Renovation of Nitrogenous Wastewater Via Land Application

Removal of inorganic and organic nitrogen from wastewater prior to recharge of ground and surface waters can be accomplished by judicious land application. This study focused attention upon the feasibility of using sprinkler irrigation as the wastewater delivery system with coastal bermudagrass (Cynodon dactylon L.,var. coastal) pasture as the wastewater sink. One site was located on a Sawyer soil near El Dorado, while the other was located on a Savannah soil near Malvern. This report is limited to the renovation of surface waters. Results revealed that nitrogen concentration in runoff water from rainfall was substantially less than nitrogen concentration of the wastewater applied to the soil and similar to background levels. Such results support the consideration of land application as a viable wastewater disposal method

A Hydrologic Carbonate Chemistry Model of Flooded Rice Fields

Many flooded rice fields in Arkansas are irrigated with subterranean waters saturated or supersaturated with respect to calcium carbonate. Deposition of calcium carbonate from these waters largely occurs near field inlets and in flow areas (1). When sufficient amounts of calcium carbonate accumulate, soil pH rises and zinc deficiency occurs in rice seedlings grown on the affected soil (2). The use of zinc fertilizers has provided a short-term solution to the problem (3), but does not provide a water management alternative which would slow, stop or reverse the localized accumulation of calcium carbonate and concomitant soil pH increase

A Survey of Soils Irrigated with Arkansas River Water

Interest in the use of Arkansas River water for irrigation has increased recently as land adjacent to the river is converted to crop production and river water is considered as an alternative to depleted underground supplies. Since the Arkansas River can contain elevated concentrations of sodium chloride, this study was designed to determine if soil conditions adverse to crop growth were developing where river water has been used. The impact of river water on sites where river water was used as either the sole source for up to 3 years or as a supplement to another surface source for up to 20 years was evaluated. The mean surface and profile ESPs were both 3.7%, while parallel ECs for 1:2 soil:, water extract were 183 and 163 umhos/cm, respectively. Mean surface and profile chloride concentrations were 32 and 50 ug/g, respectively. Mean saturated hydraulic conductivities were 0.015 cm/hr for the surface soil. No data were obtained which suggested that the use of the Arkansas River under the conditions described above was detrimental to soil physical or chemical properties. Periodic reevaluation of this conclusion is suggested at sites where direct use of Arkansas River water continues for an extended period of time

The Ursinus Weekly, May 2, 1974

Two faculty members receive promotions • Committee of USGA proposes rule changes • Henry and Perreten get study grants • Dr. Parsons and Dr. Snyder to run Pa. Dutch course • Japanese will join U.C. summer school • U.C. to honor Rep. Ware at commencement • Dave Liscom to attend St. Andrews • Editorial: So what else is new?; Say something good • Italian philosopher is reborn • Alumni corner: The Ruby in debt • The ghost of Ursinus past • Ursinus students view unicorns • New 3-plus-3 plan: Degree in 3 years • Pi Gamma Mu names 10 to membership • Brazilians say “Saudade!” • U.C. students plan summers in Europe • Review: Springsteen’s rock rocks U.C. campus • ‘Chap’ resigns his U.C posts • Lacrosse trials select players • Bear runners looking good • Faculty focus: Georgia Ferrell leads winning gymnasts • Baseball squad facing tough competition • Two Ursinus basketball stars honoredhttps://digitalcommons.ursinus.edu/weekly/1015/thumbnail.jp

The importance of identity-by-state information for the accuracy of genomic selection

<p>Abstract</p> <p>Background</p> <p>It is commonly assumed that prediction of genome-wide breeding values in genomic selection is achieved by capitalizing on linkage disequilibrium between markers and QTL but also on genetic relationships. Here, we investigated the reliability of predicting genome-wide breeding values based on population-wide linkage disequilibrium information, based on identity-by-descent relationships within the known pedigree, and to what extent linkage disequilibrium information improves predictions based on identity-by-descent genomic relationship information.</p> <p>Methods</p> <p>The study was performed on milk, fat, and protein yield, using genotype data on 35 706 SNP and deregressed proofs of 1086 Italian Brown Swiss bulls. Genome-wide breeding values were predicted using a genomic identity-by-state relationship matrix and a genomic identity-by-descent relationship matrix (averaged over all marker loci). The identity-by-descent matrix was calculated by linkage analysis using one to five generations of pedigree data.</p> <p>Results</p> <p>We showed that genome-wide breeding values prediction based only on identity-by-descent genomic relationships within the known pedigree was as or more reliable than that based on identity-by-state, which implicitly also accounts for genomic relationships that occurred before the known pedigree. Furthermore, combining the two matrices did not improve the prediction compared to using identity-by-descent alone. Including different numbers of generations in the pedigree showed that most of the information in genome-wide breeding values prediction comes from animals with known common ancestors less than four generations back in the pedigree.</p> <p>Conclusions</p> <p>Our results show that, in pedigreed breeding populations, the accuracy of genome-wide breeding values obtained by identity-by-descent relationships was not improved by identity-by-state information. Although, in principle, genomic selection based on identity-by-state does not require pedigree data, it does use the available pedigree structure. Our findings may explain why the prediction equations derived for one breed may not predict accurate genome-wide breeding values when applied to other breeds, since family structures differ among breeds.</p

Cardiopulmonary toxicity of peat wildfire particulate matter and the predictive utility of precision cut lung slices

BackgroundEmissions from a large peat fire in North Carolina in 2008 were associated with increased hospital admissions for asthma and the rate of heart failure in the exposed population. Peat fires often produce larger amounts of smoke and last longer than forest fires, however few studies have reported on their toxicity. Moreover, reliable alternatives to traditional animal toxicity testing are needed to reduce the number of animals required for hazard identification and risk assessments.MethodsSize-fractionated particulate matter (PM; ultrafine, fine, and coarse) were obtained from the peat fire while smoldering (ENCF-1) or when nearly extinguished (ENCF-4). Extracted samples were analyzed for chemical constituents and endotoxin content. Female CD-1 mice were exposed via oropharyngeal aspiration to 100μg/mouse, and assessed for relative changes in lung and systemic markers of injury and inflammation. At 24h post-exposure, hearts were removed for ex vivo functional assessments and ischemic challenge. Lastly, 8mm diameter lung slices from CD-1 mice were exposed (11μg) ± co-treatment of PM with polymyxin B (PMB), an endotoxin-binding compound.ResultsOn an equi-mass basis, coarse ENCF-1PM had the highest endotoxin content and elicited the greatest pro-inflammatory responses in the mice including: increases in bronchoalveolar lavage fluid protein, cytokines (IL-6, TNF-α, and MIP-2), neutrophils and intracellular reactive oxygen species (ROS) production. Exposure to fine or ultrafine particles from either period failed to elicit significant lung or systemic effects. In contrast, mice exposed to ENCF-1 ultrafine PM developed significantly decreased cardiac function and greater post-ischemia-associated myocardial infarction. Finally, similar exposures to mouse lung slices induced comparable patterns of cytokine production; and these responses were significantly attenuated by PMB.ConclusionsThe findings suggest that exposure to coarse PM collected during a peat fire causes greater lung inflammation in association with endotoxin and ROS, whereas the ultrafine PM preferentially affected cardiac responses. In addition, lung tissue slices were shown to be a predictive, alternative assay to assess pro-inflammatory effects of PM of differing size and composition. Importantly, these toxicological findings were consistent with the cardiopulmonary health effects noted in epidemiologic reports from exposed populations

Heritability of Attractiveness to Mosquitoes

Female mosquitoes display preferences for certain individuals over others, which is determined by differences in volatile chemicals produced by the human body and detected by mosquitoes. Body odour can be controlled genetically but the existence of a genetic basis for differential attraction to insects has never been formally demonstrated. This study investigated heritability of attractiveness to mosquitoes by evaluating the response of Aedes aegypti (=Stegomyia aegypti) mosquitoes to odours from the hands of identical and non-identical twins in a dual-choice assay. Volatiles from individuals in an identical twin pair showed a high correlation in attractiveness to mosquitoes, while non-identical twin pairs showed a significantly lower correlation. Overall, there was a strong narrow-sense heritability of 0.62 (SE 0.124) for relative attraction and 0.67 (0.354) for flight activity based on the average of ten measurements. The results demonstrate an underlying genetic component detectable by mosquitoes through olfaction. Understanding the genetic basis for attractiveness could create a more informed approach to repellent development

Evaluation and Recommendations on Good Clinical Laboratory Practice Guidelines for Phase I–III Clinical Trials

Marcella Sarzotti-Kelsoe and colleagues harmonize various approaches to Good Clinical Laboratory Practice for clinical trials into a single set of recommendations

Mast Cells Express 11 beta-hydroxysteroid Dehydrogenase Type 1: A Role in Restraining Mast Cell Degranulation:a role in restraining mast cell degranulation

Mast cells are key initiators of allergic, anaphylactic and inflammatory reactions, producing mediators that affect vascular permeability, angiogenesis and fibrosis. Glucocorticoid pharmacotherapy reduces mast cell number, maturation and activation but effects at physiological levels are unknown. Within cells, glucocorticoid concentration is modulated by the 11β-hydroxysteroid dehydrogenases (11β-HSDs). Here we show expression and activity of 11β-HSD1, but not 11β-HSD2, in mouse mast cells with 11β-HSD activity only in the keto-reductase direction, regenerating active glucocorticoids (cortisol, corticosterone) from inert substrates (cortisone, 11-dehydrocorticosterone). Mast cells from 11β-HSD1-deficient mice show ultrastructural evidence of increased activation, including piecemeal degranulation and have a reduced threshold for IgG immune complex-induced mast cell degranulation. Consistent with reduced intracellular glucocorticoid action in mast cells, levels of carboxypeptidase A3 mRNA, a glucocorticoid-inducible mast cell-specific transcript, are lower in peritoneal cells from 11β-HSD1-deficient than control mice. These findings suggest that 11β-HSD1-generated glucocorticoids may tonically restrain mast cell degranulation, potentially influencing allergic, anaphylactic and inflammatory responses

Flexible modelling of spatial variation in agricultural field trials with the R package INLA

The objective of this paper was to fit different established spatial models for analysing agricultural field trials using the open-source R package INLA. Spatial variation is common in field trials, and accounting for it increases the accuracy of estimated genetic effects. However, this is still hindered by the lack of available software implementations. We compare some established spatial models and show possibilities for flexible modelling with respect to field trial design and joint modelling over multiple years and locations. We use a Bayesian framework and for statistical inference the integrated nested Laplace approximations (INLA) implemented in the R package INLA. The spatial models we use are the well-known independent row and column effects, separable first-order autoregressive ( AR1⊗AR1 ) models and a Gaussian random field (Matérn) model that is approximated via the stochastic partial differential equation approach. The Matérn model can accommodate flexible field trial designs and yields interpretable parameters. We test the models in a simulation study imitating a wheat breeding programme with different levels of spatial variation, with and without genome-wide markers and with combining data over two locations, modelling spatial and genetic effects jointly. The results show comparable predictive performance for both the AR1⊗AR1 and the Matérn models. We also present an example of fitting the models to a real wheat breeding data and simulated tree breeding data with the Nelder wheel design to show the flexibility of the Matérn model and the R package INLA