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The San Antonio River Basin (SARB) is an ecologically diverse region in South Texas. The city of San Antonio is located within the basin and is the hub of the North American Free Trade Agreement (NAFTA). San Antonio, together with other major metropolitan centers in Texas, has experienced rapid population and economic growth over the last thirty years, which accelerated after the implementation of NAFTA in 1994. To assess the environmental implications of this growth in the SARB, we first conducted a land-change analysis using Landsat images from 1984, 1995, and 2010. Then, we analyzed spatiotemporal changes in ecosystem services across the SARB and within three watersheds in Bexar County where the city of San Antonio is located. To estimate changes in ecosystem service values (ESV) during this period, we combined the results of the land-change analysis with a benefit transfer approach using two sets of widely cited ecosystem-service valuation coefficients published in 1997 and 2014 but we modified the urban coefficient from the 2014 publication for low-density and high-density urban areas. When 1997 coefficients were applied, the ESV in the SARB decreased, on average, by $1.2 million/year during 1984–1995 and by $1.8 million/year during 1995–2010. The ESV in Bexar County decreased, on average, by $0.5 million/year and $0.7 million/year during the first and second periods, respectively. When the 2014 coefficients and modified urban value coefficients were applied, the ESV in the SARB decreased, on average, by a 27% more during the first period than when the 1997 coefficients were applied, while, ESV increased during the second period by an average of $2.2 million/year. This temporally opposite trend in ESV change did not occur in Bexar County, however. Using the 2014 coefficients, ESV in Bexar County decreased 5 times more during the first period and decreased 2.5 times more during the second period than when 1997 coefficients were applied. The differences in ESV trends resulting from the two sets of coefficients can be explained primarily by the different coefficients assigned to urban spaces ($0/ha/year in the 1997 study and $7005/ha/year in the 2014 study). Our results suggest that the value placed on urban areas in the 2014 publication, taken from a single case study and intended primarily for large urban parks, substantially overestimates the ESV of urban space. In our study areas, applying this value, even only to urban green space, led to the improbable conclusion that urbanization had a positive overall effect on the delivery of ecosystem services. While open spaces in urban areas do provide valuable ecosystem services, it is highly unlikely that their value exceeds those provided by less modified ecosystems. The ability to confidently use value coefficients when applying benefit transfer methods to estimate ESVs demands rigorous assessments of their broad applicability.

Mitochondria undergo dynamic changes to maintain function in eukaryotic cells. Insulin action in parallel regulates glucose homeostasis, but whether specific changes in mitochondrial dynamics alter insulin action and glucose homeostasis remains elusive. Here, we report that high-fat feeding in rodents incurred adaptive dynamic changes in mitochondria through an increase in mitochondrial fission in parallel to an activation of dynamin-related protein 1 (Drp1) in the dorsal vagal complex (DVC) of the brain. Direct inhibition of Drp1 negated high-fat-feeding-induced mitochondrial fission, endoplasmic reticulum (ER) stress, and insulin resistance in the DVC and subsequently restored hepatic glucose production regulation. Conversely, molecular activation of DVC Drp1 in healthy rodents was sufficient to induce DVC mitochondrial fission, ER stress, and insulin resistance. Together, these data illustrate that Drp1-dependent mitochondrial fission changes in the DVC regulate insulin action and suggest that targeting the Drp1-mitochondrial-dependent pathway in the brain may have therapeutic potential in insulin resistance.

Background. Physical activity initiation and maintenance are particular challenges in the postmastectomy recovery and in particular Dragon Boat racing seems to be a useful sport activity. The aim of this study was to evaluate the role of focal muscle vibration as a proprioceptive input to improve upper limb functioning in a group of “paddlers” patients. Methods. A group of paddlers has been evaluated before vibratory treatment (T0), immediately after therapy (T1), after one week (T2), and after one month (T3) with DASH questionnaire, Body Image Scale, McGill pain questionnaire, Constant Scale, and Short Form 36 questionnaire. Results. Fourteen patients showed a significant reduction in disability score (p=0,001) using DASH scale, an improvement of upper limb function (p=0,001) using the Constant scale, and a reduction of pain (p=0,007) at the McGill pain questionnaire. The Mental Composite Score of the Short Form 36 questionnaire showed significant results (p=0,04) while no significant results had been found regarding the physical mental score (p=0,08). Conclusion. Focal muscle vibration may be a useful treatment in a postmastectomy recovery of upper limb functionality.

Cognitive dysfunction affects 40–65% of multiple sclerosis (MS) patients and can occur in the early stages of the disease. This study aimed to explore cognitive functions by means of the Italian version of the minimal assessment of cognitive function in MS (MACFIMS) in relapsing-remitting MS (RRMS) patients with very mild clinical disability to identify the primarily involved cognitive functions. Ninety-two consecutive RRMS patients with Expanded Disability Status Scale (EDSS) scores ≤ 2.5 and forty-two healthy controls (HC) were investigated. Our results show that 51.1% of MS patients have cognitive dysfunction compared to HC. An impairment of verbal and visual memory, working memory, and executive functions was found in the RRMS group. After subgrouping RRMS by EDSS, group 1 (EDSS ≤ 1.5) showed involvement of verbal memory and executive functions; moreover, group 2 (2 ≤ EDSS ≤ 2.5) patients were also impaired in information processing speed and visual memory. Our results show that utilizing a comprehensive neuropsychological assessment, approximately half of MS patients with very mild physical disability exhibit cognitive impairment with a primary involvement of prefrontal cognitive functions. Detecting impairment of executive functions at an early clinical stage of disease could be useful to promptly enroll MS patients in targeted rehabilitation.

Background: Obstetrical analgesia remains a matter of controversy because of the fear of neurotoxicity of local anesthetics on demyelinated fibers or their potential relationship with subsequent relapses. Objective: To assess the impact of neuraxial analgesia on the risk of relapse during the first 3 months post-partum, with a focus on women who experienced relapses during pregnancy. Methods: We analyzed data of women followed-up prospectively during their pregnancies and at least 3 months post-partum, collected in the Pregnancy in Multiple Sclerosis (PRIMS) and Prevention of Post-Partum Relapses with Progestin and Estradiol in Multiple Sclerosis (POPARTMUS) studies between 1992–1995 and 2005–2012, respectively. The association of neuraxial analgesia with the occurrence of a post-partum relapse was estimated by logistic regression analysis. Results: A total of 389 women were included, 215 from PRIMS and 174 from POPARTMUS. In total, 156 women (40%) had neuraxial analgesia. Overall, 24% experienced a relapse during pregnancy and 25% in the 3 months post-partum. Women with a pregnancy relapse were more likely to have a post-partum relapse (odds ratio (OR) = 1.83, p = 0.02), independently of the use of neuraxial analgesia. There was no association between neuraxial analgesia and post-partum relapse (OR = 1.08, p = 0.78). Conclusion: Neuraxial analgesia was not associated with an increased risk of post-partum relapses, whatever multiple sclerosis (MS) activity during pregnancy.

Objectives The dorsal vagal complex (DVC) senses insulin and controls glucose homeostasis, feeding behaviour and body weight. Three-days of high-fat diet (HFD) in rats are sufficient to induce insulin resistance in the DVC and impair its ability to regulate feeding behaviour. HFD-feeding is associated with increased dynamin-related protein 1 (Drp1)-dependent mitochondrial fission in the DVC. We investigated the effects that altered Drp1 activity in the DVC has on feeding behaviour. Additionally, we aimed to uncover the molecular events and the neuronal cell populations associated with DVC insulin sensing and resistance. Methods Eight-week-old male Sprague Dawley rats received DVC stereotactic surgery for brain infusion to facilitate the localised administration of insulin or viruses to express mutated forms of Drp1 or to knockdown inducible nitric oxide synthase (iNOS) in the NTS of the DVC. High-Fat diet feeding was used to cause insulin resistance and obesity. Results We showed that Drp1 activation in the DVC increases weight gain in rats and Drp1 inhibition in HFD-fed rats reduced food intake, weight gain and adipose tissue. Rats expressing active Drp1 in the DVC had higher levels of iNOS and knockdown of DVC iNOS in HFD-fed rats led to a reduction of food intake, weight gain and adipose tissue. Finally, inhibiting mitochondrial fission in DVC astrocytes was sufficient to protect rats from HFD-dependent insulin resistance, hyperphagia, weight gain and fat deposition. Conclusion We uncovered new molecular and cellular targets for brain regulation of whole-body metabolism, which could inform new strategies to combat obesity and diabetes.

A simple approach to enable water-management agencies employing free data to create a single set of water quality predictive equations with satisfactory accuracy is proposed. Multiple regression-derived equations based on surface reflectance, band ratios, and environmental factors as predictor variables for concentrations of Total Suspended Solids (TSS) and Total Nitrogen (TN) were derived using a hybrid forward-selection method that considers both p-value and Variance Inflation Factor (VIF) in the forward-selection process. Landsat TM, ETM+, and OLI/TIRS images were jointly utilized with environmental factors, such as wind speed and water surface temperature, to derive the single set of equations. Through splitting data into calibration and validation groups, the coefficients of determination are 0.73 for TSS calibration and 0.70 for TSS validation, respectively. The coefficients of determination for TN calibration and validation are 0.64 and 0.37, respectively. Among all chosen predictor variables, ratio of reflectance of visible red (Band 3 for Landsat TM and ETM+, or Band 4 for Landsat OLI/TIRS) to visible blue (Band 1 for Landsat TM and ETM+, or Band 2 for Landsat OLI/TIRS) has a strong influence on the predictive power for TSS retrieval. Environmental factors including wind speed, remote sensing-derived water surface temperature, and time difference (in days) between the image acquisition and water sampling were found to be important in water-quality quantity estimation. The hybrid forward-selection method consistently yielded higher validation accuracy than that of the conventional forward-selection approach.

A simple approach to enable water-management agencies employing free data to achieve the goal of using a single set of predictive equations for water-quality retrievals with satisfactory accuracy is proposed. Multiple regression-derived equations based on surface reflectance, band ratios, and environmental factors as predictor variables for concentrations of Total Suspended Solids (TSS), Total Nitrogen (TN), and Total Phosphorus (TP) were derived using a hybrid forward-selection method that considers Variance Inflation Factor (VIF) in the forward-selection process. Landsat TM, ETM+, and OLI/TIRS images were jointly utilized with environmental factors, such as wind speed and water surface temperature, to derive the single set of equations. The coefficients of determination of the best-fitting resultant equations varied from 0.62 to 0.79. Among all chosen predictor variables, ratio of reflectance of visible red (Band 3 for Landsat TM and ETM+, or Band 4 for Landsat OLI/TIRS) to visible blue (Band 1 for Landsat TM and ETM+, or Band 2 for Landsat OLI/TIRS) has a strong influence on the predictive power for TSS retrieval. Environmental factors including wind speed, remote sensing-derived water surface temperature, solar altitude, and time difference (in days) between the image acquisition and water sampling were found important in water-quality parameter estimation.

As supported by the literature, forearm shaft fractures in adults have to be assimilated to articular fractures. The reduction and anatomical synthesis of these fractures is the goal of treatment and it is important to avoid complications and to aim at a complete functional restoration.

Floodplain forests serve a critical function in the global carbon cycle because floodplains constitute an important carbon sink compared with other terrestrial ecosystems. Forests on dynamic floodplain landscapes, such as those created by river meandering processes, are characterized by uneven-aged trees and exhibit high spatial variability, reflecting the influence of interacting fluvial, hydrological, and ecological processes. Detailed and accurate mapping of aboveground biomass (AGB) on floodplain landscapes characterized by uneven-aged forests is critical for improving estimates of floodplain-forest carbon pools, which is useful for greenhouse gas (GHG) life cycle assessment. It would also help improve our process understanding of biomorphodynamics of river-floodplain systems, as well as planning and monitoring of conservation, restoration, and management of riverine ecosystems. Using stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), and Cubist, we remotely estimate AGB of a bottomland hardwood forest on a meander bend of a dynamic lowland river. As predictors, we use 30-m and 10-m multispectral image bands (Landsat 7 ETM+ and SPOT 5, respectively) and ancillary data. Our findings show that SGB and MARS significantly outperform Cubist, which is used for U.S. national-scale forest biomass mapping. Across all data-experiments and algorithms, at 10-m spatial resolution, SGB yields the best estimates (RMSE = 22.49 tonnes/ha; coefficient of determination ( R 2 ) = 0.96) when geomorphometric data are also included. On the other hand, at 30-m spatial resolution, MARS yields the best estimates (RMSE = 29.2 tonnes/ha; R 2 = 0.94) when image-derived data are also included. By enabling more accurate AGB mapping of floodplains characterized by uneven-aged forests, SGB and MARS provide an avenue for improving operational estimates of AGB and carbon at local, regional/continental, and global scales.

Background Neuropsychiatric manifestations are common in patients with systemic lupus erythematosus (SLE). Furthermore, subclinical brain damage occurs in an even higher fraction of patients. However, little is known about the effect of these phenomena on brain connectivity. MRI-based connectomics relies on graph analysis of structural and functional images to detect alterations of the topographic organization of the brain and has been successfully employed to dissect network disassembly in neuroinflammatory diseases such as multiple sclerosis (MS) and Devic9s syndrome. Objectives To investigate the topographic organization of the brain of patients with SLE with and without neuropsychiatric manifestations. Methods Thirty-two patients with SLE (12 with overt neuropsychiatric involvement as per ACR criteria) were enrolled and compared with 32 healthy controls (HC) and 32 patients with relapsing-remitting MS, all matched for sex, age and disease duration (where applicable). Diffusion tensor (DT) and dual-echo MRI scans were obtained. Structural connectivity matrices between 116 cortical and subcortical brain regions were estimated and global and nodal network metrics were calculated. Results Conventional MRI revealed that patients with SLE had significantly higher T2-lesional volumes when compared to controls (p Conclusions Structural alterations of global and regional brain connectivity occur in patients with SLE, irrespectively of the clinical phenotype. AntiDNA-positive patients are characterized by a more severe phenotype, which is similar to that of patients with relapsing-remitting MS. References Sabbadini MG et al, Lupus, 1999. Filippi M et al., Lancet Neurol, 2013. Rocca MA et al., Brain Struct Funct, 2016. Disclosure of Interest None declared

New Findings What is the topic of this review? This review documents a metabolic role of insulin action in brain. What advances does it highlight? This review highlights the role of insulin signalling in the hypothalamus and dorsal vagal complex in the regulation of hepatic glucose production and food intake. Insulin resistance is a hallmark feature of type 2 diabetes and obesity. In addition to the classical view that insulin resistance in the liver, muscle and fat disrupts glucose homeostasis, studies in the past decade have illustrated that insulin resistance in the hypothalamus dysregulates hepatic glucose production and food intake, leading to type 2 diabetes and obesity. This invited review argues that in addition to the hypothalamus, insulin signalling in the dorsal vagal complex regulates hepatic glucose production and food intake. A thorough understanding of the physiological and pathophysiological mechanisms of insulin action in the hypothalamus and dorsal vagal complex is necessary in order to identify therapeutic targets for obesity and type 2 diabetes.

Research on aboveground biomass (AGB) retrieval via remote sensing in floodplain forests, in particular, is urgently needed for improved understanding of carbon cycling in such areas. AGB estimation is particularly challenging in floodplain forests, which are characterized by high spatial variability in AGB resulting from biogeomorphodynamic processes. In this study, we perform remote AGB retrieval for a deciduous riparian forest on a river meander bend based on hyperspectral/high-dimensional Hyperion bands and other input variables. We compare multivariate adaptive regression splines (MARS)-, stochastic gradient boosting (SGB)- and Cubist-based AGB estimates. Results show that MARS- and SGB-derived estimates are significantly more accurate than Cubist-based AGB. The most accurate MARS and SGB estimates have a coefficient of determination, R2, of 0.97 and 0.95, respectively, whereas the Cubist estimate with the lowest error has an R2 of 0.85. MARS and SGB AGB are not significantly different, however. Thes...

Accurate mapping of water surface boundaries in rivers is an important step for monitoring water stages, estimating discharge, flood extent, and geomorphic response to changing hydrologic conditions, and assessing riverine habitat. Nonetheless, it is a challenging task in spatially and spectrally heterogeneous river environments, commonly characterized by high spatiotemporal variations in morphology, bed material, and bank cover. In this study, we investigate the influence of channel morphology and bank characteristics on the delineation of water surface boundaries in rivers using high spatial resolution passive remote sensing and a template-matching (object-based) algorithm, and compare its efficacy with that of Support Vector Machine (SVM) (pixel-based) algorithm. We perform a detailed quantitative evaluation of boundary-delineation accuracy using spatially explicit error maps in tandem with the spatial maps of geomorphic and bank classes. Results show that template matching is more successful than SVM in delineating water surface boundaries in river sections with spatially challenging geomorphic landforms (e.g. sediment bar structures, partially submerged sediment deposits) and shallow water conditions. However, overall delineation accuracy by SVM is higher than that of template matching (without iterative hierarchical learning). Vegetation and water indices, especially when combined with texture information, improve the accuracy of template matching, for example, in river sections with overhanging trees and shadows – the two most problematic conditions in water surface boundary delineation. By identifying the influence of channel morphology and bank characteristics on water surface boundary mapping, this study helps determine river sections with higher uncertainty in delineation. In turn, the most suitable methods and data sets can be selectively utilized to improve geomorphic/hydraulic characterization. The methodology developed here can also be applied to similar studies on other geomorphic landforms including floodplains, wetlands, lakes, and coastlines. Copyright © 2014 John Wiley & Sons, Ltd.

Insulin signaling in the hypothalamus regulates food intake and hepatic glucose production in rodents. Although it is known that insulin also activates insulin receptor in the dorsal vagal complex (DVC) to lower glucose production through an extracellular signal–related kinase 1/2 (Erk1/2)–dependent and phosphatidylinositol 3-kinase (PI3K)–independent pathway, it is unknown whether DVC insulin action regulates food intake. We report here that a single acute infusion of insulin into the DVC decreased food intake in healthy male rats. Chemical and molecular inhibition of Erk1/2 signaling in the DVC negated the acute anorectic effect of insulin in healthy rats, while DVC insulin acute infusion failed to lower food intake in high fat–fed rats. Finally, molecular disruption of Erk1/2 signaling in the DVC of healthy rats per se increased food intake and induced obesity over a period of 2 weeks, whereas a daily repeated acute DVC insulin infusion for 12 days conversely decreased food intake and body weight in healthy rats. In summary, insulin activates Erk1/2 signaling in the DVC to regulate energy balance.

Optical remote sensing imagery offers a cost-effective alternative to echo sounding and bathymetric light detection and ranging surveys for deriving high density bottom depth estimates for coastal and inland water bodies. The common practice of previous studies has been to calibrate a single global bathymetric inversion model for an entire image scene. The performance of conventional global models is limited when the bottom type and water quality vary spatially within the scene. To address the inadequacy of the conventional global models, this paper presents a geographically adaptive inversion model to better estimate bottom depth. Although the general mathematical form of the geographically adaptive model is the same, model parameters are optimally determined within a geographical region or a local area, in contrast to the entire scene in the global inversion model. By using high-resolution IKONOS and moderate-resolution Landsat satellite images, we demonstrated that regionally and locally calibrated inversion models can effectively address the problems introduced by spatial heterogeneity in water quality and bottom type, and provide significantly improved bathymetric estimates for more complex coastal waters.

Hyperspectral images (HSIs) contain hundreds of spectral bands, providing high-resolution spectral information pertaining to the Earth’s surface. Additionally, abundant spatial contextual information can also be obtained simultaneously from a HSI. To characterize the properties of ground objects, classification is the most widely-used technology in the field of remote sensing, where each pixel in a HSI is assigned to a pre-defined class. Over the past decade, deep learning has attracted increasing attention in the machine-learning and computer-vision domains, due to its favourable performances for various types of tasks, and it has been successfully introduced to the remote-sensing community. Instead of utilizing the shallow features within in a given image, which is the approach that is generally adopted in other conventional classification methods, deep-learning algorithms can extract hierarchical features from raw HSI data. Within the deep-learning framework, recurrent neural networks (RNNs), which are able to encode sequential features, have exhibited promising capabilities and have achieved encouraging performances, especially for the natural-language processing and speech-recognition communities. As multi-temporal remote-sensing images can be readily obtained from increasing numbers of satellite and unmanned aircraft systems, and since analysis of such multi-temporal data comprises a critical issue within numerous research subfields, including land-cover and land-change analyses, and land-resource management, RNNs have been applied in recent studies in order to extract temporal sequential features from multi-temporal remote-sensing images for the purpose of image classification. Apart from using multi-temporal image datasets, RNNs can also be utilized on a single image, where the spectral feature/band of each individual pixel can be taken as a sequential feature for the input layer of RNNs. However, the application of such sequential feature extraction that relies on a single image still needs to be further investigated since applying RNNs to spectral bands will directly introduce more parameters that need to be optimized, consequently increasing the total training time.In this study, we propose a novel RNN-based HSI classification framework. In this framework, unlabelled pixels obtained from a single image are considered when constructing sequential features. Two spatial similarity measurements, referred to as pixel-matching and block-matching, respectively, are employed to extract pixels that are “similar” to the target pixel. Then, the sequential feature of the target pixel is constructed by exploiting several of the most “similar” pixels and ordering them based on their similarities to the target pixel. The aforementioned two schemes are advantageous, as unlabelled pixels within the given HSI are taken into consideration for similarity measurement and sequential feature construction for the RNN model. Moreover, the block-matching scheme also takes advantage of spatial contextual information, which has been widely utilized in spatial-spectral-based HSI classification methods. To evaluate the proposed methods, two benchmark HSIs are used, including a HSI collected over Pavia University, Italy by the airborne Reflective Optics System Imaging Spectrometer (ROSIS) sensor, and an image acquired over the Salinas Valley, California, USA via the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Spatio-temporally coincident ground-reference data accompanies each of these respective HSIs. In addition, the proposed methods are compared with three state-of-the-art algorithms, including support vector machine (SVM), the 1-dimensional convolutional neural network (1DCNN), and the 1-dimensional RNN (1DRNN).Experimental results indicate that our proposed methods achieve markedly better classification performance compared with the baseline algorithms on both datasets. For example, for the Pavia University image, the block-matching based RNN achieves the highest overall classification accuracy, with 94.32% accuracy, which is 9.87% higher than the next most accurate algorithm of the aforementioned three baseline methods, which in this case is the 1DCNN, with 84.45% overall accuracy. More specifically, the block-matching method performs better than the pixel-matching method in terms of both quantitative and qualitative assessments. Based on visual assessment/interpretation of the classification maps, it is apparent that “salt-and-pepper” noise is markedly alleviated; with block-matching, smoother classified images are generated compared with pixel-matching-based methods and the three baseline algorithms. Such results demonstrate the effectiveness of utilizing spatial contextual information in the similarity measurement.

Classification is a common objective when analyzing hyperspectral images, where each pixel is assigned to a predefined label. Deep learning-based algorithms have been introduced in the remote-sensing community successfully in the past decade and have achieved significant performance improvements compared with conventional models. However, research on the extraction of sequential features utilizing a single image, instead of multi-temporal images still needs to be further investigated. In this paper, a novel strategy for constructing sequential features from a single image in long short-term memory (LSTM) is proposed. Two pixel-wise-based similarity measurements, including pixel-matching (PM) and block-matching (BM), are employed for the selection of sequence candidates from the whole image. Then, the sequential structure of a given pixel can be constructed as the input of LSTM by utilizing the first several matching pixels with high similarities. The resulting PM-based LSTM and BM-based LSTM are appealing, as all pixels in the whole image are taken into consideration when calculating the similarity. In addition, BM-based LSTM also utilizes local spectral-spatial information that has already shown its effectiveness in hyperspectral image classification. Two common distance measures, Euclidean distance and spectral angle mapping, are also investigated in this paper. Experiments with two benchmark hyperspectral images demonstrate that the proposed methods achieve marked improvements in classification performance relative to the other state-of-the-art methods considered. For instance, the highest overall accuracy achieved on the Pavia University image is 96.20% (using both BM-based LSTM and spectral angle mapping), which is an improvement compared with 84.45% overall accuracy generated by 1D convolutional neural networks.

International audience; High resolution synchrotron X-ray diffraction is used to study the dynamics of oxygen ordering in a La2CuO4.08 single crystal as a function of the temperature and of the photon flux. We have observed the occurrence of a phase separation between disordered and 3D long-range ordered domains of interstitial oxygen atoms (the latter being commensurate with the lattice). We are able to study and control the phase separation by irradiating the sample while varying the temperature in a range between 350 K and 250 K. These results shed new light on the oxygen ordering in cuprates; in addition, we show that in such systems it is possible to manipulate and to control structural inhomogeneities at the atomic scale using X-ray diffraction.

The prevalence of the obesity and diabetes epidemic has triggered tremendous research investigating the role of the central nervous system (CNS) in the regulation of food intake, body weight gain and glucose homeostasis. This invited review focuses on the role of two pancreatic hormones--insulin and glucagon--that trigger signaling pathways in the brain to regulate energy and glucose homeostasis. Unlike in the periphery, insulin and glucagon signaling in the CNS does not seem to have opposing metabolic effects, as both hormones exert a suppressive effect on food intake and weight gain. They signal through different pathways and alter different neuronal populations suggesting a complementary action of the two hormones in regulating feeding behavior. Similar to its systemic effect, insulin signaling in the brain lowers glucose production. However, the ability of glucagon signaling in the brain to regulate glucose production remains unknown. Future studies that aim to dissect insulin and glucagon signaling in the CNS that regulate energy and glucose homeostasis could unveil novel signaling molecules to lower body weight and glucose levels in obesity and diabetes.

Glucagon activates hepatic protein kinase A (PKA) to increase glucose production, but the gluco-stimulatory effect is transient even in the presence of continuous intravenous glucagon infusion. Continuous intravenous infusion of insulin, however, inhibits glucose production through its sustained actions in both the liver and the mediobasal hypothalamus (MBH). In a pancreatic clamp setting, MBH infusion with glucagon activated MBH PKA and inhibited hepatic glucose production (HGP) in rats, as did central glucagon infusion in mice. Inhibition of glucagon receptor-PKA signaling in the MBH and hepatic vagotomy each negated the effect of MBH glucagon in rats, whereas the central effect of glucagon was diminished in glucagon receptor knockout mice. A sustained rise in plasma glucagon concentrations transiently increased HGP, and this transiency was abolished in rats with negated MBH glucagon action. In a nonclamp setting, MBH glucagon infusion improved glucose tolerance, and inhibition of glucagon receptor-PKA signaling in the MBH enhanced the ability of intravenous glucagon injection to increase plasma glucose concentrations. We also detected a similar enhancement of glucose concentrations that was associated with a disruption in MBH glucagon signaling in rats fed a high-fat diet. We show that hypothalamic glucagon signaling inhibits HGP and suggest that hypothalamic glucagon resistance contributes to hyperglycemia in diabetes and obesity.

Delineation of river-flow boundaries constitutes an important step in various river-related studies, including river hydraulic modeling, flow-width estimations, and river and floodplain habitat mapping and assessment. Increasing the level of automation of delineation of flow boundaries from synoptic remote-sensing images provides great potential, by reducing the labor cost, especially for studies focusing on long river reaches and those examining flow changes over time. This article investigates the boundary delineation of river channel flow from aerial photographs using Support Vector Machine (SVM) and image-derived ancillary data layers. It also includes a quantitative evaluation of delineation accuracy. The findings show that SVM performs satisfactory delineations of the boundaries, and the ancillary data layers generated using edge detectors and spatial domain texture statistics particularly increase delineation accuracy. Moreover, a multiscale evaluation scheme allows for examining the performance of...

The identification of factors that promote β cell proliferation could ultimately move type 1 diabetes treatment away from insulin injection therapy and toward a cure. We have performed high-throughput, cell-based screens using rodent β cell lines to identify molecules that induce proliferation of β cells. Herein we report the discovery and characterization of WS6, a novel small molecule that promotes β cell proliferation in rodent and human primary islets. In the RIP-DTA mouse model of β cell ablation, WS6 normalized blood glucose and induced concomitant increases in β cell proliferation and β cell number. Affinity pulldown and kinase profiling studies implicate Erb3 binding protein-1 and the IκB kinase pathway in the mechanism of action of WS6.

The Mission-Aransas coastal region (MACR) in Texas is home to settlements vulnerable to coastal hazards. The region also contains significant biodiversity including several endangered species. The habitats in the bays and estuaries of MACR are especially sensitive to changes in land use/land cover (LULC) within the drainage basins upstream. We examine LULC change in the MACR from 1990 to 2010 and its implications for coastal vulnerability of the built environment and for the biodiversity in the region. Our findings show that, from 1990 to 2010, about a quarter of the MACR experienced LULC change. Developed land increased 71% (from 118 km 2 in 1990 to 203 km 2 in 2010), by far the greatest proportional change among all land cover classes. The rate of increase of developed land was slightly higher along the coast, 75% (from 65 km 2 in 1990 to 114 km 2 in 2010). Almost 90% of all developed land was within 50 km of the protected areas in both years. Overall, our findings point to increased exposure of the people and infrastructure to coastal hazards. Given the high social vulnerability in the study area, our study can inform formulation of sustainable management options that minimize both the coastal vulnerability of people and infrastructure and the pressure on the protected areas that are critical for conservation of biodiversity in the region.

Evidence continues to emerge detailing the myriad of ways the gut microbiota influences host energy homeostasis. Among the potential mechanisms, short chain fatty acids (SCFAs), the byproducts of microbial fermentation of dietary fibers, exhibit correlative beneficial metabolic effects in humans and rodents, including improvements in glucose homeostasis. The underlying mechanisms, however, remain elusive. We here report that one of the main bacterially produced SCFAs, propionate, activates ileal mucosal free fatty acid receptor 2 to trigger a negative feedback pathway to lower hepatic glucose production in healthy rats in vivo. We further demonstrate that an ileal glucagon-like peptide-1 receptor-dependent neuronal network is necessary for ileal propionate and long chain fatty acid sensing to regulate glucose homeostasis. These findings highlight the potential to manipulate fatty acid sensing machinery in the ileum to regulate glucose homeostasis.

Background In Parkinson's disease (PD), gait disorders lead to increased risk of falls and patients' reduced participation and independence. Several observations suggest that a single session of focal muscle vibration (fMV) applied to trunk or lower limb muscles during gait may improve several gait variables in patients with PD. The possible long-term beneficial effects of repetitive sessions of fMV (r-fMV) on gait of patients with PD have been investigated. Methods A randomized, controlled trial study has been conducted in an outpatient rehabilitation department. Twenty patients with PD diagnosis have been randomized in two groups: “real” or “sham” r-fMV application to quadriceps and paraspinal muscles in patients with PD. Gait was evaluated with objective gait analysis, and a number of variables, including velocity, step length, stride length, percentage of stance, double support duration, cadence, swing velocity, and step width, have been measured. Gait analysis was performed before and 24 hours and 1 and 3 weeks after r-fMV. Results After real, but not sham, r-fMV, patients with PD had significant gait improvement as a result of increased walking velocity and stride length. The r-fMV-induced beneficial after effects lasted at least 1 week after the end of stimulation. Conclusions Data emerging from our pilot randomized, controlled trial study suggest that r-fMV may improve gait disorders in patients with PD. r-fMV might be a feasible, safe approach for possibly improving gait disorders in patients with PD and might enhance the impact of specific rehabilitation programs in PD.

The increasing interest on pervasive sensor networks and the steady development of electronic devices with low power consumption motivates the research on electronic systems capable of harvesting energy from the surrounding environment. The use of microelectronic technologies allows a series of circuit optimizations paving the way toward the exploitation of sub‐microwatt power regimes, thanks to the significant reduction of parasitics and to the efficiency of custom designed circuit topologies. This chapter reviews some of the most promising integrated circuits (ICs) for power harvesting, conversion, and management, achieved either by industry or academia, intended for exploiting several different types of energy transducers. The chapter reviews a specific case study consisting in a nanopower IC for harvesting power from multiple energy sources. It focuses on the advantages conferred by nanoelectronic ICs in this specific field. The chapter highlights recent achievements presented in scientific literature, with a special focus on nanopower‐integrated solutions.

M. L. Dell'Acqua, L. Lorenzini, G. D'Intino, S. Sivilia, P. Pasqualetti, V. Panetta, M. Paradisi, M. M. Filippi, C. Baiguera, M. Pizzi, L. Giardino, P. M. Rossini and L. Calza (2012) Neuropathology and Applied Neurobiology38, 454–470 Functional and molecular evidence of myelin- and neuroprotection by thyroid hormone administration in experimental allergic encephalomyelitis Aims: Recent data in mouse and rat demyelination models indicate that administration of thyroid hormone (TH) has a positive effect on the demyelination/remyelination balance. As axonal pathology has been recognized as an early neuropathological event in multiple sclerosis, and remyelination is considered a pre-eminent neuroprotective strategy, in this study we investigated whether TH administration improves nerve impulse propagation and protects axons. Methods: We followed up the somatosensory evoked potentials (SEPs) in triiodothyronine (T3)-treated and untreated experimental allergic encephalomyelitis (EAE) Dark-Agouti female rats during the electrical stimulation of the tail nerve. T3 treatment started on the 10th day post immunization (DPI) and a pulse administration was continued until the end of the study (33 DPI). SEPs were recorded at baseline (8 DPI) and the day after each hormone/ vehicle administration. Results: T3 treatment was associated with better outcome of clinical and neurophysiological parameters. SEPs latencies of the two groups behaved differently, being briefer and closer to control values (=faster impulse propagation) in T3-treated animals. The effect was evident on 24 DPI. In the same groups of animals, we also investigated axonal proteins, showing that T3 administration normalizes neurofilament immunoreactivity in the fasciculus gracilis and tau hyperphosphorylation in the lumbar spinal cord of EAE animals. No sign of plasma hyperthyroidism was found; moreover, the dysregulation of TH nuclear receptor expression observed in the spinal cord of EAE animals was corrected by T3 treatment. Conclusions: T3 supplementation results in myelin sheath protection, nerve conduction preservation and axon protection in this animal model of multiple sclerosis.

For aquatic studies, radiative transfer (RT) modeling can be used to compute hyperspectral above-surface remote sensing reflectance that can be utilized for inverse model development. Inverse models can provide bathymetry and inherent-and bottom-optical property estimation. Because measured oceanic field/organic datasets are often spatio-temporally sparse, synthetic data generation is useful in yielding sufficiently large datasets for inversion model development; however, these forward-modeled data are computationally expensive and time-consuming to generate. This study establishes the magnitude of wall-clock-time savings achieved for performing large, aquatic RT batch-runs using parallel computing versus a sequential approach. Given 2,600 simulations and identical compute-node characteristics, sequential architecture required ~100 hours until termination, whereas a parallel approach required only ~2.5 hours (42 compute nodes)—a 40x speed-up. Tools developed for this parallel execution are discussed.

Background QTc prolongation is a potentially life-threatening side effect of some antidepressants and antipsychotics, and a number of other electrocardiogram (ECG) alterations were associated with psychotropic drugs. Poor knowledge is available about the genetic risk factors of QTc prolongation during treatment with these drugs. Polymorphisms in the α1-subunit of cardiac L-type calcium channel (CACNA1C) were associated with several types of arrhythmic diseases (including Long QT syndrome), but no data are available in regard to their possible effect on QTc duration during psychotropic drugs use. The present study primarily aimed to investigate QTc variation in relation to the prescription of psychotropic drugs stratified according to their cardiovascular risk [3]. The possible modulating effect of polymorphisms in the α1-subunit of cardiac L-type calcium channel (CACNA1C) gene was considered. As secondary aim, we investigated other ECG alterations possibly associated with psychotropic drugs. Methods 213 patients with a diagnosis of mood, anxiety or psychotic disorder who required a pharmacological treatment with antidepressant and/or antipsychotic drugs were included. A cross-sectional sample (n=145) had one standard ECG at baseline while a prospective sample (n=68) had a baseline and follow-up ECG. 13 SNPs in the CACNA1C gene were genotyped in both samples. An independent prospective sample was available from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. Patients having a baseline and follow-up ECG were selected (n=515) and CACNA1C polymorphisms were extracted from imputed genome-wide data. In the prospective samples changes in ECG intervals (QTc, PR, QRS, RR, and QR) between baseline and follow-up were analyzed in relation to the number of psychotropic drugs stratified according to their cardiovascular risk (from moderate-high to none). In the cross-sectional sample ECG parameters were compared among groups taking psychotropic drugs with different cardiovascular risk. The effect of genotypes on these associations was tested. Results There was no evidence of mean QTc prolongation or increased risk of QTc prolongation ≥ 20 ms in association with risk drugs. The prescription of drugs with cardiovascular risk was less common in older subjects (p=0.04) or with cardiovascular comorbidities (p=0.02). Other factors (gender, ethnicity, baseline QTc, kidney function) affected QTc. rs1006737 modulated QTc duration/changes in the original prospective sample (p=0.04) and in cross-sectional sample (p=0.002) and four polymorphisms in linkage disequilibrium with it modulated QTc changes in the CATIE. An association between risk drugs and shorter RR interval or higher heart rate was found in all samples. Discussion A relevant effect of psychotropic drugs with cardiovascular risk on QTc duration was not found. A number of other factors may influence QTc. CACNA1C rs1006737 may modulate the risk of QTc prolongation in patients treated with risk drugs. Finally, high resting heart rate, even within the accepted normal range, should not be overlooked in patients treated with psychotropic drugs since it was independently associated with increased risk of all-causes mortality.

We have considered a formalism, known as partial intensity approach (PIA), previously developed to quantitatively analyze reflection electron energy loss (REEL) spectra [1,2]. The aim of the approach is, in particular, to recover the single scattering distribution of energy losses and to separate it into bulk and surface contributions, respectively referred to as the differential inverse inelastic mean free path (DIIMFP) and the differential surface excitation parameter (DSEP). As compared to [1] and [2], we have implemented a modified approach, and we have applied it to the specific geometry of the cylindrical mirror analyzer (CMA), used to acquire the REEL spectra shown here. Silicon, a material with well-defined surface and bulk plasmons, is taken as a case study to investigate the approach as a function of electron energy over the energy range typical of REELS, i.e. from 250 eV to 2 keV. Our goal is, on the one hand, to examine possible limits for the applicability of the approach and, on the other hand, to test a basic assumption of the PIA, namely that a unique DIIMFP and a unique DSEP account for REEL spectra, whatever the acquisition conditions (i.e. electron energy or angle of surface crossing) are. We find that a minimum energy exists below which the PIA cannot be applied and that the assumption of REEL spectra accounted for by unique DIIMFP and DSEP is indeed an approximation.

Signaling through Toll-like receptor 2 (TLR2) promotes inflammation and modulates CD4+CD25+ regulatory T cells (Tregs). We assessed mechanistically how this molecule would alter immunoregulation in type 1 diabetes (T1D). We also asked whether TLR2 may be involved in our recent discovery that viral infection can protect from autoimmune diabetes by expanding and invigorating regulatory T cells (Tregs). Treatment of prediabetic mice with a synthetic TLR2 agonist diminished T1D and increased the number and function of CD4+CD25+ Tregs, also conferring dendritic cells (DCs) with tolerogenic properties. TLR2 ligation also promoted the expansion of Tregs upon culture with DCs and ameliorated their capacity to prevent the disease. Protection from T1D by lymphocytic choriomeningitis virus (LCMV) infection depended on TLR2. LCMV increased the frequency of CD4+CD25+ Tregs and their production of TGF-β more significantly in wild type than TLR2-deficient mice. Furthermore, LCMV infection in vivo or LCMV-infected DCs in vitro rendered, via TLR2, CD4+CD25+ Tregs capable of diminishing T1D. We identify novel mechanisms by which TLR2 promotes immunoregulation and controls autoimmune diabetes in naïve or infected hosts. This work should help understand T1D etiology and develop novel immune-based therapeutic interventions.

Mouse protein-25 (MO25) isoforms bind to the STRAD pseudokinase and stabilise it in a conformation that can activate the LKB1 tumour suppressor kinase. We demonstrate that by binding to several STE20 family kinases, MO25 has roles beyond controlling LKB1. These new MO25 targets are SPAK/OSR1 kinases, regulators of ion homeostasis and blood pressure, and MST3/MST4/YSK1, involved in controlling development and morphogenesis. Our analyses suggest that MO25α and MO25β associate with these STE20 kinases in a similar manner to STRAD. MO25 isoforms induce approximately 100-fold activation of SPAK/OSR1 dramatically enhancing their ability to phosphorylate the ion cotransporters NKCC1, NKCC2 and NCC, leading to the identification of several new phosphorylation sites. siRNA-mediated reduction of expression of MO25 isoforms in mammalian cells inhibited phosphorylation of endogenous NKCC1 at residues phosphorylated by SPAK/OSR1, which is rescued by re-expression of MO25α. MO25α/β binding to MST3/MST4/YSK1 also stimulated kinase activity three- to four-fold. MO25 has evolved as a key regulator of a group of STE20 kinases and may represent an ancestral mechanism of regulating conformation of pseudokinases and activating catalytically competent protein kinases.

Computational trends toward shared services suggest the need to automatically manage spatial scale for overlapping applications. In three experiments using high-spatial-resolution optical imagery and LIDAR data to extract impervious, forest, and herbaceous classes, this study optimized C5.0 rule sets according to: (1) spatial scale within an image tile; (2) spatial scale within spectral clusters; and (3) stability of predicted accuracies based on cross validation. Alteration of the image segmentation scale parameter affected accuracy as did synergy with LIDAR derivatives. Within the tile examined, forest and herbaceous areas benefited more from optical and LIDAR synergy than did impervious surfaces.

One of the requirements for efficient vaccination against infection is to achieve the best combination of an adequate adjuvant with the antigenic information to deliver. Although plasmid DNA is a promising tool bearing the unique potential to activate humoral and cellular immunity, an actual challenge is to increase plasmid immunogenicity in human vaccination protocols in which efficacy has proven rather limited. Previous work showed that the bacterial DNA backbone of the plasmid has potent adjuvant properties because it contains CpG motifs that are particular activating nucleotidic sequences. Among TLRs, which are key sensors of microbial products, TLR9 can detect CpG motifs and confer activation of APCs, such as dendritic cells. However, whether the immunogenic properties of plasmid DNA involve TLR9 signaling has not been clearly established. In the current study, we demonstrate that TLR9 determines the effectiveness of vaccination against lethal lymphocytic choriomeningitis virus infection using plasmid DNA in a prime, but not prime-boost, vaccination regimen. Furthermore, we provide evidence that the presence of TLR9 in dendritic cells is necessary for effective and functional priming of virus-specific CD8+ T cells upon plasmid exposure in vitro or single-dose vaccination in vivo. Therefore, at single or low vaccine doses that are often used in human-vaccination protocols, CpG/TLR9 interactions participate in the immunogenicity of plasmid DNA. These results suggest that the TLR9 signaling pathway is involved in the efficacy of plasmid vaccination; therefore, it should remain a focus in the development or amelioration of vaccines to treat infections in humans.

We use effective medium theory (EMT) as a framework to describe reflection electron energy loss spectra (REELS) from polycrystalline graphite and amorphous carbon (a-C), the latter obtained by ion irradiation of the former. Such materials, isotropic at a macroscopic scale, are anisotropic at the micro- or nano-scale. For them, we prove the value of the concept of effective isotropic energy loss function to describe EELS in the plasmon region. Based on this function, we calculate a differential inverse inelastic mean free path (DIIMFP) which, compared to experimental spectra from pristine and ion-irradiated polycrystalline graphite, is able to reproduce their main features. Copyright © 2010 John Wiley & Sons, Ltd.

We examine how access regimes, defined by a set of interrelated institutions and organizations, facilitated the flow of production resources and benefits that resulted in patterns of land change in the Brazilian Cerrado. We analyzed remotely sensed data (Landsat MSS, TM, +ETM) for three time periods (1972/1973–1986, 1986–1992, 1992–2002) with qualitative and archival data for eastern Mato Grosso state. Overall we found that land privately colonized was cleared more rapidly and extensively than lands under no colonization scheme. We also identified significant spatial variability in Cerrado conversion within and outside colonization areas and variability of annual rates of Cerrado conversion during each period. We explain that farmers in the Cerrado engaged in land-leasing and production contracts and worked through cooperatives and firms to marshal resources, including credit, technology, and inputs, which, in turn, influenced land-use decisions and regional patterns of land-cover change. We conclude that...

Solving Pseudokinases Mutations of the protein kinase LKB1 are associated with cancer in humans. Many kinases are activated by phosphorylation, but LKB1 is activated by STRADα, a pseudokinase that is similar to protein kinases and binds ATP, but does not phosphorylate substrates. By solving the crystal structure of an activating complex containing LKB, Zeqiraj et al. (p. 1707 , published online 5 November) show that STRADα works with another protein, MO25α, to hold LKB1 in an active conformation. The results may help explain the evolutionary origin of pseudokinases, the biological roles of other pseudokinases, and the mechanisms of disease-causing mutations in LKB1.

Elastic Peak Electron Spectroscopy (EPES) is used to characterize the H termination of the (1 0 0) diamond surface. Two specific features of the technique make this possible, namely surface sensitivity and the ability to directly detect H. An approach to quantify the H content for the particular spatial distribution involved here is discussed and a measure of H surface coverage is given.

The Brazilian Cerrado is threatened by agricultural land use conversion. Accurate quantification of overall and subtype Cerrado distributions is essential for regional monitoring. In this research, unsupervised fuzzy ARTMAP was compared against conventional k-means classification of Cerrado and agriculture, based on Hyperion satellite data. We systematically tested a range of fuzzy ARTMAP parameters, determining the best parameter combinations. The effect of an additional surface liquid-water input vector was also tested. Similar results were obtained when only Hyperion apparent surface reflectance data were used; fuzzy ARTMAP, however, was generally markedly more accurate than k-means when the additional surface liquid-water input was included.

We report a systematic study of Pr 1-x Ca x MnO 3 (x = 0.4 and 0.6) thin films grown on LaAlO 3 (LAO) substrate (PCMO/LAO). X-ray diffraction measurements have shown that the PCMO/LAO film is [101]-oriented and under compressive strain due to the lattice mismatch. According to Raman spectroscopy the Jahn-Teller modes are suppressed under the application of pressure in the PCMO (x = 0.4) thin film. In particular, it was found that a pressure of 2 GPa suppresses the charge ordered state. Further high pressure measurements have confirmed that resistivity decreases linearly up to 2.4 GPa corresponding to a total reduction of about 35% in resistivity leading to a more conductive state on both concentrations. The temperature dependence of the resistivity has shown that the samples under pressure retain their semiconducting behavior. At ambient pressure the PCMO (x = 0.6) film shows a moderate magnetoresistance in the range 0-7 T and no metal to insulator transition (MIT). Raman spectroscopy confirmed that the application of a magnetic field of 1 T does not induce any remarkable changes on the electron-phonon interaction. Although, the hydrostatic pressure is not enough to induce a macroscopic metallic state, its effect is much greater than the one of the magnetic field. In addition, the effect of the 7 T magnetic field appears the same at ambient pressure and 2.5 GPa. Therefore the two effects of hydrostatic pressure and magnetic field do not seem to be coupled, at least up to the magnitudes studied.