Quantifying regional α -synuclein, amyloid β, and tau accumulation in Lewy body dementia

OBJECTIVE: Parkinson disease (PD) is defined by the accumulation of misfolded α-synuclein (α-syn) in Lewy bodies and Lewy neurites. It affects multiple cortical and subcortical neuronal populations. The majority of people with PD develop dementia, which is associated with Lewy bodies in neocortex and referred to as Lewy body dementia (LBD). Other neuropathologic changes, including amyloid β (Aβ) and tau accumulation, occur in some LBD cases. We sought to quantify α-syn, Aβ, and tau accumulation in neocortical, limbic, and basal ganglia regions. METHODS: We isolated insoluble protein from fresh frozen postmortem brain tissue samples for eight brains regions from 15 LBD, seven Alzheimer disease (AD), and six control cases. We measured insoluble α-syn, Aβ, and tau with recently developed sandwich ELISAs. RESULTS: We detected a wide range of insoluble α-syn accumulation in LBD cases. The majority had substantial α-syn accumulation in most regions, and dementia severity correlated with neocortical α-syn. However, three cases had low neocortical levels that were indistinguishable from controls. Eight LBD cases had substantial Aβ accumulation, although the mean Aβ level in LBD was lower than in AD. The presence of Aβ was associated with greater α-syn accumulation. Tau accumulation accompanied Aβ in only one LBD case. INTERPRETATION: LBD is associated with insoluble α-syn accumulation in neocortical regions, but the relatively low neocortical levels in some cases suggest that other changes contribute to impaired function, such as loss of neocortical innervation from subcortical regions. The correlation between Aβ and α-syn accumulation suggests a pathophysiologic relationship between these two processes

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.https://pubs.er.usgs.gov/publication/ofr2020107