Increased PI3-Kinase in Presympathetic Brain Areas of the Spontaneously Hypertensive Rat
Bibliographic record
Abstract
Existing evidence led us to hypothesize that increases in p85alpha, a regulatory subunit of PI3-kinase, in presympathetic brain areas contribute to hypertension. PI3-kinase p85alpha, p110alpha, and p110delta mRNA was 1.5- to 2-fold higher in the paraventricular nucleus (PVN) of spontaneously hypertensive rats (SHR) compared with their controls, Wistar Kyoto rats (WKY). The increase in p85alpha/p110delta was attenuated in SHR treated with captopril, an angiotensin (Ang)-converting enzyme inhibitor, from in utero to 6 months of age. In the rostral ventrolateral medulla (RVLM), p110delta mRNA was approximately 2-fold higher in SHR than in WKY. Moreover, the increases in mRNA were associated with higher PI3-kinase activity in both nuclei. The functional relevance was studied in neuronal cultures because SHR neurons reflect the augmented p85alpha mRNA and PI3-kinase activity. Expression of a p85 dominant-negative mutant decreased norepinephrine (NE) transporter mRNA and [3H]NE uptake by approximately 60% selectively in SHR neurons. In summary, increased p85alpha/p110delta expression in the PVN and RVLM is associated with increased PI3-kinase activity in the SHR. Furthermore, normalized PI3-kinase p85alpha/p110delta expression within the PVN might contribute to the overall effect of captopril, perhaps attributable to a consequent decrease in NE availability.
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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) | 0.001 | 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".