Despite the evolution of hardwired homeostatic mechanisms to balance food intake with energy needs, the obesity epidemic continues to escalate globally. However, recent breakthroughs in delineating the molecular signaling pathways by which neural circuits regulate consummatory behaviors, along with transformative advances in peptide-based pharmacotherapy, are fueling the development of a new generation of safe and effective treatments for obesity. Here, we outline our current understanding of how the central nervous system controls energy homeostasis and examine how emerging insights, including those related to neuroplasticity, offer new perspectives for restoring energy balance and achieving durable weight loss. Together, these advances provide promising avenues for treating obesity and managing cardiometabolic disease.

Despite promising evidence in diagnostics and therapeutics, microbiome research is not yet implemented into clinical medicine. Several initiatives, including the standardization of microbiome research, the refinement of microbiome clinical trial design, and the development of communication between microbiome researchers and clinicians, are crucial to move microbiome science toward clinical practice.

Microbiome research has expanded significantly in the last two decades, yet translating findings into clinical applications remains challenging. This perspective discusses the persistent issue of correlational studies in microbiome research and proposes an iterative method leveraging in silico, in vitro, ex vivo, and in vivo studies toward successful preclinical and clinical trials. The evolution of research methodologies, including the shift from small cohort studies to large-scale, multi-cohort, and even "meta-cohort" analyses, has been facilitated by advancements in sequencing technologies, providing researchers with tools to examine multiple health phenotypes within a single study. The integration of multi-omics approaches-such as metagenomics, metatranscriptomics, metaproteomics, and metabolomics-provides a comprehensive understanding of host-microbe interactions and serves as a robust hypothesis generator for downstream in vitro and in vivo research. These hypotheses must then be rigorously tested, first with proof-of-concept experiments to clarify the causative effects of the microbiota, and then with the goal of deep mechanistic understanding. Only following these two phases can preclinical studies be conducted with the goal of translation into the clinic. We highlight the importance of combining traditional microbiological techniques with big-data approaches, underscoring the necessity of iterative experiments in diverse model systems to enhance the translational potential of microbiome research.

RNA plays a central role in protein biosynthesis and performs diverse regulatory and catalytic functions, making it essential for all processes of life. Like DNA, RNA is constantly subjected to damage from endogenous and environmental sources. However, while the DNA damage response has been extensively studied, it was long assumed that RNA lesions are relatively inconsequential due to the transient nature of most RNA molecules. Here, we review recent studies that challenge this view by revealing complex RNA damage responses that determine survival when cells are exposed to nucleic acid-damaging agents and promote the resolution of RNA lesions.

The identification of individual protein-protein interactions (PPIs) began more than 40 years ago, using protein affinity chromatography and antibody co-immunoprecipitation. As new technologies emerged, analysis of PPIs increased to a genome-wide scale with the introduction of intracellular tagging methods, affinity purification (AP) followed by mass spectrometry (MS), and co-fractionation MS (CF-MS). Now, combining the resulting catalogs of interactions with complementary methods, including crosslinking MS (XL-MS) and cryogenic electron microscopy (cryo-EM), helps distinguish direct interactions from indirect ones within the same or between different protein complexes. These powerful approaches and the promise of artificial intelligence applications like AlphaFold herald a future where PPIs and protein complexes, including energy-driven protein machines, will be understood in exquisite detail, unlocking new insights in the contexts of both basic biology and disease.

Every cell must solve the problem of how to fold its genome. We describe how the folded state of chromosomes is the result of the combined activity of multiple conserved mechanisms. Homotypic affinity-driven interactions lead to spatial partitioning of active and inactive loci. Molecular motors fold chromosomes through loop extrusion. Topological features such as supercoiling and entanglements contribute to chromosome folding and its dynamics, and tethering loci to sub-nuclear structures adds additional constraints. Dramatically diverse chromosome conformations observed throughout the cell cycle and across the tree of life can be explained through differential regulation and implementation of these basic mechanisms. We propose that the first functions of chromosome folding are to mediate genome replication, compaction, and segregation and that mechanisms of folding have subsequently been co-opted for other roles, including long-range gene regulation, in different conditions, cell types, and species.

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI's ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies.

Behavior is tightly synchronized with bodily physiology. Internal needs from the body drive behavior selection, while optimal behavior performance requires a coordinated physiological response. Internal state is dynamically represented by the nervous system to influence mood and emotion, and body-brain signals also direct responses to external sensory cues, enabling the organism to adapt and pursue its goals within an ever-changing environment. In this review, we examine the anatomy and function of the brain-body connection, manifested across local, reflex, and central regulation levels. We explore these hierarchical loops in the context of the immune system, specifically through the lens of immunoception, and discuss the impact of its dysregulation on human health.

Evolutionary changes in human brain structure and function have enabled our specialized cognitive abilities. How these changes have come about genetically and functionally has remained an open question. However, new methods are providing a wealth of information about the genetic, epigenetic, and transcriptomic differences that set the human brain apart. Combined with in vitro models that allow access to developing brain tissue and the cells of our closest living relatives, the puzzle pieces are now coming together to yield a much more complete picture of what is actually unique about the human brain. The challenge now will be linking these observations and making the jump from correlation to causation. However, elegant genetic manipulations are now possible and, when combined with model systems such as organoids, will uncover a mechanistic understanding of how evolutionary changes at the genetic level have led to key differences in development and function that enable human cognition.

A central principle in neuroscience is that neurons within the brain act in concert to produce perception, cognition, and adaptive behavior. Neurons are organized into specialized brain areas, dedicated to different functions to varying extents, and their function relies on distributed circuits to continuously encode relevant environmental and body-state features, enabling other areas to decode (interpret) these representations for computing meaningful decisions and executing precise movements. Thus, the distributed brain can be thought of as a series of computations that act to encode and decode information. In this perspective, we detail important concepts of neural encoding and decoding and highlight the mathematical tools used to measure them, including deep learning methods. We provide case studies where decoding concepts enable foundational and translational science in motor, visual, and language processing.

Long COVID, a type of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (PASC) defined by medically unexplained symptoms following infection with SARS-CoV-2, is a newly recognized infection-associated chronic condition that causes disability in some people. Substantial progress has been made in defining its epidemiology, biology, and pathophysiology. However, there is no cure for the tens of millions of people believed to be experiencing long COVID, and industry engagement in developing therapeutics has been limited. Here, we review the current state of knowledge regarding the biology and pathophysiology of long COVID, focusing on how the proposed mechanisms explain the physiology of the syndrome and how they provide a rationale for the implementation of a broad experimental medicine and clinical trials agenda. Progress toward preventing and curing long COVID and other infection-associated chronic conditions will require deep and sustained investment by funders and industry.

Microorganisms, including bacteria, archaea, viruses, fungi, and protists, are essential to life on Earth and the functioning of the biosphere. Here, we discuss the key roles of microorganisms in achieving the United Nations Sustainable Development Goals (SDGs), highlighting recent and emerging advances in microbial research and technology that can facilitate our transition toward a sustainable future. Given the central role of microorganisms in the biochemical processing of elements, synthesizing new materials, supporting human health, and facilitating life in managed and natural landscapes, microbial research and technologies are directly or indirectly relevant for achieving each of the SDGs. More importantly, the ubiquitous and global role of microbes means that they present new opportunities for synergistically accelerating progress toward multiple sustainability goals. By effectively managing microbial health, we can achieve solutions that address multiple sustainability targets ranging from climate and human health to food and energy production. Emerging international policy frameworks should reflect the vital importance of microorganisms in achieving a sustainable future.

Microbes were the only form of life on Earth for most of its history, and they still account for the vast majority of life's diversity. They convert rocks to soil, produce much of the oxygen we breathe, remediate our sewage, and sustain agriculture. Microbes are vital to planetary health as they maintain biogeochemical cycles that produce and consume major greenhouse gases and support large food webs. Modern microbiologists analyze nucleic acids, proteins, and metabolites; leverage sophisticated genetic tools, software, and bioinformatic algorithms; and process and integrate complex and heterogeneous datasets so that microbial systems may be harnessed to address contemporary challenges in health, the environment, and basic science. Here, we consider an inevitably incomplete list of emergent themes in our discipline and highlight those that we recognize as the archetypes of its modern era that aim to address the most pressing problems of the 21st century.

The dysfunction of blood-vessel-lining endothelial cells is a major cause of mortality. Although endothelial cells, being present in all organs as a single-cell layer, are often conceived as a rather inert cell population, the vascular endothelium as a whole should be considered a highly dynamic and interactive systemically disseminated organ. We present here a holistic view of the field of vascular research and review the diverse functions of blood-vessel-lining endothelial cells during the life cycle of the vasculature, namely responsive and relaying functions of the vascular endothelium and the responsive roles as instructive gatekeepers of organ function. Emerging translational perspectives in regenerative medicine, preventive medicine, and aging research are developed. Collectively, this review is aimed at promoting disciplinary coherence in the field of angioscience for a broader appreciation of the importance of the vasculature for organ function, systemic health, and healthy aging.

Computational data-centric research techniques play a prevalent and multi-disciplinary role in life science research. In the past, scientists in wet labs generated the data, and computational researchers focused on creating tools for the analysis of those data. Computational researchers are now becoming more independent and taking leadership roles within biomedical projects, leveraging the increased availability of public data. We are now able to generate vast amounts of data, and the challenge has shifted from data generation to data analysis. Here we discuss the pitfalls, challenges, and opportunities facing the field of data-centric research in biology. We discuss the evolving perception of computational data-driven research and its rise as an independent domain in biomedical research while also addressing the significant collaborative opportunities that arise from integrating computational research with experimental and translational biology. Additionally, we discuss the future of data-centric research and its applications across various areas of the biomedical field.

Cellular senescence is a cell fate triggered in response to stress and is characterized by stable cell-cycle arrest and a hypersecretory state. It has diverse biological roles, ranging from tissue repair to chronic disease. The development of new tools to study senescence in vivo has paved the way for uncovering its physiological and pathological roles and testing senescent cells as a therapeutic target. However, the lack of specific and broadly applicable markers makes it difficult to identify and characterize senescent cells in tissues and living organisms. To address this, we provide practical guidelines called "minimum information for cellular senescence experimentation in vivo" (MICSE). It presents an overview of senescence markers in rodent tissues, transgenic models, non-mammalian systems, human tissues, and tumors and their use in the identification and specification of senescent cells. These guidelines provide a uniform, state-of-the-art, and accessible toolset to improve our understanding of cellular senescence in vivo.

Obesity causes significant morbidity and mortality globally. Research in the last three decades has delivered a step-change in our understanding of the fundamental mechanisms that regulate energy homeostasis, building on foundational discoveries in mouse models of metabolic disease. However, not all findings made in rodents have translated to humans, hampering drug discovery in this field. Here, we review how studies in mice and humans have informed our current framework for understanding energy homeostasis, discuss their challenges and limitations, and offer a perspective on how human studies may play an increasingly important role in the discovery of disease mechanisms and identification of therapeutic targets in the future.

The past 50 years of interdisciplinary research in humans and model organisms has delivered unprecedented insights into the mechanisms through which diet affects energy balance. However, translating these results to prevent and treat obesity and its associated diseases remains challenging. Given the vast scope of this literature, we focus this Review on recent conceptual advances in molecular nutrition targeting the management of energy balance, including emerging dietary and pharmaceutical interventions and their interactions with the human gut microbiome. Notably, multiple current dietary patterns of interest embrace moderate-to-high fat intake or prioritize the timing of eating over macronutrient intake. Furthermore, the rapid expansion of microbiome research findings has complicated multiple longstanding tenets of nutrition while also providing new opportunities for intervention. Continued progress promises more precise and reliable dietary recommendations that leverage our growing knowledge of the microbiome, the changing landscape of clinical interventions, and our molecular understanding of human biology.

For more than a century, physicians have searched for ways to pharmacologically reduce excess body fat. The tide has finally turned with recent advances in biochemically engineered agonists for the receptor of glucagon-like peptide-1 (GLP-1) and their use in GLP-1-based polyagonists. These polyagonists reduce body weight through complementary pharmacology by incorporating the receptors for glucagon and/or the glucose-dependent insulinotropic polypeptide (GIP). In their most advanced forms, gut-hormone polyagonists achieve an unprecedented weight reduction of up to ∼20%-30%, offering a pharmacological alternative to bariatric surgery. Along with favorable effects on glycemia, fatty liver, and kidney disease, they also offer beneficial effects on the cardiovascular system and adipose tissue. These new interventions, therefore, hold great promise for the future of anti-obesity medications.

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.