The M/GP5 Glycoprotein Complex of Porcine Reproductive and Respiratory Syndrome Virus Binds the Sialoadhesin Receptor in a Sialic Acid-Dependent Manner

The porcine reproductive and respiratory syndrome virus (PRRSV) is a major threat to swine health worldwide and is considered the most significant viral disease in the swine industry today. In past years, studies on the entry of the virus into its host cell have led to the identification of a number of essential virus receptors and entry mediators. However, viral counterparts for these molecules have remained elusive and this has made rational development of new generation vaccines impossible. The main objective of this study was to identify the viral counterparts for sialoadhesin, a crucial PRRSV receptor on macrophages. For this purpose, a soluble form of sialoadhesin was constructed and validated. The soluble sialoadhesin could bind PRRSV in a sialic acid-dependent manner and could neutralize PRRSV infection of macrophages, thereby confirming the role of sialoadhesin as an essential PRRSV receptor on macrophages. Although sialic acids are present on the GP3, GP4 and GP5 envelope glycoproteins, only the M/GP5 glycoprotein complex of PRRSV was identified as a ligand for sialoadhesin. The interaction was found to be dependent on the sialic acid binding capacity of sialoadhesin and on the presence of sialic acids on GP5. These findings not only contribute to a better understanding of PRRSV biology, but the knowledge and tools generated in this study also hold the key to the development of a new generation of PRRSV vaccines

Size-Selective Predation on Daphnia by Neomysis Mercedis

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On Rejection Rates of Paired Intervention Analysis

Before–After-Control–Impact (BACI) analysis and randomized intervention analysis (RIA) are commonly applied to time series of response measurements obtained from two ecological units, one of which is subjected to an intervention at some intermediate time. Positive results from the analyses are interpreted as evidence of a potentially mean-ingful association between the intervention and the response. Applied to 154 pairs of actual ecological time series, RIA done at the 5% level rejected the hypothesis of no association 20% of the time when both units were in fact undisturbed, and 30% of the time when one of the two units had received an intervention. Correction for first-order serial autocorrelation in the time series of between-unit differences reduced these rejection frequencies to 15% and 28%, respectively. A two-stage analysis method that attempts to adjust for temporal variability of early and late response means failed to find an association in any of the pairs of ''control'' units, and found evidence of an association in only 14–15% of the pairs in which one unit was disturbed. These results suggest that RIA (and BACI analysis) greatly overstate the evidence for associations of interventions with ecological responses, and that attempts to modify these methods to account for temporal variability of response trajectories result in tests with very limited power. It may be that the best strategy for interpreting data from BACI designs is to rely on graphical presentation, expert judgment, and common sense, rather than P values derived from hypothesis tests of questionable validity. Key words: before–after-control–impact (BACI) design; environmental impact assessment; in-tervention effects; randomized intervention analysis (RIA); serial correlation; time series; two-stage intervention analysis; Type I error rate

Inferring properties of mysid predation from injuries to Daphnia-Limnol

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Selective predation by Neomysis mercedis in Lake Washington

Feeding experiments and examination of gut contents show that Neomysis mercedis is an effective predator on zooplankton in Lake Washington. Daphnia is consistently preferred to other prey; Diaptomus and Cyclops copepodids and nauplii are always underrepresented in mysid diets. This pattern of selectivity is consistent with the hypothesis that a large population of Neomysis formerly excluded Daphnia from the lake

Appendix B. A description of how data were simulated for the evaluation of the different analysis techniques for Example 2.

A description of how data were simulated for the evaluation of the different analysis techniques for Example 2