The Development of a Sex Pheromone Lure for the American Plum Borer, \u3ci\u3eEuzophera Semifuneralis\u3c/i\u3e (Lepidoptera: Pyralidae), a Major Pest of Cherry in Michigan.

Pheromone components of the American plum borer, Euzophera semifuneralis, were defined by use of the electroantennogram screening technique and capillary gas chromatographic retention times of sex pheromone gland constituents. Field studies showed that greatest attraction was achieved with a 1 mg load rate of a 4-component blend in a rubber septum. This blend consisted of a 2:1 ratio of Z,E-9,12-14:ALD and Z9-14:ALD and an equal amount of the corresponding alcohols in a 2:1 ratio, respectively. Commercial lures were used to compare the flight patterns of the American plum borer, peachtree borer (Synanthedon exitiosa), and lesser peachtree borer (Synanthedon pictipes) adults in Michigan in 1988

Natural Enemies of Cranberry Fruitworm, \u3ci\u3eAcrobasis Vaccinii\u3c/i\u3e, (Lepidoptera: Pyraudae) in Michigan Highbush Blueberries

A two-year study was conducted in Michigan highbush blueberries to determine the complex of parasitoids attacking cranberry fruitworm, Acrobasis vaccinii. Eight parasitoid species and one fungal pathogen were collected. Parasitism of collected hosts ranged from 6.6% to 28.1%. The more common larval parasitoid encountered was Campoletis patsuiketorum (Hymenoptera: Ichneumonidae). The more common parasitoid recovered from fruitworm hibernacula was Villa lateralis (Diptera: Bombyliidae). This study documented six unreported natural enemies of cranberry fruitworm, including C. patsuiketorum; V. lateralis; Diadegma compressum (Hymenoptera: Ichneumonidae); Compsilura concinnata (Diptera: Tachinidae); Memorilla pyste (Diptera: Tachinidae); an undescribed Microtypus species (Hymenoptera: Braconidae); and a fungal pathogen, Paecilomyces near farinosus. This is the first known host association for the undescribed Microtypus species, and increases the known parasitoid complex of cranberry fruitworm to 17 species

A Detailed Hydro-Economic Model for Assessing the Effects of Surface Water and Groundwater Policies: A Demonstration Model from Brazil

Policymakers, managers of water use associations, and many others in developing countries are considering policy actions that will directly or indirectly change the costs and availability of groundwater and surface water for agricultural users. While in many cases such actions may bring about welcomed increases in water use efficiency, little is known about the likely effects of changes in irrigation costs or water access on farmer behavior, or on farmer incomes in the short or long runs, and virtually nothing is known about the detailed immediate or knock-on effects on water resources that such policy actions might cause. This paper reports the preliminary results of research aiming to fill these large scientific gaps by developing a detailed hydrologic model and a detailed economic model of agriculture in the context of the Buriti Vermelho (BV) sub-catchment area of the São Francisco River Basin in Brazil. A spatially explicit, farm-level, positive mathematical programming model capable of accommodating a broad array of farm sizes and farm/farmer characteristics is being developed to predict the effects of alternative water policies and neighbors water use patterns on agricultural production. Special attention is given to precisely defining and estimating the distinct variable costs (including labor and electrical energy costs) and capital costs of surface water and groundwater, which are considered perfect substitutes for irrigation. Shadow values for non-marketed inputs (land, family labor, and water) are estimated in the first step of the modeling process. A high-resolution, spatially distributed hydrologic model (MOD-HMS) is being developed to simulate three-dimensional, variably-saturated subsurface flow and solute transport. Subsurface flow is simulated using the three-dimensional Richards equation while accounting for a) application of water at the surface, b) precipitation, c) soil evaporation and crop transpiration, and d) agricultural pumping. Demonstration versions of both models are presented and tested: the economic model assesses the effects of increasing water scarcity on cultivated area, crop mix, input mix and farm profits; the hydrologic model uses two irrigation water use scenarios to demonstrate the effects of each on surface water flows and storage, and on groundwater storage and well depth. The models are not currently linked, but a detailed plan to do so is presented and discussed. The paper concludes by discussing next steps in research and policy simulations.Resource /Energy Economics and Policy,

The native tribes of South-east Australia

Appendix: Some legends of Central Australian tribes: p. 779-806.Mode of access: Internet

ADENOVIRUS INTERACTION WITH ITS CELLULAR RECEPTOR CAR.

The mechanism of adenovirus attachment to the host cell plasma membrane has been revealed in detail by research over the past 10 years. It has long been known that receptor binding activity is associated with the viral fibers, trimeric spike proteins that protrude radially from the vertices of the icosahedral capsid (Philipson et al. 1968). In some adenovirus serotypes, fiber and other virus structural proteins are synthesized in excess and accumulate in the cell nucleus during late stages of infection. Fiber protein can be readily purified from lysates of cells infected with subgroup C viruses, for example Ad2 and Ad5 (Boulanger and Puvion 1973). Addition of purified fiber protein to virus suspensions during adsorption strongly inhibits infection, indicating that fiber and intact virus particles compete for binding sites on host cells (Philipson et al. 1968; Hautala et al. 1998). Cell binding studies using purified radiolabeled fiber demonstrated that fiber binds specifically and with high affinity to the cell plasma membrane, and that cell lines typically used for laboratory propagation of adenovirus have approximately 10{sup 4} high-affinity receptor sites per cell (Persson et al. 1985; Freimuth 1996). Similar numbers of high-affinity binding sites for radiolabeled intact virus particles also were observed (Seth et al. 1994)

A Novel Patient-Specific Model for Predicting Severe Oliguria; Development and Comparison With Kidney Disease: Improving Global Outcomes Acute Kidney Injury Classification

Objectives: The Kidney Disease: Improving Global Outcomes urine output criteria for acute kidney injury lack specificity for identifying patients at risk of adverse renal outcomes. The objective was to develop a model that analyses hourly urine output values in real time to identify those at risk of developing severe oliguria. Design: This was a retrospective cohort study utilizing prospectively collected data. Setting: A cardiac ICU in the United Kingdom. Patients: Patients undergoing cardiac surgery between January 2013 and November 2017. Interventions: None. Measurement and Main Results: Patients were randomly assigned to development (n = 981) and validation (n = 2,389) datasets. A patient-specific, dynamic Bayesian model was developed to predict future urine output on an hourly basis. Model discrimination and calibration for predicting severe oliguria ( 0.8) were identified and their outcomes were compared with those for low-risk patients and for patients who met the Kidney Disease: Improving Global Outcomes urine output criterion for acute kidney injury. Model discrimination was excellent at all time points (area under the curve > 0.9 for all). Calibration of the model’s predictions was also excellent. After adjustment using multivariable logistic regression, patients in the high-risk group were more likely to require renal replacement therapy (odds ratio, 10.4; 95% CI, 5.9–18.1), suffer prolonged hospital stay (odds ratio, 4.4; 95% CI, 3.0–6.4), and die in hospital (odds ratio, 6.4; 95% CI, 2.8–14.0) (p < 0.001 for all). Outcomes for those identified as high risk by the model were significantly worse than for patients who met the Kidney Disease: Improving Global Outcomes urine output criterion. Conclusions: This novel, patient-specific model identifies patients at increased risk of severe oliguria. Classification according to model predictions outperformed the Kidney Disease: Improving Global Outcomes urine output criterion. As the new model identifies patients at risk before severe oliguria develops it could potentially facilitate intervention to improve patient outcomes