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There has been a large discussion in literature regarding the proper management of asymptomatic patients with significant carotid artery stenosis. This study aims to identify potential risk factors associated with high-risk carotid plaques.

Purpose: Colour fundus images are widely used in diagnosis treatment decision of several retinal diseases such as diabetic retinopathy (DR), glaucoma and age-related macular degeneration (AMD). These very common conditions must be detected early and monitored to prevent progression and avoid permanent damage. Fundus images revealed to be useful also for the diagnosis of cataracts. Methods: In this review paper, an overview of traditional, machine learning and modern deep learning techniques for ophthalmic disease diagnosis (i.e. glaucoma, DR, AMD, and cataract) using retinal fundus images is presented. In addition, various publicly available image datasets used for such purposes are described. Results: The current main challenges and findings are identified, as well as common aspects and discrepancies between the various methods developed for the various diseases. Conclusion: The overview of what has been done about all pathologies, rather than only on a specific one, could favour a migration of the best solutions and, hopefully, the development of a more precise and clinically useful automatic analysis of all pathologies. Important critical insights and research trends are also discussed. Graphical abstract:

Although the incidence of restenosis and stent thrombosis has substantially declined during the last decades, they still constitute the two major causes of stent failure. These complications are partially attributed to the currently used cytostatic drugs, which can cause local inflammation, delay or prevent re-endothelialization and essentially cause arterial cell toxicity. Retinoic acid (RA), a vitamin A (retinol) derivative, is a naturally occurring substance used for the treatment of cell proliferation disorders. The agent has pleiotropic effects on vascular smooth muscle cells and macrophages: it influences the proliferation, migration, and transition of smooth muscle cells to other cell types and modulates macrophage activation. These observations are supported by accumulated evidence from in vitro and in vivo experiments. In addition, systemic and topical administration of RA can decrease the development of atherosclerotic plaques and reduce or inhibit restenosis after vascular injury (caused by embolectomy, balloon catheters, or ligation of arteries) in various experimental models. Recently, an RA-drug eluting stent (DES) has been tested in an animal model. In this review, we explore the effects of RA in atherosclerosis and the potential of the local delivery of RA through an RA-DES or RA-coated balloon for targeted therapeutic percutaneous vascular interventions. Despite promising published results, further experimental study is warranted to examine the safety and efficacy of RA-eluting devices in vascular artery disease.

The daily healthy diet and balanced intake of essential nutrients play an important role in modern lifestyle. The estimation of a meal's nutrient content is an integral component of significant diseases, such as diabetes, obesity and cardiovascular disease. Lately, there has been an increasing interest towards the development and utilization of smartphone applications with the aim of promoting healthy behaviours. The semi – automatic or automatic, precise and in real-time estimation of the nutrients of daily consumed meals is approached in relevant literature as a computer vision problem using food images which are taken via a user's smartphone. Herein, we present the state-of-the-art on automatic food recognition and food volume estimation methods starting from their basis, i.e., the food image databases. First, by methodically organizing the extracted information from the reviewed studies, this review study enables the comprehensive fair assessment of the methods and techniques applied for segmenting food images, classifying their food content and computing the food volume, associating their results with the characteristics of the used datasets. Second, by unbiasedly reporting the strengths and limitations of these methods and proposing pragmatic solutions to the latter, this review can inspire future directions in the field of dietary assessment systems.

Eye behaviour provides valuable information revealing one’s higher cognitive functions and state of affect. Although eye tracking is gaining ground in the research community, it is not yet a popular approach for the detection of emotional and cognitive states. In this paper, we present a review of eye and pupil tracking related metrics (such as gaze, fixations, saccades, blinks, pupil size variation, etc.) utilized towards the detection of emotional and cognitive processes, focusing on visual attention, emotional arousal and cognitive workload. Besides, we investigate their involvement as well as the computational recognition methods employed for the reliable emotional and cognitive assessment. The publicly available datasets employed in relevant research efforts were collected and their specifications and other pertinent details are described. The multimodal approaches which combine eye-tracking features with other modalities (e.g. biosignals), along with artificial intelligence and machine learning techniques were also surveyed in terms of their recognition/classification accuracy. The limitations, current open research problems and prospective future research directions were discussed for the usage of eye-tracking as the primary sensor modality. This study aims to comprehensively present the most robust and significant eye/pupil metrics based on available literature towards the development of a robust emotional or cognitive computational model.

Prostate cancer diagnosis and treatment relies on precise MRI lesion segmentation, a challenge notably for small (<15 mm) and intermediate (15–30 mm) lesions. Our study introduces ProLesA-Net, a multi-channel 3D deep-learning architecture with multi-scale squeeze and excitation and attention gate mechanisms. Tested against six models across two datasets, ProLesA-Net significantly outperformed in key metrics: Dice score increased by 2.2%, and Hausdorff distance and average surface distance improved by 0.5 mm, with recall and precision also undergoing enhancements. Specifically, for lesions under 15 mm, our model showed a notable increase in five key metrics. In summary, ProLesA-Net consistently ranked at the top, demonstrating enhanced performance and stability. This advancement addresses crucial challenges in prostate lesion segmentation, enhancing clinical decision making and expediting treatment processes.

Coronary CT angiography–derived endothelial shear stress provided useful information for predicting impaired vasodilating capacity assessed by using PET myocardial perfusion imaging.

Heart failure (HF) is the most rapidly growing cardiovascular condition with an estimated prevalence of >37.7 million individuals globally. HF is associated with increased mortality and morbidity and confers a substantial burden, in terms of cost and quality of life, for the individuals and the healthcare systems, highlighting thus the need for early and accurate diagnosis of HF. The accuracy of HF diagnosis, severity estimation, and prediction of adverse events has improved by the utilization of blood tests measuring biomarkers. The contribution of biomarkers for HF management is intensified by the fact that they can be measured in short time at the point-of-care. This is allowed by the development of portable analytical devices, commonly known as point-of-care testing (POCT) devices, which exploit the advancements in the area of microfluidics and nanotechnology. The aim of this review paper is to present a review of POCT devices used for the measurement of biomarkers facilitating decision making when managing HF patients. The devices are either commercially available or in the form of prototypes under development. Both blood and saliva samples are considered. The challenges concerning the implementation of POCT devices and the barriers for their adoption in clinical practice are discussed.

Although several studies have deployed gradient boosting trees (GBT) as a robust classifier for federated learning tasks (federated GBT [FGBT]), even with dropout rates (federated gradient boosting trees with dropout rate [FDART]), none of them have investigated the overfitting effects of FGBT across heterogeneous and highly imbalanced datasets within federated environments nor the effect of dropouts in the loss function. In this work, we present the federated hybrid boosted forests (FHBF) algorithm, which incorporates a hybrid weight update approach to overcome ill-posed problems that arise from overfitting effects during the training across highly imbalanced datasets in the cloud. Eight case studies were conducted to stress the performance of FHBF against existing algorithms toward the development of robust AI models for lymphoma development across 18 European federated databases. Our results highlight the robustness of FHBF, yielding an average loss of 0.527 compared with FGBT (0.611) and FDART (0.584) with increased classification performance (0.938 sensitivity, 0.732 specificity).

Nanoscopic artificial vesicles containing functional protein transporters are fundamental for synthetic biology. Energy-providing modules, such as proton pumps, are a basis for simple nanoreactors. We report on the first insertion of a functional transmembrane protein into asymmetric polymersomes from an ABC triblock copolymer. The polymer with the composition poly(ethylene glycol)-poly(diisopropylaminoethyl methacrylate)-poly(styrenesulfonate) (PEG-PDPA-PSS) was synthesized by sequential controlled radical polymerization. PEG and PSS are two distinctively different hydrophilic blocks, allowing for a specific orientation of our protein, the light-activated proton pump proteorhodopsin (PR), into the final proteopolymersome. A very interesting aspect of the PEG-PDPA-PSS triblock copolymers is that it allowed for simultaneous vesicle formation and oriented insertion of PR simply by adjusting the pH. The intrinsic positive charge of PR’s intracellular surface was enhanced by a His-tag, which aligns readily with the negative charges of the PSS on the outside of the polymersomes. The directed insertion of PR was confirmed by a light-dependent pH change of the proteopolymersome solution, indicating the intended orientation. We have hereby demonstrated the first successful oriented insertion of a proton pump into an artificial asymmetric membrane.

In this review, the critical parts and milestones for data harmonization, from the biomedical engineering perspective, are outlined. The need for data sharing between heterogeneous sources paves the way for cohort harmonization; thus, fostering data integration and interdisciplinary research. Unmet needs in chronic diseases, as well as in other diseases, can be addressed based on the integration of patient health records and the sharing of information of the clinical picture and outcome. The stratification of patients, the determination of various clinical and outcome features, and the identification of novel biomarkers for the different phenotypes of the disease characterize the impact of cohort harmonization in patient-centered clinical research and in precision medicine. Subsequently, the establishment of matching techniques and ontologies for the creation of data schemas are also presented. The exploitation of web technologies and data-collection tools supports the opportunities to achieve new levels of integration and interoperability. Ethical and legal issues that arise when sharing and harmonizing individual-level data are discussed in order to evaluate the harmonization potential. Use cases that shape and test the harmonization approach are explicitly analyzed along with their significant results on their research objectives. Finally, future trends and directions are discussed and critically reviewed toward a roadmap in cohort harmonization for clinical medicine.

AimTo examine the effect of endothelial shear stress (ESS) on the dynamic changes in plaque phenotype.MethodsPatients with myocardial infarction that had intravascular ultrasound-virtual histology (IVUS-VH) and optical coherence tomography (OCT) at baseline and 13-month follow-up were studied. The IVUS-VH data were used to reconstruct the nonculprit vessels, and in the obtained models the ESS was estimated in 3 mm segments. Plaque morphology was derived in each segment from IVUS-VH and OCT. Disease progression was defined as the presence of ≥2 out of the following criteria: reduction in lumen area, increase in plaque burden and change of plaque morphology to a more vulnerable phenotype. Linear mixed effects models were used to assess the effect of ESS in different phenotypes.ResultsSixty-eight vessels were included in the analysis. Low ESS was associated with plaque progression in all phenotypes. The effect of ESS on plaque burden (p for interaction=0.467) and phenotype (p for interaction=0.188) was similar in all plaque types, whereas the effect of ESS on the changes in lumen dimensions was more prominent in disease-free (β=0.70, p<0.001) than fibrotic/fibrocalcific (β=0.28, p<0.001) or lipid-rich plaques (β=0.15, p=0.015). Standalone IVUS-VH misclassified plaque morphology in one-third of the cases leading to erroneous estimations about the effect of ESS on plaque evolution in different phenotypes.ConclusionsThe effect of ESS on plaque progression is similar in all phenotypes and cannot be accurately assessed by standalone IVUS-VH which often misclassifies plaque morphology. Therefore, multimodality imaging should be considered to examine the implications of ESS on plaque evolution.Clinical trial registrationNCT00962416; Post-results.

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.

AbstractParkinson’s disease (PD) is a degenerative disorder of the central nervous system, which requires a long-term, interdisciplinary disease management. The EU Horizon 2020 project PD_manager (http://www.parkinson-manager.eu/) is aimed at developing a decision support system for PD management. As part of this task, we have developed decision-support models that identify situations in which the disease has progressed to the point which requires a change of medical therapy. The input data includes motor symptoms, non-motor symptoms and epidemiologic data. The models were developed in collaboration with medical experts, using a qualitative multi-criteria method DEX. In this paper, we describe the process and results of model development, and assess the quality of models in terms of classification accuracy, transparency, correctness and completeness.

One major objective of synthetic biology is the bottom-up assembly of minimalistic nanocells consisting of lipid or polymer vesicles as architectural scaffolds and of membrane and soluble proteins as functional elements. However, there is no reliable method to orient membrane proteins reconstituted into vesicles. Here, we introduce a simple approach to orient the insertion of the light-driven proton pump proteorhodopsin (PR) into liposomes. To this end, we engineered red or green fluorescent proteins to the N- or C-terminus of PR, respectively. The fluorescent proteins optically identified the PR constructs and guided the insertion of PR into liposomes with the unoccupied terminal end facing inward. Using the PR constructs, we generated proton gradients across the vesicle membrane along predefined directions such as are required to power (bio)chemical processes in nanocells. Our approach may be adapted to direct the insertion of other membrane proteins into vesicles.

To understand how membrane proteins function requires characterizing their structure, assembly, and inter- and intramolecular interactions in physiologically relevant conditions. Conventionally, such multiparametric insight is revealed by applying different biophysical methods. Here we introduce the combination of confocal microscopy, force–distance curve-based (FD-based) atomic force microscopy (AFM), and single-molecule force spectroscopy (SMFS) for the identification of native membranes and the subsequent multiparametric analysis of their membrane proteins. As a well-studied model system, we use native purple membrane from Halobacterium salinarum, whose membrane protein bacteriorhodopsin was His-tagged to bind nitrilotriacetate (NTA) ligands. First, by confocal microscopy we localize the extracellular and cytoplasmic surfaces of purple membrane. Then, we apply AFM to image single bacteriorhodopsins approaching sub-nanometer resolution. Afterwards, the binding of NTA ligands to bacteriorhodopsins is localized and quantified by FD-based AFM. Finally, we apply AFM-based SMFS to characterize the (un)folding of the membrane protein and to structurally map inter- and intramolecular interactions. The multimethodological approach is generally applicable to characterize biological membranes and membrane proteins at physiologically relevant conditions.

Diabetes is a chronic metabolic disorder requiring the active and continuous participation of diabetic individuals, their caregivers and physicians in order to be managed and well-controlled. Diabetes care has evolved considerably over the years with the development of advanced medical technologies and therapeutics. In the first part of this paper, we present the state of the art in wearable medical devices for monitoring and controlling blood glucose levels with special emphasis on continuous glucose monitoring (CGM) devices and insulin pumps. Moreover, a description is made of the significant steps taken towards a portable fully automated closed-loop glucose control system (artificial pancreas) suitable for outpatient use. The second part of this paper is concerned with mobile self-management support interventions in diabetes care. Advances in mobile computing and wireless communications have enabled the development of efficient mobile applications for self-monitoring diabetes and providing feedback. Both literature and digital distribution stores demonstrate a plethora of such paradigms with, admittedly, obvious variety in their functionalities, design and validity. The way in which mobile health technology has contributed to improvements in diabetes health outcomes and life is also discussed and future directions for research are identified.

Purified membrane proteins are ternary complexes consisting of protein, lipid, and detergent. Information about the amounts of detergent and endogenous phospholipid molecules bound to purified membrane proteins is largely lacking. In this systematic study, three model membrane proteins of different oligomeric states were purified in nine different detergents at commonly used concentrations and characterized biochemically and biophysically. Detergent-binding capacities and phospholipid contents of the model proteins were determined and compared. The insights on ternary complexes obtained from the experimental results, when put into a general context, are summarized as follows. 1), The amount of detergent and 2) the amount of endogenous phospholipids bound to purified membrane proteins are dependent on the size of the hydrophobic lipid-accessible protein surface areas and the physicochemical properties of the detergents used. 3), The size of the detergent and lipid belt surrounding the hydrophobic lipid-accessible surface of purified membrane proteins can be tuned by the appropriate choice of detergent. 4), The detergents n-nonyl-β-D-glucopyranoside and Cymal-5 have exceptional delipidating effects on ternary complexes. 5), The types of endogenous phospholipids bound to membrane proteins can vary depending on the detergent used for solubilization and purification. 6), Furthermore, we demonstrate that size-exclusion chromatography can be a suitable method for estimating the molecular mass of ternary complexes. The findings presented suggest a strategy to control and tune the numbers of detergent and endogenous phospholipid molecules bound to membrane proteins. These two parameters are potentially important for the successul crystallization of membrane proteins for structure determination by crystallographic approaches.

In this paper, we propose a method to estimate the density of a data space represented by a geometric transformation of an initial Gaussian mixture model. The geometric transformation is hierarchical, and it is decomposed into two steps. At first, the initial model is assumed to undergo a global similarity transformation modeled by translation, rotation, and scaling of the model components. Then, to increase the degrees of freedom of the model and allow it to capture fine data structures, each individual mixture component may be transformed by another, local similarity transformation, whose parameters are distinct for each component of the mixture. In addition, to constrain the order of magnitude of the local transformation (LT) with respect to the global transformation (GT), zero-mean Gaussian priors are imposed onto the local parameters. The estimation of both GT and LT parameters is obtained through the expectation maximization framework. Experiments on artificial data are conducted to evaluate the proposed model, with varying data dimensionality, number of model components, and transformation parameters. In addition, the method is evaluated using real data from a speech recognition task. The obtained results show a high model accuracy and demonstrate the potential application of the proposed method to similar classification problems.

The scintillation proximity assay (SPA) is a rapid radioligand binding assay. Upon binding of radioactively labeled ligands (here L-[3H]arginine or D-[3H]glucose) to acceptor proteins immobilized on fluoromicrospheres (containing the scintillant), a light signal is stimulated and measured. The application of SPA to purified, detergent-solubilized membrane transport proteins allows substrate-binding properties to be assessed (e.g., substrate specificity and affinity), usually within 1 d. Notably, the SPA makes it possible to study specific transporters without interference from other cellular components, such as endogenous transporters. Reconstitution of the target transporter into proteoliposomes is not required. The SPA procedure allows high sample throughput and simple sample handling without the need for washing or separation steps: components are mixed in one well and the signal is measured directly after incubation. Therefore, the SPA is an excellent tool for high-throughput screening experiments, e.g., to search for substrates and inhibitors, and it has also recently become an attractive tool for drug discovery.

PBOND is a web server that predicts the conformation of the peptide bond between any two amino acids. PBOND classifies the peptide bonds into one out of four classes, namely cisimide (cis-Pro), cisamide (cis-nonPro), transimide (trans-Pro) and transamide (trans-nonPro). Moreover, for every prediction a reliability index is computed. The underlying structure of the server consists of three stages: (1) feature extraction, (2) feature selection and (3) peptide bond classification. PBOND can handle both single sequences as well as multiple sequences for batch processing. The predictions can either be directly downloaded from the web site or returned via e-mail. The PBOND web server is freely available at http://195.251.198.21/pbond.html.

We present a system for multi-class protein classification based on neural networks. The basic issue concerning the construction of neural network systems for protein classification is the sequence encoding scheme that must be used in order to feed the neural network. To deal with this problem we propose a method that maps a protein sequence into a numerical feature space using the matching scores of the sequence to groups of conserved patterns (called motifs) into protein families. We consider two alternative ways for identifying the motifs to be used for feature generation and provide a comparative evaluation of the two schemes. We also evaluate the impact of the incorporation of background features (2-grams) on the performance of the neural system. Experimental results on real datasets indicate that the proposed method is highly efficient and is superior to other well-known methods for protein classification.

G protein-coupled receptors (GPCRs) are ubiquitous and essential in modulating virtually all physiological processes. These receptors share a similar structural design consisting of the seven-transmembrane α-helical segments. The active conformations of the receptors are stabilized by an agonist and couple to structurally highly conserved heterotrimeric G proteins. One of the most important unanswered questions is how GPCRs couple to their cognate G proteins. Phototransduction represents an excellent model system for understanding G protein signaling, owing to the high expression of rhodopsin in rod photoreceptors and the multidisciplinary experimental approaches used to study this GPCR. Here, we describe how a G protein (transducin) docks on to an oligomeric GPCR (rhodopsin), revealing structural details of this critical interface in the signal transduction process. This conceptual model takes into account recent structural information on the receptor and G protein, as well as oligomeric states of GPCRs.

The development of a new fast and robust computerised system is examined in detecting electrocardiogram (ECG) changes in long duration ECG recordings. The system distinguishes these changes between ST-segment deviation and T-wave alterations and can support the produced diagnosis by providing explanations for the decisions made. The European Society of Cardiology ST-T Database was used for evaluating the performance of the system. Sensitivity and positive predictive accuracy were the performance measures used and the proposed system scored 92.02% and 93.77%, respectively, in detecting ST-segment episodes and 91.09% and 80.09% in detecting T-wave episodes. By using the chi-square test we also compared the performance of the system between ECG recordings with minimal and substantial amount of noise. The sensitivity of the proposed system is higher than of other algorithms reported in the literature and the positive predictive accuracy is comparable to, or better than, most of them.

Objective: To objectively and precisely define the spatial distribution of osteonecrosis and to investigate the influence of various factors including etiology. Design: A volumetric method is presented to describe the size and spatial distribution of necrotic lesions of the femoral head, using MRI scans. The technique is based on the definition of an equivalent sphere model for the femoral head. Patients: The gender, age, number of hips involved, disease duration, pain intensity, limping disability and etiology were correlated with the distribution of the pathologic bone. Seventy-nine patients with 122 hips affected by osteonecrosis were evaluated. Results: The lesion size ranged from 7% to 73% of the sphere equivalent. The lateral octants presented considerable variability, ranging from wide lateral lesions extending beyond the lip of the acetabulum, to narrow medial lesions, leaving a lateral supporting pillar of intact bone. Patients with sickle cell disease and steroid administration presented the largest lesions. The extent of the posterior superior medial octant involvement correlated with the symptom intensity, a younger age and male gender. Conclusion: The methodology presented here has proven a reliable and straightforward imaging tool for precise assessment of necrotic lesions. It also enables us to target accurately the drilling and grafting procedures.

Electron crystallography and atomic force microscopy allow the study of two‐dimensional membrane protein crystals. While electron crystallography provides atomic scale three‐dimensional density maps, atomic force microscopy gives insight into the surface structure and dynamics at sub‐nanometer resolution. Importantly, the membrane protein studied is in its native environment and its function can be assessed directly. The approach allows both the atomic structure of the membrane protein and the dynamics of its surface to be analyzed. In this way, the function‐related conformational changes can be assessed, thus providing a detailed insight on the molecular mechanisms of essential biological processes.

Here we discuss the experimental approaches that have allowed high resolution atomic force microscopy (AFM) imaging, and review results that show AFM to be of great interest for biologists, AFM allows single proteins to be imaged under physiologically relevant conditions. The exceptional signal-to-noise ratio and resolution of AFM topographs enables the oligomerization state and characteristic substructures of individual proteins to be resolved. Several examples demonstrate the capabilities of AFM to directly observe single proteins, and their conformational changes, to study protein-protein interactions and to follow the assembly of membrane proteins. We consider the AFM techniques that have allowed high resolution imaging, and review results that show AFM to be a powerful method to analyze biological processes at the level of single molecules.

Two members of the aquaporin family, PM28A and a new one, PM28C, were isolated and shown to be the major constituents of spinach leaf plasma membranes. These two isoforms were identified and characterized by matrix-assisted laser desorption ionization-mass spectrometry. Edman degradation yielded the amino acid sequence of two domains belonging to the new isoform. PM28B, a previously described isoform, was not found in our preparations. Scanning transmission electron microscopy mass analysis revealed both PM28 isoforms to be tetrameric. Two types of particles, a larger and a smaller one, were found by transmission electron microscopy of negatively stained solubilized proteins and by atomic force microscopy of PM28 two-dimensional crystals. The ratio of larger to smaller particles observed by transmission electron microscopy and single particle analysis correlated with the ratio of PM28A to PM28C determined by matrix-assisted laser desorption ionization-mass spectrometry. The absence of PM28B and the ratio of PM28A to PM28C indicate that these plasma membrane intrinsic proteins are differentially expressed in spinach leaves. These findings suggest that differential expression of the various aquaporin isoforms may regulate the water flux across the plasma membrane, in addition to the known mechanism of regulation by phosphorylation.

The lens major intrinsic protein (MIP, AQP0) is known to function as a water and solute channel. However, MIP has also been reported to occur in close membrane contacts between lens fiber cells, indicating that it has adhesive properties in addition to its channel function. Using atomic force and cryo-electron microscopy we document that crystalline sheets reconstituted from purified ovine lens MIP mostly consisted of two layers. MIP lattices in the apposing membranes were in precise register, and determination of the membrane sidedness demonstrated that MIP molecules bound to each other via their extracellular surfaces. The surface structure of the latter was resolved to 0.61 nm and revealed two protruding domains providing a tight “tongue-and-groove” fit between apposing MIP molecules. Cryo-electron crystallography produced a projection map at 0.69 nm resolution with a mirror symmetry axis at 45 ° to the lattice which was consistent with the double-layered nature of the reconstituted sheets. These data strongly suggest an adhesive function of MIP, and strengthen the view that MIP serves dual roles in the lens. Copyright 2000 Academic Press

No abstract

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To achieve high-resolution topographs of native biological macromolecules in aqueous solution with the atomic force microscope (AFM) interactions between AFM tip and sample need to be considered. Short-range forces produce the submolecular information of high-resolution topographs. In contrast, no significant high-resolution information is provided by the long-range electrostatic double-layer force. However, this force can be adjusted by pH and electrolytes to distribute the force applied to the AFM tip over a large sample area. As demonstrated on fragile biological samples, adjustment of the electrolyte solution results in a local reduction of both vertical and lateral forces between the AFM tip and proteinous substructures. Under such electrostatically balanced conditions, the deformation of the native protein is minimized and the sample surface can be reproducibly contoured at a lateral resolution of 0.6nm.

The three-dimensional (3D) structure of the reaction center (RC) complex isolated from the green sulfur bacterium Chlorobium tepidum was determined from projections of negatively stained preparations by angular reconstitution. The purified complex contained the PscA, PscC, PscB, PscD subunits and the Fenna-Matthews-Olson (FMO) protein. Its mass was found to be 454 kDa by scanning transmission electron microscopy (STEM), indicating the presence of two copies of the PscA subunit, one copy of the PscB and PscD subunits, three FMO proteins and at least one copy of the PscC subunit. An additional mass peak at 183 kDa suggested that FMO trimers copurify with the RC complexes. Images of negatively stained RC complexes were recorded by STEM and aligned and classified by multivariate statistical analysis. Averages of the major classes indicated that different morphologies of the elongated particles (length = 19 nm, width = 8 nm) resulted from a rotation around the long axis. The 3D map reconstructed from these projections allowed visualization of the RC complex associated with one FMO trimer. A second FMO trimer could be correspondingly accommodated to yield a symmetric complex, a structure observed in a small number of side views and proposed to be the intact form of the RC complex.

Two-dimensional (2D) crystals of the photosystem I (PSI) reaction center from Synechococcus sp. OD24 were analyzed by electron and atomic force microscopy. Surface relief reconstructions from electron micrographs of freeze-dried unidirectionally shadowed samples and topographs recorded with the atomic force microscope (AFM) provided a precise definition of the lumenal and stromal PSI surfaces. The lumenal surface was composed of four protrusions that surrounded an indentation. One of the protrusions, the PsaF subunit, was often missing. Removal of the extrinsic proteins with the AFM stylus exposed the stromal side of the PSI core, whose surface structure could then be imaged at a resolution better than 1.4 nm. This interfacial surface between core and extrinsic subunits, had a pseudo-2-fold symmetry and protrusions that correlated with the surface helices e and e′ or were at the sites of putative α-helix-connecting loops estimated from the 4 A˚ map of the complex. The molecular dissection achieved with the AFM, opens new possibilities to unveil the interfaces between subunits of supramolecular assemblies.

The mapping of flexible protein domains with the atomic force microscope is reviewed. Examples discussed are the bacteriorhodopsin from Halobacterium salinarum, the head‐tail‐connector from phage φ29, and the hexagonally packed intermediate layer from Deinococcus radioduranswhich all were recorded in physiological buffer solution. All three proteins undergo reversible structural changes that are reflected in standard deviation maps calculated from aligned topographs of individual protein complexes. Depending on the lateral resolution (up to 0.8 nm) flexible surface regions can ultimately be correlated with individual polypeptide loops. In addition, multivariate statistical classification revealed the major conformations of the protein surface.

Ceramides have been identified as novel biomarkers for cardiovascular disease (CVD) related events and mortality but their role in etiology of subclinical atherosclerosis is unknown. We aimed to assess association between plasma ceramides and carotid intima-media thickness (CIMT) and evaluate predictive value of the ceramides for high CIMT over traditional CVD risk factors.

Patients with diabetes mellitus (DM) and coronary artery disease (CAD) represent a high-risk population, where comorbidities are common and the progression of coronary heart disease is relatively rapid and extensive. The present survey, conducted nationwide in a Eurozone country, Greece, with a properly organized national health system, aimed to record specific data from a significant number of patients with diabetes and documented stable CAD (SCAD).

Motivation: This paper studies the problem of discovering subsequences, known as motifs, that are common to a given collection of related biosequences, by proposing a greedy algorithm for learning a mixture of motifs model through likelihood maximization. The approach adds sequentially a new motif to a mixture model by performing a combined scheme of global and local search for appropriately initializing its parameters. In addition, a hierarchical partitioning scheme based on kd-trees is presented for partitioning the input dataset in order to speed-up the global searching procedure. The proposed method compares favorably over the well-known MEME approach and treats successfully several drawbacks of MEME. Results: Experimental results indicate that the algorithm is advantageous in identifying larger groups of motifs characteristic of biological families with significant conservation. In addition, it offers better diagnostic capabilities by building more powerful statistical motif-models with improved classification accuracy. Availability: Source code in Matlab is available at http://www.cs.uoi.gr/~kblekas/greedy/GreedyEM.html Contact: kblekas@cs.uoi.gr * To whom correspondence should be addressed.