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Record W4383302015 · doi:10.1161/atvbaha.122.318247

Sex-Specific Differences in Lipoprotein Production and Clearance

2023· review· en· W4383302015 on OpenAlexaff
Donna Conlon, Francine K. Welty, Gissette Reyes‐Soffer, Jaume Amengual

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2023
Typereview
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsColumbia College
FundersNational Heart, Lung, and Blood InstituteNational Institute of Food and AgricultureNational Institutes of HealthU.S. Department of Agriculture
KeywordsDiseaseLipoproteinMedicineLipoprotein(a)BioinformaticsBiologyCholesterolInternal medicine

Abstract

fetched live from OpenAlex

Therapeutic approaches to reduce atherogenic lipid and lipoprotein levels remain the most effective and assessable strategies to prevent and treat cardiovascular disease. The discovery of novel research targets linked to pathways associated with cardiovascular disease development has enhanced our ability to decrease disease burden; however, residual cardiovascular disease risks remain. Advancements in genetics and personalized medicine are essential to understand some of the factors driving residual risk. Biological sex is among the most relevant factors affecting plasma lipid and lipoprotein profiles, playing a pivotal role in the development of cardiovascular disease. This minireview summarizes the most recent preclinical and clinical studies covering the effect of sex on plasma lipid and lipoprotein levels. We highlight the recent advances in the mechanisms regulating hepatic lipoprotein production and clearance as potential drivers of disease presentation. We focus on using sex as a biological variable in studying circulating lipid and lipoprotein levels.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.256
GPT teacher head0.386
Teacher spread0.130 · 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 designNot applicable
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

Citations34
Published2023
Admission routes1
Has abstractyes

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