Similar Binding Modes of cGMP Analogues Limit Selectivity in Modulating Retinal CNG Channels via the Cyclic Nucleotide-Binding Domain.

In treating retinitis pigmentosa, a genetic disorder causing progressive vision loss, selective inhibition of rod cyclic nucleotide-gated (CNG) channels holds promise. Blocking the increased Ca2+-influx in rod photoreceptors through CNG channels can potentially delay disease progression and improve the quality of life for patients. To find inhibitors for rod CNG channels, we investigated the impact of 16 cGMP analogues on both rod and cone CNG channels using the patch-clamp technique. Although modifications at the C8 position of the guanine ring did not change the ligand efficacy, modifications at the N1 and N2 positions rendered cGMP largely ineffective in activating retinal CNG channels. Notably, PET-cGMP displayed selective potential, favoring rod over cone, whereas Rp-cGMPS showed greater efficiency in activating cone over rod CNG channels. Ligand docking and molecular dynamics simulations on cyclic nucleotide-binding domains showed comparable binding energies and binding modes for cGMP and its analogues in both rod and cone CNG channels (CNGA1 vs CNGA3 subunits). Computational experiments on CNGB1a vs CNGB3 subunits showed similar binding modes albeit with fewer amino acid interactions with cGMP due to an inactivated conformation of their C-helix. In addition, no clear correlation could be observed between the computational scores and the CNG channel efficacy values, suggesting additional factors beyond binding strength determining ligand selectivity and potency. This study highlights the importance of looking beyond the cyclic nucleotide-binding domain and toward the gating mechanism when searching for selective modulators. Future efforts in developing selective modulators for CNG channels should prioritize targeting alternative channel domains.

Ferric reduction by a CYBDOM protein counteracts increased iron availability in root meristems induced by phosphorus deficiency.

To mobilize sparingly available phosphorus (P) in the rhizosphere, many plant species secrete malate to release P sorbed onto (hydr)oxides of aluminum and iron (Fe). In the presence of Fe, malate can provoke Fe over-accumulation in the root apoplast, triggering a series of events that inhibit root growth. Here, we identified HYPERSENSITIVE TO LOW P1 (HYP1), a CYBDOM protein constituted of a DOMON and a cytochrome b561 domain, as critical to maintain cell elongation and meristem integrity under low P. We demonstrate that HYP1 mediates ascorbate-dependent trans-plasma membrane electron transport and can reduce ferric and cupric substrates in Xenopus laevis oocytes and in planta. HYP1 expression is up-regulated in response to P deficiency in the proximal zone of the root apical meristem. Disruption of HYP1 leads to increased Fe and callose accumulation in the root meristem and causes significant transcriptional changes in roots. We further demonstrate that HYP1 activity overcomes malate-induced Fe accumulation, thereby preventing Fe-dependent root growth arrest in response to low P. Collectively, our results uncover an ascorbate-dependent metalloreductase that is critical to protect root meristems of P-deficient plants from increased Fe availability and provide insights into the physiological function of the yet poorly characterized but ubiquitous CYBDOM proteins.

Glomerular-tubular crosstalk via cold shock Y-box binding protein-1 in the kidney.

Glomerular-tubular crosstalk within the kidney has been proposed, but the paracrine signals enabling this remain largely unknown. The cold-shock protein Y-box binding protein 1 (YBX1) is known to regulate inflammation and kidney diseases but its role in podocytes remains undetermined. Therefore, we analyzed mice with podocyte specific Ybx1 deletion (Ybx1ΔPod). Albuminuria was increased in unchallenged Ybx1ΔPod mice, which surprisingly was associated with reduced glomerular, but enhanced tubular damage. Tubular toll-like receptor 4 (TLR4) expression, node-like receptor protein 3 (NLRP3) inflammasome activation and kidney inflammatory cell infiltrates were all increased in Ybx1ΔPod mice. In vitro, extracellular YBX1 inhibited NLRP3 inflammasome activation in tubular cells. Co-immunoprecipitation, immunohistochemical analyses, microscale cell-free thermophoresis assays, and blunting of the YBX1-mediated TLR4-inhibition by a unique YBX1-derived decapeptide suggests a direct interaction of YBX1 and TLR4. Since YBX1 can be secreted upon post-translational acetylation, we hypothesized that YBX1 secreted from podocytes can inhibit TLR4 signaling in tubular cells. Indeed, mice expressing a non-secreted YBX1 variant specifically in podocytes (Ybx1PodK2A mice) phenocopied Ybx1ΔPod mice, demonstrating a tubular-protective effect of YBX1 secreted from podocytes. Lipopolysaccharide-induced tubular injury was aggravated in Ybx1ΔPod and Ybx1PodK2A mice, indicating a pathophysiological relevance of this glomerular-tubular crosstalk. Thus, our data show that YBX1 is physiologically secreted from podocytes, thereby negatively modulating sterile inflammation in the tubular compartment, apparently by binding to and inhibiting tubular TLR4 signaling. Hence, we have uncovered an YBX1-dependent molecular mechanism of glomerular-tubular crosstalk.

Detecting Protein-Ligand Interactions with Nitroxide Based Paramagnetic Cosolutes.

NMR spectroscopy techniques can provide important information about protein-ligand interactions. Here we tested an NMR approach which relies on the measurement of paramagnetic relaxation enhancements (PREs) arising from analogous cationic, anionic or neutral soluble nitroxide molecules, which distribute around the protein-ligand complex depending on near-surface electrostatic potentials. We applied this approach to two protein-ligand systems, interleukin-8 interacting with highly charged glycosaminoglycans and the SH2 domain of Grb2 interacting with less charged phospho-tyrosine tripeptides. The electrostatic potential around interleukin-8 and its changes upon binding of glycosaminoglycans could be derived from the PRE data and confirmed by theoretical predictions from Poisson-Boltzmann calculations. The ligand influence on the PREs and NMR-derived electrostatic potentials of Grb2 SH2 was localized to a narrow protein region which allowed the localization of the peptide binding pocket. Our analysis suggests that experiments with nitroxide cosolutes can be useful for investigating protein-ligand electrostatic interactions and mapping ligand binding sites.

[Contrast-enhanced ultrasound (CEUS) for characterisation of focal liver lesions]. / Kontrastverstärkte Sonografie (CEUS) zur Diagnostik fokaler Leberläsionen.

Due to the trend towards increased use of imaging and rising awareness among high-risk patients, gastroenterologists and hepatologists are more frequently confronted with patients with focal liver lesions. In the differentiation of these lesions, CT and MRI have increasingly found their way into primary diagnostic steps in everyday clinical practice. Contrast-enhanced sonography, on the other hand, is a very effective and cost-efficient method for assessing focal liver lesions. The success of the method is not only based on the visualisation of microvascularisation in real time. If sonography is performed by the treating physician, he can use the exact knowledge of history and clinical findings to specifically adapt the examination procedure and to interpret the sonographic findings with greater accuracy ("clinical sonography"). At the same time, the method enables the practitioner to combine diagnostics and management decisions in his or her own hands. To achieve excellent results with contrast-enhanced sonography-as with any other imaging method-it is necessary that the examiner is sufficiently qualified.This article systematically presents the sonographic characteristics of the most common liver lesions and clearly shows their contrast patterns using videos (available via QR code). The article illustrates that CEUS could-and from the authors' point of view, should-have an even greater significance in the future.

Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels.

Ion channels play important roles in fundamental biological processes, such as electric signaling in cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion channels with drugs represents a treatment option for neurological and cardiovascular diseases, muscular degradation disorders, and pathologies related to disturbed pain sensation. While there are more than 300 different ion channels in the human organism, drugs have been developed only for some of them and currently available drugs lack selectivity. Computational approaches are an indispensable tool for drug discovery and can speed up, especially, the early development stages of lead identification and optimization. The number of molecular structures of ion channels has considerably increased over the last ten years, providing new opportunities for structure-based drug development. This review summarizes important knowledge about ion channel classification, structure, mechanisms, and pathology with the main focus on recent developments in the field of computer-aided, structure-based drug design on ion channels. We highlight studies that link structural data with modeling and chemoinformatic approaches for the identification and characterization of new molecules targeting ion channels. These approaches hold great potential to advance research on ion channel drugs in the future.

Guiding protein design choices by per-residue energy breakdown analysis with an interactive web application.

Recent developments in machine learning have greatly facilitated the design of proteins with improved properties. However, accurately assessing the contributions of an individual or multiple amino acid mutations to overall protein stability to select the most promising mutants remains a challenge. Knowing the specific types of amino acid interactions that improve energetic stability is crucial for finding favorable combinations of mutations and deciding which mutants to test experimentally. In this work, we present an interactive workflow for assessing the energetic contributions of single and multi-mutant designs of proteins. The energy breakdown guided protein design (ENDURE) workflow includes several key algorithms, including per-residue energy analysis and the sum of interaction energies calculations, which are performed using the Rosetta energy function, as well as a residue depth analysis, which enables tracking the energetic contributions of mutations occurring in different spatial layers of the protein structure. ENDURE is available as a web application that integrates easy-to-read summary reports and interactive visualizations of the automated energy calculations and helps users selecting protein mutants for further experimental characterization. We demonstrate the effectiveness of the tool in identifying the mutations in a designed polyethylene terephthalate (PET)-degrading enzyme that add up to an improved thermodynamic stability. We expect that ENDURE can be a valuable resource for researchers and practitioners working in the field of protein design and optimization. ENDURE is freely available for academic use at: http://endure.kuenzelab.org.

Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection.

G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of Cα-Cα-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications.

Recent Advances in NMR Protein Structure Prediction with ROSETTA.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for studying the structure and dynamics of proteins in their native state. For high-resolution NMR structure determination, the collection of a rich restraint dataset is necessary. This can be difficult to achieve for proteins with high molecular weight or a complex architecture. Computational modeling techniques can complement sparse NMR datasets (<1 restraint per residue) with additional structural information to elucidate protein structures in these difficult cases. The Rosetta software for protein structure modeling and design is used by structural biologists for structure determination tasks in which limited experimental data is available. This review gives an overview of the computational protocols available in the Rosetta framework for modeling protein structures from NMR data. We explain the computational algorithms used for the integration of different NMR data types in Rosetta. We also highlight new developments, including modeling tools for data from paramagnetic NMR and hydrogen-deuterium exchange, as well as chemical shifts in CS-Rosetta. Furthermore, strategies are discussed to complement and improve structure predictions made by the current state-of-the-art AlphaFold2 program using NMR-guided Rosetta modeling.

Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction.

A single experimental method alone often fails to provide the resolution, accuracy, and coverage needed to model integral membrane proteins (IMPs). Integrating computation with experimental data is a powerful approach to supplement missing structural information with atomic detail. We combine RosettaNMR with experimentally-derived paramagnetic NMR restraints to guide membrane protein structure prediction. We demonstrate this approach using the disulfide bond formation protein B (DsbB), an α-helical IMP. Here, we attached a cyclen-based paramagnetic lanthanide tag to an engineered non-canonical amino acid (ncAA) using a copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry reaction. Using this tagging strategy, we collected 203 backbone HN pseudocontact shifts (PCSs) for three different labeling sites and used these as input to guide de novo membrane protein structure prediction protocols in Rosetta. We find that this sparse PCS dataset combined with 44 long-range NOEs as restraints in our calculations improves structure prediction of DsbB by enhancements in model accuracy, sampling, and scoring. The inclusion of this PCS dataset improved the Cα-RMSD transmembrane segment values of the best-scoring and best-RMSD models from 9.57 Å and 3.06 Å (no NMR data) to 5.73 Å and 2.18 Å, respectively.

Structure and function of the metagenomic plastic-degrading polyester hydrolase PHL7 bound to its product.

The recently discovered metagenomic-derived polyester hydrolase PHL7 is able to efficiently degrade amorphous polyethylene terephthalate (PET) in post-consumer plastic waste. We present the cocrystal structure of this hydrolase with its hydrolysis product terephthalic acid and elucidate the influence of 17 single mutations on the PET-hydrolytic activity and thermal stability of PHL7. The substrate-binding mode of terephthalic acid is similar to that of the thermophilic polyester hydrolase LCC and deviates from the mesophilic IsPETase. The subsite I modifications L93F and Q95Y, derived from LCC, increased the thermal stability, while exchange of H185S, derived from IsPETase, reduced the stability of PHL7. The subsite II residue H130 is suggested to represent an adaptation for high thermal stability, whereas L210 emerged as the main contributor to the observed high PET-hydrolytic activity. Variant L210T showed significantly higher activity, achieving a degradation rate of 20 µm h-1 with amorphous PET films.

Targeting biased signaling by PAR1: function and molecular mechanism of parmodulins.

The G protein-coupled receptor (GPCR) protease-activated receptor 1 (PAR1) is a therapeutic target that was originally pursued with the aim of restricting platelet activation and the burden of cardiovascular diseases. In clinical studies, the use of orthosteric PAR1 inhibitors was associated with an increased risk of hemorrhage, including intracranial hemorrhage. Because (1) PAR1 is expressed by various cell types, including endothelial cells, (2) conveys in mice a physiological indispensable function for vascular development during embryogenesis, and (3) is subject to biased signaling dependent on the activating proteases, orthosteric PAR1 inhibition may be associated with unwanted side effects. Alternatively, the protease-activated protein C (aPC) and its variants can promote valuable anti-inflammatory signaling via PAR1. Most recently, small molecule allosteric modulators of PAR1 signaling, called parmodulins, have been developed. Parmodulins inhibit coagulation and platelet activation yet maintain cytoprotective effects typically provoked by PAR1 signaling upon the activation by aPC. In this study, we review the discovery of parmodulins and their preclinical data, summarize the current knowledge about their mode of action, and compare the structural interaction of parmodulin and PAR1 with that of other intracellularly binding allosteric GPCR modulators. Thus, we highlight the pharmaceutical potential and challenges associated with the future development of parmodulins.

Structural basis of the activation of PPARγ by the plasticizer metabolites MEHP and MINCH.

Di-2-ethylhexyl phthalate (DEHP) and its substitute 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH) are widely used as plasticizers but may have adverse health effects. Via hydrolysis of one of the two ester bonds in the human body, DEHP and DINCH form the monoesters MEHP and MINCH, respectively. Previous studies demonstrated binding of these metabolites to PPARγ and the induction of adipogenesis via this pathway. Detailed structural understanding of how these metabolites interact with PPARγ and thereby affect human health is lacking until now. We therefore characterized the binding modes of MINCH and MEHP to the ligand binding domain of PPARγ by X-ray crystallography and molecular dynamics (MD) simulations. Both compounds bind to the activating function-2 (AF-2) binding site via an interaction of the free carboxylates with the histidines 323 and 449, tyrosine 473 and serine 289. The alkyl chains form hydrophobic interactions with the tunnel next to cysteine 285. These binding modes are generally stable as demonstrated by the MD simulations and they resemble the complexation of fatty acids and their metabolites to the AF-2 site of PPARγ. Similar to the situation for these natural PPARγ agonists, the interaction of the free carboxylate groups of MEHP and MINCH with tyrosine 473 and surrounding residues stabilizes the AF-2 helix in the upward conformation. This state promotes binding of coactivator proteins and thus formation of the active complex for transcription of the specific target genes. Moreover, a comparison of the residues involved in binding of the plasticizer metabolites in vertebrate PPARγ orthologs shows that these compounds likely have similar effects in other species.

Targeting ion channels with ultra-large library screening for hit discovery.

Ion channels play a crucial role in a variety of physiological and pathological processes, making them attractive targets for drug development in diseases such as diabetes, epilepsy, hypertension, cancer, and chronic pain. Despite the importance of ion channels in drug discovery, the vastness of chemical space and the complexity of ion channels pose significant challenges for identifying drug candidates. The use of in silico methods in drug discovery has dramatically reduced the time and cost of drug development and has the potential to revolutionize the field of medicine. Recent advances in computer hardware and software have enabled the screening of ultra-large compound libraries. Integration of different methods at various scales and dimensions is becoming an inevitable trend in drug development. In this review, we provide an overview of current state-of-the-art computational chemistry methodologies for ultra-large compound library screening and their application to ion channel drug discovery research. We discuss the advantages and limitations of various in silico techniques, including virtual screening, molecular mechanics/dynamics simulations, and machine learning-based approaches. We also highlight several successful applications of computational chemistry methodologies in ion channel drug discovery and provide insights into future directions and challenges in this field.

Molecular Simulations Reveal Distinct Energetic and Kinetic Binding Properties of [18F]PI-2620 on Tau Filaments from 3R/4R and 4R Tauopathies.

Tauopathies are a class of neurodegenerative disorders characterized by the accumulation of tau protein filaments in the brain. On the basis of isoforms with three or four microtubule-binding repeats (3R or 4R) that constitute tau filaments, tauopathies can be divided into 3R, 4R, and 3R/4R tauopathies. [18F]PI-2620 is a tau-positron emission tomography (PET) tracer that detects tau filaments in the 3R/4R tauopathy Alzheimer's disease (AD) and the 4R tauopathies corticobasal degeneration (CBD) and progressive supranuclear palsy (PSP) with differential binding characteristics. A multiscale simulation workflow, including molecular docking, molecular dynamics simulation, metadynamics, and Brownian dynamics, was applied to uncover the molecular basis for the different binding properties of [18F]PI-2620 in these tauopathies. The energetically best binding sites of [18F]PI-2620 in the AD-tau filament are located in the C-shaped groove of the filament core structure that is accessible to the outside. The most favorable binding sites in CBD-tau and PSP-tau filaments are localized to cavities in the inner filament core. Sites on the outer surface have higher binding free energies, and interaction of [18F]PI-2620 at these sites was short-lived in the molecular dynamics simulations. Computationally predicted associated rates of [18F]PI-2620 with the groove sites in the AD-tau filament were higher than association rates with the cavity sites in the CBD- and PSP-tau filaments. The results indicate that tau filaments in AD combine favorable energetic and kinetic properties with regard to tracer binding, while the binding of [18F]PI-2620 to filaments in CBD and PSP is kinetically restricted. Our findings reveal that distinct structural, energetic, and kinetic properties of tau filaments from AD, CBD, and PSP govern their interaction with PET tracers, which highlights the possibility to achieve tau isoform specificity in future tracer developments.

Paramagnetic spin labeling of a bacterial DnaB helicase for solid-state NMR.

Labeling of biomolecules with a paramagnetic probe for nuclear magnetic resonance (NMR) spectroscopy enables determining long-range distance restraints, which are otherwise not accessible by classically used dipolar coupling-based NMR approaches. Distance restraints derived from paramagnetic relaxation enhancements (PREs) can facilitate the structure determination of large proteins and protein complexes. We herein present the site-directed labeling of the large oligomeric bacterial DnaB helicase from Helicobacter pylori with cysteine-reactive maleimide tags carrying either a nitroxide radical or a lanthanide ion. The success of the labeling reaction was followed by quantitative continuous-wave electron paramagnetic resonance (EPR) experiments performed on the nitroxide-labeled protein. PREs were extracted site-specifically from 2D and 3D solid-state NMR spectra. A good agreement with predicted PRE values, derived by computational modeling of nitroxide and Gd3+ tags in the low-resolution DnaB crystal structure, was found. Comparison of experimental PREs and model-predicted spin label-nucleus distances indicated that the size of the "blind sphere" around the paramagnetic center, in which NMR resonances are not detected, is slightly larger for Gd3+ (∼14 Å) than for nitroxide (∼11 Å) in 13C-detected 2D spectra of DnaB. We also present Gd3+-Gd3+ dipolar electron-electron resonance EPR experiments on DnaB supporting the conclusion that DnaB was present as a hexameric assembly.

Investigation of the structure of regulatory proteins interacting with glycosaminoglycans by combining NMR spectroscopy and molecular modeling - the beginning of a wonderful friendship.

The interaction of regulatory proteins with extracellular matrix or cell surface-anchored glycosaminoglycans (GAGs) plays important roles in molecular recognition, wound healing, growth, inflammation and many other processes. In spite of their high biological relevance, protein-GAG complexes are significantly underrepresented in structural databases because standard tools for structure determination experience difficulties in studying these complexes. Co-crystallization with subsequent X-ray analysis is hampered by the high flexibility of GAGs. NMR spectroscopy experiences difficulties related to the periodic nature of the GAGs and the sparse proton network between protein and GAG with distances that typically exceed the detection limit of nuclear Overhauser enhancement spectroscopy. In contrast, computer modeling tools have advanced over the last years delivering specific protein-GAG docking approaches successfully complemented with molecular dynamics (MD)-based analysis. Especially the combination of NMR spectroscopy in solution providing sparse structural constraints with molecular docking and MD simulations represents a useful synergy of forces to describe the structure of protein-GAG complexes. Here we review recent methodological progress in this field and bring up examples where the combination of new NMR methods along with cutting-edge modeling has yielded detailed structural information on complexes of highly relevant cytokines with GAGs.

Contrast-Enhanced Ultrasound Algorithms (CEUS-LIRADS/ESCULAP) for the Noninvasive Diagnosis of Hepatocellular Carcinoma - A Prospective Multicenter DEGUM Study.

BACKGROUND: This prospective multicenter study funded by the DEGUM assesses the diagnostic accuracy of standardized contrast-enhanced ultrasound (CEUS) for the noninvasive diagnosis of hepatocellular carcinoma (HCC) in high-risk patients. METHODS: Patients at high risk for HCC with a histologically proven focal liver lesion on B-mode ultrasound were recruited prospectively in a multicenter approach. Clinical and imaging data were entered via online entry forms. The diagnostic accuracies for the noninvasive diagnosis of HCC were compared for the conventional interpretation of standardized CEUS at the time of the examination (= CEUS on-site) and the two CEUS algorithms ESCULAP (Erlanger Synopsis for Contrast-enhanced Ultrasound for Liver lesion Assessment in Patients at risk) and CEUS LI-RADS (Contrast-Enhanced UltraSound Liver Imaging Reporting and Data System). RESULTS: 321 patients were recruited in 43 centers; 299 (93.1 %) had liver cirrhosis. The diagnosis according to histology was HCC in 256 cases, and intrahepatic cholangiocarcinoma (iCCA) in 23 cases. In the subgroup of cirrhotic patients (n = 299), the highest sensitivity for the diagnosis of HCC was achieved with the CEUS algorithm ESCULAP (94.2 %) and CEUS on-site (90.9 %). The lowest sensitivity was reached with the CEUS LI-RADS algorithm (64 %; p < 0.001). However, the specificity of CEUS LI-RADS (78.9 %) was superior to that of ESCULAP (50.9 %) and CEUS on-site (64.9 %; p < 0.001). At the same time, the negative predictive value (NPV) of CEUS LI-RADS was significantly inferior to that of ESCULAP (34.1 % vs. 67.4 %; p < 0.001) and CEUS on-site (62.7 %; p < 0.001). The positive predictive values of all modalities were high (around 90 %), with the best results seen for CEUS LI-RADS and CEUS on-site. CONCLUSION: This is the first multicenter, prospective comparison of standardized CEUS and the recently developed CEUS-based algorithms in histologically proven liver lesions in cirrhotic patients. Our results reaffirm the excellent diagnostic accuracy of CEUS for the noninvasive diagnosis of HCC in high-risk patients. However, on-site diagnosis by an experienced examiner achieves an almost equal diagnostic accuracy compared to CEUS-based diagnostic algorithms.

Clinical Ultrasound in Inflammatory Bowel Disease.

Ultrasound should be the first-line imaging method in the medical care of patients with inflammatory bowel disease. It can be used to differentiate between Crohn's disease and ulcerative colitis and to detect numerous complications like stenoses, fistulas, and abscesses. As the method is also highly suitable for follow-up, stressful endoscopic procedures and examinations involving radiation are less necessary. Comparison studies with MRI and CT show that ultrasound is not an inferior method and it is therefore included in all guidelines. Intensifying physician training in this method will help to ensure its comprehensive use.