RGS2 gene product from candidate hypertension allele shows decreased plasma membrane association and inhibition of Gq
Bibliographic record
Abstract
Hypertension is a leading cause of mortality and morbidity in North America. Recent work has identified the Regulator of G‐protein Signaling 2(RGS2) as a candidate gene in the development of hypertension. Specifically, a single nucleotide polymorphism resulting in a missense mutation (R44H) has been correlated with hypertensive patients in a subset of the Japanese population. In our work, we identify the functional characteristics of the R44H mutation and the mechanisms by which they occur. Single cell calcium imaging shows that the mutant protein is less able to inhibit Gq signaling. Previously, we have shown that plasma membrane (PM) localization via RGS‐lipid interactions dependent on the amphipathic alpha helix is important for efficient Gq inhibition. Confocal microscopy of the R44H mutant shows greatly reduced tonic association with the PM. Finally, tryptophan spectroscopy of the helix domain shows an inability to associate with liposomes. In conclusion, we have shown that RGS2 R44H is a poor inhibitor of the M1‐muscarinic receptor and that this reduced function is a result of deficient RGS2‐lipid interactions leading to the inability to associate with the PM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".