This Consensus Statement provides a nomenclature framework and experimental recommendations for studying mitochondrial transfer and transplantation.

This Review defines seven hallmarks of skeletal muscle homeostasis, providing a unifying framework for understanding, measuring and preserving muscle health.

This Review provides an overview of the biology of short-chain fatty acids, with a focus on their synthesis, signalling and physiological effects, highlighting their translational potential for metabolic and inflammatory diseases.

In a meta-analysis including 1.5 million incidences of cancer, positive associations between body mass index and 19 cancers were identified, underlining the impact of obesity on cancer risk.

A multi-organ proteomics resource of diet-induced obesity and its regression in male mice, spanning 15 organs and 4 timepoints, highlights systemic changes as well as impairments in adipose tissue function even under weight loss conditions.

Rewiring of branched-chain amino acid catabolism in prostate cancer fuels propionyl-CoA synthesis, lysine propionylation and stabilization of SREBP2, leading to increased cholesterol and androgen synthesis, and thus promotes metabolic adaptation of cancer cells and disease progression.

cGAS–STING signalling in intestinal epithelial cells modulates gut microbiome-derived indole-3-acetic acid production to regulate adipose thermogenesis and systemic metabolic health.

Using activity-dependent genetic labelling in mice, the authors identify cold-activated neurons in the parabrachial nucleus that coordinate autonomic, metabolic, behavioural and affective adaptations to cold exposure.

DHHC17-mediated palmitoylation promotes laminin-511 stabilization and availability in the liver metastatic niche, which decreases the cancer cell-killing capacity of neutrophils.

The study reports a non-classical tocopherol pathway in Rhodobacter that enables heterologous α-tocopherol synthesis by bypassing DMPBQ via a γ/β-tocopherol methyltransferase.

Somatic mutations are linked to diseases, yet their prevalence and relevance in health remain poorly defined. Technological advancements now enable us to delineate how tissue-specific somatic mutations drive adaptive metabolism across the lifespan and uncover hidden determinants of health and drivers of diseases.

Machine learning approaches are increasingly being used to aid small-molecule structure elucidation from mass spectrometry data. Surprisingly, however, current models often fail to outperform even simple baseline methods. Here we examine why these approaches fall short and propose strategies to overcome their limitations.

Artificial intelligence (AI) excels at prediction but often remains disconnected from biological mechanisms. We propose that metabolism may serve as a biochemical language through which AI systems can gain mechanistic understanding of how molecular states govern physiological function.

The recent global consensus to rename polycystic ovary syndrome (PCOS) as polyendocrine metabolic ovarian syndrome (PMOS) accurately reframes the condition as a lifelong, multisystemic disorder rather than a localized ovarian pathology. This transition underscores the central role of metabolic dysfunction, specifically the high prevalence of insulin resistance and hyperinsulinaemia, and has important consequences for basic and clinical research.

Co-submissions bring together independent studies that offer complementary insights and strengthen one another, and they remain an integral part of how we support robust research at Nature Metabolism.