Exploring the limits of knowledge on boreal peatland development using a new model: the Holocene Peatland Model

The Holocene Peatland Model (HPM) (Frolking et al. 2009, Frolking et al. in prep.) is a recently developed tool integrating up-to-date knowledge on peatland dynamics that explores peatland development and carbon dynamics on a millennial timescale. HPM combines the water and carbon cycles with net primary production and peat decomposition and takes the multiple feedbacks into account. The model remains simple and few site-specific inputs are needed. HPM simulates the transient development of the peatland and delivers peat age, peat depth, peat composition, carbon accumulation and water table depth for each simulated year. Evaluating the ability of the model to reproduce peatland development can be achieved in several manners. Commonly one could choose to compare simulations results with observations from field data. However, we argue that the overall response of the model does not give much information about the value of the model design. Modelling of peatlands dynamics requires a lot of information regarding the behaviour of a peatland system within its environment (including allogenic changes in climate, hydrological conditions, nutrient availability or autogenic processes such as microtopographical effects). The actual state of knowledge does not cover all processes, interactions or feedbacks and a lot of peatland properties are neither well defined nor measured yet, so that estimates have been needed to build the model. The work presented here aims at analyzing the role of the model parameterization on the simulation results. To do so, a sensitivity analysis is performed with a Monte-Carlo analysis and with help of the GUI-HDMR software (Ziehn and Tomlin, 2009). This method ranks the parameters and combinations of them according to their influence on simulation results. The results will emphasize how the simulation is sensitive to the parameter values. First, the distribution of outputs gives insight into the possible responses of the simulation to HPM’s assemblage of current knowledge. Second, the importance of some parameters on simulation results points out certain gaps in the current understanding of peatland dynamics. Thus, this study helps determine some avenues that should be explored in future in order to improve peatlands dynamics understanding

Monovision LASIK in emmetropic presbyopic patients.

BackgroundTo evaluate the efficacy and patient satisfaction of laser in situ keratomileusis (LASIK) monovision correction in presbyopic emmetropic patients.MethodsA retrospective review of 294 patients who underwent LASIK for monovision was conducted. All patients had preoperative uncorrected distance visual acuity in each eye of 20/25 or better in both eyes and underwent primary LASIK treatment in one eye with a near target; 82 patients underwent surgery in the distant eye for hypermetropia. Patients completed a patient-reported-outcome questionnaire at their one-month postoperative visit. Analysis was performed on a per patient basis with a logistic regression model.ResultsPatients achieved a postoperative mean spherical equivalent of -0.05 diopters (D) in the distant eye and -1.92 D in the near eye. Prior to surgery, 64.7% (n=178) of patients reported they were satisfied or very satisfied with their vision; postoperatively, this increased to 85.4% (n=251). The greatest predictor of dissatisfaction after surgery was severe patient-reported visual phenomena (glare, halos, starbursts, ghosting) (odds ratio 1.18, P=0.001).ConclusionsLASIK monovision for presbyopic patients with low refractive error and good preoperative uncorrected distance visual acuity is both safe and effective with high patient satisfaction. Patients who were dissatisfied in the postoperative period tended to be those with postoperative visual symptoms

Spatial Misalignment in time series studies of air pollution and health data

Time series studies of environmental exposures often involve comparing daily changes in a toxicant measured at a point in space with daily changes in an aggregate measure of health. Spatial misalignment of the exposure and response variables can bias the estimation of health risk and the magnitude of this bias depends on the spatial variation of the exposure of interest. In air pollution epidemiology, there is an increasing focus on estimating the health effects of the chemical components of particulate matter. One issue that is raised by this new focus is the spatial misalignment error introduced by the lack of spatial homogeneity in many of the particulate matter components. Current approaches to estimating short-term health risks via time series modeling do not take into account the spatial properties of the chemical components and therefore could result in biased estimation of those risks. We present a spatial-temporal statistical model for quantifying spatial misalignment error and show how adjusted heath risk estimates can be obtained using a regression calibration approach and a two-stage Bayesian model. We apply our methods to a database containing information on hospital admissions, air pollution, and weather for 20 large urban counties in the United States

Dynamic Patterns of Transcript Abundance of Transposable Element Families in Maize.

Transposable Elements (TEs) are mobile elements that contribute the majority of DNA sequences in the maize genome. Due to their repetitive nature, genomic studies of TEs are complicated by the difficulty of properly attributing multi-mapped short reads to specific genomic loci. Here, we utilize a method to attribute RNA-seq reads to TE families rather than particular loci in order to characterize transcript abundance for TE families in the maize genome. We applied this method to assess per-family expression of transposable elements in >800 published RNA-seq libraries representing a range of maize development, genotypes, and hybrids. While a relatively small proportion of TE families are transcribed, expression is highly dynamic with most families exhibiting tissue-specific expression. A large number of TE families were specifically detected in pollen and endosperm, consistent with reproductive dynamics that maintain silencing of TEs in the germ line. We find that B73 transcript abundance is a poor predictor of TE expression in other genotypes and that transcript levels can differ even for shared TEs. Finally, by assessing recombinant inbred line and hybrid transcriptomes, complex patterns of TE transcript abundance across genotypes emerged. Taken together, this study reveals a dynamic contribution of TEs to maize transcriptomes

Effects of Low-Energy X-rays and UV Radiation on Fibroblast Cells

https://tigerprints.clemson.edu/csrp/1003/thumbnail.jp

The Exposure–Response Curve for Ozone and Risk of Mortality and the Adequacy of Current Ozone Regulations

Time-series analyses have shown that ozone is associated with increased risk of premature mortality, but little is known about how O(3) affects health at low concentrations. A critical scientific and policy question is whether a threshold level exists below which O(3) does not adversely affect mortality. We developed and applied several statistical models to data on air pollution, weather, and mortality for 98 U.S. urban communities for the period 1987–2000 to estimate the exposure–response curve for tropospheric O(3) and risk of mortality and to evaluate whether a “safe” threshold level exists. Methods included a linear approach and subset, threshold, and spline models. All results indicate that any threshold would exist at very low concentrations, far below current U.S. and international regulations and nearing background levels. For example, under a scenario in which the U.S. Environmental Protection Agency’s 8-hr regulation is met every day in each community, there was still a 0.30% increase in mortality per 10-ppb increase in the average of the same and previous days’ O(3) levels (95% posterior interval, 0.15–0.45%). Our findings indicate that even low levels of tropospheric O(3) are associated with increased risk of premature mortality. Interventions to further reduce O(3) pollution would benefit public health, even in regions that meet current regulatory standards and guidelines

Heat-Related Mortality and Adaptation to Heat in the United States

Background: In a changing climate, increasing temperatures are anticipated to have profound health impacts. These impacts could be mitigated if individuals and communities adapt to changing exposures; however, little is known about the extent to which the population may be adapting. Objective: We investigated the hypothesis that if adaptation is occurring, then heat-related mortality would be decreasing over time. Methods: We used a national database of daily weather, air pollution, and age-stratified mortality rates for 105 U.S. cities (covering 106 million people) during the summers of 1987–2005. Time-varying coefficient regression models and Bayesian hierarchical models were used to estimate city-specific, regional, and national temporal trends in heat-related mortality and to identify factors that might explain variation across cities. Results: On average across cities, the number of deaths (per 1,000 deaths) attributable to each 10°F increase in same-day temperature decreased from 51 [95% posterior interval (PI): 42, 61] in 1987 to 19 (95% PI: 12, 27) in 2005. This decline was largest among those ≥ 75 years of age, in northern regions, and in cities with cooler climates. Although central air conditioning (AC) prevalence has increased, we did not find statistically significant evidence of larger temporal declines among cities with larger increases in AC prevalence. Conclusions: The population has become more resilient to heat over time. Yet even with this increased resilience, substantial risks of heat-related mortality remain. Based on 2005 estimates, an increase in average temperatures by 5°F (central climate projection) would lead to an additional 1,907 deaths per summer across all cities. Citation: Bobb JF, Peng RD, Bell ML, Dominici F. 2014. Heat-related mortality and adaptation to heat in the United States. Environ Health Perspect 122:811–816; http://dx.doi.org/10.1289/ehp.130739

Proximity Driven Enhanced Magnetic Order at Ferromagnetic Insulator / Magnetic Topological Insulator Interface

Magnetic exchange driven proximity effect at a magnetic insulator / topological insulator (MI/TI) interface provides a rich playground for novel phenomena as well as a way to realize low energy dissipation quantum devices. Here we report a dramatic enhancement of proximity exchange coupling in the MI / magnetic-TI EuS / Sb$_{2-x}$V$_x$Te$_3$ hybrid heterostructure, where V doping is used to drive the TI (Sb$_{2}$Te$_3$) magnetic. We observe an artificial antiferromagnetic-like structure near the MI/TI interface, which may account for the enhanced proximity coupling. The interplay between the proximity effect and doping provides insights into controllable engineering of magnetic order using a hybrid heterostructure.Comment: 5 pages, 4 figure

Interaction of CK1δ with γTuSC ensures proper microtubule assembly and spindle positioning.

Casein kinase 1δ (CK1δ) family members associate with microtubule-organizing centers (MTOCs) from yeast to humans, but their mitotic roles and targets have yet to be identified. We show here that budding yeast CK1δ, Hrr25, is a γ-tubulin small complex (γTuSC) binding factor. Moreover, Hrr25's association with γTuSC depends on its kinase activity and its noncatalytic central domain. Loss of Hrr25 kinase activity resulted in assembly of unusually long cytoplasmic microtubules and defects in spindle positioning, consistent with roles in regulation of γTuSC-mediated microtubule nucleation and the Kar9 spindle-positioning pathway, respectively. Hrr25 directly phosphorylated γTuSC proteins in vivo and in vitro, and this phosphorylation promoted γTuSC integrity and activity. Because CK1δ and γTuSC are highly conserved and present at MTOCs in diverse eukaryotes, similar regulatory mechanisms are expected to apply generally in eukaryotes

Assessment of the disinfection capacity and eco-toxicological impact of atmospheric cold plasma for treatment of food industry effluents

Generation of wastewater is one of the main environmental sustainability issues across food sector industries. The constituents of food process effluents are often complex and require high energy and processing for regulatory compliance. Wastewater streams are the subject of microbiological and chemical criteria, and can have a significant eco-toxicological impact on the aquatic life. Thus, innovative treatment approaches are required to mitigate environmental impact in an energy efficient manner. Here, dielectric barrier discharge atmospheric cold plasma (ACP) was evaluated for control of key microbial indicators encountered in food industry effluent. This study also investigated the eco-toxicological impact of cold plasma treatment of the effluents using a range of aquatic bioassays. Continuous ACP treatment was applied to synthetic dairy and meat effluents. Microbial inactivation showed treatment time dependence with significant reduction in microbial populations within 120 s, and to undetectable levels after 300 s. Post treatment retention time emerged as critical control parameter which promoted ACP bacterial inactivation efficiency. Moreover, ACP treatment for 20 min achieved significant reduction (≥2 Log10) in Bacillus megaterium endospores in wastewater effluent. Acute aquatic toxicity was assessed using two fish cell lines (PLHC-1 and RTG-2) and a crustacean model (Daphnia magna). Untreated effluents were toxic to the aquatic models, however, plasma treatment limited the toxic effects. Differing sensitivities were observed to ACP treated effluents across the different test bio-assays in the following order: PLHC-1 \u3e RTG-2 ≥ D. magna; with greater sensitivity retained to plasma treated meat effluent than dairy effluent. The toxic effects were dependent on concentration and treatment time of the ACP treated effluent; with 30% cytotoxicity in D. magna and fish cells observed after 24 h of exposure to ACP treated effluent for concentrations up to 5%. The findings suggest the need to employ wider variety of aquatic organisms for better understanding and complete toxicity evaluation of long-term effects. The study demonstrates the potential to tailor ACP system parameters to control pertinent microbial targets (mono/poly-microbial, vegetative or spore form) found in complex and nutritious wastewater effluents whilst maintaining a safe eco-toxicity profile for aquatic species