Imputation of missing sub-hourly precipitation data in a large sensor network : a machine learning approach

This research was supported by a UKRI-NERC Constructing a Digital Environment Strategic Priority grant “Engineering Transformation for the Integration of Sensor Networks: A Feasibility Study” [NE/S016236/1 & NE/S016244/1].Peer reviewedPostprin

Preclinical Development of ADCT-601, a Novel Pyrrolobenzodiazepine Dimer-based Antibody-drug Conjugate Targeting AXL-expressing Cancers

AXL, a tyrosine kinase receptor that is overexpressed in many solid and hematologic malignancies, facilitates cancer progression and is associated with poor clinical outcomes. Importantly, drug-induced expression of AXL results in resistance to conventional chemotherapy and targeted therapies. Together with its presence on multiple cell types in the tumor immune microenvironment, these features make it an attractive therapeutic target for AXL-expressing malignancies. ADCT-601 (mipasetamab uzoptirine) is an AXL-targeted antibody–drug conjugate (ADC) comprising a humanized anti-AXL antibody site specifically conjugated using GlycoConnect technology to PL1601, which contains HydraSpace, a Val-Ala cleavable linker and the potent pyrrolobenzodiazepine (PBD) dimer cytotoxin SG3199. This study aimed to validate the ADCT-601 mode of action and evaluate its efficacy in vitro and in vivo, as well as its tolerability and pharmacokinetics. ADCT-601 bound to both soluble and membranous AXL, and was rapidly internalized by AXL-expressing tumor cells, allowing release of PBD dimer, DNA interstrand cross-linking, and subsequent cell killing. In vivo, ADCT-601 had potent and durable antitumor activity in a wide variety of human cancer xenograft mouse models, including patient-derived xenograft models with heterogeneous AXL expression where ADCT-601 antitumor activity was markedly superior to an auristatin-based comparator ADC. Notably, ADCT-601 had antitumor activity in a monomethyl auristatin E–resistant lung-cancer model and synergized with the PARP inhibitor olaparib in a BRCA1-mutated ovarian cancer model. ADCT-601 was well tolerated at doses of up to 6 mg/kg and showed excellent stability in vivo. These preclinical results warrant further evaluation of ADCT-601 in the clinic

Economic Impacts of Non-Native Forest Insects in the Continental United States

Reliable estimates of the impacts and costs of biological invasions are critical to developing credible management, trade and regulatory policies. Worldwide, forests and urban trees provide important ecosystem services as well as economic and social benefits, but are threatened by non-native insects. More than 450 non-native forest insects are established in the United States but estimates of broad-scale economic impacts associated with these species are largely unavailable. We developed a novel modeling approach that maximizes the use of available data, accounts for multiple sources of uncertainty, and provides cost estimates for three major feeding guilds of non-native forest insects. For each guild, we calculated the economic damages for five cost categories and we estimated the probability of future introductions of damaging pests. We found that costs are largely borne by homeowners and municipal governments. Wood- and phloem-boring insects are anticipated to cause the largest economic impacts by annually inducing nearly $1.7 billion in local government expenditures and approximately$830 million in lost residential property values. Given observations of new species, there is a 32% chance that another highly destructive borer species will invade the U.S. in the next 10 years. Our damage estimates provide a crucial but previously missing component of cost-benefit analyses to evaluate policies and management options intended to reduce species introductions. The modeling approach we developed is highly flexible and could be similarly employed to estimate damages in other countries or natural resource sectors

Plankton as prevailing conditions: A surveillance role for plankton indicators within the Marine Strategy Framework Directive

https://www.sciencedirect.com/science/article/pii/S0308597X17306711The Marine Strategy Framework Directive (MSFD) uses an indicator-based approach for ecosystem assessment; indicators of the state of ecosystem components ('state indicators') are used to determine whether, or not, these ecosystem components are at ‘Good Environmental Status’ relative to prevailing oceanographic conditions. Here, it is illustrated that metrics of change in plankton communities frequently provide indications of changing prevailing oceanographic conditions. Plankton indicators can therefore provide useful diagnostic information when interpreting results and determining assessment outcomes for analyses of state indicators across the food web. They can also perform a strategic role in assessing these state indicators by influencing target setting and management measures. In addition to their primary role of assessing the state of pelagic habitats against direct anthropogenic pressures, plankton community indicators can therefore also fulfil an important 'surveillance' role for other state indicators used to formally assess biodiversity status under the MSFD

Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes

Abstract: Purpose: This review of sediment source fingerprinting assesses the current state-of-the-art, remaining challenges and emerging themes. It combines inputs from international scientists either with track records in the approach or with expertise relevant to progressing the science. Methods: Web of Science and Google Scholar were used to review published papers spanning the period 2013–2019, inclusive, to confirm publication trends in quantities of papers by study area country and the types of tracers used. The most recent (2018–2019, inclusive) papers were also benchmarked using a methodological decision-tree published in 2017. Scope: Areas requiring further research and international consensus on methodological detail are reviewed, and these comprise spatial variability in tracers and corresponding sampling implications for end-members, temporal variability in tracers and sampling implications for end-members and target sediment, tracer conservation and knowledge-based pre-selection, the physico-chemical basis for source discrimination and dissemination of fingerprinting results to stakeholders. Emerging themes are also discussed: novel tracers, concentration-dependence for biomarkers, combining sediment fingerprinting and age-dating, applications to sediment-bound pollutants, incorporation of supportive spatial information to augment discrimination and modelling, aeolian sediment source fingerprinting, integration with process-based models and development of open-access software tools for data processing. Conclusions: The popularity of sediment source fingerprinting continues on an upward trend globally, but with this growth comes issues surrounding lack of standardisation and procedural diversity. Nonetheless, the last 2 years have also evidenced growing uptake of critical requirements for robust applications and this review is intended to signpost investigators, both old and new, towards these benchmarks and remaining research challenges for, and emerging options for different applications of, the fingerprinting approach

Placental transfer of Fc-containing biopharmaceuticals across species, an industry survey analysis

BACKGROUND: Understanding species differences in placental transfer of Fc-containing biopharmaceuticals (particularly monoclonal antibodies) will improve human risk extrapolation from nonclinical embryo-fetal development toxicity data. METHODS: Maternal and fetal concentration data from 10, 15, 8, and 34 Fc-containing biopharmaceuticals in the rabbit, rat, mouse, and cynomolgus monkey, respectively, from an industry survey were analyzed for trends in placental transfer. RESULTS AND CONCLUSIONS: Embryonic (before the end of organogenesis) exposure was assessed in one molecule each in rabbit, rat, and mouse, but detectable levels were present only in rodents. In rodents, fetal levels remained relatively constant from gestation day (GD) 16 and 17 until the end of gestation, while maternal levels decreased or remained constant in rat and decreased in mice. In rabbits, following a last dose on GD 19, fetal levels increased markedly in late gestation while maternal levels decreased. In the cynomolgus monkey, fetal levels increased substantially from GD 50 to 100 and were maintained relatively constant through parturition (approximately GD 165). Based on available data of both the monkey and rabbit, IgG1 molecules appeared to transfer more readily than other isotypes in late gestation. Across all species, there was no differential transfer based on pharmacologic target being soluble or membrane bound. Within each species there was a correlation between maternal and fetal exposure, suggesting it may be possible to predict fetal exposures from maternal exposure data. These nonclinical data (both temporal and quantitative aspects) are discussed in a comparative context relative to our understanding of IgG placental transfer in humans. © 2014 Wiley Periodicals, Inc

Reducing grid energy consumption through choice of resource allocation method

Energy consumption is an increasingly important consideration in computing. High-performance computing environments consume substantial amounts of energy, at an increasing financial and environmental cost. We explore the possibility of reducing the energy consumption of a grid of heterogeneous computers through appropriate resource allocation strategies. We examine a number of possible grid workload scenarios and analyse the impact of different resource allocation mechanisms on energy consumption. We perform this analysis first on a cluster of heterogeneous nodes, then on a grid of several clusters. Our results show that different resource allocation mechanisms perform better under different scenarios, and that selection of an appropriate resource allocation mechanism can significantly reduce the total grid energy consumption

Resource allocation to conserve energy in distributed computing

Energy consumption is an issue in grid computing. There has been substantial research into grid resource allocation, but little research on energy aware resource allocation. We propose that altering the resource allocation mechanism to incorporate node power and performance data can make a substantial difference to both the time taken to execute tasks and the energy consumed by the grid. This paper examines the use of three simple economic resource allocation mechanisms through simulation. We discover that different mechanisms perform better under different circumstances, and that changing the resource allocation mechanism to incorporate the power and performance information of individual nodes can result in a substantial difference to the time taken to execute tasks, and over time can make a marked difference to the total energy consumption of the grid resource

Reducing energy consumption in distributed computing through economic resource allocation

Energy consumption is an increasingly important consideration in computing. High-performance computing environments consume substantial amounts of energy and the cost of energy is increasing. We explore the possibility of reducing the energy consumption of a grid of heterogeneous computers through appropriate resource allocation strategies. We examine a number of possible grid workload scenarios and analyse the impact of different resource allocation mechanisms on energy consumption and time taken to execute tasks. We perform this analysis first on a cluster of heterogeneous nodes and then scale up the experiment to a grid of multiple clusters. Our results show that different resource allocation mechanisms perform better under different scenarios, and that selection of the resource allocation mechanism can significantly alter grid energy consumption