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Record W4223915385 · doi:10.31083/j.rcm2304119

Genetics of Normotension Preventing Hypertension Leads to a Novel Physiological Paradigm

2022· review· en· W4223915385 on OpenAlexafffund
Alan Y. Deng

Bibliographic record

VenueReviews in Cardiovascular Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersHeart and Stroke Foundation of Canada
KeywordsMedicineIntensive care medicineBioinformaticsBiology

Abstract

fetched live from OpenAlex

Possessing blood pressure in normal ranges is considered healthy, and does not warrant medical attention for obvious clinical reasons. However, to realize normotension and then maintain it even when confronted with a hypertensive threat must have its biological 'shield of armour'. While sensitivity to hypertension has been widely recognized and studied, inherent mechanisms that enable a physiological resistance to hypertension to occur have received little attention. Recent advances in normotension genetics have produced unexpected insights. A hypertension 'suppressor' likely inhabits the normotensive genome of inbred Lewis rats. This suppressor behaves as a 'master' control capable of functionally abrogating the effects of hypertension-promoting alleles from multiple quantitative trait loci. This conceptual advancement lays the foundation for uncovering an anti-hypertension gene. Discovering its identity will assist our attempts at developing innovative diagnostic and therapeutic strategies for circumventing and treating hypertension. This new domain of suppressing hypertension goes beyond the conventional pharmacological treatments of hypertension before symptoms appear. For this purpose, a valid theoretical basis and framework is needed that can interpret the experimental data and produce testable predictions for authenticating, enriching or amending the normotension paradigm in the future.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0130.004
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.176
GPT teacher head0.366
Teacher spread0.190 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations1
Published2022
Admission routes2
Has abstractyes

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