Reference ranges ("normal values") for cardiovascular magnetic resonance (CMR) in adults and children: 2020 update

Cardiovascular magnetic resonance (CMR) enables assessment and quantification of morphological and functional parameters of the heart, including chamber size and function, diameters of the aorta and pulmonary arteries, flow and myocardial relaxation times. Knowledge of reference ranges ("normal values") for quantitative CMR is crucial to interpretation of results and to distinguish normal from disease. Compared to the previous version of this review published in 2015, we present updated and expanded reference values for morphological and functional CMR parameters of the cardiovascular system based on the peer-reviewed literature and current CMR techniques. Further, databases and references for deep learning methods are included

Dissociating Markers of Senescence and Protective Ability in Memory T Cells

No unique transcription factor or biomarker has been identified to reliably distinguish effector from memory T cells. Instead a set of surface markers including IL-7Rα and KLRG1 is commonly used to predict the potential of CD8 effector T cells to differentiate into memory cells. Similarly, these surface markers together with the tumor necrosis factor family member CD27 are frequently used to predict a memory T cell's ability to mount a recall response. Expression of these markers changes every time a memory cell is stimulated and repeated stimulation can lead to T cell senescence and loss of memory T cell responsiveness. This is a concern for prime–boost vaccine strategies which repeatedly stimulate T cells with the aim of increasing memory T cell frequency. The molecular cues that cause senescence are still unknown, but cell division history is likely to play a major role. We sought to dissect the roles of inflammation and cell division history in developing T cell senescence and their impact on the expression pattern of commonly used markers of senescence. We developed a system that allows priming of CD8 T cells with minimal inflammation and without acquisition of maximal effector function, such as granzyme expression, but a cell division history similar to priming with systemic inflammation. Memory cells derived from minimal effector T cells are fully functional upon rechallenge, have full access to non-lymphoid tissue and appear to be less senescent by phenotype upon rechallenge. However, we report here that these currently used biomarkers to measure senescence do not predict proliferative potential or protective ability, but merely reflect initial priming conditions

The Kuroshio Extension : a leading mechanism for the seasonal sea-level variability along the west coast of Japan

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Ocean Dynamics 60 (2010): 667-672, doi:10.1007/s10236-009-0239-9.Sea level changes coherently along the two coasts of Japan on the seasonal time scale. AVISO satellite altimetry data and OFES (OGCM for the Earth Simulator) results indicate that the variation propagates clockwise from Japan's east coast through the Tsushima Strait into the Japan/East Sea (JES) and then northward along the west coast. In this study, we hypothesize and test numerically that the sea level variability along the west coast of Japan is remotely forced by the Kuroshio Extension (KE) off the east coast. Topographic Rossby waves and boundary Kelvin waves facilitate the connection. Our 3-d POM model when forced by observed wind stress reproduces well the seasonal changes in the vicinity of JES. Two additional experiments were conducted to examine the relative roles of remote forcing and local forcing. The sea level variability inside the JES was dramatically reduced when the Tsushima Strait is blocked in one experiment. The removal of the local forcing, in another experiment, has little effect on the JES variability. Both experiments support our hypothesis that the open-ocean forcing, possibly through the KE variability, is the leading forcing mechanism for sea level change along the west coast of Japan.This work was conducted when Chao Ma was a visiting graduate student at WHOI. His visit has been supported by China Scholarship Council and WHOI Academics Office. This study has been supported by WHOI’s Coastal Ocean Institute, the National Basic Research Program of China 2005CB422303 and 2007CB481804), the International Science and Technology Cooperation Program of China (2006DFB21250), the Natural Science Foundation of China (40706006) , and the Ministry of Education’s 111 Project (B07036). Lin was supported by the Program for New Century Excellent Talents in University (NECT-07-0781)

The driver landscape of sporadic chordoma

Chordoma is a malignant, often incurable bone tumour showing notochordal differentiation. Here, we defined the somatic driver landscape of 104 cases of sporadic chordoma. We reveal somatic duplications of the notochordal transcription factor brachyury (T) in up to 27% of cases. These variants recapitulate the rearrangement architecture of the pathogenic germline duplications of T that underlie familial chordoma. In addition, we find potentially clinically actionable PI3K signalling mutations in 16% of cases. Intriguingly, one of the most frequently altered genes, mutated exclusively by inactivating mutation, was LYST (10%), which may represent a novel cancer gene in chordoma

Circumstellar discs: What will be next?

This prospective chapter gives our view on the evolution of the study of circumstellar discs within the next 20 years from both observational and theoretical sides. We first present the expected improvements in our knowledge of protoplanetary discs as for their masses, sizes, chemistry, the presence of planets as well as the evolutionary processes shaping these discs. We then explore the older debris disc stage and explain what will be learnt concerning their birth, the intrinsic links between these discs and planets, the hot dust and the gas detected around main sequence stars as well as discs around white dwarfs.Comment: invited review; comments welcome (32 pages

Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding

The recognition of cryptic small-molecular binding sites in protein structures is important for understanding off-target side effects and for recognizing potential new indications for existing drugs. Current methods focus on the geometry and detailed chemical interactions within putative binding pockets, but may not recognize distant similarities where dynamics or modified interactions allow one ligand to bind apparently divergent binding pockets. In this paper, we introduce an algorithm that seeks similar microenvironments within two binding sites, and assesses overall binding site similarity by the presence of multiple shared microenvironments. The method has relatively weak geometric requirements (to allow for conformational change or dynamics in both the ligand and the pocket) and uses multiple biophysical and biochemical measures to characterize the microenvironments (to allow for diverse modes of ligand binding). We term the algorithm PocketFEATURE, since it focuses on pockets using the FEATURE system for characterizing microenvironments. We validate PocketFEATURE first by showing that it can better discriminate sites that bind similar ligands from those that do not, and by showing that we can recognize FAD-binding sites on a proteome scale with Area Under the Curve (AUC) of 92%. We then apply PocketFEATURE to evolutionarily distant kinases, for which the method recognizes several proven distant relationships, and predicts unexpected shared ligand binding. Using experimental data from ChEMBL and Ambit, we show that at high significance level, 40 kinase pairs are predicted to share ligands. Some of these pairs offer new opportunities for inhibiting two proteins in a single pathway

Exploiting protein flexibility to predict the location of allosteric sites

Background: Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results: By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. Conclusions: We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors

Molecular dynamics simulations and drug discovery

This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role