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The nuclear long non-coding RNA LUCAT1 has previously been identified as a negative feedback regulator of type I interferon and inflammatory cytokine expression in human myeloid cells. Here, we define the mechanistic basis for the suppression of inflammatory gene expression by LUCAT1. Using comprehensive identification of RNA-binding proteins by mass spectrometry as well as RNA immunoprecipitation, we identified proteins important in processing and alternative splicing of mRNAs as LUCAT1-binding proteins. These included heterogeneous nuclear ribonucleoprotein C, M, and A2B1. Consistent with this finding, cells lacking LUCAT1 have altered splicing of selected immune genes. In particular, upon lipopolysaccharide stimulation, the splicing of the nuclear receptor 4A2 (NR4A2) gene was particularly affected. As a consequence, expression of NR4A2 was reduced and delayed in cells lacking LUCAT1. NR4A2-deficient cells had elevated expression of immune genes. These observations suggest that LUCAT1 is induced to control the splicing and stability of NR4A2, which is in part responsible for the anti-inflammatory effect of LUCAT1. Furthermore, we analyzed a large cohort of patients with inflammatory bowel disease as well as asthma and chronic obstructive pulmonary disease. In these patients, LUCAT1 levels were elevated and in both diseases, positively correlated with disease severity. Collectively, these studies define a key molecular mechanism of LUCAT1-dependent immune regulation through post-transcriptional regulation of mRNAs highlighting its role in the regulation of inflammatory disease.

The propagation of spin waves in magnetically ordered systems has emerged as a potential means to shuttle quantum information over large distances. Conventionally, the arrival time of a spin wavepacket at a distance, d, is assumed to be determined by its group velocity, vg . Here, we report time-resolved optical measurements of wavepacket propagation in the Kagome ferromagnet Fe₃Sn₂ that demonstrate the arrival of spin information at times significantly less than d/vg . We show that this spin wave “precursor” originates from the interaction of light with the unusual spectrum of magnetostatic modes in Fe₃Sn₂. Related effects may have far-reaching consequences toward realizing long-range, ultrafast spin wave transport in both ferromagnetic and antiferromagnetic systems.

The potential benefits of autonomous systems are obvious. However, there are still major issues to be dealt with before developing such systems becomes a commonplace engineering practice, with accepted and trustworthy deliverables. We argue that a solid, evolving, publicly available, community-controlled foundation for developing next-generation autonomous systems is a must, and term the desired foundation “autonomics.” We focus on three main challenges: 1) how to specify autonomous system behavior in the face of unpredictability; 2) how to carry out faithful analysis of system behavior with respect to rich environments that include humans, physical artifacts, and other systems; and 3) howto build such systems by combining executable modeling techniques from software engineering with artificial intelligence and machine learning.

The phosphoinositide, phosphatidylinositol 4,5-bisphosphate (PIP₂), has long been established as a major contributor to intracellular signaling, primarily by virtue of its role as a substrate for phospholipase C (PLC). Signaling by Gq-protein–coupled receptors triggers PLC-mediated hydrolysis of PIP₂ into inositol 1,4,5-trisphosphate and diacylglycerol, which are well known to modulate vascular ion channel activity. Often overlooked, however, is the role PIP₂ itself plays in this regulation. Although numerous reports have demonstrated that PIP₂ is critical for ion channel regulation, how it impacts vascular function has received scant attention. In this review, we focus on PIP₂ as a regulator of ion channels in smooth muscle cells and endothelial cells—the two major classes of vascular cells. We further address the concerted effects of such regulation on vascular function and blood flow control. We close with a consideration of current knowledge regarding disruption of PIP₂ regulation of vascular ion channels in disease.

Fragile X syndrome (FXS) results in intellectual disability (ID) most often caused by silencing of the fragile X mental retardation 1 (FMR1) gene. The resulting absence of fragile X mental retardation protein 1 (FMRP) leads to both pre–and postsynaptic defects, yet whether the pre–and postsynaptic functions of FMRP are independent and have distinct roles in FXS neuropathology remain poorly understood. Here, we demonstrate an independent presynaptic function for FMRP through the study of an ID patient with anFMR1missense mutation. This mutation, c.413G > A (R138Q), preserves FMRP’s canonical functions in RNA binding and translational regulation, which are traditionally associated with postsynaptic compartments. However, neuronally driven expression of the mutant FMRP is unable to rescue structural defects at the neuromuscular junction in fragile x mental retardation 1 (dfmr1)-deficientDrosophila, suggesting a presynaptic-specific impairment. Furthermore, mutant FMRP loses the ability to rescue presynaptic action potential (AP) broadening inFmr1KO mice. The R138Q mutation also disrupts FMRP’s interaction with the large-conductance calcium-activated potassium (BK) channels that modulate AP width. These results reveal a presynaptic–and translation-independent function of FMRP that is linked to a specific subset of FXS phenotypes.

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

We examine inDrosophilaa group of ∼35 ionotropic receptors (IRs), the IR20a clade, about which remarkably little is known. Of 28 genes analyzed,GAL4drivers representing 11 showed expression in the larva. Eight drivers labeled neurons of the pharynx, a taste organ, and three labeled neurons of the body wall that may be chemosensory. Expressionwas not observed in neurons of one taste organ, the terminal organ, although these neurons express many drivers of theGr(Gustatory receptor) family. For most drivers of theIR20aclade, we observed expression in a single pair of cells in the animal, with limited coexpression, and only a fraction of pharyngeal neurons are labeled. The organization ofIR20aclade expression thus appears different from the organization of theGrfamily or theOdor receptor(Or) family in the larva. A remarkable feature of the larval pharynx is that some of its organs are incorporated into the adult pharynx, and several drivers of this clade are expressed in the pharynx of both larvae and adults. Different IR drivers show different developmental dynamics across the larval stages, either increasing or decreasing. Among neurons expressing drivers in the pharynx, two projection patterns can be distinguished in the CNS. Neurons exhibiting these two kinds of projection patterns may activate different circuits, possibly signaling the presence of cues with different valence. Taken together, the simplest interpretation of our results is that theIR20aclade encodes a class of larval taste receptors.

Inorganic elements, although required only in trace amounts, permit life and primary productivity because of their functions in catalysis. Every organism has a minimal requirement of each metal based on the intracellular abundance of proteins that use inorganic cofactors, but elemental sparing mechanisms can reduce this quota. A well-studied copper-sparing mechanism that operates in microalgae faced with copper deficiency is the replacement of the abundant copper protein plastocyanin with a heme-containing substitute, cytochrome (Cyt)c₆. This switch, which is dependent on a copper-sensing transcription factor, copper response regulator 1 (CRR1), dramatically reduces the copper quota. We show here that in a situation of marginal copper availability, copper is preferentially allocated from plastocyanin, whose function is dispensable, to other more critical copper-dependent enzymes like Cyt oxidase and a ferroxidase. In the absence of an extracellular source, copper allocation to Cyt oxidase includes CRR1-dependent proteolysis of plastocyanin and quantitative recycling of the copper cofactor from plastocyanin to Cyt oxidase. Transcriptome profiling identifies a gene encoding a Zn-metalloprotease, as a candidate effecting copper recycling. One reason for the retention of genes encoding both plastocyanin and Cytc₆ in algal and cyanobacterial genomes might be because plastocyanin provides a competitive advantage in copper-depleted environments as a ready source of copper.

DNA sequencing has revealed high levels of variability within most species. Statistical methods based on population genetics theory have been applied to the resulting data and suggest that most mutations affecting functionally important sequences are deleterious but subject to very weak selection. Quantitative genetic studies have provided information on the extent of genetic variation within populations in traits related to fitness and the rate at which variability in these traits arises by mutation. This paper attempts to combine the available information from applications of the two approaches to populations of the fruitflyDrosophilain order to estimate some important parameters of genetic variation, using a simple population genetics model of mutational effects on fitness components. Analyses based on this model suggest the existence of a class of mutations with much larger fitness effects than those inferred from sequence variability and that contribute most of the standing variation in fitness within a population caused by the input of mildly deleterious mutations. However, deleterious mutations explain only part of this standing variation, and other processes such as balancing selection appear to make a large contribution to genetic variation in fitness components inDrosophila.

The molecular basis for the severity and rapid spread of the COVID-19 disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely unknown. ORF8 is a rapidly evolving accessory protein that has been proposed to interfere with immune responses. The crystal structure of SARS-CoV-2 ORF8 was determined at 2.04-Å resolution by X-ray crystallography. The structure reveals a ∼60-residue core similar to SARS-CoV-2 ORF7a, with the addition of two dimerization interfaces unique to SARS-CoV-2 ORF8. A covalent disulfide-linked dimer is formed through an N-terminal sequence specific to SARS-CoV-2, while a separate noncovalent interface is formed by another SARS-CoV-2−specific sequence, 73YIDI76. Together, the presence of these interfaces shows how SARS-CoV-2 ORF8 can form unique large-scale assemblies not possible for SARS-CoV, potentially mediating unique immune suppression and evasion activities.