Expression Of Epithelial Na+ Channel (ENaC) And Serum/glucocorticoid Regulated Kinase 1 (SGK1) In Brain Nuclei of Rats Post‐MI
Bibliographic record
Abstract
Blockade of brain mineralocorticoid receptors (MR) or ENaC prevents sympathetic hyperactivity and improves cardiac function in rats post MI. To assess whether this response reflects increases in ENaC activity, we studied mRNA expression of ENaC (α, β, γ) subunits and SGK1, an important regulator of ENaC, in brain nuclei of male Wistar rats at 2 & 4 weeks (wks) post MI. Micro‐punches were taken from the subfornical organ (SFO), paraventricular nucleus (PVN) and supraoptic nucleus (SON). Expression of mRNA was measured by real‐time qRT‐PCR, normalized by house keeping gene phosphoglycerate kinase 1 (PGK1). In SFO, α and β subunit mRNA levels significantly increased at 4 (1.7±0.2 vs 1.2±0.1 α/PGK1 [×10 −3 ]; 1.0±0.1 vs 0.6±0.1 β/PGK1 [×10 −4 ]) but not 2 wks compared to sham. In PVN, α subunit mRNA levels decreased at 2 (2.9±0.5 vs 4.5±0.6 [×10 −3 ], p<0.05) but not 4 wks post MI. In contrast, mRNA levels of γ subunit significantly increased at 4 (1.2±0.2 vs 0.6±0.2 [×10 −4 ]) but not 2 wks. No changes of ENaC subunit mRNA was found in SON. mRNA levels of SGK1 were similar in SFO, PVN and SON between MI and sham at 2 & 4 wks. These results indicate that in rats post MI, ENaC subunit mRNA expression is differentially regulated in brain nuclei. SGK1 transcription regulation appears not to be involved. Upregulation of ENaC subunit transcription in SFO and PVN may increase ENaC activity and thereby contribute to sympathetic hyperactivity.
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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 | 0.001 | 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) | 0.002 | 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".