Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs.

Purpose To develop and evaluate a publicly available deep learning model for segmenting and classifying cardiac implantable electronic devices (CIEDs) on Digital Imaging and Communications in Medicine (DICOM) and smartphone-based chest radiographs. Materials and Methods This institutional review board-approved retrospective study included patients with implantable pacemakers, cardioverter defibrillators, cardiac resynchronization therapy devices, and cardiac monitors who underwent chest radiography between January 2012 and January 2022. A U-Net model with a ResNet-50 backbone was created to classify CIEDs on DICOM and smartphone images. Using 2321 chest radiographs in 897 patients (median age, 76 years [range, 18-96 years]; 625 male, 272 female), CIEDs were categorized into four manufacturers, 27 models, and one "other" category. Five smartphones were used to acquire 11 072 images. Performance was reported using the Dice coefficient on the validation set for segmentation or balanced accuracy on the test set for manufacturer and model classification, respectively. Results The segmentation tool achieved a mean Dice coefficient of 0.936 (IQR: 0.890-0.958). The model had an accuracy of 94.36% (95% CI: 90.93%, 96.84%; 251 of 266) for CIED manufacturer classification and 84.21% (95% CI: 79.31%, 88.30%; 224 of 266) for CIED model classification. Conclusion The proposed deep learning model, trained on both traditional DICOM and smartphone images, showed high accuracy for segmentation and classification of CIEDs on chest radiographs. Keywords: Conventional Radiography, Segmentation Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Júdice de Mattos Farina and Celi in this issue.

Defining the Middle Corona.

The middle corona, the region roughly spanning heliocentric distances from 1.5 to 6 solar radii, encompasses almost all of the influential physical transitions and processes that govern the behavior of coronal outflow into the heliosphere. The solar wind, eruptions, and flows pass through the region, and they are shaped by it. Importantly, the region also modulates inflow from above that can drive dynamic changes at lower heights in the inner corona. Consequently, the middle corona is essential for comprehensively connecting the corona to the heliosphere and for developing corresponding global models. Nonetheless, because it is challenging to observe, the region has been poorly studied by both major solar remote-sensing and in-situ missions and instruments, extending back to the Solar and Heliospheric Observatory (SOHO) era. Thanks to recent advances in instrumentation, observational processing techniques, and a realization of the importance of the region, interest in the middle corona has increased. Although the region cannot be intrinsically separated from other regions of the solar atmosphere, there has emerged a need to define the region in terms of its location and extension in the solar atmosphere, its composition, the physical transitions that it covers, and the underlying physics believed to shape the region. This article aims to define the middle corona, its physical characteristics, and give an overview of the processes that occur there.

Understanding the Origins of Problem Geomagnetic Storms Associated with "Stealth" Coronal Mass Ejections.

Geomagnetic storms are an important aspect of space weather and can result in significant impacts on space- and ground-based assets. The majority of strong storms are associated with the passage of interplanetary coronal mass ejections (ICMEs) in the near-Earth environment. In many cases, these ICMEs can be traced back unambiguously to a specific coronal mass ejection (CME) and solar activity on the frontside of the Sun. Hence, predicting the arrival of ICMEs at Earth from routine observations of CMEs and solar activity currently makes a major contribution to the forecasting of geomagnetic storms. However, it is clear that some ICMEs, which may also cause enhanced geomagnetic activity, cannot be traced back to an observed CME, or, if the CME is identified, its origin may be elusive or ambiguous in coronal images. Such CMEs have been termed "stealth CMEs". In this review, we focus on these "problem" geomagnetic storms in the sense that the solar/CME precursors are enigmatic and stealthy. We start by reviewing evidence for stealth CMEs discussed in past studies. We then identify several moderate to strong geomagnetic storms (minimum Dst < - 50  nT) in solar cycle 24 for which the related solar sources and/or CMEs are unclear and apparently stealthy. We discuss the solar and in situ circumstances of these events and identify several scenarios that may account for their elusive solar signatures. These range from observational limitations (e.g., a coronagraph near Earth may not detect an incoming CME if it is diffuse and not wide enough) to the possibility that there is a class of mass ejections from the Sun that have only weak or hard-to-observe coronal signatures. In particular, some of these sources are only clearly revealed by considering the evolution of coronal structures over longer time intervals than is usually considered. We also review a variety of numerical modelling approaches that attempt to advance our understanding of the origins and consequences of stealthy solar eruptions with geoeffective potential. Specifically, we discuss magnetofrictional modelling of the energisation of stealth CME source regions and magnetohydrodynamic modelling of the physical processes that generate stealth CME or CME-like eruptions, typically from higher altitudes in the solar corona than CMEs from active regions or extended filament channels.

Magnetic Structure and Propagation of Two Interacting CMEs From the Sun to Saturn.

One of the grand challenges in heliophysics is the characterization of coronal mass ejection (CME) magnetic structure and evolution from eruption at the Sun through heliospheric propagation. At present, the main difficulties are related to the lack of direct measurements of the coronal magnetic fields and the lack of 3D in-situ measurements of the CME body in interplanetary space. Nevertheless, the evolution of a CME magnetic structure can be followed using a combination of multi-point remote-sensing observations and multi-spacecraft in-situ measurements as well as modeling. Accordingly, we present in this work the analysis of two CMEs that erupted from the Sun on April 28, 2012. We follow their eruption and early evolution using remote-sensing data, finding indications of CME-CME interaction, and then analyze their interplanetary counterpart(s) using in-situ measurements at Venus, Earth, and Saturn. We observe a seemingly single flux rope at all locations, but find possible signatures of interaction at Earth, where high-cadence plasma data are available. Reconstructions of the in-situ flux ropes provide almost identical results at Venus and Earth but show greater discrepancies at Saturn, suggesting that the CME was highly distorted and/or that further interaction with nearby solar wind structures took place before 10 AU. This work highlights the difficulties in connecting structures from the Sun to the outer heliosphere and demonstrates the importance of multi-spacecraft studies to achieve a deeper understanding of the magnetic configuration of CMEs.

X-Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A2A Adenosine Receptor Antagonists.

We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X-ray crystallography to reveal the binding mode of an antagonist series to the A2A adenosine receptor (AR). Eight A2A AR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A2A AR were experimentally determined and investigated through a cycle of ligand-FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X-ray crystallography of the A2A AR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A2A AR, an emerging target in immuno-oncology.

SHORE-based detection and imputation of dropout in diffusion MRI.

PURPOSE: In diffusion MRI, dropout refers to a strong attenuation of the measured signal that is caused by bulk motion during the diffusion encoding. When left uncorrected, dropout will be erroneously interpreted as high diffusivity in the affected direction. We present a method to automatically detect dropout, and to replace the affected measurements with imputed values. METHODS: Signal dropout is detected by deriving an outlier score from a simple harmonic oscillator-based reconstruction and estimation (SHORE) fit of all measurements. The outlier score is defined to detect measurements that are substantially lower than predicted by SHORE in a relative sense, while being less sensitive to measurement noise in cases of weak baseline signal. A second SHORE fit is based on detected inliers only, and its predictions are used to replace outliers. RESULTS: Our method is shown to reliably detect and accurately impute dropout in simulated data, and to achieve plausible results in corrupted in vivo dMRI measurements. Computational effort is much lower than with previously proposed alternatives. CONCLUSIONS: Deriving a suitable outlier score from SHORE results in a fast and accurate method for detection and imputation of dropout in diffusion MRI. It requires measurements with multiple b values (such as multi-shell or DSI), but is independent from the models used for analysis (such as DKI, NODDI, deconvolution, etc.).

Structural insight into allosteric modulation of protease-activated receptor 2.

Protease-activated receptors (PARs) are a family of G-protein-coupled receptors (GPCRs) that are irreversibly activated by proteolytic cleavage of the N terminus, which unmasks a tethered peptide ligand that binds and activates the transmembrane receptor domain, eliciting a cellular cascade in response to inflammatory signals and other stimuli. PARs are implicated in a wide range of diseases, such as cancer and inflammation. PARs have been the subject of major pharmaceutical research efforts but the discovery of small-molecule antagonists that effectively bind them has proved challenging. The only marketed drug targeting a PAR is vorapaxar, a selective antagonist of PAR1 used to prevent thrombosis. The structure of PAR1 in complex with vorapaxar has been reported previously. Despite sequence homology across the PAR isoforms, discovery of PAR2 antagonists has been less successful, although GB88 has been described as a weak antagonist. Here we report crystal structures of PAR2 in complex with two distinct antagonists and a blocking antibody. The antagonist AZ8838 binds in a fully occluded pocket near the extracellular surface. Functional and binding studies reveal that AZ8838 exhibits slow binding kinetics, which is an attractive feature for a PAR2 antagonist competing against a tethered ligand. Antagonist AZ3451 binds to a remote allosteric site outside the helical bundle. We propose that antagonist binding prevents structural rearrangements required for receptor activation and signalling. We also show that a blocking antibody antigen-binding fragment binds to the extracellular surface of PAR2, preventing access of the tethered ligand to the peptide-binding site. These structures provide a basis for the development of selective PAR2 antagonists for a range of therapeutic uses.

Impact of protein-ligand solvation and desolvation on transition state thermodynamic properties of adenosine A2A ligand binding kinetics.

Ligand-protein binding kinetic rates are growing in importance as parameters to consider in drug discovery and lead optimization. In this study we analysed using surface plasmon resonance (SPR) the transition state (TS) properties of a set of six adenosine A2A receptor inhibitors, belonging to both the xanthine and the triazolo-triazine scaffolds. SPR highlighted interesting differences among the ligands in the enthalpic and entropic components of the TS energy barriers for the binding and unbinding events. To better understand at a molecular level these differences, we developed suMetaD, a novel molecular dynamics (MD)-based approach combining supervised MD and metadynamics. This method allows simulation of the ligand unbinding and binding events. It also provides the system conformation corresponding to the highest energy barrier the ligand is required to overcome to reach the final state. For the six ligands evaluated in this study their TS thermodynamic properties were linked in particular to the role of water molecules in solvating/desolvating the pocket and the small molecules. suMetaD identified kinetic bottleneck conformations near the bound state position or in the vestibule area. In the first case the barrier is mainly enthalpic, requiring the breaking of strong interactions with the protein. In the vestibule TS location the kinetic bottleneck is instead mainly of entropic nature, linked to the solvent behaviour.

Purification of Stabilized GPCRs for Structural and Biophysical Analyses.

G protein-coupled receptors (GPCRs) are of particular importance for drug discovery, being the targets of many existing drugs, and being linked to many diseases where new therapies are required. However, as integral membrane proteins, they are generally unstable when removed from their membrane environment, precluding them from the wide range of structural and biophysical techniques which can be applied to soluble proteins such as kinases. Through the use of protein engineering methods, mutations can be identified which both increase the thermostability of GPCRs when purified in detergent, as well as biasing the receptor toward a specific physiologically relevant conformational state. The resultant stabilized receptor (known as a StaR) can be purified in multiple-milligram quantities, whilst retaining correct folding, thus enabling the generation of reagents suitable for a broad range of structural and biophysical studies. Example protocols for the purification of StaR proteins for analysis, ligand screening with the thiol-specific fluorochrome N-[4-(7-diethylamino-4-methyl-3-coumarinyl)phenyl]maleimide (CPM), surface plasmon resonance (SPR), and crystallization for structural studies are presented.

Biosensor-based affinities and binding kinetics of small molecule antagonists to the adenosine A(2A) receptor reconstituted in HDL like particles.

The options for investigating solubilised G protein-coupled receptors (GPCRs) by biophysical techniques have long been hampered by their instability. A thermostabilised adenosine A2A receptor expressed in insect cells, purified in detergent and reconstituted into high-density lipoprotein (HDL) particles was immobilised onto a Surface Plasmon Resonance sensor chip. This allowed measurement of affinities and kinetics for A2A antagonists with affinities ranging from 50 pM to almost 2 µM. Compared with other formats, reproduction of affinities, and dissociation and association rate constants are good, reasonable and poor respectively, indicating stabilised receptors in HDL particles are useful for investigating specific aspects of GPCR-ligand interactions.

Monoclonal anti-ß1-adrenergic receptor antibodies activate G protein signaling in the absence of ß-arrestin recruitment.

Thermostabilized G protein-coupled receptors used as antigens for in vivo immunization have resulted in the generation of functional agonistic anti-ß1-adrenergic (ß1AR) receptor monoclonal antibodies (mAbs). The focus of this study was to examine the pharmacology of these antibodies to evaluate their mechanistic activity at ß1AR. Immunization with the ß1AR stabilized receptor yielded five stable hybridoma clones, four of which expressed functional IgG, as determined in cell-based assays used to evaluate cAMP stimulation. The antibodies bind diverse epitopes associated with low nanomolar agonist activity at ß1AR, and they appeared to show some degree of biased signaling as they were inactive in an assay measuring signaling through ß-arrestin. In vitro characterization also verified different antibody receptor interactions reflecting the different epitopes on the extracellular surface of ß1AR to which the mAbs bind. The anti-ß1AR mAbs only demonstrated agonist activity when in dimeric antibody format, but not as the monomeric Fab format, suggesting that agonist activation may be mediated through promoting receptor dimerization. Finally, we have also shown that at least one of these antibodies exhibits in vivo functional activity at a therapeutically-relevant dose producing an increase in heart rate consistent with ß1AR agonism.

Identification of novel adenosine A(2A) receptor antagonists by virtual screening.

Virtual screening was performed against experimentally enabled homology models of the adenosine A(2A) receptor, identifying a diverse range of ligand efficient antagonists (hit rate 9%). By use of ligand docking and Biophysical Mapping (BPM), hits 1 and 5 were optimized to potent and selective lead molecules (11-13 from 5, pK(I) = 7.5-8.5, 13- to >100-fold selective versus adenosine A(1); 14-16 from 1, pK(I) = 7.9-9.0, 19- to 59-fold selective).

Discovery of 1,2,4-triazine derivatives as adenosine A(2A) antagonists using structure based drug design.

Potent, ligand efficient, selective, and orally efficacious 1,2,4-triazine derivatives have been identified using structure based drug design approaches as antagonists of the adenosine A(2A) receptor. The X-ray crystal structures of compounds 4e and 4g bound to the GPCR illustrate that the molecules bind deeply inside the orthosteric binding cavity. In vivo pharmacokinetic and efficacy data for compound 4k are presented, demonstrating the potential of this series of compounds for the treatment of Parkinson's disease.

Biophysical mapping of the adenosine A2A receptor.

A new approach to generating information on ligand receptor interactions within the binding pocket of G protein-coupled receptors has been developed, called Biophysical Mapping (BPM). Starting from a stabilized receptor (StaR), minimally engineered for thermostability, additional single mutations are then added at positions that could be involved in small molecule interactions. The StaR and a panel of binding site mutants are captured onto Biacore chips to enable characterization of the binding of small molecule ligands using surface plasmon resonance (SPR) measurement. A matrix of binding data for a set of ligands versus each active site mutation is then generated, providing specific affinity and kinetic information (K(D), k(on), and k(off)) of receptor-ligand interactions. This data set, in combination with molecular modeling and docking, is used to map the small molecule binding site for each class of compounds. Taken together, the many constraints provided by these data identify key protein-ligand interactions and allow the shape of the site to be refined to produce a high quality three-dimensional picture of ligand binding, thereby facilitating structure based drug design. Results of biophysical mapping of the adenosine A(2A) receptor are presented.

The properties of thermostabilised G protein-coupled receptors (StaRs) and their use in drug discovery.

G protein-coupled receptors (GPCRs) are one of the most important target classes in the central nervous system (CNS) drug discovery, however the fact they are integral membrane proteins and are unstable when purified out of the cell precludes them from a wide range of structural and biophysical techniques that are used for soluble proteins. In this study we demonstrate how protein engineering methods can be used to identify mutations which can both increase the thermostability of receptors, when purified in detergent, as well as biasing the receptor towards a specific physiologically relevant conformational state. We demonstrate this method for the adenosine A(2A) receptor and muscarinic M(1) receptor. The resultant stabilised receptors (known as StaRs) have a pharmacological profile consistent with the inverse agonist conformation. The stabilised receptors can be purified in large quantities, whilst retaining correct folding, thus generating reagents suitable for a broad range of structural and biophysical studies. In the case of the A(2A)-StaR we demonstrate that surface plasmon resonance can be used to profile the association and dissociation rates of a range of antagonists, a technique that can be used to improve the in vivo efficacy of receptor antagonists.

Label-free primary screening and affinity ranking of fragment libraries using parallel analysis of protein panels.

The authors present fragment screening data obtained using a label-free parallel analysis approach where the binding of fragment library compounds to 4 different target proteins can be screened simultaneously using surface plasmon resonance detection. They suggest this method as a first step in fragment screening to identify and select binders, reducing the demanding requirements on subsequent X-ray or nuclear magnetic resonance studies, and as a valuable "clean-up" tool to eliminate unwanted promiscuous binders from libraries. A small directed fragment library of known thrombin binders and a general 500-compound fragment library were used in this study. Thrombin, blocked thrombin, carbonic anhydrase, and glutathione-S-transferase were immobilized on the sensor chip surface, and the direct binding of the fragments was studied in real time. Only 12 microg of each protein is needed for screening of a 3000-compound fragment library. For screening, a binding site-blocked target as reference facilitates the identification of binding site-selective hits and the signals from other reference proteins for the elimination of false positives. The scope and limitations of this screening approach are discussed for both target-directed and general fragment libraries.

Statistical aspects of van't Hoff analysis: a simulation study.

The thermodynamics of biological interactions is frequently studied by the van't Hoff analysis whereby data on variation of the binding constant K(D) with temperature are used to obtain estimates of standard enthalpy (Delta H degrees ), entropy (Delta S degrees ), and heat capacity (Delta C degrees P) of complex formation. A Monte Carlo simulation demonstrates that the absolute error of the above parameters is proportional to the relative error of KD and independent of the actual values of KD and of the way they vary with temperature. The error of Delta H degrees is approximately the same as that of T Delta S degrees (within 14% in the temperature range 5-45 degrees C). The error depends both on the number of temperature points within the experimental temperature range and on the size of the range, but it is more sensitive to the latter. Using the linear form of the van't Hoff equation to fit data with non-zero Delta C degrees P gives erroneous Delta H degrees and DeltaS degrees estimates at standard temperature except for the case when the T points are placed symmetrically with respect to the standard temperature. With the range of Delta C degrees P values usual for protein-protein interactions, the KD error must be very low to confidently infer that Delta C degrees P is non-zero or to claim that two interactions have different Delta C degrees P.

Optimizing the surface plasmon resonance/mass spectrometry interface for functional proteomics applications: how to avoid and utilize nonspecific adsorption.

A great challenge in functional or interaction proteomics is to map protein networks and establish a functional relationship between expressed proteins and their effects on cellular processes. These cellular processes can be studied by characterizing binding partners to a "bait" protein against a complex background of other molecules present in cells, tissues, or biological fluids. This so-called ligand fishing process can be performed by combining surface plasmon resonance biosensors with MS. This combination generates a unique and automated method to quantify and characterize biomolecular interactions, and identify the interaction partners. A general problem in chip-based affinity separation systems is the large surface-to-volume ratio of the fluidic system. Extreme care, therefore, is required to avoid nonspecific adsorption, resulting in losses of the target protein and carry-over during the affinity purification process, which may lead to unwanted signals in the final MS analysis and a reduction in sensitivity. In this study, carry-over of protein and low-molecular weight substances has been investigated systematically and cleaning strategies are presented. Furthermore, it is demonstrated that by the introduction of colloidal particles as a capturing and transporting agent, the recovery yield of the affinity-purified ligand could be improved nearly twofold.

Integration of surface plasmon resonance with mass spectrometry: automated ligand fishing and sample preparation for MALDI MS using a Biacore 3000 biosensor.

Integrating surface plasmon resonance analysis with mass spectrometry allows detection and characterization of molecular interactions to be complemented with identification of interaction partners. We have developed a procedure for Biacore 3000 that automatically performs all steps from ligand fishing and recovery to sample preparation for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry including on-target digestion. In the model system used in this study a signal transduction protein, calmodulin, was selectively captured from brain extract by one of its interaction partners immobilized on a sensor chip. The bound material was eluted, deposited directly onto a MALDI target, and analyzed by mass spectrometry both as an intact protein and after on-target tryptic digestion. The procedure with direct deposition of recovered material on the MALDI target reduces sample losses and, in combination with automatic sample processing, increases the throughput of surface plasmon resonance mass spectrometry analysis.