About 2.5 × 106 snapshots on microcrystals of photoactive yellow protein (PYP) from a recent serial femtosecond crystallographic (SFX) experiment were reanalyzed to maximum resolution. The resolution is pushed to 1.46 Å, and a PYP structural model is refined at that resolution. The result is compared to other PYP models determined at atomic resolution around 1 Å and better at the synchrotron. By comparing subtleties such as individual isotropic temperature factors and hydrogen bond lengths, we were able to assess the quality of the SFX data at that resolution. We also show that the determination of anisotropic temperature factor ellipsoids starts to become feasible with the SFX data at resolutions better than 1.5 Å.
Methicillin resistant Staphylococcus aureus (MRSA) is currently a major cause of skin and soft tissue infections (SSTI) in the United States. Seasonal variation of MRSA infections in hospital settings has been widely observed. However, systematic time-series analysis of incidence data is desirable to understand the seasonality of community acquired (CA)-MRSA infections at the population level. In this paper, using data on monthly SSTI incidence in children aged 0–19 years and enrolled in Medicaid in Maricopa County, Arizona, from January 2005 to December 2008, we carried out time-series and nonlinear regression analysis to determine the periodicity, trend, and peak timing in SSTI incidence in children at different age: 0-4 years, 5-9 years, 10-14 years, and 15-19 years. We also assessed the temporal correlation between SSTI incidence and meteorological variables including average temperature and humidity. Our analysis revealed a strong annual seasonal pattern of SSTI incidence with peak occurring in early September. This pattern was consistent across age groups. Moreover, SSTIs followed a significantly increasing trend over the 4-year study period with annual incidence increasing from 3.36% to 5.55% in our pediatric population of approximately 290,000. We also found a significant correlation between the temporal variation in SSTI incidence and mean temperature and specific humidity. Our findings could have potential implications on prevention and control efforts against CA-MRSA.
Background: Prior research shows that work in agriculture and construction/extraction occupations increases the risk of environmental heat-associated death.
Purpose: To assess the risk of environmental heat-associated death by occupation.
Methods: This was a case-control study. Cases were heat-caused and heat-related deaths occurring from May-October during the period 2002–2009 in Maricopa County, Arizona. Controls were selected at random from non-heat-associated deaths during the same period in Maricopa County. Information on occupation, age, sex, and race-ethnicity was obtained from death certificates. Logistic regression analysis was used to estimate odds ratios for heat-associated death.
Results: There were 444 cases of heat-associated deaths in adults (18+ years) and 925 adult controls. Of heat-associated deaths, 332 (75%) occurred in men; a construction/extraction or agriculture occupation was described on the death certificate in 115 (35%) of these men. In men, the age-adjusted odds ratios for heat-associated death were 2.32 (95% confidence interval 1.55, 3.48) in association with construction/extraction and 3.50 (95% confidence interval 1.94, 6.32) in association with agriculture occupations. The odds ratio for heat-associated death was 10.17 (95% confidence interval 5.38, 19.23) in men with unknown occupation. In women, the age-adjusted odds ratio for heat-associated death was 6.32 (95% confidence interval 1.48, 27.08) in association with unknown occupation. Men age 65 years and older in agriculture occupations were at especially high risk of heat-associated death.
Conclusion: The occurrence of environmental heat-associated death in men in agriculture and construction/extraction occupations in a setting with predictable periods of high summer temperatures presents opportunities for prevention.
Many studies link the compositions of microbial communities to their environments, but the energetics of organism-specific biomass synthesis as a function of geochemical variables have rarely been assessed. We describe a thermodynamic model that integrates geochemical and metagenomic data for biofilms sampled at five sites along a thermal and chemical gradient in the outflow channel of the hot spring known as “Bison Pool” in Yellowstone National Park. The relative abundances of major phyla in individual communities sampled along the outflow channel are modeled by computing metastable equilibrium among model proteins with amino acid compositions derived from metagenomic sequences. Geochemical conditions are represented by temperature and activities of basis species, including pH and oxidation-reduction potential quantified as the activity of dissolved hydrogen. By adjusting the activity of hydrogen, the model can be tuned to closely approximate the relative abundances of the phyla observed in the community profiles generated from BLAST assignments. The findings reveal an inverse relationship between the energy demand to form the proteins at equal thermodynamic activities and the abundance of phyla in the community. The distance from metastable equilibrium of the communities, assessed using an equation derived from energetic considerations that is also consistent with the information-theoretic entropy change, decreases along the outflow channel. Specific divergences from metastable equilibrium, such as an underprediction of the relative abundances of phototrophic organisms at lower temperatures, can be explained by considering additional sources of energy and/or differences in growth efficiency. Although the metabolisms used by many members of these communities are driven by chemical disequilibria, the results support the possibility that higher-level patterns of chemotrophic microbial ecosystems are shaped by metastable equilibrium states that depend on both the composition of biomass and the environmental conditions.
In this study we characterized the relationship between temperature and mortality in central Arizona desert cities that have an extremely hot climate. Relationships between daily maximum apparent temperature (ATmax) and mortality for eight condition-specific causes and all-cause deaths were modeled for all residents and separately for males and females ages <65 and ≥65 during the months May-October for years 2000-2008. The most robust relationship was between ATmax on day of death and mortality from direct exposure to high environmental heat. For this condition-specific cause of death, the heat thresholds in all gender and age groups (ATmax = 90–97 °F; 32.2‒36.1 °C) were below local median seasonal temperatures in the study period (ATmax = 99.5 °F; 37.5 °C). Heat threshold was defined as ATmax at which the mortality ratio begins an exponential upward trend. Thresholds were identified in younger and older females for cardiac disease/stroke mortality (ATmax = 106 and 108 °F; 41.1 and 42.2 °C) with a one-day lag. Thresholds were also identified for mortality from respiratory diseases in older people (ATmax = 109 °F; 42.8 °C) and for all-cause mortality in females (ATmax = 107 °F; 41.7 °C) and males <65 years (ATmax = 102 °F; 38.9 °C). Heat-related mortality in a region that has already made some adaptations to predictable periods of extremely high temperatures suggests that more extensive and targeted heat-adaptation plans for climate change are needed in cities worldwide.
