeoxynucleotides Attenuates the Development of Hypertension and Tachycardia in Spontaneously Hypertensive Rats
Bibliographic record
Abstract
BACKGROUND: We previously showed that the levels of both Giα-2 and Giα-3 proteins were augmented in spontaneously hypertensive rats (SHRs) before the onset of hypertension. In addition, intraperitoneal injection of pertussis toxin, which inactivates both Giα proteins, prevented the development of hypertension in SHRs. The aim of the present study was to determine the specific contributions of Giα-2 and Giα-3 proteins to the development of hypertension. METHODS AND RESULTS: Antisense oligodeoxynucleotide of Giα-2 and Giα-3 encapsulated in PEG/DOTAP/DOPE cationic liposomes were administrated intravenously into 3-week-old prehypertensive SHRs and Wistar Kyoto rats, whereas the control Wistar Kyoto rats and SHRs received PBS, empty liposomes, or sense. The knockdown of Giα-2 but not Giα-3 protein attenuated tachycardia and prevented the development of hypertension up to age 6 weeks; thereafter, blood pressure started increasing and reached the same level as that of untreated SHRs at 9 weeks. Furthermore, Giα-2 and Giα-3 antisense oligodeoxynucleotide treatments significantly decreased the enhanced levels of Giα-2 and Giα-3 proteins, respectively, and enhanced levels of superoxide anion and NADPH oxidase activity in heart, aorta, and kidney and hyperproliferation of vascular smooth muscle cells from SHRs aged 6 weeks. In addition, antisense oligodeoxynucleotide treatment with Giα-2 but not Giα-3 restored enhanced inhibition of adenylyl cyclase by oxotremorine to WKY levels. CONCLUSIONS: These results suggested that the enhanced expression of Giα-2 but not Giα-3 protein plays an important role in the pathogenesis of hypertension and tachycardia in SHRs.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".