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Increased PI3-Kinase in Presympathetic Brain Areas of the Spontaneously Hypertensive Rat

2005· article· en· W2146835257 on OpenAlexfundno aff
Shereeni J. Veerasingham, Masanobu Yamazato, Kathleen H. Berecek, J. Michael Wyss, Mohan K. Raizada

Bibliographic record

VenueCirculation Research · 2005
Typearticle
Languageen
FieldMedicine
TopicRenin-Angiotensin System Studies
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsEndocrinologyInternal medicineCaptoprilKinaseSpontaneously hypertensive ratBiologyChemistryMedicineCell biologyBlood pressure

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.060
GPT teacher head0.348
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations49
Published2005
Admission routes1
Has abstractyes

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