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Record W3209643218 · doi:10.21203/rs.3.rs-956885/v1

IL-17A Contributes to the Angiotensin II-induced Neurovascular Coupling impairment through Oxidative Stress

2021· preprint· en· W3209643218 on OpenAlexaff
Jessica Youwakim, Diane Vallerand, Hélène Girouard

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsOxidative stressCerebral blood flowAngiotensin IIMedicineSuperoxideEndocrinologyContext (archaeology)Internal medicineMediatorStroke (engine)Nitric oxideReceptorChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Hypertension, a multifactorial chronic inflammatory condition, is a risk factor for neurodegenerative diseases including stroke and Alzheimer’s disease. These diseases have been associated with higher concentration of blood interleukin (IL)-17A. However, the role that IL-17A plays in the relationship between hypertension and brain remains misunderstood. Cerebral blood flow regulation may be the crossroads of these conditions. Hypertension alters cerebral blood flow regulation including neurovascular coupling (NVC). In the present study, the effects of IL-17A on NVC in the context of hypertension induced by angiotensin (Ang) II will be examined. Our results show that the neutralization of IL-17A or the specific inhibition of its receptor prevent the Ang II- induced NVC impairment. These treatments reduce the Ang II-induced cerebral oxidative stress. Tempol and NOX-2 depletion prevent NVC impairment induced by IL-17A. These findings suggest that IL-17A, through superoxide anion production, is an important mediator of cerebrovascular dysregulation induced by Ang II.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.106
GPT teacher head0.375
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

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