What does an explanted PASCAL device look like?

We report the case of a 78-year-old female patient who had a PASCAL device implanted for severe degenerative mitral regurgitation. Intraprocedural echocardiography revealed persistent severe mitral regurgitation due to device dislocation. Implanting another device was not possible. After 8 days, the device was explanted, and the valve was replaced with a biological pro We report the case of a 78-year-old female patient who had a PASCAL device implanted for severe degenerative mitral regurgitation. Intraprocedural echocardiography revealed persistent severe mitral regurgitation due to device dislocation. Implanting another device was not possible. After 8 days, the device was explanted, and the valve was replaced with a biological prosthesis. The PASCAL device and resected mitral valve leaflets were sent for histopathological workup. Keywords: Mitral regurgitation; PASCAL device; Transcatheter therapysthesis. The PASCAL device and resected mitral valve leaflets were sent for histopathological workup

Spatially Offset Raman Spectroscopic (SORS) Analysis of Wine Alcoholic Fermentation: A Preliminary Study

Spatially offset Raman spectroscopy (SORS) is a non-invasive analytical technique that allows the analysis of samples through a container. This makes it an effective tool for studying food and beverage products, as it can measure the sample without being affected by the packaging or the container. In this study, a portable SORS equipment was used for the first time to analyse the alcoholic fermentation process of white wine. Different sample measurement arrangements were tested in order to determine the most effective method for monitoring the fermentation process and predicting key oenological parameters. The best results were obtained when the sample was directly measured through the glass container in which the fermentation was occurring. This allowed for the accurate monitoring of the process and the prediction of density and pH with a root mean square error of cross-validation (RMSECV) of 0.0029 g·L−1 and 0.04, respectively, and R2 values of 0.993 and 0.961 for density and pH, respectively. Additionally, the sources of variability depending on the measurement arrangements were studied using ANOVA-Simultaneous Component Analysis (ASCA)

Influence of Si substitution on the reactivity of a-tricalcium phosphate

Silicon substituted calcium phosphates have been widely studied over the last ten years due to their enhanced osteogenic properties. Notwithstanding, the role of silicon on a-TCP reactivity is not clear yet. Therefore, the aim of this work was to evaluate the reactivity and the properties of Si-a-TCP in comparison to a-TCP. Precursor powders have similar properties regarding purity, particle size distribution and specific surface area, which allowed a better comparison of the Si effects on their reactivity and cements properties. Both Si-a-TCP and a-TCP hydrolyzed to a calcium-deficient hydroxyapatite when mixed with water but their conversion rates were different. Si-a-TCP exhibited a slower setting rate than a-TCP, i.e. kSSA for Si-TCP (0.021 g·m- 2·h- 1) was almost four times lower than for a-TCP (0.072 g·m- 2·h- 1). On the other hand, the compressive strength of the CPC resulting from fully reacted Si-a-TCP was significantly higher (12.80 ± 0.38 MPa) than that of a-TCP (11.44 ± 0.54 MPa), due to the smaller size of the entangled precipitated apatite crystals.Preprin

Assessment of variability sources in grape ripening parameters by using FTIR and multivariate modelling

The variability in grape ripening is associated with the fact that each grape berry undergoes its own biochemical processes. Traditional viticulture manages this by averaging the physicochemical values of hundreds of grapes to make decisions. However, to obtain accurate results it is necessary to evaluate the different sources of variability, so exhaustive sampling is essential. In this article, the factors “grape maturity over time” and “position of the grape” (both in the grapevine and in the bunch/cluster) were considered and studied by analyzing the grapes with a portable ATR-FTIR instrument and evaluating the spectra obtained with ANOVA–simultaneous component analysis (ASCA). Ripeness over time was the main factor affecting the characteristics of the grapes. Position in the vine and in the bunch (in that order) were also significantly important, and their effect on the grapes evolves over time. In addition, it was also possible to predict basic oenological parameters (TSS and pH with errors of 0.3 °Brix and 0.7, respectively). Finally, a quality control chart was built based on the spectra obtained in the optimal state of ripening, which could be used to decide which grapes are suitable for harvest

Prior intake of new oral anticoagulants adversely affects outcome following surgery for acute type A aortic dissection

Objectives: Oral anticoagulation prior to emergency surgery is associated with an increased risk of perioperative bleeding, especially when this therapy cannot be discontinued or reversed in time. The goal of this study was to analyse the impact of different oral anticoagulants on the outcome of patients who underwent emergency surgery for acute type A aortic dissection (ATAAD). Methods: This was a single-centre retrospective study of patients treated with oral anticoagulation at the time of surgery for ATAAD. Outcomes of patients on new oral anticoagulant (NOAC) therapy were compared to respective outcomes of patients on Coumadin. Additionally, a survival analysis was performed comparing these 2 groups with patients who were operated on with no prior anticoagulation. Results: Between January 2013 and April 2020, a total of 437 patients (63.8 ± 11.8 years, 68.4% male) received emergency surgery for ATAAD; 35 (8%) were taking oral anticoagulation at the time of hospital admission: 20 received phenprocoumon; 14, rivaroxaban; and 1, dabigatran. Compared to Coumadin, NOAC was associated with a greater need for blood-product transfusions and haemodynamic compromise. Operative mortality was 53% in the NOAC group and 30% in the Coumadin group. A 5-year survival analysis showed no significant difference between the NOAC and the Coumadin group (P = 0.059). Compared to 402 patients treated during the study period without anticoagulation, patients taking NOAC had significantly worse survival (P = 0.001), whereas that effect was not observed in patients undergoing surgery who were taking Coumadin (P = 0.99). Conclusions: Emergency surgery for ATAAD in patients taking NOAC is associated with high morbidity and mortality. NOAC are a major risk factor for uncontrollable bleeding and haemodynamic compromise. New treatment strategies must be defined to improve surgical outcomes in these high-risk patients. Keywords: Acute aortic syndrome; Aortic dissection; Bleeding; Coumadin; DOAC; NOAC; Oral anticoagulation; Type A dissection

Nanoscale magnetic structure and properties of solution-derived self-assembled La0.7Sr0.3MnO3 islands

The following article appeared in Journal of Applied Physics 111.2 (2012): 024307 and may be found at http://scitation.aip.org/content/aip/journal/jap/111/2/10.1063/1.3677985Strain-induced self-assembled La0.7Sr0.3MnO 3 nanoislands of lateral size 50-150 nm and height 10-40 nm have been grown on yttria-stabilized zirconia (001)-substrates from ultradiluted chemical solutions based on metal propionates. The nanoislands grow highly relaxed withstanding the epitaxial relation (001)LSMO[110]//(001) Ysz[010] and show bulk-like average magnetic properties in terms of Curie temperature and saturation magnetization. The interplay of the magnetocrystalline and shape anisotropy within the nanoisland ensemble results in an in-plane magnetic anisotropy with a magnetocrystalline constant K 1(150K) = -(5±1) kJ/m3 and in-plane easy axis along the [110] -La0.7Sr0.3MnO3 direction as measured, for the first time, through ferromagnetic resonance experiments. Magnetic force microscopy studies reveal the correlation between nanoisland size and its magnetic domain structure in agreement with micromagnetic simulations. In particular, we have established the required geometric conditions for single domain, multidomain, and vortex configurations.We acknowledge the financial support from MEC (MAT2008-01022, Consolider NANOSELECT and FPU), Comunidad Autónoma de Madrid (CAM S2009/MAT-1467), Generalitat de Catalunya (Catalan Pla de Recerca 2009-SGR- 770 and XaRMAE), and EU (NESPA). R. D. Zysler and C. A. Ramos acknowledge support from PIP-1333(2007) CONICET and PICT 829 (2006) and PICT 832(2006) ANPCyT of Argentina. Serveis Científic-Tècnics from Universitat de Barcelona and Servei de Micròscopia from Universitat Auto`noma de Barcelona are acknowledged for TEM facilities

ChemProt: a disease chemical biology database

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical–protein annotation resources, as well as disease-associated protein–protein interactions (PPIs). We assembled more than 700 000 unique chemicals with biological annotation for 30 578 proteins. We gathered over 2-million chemical–protein interactions, which were integrated in a quality scored human PPI network of 428 429 interactions. The PPI network layer allows for studying disease and tissue specificity through each protein complex. ChemProt can assist in the in silico evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram, an antidepressant, with osteogenesis imperfect and leukemia and bisphenol A, an endocrine disruptor, with certain types of cancer, respectively. The server can be accessed at http://www.cbs.dtu.dk/services/ChemProt/

The Mycobacterium tuberculosis Drugome and Its Polypharmacological Implications

We report a computational approach that integrates structural bioinformatics, molecular modelling and systems biology to construct a drug-target network on a structural proteome-wide scale. The approach has been applied to the genome of Mycobacterium tuberculosis (M.tb), the causative agent of one of today's most widely spread infectious diseases. The resulting drug-target interaction network for all structurally characterized approved drugs bound to putative M.tb receptors, we refer to as the ‘TB-drugome’. The TB-drugome reveals that approximately one-third of the drugs examined have the potential to be repositioned to treat tuberculosis and that many currently unexploited M.tb receptors may be chemically druggable and could serve as novel anti-tubercular targets. Furthermore, a detailed analysis of the TB-drugome has shed new light on the controversial issues surrounding drug-target networks [1]–[3]. Indeed, our results support the idea that drug-target networks are inherently modular, and further that any observed randomness is mainly caused by biased target coverage. The TB-drugome (http://funsite.sdsc.edu/drugome/TB) has the potential to be a valuable resource in the development of safe and efficient anti-tubercular drugs. More generally the methodology may be applied to other pathogens of interest with results improving as more of their structural proteomes are determined through the continued efforts of structural biology/genomics

Automatic Filtering and Substantiation of Drug Safety Signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions