A collaboratively derived international research agenda on legislative science advice

The quantity and complexity of scientific and technological information provided to policymakers have been on the rise for decades. Yet little is known about how to provide science advice to legislatures, even though scientific information is widely acknowledged as valuable for decision-making in many policy domains. We asked academics, science advisers, and policymakers from both developed and developing nations to identify, review and refine, and then rank the most pressing research questions on legislative science advice (LSA). Experts generally agree that the state of evidence is poor, especially regarding developing and lower-middle income countries. Many fundamental questions about science advice processes remain unanswered and are of great interest: whether legislative use of scientific evidence improves the implementation and outcome of social programs and policies; under what conditions legislators and staff seek out scientific information or use what is presented to them; and how different communication channels affect informational trust and use. Environment and health are the highest priority policy domains for the field. The context-specific nature of many of the submitted questions—whether to policy issues, institutions, or locations—suggests one of the significant challenges is aggregating generalizable evidence on LSA practices. Understanding these research needs represents a first step in advancing a global agenda for LSA research.Fil: Akerlof, Karen. George Mason University; Estados UnidosFil: Tyler, Chris. University College London;Fil: Foxen, Sarah Elizabeth. University College London;Fil: Heath, Erin. American Association for the Advancement of Science; Estados UnidosFil: Gual Soler, Marga. American Association for the Advancement of Science; Estados UnidosFil: Allegra, Alessandro. University College London;Fil: Cloyd, Emily T.. American Association for the Advancement of Science; Estados UnidosFil: Hird, John A.. University of Massachussets; Estados UnidosFil: Nelson, Selena M.. George Mason University; Estados UnidosFil: Nguyen, Christina T.. George Mason University; Estados UnidosFil: Gonnella, Cameryn J.. Herndon; Estados UnidosFil: Berigan, Liam A.. Kansas State University; Estados UnidosFil: Abeledo, Carlos R.. Universidad de Buenos Aires; ArgentinaFil: Al Yakoub, Tamara Adel. Yarmouk University; JordaniaFil: Andoh, Harris Francis. Tshwane University Of Technology; Sudáfrica. Tshwane University of Technology; GhanaFil: dos Santos Boeira, Laura. Veredas Institute; BrasilFil: van Boheemen, Pieter. Rathenau Instituut; Países BajosFil: Cairney, Paul. University of Stirling; Reino UnidoFil: Cook Deegan, Robert. Arizona State University; Estados UnidosFil: Costigan, Gavin. Foundation For Science And Technology; Reino UnidoFil: Dhimal, Meghnath. Nepal Health Research Council; NepalFil: Di Marco, Martín Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Sociales. Instituto de Investigaciones "Gino Germani"; ArgentinaFil: Dube, Donatus. National University of Science and Technology; Zimbabu

The respiratory virome and exacerbations in patients with chronic obstructive pulmonary disease

Introduction Exacerbations are major contributors to morbidity and mortality in patients with chronic obstructive pulmonary disease (COPD), and respiratory bacterial and viral infections are an important trigger. However, using conventional diagnostic techniques, a causative agent is not always found. Metagenomic next-generation sequencing (mNGS) allows analysis of the complete virome, but has not yet been applied in COPD exacerbations. Objectives To study the respiratory virome in nasopharyngeal samples during COPD exacerbations using mNGS. Study design 88 nasopharyngeal swabs from 63 patients from the Bergen COPD Exacerbation Study (2006-2010) were analysed by mNGS and in-house qPCR for respiratory viruses. Both DNA and RNA were sequenced simultaneously using an Illumina library preparation protocol with in-house adaptations. Results By mNGS, 24/88 samples tested positive. Sensitivity and specificity, as compared with PCR, were 96% and 98% for diagnostic targets (23/24 and 1093/1120, respectively). Additional viral pathogens detected by mNGS were herpes simplex virus type 1 and coronavirus OC43. A positive correlation was found between Cq value and mNGS viral normalized species reads (log value) (p = 0.002). Patients with viral pathogens had lower percentages of bacteriophages (p<0.001). No correlation was found between viral reads and clinical markers. Conclusions The mNGS protocol used was highly sensitive and specific for semi-quantitative detection of respiratory viruses. Excellent negative predictive value implicates the power of mNGS to exclude any pathogenic respiratory viral infectious cause in one test, with consequences for clinical decision making. Reduced abundance of bacteriophages in COPD patients with viral pathogens implicates skewing of the virome during infection, with potential consequences for the bacterial populations, during infection

Robot navigation in orchards with localization based on Particle filter and Kalman filter

Fruit production in orchards currently relies on high labor inputs. Concerns arising from the increasing labor cost and shortage of labor can be mitigated by the availability of an autonomous orchard robot. A core feature for every mobile orchard robot is autonomous navigation, which depends on sensor-based robot localization in the orchard environment. This research validated the applicability of two probabilistic localization algorithms that used a 2D LIDAR scanner for in-row robot navigation in orchards. The first localization algorithm was a Particle filter (PF) with a laser beam model, and the second was a Kalman filter (KF) with a line-detection algorithm. We evaluated the performance of the two algorithms when autonomously navigating a robot in a commercial Dutch apple orchard. Two experiments were executed to assess the navigation performance of the two algorithms under comparable conditions. The first experiment assessed the navigation accuracy, whereas the second experiment tested the algorithms’ robustness. In the first experiment, when the robot was driven with 0.25 m/s the root mean square error (RMSE) of the lateral deviation was 0.055 m with the PF algorithm and 0.087 m with the KF algorithm. At 0.50 m/s, the RMSE was 0.062 m with the PF algorithm and 0.091 m with the KF algorithm. In addition, with the PF the lateral deviations were equally distributed to both sides of the optimal navigation line, whereas with the KF the robot tended to navigate to the left of the optimal line. The second experiment tested the algorithms’ robustness to cope with missing trees in six different tree row patterns. The PF had a lower RMSE of the lateral deviation in five tree patterns. In three out of the six patterns, navigation with the KF led to lateral deviations that were biased to the left of the optimal line. The angular deviations of the PF and the KF were in the same range in both experiments. From the results, we conclude that a PF with laser beam model is to be preferred over a line-based KF for the in-row navigation of an autonomous orchard robot

Robot navigation in orchards with localization based on Particle filter and Kalman filter

Fruit production in orchards currently relies on high labor inputs. Concerns arising from the increasing labor cost and shortage of labor can be mitigated by the availability of an autonomous orchard robot. A core feature for every mobile orchard robot is autonomous navigation, which depends on sensor-based robot localization in the orchard environment. This research validated the applicability of two probabilistic localization algorithms that used a 2D LIDAR scanner for in-row robot navigation in orchards. The first localization algorithm was a Particle filter (PF) with a laser beam model, and the second was a Kalman filter (KF) with a line-detection algorithm. We evaluated the performance of the two algorithms when autonomously navigating a robot in a commercial Dutch apple orchard. Two experiments were executed to assess the navigation performance of the two algorithms under comparable conditions. The first experiment assessed the navigation accuracy, whereas the second experiment tested the algorithms’ robustness. In the first experiment, when the robot was driven with 0.25 m/s the root mean square error (RMSE) of the lateral deviation was 0.055 m with the PF algorithm and 0.087 m with the KF algorithm. At 0.50 m/s, the RMSE was 0.062 m with the PF algorithm and 0.091 m with the KF algorithm. In addition, with the PF the lateral deviations were equally distributed to both sides of the optimal navigation line, whereas with the KF the robot tended to navigate to the left of the optimal line. The second experiment tested the algorithms’ robustness to cope with missing trees in six different tree row patterns. The PF had a lower RMSE of the lateral deviation in five tree patterns. In three out of the six patterns, navigation with the KF led to lateral deviations that were biased to the left of the optimal line. The angular deviations of the PF and the KF were in the same range in both experiments. From the results, we conclude that a PF with laser beam model is to be preferred over a line-based KF for the in-row navigation of an autonomous orchard robot.</p

HIV-1 resistance against dolutegravir fluctuates rapidly alongside erratic treatment adherence: a case report

ABSTRACT: Objectives: We report a case of incomplete HIV-1 suppression on a dolutegravir, lamivudine, and abacavir single-tablet regimen with the emergence of the H51Y and G118R integrase resistance mutations. Methods: Integrase sequencing was performed retrospectively by Sanger and next-generation sequencing. Rates of emergence and decline of resistance mutations were calculated using next-generation sequencing data. Dolutegravir plasma concentrations were measured by ultra-performance liquid chromatography-tandem mass spectrometry. The effects of H51Y and G118R on infectivity, fitness, and susceptibility to dolutegravir were quantified using cell-based assays. Results: During periods of non-adherence to treatment, mutations were retrospectively documented only by next-generation sequencing. Misdiagnosis by Sanger sequencing was caused by the rapid decline of mutant strains within the retroviral population. This observation was also true for a M184V lamivudine-resistant reverse transcriptase mutation found in association with integrase mutations on single HIV genomes. Resistance rebound upon treatment re-initiation was swift (>8000 copies per day). Next-generation sequencing indicated cumulative adherence to treatment. Compared to WT HIV-1, relative infectivity was 73%, 38%, and 43%; relative fitness was 100%, 35%, and 10% for H51Y, G118R, and H51Y+G118R viruses, respectively. H51Y did not change the susceptibility to dolutegravir, but G188R and H51Y+G118R conferred 7- and 28-fold resistance, respectively. Conclusion: This case illustrates how poorly-fit drug-resistant viruses wax and wane alongside erratic treatment adherence and are easily misdiagnosed by Sanger sequencing. We recommend next-generation sequencing to improve the clinical management of incomplete virological suppression with dolutegravir