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Bone vasculature provides protection and signals necessary to control stem cell quiescence and renewal1. Specifically, type H capillaries, which highly express Endomucin, constitute the endothelial niche supporting a microenvironment of osteoprogenitors and long-term hematopoietic stem cells2–4. The age-dependent decline in type H endothelial cells was shown to be associated with bone dysregulation and accumulation of hematopoietic stem cells, which display cell-intrinsic alterations and reduced functionality3. The regulation of bone vasculature by chronic diseases, such as heart failure is unknown. Here, we describe the effects of myocardial infarction and post-infarction heart failure on the vascular bone cell composition. We demonstrate an age-independent loss of type H bone endothelium in heart failure after myocardial infarction in both mice and in humans. Using single-cell RNA sequencing, we delineate the transcriptional heterogeneity of human bone marrow endothelium showing increased expression of inflammatory genes, including IL1B and MYC, in ischemic heart failure. Inhibition of NLRP3-dependent IL-1β production partially prevents the post-myocardial infarction loss of type H vasculature in mice. These results provide a rationale for using anti-inflammatory therapies to prevent or reverse the deterioration of vascular bone function in ischemic heart disease.
Efficient processing of visual environment necessitates the integration of incoming sensory evidence with concurrent contextual inputs and mnemonic content from our past experiences. To delineate how this integration takes place in the brain, we studied modulations of feedback neural patterns in non-stimulated areas of the early visual cortex in humans (i.e., V1 and V2). Using functional magnetic resonance imaging and multivariate pattern analysis, we show that both, concurrent contextual and time-distant mnemonic information, coexist in V1/V2 as feedback signals. The extent to which mnemonic information is reinstated in V1/V2 depends on whether the information is retrieved episodically or semantically. These results demonstrate that our stream of visual experience contains not just information from the visual surrounding, but also memory-based predictions internally generated in the brain.
Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIT outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and can affect multiple organs, among which is the circulatory system. Inflammation and mortality risk markers were previously detected in COVID-19 plasma and red blood cells (RBCs) metabolic and proteomic profiles. Additionally, biophysical properties, such as deformability, were found to be changed during the infection. Based on such data, we aim to better characterize RBC functions in COVID-19. We evaluate the flow properties of RBCs in severe COVID-19 patients admitted to the intensive care unit by using in vitro microfluidic techniques and automated methods, including artificial neural networks, for an unbiased RBC analysis. We find strong flow and RBC shape impairment in COVID-19 samples and demonstrate that such changes are reversible upon suspension of COVID-19 RBCs in healthy plasma. Vice versa, healthy RBCs immediately resemble COVID-19 RBCs when suspended in COVID-19 plasma. Proteomics and metabolomics analyses allow us to detect the effect of plasma exchanges on both plasma and RBCs and demonstrate a new role of RBCs in maintaining plasma equilibria at the expense of their flow properties. Our findings provide a framework for further investigations of clinical relevance for therapies against COVID-19 and possibly other infectious diseases.
Coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and can affect multiple organs, among which is the circulatory system. Inflammation and mortality risk markers were previously detected in COVID-19 plasma and red blood cells (RBCs) metabolic and proteomic profiles. Additionally, biophysical properties, such as deformability, were found to be changed during the infection. Based on such data, we aim to better characterize RBC functions in COVID-19. We evaluate the flow properties of RBCs in severe COVID-19 patients admitted to the intensive care unit by using in vitro microfluidic techniques and automated methods, including artificial neural networks, for an unbiased RBC analysis. We find strong flow and RBC shape impairment in COVID-19 samples and demonstrate that such changes are reversible upon suspension of COVID-19 RBCs in healthy plasma. Vice versa, healthy RBCs immediately resemble COVID-19 RBCs when suspended in COVID-19 plasma. Proteomics and metabolomics analyses allow us to detect the effect of plasma exchanges on both plasma and RBCs and demonstrate a new role of RBCs in maintaining plasma equilibria at the expense of their flow properties. Our findings provide a framework for further investigations of clinical relevance for therapies against COVID-19 and possibly other infectious diseases.
We carry out an in-depth analysis of the prompt-collapse behaviour of binary neutron star (BNS) mergers. To this end, we perform more than 80 general relativistic BNS merger simulations using a family of realistic Equations of State (EOS) with different stiffness, which feature a first order deconfinement phase transition between hadronic and quark matter. From these simulations we infer the critical binary mass Mcrit that separates the prompt from the non-prompt collapse regime. We show that the critical mass increases with the stiffness of the EOS and obeys a tight quasi-universal relation, Mcrit/MTOV ≈ 1.41 ± 0.06, which links it to the maximum mass MTOV of static neutron stars, and therefore provides a straightforward estimate for the total binary mass beyond which prompt collapse becomes inevitable. In addition, we introduce a novel gauge independent definition for a one-parameter family of threshold masses in terms of curvature invariants of the Riemann tensor which characterizes the development toward a more rapid collapse with increasing binary mass. Using these diagnostics, we find that the amount of matter remaining outside the black hole sharply drops in supercritical mass mergers compared to subcritical ones and is further reduced in mergers where the black hole collapse is induced by the formation of a quark matter core. This implies that Mcrit, particularly for merger remnants featuring quark matter cores, imposes a strict upper limit on the emission of any detectable electromagnetic counterpart in BNS mergers.
In this special issue of Matrix Biology centered on proteoglycan biology we have assembled a blend of articles focused on the state-of-the-art of proteoglycanology. The field has greatly expanded in the past three decades and now encompasses all the areas of biology. This special issue is divided into five chapters describing hyaluronan metabolism, biosynthetic and catabolic pathways of proteoglycans and their roles in inflammation, cancer, repair and development. We hope that the new original work and the reviews from recognized leaders will stimulate investigations in this exciting and fertile field of research.
Post-merger gravitational-wave signal from neutron-star binaries: a new look at an old problem
(2023)
The spectral properties of the post-merger gravitational-wave signal from a binary of neutron stars encodes a variety of information about the features of the system and of the equation of state describing matter around and above nuclear saturation density. Characterising the properties of such a signal is an “old” problem, which first emerged when a number of frequencies were shown to be related to the properties of the binary through “quasi-universal” relations. Here we take a new look at this old problem by computing the properties of the signal in terms of the Weyl scalar ψ4. In this way, and using a database of more than 100 simulations, we provide the first evidence for a new instantaneous frequency, f ψ4 0, associated with the instant of quasi timesymmetry in the postmerger dynamics, and which also follows a quasi-universal relation. We also derive a new quasi-universal relation for the merger frequency f h mer, which provides a description of the data that is four times more accurate than previous expressions while requiring fewer fitting coefficients. Finally, consistently with the findings of numerous studies before ours, and using an enlarged ensamble of binary systems we point out that the ℓ = 2, m = 1 gravitational-wave mode could become comparable with the traditional ℓ = 2, m = 2 mode on sufficiently long timescales, with strain amplitudes in a ratio |h 21|/|h 22| ∼ 0.1 − 1 under generic orientations of the binary, which could be measured by present detectors for signals with large signal-to-noise ratio or by third-generation detectors for generic signals should no collapse occur.
A considerable effort has been dedicated recently to the construction of generic equations of state (EOSs) for matter in neutron stars. The advantage of these approaches is that they can provide model-independent information on the interior structure and global properties of neutron stars. Making use of more than 106 generic EOSs, we asses the validity of quasi-universal relations of neutron star properties for a broad range of rotation rates, from slow-rotation up to the mass-shedding limit. In this way, we are able to determine with unprecedented accuracy the quasi-universal maximum-mass ratio between rotating and nonrotating stars and reveal the existence of a new relation for the surface oblateness, i.e., the ratio between the polar and equatorial proper radii. We discuss the impact that our findings have on the imminent detection of new binary neutron-star mergers and how they can be used to set new and more stringent limits on the maximum mass of nonrotating neutron stars, as well as to improve the modelling of the X-ray emission from the surface of rotating stars.