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Enregistrement W4405990472 · doi:10.1097/mol.0000000000000969

Editorial introductions

2025· article· en· W4405990472 sur OpenAlexaboutno aff

Notice bibliographique

RevueCurrent Opinion in Lipidology · 2025
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueContemporary Sociological Theory and Practice
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicine

Résumé

récupéré en direct d'OpenAlex

Current Opinion in Lipidology was launched in 1990. It is part of a successful series of review journals whose unique format is designed to provide a systematic and critical assessment of the literature as presented in the many primary journals. The field of lipidology is divided into six sections that are reviewed once a year. Each section is assigned a Section Editor, a leading authority in the area, who identifies the most important topics at that time. Here we are pleased to introduce the Editor and the Section Editors for this issue. EDITOR Robert A HegeleRobert A HegeleRob Hegele is a distinguished University Professor of Medicine and Biochemistry, University of Western Ontario, Canada, and Director of the Lipid Genetics Clinic and the London Regional Genomics Centre in London, Ontario, Canada. He received his MD degree from the University of Toronto in 1981. His specialty training in internal medicine and in endocrinology & metabolism was also in Toronto. His post-doctoral research fellowships were at Rockefeller University, USA, and Howard Hughes Medical Institute, University of Utah, USA. From 1989 to 1997 he was on the Faculty of Medicine at the University of Toronto. In 1997 Dr Hegele joined the Schulich School of Medicine and Dentistry and the Robarts Research Institute at the Western University, in London, Ontario, Canada, where he holds the Jacob J. Wolfe Distinguished Medical Research Chair and the Martha Blackburn Chair in Cardiovascular Research. His lab studies the genetics of lipoprotein metabolism, cardiovascular disease and diabetes mellitus. Solely or through collaborations, his lab was first to describe the molecular genetic basis of 20 human diseases. His lab has also defined much of the genetic basis of complex disorders, including hypertriglyceridemia. He has co-authored more than 600 peer-reviewed publications and has contributed to national treatment guidelines for dyslipidemia, hypertension and diabetes. He is a practicing endocrinologist and has participated in numerous clinical trials. He has trained numerous physicians and graduate students. SECTION EDITORS Majken K. JensenMajken K. JensenMajken K. Jensen, PhD, is Associate Professor of Nutrition and Epidemiology at Harvard T. H. Chan School of Public Health. Dr Jensen's primary research interests include novel metabolic markers, nutrition, and genetics, in relation to chronic lifestyle diseases. In ongoing collaborations with Dr Frank Sacks, they investigate how the presence of a small proinflammatory protein (apolipoprotein C-III) on HDL particles marks a potentially dysfunctional type of HDL that is not inversely associated with risk of cardiometabolic health, such as IMT, diabetes and cardiovascular disease. Other currently funded work is focused on lipoprotein metabolism and Alzheimer's disease and stroke. Her research predominantly utilizes large-scale observational studies (including the Health Professionals Follow-Up Study, the Nurses’ Health Study, the Danish Diet, Cancer and Health study, the Multi-Ethnic Study of Atherosclerosis, and the Cardiovascular Health Study) where cost-efficient prospective case-control studies are nested within for the purpose of measuring novel biomarkers or genome-wide markers. Dr Jensen's research has been published in leading scientific journals and has been recognized with numerous awards. She received the Trudy Bush Fellowship for Cardiovascular Disease Research in Women's Health from the American Heart Association in 2011 and originally came for research studies at Harvard T. H. Chan School of Public Health as a Fulbright scholar. Dr Jensen has published more than 80 original research articles and five reviews, editorials, and letters. Marta Guasch-FerréMarta Guasch-FerréDr. Guasch-Ferré is an Associate Professor and Group Leader at the Department of Public Health and Novo Nordisk Center for Basic Metabolic Research at the University of Copenhagen, Denmark. She also holds an appointment as Adjunct Associate Professor at the Department of Nutrition at Harvard T.H. Chan School of Public Health, USA. Her research focuses on nutritional and lifestyle epidemiology and the prevention of type 2 diabetes (T2D) and cardiovascular disease (CVD). She has incorporated high-throughput –omics techniques, particularly metabolomics, into traditional epidemiological analysis to gain insights into underlying mechanisms that could explain the associations between lifestyle factors in relation to CVD and T2D. She has been involved in the design and implementation of several clinical trials including the well-known PREDIMED trial, a primary cardiovascular prevention trial. She currently works on large prospective cohort studies on the Nurses’ Health Study and the Health Professional's Follow-up Study. Her research activities have resulted in numerous manuscripts (>130, H-index 43), and she has been awarded various competitive European and American grants. Dr. Guasch-Ferré was the recipient of the Sandra A. Daugherty Award for Excellence in Cardiovascular Disease or Hypertension Epidemiology and Prevention by the American Heart Association (2021). She serves as the P.I. of a NIH-funded project entitled ‘Circulating plasma metabolites, lifestyle factors, and mortality risk’. She is also an investigator in two NIH-funded projects to study Mediterranean dietary interventions, plasma metabolites, and the risk of CVD and T2D

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,008
score de la tête « metaresearch » (Gemma)0,064
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,154
Score d'incertitude au seuil0,515

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,064
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0060,002
Études des sciences et des technologies0,0030,002
Communication savante0,0080,005
Science ouverte0,0040,003
Intégrité de la recherche0,0070,008
Charge utile insuffisante (le modèle a refusé de juger)0,1540,096

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,105
Tête enseignante GPT0,455
Écart entre enseignants0,351 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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