Tracking antioxidant properties and color changes in low-sugar bilberry jam as effect of processing, storage and pectin concentration

<p>Abstract</p> <p>Background</p> <p>Recently, an increased interest in the identification of valuable possibilities for preserving the antioxidant properties of products obtained by thermal processing of fruits rich in bioactive compounds can be noticed. In this regard, an extensive analysis is necessary in terms of thermal processed products behavior in relation to various factors. The purpose of the present study was to assess the effect which processing and storage at 20°C has on the antioxidant properties and color quality of low-sugar bilberry jam with different low-methoxyl pectin (LMP) concentrations.</p> <p>Results</p> <p>For all measured parameters, it should be noted that thermal processing induced significant alterations reported to the values registered for fresh fruit. Most important losses due to thermal processing were recorded for total monomeric anthocyanins (TMA) (81-84%), followed by L-ascorbic acid (L-AsAc) content (53-58%), total phenolics (TP) content (42-51%) and FRAP (ferric reducing antioxidant power) values (36-47%). Moreover, depreciation of the investigated compounds occurred during storage at 20°C. Jam storage for 7 months resulted in severe losses in TMA content in the range 58-72% from the value recorded one day after processing. This coincided with marked increases in polymeric color percent of these products after 7 months of storage. Also, bilberry jam storage for 7 months resulted in a decrease in L-AsAc content of 40-53% from the value recorded one day after processing, 41-57% in TP content and 33-46% from the value recorded one day after processing for FRAP values. By decreasing of LMP concentration in the jam recipe from 1 to 0.3% there has been an increase in losses of investigated compounds.</p> <p>Conclusion</p> <p>Overall, the results indicated that bilberry jams can also represent a good source of antioxidant compounds, although compared to the fruit, important losses seem to occur. Practical application of this work is that this kind of information will be very useful in optimizing the jam processing technology and storage conditions, in order to improve the quality of these products.</p

Applying Bayesian model averaging for uncertainty estimation of input data in energy modelling

Background Energy scenarios that are used for policy advice have ecological and social impact on society. Policy measures that are based on modelling exercises may lead to far reaching financial and ecological consequences. The purpose of this study is to raise awareness that energy modelling results are accompanied with uncertainties that should be addressed explicitly. Methods With view to existing approaches of uncertainty assessment in energy economics and climate science, relevant requirements for an uncertainty assessment are defined. An uncertainty assessment should be explicit, independent of the assessor&#8217;s expertise, applicable to different models, including subjective quantitative and statistical quantitative aspects, intuitively understandable and be reproducible. Bayesian model averaging for input variables of energy models is discussed as method that satisfies these requirements. A definition of uncertainty based on posterior model probabilities of input variables to energy models is presented. Results The main findings are that (1) expert elicitation as predominant assessment method does not satisfy all requirements, (2) Bayesian model averaging for input variable modelling meets the requirements and allows evaluating a vast amount of potentially relevant influences on input variables and (3) posterior model probabilities of input variable models can be translated in uncertainty associated with the input variable. Conclusions An uncertainty assessment of energy scenarios is relevant if policy measures are (partially) based on modelling exercises. Potential implications of these findings include that energy scenarios could be associated with uncertainty that is presently neither assessed explicitly nor communicated adequately

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Model selection in historical research using approximate Bayesian computation

Formal Models and History Computational models are increasingly being used to study historical dynamics. This new trend, which could be named Model-Based History, makes use of recently published datasets and innovative quantitative methods to improve our understanding of past societies based on their written sources. The extensive use of formal models allows historians to reevaluate hypotheses formulated decades ago and still subject to debate due to the lack of an adequate quantitative framework. The initiative has the potential to transform the discipline if it solves the challenges posed by the study of historical dynamics. These difficulties are based on the complexities of modelling social interaction, and the methodological issues raised by the evaluation of formal models against data with low sample size, high variance and strong fragmentation. This work examines an alternate approach to this evaluation based on a Bayesian-inspired model selection method. The validity of the classical Lanchester's laws of combat is examined against a dataset comprising over a thousand battles spanning 300 years. Four variations of the basic equations are discussed, including the three most common formulations (linear, squared, and logarithmic) and a new variant introducing fatigue. Approximate Bayesian Computation is then used to infer both parameter values and model selection via Bayes Factors. Results indicate decisive evidence favouring the new fatigue model. The interpretation of both parameter estimations and model selection provides new insights into the factors guiding the evolution of warfare. At a methodological level, the case study shows how model selection methods can be used to guide historical research through the comparison between existing hypotheses and empirical evidence.Funding for this work was provided by the SimulPast Consolider Ingenio project (CSD2010-00034) of the former Ministry for Science and Innovation of the Spanish Government and the European Research Council Advanced Grant EPNet (340828).Peer ReviewedPostprint (published version

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

How does scapula motion change after reverse total shoulder arthroplasty? - a preliminary report

<p>Abstract</p> <p>Background</p> <p>Arm elevation is composed of glenohumeral and scapulothoracic motion. Many reports have addressed changes of scapular position across a spectrum of shoulder disease. However, no study has examined changes in scapular position after reverse total shoulder arthroplasty (RTSA). The purpose of this study was to evaluate the changes in scapular position after RTSA compared to patients’ contralateral, nonoperated shoulder.</p> <p>Methods</p> <p>Seven patients that underwent RTSA for cuff tear arthropathy from July 2007 to October 2008 were enrolled. The distance between the long axis of the thoracic spine and the inferior pole of the scapula (lateralization of the scapula) was measured on shoulder A-P radiographs at 0 degrees (the neutral position) and at 30, 60, 90, and 120 degrees of shoulder abduction. In addition, the angle between the long axis of the thoracic spine and medial border of the scapula was measured and compared with the patients’ contralateral shoulder.</p> <p>Results</p> <p>Scapulohumeral rhythm was 2.4:1 on the operated shoulder and 4.1:1 on the nonoperated, contralateral shoulder at 120 degrees of abduction. The distance between the line of the interspinous process of upper thoracic vertebra and the inferior pole of the scapula showed a negative slope at 0 to 30 degrees abduction on the operated side, but beyond 30 degrees of abduction, this distance showed a more sudden increase than in the contralateral shoulder. The angle between the vertical vertebral line and the scapular medial border also showed greater increase beyond 30 degrees abduction on the operated limb.</p> <p>Conclusions</p> <p>The pattern of scapular position after RTSA, was found to differ from that of the contralateral shoulder, and showed a more scapular upward rotation.</p