NMR approaches in structure-based lead discovery: recent developments and new frontiers for targeting multi-protein complexes.

This is the final version. It was first published by Elsevier at http://www.sciencedirect.com/science/article/pii/S007961071400087X.Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets.The authors are very grateful to the organizations that funded their research: the UK Biotechnology and Biological Sciences Research Council (BBSRC, grants BB/J001201/1 and David Phillips Fellowship BB/G023123/1 to A.C.), the European Research Council (ERC-2012-StG-311460 DrugE3CRLs, Starting Grant to A.C.) the European Commission (Bio-NMR, Project 261863), and the Fundação para a Ciência e a Tecnologia (FCT, SFRH/BD/81735/2011 Studentship to D.M.D.)

Smart Property Valuation. Problem Solving for Industry

The analysis of this project it is used the CRISP-DM method. Smart Property Valuation (SPV) is a fictional company created by David Silva, Luiz Dias, and Raul Fuzita to analyse, explore, and prove the conception of a model capable of predicting or estimating prices for properties. They believe they can benefit common people, realtors, and construction companies with their solutions. This research is for educational purposes and should be treated as such

34. Grip strength across Europe –North/ South and East/West divides

info:eu-repo/semantics/publishedVersio

Multilevel network meta-regression for general likelihoods: synthesis of individual and aggregate data with applications to survival analysis

Network meta-analysis combines aggregate data (AgD) from multiple randomised controlled trials, assuming that any effect modifiers are balanced across populations. Individual patient data (IPD) meta-regression is the "gold standard" method to relax this assumption, however IPD are frequently only available in a subset of studies. Multilevel network meta-regression (ML-NMR) extends IPD meta-regression to incorporate AgD studies whilst avoiding aggregation bias, but currently requires the aggregate-level likelihood to have a known closed form. Notably, this prevents application to time-to-event outcomes. We extend ML-NMR to individual-level likelihoods of any form, by integrating the individual-level likelihood function over the AgD covariate distributions to obtain the respective marginal likelihood contributions. We illustrate with two examples of time-to-event outcomes, showing the performance of ML-NMR in a simulated comparison with little loss of precision from a full IPD analysis, and demonstrating flexible modelling of baseline hazards using cubic M-splines with synthetic data on newly diagnosed multiple myeloma. ML-NMR is a general method for synthesising individual and aggregate level data in networks of all sizes. Extension to general likelihoods, including for survival outcomes, greatly increases the applicability of the method. R and Stan code is provided, and the methods are implemented in the multinma R package.Comment: 43 pages, 8 figures (corrected metadata

Pando: Personal Volunteer Computing in Browsers

The large penetration and continued growth in ownership of personal electronic devices represents a freely available and largely untapped source of computing power. To leverage those, we present Pando, a new volunteer computing tool based on a declarative concurrent programming model and implemented using JavaScript, WebRTC, and WebSockets. This tool enables a dynamically varying number of failure-prone personal devices contributed by volunteers to parallelize the application of a function on a stream of values, by using the devices' browsers. We show that Pando can provide throughput improvements compared to a single personal device, on a variety of compute-bound applications including animation rendering and image processing. We also show the flexibility of our approach by deploying Pando on personal devices connected over a local network, on Grid5000, a French-wide computing grid in a virtual private network, and seven PlanetLab nodes distributed in a wide area network over Europe.Comment: 14 pages, 12 figures, 2 table

Natural pigments of anthocyanin and betalain for coloring soy-based yogurt alternative

The aim of this work was to evaluate the color stability of betalain- and anthocyanin-rich extracts in yogurt-like fermented soy, in order to develop a preliminary understanding of how these pigments behave in this type of food system during storage for 21 days at 4 °C. Thus, the extracts of red beetroot, opuntia, hibiscus and red radish were integrated into the yogurt-like fermented soy in two different ways—directly after lyophilization, and encapsulated in nanosystems based in soybean lecithin—as this approach has never been used to further increase the value and potential of the dairy-free alternatives of yogurt-like fermented soy. The results showed that non-encapsulated betalain-rich extracts from red radish are the most promising for coloring yogurt-like fermented soy. However, encapsulated opuntia extracts can also be an alternative to supplement the soy fermented beverages with betalains, without changing significantly the color of the system but giving all its health benefits, due to the protection of the pigments by nanoencapsulation.This research was funded by COMPETE 2020 program, co-financed by the FEDER and the European Union, PTDC/ASP-AGR/30154/2017 (POCI-01-0145-FEDER-030154). Foundation for Science and Technology (FCT, Portugal), and FEDER-COMPETE-QREN-EU funded research centers CQ-UM (UID/QUI/00686/2019), CF-UM-UP (UID/FIS/04650/2019) and REQUIMTE (UIDB/50006/2020)

Exploring the Impact of a Gamified Exercise Platform to Support Healthy Ageing:Home-Based Study with Older Adults

Active ageing is an increasingly important concept within society due to the ageing of the world population and search for enhanced quality of life. Technological resources such as serious games can be used as a means to promote healthier lifestyle and ageing, particularly in older adults. This study intended to explore the effects of using a digital approach composed of serious games to support physical and cognitive exercise at home, to support healthy ageing. Eleven older adults voluntarily participated in an eight-day home-based study. The aim of the study was to explore the feasibility of the digital approach in autonomous sessions at home, by measuring satisfaction and motivation, and assessing the impact of different gamification strategies. The results showed that participants exercised autonomously on average on 5.5 out of the 8 days. Each session had an average duration of 35 minutes. Moreover, participants reported an average satisfaction of 80.0% throughout the sessions. Yet, the findings indicate that system usability should still be improved. Participants provided suggestions towards an easier user experience, pointing for example to the importance of personalized exercise plans. The findings suggest that gamification strategies focused on multi-joint and dynamic exercises were preferred over single limb and more monotonous exercises. The current study highlights the potential of home-based digital solutions to support healthy ageing in older adults and provide suggestions for future endeavors in this area.</p

Beetroot as a source of natural dyes for ham

Beetroot (Beta vulgaris L.) was subjected to extraction procedures in order to obtain the respective extracts containing the natural dyes and subjected to cytotoxicity assays in AGS cell line. Encapsulation of the extracts in nanosystems based on soybean lecithin and maltodextrin was performed. Lyophilized extracts before and after encapsulation in maltodextrin were applied in the formulation of leg ham and used in pilot scale of production. The colour of ham samples from the different assays was evaluated visually and by colorimetry.Dias, S.; Pereira, D.M.; Castanheira, E.M.S.; Fortes, A.G.; Pereira, R.; Gonçalves, a.M.S.T. Beetroot as a Source of Natural Dyes for Ham. Proceedings 2019, 41, 82. https://doi.org/10.3390/ecsoc-23-0662

Rethinking Leahy’s Emotional Schema Scale (LESS): Results from the Portuguese Adaptation of the LESS

This study aims to contribute to the study of emotional schemas, through the adaptation of the Leahy Emotional Schema Scale (LESS) to Portuguese. The LESS is a 50 item self-report with 14 theoretical dimensions, representing concepts, evaluations, attributions of emotions, and strategies of emotion regulation (Leahy in Cognit Behav Pract 9(3):177–190, 2002. https://doi.org/10.1016/S1077-7229(02)80048- 7). Translation, back-translation and pilot assessment of LESS’s Portuguese version were completed. Data was collected online with 396 participants. An exploratory principal component analysis was conducted. Parallel analysis revealed a 5-component structure, which after the deletion of eight items generated a fnal solution explaining 48% of the variance. Components internal consistency was adequate and convergent validity supported with signifcant correlations with difculties in emotional regulation and emotional processing, and psychopathology. It presents dimensions that are highly relevant for assessment, case conceptualization and clinical decision making. Although this scale is related to a specifc cognitive theory, the construct and its subscales may be useful beyond the psychotherapeutic model, stressing the transtheoretical potential of the scale.info:eu-repo/semantics/publishedVersio

Multinma: A comprehensive R package for network meta-analysis of survival outcomes with aggregate data, individual patient data, or a mixture of both

IntroductionSurvival or time-to-event outcomes are commonplace in disease areas such as oncology. Healthcare decision makers require estimates of relative efficacy between different treatment options, however treatments of interest are frequently not all compared in head-to-head randomised controlled trials, and so indirect comparison and network meta-analysis (NMA) methods are required to synthesise evidence from a connected network of trials and treatments. An extension of NMA, multilevel network meta-regression (ML-NMR), is increasingly used to account for differences in effect modifiers between populations where individual patient data are available from one or more trials. However, to date there has been no user-friendly software package that can perform NMA or ML-NMR with survival outcomes; instead analysts have needed to rely on complex bespoke modelling code. MethodsA recent update to the multinma R package provides a user-friendly suite of models and tools for synthesising survival outcomes from multiple trials, with aggregate data, individual patient data, or mixtures of both. Models are fitted in a Bayesian framework using Stan. A full range of parametric proportional hazards and accelerated failure time survival distributions are implemented, along with flexible baseline hazard models via M-splines or piecewise exponential hazards with a novel random walk shrinkage prior that avoids overfitting. Shape parameters may be stratified or regressed on treatment arm and/or covariates to relax proportionality. Right, left, and interval censoring, and delayed entry are all supported.ResultsWe present analyses of two case studies using the multinma package. First, we performed a NMA of published aggregate data from a network of treatments for advanced non-small cell lung cancer using flexible M-spline baseline hazards. We introduced treatment effects onto the spline coefficients to account for non-proportional hazards, and produced estimated survival curves in a target population required for further economic modelling.Second, we performed a ML-NMR using a mixture of individual patient data and aggregate data from a network of treatments for newly-diagnosed multiple myeloma. We adjusted for effect-modifying covariates, and produced population-adjusted estimates for target populations of interest to decision-making. Covariate adjustment removed evidence for non-proportional hazards that was present in unadjusted models.ConclusionsThe multinma package makes NMA and ML-NMR methods accessible to a broad audience. The latest update to include a suite of functionality for survival analysis facilitates application of these methods to widespread settings such as oncology, where until now there was no user-friendly software available