Influenza and Other Respiratory Virus Weekly Activity Report, October 25, 2008, Week 43

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, October 18, 2008, Week 43

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, October 18, 2008, Week 42

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, October 11, 2008, Week 41

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, May 29, 2009, revised Week 20

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, May 30, 2009, revised Week 21

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, June 13, 2009, revised Week 23

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, June 6, 2009, Week 22

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, June 27, 2009, Week 25

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, June 20, 2009, Week 24

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, July 4, 2009, Week 26

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Influenza and Other Respiratory Virus Weekly Activity Report, July 11, 2009, Week 27

Weekly report of the Iowa Influenza Surveillance Network produced by the Iowa Department of Public Health.

Length of activity season drives geographic variation in body size of a widely distributed lizard

Understanding the factors that drive geographic variation in life history is an important challenge in evolutionary ecology. Here, we analyze what predicts geographic variation in life-history traits of the common lizard, Zootoca vivipara, which has the globally largest distribution range of all terrestrial reptile species. Variation in body size was predicted by differences in the length of activity season, while we found no effects of environmental temperature per se. Females experiencing relatively short activity season mature at a larger size and remain larger on average than females in populations with relatively long activity seasons. Interpopulation variation in fecundity was largely explained by mean body size of females and reproductive mode, with viviparous populations having larger clutch size than oviparous populations. Finally, body size-fecundity relationship differs between viviparous and oviparous populations, with relatively lower reproductive investment for a given body size in oviparous populations. While the phylogenetic signal was weak overall, the patterns of variation showed spatial effects, perhaps reflecting genetic divergence or geographic variation in additional biotic and abiotic factors. Our findings emphasize that time constraints imposed by the environment rather than ambient temperature play a major role in shaping life histories in the common lizard. This might be attributed to the fact that lizards can attain their preferred body temperature via behavioral thermoregulation across different thermal environments. Length of activity season, defining the maximum time available for lizards to maintain optimal performance, is thus the main environmental factor constraining growth rate and annual rates of mortality. Our results suggest that this factor may partly explain variation in the extent to which different taxa follow ecogeographic rules.

Application of real-time PCR for total airborne bacterial assessment : comparison with epifluorescence microscopy and culture-dependent methods

Traditional culture-dependent methods to quantify and identify airborne microorganisms are limited by factors such as short-duration sampling times and inability to count nonculturableor non-viable bacteria. Consequently, the quantitative assessment of bioaerosols is often underestimated. Use of the real-time quantitative polymerase chain reaction (Q-PCR) to quantify bacteria in environmental samples presents an alternative method, which should overcome this problem. The aim of this study was to evaluate the performance of a real-time Q-PCR assay as a simple and reliable way to quantify the airborne bacterial load within poultry houses and sewage treatment plants, in comparison with epifluorescencemicroscopy and culture-dependent methods. The estimates of bacterial load that we obtained from real-time PCR and epifluorescence methods, are comparable, however, our analysis of sewage treatment plants indicate these methods give values 270-290 fold greater than those obtained by the ''impaction on nutrient agar'' method. The culture-dependent method of air impaction on nutrient agar was also inadequate in poultry houses, as was the impinger-culture method, which gave a bacterial load estimate 32-fold lower than obtained by Q-PCR. Real-time quantitative PCR thus proves to be a reliable, discerning, and simple method that could be used to estimate airborne bacterial load in a broad variety of other environments expected to carry high numbers of airborne bacteria. [Authors]

Impact of biological and environmental variabilities on biological monitoring: an approach using toxicokinetic models

Biological monitoring of occupational exposure is characterized by important variability, due both to variability in the environment and to biological differences between workers. A quantitative description and understanding of this variability is important for a dependable application of biological monitoring. This work describes this variability,using a toxicokinetic model, for a large range of chemicals for which reference biological reference values exist. A toxicokinetic compartmental model describing both the parent compound and its metabolites was used. For each chemical, compartments were given physiological meaning. Models were elaborated based on physiological, physicochemical, and biochemical data when available, and on half-lives and central compartment concentrations when not available. Fourteen chemicals were studied (arsenic, cadmium, carbon monoxide, chromium, cobalt, ethylbenzene, ethyleneglycol monomethylether, fluorides, lead, mercury, methyl isobutyl ketone, penthachlorophenol, phenol, and toluene), representing 20 biological indicators. Occupational exposures were simulated using Monte Carlo techniques with realistic distributions of both individual physiological parameters and exposure conditions. Resulting biological indicator levels were then analyzed to identify the contribution of environmental and biological variability to total variability. Comparison of predicted biological indicator levels with biological exposure limits showed a high correlation with the model for 19 out of 20 indicators. Variability associated with changes in exposure levels (GSD of 1.5 and 2.0) is shown to be mainly influenced by the kinetics of the biological indicator. Thus, with regard to variability, we can conclude that, for the 14 chemicals modeled, biological monitoring would be preferable to air monitoring. For short half-lives (less than 7 hr), this is very similar to the environmental variability. However, for longer half-lives, estimated variability decreased. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resource: tables detailing the CBTK models for all 14 chemicals and the symbol nomenclature that was used.] [Authors]