Go protein subunit Goα and the secretory process of the natriuretic peptide hormones ANF and BNP
Bibliographic record
Abstract
Expression of the G protein subunit Goα has been shown to be prominent in the atria of the rat heart and to be significantly associated with atrial natriuretic factor (ANF)-containing atrial-specific secretory granules by immunocytochemistry. In addition, differential expression profile analysis using oligonucleotide arrays has shown that the Goα isoform 1 (Goα1) is 2.3-fold more abundant in the atria than it is in the ventricles. In the present report, we show protein-protein interaction between Goα and ANF by yeast two-hybrid and by immunoprecipitation. A cardiac conditional Goα knockout model developed for the present study showed a 90% decrease in Goα expression and decreased atrial expression and ANF and brain natriuretic peptides (BNP) content. Expression of chromogranin A, a specific atrial granule core constituent, was not affected. Morphometric assessment of atrial tissue showed a very significant decrease in atrial-specific granule density as well as granule core electron density. Atrial electrical activity was not affected. The results obtained are compatible with the suggestion that Goα plays a role in ANF sorting during intracellular vectorial transport and with the presence of a mechanism that preserves the molar relationship between cellular ANF and BNP stores in the face of the decreased production of these hormones.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".