Enhancing risk prediction capabilities in patients with carotid artery disease using a 2-level computational approach.

One of the main causes of death worldwide is carotid artery disease, which causes increasing arterial stenosis and may induce a stroke. To address this problem, the scientific community aims to improve our understanding of the underlying atherosclerotic mechanisms, as well as to make it possible to forecast the progression of atherosclerosis. Additionally, over the past several years, developments in the field of cardiovascular modeling have made it possible to create precise three-dimensional models of patient-specific main carotid arteries. The aforementioned 3D models are then implemented by computational models to forecast either the progression of atherosclerotic plaque or several flow-related metrics which are correlated to risk evaluation. A precise representation of both the blood flow and the fundamental atherosclerotic process within the arterial wall is made possible by computational models, therefore, allowing for the prediction of future lumen stenoses, plaque areas and risk prediction. This work presents an attempt to integrate the outcomes of a novel plaque growth model with advanced blood flow dynamics where the deformed luminal shape derived from the plaque growth model is compared to the actual patient-specific luminal model in terms of several hemodynamic metrics, to identify the prediction accuracy of the aforementioned model. Pressure drop ratios had a mean difference of <3%, whereas OSI-derived metrics were identical in 2/3 cases.Clinical Relevance-This establishes the accuracy of our plaque growth model in predicting the arterial geometry after the desired timeline.

Accurate adventitia reconstruction; significant or not in atherosclerotic plaque growth simulationsƒ A comparative study.

A reform in the diagnosis and treatment process is urgently required as carotid artery disease remains a leading cause of death in the world. To this purpose, all computational techniques are now being applied to enhancing the most cutting-edge diagnosis techniques. Computational modeling of plaque generation and evolution is being refined over the past years to forecast the atherosclerotic progression and the corresponding risk in patient-specific carotid arteries. A prerequisite to their implementation is the reconstruction of the precise three-dimensional models of patient-specific main carotid arteries. Even with the most sophisticated algorithms, accurate reconstruction of the arterial vessel is frequently difficult. Furthermore, there are several works of plaque growth modeling that ignore the reconstruction of the artery's outer layer in favor of a virtual one. In this paper, we investigate the importance of an accurate adventitia layer in plaque growth modeling. This is done as a comparative study by implementing a novel plaque growth model in two reconstructed carotid arterial segments using either their realistic or virtual adventitia layer as input. The results indicate that accurate adventitia reconstruction is of minor importance regarding species distributions and plaque growth in carotid segments, which initially did not contain any plaque regions.Clinical Relevance- The findings of this comparative study emphasize the importance of precise adventitia geometry in plaque growth modeling. As a result, this work sets a higher standard for publishing new plaque growth models.

Prediction of the atherosclerotic plaque development in carotid arteries; the effect of T-cells.

The carotid artery disease is one of the leading causes of mortality worldwide, as it leads to the progressive arterial stenosis that may result to stroke. To address this issue, the scientific community is attempting not only to enrich our knowledge on the underlying atherosclerotic mechanisms, but also to enable the prediction of the atherosclerotic progression. This study investigates the role of T-cells in the atherosclerotic plaque growth process through the implementation of a computational model in realistic geometries of carotid arteries. T-cells mediate in the inflammatory process by secreting interferon-y that enhances the activation of macrophages. In this analysis, we used 5 realistic human carotid arterial segments as input to the model. In particular, magnetic resonance imaging data, as well as, clinical data were collected from the patients at two time points. Using the baseline data, plaque growth was predicted and correlated to the follow-up arterial geometries. The results exhibited a very good agreement between them, presenting a high coefficient of determination R2=0.64.

A Machine Learning Model for the Identification of High risk Carotid Atherosclerotic Plaques.

Carotid artery disease is an inflammatory condition involving the deposition and accumulation of lipid species and leucocytes from blood into the arterial wall, which causes the narrowing of the carotid arteries on either side of the neck. Different imaging modalities can by implemented to determine the presence and the location of carotid artery stenosis, such as carotid ultrasound, computed tomography angiography (CTA), magnetic resonance angiography (MRA), or cerebral angiography. However, except of the presence and the degree of stenosis of the carotid arteries, the vulnerability of the carotid atherosclerotic plaques constitutes a significant factor for the progression of the disease and the presence of disease symptoms. In this study, our aim is to develop and present a machine learning model for the identification of high risk plaques using non imaging based features and non-invasive imaging based features. Firstly, we implemented statistical analysis to identify the most statistical significant features according to the defined output, and subsequently, we implemented different feature selection techniques and classification schemes for the development of our machine learning model. The overall methodology has been trained and tested using 208 cases of 107 cases of low risk plaques and 101 cases of high risk plaques. The highest accuracy of 0.76 was achieved using the relief feature selection technique and the support vector machine classification scheme. The innovative aspect of the proposed machine learning model is both the different categories of the utilized input features and the definition of the problem to be solved.

Computational modeling of atherosclerotic plaque progression in carotid lesions with moderate degree of stenosis.

Carotid atherosclerotic plaque growth leads to the progressive luminal stenosis of the vessel, which may erode or rupture causing thromboembolism and cerebral infarction, manifested as stroke. Carotid atherosclerosis is considered the major cause of ischemic stroke in Europe and thus new imaging-based computational tools that can improve risk stratification and management of carotid artery disease patients are needed. In this work, we present a new computational approach for modeling atherosclerotic plaque progression in real patient-carotid lesions, with moderate to severe degree of stenosis (>50%). The model incorporates for the first time, the baseline 3D geometry of the plaque tissue components (e.g. Lipid Core) identified by MR imaging, in which the major biological processes of atherosclerosis are simulated in time. The simulated plaque tissue production results in the inward remodeling of the vessel wall promoting luminal stenosis which in turn predicts the region of the actual stenosis progression observed at the follow-up visit. The model aims to support clinical decision making, by identifying regions prone to plaque formation, predict carotid stenosis and plaque burden progression, and provide advice on the optimal time for patient follow-up screening.

Development of novel GnRH and Tat48-60 based luminescent probes with enhanced cellular uptake and bioimaging profile.

There is a clear need to develop photostable chromophores for bioimaging with respect to the classically utilized green fluorescent dye fluorescein. Along these lines, we utilized a phosphorescent carboxy-substituted ruthenium(ii) polypyridyl [Ru(bipy)2(mcb)]2+ (bipy = 2,2'-bipyridyl and mcb = 4-carboxy-4'-methyl-2,2'-bipyridyl) complex. We developed two luminescent peptide conjugates of the cell-penetrating peptide Tat48-60 consisting of either [Ru(bipy)2(mcb)]2+ or 5(6)-carboxyfluorescein (5(6)-FAM) tethered on the Lys50 of the peptide through amide bond. We confirmed the efficient cellular uptake of both bioconjugates in HeLa cells by confocal microscopy and flow cytometry and proved that the ruthenium-based chromophore possesses enhanced photostability compared to a 5(6)-FAM-based peptide, after continuous laser scanning. Furthermore, we designed and developed a luminescent agent with high photostability, based on the ruthenium core, that could be selectively localized in cancer cells overexpressing the GnRH receptor (GnRH-R). To achieve this, we took advantage of the tumor-homing character of d-Lys6-GnRH which selectively recognizes the GnRH-R. The [Ru(bipy)2(mcb)]2+-d-Lys6-GnRH peptide conjugate was synthesized, and its cellular uptake was evaluated through flow cytometric analysis and live-cell imaging in HeLa and T24 bladder cancer cells as negative and positive controls of GnRH-R, respectively. Besides the selective targeting that the specific conjugate could offer, we also recorded high internalization levels in T24 bladder cancer cells. The ruthenium(ii) polypyridyl peptide-based conjugates we developed is an intriguing approach that offers targeted cell imaging in the Near Infrared region, and simultaneously paves the way for further advancements in the dynamic studies on cellular imaging.

A deep learning oriented method for automated 3D reconstruction of carotid arterial trees from MR imaging.

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.

The TAXINOMISIS Project: A multidisciplinary approach for the development of a new risk stratification model for patients with asymptomatic carotid artery stenosis.

INTRODUCTION: Asymptomatic carotid artery stenosis (ACAS) may cause future stroke and therefore patients with ACAS require best medical treatment. Patients at high risk for stroke may opt for additional revascularization (either surgery or stenting) but the future stroke risk should outweigh the risk for peri/post-operative stroke/death. Current risk stratification for patients with ACAS is largely based on outdated randomized-controlled trials that lack the integration of improved medical therapies and risk factor control. Furthermore, recent circulating and imaging biomarkers for stroke have never been included in a risk stratification model. The TAXINOMISIS Project aims to develop a new risk stratification model for cerebrovascular complications in patients with ACAS and this will be tested through a prospective observational multicentre clinical trial performed in six major European vascular surgery centres. METHODS AND ANALYSIS: The risk stratification model will compromise clinical, circulating, plaque and imaging biomarkers. The prospective multicentre observational study will include 300 patients with 50%-99% ACAS. The primary endpoint is the three-year incidence of cerebrovascular complications. Biomarkers will be retrieved from plasma samples, brain MRI, carotid MRA and duplex ultrasound. The TAXINOMISIS Project will serve as a platform for the development of new computer tools that assess plaque progression based on radiology images and a lab-on-chip with genetic variants that could predict medication response in individual patients. CONCLUSION: Results from the TAXINOMISIS study could potentially improve future risk stratification in patients with ACAS to assist personalized evidence-based treatment decision-making.

Hydroxytyrosol inhibits hydrogen peroxide-induced apoptotic signaling via labile iron chelation.

Although it is known that Mediterranean diet plays an important role in maintaining human health, the underlying molecular mechanisms remain largely unknown. The aim of this investigation was to elucidate the potential role of ortho-dihydroxy group containing natural compounds in H2O2-induced DNA damage and apoptosis. For this purpose, the main phenolic alcohols of olive oil, namely hydroxytyrosol and tyrosol, were examined for their ability to protect cultured cells under conditions of oxidative stress. A strong correlation was observed between the ability of hydroxytyrosol to mitigate intracellular labile iron level and the protection offered against H2O2-induced DNA damage and apoptosis. On the other hand, tyrosol, which lacks the ortho-dihydroxy group, was ineffective. Moreover, hydroxytyrosol (but not tyrosol), was able to diminish the late sustained phase of H2O2-induced JNK and p38 phosphorylation. The derangement of intracellular iron homeostasis, following exposure of cells to H2O2, played pivotal role both in the induction of DNA damage and the initiation of apoptotic signaling. The presented results suggest that the protective effects exerted by ortho-dihydroxy group containing dietary compounds against oxidative stress-induced cell damage are linked to their ability to influence changes in the intracellular labile iron homeostasis.

PRESS: PRotEin S-Sulfenylation server.

MOTIVATION: Transient S-sulfenylation of cysteine thiols mediated by reactive oxygen species plays a critical role in pathology, physiology and cell signaling. Therefore, discovery of new S-sulfenylated sites in proteins is of great importance towards understanding how protein function is regulated upon redox conditions. RESULTS: We developed PRESS (PRotEin S-Sulfenylation) web server, a server which can effectively predict the cysteine thiols of a protein that could undergo S-sulfenylation under redox conditions. We envisage that this server will boost and facilitate the discovery of new and currently unknown functions of proteins triggered upon redox conditions, signal regulation and transduction, thus uncovering the role of S-sulfenylation in human health and disease. AVAILABILITY AND IMPLEMENTATION: The PRESS web server is freely available at http://press-sulfenylation.cse.uoi.gr/ CONTACTS: agtzakos@gmail.com or gtzortzi@cs.uoi.gr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Microcystin LR Shows Cytotoxic Activity Against Pancreatic Cancer Cells Expressing the Membrane OATP1B1 and OATP1B3 Transporters.

Microcystin-LR (MC-LR) is a cyanobacterial cyclopeptide, known for its unique ability to cause acute liver injury. Its cellular uptake is facilitated by specific transmembrane organic anion-transporting polypeptides (OATPs) specifically OATP1B1 and 1B3. The objective of the present study was to investigate the expression of OATPs 1A2, 1B1 and 1B3 in pancreatic cancer cell lines BxPC-3 and MIA PACA-2 and assess their role in MC-LR-mediated cytotoxicity by using the novel xCELLigence system and flow cytometry. OATP1B1 and 1B3 were found to be expressed in both cell lines at both the mRNA and protein levels. The cytotoxic effects of MC-LR were proportionally related to the expression of these transporters. Moreover the cytotoxic potency of MC-LR was found superior to gemcitabine. Based on the expression of the organic anion transporting polypeptides 1B1 and 1B3 in pancreatic carcinoma tissue and cell lines and the potent cytotoxicity induced by MC-LR in vitro, we propose that this molecule could be held as structural basis for the development of novel targeted-compounds against pancreatic cancer.

Direct binding of Bcl-2 family proteins by quercetin triggers its pro-apoptotic activity.

Bcl-2 family proteins are important regulators of apoptosis and its antiapoptotic members, which are overexpressed in many types of cancer, are of high prognostic significance, establishing them as attractive therapeutic targets. Quercetin, a natural flavonoid, has drawn much attention because it exerts anticancer effects, while sparing normal cells. A multidisciplinary approach has been employed herein, in an effort to reveal its mode of action including dose-response antiproliferative activity and induced apoptosis effect, biochemical and physicochemical assays, and computational calculations. It may be concluded that, quercetin binds directly to the BH3 domain of Bcl-2 and Bcl-xL proteins, thereby inhibiting their activity and promoting cancer cell apoptosis.

Insulin resistance: an adaptive mechanism becomes maladaptive in the current environment - an evolutionary perspective.

Human survival has relied upon the ability to withstand starvation through energy storage, the capacity to fight off infection by a proinflammatory immune response, and the ability to cope with physical stressors by an adaptive stress response. Energy storage, mainly as glycogen in liver and triglycerides in adipose tissue, is regulated by the anabolic actions of insulin. On the other hand, mobilization of stored energy during infection, trauma or stress is served by the temporary inhibition of insulin action (insulin resistance) in target tissues by proinflammatory cytokines and stress hormones. In the current environment, high energy intake, low physical activity, and chronic stress favor the storage of surplus fat in adipose tissue depots that far exceeds their storage capacity and liporegulation. Lipid overload in central fat depots initiates an inflammatory response and adipocyte dysfunction with resultant low-grade systemic inflammation and lipid overflow to peripheral tissues. In turn, proinflammatory cytokines and non-oxidized lipid metabolites, accumulated in liver and muscle cells, activate the mechanism of insulin resistance as would occur in the case of infection or stress. The same factors together with the ensuing insulin resistance further contribute to pancreatic ß-cell dysfunction and ultimately to type 2 diabetes and cardiovascular disease. The present review supports the hypothesis that insulin resistance evolved as a physiological adaptive mechanism in human survival and that the same mechanism is inappropriately activated on a chronic basis in the current environment, leading to the manifestations of the metabolic syndrome.

Lipophilic caffeic acid derivatives protect cells against H2O2-Induced DNA damage by chelating intracellular labile iron.

Naturally occurring cinnamic acid derivatives are ubiquitously distributed in the plant kingdom, and it has been proposed that their consumption contributes to the maintenance of human health. However, the molecular mechanisms underlying their health keeping effects remain unknown. In the present investigation, we evaluated the capacity of several cinnamic acid derivatives (trans-cinnamic, p-coumaric, caffeic and ferulic acids, as well as caffeic acid-methyl and -propyl esters) to protect cells from oxidative stress-induced DNA damage. It was observed that effective protection was based on the ability of each compound to (i) reach the intracellular space and (ii) chelate intracellular "labile" iron. These results support the notion that numerous lipophilic iron chelating compounds, present abundantly in plant-derived diet components, may protect cells in conditions of oxidative stress and in this way be important contributors toward maintenance of human health.

Interruption of triacylglycerol synthesis in the endoplasmic reticulum is the initiating event for saturated fatty acid-induced lipotoxicity in liver cells.

The aim of the present study was to investigate in detail the molecular mechanisms by which free fatty acids induce liver toxicity in liver cells. HepG2 and Huh7 human liver cell lines were exposed to varying concentrations of stearate (18:0), oleate (18:1), or mixtures of the two fatty acids, and the effects on cell proliferation, lipid droplet accumulation and induction of endoplasmic reticulum stress and apoptosis were evaluated. It was observed that: (a) stearate, but not oleate, inhibited cell proliferation and induced cell death; (b) stearate-induced cell death had the characteristics of endoplasmic reticulum stress-mediated and mitochondrial-mediated apoptosis; (c) the activation of stearate in the form of stearoyl-CoA was a necessary step for the lipotoxic effect; (d) the capacity of cells to produce and accumulate triacylglycerols in the form of lipid droplets was interrupted following exposure to stearate, whereas it proceeded normally in oleate-treated cells; and (e) the presence of relatively low amounts of oleate protected cells from stearate-induced toxicity and restored the ability of the cells to accumulate triacylglycerols. Our data suggest that interruption of triacylglycerol synthesis in the endoplasmic reticulum, apparently because of the formation of a pool of oversaturated intermediates, represents the key initiating event in the mechanism of saturated fatty acid-induced lipotoxicity.