Proceedings of the 23rd annual Central Plains irrigation conference

Presented at Proceedings of the 23rd annual Central Plains irrigation conference held in Burlington, Colorado on February 22-23, 2011.Includes bibliographical references.Irrigation water management practices could greatly benefit from using soil moisture sensors that accurately measure soil water content or potential. Therefore, an assessment on soil moisture sensor reading accuracy is important. In this study, a performance evaluation of selected sensor calibration was performed considering factory- laboratory- and field-based calibrations. The selected sensors included: the Digitized Time Domain Transmissometry (TDT, Acclima, Inc., Meridian, ID) which is a volumetric soil water content sensor, and a resistance-based soil water potential sensor (Watermark 200, Irrometer Company, Inc., Riverside, CA). Measured soil water content/potential values, on a sandy clay loam soil, were compared with corresponding values derived from gravimetric samples. Under laboratory and field conditions, the factory-based calibrations for the TDT sensor accurately measured volumetric soil water content. Therefore, the use of the TDT sensor for irrigation water management seems very promising. Laboratory tests indicated that a linear calibration for the TDT sensor and a logarithmic calibration for the watermark sensor improved the factory calibration. In the case of the watermark, a longer set of field data is needed to properly establish its accuracy and reliability

Recombination between phages and CRISPR-cas loci facilitates horizontal gene transfer in staphylococci

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record.CRISPR (clustered regularly interspaced short palindromic repeats) loci and their associated (cas) genes encode an adaptive immune system that protects prokaryotes from viral1 and plasmid2 invaders. Following viral (phage) infection, a small fraction of the prokaryotic cells are able to integrate a small sequence of the invader's genome into the CRISPR array1. These sequences, known as spacers, are transcribed and processed into small CRISPR RNA guides3-5 that associate with Cas nucleases to specify a viral target for destruction6-9. Although CRISPR-cas loci are widely distributed throughout microbial genomes and often display hallmarks of horizontal gene transfer10-12, the drivers of CRISPR dissemination remain unclear. Here, we show that spacers can recombine with phage target sequences to mediate a form of specialized transduction of CRISPR elements. Phage targets in phage 85, ΦNM1, ΦNM4 and Φ12 can recombine with spacers in either chromosomal or plasmid-borne CRISPR loci in Staphylococcus, leading to either the transfer of CRISPR-adjacent genes or the propagation of acquired immunity to other bacteria in the population, respectively. Our data demonstrate that spacer sequences not only specify the targets of Cas nucleases but also can promote horizontal gene transfer.Natural Environment Research Council (NERC)Biotechnology & Biological Sciences Research Council (BBSRC)Rita Allen Scholars ProgramNational Institutes of Health (NIH

Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection

Deep convective updraft invigoration via indirect effects of increased aerosol number concentration on cloud microphysics is frequently cited as a driver of correlations between aerosol and deep convection properties. Here, we critically evaluate the theoretical, modeling, and observational evidence for warm- and cold-phase invigoration pathways. Though warm-phase invigoration is plausible and theoretically supported via lowering of the supersaturation with increased cloud droplet concentration in polluted conditions, the significance of this effect depends on substantial supersaturation changes in real-world convective clouds that have not been observed. Much of the theoretical support for cold-phase invigoration depends on unrealistic assumptions of instantaneous freezing and unloading of condensate in growing, isolated updrafts. When applying more realistic assumptions, impacts on buoyancy from enhanced latent heating via fusion in polluted conditions are largely canceled by greater condensate loading. Many foundational observational studies supporting invigoration have several fundamental methodological flaws that render their findings incorrect or highly questionable. Thus, much of the evidence for invigoration has come from numerical modeling, but different models and setups have produced a vast range of results. Furthermore, modeled aerosol impacts on deep convection are rarely tested for robustness, and microphysical biases relative to observations persist, rendering many results unreliable for application to the real world. Without clear theoretical, modeling, or observational support, and given that enervation rather than invigoration may occur for some deep convective regimes and environments, it is entirely possible that the overall impact of cold-phase invigoration is negligible. Substantial mesoscale variability of dominant thermodynamic controls on convective updraft strength coupled with substantial updraft and aerosol variability in any given event are poorly quantified by observations and present further challenges to isolating aerosol effects. Observational isolation and quantification of convective invigoration by aerosols is also complicated by limitations of available cloud condensation nuclei and updraft speed proxies, aerosol correlations with meteorological conditions, and cloud impacts on aerosols. Furthermore, many cloud processes, such as entrainment and condensate fallout, modulate updraft strength and aerosol–cloud interactions, varying with cloud life cycle and organization, but these processes remain poorly characterized. Considering these challenges, recommendations for future observational and modeling research related to aerosol invigoration of deep convection are provided.</p

The DYMECS project: a statistical approach for the evaluation of convective storms in high-resolution NWP models

A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather services. However, this is not a panacea; significant systematic errors remain in the character of convective storms and rainfall distributions. The DYMECS project (Dynamical and Microphysical Evolution of Convective Storms) is taking a fundamentally new approach to evaluate and improve such models: rather than relying on a limited number of cases, which may not be representative, we have gathered a large database of 3D storm structures on 40 convective days using the Chilbolton radar in southern England. We have related these structures to storm life-cycles derived by tracking features in the rainfall from the UK radar network, and compared them statistically to storm structures in the Met Office model, which we ran at horizontal grid length between 1.5 km and 100 m, including simulations with different subgrid mixing length. We also evaluated the scale and intensity of convective updrafts using a new radar technique. We find that the horizontal size of simulated convective storms and the updrafts within them is much too large at 1.5-km resolution, such that the convective mass flux of individual updrafts can be too large by an order of magnitude. The scale of precipitation cores and updrafts decreases steadily with decreasing grid lengths, as does the typical storm lifetime. The 200-m grid-length simulation with standard mixing length performs best over all diagnostics, although a greater mixing length improves the representation of deep convective storms

Cloud-resolving model intercomparison of an MC3E squall line case: Part I-Convective updrafts

An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Z_e > 45 dBZ) than observed but a much narrower stratiform area. The magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speed are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Ze in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low-level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low-level vertical wind shear, and rear-inflow jets. Updraft velocity variability between schemes is mainly controlled by differences in simulated ice-related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no-ice simulations mainly because of scheme differences in collision-coalescence parameterizations

Replication in Cells of Hematopoietic Origin Is Necessary for Dengue Virus Dissemination

Dengue virus (DENV) is a mosquito-borne pathogen for which no vaccine or specific therapeutic is available. Although it is well established that dendritic cells and macrophages are primary sites of DENV replication, it remains unclear whether non-hematopoietic cellular compartments serve as virus reservoirs. Here, we exploited hematopoietic-specific microRNA-142 (miR-142) to control virus tropism by inserting tandem target sites into the virus to restrict replication exclusively in this cell population. In vivo use of this virus restricted infection of CD11b+, CD11c+, and CD45+ cells, resulting in a loss of virus spread, regardless of the route of administration. Furthermore, sequencing of the targeted virus population that persisted at low levels, demonstrated total excision of the inserted miR-142 target sites. The complete conversion of the virus population under these selective conditions suggests that these immune cells are the predominant sources of virus amplification. Taken together, this work highlights the importance of hematopoietic cells for DENV replication and showcases an invaluable tool for the study of virus pathogenesis

Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images

PURPOSEChest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associations between clinical and radiographic features as well as to assess the feasibility of deep learning applied to chest X-rays in the setting of an acute COVID-19 outbreak.METHODSA retrospective study of X-rays, clinical, and laboratory data was performed from 48 SARS-CoV-2 RT-PCR positive patients (age 60±17 years, 15 women) between February 22 and March 6, 2020 from a tertiary care hospital in Milan, Italy. Sixty-five chest X-rays were reviewed by two radiologists for alveolar and interstitial opacities and classified by severity on a scale from 0 to 3. Clinical factors (age, symptoms, comorbidities) were investigated for association with opacity severity and also with placement of central line or endotracheal tube. Deep learning models were then trained for two tasks: lung segmentation and opacity detection. Imaging characteristics were compared to clinical datapoints using the unpaired student’s t-test or Mann-Whitney U test. Cohen’s kappa analysis was used to evaluate the concordance of deep learning to conventional radiologist interpretation.RESULTSFifty-six percent of patients presented with alveolar opacities, 73% had interstitial opacities, and 23% had normal X-rays. The presence of alveolar or interstitial opacities was statistically correlated with age (P = 0.008) and comorbidities (P = 0.005). The extent of alveolar or interstitial opacities on baseline X-ray was significantly associated with the presence of endotracheal tube (P = 0.0008 and P = 0.049) or central line (P = 0.003 and P = 0.007). In comparison to human interpretation, the deep learning model achieved a kappa concordance of 0.51 for alveolar opacities and 0.71 for interstitial opacities.CONCLUSIONChest X-ray analysis in an acute COVID-19 outbreak showed that the severity of opacities was associated with advanced age, comorbidities, as well as acuity of care. Artificial intelligence tools based upon deep learning of COVID-19 chest X-rays are feasible in the acute outbreak setting

Regulation of microRNA biogenesis and turnover by animals and their viruses

Item does not contain fulltextMicroRNAs (miRNAs) are a ubiquitous component of gene regulatory networks that modulate the precise amounts of proteins expressed in a cell. Despite their small size, miRNA genes contain various recognition elements that enable specificity in when, where and to what extent they are expressed. The importance of precise control of miRNA expression is underscored by functional studies in model organisms and by the association between miRNA mis-expression and disease. In the last decade, identification of the pathways by which miRNAs are produced, matured and turned-over has revealed many aspects of their biogenesis that are subject to regulation. Studies in viral systems have revealed a range of mechanisms by which viruses target these pathways through viral proteins or non-coding RNAs in order to regulate cellular gene expression. In parallel, a field of study has evolved around the activation and suppression of antiviral RNA interference (RNAi) by viruses. Virus encoded suppressors of RNAi can impact miRNA biogenesis in cases where miRNA and small interfering RNA pathways converge. Here we review the literature on the mechanisms by which miRNA biogenesis and turnover are regulated in animals and the diverse strategies that viruses use to subvert or inhibit these processes