Pesticides at brain borders: Impact on the blood-brain barrier, neuroinflammation, and neurological risk trajectories

Data availability: No data was used for the research described in the article.Pesticides are omnipresent, and they pose significant environmental and health risks. Translational studies indicate that acute exposure to high pesticide levels is detrimental, and prolonged contact with low concentrations of pesticides, as single and cocktail, could represent a risk factor for multi-organ pathophysiology, including the brain. Within this research template, we focus on pesticides' impact on the blood-brain barrier (BBB) and neuroinflammation, physical and immunological borders for the homeostatic control of the central nervous system (CNS) neuronal networks. We examine the evidence supporting a link between pre- and postnatal pesticide exposure, neuroinflammatory responses, and time-depend vulnerability footprints in the brain. Because of the pathological influence of BBB damage and inflammation on neuronal transmission from early development, varying exposures to pesticides could represent a danger, perhaps accelerating adverse neurological trajectories during aging. Refining our understanding of how pesticides influence brain barriers and borders could enable the implementation of pesticide-specific regulatory measures directly relevant to environmental neuroethics, the exposome, and one-health frameworks.This work was supported by ANR-Hepatobrain, Anses-Epidimicmac, iMUSE Pestifish to NM, and iMUSE Envirodisorders to NM and JP; partially supported by Anses-OptoFish, ANR-EpiNeurAge, ANR/Era-Net Neu-Vasc to NM. MC is thankful to Daphne Jackson Trust (UK) for her fellowship. JG is grateful to the EU project Agromix

PeRL : a circum-Arctic Permafrost Region Pond and Lake database

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i. e., waterbodies with surface areas smaller than 1.0 x 10(4) m(2), have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002-2013) high-resolution aerial and satellite imagery with a resolution of 5m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1.4 x 10(6) km(2) across the Arctic, about 17% of the Arctic lowland (Peer reviewe

Ruelle–Takens–Newhouse scenario in reaction-diffusion-convection system

Direct numerical simulations of the transition process from periodic to chaotic dynamics are presented for two variable Oregonator-diffusion model coupled with convection. Numerical solutions to the corresponding reaction-diffusion-convection system of equations show that natural convection can change in a qualitative way, the evolution of concentration distribution, as compared with convectionless conditions. The numerical experiments reveal distinct bifurcations as the Grashof number is increased. A transition to chaos similar to Ruelle-Takens-Newhouse scenario is observed. Numerical results are in agreement with the experiments

Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time

Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km2 (100 m2) to 1 km2. We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic

PeRL:A circum-Arctic Permafrost Region Pond and Lake database

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 104ĝ€m2, have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002-2013) high-resolution aerial and satellite imagery with a resolution of 5ĝ€m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6ĝ€m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 106ĝ€km2 across the Arctic, about 17ĝ€% of the Arctic lowland ( &lt; ĝ€300ĝ€mĝ€a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 106ĝ€m2 down to 1. 0 × 102ĝ€m2 contributed up to 21ĝ€% to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 101ĝ€kmĝ'2. Ponds are the dominant waterbody type by number in all landscapes representing 45-99ĝ€% of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349

Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time

Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (&lt;5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km2 (100 m2) to 1 km2. We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R2 = 0.97, p &lt; 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes

An integarted surgical suite management information system

The operational aspects, application areas, and results achieved from an integrated surgical suite management information system are described. The system, which has been operating within Henry Ford Hospital in Detroit, Michigan, for 4 years, captures comprehensive data for each surgical episode, performs extensive edits on these data to assure data base integrity, and utilizes this data base in multiple applications. These applications include fixed-format reporting for medical staff and management; ad hoc retrieval capabilities to support research, education, and decision making; and linkage to other hospital systems to reduce both data redundancy and paper flow.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45000/1/10916_2005_Article_BF02222176.pd

Nrf2-dependent persistent oxidative stress results in stress-induced vulnerability to depression.

Stressful life events produce a state of vulnerability to depression in some individuals. The mechanisms that contribute to vulnerability to depression remain poorly understood. A rat model of intense stress (social defeat (SD), first hit) produced vulnerability to depression in 40% of animals. Only vulnerable animals developed a depression-like phenotype after a second stressful hit (chronic mild stress). We found that this vulnerability to depression resulted from a persistent state of oxidative stress, which was reversed by treatment with antioxidants. This persistent state of oxidative stress was due to low brain-derived neurotrophic factor (BDNF) levels, which characterized the vulnerable animals. We found that BDNF constitutively controlled the nuclear translocation of the master redox-sensitive transcription factor Nrf2, which activates antioxidant defenses. Low BDNF levels in vulnerable animals prevented Nrf2 translocation and consequently prevented the activation of detoxifying/antioxidant enzymes, ultimately resulting in the generation of sustained oxidative stress. Activating Nrf2 translocation restored redox homeostasis and reversed vulnerability to depression. This mechanism was confirmed in Nrf2-null mice. The mice displayed high levels of oxidative stress and were inherently vulnerable to depression, but this phenotype was reversed by treatment with antioxidants. Our data reveal a novel role for BDNF in controlling redox homeostasis and provide a mechanistic explanation for post-stress vulnerability to depression while suggesting ways to reverse it. Because numerous enzymatic reactions produce reactive oxygen species that must then be cleared, the finding that BDNF controls endogenous redox homeostasis opens new avenues for investigation

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the 21st century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include: warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land-use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large scale water withdrawals, land use and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that Integrated Assessment Models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts