How can remote sensing contribute in groundwater modeling?

Groundwater resources assessment, modeling and management are hampered considerably by a lack of data, especially in semi-arid and arid environments with a weak observation infrastructure. Usually, only a limited number of point measurements are available, while groundwater models need spatial and temporal distributions of input and calibration data. If such data are not available, models cannot play their proper role in decision support as they are notoriously underdetermined and uncertain. Recent developments in remote sensing have opened new sources for distributed spatial data. As the relevant entities such as water fluxes, heads or transmissivities cannot be observed directly by remote sensing, ways have to be found to link the observable quantities to input data required by the model. An overview of the possibilities for employing remote-sensing observations in groundwater modeling is given, supported by examples in Botswana and China. The main possibilities are: (1) use of remote-sensing data to create some of the spatially distributed input parameter sets for a model, and (2) constraining of models during calibration by spatially distributed data derived from remote sensing. In both, models can be improved conceptually and quantitativel

An automated method to build groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs

Abstract. Large-scale integrated hydrological models are important decision support tools in water resources management. The largest source of uncertainty in such models is the hydrostratigraphic model. Geometry and configuration of hydrogeological units are often poorly determined from hydrogeological data alone. Due to sparse sampling in space, lithological borehole logs may overlook structures that are important for groundwater flow at larger scales. Good spatial coverage along with high spatial resolution makes airborne time-domain electromagnetic (AEM) data valuable for the structural input to large-scale groundwater models. We present a novel method to automatically integrate large AEM data-sets and lithological information into large-scale hydrological models. Clay-fraction maps are produced by translating geophysical resistivity into clay-fraction values using lithological borehole information. Voxel models of electrical resistivity and clay fraction are classified into hydrostratigraphic zones using k-means clustering. Hydraulic conductivity values of the zones are estimated by hydrological calibration using hydraulic head and stream discharge observations. The method is applied to a Danish case study. Benchmarking hydrological performance by comparison of simulated hydrological state variables, the cluster model performed competitively. Calibrations of 11 hydrostratigraphic cluster models with 1–11 hydraulic conductivity zones showed improved hydrological performance with increasing number of clusters. Beyond the 5-cluster model hydrological performance did not improve. Due to reproducibility and possibility of method standardization and automation, we believe that hydrostratigraphic model generation with the proposed method has important prospects for groundwater models used in water resources management.</jats:p

In vitro efficacy of artemisinin-based treatments against SARS-CoV-2

Effective and affordable treatments for patients suffering from coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are needed. We report in vitro efficacy of Artemisia annua extracts as well as artemisinin, artesunate, and artemether against SARS-CoV-2. The latter two are approved active pharmaceutical ingredients of anti-malarial drugs. Concentration–response antiviral treatment assays, based on immunostaining of SARS-CoV-2 spike glycoprotein, revealed that treatment with all studied extracts and compounds inhibited SARS-CoV-2 infection of VeroE6 cells, human hepatoma Huh7.5 cells and human lung cancer A549-hACE2 cells, without obvious influence of the cell type on antiviral efficacy. In treatment assays, artesunate proved most potent (range of 50% effective concentrations (EC50) in different cell types: 7–12 µg/mL), followed by artemether (53–98 µg/mL), A. annua extracts (83–260 µg/mL) and artemisinin (151 to at least 208 µg/mL). The selectivity indices (SI), calculated based on treatment and cell viability assays, were mostly below 10 (range 2 to 54), suggesting a small therapeutic window. Time-of-addition experiments in A549-hACE2 cells revealed that artesunate targeted SARS-CoV-2 at the post-entry level. Peak plasma concentrations of artesunate exceeding EC50 values can be achieved. Clinical studies are required to further evaluate the utility of these compounds as COVID-19 treatment

Hepatitis C virus cell-cell transmission and resistance to direct-acting antiviral agents

Hepatitis C virus (HCV) is transmitted between hepatocytes via classical cell entry but also uses direct cell-cell transfer to infect neighboring hepatocytes. Viral cell-cell transmission has been shown to play an important role in viral persistence allowing evasion from neutralizing antibodies. In contrast, the role of HCV cell-cell transmission for antiviral resistance is unknown. Aiming to address this question we investigated the phenotype of HCV strains exhibiting resistance to direct-acting antivirals (DAAs) in state-of-the-art model systems for cell-cell transmission and spread. Using HCV genotype 2 as a model virus, we show that cell-cell transmission is the main route of viral spread of DAA-resistant HCV. Cell-cell transmission of DAA-resistant viruses results in viral persistence and thus hampers viral eradication. We also show that blocking cell-cell transmission using host-targeting entry inhibitors (HTEIs) was highly effective in inhibiting viral dissemination of resistant genotype 2 viruses. Combining HTEIs with DAAs prevented antiviral resistance and led to rapid elimination of the virus in cell culture model. In conclusion, our work provides evidence that cell-cell transmission plays an important role in dissemination and maintenance of resistant variants in cell culture models. Blocking virus cell-cell transmission prevents emergence of drug resistance in persistent viral infection including resistance to HCV DAAs

SARS-CoV-2 Production in a Scalable High Cell Density Bioreactor

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has demonstrated the value of pursuing different vaccine strategies. Vaccines based on whole viruses, a widely used vaccine technology, depend on efficient virus production. This study aimed to establish SARS-CoV-2 production in the scalable packed-bed CelCradle(TM) 500-AP bioreactor. CelCradle(TM) 500-AP bottles with 0.5 L working volume and 5.5 g BioNOC™ II carriers were seeded with 1.5 × 10(8) Vero (WHO) cells, approved for vaccine production, in animal component-free medium and infected at a multiplicity of infection of 0.006 at a total cell number of 2.2–2.5 × 10(9) cells/bottle seven days post cell seeding. Among several tested conditions, two harvests per day and a virus production temperature of 33 °C resulted in the highest virus yield with a peak SARS-CoV-2 infectivity titer of 7.3 log(10) 50% tissue culture infectious dose (TCID(50))/mL at 72 h post-infection. Six harvests had titers of ≥6.5 log(10) TCID(50)/mL, and a total of 10.5 log(10) TCID(50) were produced in ~5 L. While trypsin was reported to enhance virus spread in cell culture, addition of 0.5% recombinant trypsin after infection did not improve virus yields. Overall, we demonstrated successful animal component-free production of SARS-CoV-2 in well-characterized Vero (WHO) cells in a scalable packed-bed bioreactor