MétaCan
Menu
Back to cohort
Record W1991751528 · doi:10.1097/hjh.0000000000000479

Genetic mechanisms of polygenic hypertension

2015· review· en· W1991751528 on OpenAlexafffund
Alan Y. Deng

Bibliographic record

VenueJournal of Hypertension · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health Research
KeywordsEpistasisGenetic architectureQuantitative trait locusMendelian inheritanceTraitMechanism (biology)GeneticsComputational biologyMedicineEvolutionary biologyGeneBiologyComputer science

Abstract

fetched live from OpenAlex

Essential hypertension is one of the most common disorders that underpin significant morbidity and mortality; however, underlying mechanisms remain elusive that either dictate the actions of individual quantitative trait loci (QTLs) or engineer the overall genetic architecture from them. Recent experimental evidence has unveiled that the genetic architecture determining blood pressure (BP) is assembled from QTL-building blocks by epistasis into regulatory hierarchies. BP, a polygenic and quantitative trait, is homeostasized via pathways participated by Mendelian constituents that operate distantly from end-phase physiological genes. Epistasis genetics performed in the current article has mechanistically unravelled the order and regulatory relationships between certain BP QTLs, and is the first study ever conducted in a mammalian system in analysing a complex trait. The elucidation of the sequence of event and regulatory hierarchies of QTL actions in these pathways will facilitate mechanism-based diagnoses and cause-driven treatments for essential 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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.071
GPT teacher head0.305
Teacher spread0.234 · 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 designSystematic review
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

Citations21
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal of HypertensionSame topicGenetic Associations and EpidemiologyFrench-language works237,207