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Gulf War illness (GWI) is an important exemplar of environmentally-triggered chronic multisymptom illness, and a potential model for accelerated aging. Inflammation is the main hypothesized mechanism for GWI, with mitochondrial impairment also proposed. No study has directly assessed mitochondrial respiratory chain function (MRCF) on muscle biopsy in veterans with GWI (VGWI). We recruited 42 participants, half VGWI, with biopsy material successfully secured in 36. Impaired MRCF indexed by complex I and II oxidative phosphorylation with glucose as a fuel source (CI&CIIOXPHOS) related significantly or borderline significantly in the predicted direction to 17 of 20 symptoms in the combined sample. Lower CI&CIIOXPHOS significantly predicted GWI severity in the combined sample and in VGWI separately, with or without adjustment for hsCRP. Higher-hsCRP (peripheral inflammation) related strongly to lower-MRCF (particularly fatty acid oxidation (FAO) indices) in VGWI, but not in controls. Despite this, whereas greater MRCF-impairment predicted greater GWI symptoms and severity, greater inflammation did not. Surprisingly, adjusted for MRCF, higher hsCRP significantly predicted lesser symptom severity in VGWI selectively. Findings comport with a hypothesis in which the increased inflammation observed in GWI is driven by FAO-defect-induced mitochondrial apoptosis. In conclusion, impaired mitochondrial function—but not peripheral inflammation—predicts greater GWI symptoms and severity.

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Abstract:The Ecosystem Management Decision Support (EMDS) system is an application framework for designing and implementing spatially enabled knowledge-based decision support systems for environmental analysis and planning at any geographic scale(s). The system integrates state-of-the-art geographic information system, as well as knowledge-based reasoning and decision modeling, technologies to provide decision support for the adaptive management process of ecosystem management. It integrates a logic engine to perform landscape evaluations, and a decision engine for developing management priorities. The logic component: (1) reasons about large, abstract, multi-faceted ecosystem management problems; (2) performs useful evaluations with incomplete information; (3) evaluates the influence of missing information, and (4) determines priorities for missing information. The planning component determines priorities for management activities, taking into account not only ecosystem condition, but also criteria that account for logistical concerns of potential management actions. Both OPEN ACCESSForests 2015, 6 28 components include intuitive diagnostic features that facilitate communicating modeling results to a broad audience. Features of the system design that have figured in its success over the past 20 years are highlighted, together with design features planned for the next several versions needed to provide spatial decision support for adaptive management under climate change.

We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks’ conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a −1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.