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Canine distemper virus (CDV) is an enveloped RNA morbillivirus that triggers respiratory, enteric, and high incidence of severe neurological disorders. CDV induces devastating outbreaks in wild and endangered animals as well as in domestic dogs in countries associated with suboptimal vaccination programs. The receptor-binding tetrameric attachment (H)-protein is part of the morbilliviral cell entry machinery. Here, we present the cryo-electron microscopy (cryo-EM) structure and supramolecular organization of the tetrameric CDV H-protein ectodomain. The structure reveals that the morbilliviral H-protein is composed of three main domains: stalk, neck, and heads. The most unexpected feature was the inherent asymmetric architecture of the CDV H-tetramer being shaped by the neck, which folds into an almost 90° bent conformation with respect to the stalk. Consequently, two non-contacting receptor-binding H-head dimers, which are also tilted toward each other, are located on one side of an intertwined four helical bundle stalk domain. Positioning of the four protomer polypeptide chains within the neck domain is guided by a glycine residue (G158), which forms a hinge point exclusively in two protomer polypeptide chains. Molecular dynamics simulations validated the stability of the asymmetric structure under near physiological conditions and molecular docking showed that two receptor-binding sites are fully accessible. Thus, this spatial organization of the CDV H-tetramer would allow for concomitant protein interactions with the stalk and head domains without steric clashes. In summary, the structure of the CDV H-protein ectodomain provides new insights into the morbilliviral cell entry system and offers a blueprint for next-generation structure-based antiviral drug discovery.

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI.

For many decades, the clinical unmet needs of primary Sjögren's Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-art data analytics services to address the pSS clinical unmet needs, including the development of lymphoma classification models and the identification of biomarkers for lymphomagenesis. The users of the platform have been able to successfully interlink, curate, and harmonize 21 regional, national, and international European cohorts of 7,551 pSS patients with respect to the ethical and legal issues for data sharing. Federated AI algorithms were trained across the harmonized databases, with reduced execution time complexity, yielding robust lymphoma classification models with 85% accuracy, 81.25% sensitivity, 85.4% specificity along with 5 biomarkers for lymphoma development. To our knowledge, this is the first GDPR compliant platform that provides federated AI services to address the pSS clinical unmet needs. © 2022 The Author(s)

During the preceding decades, human gait analysis has been the center of attention for the scientific community, while the association between gait analysis and overall health monitoring has been extensively reported. Technological advances further assisted in this alignment, resulting in access to inexpensive and remote healthcare services. Various assessment tools, such as software platforms and mobile applications, have been proposed by the scientific community and the market that employ sensors to monitor human gait for various purposes ranging from biomechanics to the progression of functional recovery. The framework presented herein offers a valuable digital biomarker for diagnosing and monitoring Parkinson's disease that can help clinical experts in the decision-making process leading to corrective planning or patient-specific treatment. More accurate and reliable decisions can be provided through a wide variety of integrated Artificial Intelligence algorithms and straightforward visualization techniques, including, but not limited to, heatmaps and bar plots. The framework consists of three core components: the insole pair, the mobile application, and the cloud-based platform. The insole pair deploys 16 plantar pressure sensors, an accelerometer, and a gyroscope to acquire gait data. The mobile application formulates the data for the cloud platform, which orchestrates the component interaction through the web application. Utilizing open communication protocols enables the straightforward replacement of one of the core components with a relative one (e.g., a different model of insoles), transparently from the end user, without affecting the overall architecture, resulting in a framework with the flexibility to adjust its modularity., Comment: 8 pages, 9 figures

Multiple enveloped RNA viruses of the family Paramyxoviridae and Pneumoviridae, like measles virus (MeV), Nipah virus (NiV), canine distemper virus (CDV), or respiratory syncytial virus (RSV), are of high clinical relevance. Each year a huge number of lives are lost as a result of these viral infections. Worldwide, MeV infection alone is responsible for over a hundred thousand deaths each year despite available vaccine. Therefore, there is an urgent need for treatment options to counteract these viral infections. The development of antiviral drugs in general stands as a huge challenge due to the rapid emergence of viral escape mutants. Here, we disclose the discovery of a small-molecule antiviral, compound 1 (ZHAWOC9045), active against several pneumo-/paramyxoviruses, including MeV, NiV, CDV, RSV, and parainfluenza virus type 5 (PIV-5). A series of mechanistic characterizations revealed that compound 1 targets a host factor which is indispensable for viral genome replication. Drug resistance profiling against a paramyxovirus model (CDV) demonstrated no detectable adaptation despite prolonged time of investigation, thereby mitigating the rapid emergence of escape variants. Furthermore, a thorough structure-activity relationship analysis of compound 1 led to the invention of 100-times-more potent-derivatives, e.g., compound 2 (ZHAWOC21026). Collectively, we present in this study an attractive host-directed pneumoviral/paramyxoviral replication inhibitor with potential therapeutic application. IMPORTANCE Measles virus, respiratory syncytial virus, canine distemper virus, and Nipah virus are some of the clinically significant RNA viruses that threaten substantial number of lives each year. Limited to no availability of treatment options for these viral infections makes it arduous to handle the outbreaks. This highlights the major importance of developing antivirals to fight not only ongoing infections but also potential future epidemics. Most of the discovered antivira

info:eu-repo/semantics/published

Background: Machine learning (ML) and artificial intelligence are emerging as important components of precision medicine that enhance diagnosis and risk stratification. Risk stratification tools for hypertrophic cardiomyopathy (HCM) exist, but they are based on traditional statistical methods. The aim was to develop a novel machine learning risk stratification tool for the prediction of 5-year risk in HCM. The goal was to determine if its predictive accuracy is higher than the accuracy of the state-of-the-art tools. Method: Data from a total of 2302 patients were used. The data were comprised of demographic characteristics, genetic data, clinical investigations, medications, and disease-related events. Four classification models were applied to model the risk level, and their decisions were explained using the SHAP (SHapley Additive exPlanations) method. Unwanted cardiac events were defined as sustained ventricular tachycardia occurrence (VT), heart failure (HF), ICD activation, sudden cardiac death (SCD), cardiac death, and all-cause death. Results: The proposed machine learning approach outperformed the similar existing risk-stratification models for SCD, cardiac death, and all-cause death risk-stratification: it achieved higher AUC by 17%, 9%, and 1%, respectively. The boosted trees achieved the best performing AUC of 0.82. The resulting model most accurately predicts VT, HF, and ICD with AUCs of 0.90, 0.88, and 0.87, respectively. Conclusions: The proposed risk-stratification model demonstrates high accuracy in predicting events in patients with hypertrophic cardiomyopathy. The use of a machine-learning risk stratification model may improve patient management, clinical practice, and outcomes in general.

Canine distemper virus (CDV), a close relative of the human pathogen measles virus (MeV), is an enveloped, negative sense RNA virus that belongs to the genus Morbillivirus and causes severe diseases in dogs and other carnivores. Although the vaccination is available as a preventive measure against the disease, the occasional vaccination failure highlights the importance of therapeutic alternatives such as antivirals against CDV. The morbilliviral cell entry system relies on two interacting envelope glycoproteins: the attachment (H) and fusion (F) proteins. Here, to potentially discover novel entry inhibitors targeting CDV H, F and/or the cognate receptor: signaling lymphocyte activation molecule (SLAM) proteins, we designed a quantitative cell-based fusion assay that matched high-throughput screening (HTS) settings. By screening two libraries of small molecule compounds, we successfully identified two membrane fusion inhibitors (F2736-3056 and F2261-0043). Although both inhibitors exhibited similarities in structure and potency with the small molecule compound 3G (an AS-48 class morbilliviral F-protein inhibitor), F2736-3056 displayed improved efficacy in blocking fusion activity when a 3G-escape variant was employed. Altogether, we present a cell-based fusion assay that can be utilized not only to discover antiviral agents against CDV but also to dissect the mechanism of morbilliviral-mediated cell-binding and cell-to-cell fusion activity.

Measles virus (MeV) and canine distemper virus (CDV), two members of the Morbillivirus genus, are still causing important global diseases of humans and animals, respectively. To enter target cells, morbilliviruses rely on an envelope-anchored machinery, which is composed of two interacting glycoproteins: a tetrameric receptor binding (H) protein and a trimeric fusion (F) protein. To execute membrane fusion, the F protein initially adopts a metastable, prefusion state that refolds into a highly stable postfusion conformation as the result of a finely coordinated activation process mediated by the H protein. Here, we employed cryo-electron microscopy (cryo-EM) and single particle reconstruction to elucidate the structure of the prefusion state of the CDV F protein ectodomain (solF) at 4.3 Å resolution. Stabilization of the prefusion solF trimer was achieved by fusing the GCNt trimerization sequence at the C-terminal protein region, and expressing and purifying the recombinant protein in the presence of a morbilliviral fusion inhibitor class compound. The three-dimensional cryo-EM map of prefusion CDV solF in complex with the inhibitor clearly shows density for the ligand at the protein binding site suggesting common mechanisms of membrane fusion activation and inhibition employed by different morbillivirus members.

Morbilliviruses (e.g. measles virus [MeV] or canine distemper virus [CDV]) employ the attachment (H) and fusion (F) envelope glycoproteins for cell entry. H protein engagement to a cognate receptor eventually leads to F-triggering. Upon activation, F proteins transit from a prefusion to a postfusion conformation; a refolding process that is associated with membrane merging. Small-molecule morbilliviral fusion inhibitors such as the compound 3G (a chemical analog in the AS-48 class) were previously generated and mechanistic studies revealed a stabilizing effect on morbilliviral prefusion F trimers. Here, we aimed at designing 3G-resistant CDV F mutants by introducing single cysteine residues at hydrophobic core positions of the helical stalk region. Covalently-linked F dimers were generated, which highlighted substantial conformational flexibility within the stalk to achieve those irregular F conformations. Our findings demonstrate that "top-stalk" CDV F cysteine mutants (F-V571C and F-L575C) remained functional and gained resistance to 3G. Conversely, although not all "bottom-stalk" F cysteine variants preserved proper bioactivity, those that remained functional exhibited 3G-sensitivity. According to the recently determined prefusion MeV F trimer/AS-48 co-crystal structure, CDV residues F-V571 and F-L575 may directly interact with 3G. A combination of conformation-specific anti-F antibodies and low-resolution electron microscopy structural analyses confirmed that 3G lost its stabilizing effect on "top-stalk" F cysteine mutants thus suggesting a primary resistance mechanism. Overall, our data suggest that the fusion inhibitor 3G stabilizes prefusion CDV F trimers by docking at the top of the stalk domain.

Intravascular ultrasound (IVUS) imaging offers accurate cross-sectional vessel information. To this end, registering temporal IVUS pullbacks acquired at two time points can assist the clinicians to accurately assess pathophysiological changes in the vessels, disease progression and the effect of the treatment intervention. In this paper, we present a novel two-stage registration framework for aligning pairs of longitudinal and axial IVUS pullbacks. Initially, we use a Dynamic Time Warping (DTW)-based algorithm to align the pullbacks in a temporal fashion. Subsequently, an intensity-based registration method, that utilizes a variant of the Harmony Search optimizer to register each matched pair of the pullbacks by maximizing their Mutual Information, is applied. The presented method is fully automated and only required two single global image-based measurements, unlike other methods that require extraction of morphology-based features. The data used includes 42 synthetically generated pullback pairs, achieving an alignment error of 0.1853 frames per pullback, a rotation error 0.93° and a translation error of 0.0161 mm. In addition, it was also tested on 11 baseline and follow-up, and 10 baseline and post-stent deployment real IVUS pullback pairs from two clinical centres, achieving an alignment error of 4.3±3.9 for the longitudinal registration, and a distance and a rotational error of 0.56±0.323 mm and 12.4°±10.5°, respectively, for the axial registration. Although the performance of the proposed method does not match that of the state-of-the-art, our method relies on computationally lighter steps for its computations, which is crucial in real-time applications. On the other hand, the proposed method performs even or better that the state-of-the-art when considering the axial registration. The results indicate that the proposed method can support clinical decision making and diagnosis based on sequential imaging examinations.

Objective. The objective of this work is to present a Training Tool designed to support healthcare professionals involved in the diagnosis and management of Sjögren's syndrome. Methods. The Training Tool aims to fulfil the gap of targeted education by providing a structured protocol of training including state of the art guidelines and practices. For the development of the Training Tool, latest relevant technologies have been used to assure efficiency and usability. Core functionalities include training by a series of multimedia courses, testing during the learning process, and profiling for monitoring the progress. An iterative requirement analysis process was established involving a large number of clinical experts, with the objective to identify user's training needs. Results. Comprehensive usability evaluation was performed by applying, an Unmoderated Remote Usability Test resulting to 97.2% Success Rate; and the well-established System Usability Scale, reaching a score of 90.4 which classifies the Training Tool as "A"gradedexcellent. Conclusion. The Training Tool offers open-online training of healthcare professionals involved in the diagnosis and management of Sjögren's syndrome, using a well-designed training protocol in highly usable manner. To our knowledge, this is the first such tool for Sjögren's syndrome., SCOPUS: ar.j, info:eu-repo/semantics/published

Prostate segmentation from magnetic resonance imaging (MRI) is a challenging task. In recent years, several network architectures have been proposed to automate this process and alleviate the burden of manual annotation. Although the performance of these models has achieved promising results, there is still room for improvement before these models can be used safely and effectively in clinical practice. One of the major challenges in prostate MR image segmentation is the presence of class imbalance in the image labels where the background pixels dominate over the prostate. In the present work we propose a DL-based pipeline for cropping the region around the prostate from MRI images to produce a more balanced distribution of the foreground pixels (prostate) and the background pixels and improve segmentation accuracy. The effect of DL-cropping for improving the segmentation performance compared to standard center-cropping is assessed using five popular DL networks for prostate segmentation, namely U-net, U-net+, Res Unet++, Bridge U-net and Dense U-net. The proposed smart-cropping outperformed the standard center cropping in terms of segmentation accuracy for all the evaluated prostate segmentation networks. In terms of Dice score, the highest improvement was achieved for the U-net+ and ResU-net++ architectures corresponding to 8.9% and 8%, respectively., Comment: 8 pages, 6 figures, 1 table

Background Advances in three-dimensional reconstruction techniques and computational fluid dynamics of coronary CT angiography (CCTA) data sets make feasible evaluation of endothelial shear stress (ESS) in the vessel wall. Purpose To investigate the relationship between CCTA-derived computational fluid dynamics metrics, anatomic and morphologic characteristics of coronary lesions, and their comparative performance in predicting impaired coronary vasodilating capability assessed by using PET myocardial perfusion imaging (MPI). Materials and Methods In this retrospective study, conducted between October 2019 and September 2020, coronary vessels in patients with stable chest pain and with intermediate probability of coronary artery disease who underwent both CCTA and PET MPI with oxygen 15-labeled water or nitrogen 13 ammonia and quantification of myocardial blood flow were analyzed. CCTA images were used in assessing stenosis severity, lesion-specific total plaque volume (PV), noncalcified PV, calcified PV, and plaque phenotype. PET MPI was used in assessing significant coronary stenosis. The predictive performance of the CCTA-derived parameters was evaluated by using area under the receiver operating characteristic curve (AUC) analysis. Results There were 92 coronary vessels evaluated in 53 patients (mean age, 65 years ± 7; 31 men). ESS was higher in lesions with greater than 50% stenosis versus those without significant stenosis (mean, 15.1 Pa ± 30 vs 4.6 Pa ± 4 vs 3.3 Pa ± 3; P = .004). ESS was higher in functionally significant versus nonsignificant lesions (median, 7 Pa [interquartile range, 5-23 Pa] vs 2.6 Pa [interquartile range, 1.8-5 Pa], respectively; P ≤ .001). Adding ESS to stenosis severity improved prediction (change in AUC, 0.10; 95% CI: 0.04, 0.17; P = .002) for functionally significant lesions. Conclusion The combination of endothelial shear stress with coronary CT angiography (CCTA) stenosis severity improved prediction of an abnormal PET myocardial

The green-light absorbing proteorhodopsin (GPR) is the archetype of bacterial light-driven proton pumps. Here, we present the 2.9 Å cryo-EM structure of pentameric GPR, resolving important residues of the proton translocation pathway and the oligomerization interface. Superposition with the structure of a close GPR homolog and molecular dynamics simulations reveal conformational variations, which regulate the solvent access to the intra- and extracellular half channels harbouring the primary proton donor E109 and the proposed proton release group E143. We provide a mechanism for the structural rearrangements allowing hydration of the intracellular half channel, which are triggered by changing the protonation state of E109. Functional characterization of selected mutants demonstrates the importance of the molecular organization around E109 and E143 for GPR activity. Furthermore, we present evidence that helices involved in the stabilization of the protomer interfaces serve as scaffolds for facilitating the motion of the other helices. Combined with the more constrained dynamics of the pentamer compared to the monomer, these observations illustrate the previously demonstrated functional significance of GPR oligomerization. Overall, this work provides molecular insights into the structure, dynamics and function of the proteorhodopsin family that will benefit the large scientific community employing GPR as a model protein.

The scope of this paper is to present a new carotid vessel segmentation algorithm implementing the U-net based convolutional neural network architecture. With carotid atherosclerosis being the major cause of stroke in Europe, new methods that can provide more accurate image segmentation of the carotid arterial tree and plaque tissue can help improve early diagnosis, prevention and treatment of carotid disease. Herein, we present a novel methodology combining the U-net model and morphological active contours in an iterative framework that accurately segments the carotid lumen and outer wall. The method automatically produces a 3D meshed model of the carotid bifurcation and smaller branches, using multispectral MR image series obtained from two clinical centres of the TAXINOMISIS study. As indicated by a validation study, the algorithm succeeds high accuracy (99.1% for lumen area and 92.6% for the perimeter) for lumen segmentation. The proposed algorithm will be used in the TAXINOMISIS study to obtain more accurate 3D vessel models for improved computational fluid dynamics simulations and the development of models of atherosclerotic plaque progression.

Bone healing process is a complicated phenomenon regulated by biochemical and mechanical signals. Experimental studies have shown that ultrasound (US) accelerates bone ossification and has a multiple influence on cell differentiation and angiogenesis. In a recent work of the authors, a bioregulatory model for providing bone-healing predictions was addressed, taking into account for the first time the salutary effect of US on the involved angiogenesis. In the present work, a mechanobioregulatory model of bone solidification under the US presence incorporating also the mechanical environment on the regeneration process, which is known to affect cellular processes, is presented. An iterative procedure is adopted, where the finite element method is employed to compute the mechanical stimuli at the linear elastic phases of the poroelastic callus region and a coupled system of partial differential equations to simulate the enhancement by the US cell angiogenesis process and thus the oxygen concentration in the fractured area. Numerical simulations with and without the presence of US that illustrate the influence of progenitor cells' origin in the healing pattern and the healing rate and simultaneously demonstrate the salutary effect of US on bone repair are presented and discussed.

Pichia pastoris, a methylotrophic yeast, is an established system for the production of heterologous proteins, particularly biopharmaceuticals and industrial enzymes. To maximise and optimise the production of recombinant products, recent molecular research has focused on numerous issues including the design of expression vectors, optimisation of gene copy number, co-expression of secretory proteins such as chaperones, engineering of glycosylation and secretory pathways, etc. However, the physiological effects of different cultivation strategies are often difficult to separate from the molecular effects of the gene construct (e.g., cellular stress through over-expression or incorrect post-translational processing). Hence, overall system optimisation is difficult, even though it is urgently required in order to describe and understand the behaviour of new molecular constructs. This review focuses on particular aspects of recombinant protein production related to variations in biomass growth and their implications for strain design and screening, as well as on the concept of rational comparisons between cultivation systems for the development of specific production processes in bioreactors. The relationship between specific formation rates of secreted recombinant proteins, qp, and specific growth rates, μ, has been analysed in a conceptual attempt to compare different systems, particularly those based on AOX1/methanol and GAP/glucose, and this has now evolved into a pivotal concept for bioprocess engineering of P. pastoris.

Bone healing is a complex biological procedure in which several cellular actions, directed by biochemical and mechanical signals, take place. Experimental studies have shown that ultrasound accelerates bone ossification and has a multiple influence on angiogenesis. In this study a mathematical model predicting bone healing under the presence of ultrasound is demonstrated. The primary objective is to account for the ultrasound effect on angiogenesis and more specifically on the transport of the Vascular Endothelial Growth Factor (VEGF). Partial differential equations describing the spatiotemporal evolution of cells, growth factors, tissues and ultrasound acoustic pressure and velocity equations determining the development of the blood vessel network constitute the present model. The effect of the ultrasound characteristics on angiogenesis and bone healing is investigated by applying different boundary conditions of acoustic pressure at the periosteal region of the bone model, which correspond to different intensity values. The results made clear that ultrasound enhances angiogenesis mechanisms during bone healing. The proposed model could be regarded as a step towards the monitoring of the effect of ultrasound on bone regeneration.

The L-type amino acid transporter 1 (LAT1, SLC7A5) transports essential amino acids across the blood-brain barrier (BBB) and into cancer cells. To utilize LAT1 for drug delivery, potent amino acid promoieties are desired, as prodrugs must compete with millimolar concentrations of endogenous amino acids. To better understand ligand-transporter interactions that could improve potency, we developed structural LAT1 models to guide the design of substituted analogues of phenylalanine and histidine. Furthermore, we evaluated the structure-activity relationship (SAR) for both enantiomers of naturally occurring LAT1 substrates. Analogues were tested in cis-inhibition and trans-stimulation cell assays to determine potency and uptake rate. Surprisingly, LAT1 can transport amino acid-like substrates with wide-ranging polarities including those containing ionizable substituents. Additionally, the rate of LAT1 transport was generally nonstereoselective even though enantiomers likely exhibit different binding modes. Our findings have broad implications to the development of new treatments for brain disorders and cancer.

High-resolution microscopy techniques provide a plethora of information on biological structures from the cellular level down to the molecular level. In this review, we present the unique capabilities of transmission electron and atomic force microscopy to assess the structure, oligomeric state, function and dynamics of channel and transport proteins in their native environment, the lipid bilayer. Most importantly, membrane proteins can be visualized in the frozen-hydrated state and in buffer solution by cryo-transmission electron and atomic force microscopy, respectively. We also illustrate the potential of the scintillation proximity assay to study substrate binding of detergent-solubilized transporters prior to crystallization and structural characterization

Single-molecule force spectroscopy (SMFS) provides detailed insight into the mechanical (un)folding pathways and structural stability of membrane proteins. So far, SMFS could only be applied to membrane proteins embedded in native or synthetic membranes adsorbed to solid supports. This adsorption causes experimental limitations and raises the question to what extent the support influences the results obtained by SMFS. Therefore, we introduce here SMFS from native purple membrane freely spanning across nanopores. We show that correct analysis of the SMFS data requires extending the worm-like chain model, which describes the mechanical stretching of a polypeptide, by the cubic extension model, which describes the bending of a purple membrane exposed to mechanical stress. This new experimental and theoretical approach allows to characterize the stepwise (un)folding of the membrane protein bacteriorhodopsin and to assign the stability of single and grouped secondary structures. The (un)folding and stability of bacteriorhodopsin shows no significant difference between freely spanning and directly supported purple membranes. Importantly, the novel experimental SMFS setup opens an avenue to characterize any protein from freely spanning cellular or synthetic membranes.

Pressure measurements using finite element computations without the need of a wire could be valuable in clinical practice. Our aim was to compare the computed distal coronary pressure values with the measured values using a pressure wire, while testing the effect of different boundary conditions for the simulation. Eight coronary arteries (lumen and outer vessel wall) from six patients were reconstructed in three-dimensional (3D) space using intravascular ultrasound and biplane angiographic images. Pressure values at the distal and proximal end of the vessel and flow velocity values at the distal end were acquired with the use of a combo pressure-flow wire. The 3D lumen and wall models were discretized into finite elements; fluid structure interaction (FSI) and rigid wall simulations were performed for one cardiac cycle both with pulsatile and steady flow in separate simulations. The results showed a high correlation between the measured and the computed coronary pressure values (coefficient of determination [r[superscript 2]] ranging between 0.8902 and 0.9961), while the less demanding simulations using steady flow and rigid walls resulted in very small relative error. Our study demonstrates that computational assessment of coronary pressure is feasible and seems to be accurate compared to the wire-based measurements., European Union. European Regional Development Fund

Heteromeric amino acid transporters (HATs) are the unique example, known in all kingdoms of life, of solute transporters composed of two subunits linked by a conserved disulfide bridge. In metazoans, the heavy subunit is responsible for the trafficking of the heterodimer to the plasma membrane, and the light subunit is the transporter. HATs are involved in human pathologies such as amino acidurias, tumor growth and invasion, viral infection and cocaine addiction. However structural information about interactions between the heavy and light subunits of HATs is scarce. In this work, transmission electron microscopy and single-particle analysis of purified human 4F2hc/L-type amino acid transporter 2 (LAT2) heterodimers overexpressed in the yeast Pichia pastoris, together with docking analysis and crosslinking experiments, reveal that the extracellular domain of 4F2hc interacts with LAT2, almost completely covering the extracellular face of the transporter. 4F2hc increases the stability of the light subunit LAT2 in detergent-solubilized Pichia membranes, allowing functional reconstitution of the heterodimer into proteoliposomes. Moreover, the extracellular domain of 4F2hc suffices to stabilize solubilized LAT2. The interaction of 4F2hc with LAT2 gives insights into the structural bases for light subunit recognition and the stabilizing role of the ancillary protein in HATs., This work was supported by Spanish Ministry of Science and Innovation Grants BIO2010-22324 (to J.F.-R.) and SAF2012- 40080-C02-01, European Commission Frame Program 7 Grant 201924 (European Drug Initative on Channels and Transporters), Fundación Ramón Areces, and the Generalitat de Catalunya Grant SGR2009-1355 (to M.P.); by University of Bern, Swiss National Science Foundation Grants 31003A_125150 and 31003A_144168; the Bern University Research Foundation; the Novartis Foundation; the Marie Curie Actions International Fellowship Program; and National Center of Competence in Research TransCure (D.F.)., Peer Reviewed, Postprint (published version)

The atomic force microscope (AFM) provides a powerful instrument for investigating and manipulating biological samples down to the subnanometer scale. In contrast to other microscopy methods, AFM does not require labeling, staining, nor fixation of samples and allows the specimen to be fully hydrated in buffer solution during the experiments. Moreover, AFM clearly compares in resolution to other techniques. In general, the AFM can be operated in an imaging or a force spectroscopy mode. In the present work, advantage was taken of this versatility to investigate single biomolecules and biomolecular assemblies. A novel approach to investigate the visco-elastic behavior of biomolecules under force was established, using dextran as an example. While a molecule tethered between a solid support and the cantilever tip was stretched at a constant velocity, the thermally driven oscillation of the cantilever was recorded. Analysis of the cantilever Brownian noise provided information about the visco-elastic properties of dextran that corresponded well to parameters obtained by alternative methods. However, the approach presented here was easier to implement and less time-consuming than previously used methods. A computer controlled force-clamp system was set up, circumventing the need for custom built analogue electronics. A commercial PicoForce AFM was extended by two computers which hosted data acquisition hardware. While the first computer recorded data, the second computer drove the AFM bypassing the manufacturer's microscope control software. To do so, a software-based proportional-integral-differential (PID) controller was implemented on the second computer. It allowed the force applied to a molecule to be held constant over time. After tuning of the PID controller, response times obtained using that force-clamp setup were comparable to those of the recently reported analogue systems. The performance of the setup was demonstrated by force-clamp unfolding of a pentameric

High-resolution microscopy techniques provide a plethora of information on biological structures from the cellular level down to the molecular level. In this review, we present the unique capabilities of transmission electron and atomic force microscopy to assess the structure, oligomeric state, function and dynamics of channel and transport proteins in their native environment, the lipid bilayer. Most importantly, membrane proteins can be visualized in the frozen-hydrated state and in buffer solution by cryo-transmission electron and atomic force microscopy, respectively. We also illustrate the potential of the scintillation proximity assay to study substrate binding of detergent-solubilized transporters prior to crystallization and structural characterization