Evidence mapPaperPMID 41134486Full record

ReviewJournal of physiology and biochemistry2025

Preclinical research in obesity-associated metabolic diseases using in vitro, multicellular, and non-mammalian models.

Paula Aranaz, Marina Clavel-Millan, Katherine Gil-Cardoso, Maitane González-Arceo, David Hernández-González, Francisco Les, Jérôme Salles, Ez-Zoubir Amri, José M Arbones-Mainar, Claude Atgié and 9 more

Abstract readReview
In one paragraph

Review in Journal of physiology and biochemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Paula AranazDepartment of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, Pamplona, 31008, Spain.
Marina Clavel-MillanAdipocyte and Fat Biology Laboratory (AdipoFat), Hospital Universitario Miguel Servet, Zaragoza, 50009, Spain.
Katherine Gil-CardosoEurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, 43204, Spain.
Maitane González-ArceoNutrition and Obesity Group, Department of Nutrition and Food Science, University of the Basque Country (UPV/EHU) and Lucio Lascaray Research Institute, Vitoria, 01006, Spain.
David Hernández-GonzálezNeuroendocrinology and Obesity Team, Faculty of Medicine, INCyL and IBSAL, University of Salamanca, Salamanca, Spain.
Francisco LesDepartment of Pharmacy, Faculty of Health Sciences, Universidad San Jorge, Zaragoza, 50830, Spain.
Jérôme SallesUnité de Nutrition Humaine (UNH), UMR1019, Université Clermont Auvergne, INRAE, CRNH Auvergne, Clermont-Ferrand, France.
Ez-Zoubir AmriCNRS, Inserm, Adipocible Research Study Group, Institute Biology Valrose (iBV), Université Côte d'Azur, Nice, France.
José M Arbones-MainarAdipocyte and Fat Biology Laboratory (AdipoFat), Hospital Universitario Miguel Servet, Zaragoza, 50009, Spain.
Claude AtgiéUniversité de Bordeaux, Bordeaux INP, CNRS, Institut CBMN, UMR 5248, Equipe Val'Actif (Valorisation d'Actifs), Pessac, 33600, France.
Frédéric CapelUnité de Nutrition Humaine (UNH), UMR1019, Université Clermont Auvergne, INRAE, CRNH Auvergne, Clermont-Ferrand, France.
Arnaud CourtoisUMR OEnologie (UMR 1366, INRAE, Bordeaux INP), Institut des Sciences de la Vigne et du Vin, Université de Bordeaux, Villenave d'Ornon, 33882, France.
Xavier EscotéEurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, 43204, Spain.
María José García-BarradoNeuroendocrinology and Obesity Team, Faculty of Medicine, INCyL and IBSAL, University of Salamanca, Salamanca, Spain.
Stéphanie KrisaUMR OEnologie (UMR 1366, INRAE, Bordeaux INP), Institut des Sciences de la Vigne et du Vin, Université de Bordeaux, Villenave d'Ornon, 33882, France.
Víctor LópezDepartment of Pharmacy, Faculty of Health Sciences, Universidad San Jorge, Zaragoza, 50830, Spain.
Fermín I MilagroDepartment of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, Pamplona, 31008, Spain.
María P PortilloNutrition and Obesity Group, Department of Nutrition and Food Science, University of the Basque Country (UPV/EHU) and Lucio Lascaray Research Institute, Vitoria, 01006, Spain.
Silvia Lorente-CebriánAdipocyte and Fat Biology Laboratory (AdipoFat), Hospital Universitario Miguel Servet, Zaragoza, 50009, Spain. slorentec@unizar.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Addressing the physiological effects of bioactive compounds in metabolic diseases (i.e., obesity, diabetes, liver steatosis) and establishing their mechanisms of action have been a major interest for the last decades. However, methodologies that can be applied to achieve this can vary greatly, leading to a limited type of information. Thus, the accuracy, robustness, reliability and potential (human) translation are highly reliant on the experimental design and selected methodological models. This review presents an update exploring the main features, advantages and disadvantages of most important pre-clinical models used at the present time to study the effects of bioactive compounds on metabolic diseases. Moreover, future challenges in developing new methods are also depicted. In vitro models (enzyme assays and standard two-dimensional cultures of adipocytes, skeletal muscle cells) are intrinsically well established and constitute the first choice and most widely used methods to study bioactive compounds in metabolic diseases. However, novel models such as three-dimensional cultures (spheroids, organoids) are also starting to emerge and complement traditional culture systems. Models of small organisms (C. elegans, D. melanogaster) and non-mammal vertebrates (D. rerio) represent a scientific advantage and a middle-step before traditional mammalian models (rats and mice). This article provides extensive information and a critical overview of a wide range of methods that represent present and future avenues towards a further understanding of metabolic diseases. Combining and developing new methods will be key for future progression on the effects of bioactive compounds on metabolic diseases, as well as to minimize the use of mammalian models due to ethical reasons.

Indexed as

Metabolic DiseasesObesityAdipocytesAnimalsCaenorhabditis elegansDisease Models, AnimalHumansMiceZebrafishAdipocytesCaenorhabditis elegansDrosophilaEnterocytesGastrointestinal simulatorOrganoidsSkeletal muscle cellsSpheroidsTissue explantsZebrafish

Identifiers

PMID41134486
PMCPMC12738671

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.