No abstract
BackgroundDisplacing the use of polluting and inefficient cookstoves in developing countries is necessary to achieve the potential health and environmental benefits sought through clean cooking solutions. Yet little quantitative context has been provided on how much displacement of traditional technologies is needed to achieve targets for household air pollutant concentrations or fuel savings.ObjectivesThis paper provides instructive guidance on the usage of cooking technologies required to achieve health and environmental improvements.MethodsWe evaluated different scenarios of displacement of traditional stoves with use of higher performing technologies. The air quality and fuel consumption impacts were estimated for these scenarios using a single-zone box model of indoor air quality and ratios of thermal efficiency.ResultsStove performance and usage should be considered together, as lower performing stoves can result in similar or greater benefits than a higher performing stove if the lower performing stove has considerably higher displacement of the baseline stove. Based on the indoor air quality model, there are multiple performance–usage scenarios for achieving modest indoor air quality improvements. To meet World Health Organization guidance levels, however, three-stone fire and basic charcoal stove usage must be nearly eliminated to achieve the particulate matter target (< 1–3 hr/week), and substantially limited to meet the carbon monoxide guideline (< 7–9 hr/week).ConclusionsModerate health gains may be achieved with various performance–usage scenarios. The greatest benefits are estimated to be achieved by near-complete displacement of traditional stoves with clean technologies, emphasizing the need to shift in the long term to near exclusive use of clean fuels and stoves. The performance–usage scenarios are also provided as a tool to guide technology selection and prioritize behavior change opportunities to maximize impact.CitationJohnson MA, Chiang RA. 2015. Quantitative guidance for stove usage and performance to achieve health and environmental targets. Environ Health Perspect 123:820–826; http://dx.doi.org/10.1289/ehp.1408681
To study the substrate specificity of enzymes, we use the amidohydrolase and enolase superfamilies as model systems; members of these superfamilies share a common TIM barrel fold and catalyze a wide range of chemical reactions. Here, we describe a collaboration between the Enzyme Specificity Consortium (ENSPEC) and the New York SGX Research Center for Structural Genomics (NYSGXRC) that aims to maximize the structural coverage of the amidohydrolase and enolase superfamilies. Using sequence-and structure-based protein comparisons, we first selected 535 target proteins from a variety of genomes for high-throughput structure determination by X-ray crystallography; 63 of these targets were not previously annotated as superfamily members. To date, 20 unique amidohydrolase and 41 unique enolase structures have been determined, increasing the fraction of sequences in the two superfamilies that can be modeled based on at least 30% sequence identity from 45% to 73%. We present case studies of proteins related to uronate isomerase (an amidohydrolase superfamily member) and mandelate racemase (an enolase superfamily member), to illustrate how this structure-focused approach can be used to generate hypotheses about sequence-structure-function relationships.
The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies.
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