6 resultados para Methodist Epis. Ch., U.S.

em Duke University


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Directional drilling and hydraulic-fracturing technologies are dramatically increasing natural-gas extraction. In aquifers overlying the Marcellus and Utica shale formations of northeastern Pennsylvania and upstate New York, we document systematic evidence for methane contamination of drinking water associated with shale-gas extraction. In active gas-extraction areas (one or more gas wells within 1 km), average and maximum methane concentrations in drinking-water wells increased with proximity to the nearest gas well and were 19.2 and 64 mg CH(4) L(-1) (n = 26), a potential explosion hazard; in contrast, dissolved methane samples in neighboring nonextraction sites (no gas wells within 1 km) within similar geologic formations and hydrogeologic regimes averaged only 1.1 mg L(-1) (P < 0.05; n = 34). Average δ(13)C-CH(4) values of dissolved methane in shallow groundwater were significantly less negative for active than for nonactive sites (-37 ± 7‰ and -54 ± 11‰, respectively; P < 0.0001). These δ(13)C-CH(4) data, coupled with the ratios of methane-to-higher-chain hydrocarbons, and δ(2)H-CH(4) values, are consistent with deeper thermogenic methane sources such as the Marcellus and Utica shales at the active sites and matched gas geochemistry from gas wells nearby. In contrast, lower-concentration samples from shallow groundwater at nonactive sites had isotopic signatures reflecting a more biogenic or mixed biogenic/thermogenic methane source. We found no evidence for contamination of drinking-water samples with deep saline brines or fracturing fluids. We conclude that greater stewardship, data, and-possibly-regulation are needed to ensure the sustainable future of shale-gas extraction and to improve public confidence in its use.

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Earth's surface is rapidly urbanizing, resulting in dramatic changes in the abundance, distribution and character of surface water features in urban landscapes. However, the scope and consequences of surface water redistribution at broad spatial scales are not well understood. We hypothesized that urbanization would lead to convergent surface water abundance and distribution: in other words, cities will gain or lose water such that they become more similar to each other than are their surrounding natural landscapes. Using a database of more than 1 million water bodies and 1 million km of streams, we compared the surface water of 100 US cities with their surrounding undeveloped land. We evaluated differences in areal (A WB) and numeric densities (N WB) of water bodies (lakes, wetlands, and so on), the morphological characteristics of water bodies (size), and the density (D C) of surface flow channels (that is, streams and rivers). The variance of urban A WB, N WB, and D C across the 100 MSAs decreased, by 89, 25, and 71%, respectively, compared to undeveloped land. These data show that many cities are surface water poor relative to undeveloped land; however, in drier landscapes urbanization increases the occurrence of surface water. This convergence pattern strengthened with development intensity, such that high intensity urban development had an areal water body density 98% less than undeveloped lands. Urbanization appears to drive the convergence of hydrological features across the US, such that surface water distributions of cities are more similar to each other than to their surrounding landscapes. © 2014 The Author(s).

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Theory suggests that economic instruments, such as pollution taxes or tradable permits, can provide more efficient technology adoption incentives than conventional regulatory standards. We explore this issue for an important industry undergoing dramatic decreases in allowed pollution - the U.S. petroleum industry's phasedown of lead in gasoline. Using a duration model applied to a panel of refineries from 1971-1995, we find that the pattern of technology adoption is consistent with an economic response to market incentives, plant characteristics, and alternative policies. Importantly, evidence suggests that the tradable permit system used during the phasedown provided incentives for more efficient technology adoption decisions.

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Selecting a suitable site to deposit their eggs is an important reproductive need of Drosophila females. Although their choosiness toward egg-laying sites is well documented, the specific neural mechanism that activates females' search for attractive egg-laying sites is not known. Here, we show that distention and contraction of females' internal reproductive tract triggered by egg delivery through the tract plays a critical role in activating such search. We found that females start to exhibit acetic acid (AA) attraction prior to depositing each egg but no attraction when they are not laying eggs. Artificially distending the reproductive tract triggers AA attraction in non-egg-laying females, whereas silencing the mechanosensitive neurons we identified that can sense the contractile status of the tract eliminates such attraction. Our work uncovers the circuit basis of an important reproductive need of Drosophila females and provides a simple model for dissecting the neural mechanism that underlies a reproductive need-induced behavioral modification.

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High-throughput analysis of animal behavior requires software to analyze videos. Such software typically depends on the experiments' being performed in good lighting conditions, but this ideal is difficult or impossible to achieve for certain classes of experiments. Here, we describe techniques that allow long-duration positional tracking in difficult lighting conditions with strong shadows or recurring "on"/"off" changes in lighting. The latter condition will likely become increasingly common, e.g., for Drosophila due to the advent of red-shifted channel rhodopsins. The techniques enabled tracking with good accuracy in three types of experiments with difficult lighting conditions in our lab. Our technique handling shadows relies on single-animal tracking and on shadows' and flies' being accurately distinguishable by distance to the center of the arena (or a similar geometric rule); the other techniques should be broadly applicable. We implemented the techniques as extensions of the widely-used tracking software Ctrax; however, they are relatively simple, not specific to Drosophila, and could be added to other trackers as well.

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BACKGROUND AND OBJECTIVES: Pain symptoms are common among Iraq/Afghanistan-era veterans, many of whom continue to experience persistent pain symptoms despite multiple pharmacological interventions. Preclinical data suggest that neurosteroids such as allopregnanolone demonstrate pronounced analgesic properties, and thus represent logical biomarker candidates and therapeutic targets for pain. Allopregnanolone is also a positive GABAA receptor modulator with anxiolytic, anticonvulsant, and neuroprotective actions in rodent models. We previously reported inverse associations between serum allopregnanolone levels and self-reported pain symptom severity in a pilot study of 82 male veterans. METHODS: The current study investigates allopregnanolone levels in a larger cohort of 485 male Iraq/Afghanistan-era veterans to attempt to replicate these initial findings. Pain symptoms were assessed by items from the Symptom Checklist-90-R (SCL-90-R) querying headache, chest pain, muscle soreness, and low back pain over the past 7 days. Allopregnanolone levels were quantified by gas chromatography/mass spectrometry. RESULTS: Associations between pain ratings and allopregnanolone levels were examined with Poisson regression analyses, controlling for age and smoking. Bivariate nonparametric Mann–Whitney analyses examining allopregnanolone levels across high and low levels of pain were also conducted. Allopregnanolone levels were inversely associated with muscle soreness [P = 0.0028], chest pain [P = 0.032], and aggregate total pain (sum of all four pain items) [P = 0.0001]. In the bivariate analyses, allopregnanolone levels were lower in the group reporting high levels of muscle soreness [P = 0.001]. CONCLUSIONS: These findings are generally consistent with our prior pilot study and suggest that allopregnanolone may function as an endogenous analgesic. Thus, exogenous supplementation with allopregnanolone could have therapeutic potential. The characterization of neurosteroid profiles may also have biomarker utility.