Metabolic profile analysis of zebrafish embryos

A growing goal in the field of metabolism is to determine the impact of genetics on different aspects of mitochondrial function. Understanding these relationships will help to understand the underlying etiology for a range of diseases linked with mitochondrial dysfunction, such as diabetes and obesity. Recent advances in instrumentation, has enabled the monitoring of distinct parameters of mitochondrial function in cell lines or tissue explants. Here we present a method for a rapid and sensitive analysis of mitochondrial function parameters in vivo during zebrafish embryonic development using the Seahorse bioscience XF 24 extracellular flux analyser. This protocol utilizes the Islet Capture microplates where a single embryo is placed in each well, allowing measurement of bioenergetics, including: (i) basal respiration; (ii) basal mitochondrial respiration (iii) mitochondrial respiration due to ATP turnover; (iv) mitochondrial uncoupled respiration or proton leak and (iv) maximum respiration. Using this approach embryonic zebrafish respiration parameters can be compared between wild type and genetically altered embryos (mutant, gene over-expression or gene knockdown) or those manipulated pharmacologically. It is anticipated that dissemination of this protocol will provide researchers with new tools to analyse the genetic basis of metabolic disorders in vivo in this relevant vertebrate animal model

Technical report: Optimization of the harvest stage for reducing cooking banana postharvest losses: a multi-criteria approach targeting matooke end-product.

This report presents results of RTB-ENDURE sub-output 1.3; ‘Determining appropriate harvest time for the cooking bananas with intrinsic long shelf-life using physical, chemical and sensory attributes’ of the cooking banana business case’s Output 1, entitled “Increased access of farmers to cooking banana varieties with preferred quality attributes and intrinsic long shelf life traits”. The worked aimed at reducing postharvest losses for cooking banana while modulating harvest stage for green life extension. The originality of this investigation was to evaluate the putative impact of fruit stage of harvest onto its potential storage life and eating quality. The optimal harvest stage was evaluated by coupling three antagonist parameters, namely fruit diameter, green life, and eating quality, to optimize harvest stage of the variety Kibuzi in specific edapho-climatic conditions of Rakai and Isingiro districts in southwestern Uganda. A temperature record was considered in both sites between flowering and harvest. The interval between flowering and harvest (IFH) of Kibuzi banana variety was used as a quantitative explanatory variable, and the site location (Rakai at 1270 masl vs Isingiro at 1440 masl) was used as a qualitative one. Since the sites were at different altitudes, two Tynitag temperature data loggers were installed to record temperatures. Fruits size, dry matter, fruit firmness, total soluble solids, titratable acidity and sensory attributes were recorded at four harvest stages: 112, 126, 138, 152 days and 111, 125, 137, 151 days after flowering. The evolution of three parameters; diameter of fruit, green life and overall acceptability of the end-product - Matooke - were simulated for 110 to 155 days range, leading to the identification of a range of optimal harvest ages for variety Kibuzi in Rakai at between 133 to 142 days and 133 to 150 days for Isingiro. The prediction of the optimal harvest stage will remain only valid for the two locations without taking into account thermal sum for establishing a strong relationship between fruit age in degree.days and green life. Given the respective altitudes at Rakai and Isingiro, it implies that the two edapho-climatic conditions were not so different in terms of on field temperature. With some more diverse thermal conditions in the experimental sites (lowland vs highland with at least 3°C needed between sites), the thermal sum concept will be even more precise for the prediction of the optimal harvest stage for bananas, regardless the location site (lowland, highland, with hot or cool local conditions). Such original multi-criteria approach (agro-morphological, physiological traits, and end-product sensory attributes) was relevant for the prediction of the optimal harvest stage, in order to reduce banana postharvest losses during transport and until Matooke preparation by end-users. Such innovative methodology can be applied to some other banana culinary recipes and end-uses

Unpacking the Drivers of LGBT+ Legislation

This paper stems from the hypothesis that there are various key factors rooted in economic, political, and social grounds which actively influence and determine the adoption and evolution of LGBT+ rights in the legal framework of any country. The goal of this research is to analyze these factors and understand how they channel the LGBT+ legislation in our present world. Assuming there is an asymmetry in this application and by extension in LGBT+ individuals' human rights, which are often ignored if not deprived in many parts of the world, this study seeks to understand the reasons behind that asymmetry. Based on a sample of 127 countries, a correlation analysis and a Panel data model were developed to analyze the real impact of these factors

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

<p>Abstract</p> <p>Background</p> <p>Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved.</p> <p>Method</p> <p>This paper introduces a new hybrid methodology <it>Expert-based Cooperative Analysis </it>(EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by <it>EbCA-Data Envelopment Analysis (EbCA-DEA)</it>, and 2) Case-mix of schizophrenia based on functional dependency using <it>Clustering Based on Rules (ClBR)</it>. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases.</p> <p>Results</p> <p>EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here <it>Implicit Knowledg </it>-IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases.</p> <p>Discussion</p> <p>This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.</p

A data science approach for spatiotemporal modelling of low and resident air pollution in Madrid (Spain): Implications for epidemiological studies

Model developments to assess different air pollution exposures within cities are still a key challenge in environmental epidemiology. Background air pollution is a long-term resident and low-level concentration pollution difficult to quantify, and to which population is chronically exposed. In this study, hourly time series of four key air pollutants were analysed using Hidden Markov Models to estimate the exposure to background pollution in Madrid, from 2001 to 2017. Using these estimates, its spatial distribution was later analysed after combining the interpolation results of ordinary kriging and inverse distance weighting. The ratio of ambient to background pollution differs according to the pollutant studied but is estimated to be on average about six to one. This methodology is proposed not only to describe the temporal and spatial variability of this complex exposure, but also to be used as input in new modelling approaches of air pollution in urban areas. (c) 2018 The Author

Implementation of sub-nanosecond time-to-digital convertor in field-programmable gate array: applications to time-of-flight analysis in muon radiography

International audienceTime-of-flight (tof) techniques are standard techniques in high energy physics to determine particles propagation directions. Since particles velocities are generally close to c, the speed of light, and detectors typical dimensions at the meter level, the state-of-the-art tof techniques should reach sub-nanosecond timing resolution. Among the various techniques already available, the recently developed ring oscillator TDC ones, implemented in low cost FPGA, feature a very interesting figure of merit since a very good timing performance may be achieved with limited processing ressources. This issue is relevant for applications where unmanned sensors should have the lowest possible power consumption. Actually this article describes in details the application of this kind of tof technique to muon tomography of geological bodies. Muon tomography aims at measuring density variations and absolute densities through the detection of atmospheric muons flux's attenuation, due to the presence of matter. When the measured fluxes become very low, an identified source of noise comes from backwards propagating particles hitting the detector in a direction pointing to the geological body. The separation between through-going and backward-going particles, on the basis of the tof information is therefore a key parameter for the tomography analysis and subsequent previsions

Middle-Atmosphere Dynamics Observed With a Portable Muon Detector

In the past years, large particle physics experiments have shown that muon rate variations detected in underground laboratories are sensitive to regional, middle-atmosphere temperature variations. Potential applications include tracking short-term atmosphere dynamics, such as Sudden Stratospheric Warmings. We report here that such sensitivity is not only limited to large surface detectors under high-opacity conditions. We use a portable muon detector conceived for muon tomography for geophysical applications, and we study muon rate variations observed over 1 year of measurements at the Mont Terri Underground Rock Laboratory, Switzerland (opacity of ~700 meter water equivalent). We observe a direct correlation between middle-atmosphere seasonal temperature variations and muon rate. Muon rate variations are also sensitive to the abnormal atmosphere heating in January–February 2017, associated to a Sudden Stratospheric Warming. Estimates of the effective temperature coefficient for our particular case agree with theoretical models and with those calculated from large neutrino experiments under comparable conditions. Thus, portable muon detectors may be useful to (1) study seasonal and short-term middle-atmosphere dynamics, especially in locations where data are lacking such as midlatitudes, and (2) improve the calibration of the effective temperature coefficient for different opacity conditions. Furthermore, we highlight the importance of assessing the impact of temperature on muon rate variations when considering geophysical applications. Depending on latitude and opacity conditions, this effect may be large enough to hide subsurface density variations due to changes in groundwater content and should therefore be removed from the time series.Fil: Tramontini, Matías Leandro. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Departamento de Geofísica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad de Lyon 3; FranciaFil: Rosas Carbajal, Marina Andrea. Institut de Physique Du Globe de Paris; FranciaFil: Nussbaum, C.. Swiss Geological Survey At Swisstopo; SuizaFil: Gibert, D.. Universite de Rennes I; FranciaFil: Marteau, Jacques Emmanuel. Universidad de Lyon 3; Franci