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Stellar binaries may form through several formation pathways, including disk or core fragmentation. Their spin–orbit angles are a signature of formation, although individual measurements for visual binaries are limited and broad. A seminal work by A. Hale found that visual binaries with separations ≲30 au tend to be more aligned, which laid the groundwork for binary formation theories. However, A. B. Justesen & S. Albrecht found that underestimated stellar radii lead to inaccurate spin–orbit angles and that Kolmogorov–Smirnov (KS) statistics do not provide meaningful population-level constraints, even with updated radii. Using a hierarchical Bayesian model to reanalyze their dataset, we find evidence with a Bayes factor of 12 for two subpopulations of spin–orbit angles separated by a ∼31–38 au cutoff. Binaries inside (outside) the cutoff are more (less) aligned, consistent with a Fisher distribution with κ = 48 (κ = 6). We also find possible indications of a secondary cutoff at ∼10–17 au, although more data are required to resolve this prediction. These cutoffs may mark transitions between formation pathways: closer-in binaries tend to form aligned in a shared protostellar disk, while wider binaries tend to form less aligned through turbulent fragmentation.

Macrophages are innate immune cells that form a 3D network in all our tissues, where they phagocytose dying cells and cell debris, immune complexes, bacteria and other waste products. Simultaneously, they produce growth factors and signalling molecules — such activities not only promote host protection in response to invading microorganisms but are also crucial for organ development and homeostasis. There is mounting evidence of macrophages orchestrating fundamental physiological processes, such as blood vessel formation, adipogenesis, metabolism and central and peripheral neuronal function. In parallel, novel methodologies have led to the characterization of tissue-specific macrophages, with distinct subpopulations of these cells showing different developmental trajectories, transcriptional programmes and life cycles. Here, we summarize our growing knowledge of macrophage diversity and how macrophage subsets orchestrate tissue development and function. We further interrelate macrophage ontogeny with their core functions across tissues, that is, the signalling events within the macrophage niche that may control organ functionality during development, homeostasis and ageing. Finally, we highlight the open questions that will need to be addressed by future studies to better understand the tissue-specific functions of distinct macrophage subsets.Macrophages are important for host immunity to infections and for clearing waste products from tissues, but they also maintain tissue health by regulating metabolism, neuronal functions and many other biological processes. Here, Elvira Mass and co-workers discuss the different tissue-specific macrophage populations that are found throughout the body, highlighting shared and unique aspects of their developmental trajectories, transcriptional programmes and physiological functions.

Peritoneal fibrosis is characterized by abnormal production of extracellular matrix proteins leading to progressive thickening of the submesothelial compact zone of the peritoneal membrane. This process may be caused by a number of insults including pathological conditions linked to clinical practice, such as peritoneal dialysis, abdominal surgery, hemoperitoneum, and infectious peritonitis. All these events may cause acute/chronic inflammation and injury to the peritoneal membrane, which undergoes progressive fibrosis, angiogenesis, and vasculopathy. Among the cellular processes implicated in these peritoneal alterations is the generation of myofibroblasts from mesothelial cells and other cellular sources that are central in the induction of fibrosis and in the subsequent functional deterioration of the peritoneal membrane. Myofibroblast generation and activity is actually integrated in a complex network of extracellular signals generated by the various cellular types, including leukocytes, stably residing or recirculating along the peritoneal membrane. Here, the main extracellular factors and the cellular players are described with emphasis on the cross-talk between immune system and cells of the peritoneal stroma. The understanding of cellular and molecular mechanisms underlying fibrosis of the peritoneal membrane has both a basic and a translational relevance, since it may be useful for setup of therapies aimed at counteracting the deterioration as well as restoring the homeostasis of the peritoneal membrane.

The term ‘fibroblast’ often serves as a catch-all for a diverse array of mesenchymal cells, including perivascular cells, stromal progenitor cells and bona fide fibroblasts. Although phenotypically similar, these subpopulations are functionally distinct, maintaining tissue integrity and serving as local progenitor reservoirs. In response to tissue injury, these cells undergo a dynamic fibroblast–myofibroblast transition, marked by extracellular matrix secretion and contraction of actomyosin-based stress fibres. Importantly, whereas transient activation into myofibroblasts aids in tissue repair, persistent activation triggers pathological fibrosis. In this Review, we discuss the roles of mechanical cues, such as tissue stiffness and strain, alongside cell signalling pathways and extracellular matrix ligands in modulating myofibroblast activation and survival. We also highlight the role of epigenetic modifications and myofibroblast memory in physiological and pathological processes. Finally, we discuss potential strategies for therapeutically interfering with these factors and the associated signal transduction pathways to improve the outcome of dysregulated healing.Fibroblasts undergo transient activation into myofibroblasts to restore homeostasis to injured tissues. This Review explores the influence of mechanical cues and epigenetic modifications on (myo)fibroblast activation and memory and discusses potential therapeutic prevention of persistent myofibroblast activation in fibrosis.

Viewing metabolism through the lens of exercise biology has proven an accessible and practical strategy to gain new insights into local and systemic metabolic regulation. Recent methodological developments have advanced understanding of the central role of skeletal muscle in many exercise-associated health benefits and have uncovered the molecular underpinnings driving adaptive responses to training regimens. In this Review, we provide a contemporary view of the metabolic flexibility and functional plasticity of skeletal muscle in response to exercise. First, we provide background on the macrostructure and ultrastructure of skeletal muscle fibres, highlighting the current understanding of sarcomeric networks and mitochondrial subpopulations. Next, we discuss acute exercise skeletal muscle metabolism and the signalling, transcriptional and epigenetic regulation of adaptations to exercise training. We address knowledge gaps throughout and propose future directions for the field. This Review contextualizes recent research of skeletal muscle exercise metabolism, framing further advances and translation into practice.Skeletal muscles show high metabolic flexibility and functional plasticity in their response to different exercise modalities. Recent findings have advanced our understanding of signalling, transcriptional and epigenetic mechanisms that regulate muscle adaptation to exercise and their impact on muscle physiology.

Each tumour contains diverse cellular states that underlie intratumour heterogeneity (ITH), a central challenge of cancer therapeutics 1 . Dozens of recent studies have begun to describe ITH by single-cell RNA sequencing, but each study typically profiled only a small number of tumours and provided a narrow view of transcriptional ITH 2 . Here we curate, annotate and integrate the data from 77 different studies to reveal the patterns of transcriptional ITH across 1,163 tumour samples covering 24 tumour types. Among the malignant cells, we identify 41 consensus meta-programs, each consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many tumours. The meta-programs cover diverse cellular processes including both generic (for example, cell cycle and stress) and lineage-specific patterns that we map into 11 hallmarks of transcriptional ITH. Most meta-programs of carcinoma cells are similar to those identified in non-malignant epithelial cells, suggesting that a large fraction of malignant ITH programs are variable even before oncogenesis, reflecting the biology of their cell of origin. We further extended the meta-program analysis to six common non-malignant cell types and utilize these to map cell–cell interactions within the tumour microenvironment. In summary, we have assembled a comprehensive pan-cancer single-cell RNA-sequencing dataset, which is available through the Curated Cancer Cell Atlas website, and leveraged this dataset to carry out a systematic characterization of transcriptional ITH. A study identifies 41 consensus gene expression meta-programs that are coordinately upregulated in subpopulations of malignant cells across tumour types, providing a comprehensive picture of hallmarks of intratumour heterogeneity.

With the desire to model population genetic processes under increasingly realistic scenarios, forward genetic simulations have become a critical part of the toolbox of modern evolutionary biology. The SLiM forward genetic simulation framework is one of the most powerful and widely used tools in this area. However, its foundation in the Wright–Fisher model has been found to pose an obstacle to implementing many types of models; it is difficult to adapt the Wright–Fisher model, with its many assumptions, to modeling ecologically realistic scenarios such as explicit space, overlapping generations, individual variation in reproduction, density-dependent population regulation, individual variation in dispersal or migration, local extinction and recolonization, mating between subpopulations, age structure, fitness-based survival and hard selection, emergent sex ratios, and so forth. In response to this need, we here introduce SLiM 3, which contains two key advancements aimed at abolishing these limitations. First, the new non-Wright–Fisher or “nonWF” model type provides a much more flexible foundation that allows the easy implementation of all of the above scenarios and many more. Second, SLiM 3 adds support for continuous space, including spatial interactions and spatial maps of environmental variables. We provide a conceptual overview of these new features, and present several example models to illustrate their use.