Emotions are part and parcel of the human condition, but their nature is debated. Three broad classes of theories about the nature of emotions can be distinguished affect-program theories, constructionist theories, and appraisal theories. Integrating these broad classes of theories into a unifying theory is challenging. An integrative psychometric model of emotions can inform such a theory because psychometric models are intertwined with theoretical perspectives about constructs. To identify an integrative psychometric model, we delineate properties of emotions stated by emotion theories and investigate whether psychometric models account for these properties. Specifically, an integrative psychometric model of emotions should allow (a) identifying distinct emotions (central in affect-program theories), (b) between- and within-person variations of emotions (central in constructionist theories), and (c) causal relationships between emotion components (central in appraisal theories). Evidence suggests that the popular reflective and formative latent variable models-in which emotions are conceptualized as unobservable causes or consequences of emotion components-cannot account for all properties. Conversely, a psychometric network model-in which emotions are conceptualized as systems of causally interacting emotion components-accounts for all properties. The psychometric network model thus constitutes an integrative psychometric model of emotions, facilitating progress toward a unifying theory.Osteocytes are an ancient cell, appearing in fossilized skeletal remains of early fish and dinosaurs. Despite its relative high abundance, even in the context of nonskeletal cells, the osteocyte is perhaps among the least studied cells in all of vertebrate biology. Osteocytes are cells embedded in bone, able to modify their surrounding extracellular matrix via specialized molecular remodeling mechanisms that are independent of the bone forming osteoblasts and bone-resorbing osteoclasts. Osteocytes communicate with osteoclasts and osteoblasts via distinct signaling molecules that include the RankL/OPG axis and the Sost/Dkk1/Wnt axis, among others. Osteocytes also extend their influence beyond the local bone environment by functioning as an endocrine cell that controls phosphate reabsorption in the kidney, insulin secretion in the pancreas, and skeletal muscle function. These cells are also finely tuned sensors of mechanical stimulation to coordinate with effector cells to adjust bone mass, size, and shape to conform to mechanical demands.Cardiac fibrosis is a pathological condition that occurs after injury and during aging.  https://www.selleckchem.com/products/epacadostat-incb024360.html  Currently, there are limited means to effectively reduce or reverse fibrosis. Key to identifying methods for curbing excess deposition of extracellular matrix is a better understanding of the cardiac fibroblast, the cell responsible for collagen production. In recent years, the diversity and functions of these enigmatic cells have been gradually revealed. In this review, I outline current approaches for identifying and classifying cardiac fibroblasts. An emphasis is placed on new insights into the heterogeneity of these cells as determined by lineage tracing and single-cell sequencing in development, adult, and disease states. These recent advances in our understanding of the fibroblast provide a platform for future development of novel therapeutics to combat cardiac fibrosis.The limits of evolution have long fascinated biologists. However, the causes of evolutionary constraint have remained elusive due to a poor mechanistic understanding of studied phenotypes. Recently, a range of innovative approaches have leveraged mechanistic information on regulatory networks and cellular biology. These methods combine systems biology models with population and single-cell quantification and with new genetic tools, and they have been applied to a range of complex cellular functions and engineered networks. In this article, we review these developments, which are revealing the mechanistic causes of epistasis at different levels of biological organization-in molecular recognition, within a single regulatory network, and between different networks-providing first indications of predictable features of evolutionary constraint. Expected final online publication date for the Annual Review of Biophysics, Volume 49 is May 6, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.We review the adaptations of enzyme activity to different temperatures. Psychrophilic (cold-adapted) enzymes show significantly different activation parameters (lower activation enthalpies and entropies) than their mesophilic counterparts. Furthermore, there is increasing evidence that the temperature dependence of many enzyme-catalyzed reactions is more complex than is widely believed. Many enzymes show curvature in plots of activity versus temperature that is not accounted for by denaturation or unfolding. This is explained by macromolecular rate theory A negative activation heat capacity for the rate-limiting chemical step leads directly to predictions of temperature optima; both entropy and enthalpy are temperature dependent. Fluctuations in the transition state ensemble are reduced compared to the ground state. We show how investigations combining experiment with molecular simulation are revealing fundamental details of enzyme thermoadaptation that are relevant for understanding aspects of enzyme evolution. Simulations can calculate relevant thermodynamic properties (such as activation enthalpies, entropies, and heat capacities) and reveal the molecular mechanisms underlying experimentally observed behavior. Expected final online publication date for the Annual Review of Biophysics, Volume 49 is May 6, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.Cleft palate is among the most common structural birth defects in humans. Previous studies have shown that mutations in FOXF2 are associated with cleft palate in humans and mice and that Foxf2 acts in a Shh-Foxf-Fgf18-Shh molecular network controlling palatal shelf growth. In this study, we combined RNA-seq and ChIP-seq approaches to identify direct transcriptional target genes mediating Foxf2 function in palate development in mice. Of 155 genes that exhibited Foxf2-dependent expression in the developing palatal mesenchyme, 88 contained or were located next to Foxf2-binding sites. Through in situ hybridization analyses, we demonstrate that expression of many of these target genes, including multiple genes encoding transcription factors and several encoding extracellular matrix-modifying proteins, were specifically upregulated in the posterior region of palatal shelves in Foxf2-/- mouse embryos. Foxf2 occupancy at many of these putative target loci, including Fgf18, in the developing palatal tissues was verified by ChIP-polymerase chain reaction analyses.