Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
The glucagon-like peptide 1 receptor agonist (GLP-1RA) class of medicines has emerged as transformative for the treatment of diabetes, obesity and other diseases. On the twentieth anniversary of the approval of exenatide (Byetta), three former employees of Amylin Pharmaceuticals acknowledge the contributions of some of the individuals and the innovation responsible for delivering the first approved GLP-1RA — the forerunner to the modern blockbuster drugs.
Social media has become a go-to source for nutritional advice, and a space in which influencers compete with, and often drown out, evidence-based guidance. The scientific community should counter this viral spread of misinformation by making trustworthy information more accessible.
Obesity is a global public health concern closely linked to cardiometabolic complications. This Comment provides our views on recent breakthroughs, emerging innovations and future needs of therapeutic interventions to counteract obesity and its associated health risks.
Clustering and nesting (C&N) arise in many preclinical studies, such as when animals are group-housed or share litters, or in cell culture. Ignoring C&N undermines the validity of analyses. Here, we explain how C&N arise, as well as valid designs and analyses.
At Nature Metabolism, we believe that peer review benefits from the views of a diverse pool of reviewers. Here, we share some data about the gender, career stages and geographical distribution of our reviewers.
Pathway analysis, originally developed for gene expression data, has been adapted for metabolomics. However, owing to the unique characteristics and constraints of metabolites compared with genes, pathway analysis in metabolomics often yields misleading or nonsensical results.
Here, we introduce Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI), a multidisciplinary data-generation project designed to create and share a multimodal dataset optimized for artificial intelligence research in type 2 diabetes mellitus.
We have lost a distinguished scientist who made indelible contributions to our knowledge of exercise physiology and diabetes and was an advocate for mentoring and transparency in research.
Although Western societies are mesmerized by the power of new anti-obesity drugs, we must not forget how diet can affect metabolic outcomes. In this Focus issue, and accompanying web collection, we showcase a series of Reviews, Comments and original research articles that present up-to-date evidence on how dietary interventions can affect cardiometabolic health.
Extracellular vesicles (EVs) are now recognized as powerful modulators of metabolism, and thus the new field of EV-mediated metabolic regulation is growing exponentially. Here, we discuss special experimental considerations for the study of EV function in metabolism.
Despite the high utility and widespread use of Cre driver lines, lack of Cre specificity, Cre-induced toxicity or poor experimental design can affect experimental results and conclusions. Such pitfalls must be considered before embarking on any Cre-based studies in metabolic research.
Time-restricted eating has become a popular diet for weight management and has spurred tremendous interest in the scientific community. The translation of results from TRE trials heavily depends on trial design. In this Comment, we provide general guidelines on optimizing the design and performance of time-restricted eating trials in human participants.