123 research outputs found

    A global surveillance system for crop diseases

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    To satisfy a growing demand for food, global agricultural production must increase by 70% by 2050. However, pests and crop diseases put global food supplies at risk. Worldwide, yield losses caused by pests and diseases are estimated to average 21.5% in wheat, 30.0% in rice, 22.6% in maize, 17.2% in potato, and 21.4% in soybean (1); these crops account for half of the global human calorie intake (2). Climate change and global trade drive the distribution, host range, and impact of plant diseases (3), many of which can spread or reemerge after having been under control (4). Though many national and regional plant protection organizations (NPPOs and RPPOs) work to monitor and contain crop disease outbreaks, many countries, particularly low-income countries (LICs), do not efficiently exchange information, delaying coordinated responses to prevent disease establishment and spread. To improve responses to unexpected crop disease spread, we propose a Global Surveillance System (GSS) that will extend and adapt established biosecurity practices and networking facilities into LICs, enabling countries and regions to quickly respond to emerging disease outbreaks to stabilize food supplies, enhancing global food protection

    Prima facie reasons to question enclosed intellectual property regimes and favor open-source regimes for germplasm

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    In principle, intellectual property protections (IPPs) promote and protect important but costly investment in research and development. However, the empirical reality of IPPs has often gone without critical evaluation, and the potential of alternative approaches to lend equal or greater support for useful innovation is rarely considered. In this paper, we review the mounting evidence that the global intellectual property regime (IPR) for germplasm has been neither necessary nor sufficient to generate socially beneficial improvements in crop plants and maintain agrobiodiversity. Instead, based on our analysis, the dominant global IPR appears to have contributed to consolidation in the seed industry while failing to genuinely engage with the potential of alternatives to support social goods such as food security, adaptability, and resilience. The dominant IPR also constrains collaborative and cumulative plant breeding processes that are built upon the work of countless farmers past and present. Given the likely limits of current IPR, we propose that social goods in agriculture may be better supported by alternative approaches, warranting a rapid move away from the dominant single-dimensional focus on encouraging innovation through ensuring monopoly profits to IPP holders

    Comparison of diurnal variations, gestational age and gender related differences in fetal heart rate (FHR) parameters between appropriate-for-gestational-age (AGA) and small-for-gestational-age (SGA) fetuses in the home environment

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    Objective To assess the influence of gender, time of the day and gestational age on fetal heart rate (FHR) parameters between appropriate-for-gestational-age (AGA) and small-for-gestational age (SGA) fetuses using a portable fetal ECG monitor employed in the home setting. Methods We analysed and compared the antenatal FHR data collected in the home setting on 61 healthy pregnant women with singleton pregnancies from 24 weeks gestation. Of the 61 women, 31 had SGA fetuses (estimated fetal weight below the tenth gestational centile) and 30 were pregnant with AGA fetuses. FHR recordings were collected for up to 20 h. Two 90 min intervals were deliberately chosen retrospectively with respect to signal recording quality, one during day-time and one at night-time for comparison. Results Overall, success rate of the fetal abdominal ECG in the AGA fetuses was 75.7% compared to 48.6% in the SGA group. Based on randomly selected episodes of heart rate traces where recording quality exceeded 80% we were able to show a marginal difference between day and night-time recordings in AGA vs. SGA fetuses beyond 32 weeks of gestation. A selection bias in terms of covering different representation periods of fetal behavioural states cannot be excluded. In contrast to previous studies, we neither controlled maternal diet and activity nor measured maternal blood hormone and heart rate as all mothers were monitored in the home environment. Conclusion Based on clinically unremarkable, but statistically significant differences in the FHR parameters between the AGA and SGA group we suggest that further studies with large sample size are required to assess the clinical value of antenatal fetal ECG monitoring

    Is short-term-variation of fetal-heart-rate a better predictor of fetal acidaemia in labour? A feasibility study

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    Background Continuous intrapartum fetal monitoring is challenging and its clinical benefits are debated. The project evaluated whether short-term-variation (STV) and other computerised fetal heart rate (FHR) parameters (baseline FHR, long-term-variation, accelerations and decelerations) predicted acidaemia at birth. The aims of the study were to assess the changes in FHR pattern during labour and determine the feasibility of undertaking a definitive trial by reporting the practicalities of using the monitoring device, participant recruitment, data collection and staff training. Methods 200 high-risk women carrying a term singleton, non-anomalous fetus, requiring continuous FHR monitoring in labour were consented to participate from the Jessop Wing maternity unit, Sheffield, UK. The trans-abdominal fetal ECG monitor was placed as per clinical protocol. During the monitoring session, clinicians were blinded to the computerised FHR parameters. We analysed the last hour of the FHR and its ability to predict umbilical arterial blood pH <7.20 using receiver operator characteristics (ROC) curves. Results Of 200 women, 137 cases were excluded as either the monitor did not work from the onset of labour (n = 30), clinical staff did not return or used the monitor on another patient (n = 37), umbilical cord blood not obtained (n = 25), FHR data not recorded within an hour of birth (n = 34) and other reasons (n = 11). In 63 cases included in the final analysis, the computer-derived FHR parameters did not show significant correlation with umbilical artery cord pH <7.20. Labour was associated with a significant increase in short and long term variation of FHR and number of deceleration (P<0.001). However, baseline FHR decreased significantly before delivery (P<0.001). Conclusions The project encountered a number of challenges, with learning points crucial to informing the design of a large study to evaluate the potential place of intrapartum computerised FHR parameters, using abdominal fetal ECG monitor before its clinical utility and more widespread adoption can be ascertained

    Granger Causality Analysis of Steady-State Electroencephalographic Signals during Propofol-Induced Anaesthesia

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    Changes in conscious level have been associated with changes in dynamical integration and segregation among distributed brain regions. Recent theoretical developments emphasize changes in directed functional (i.e., causal) connectivity as reflected in quantities such as ‘integrated information’ and ‘causal density’. Here we develop and illustrate a rigorous methodology for assessing causal connectivity from electroencephalographic (EEG) signals using Granger causality (GC). Our method addresses the challenges of non-stationarity and bias by dividing data into short segments and applying permutation analysis. We apply the method to EEG data obtained from subjects undergoing propofol-induced anaesthesia, with signals source-localized to the anterior and posterior cingulate cortices. We found significant increases in bidirectional GC in most subjects during loss-of-consciousness, especially in the beta and gamma frequency ranges. Corroborating a previous analysis we also found increases in synchrony in these ranges; importantly, the Granger causality analysis showed higher inter-subject consistency than the synchrony analysis. Finally, we validate our method using simulated data generated from a model for which GC values can be analytically derived. In summary, our findings advance the methodology of Granger causality analysis of EEG data and carry implications for integrated information and causal density theories of consciousness
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