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Record W4234361094 · doi:10.1055/s-0031-1276451

Oxyradicals as a mechanism of angiotensin-induced hypertension

2004· article· en· W4234361094 on OpenAlexaff
Kailash Prasad

Bibliographic record

VenueInternational Journal of Angiology · 2004
Typearticle
Languageen
FieldMedicine
TopicNitric Oxide and Endothelin Effects
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPeroxynitriteProstacyclinReactive oxygen speciesNADPH oxidaseOxidative stressSuperoxideVasodilationAngiotensin IINitric oxideIsoprostanesNOX4VasoconstrictionPharmacologyEndothelial dysfunctionChemistryInternal medicineNOX1EndocrinologyMedicineBiochemistryLipid peroxidationEnzymeReceptor

Abstract

fetched live from OpenAlex

Angiotensin II (ANG II) generates reactive oxygen species (ROS) via an NADPH-oxidase in vascular system and leukocytes. ROS increase the formation of isoprostanes, which in turn increase the synthesis and release of endothelin (ET). ROS, isoprostane and ET are vasoconstrictors. ROS degrade nitric oxide (NO) a vasodilator. Superoxide, a member of the ROS family reacts with NO to generate peroxynitrite a potent oxidant. Peroxynitrite stimulates PGH 2 synthase and hence increases the production of thromboxane A 2 , a vasoconstrictor. Peroxynitrite also inhibits prostacyclin synthase that would result in decreased synthesis of prostacyclin a vasodilator. ROS and peroxynitrite would produce endothelial cell dysfunction resulting in a decrease in production of vasodilators and hence unopposed action of circulating vasoconstrictors. Ang II-induced hypertension is attenuated by antioxidants and this effect is associated with a reduction in oxidative stress. The evidence to date suggests that Ang II releases ROS by stimulating NADPH-oxidase in the vascular system and leukocytes. ROS directly or through synthesis and release of isoprostanes and ET, in activation of NO and generation of peroxyinitrite produces vasoconstriction and hence induce hypertension.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.299
Teacher spread0.277 · 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 designBench or experimental
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

Citations3
Published2004
Admission routes1
Has abstractyes

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