Community-based assessment of the dynamics of urban landscape characteristics and ecosystem services in the rainforest and guinea savanna ecoregions of Nigeria.

Understanding the dynamics of urban landscapes and their impacts on ecological well-being is crucial for developing sustainable urban management strategies in times of rapid urbanisation. This study assesses the nature and drivers of the changing urban landscape and ecosystem services in cities located in the rainforest (Akure and Owerri) and guinea savannah (Makurdi and Minna) of Nigeria using a combination of remote sensing and socioeconomic techniques. Landsat 8 datasets provided spatial patterns of the normalised difference vegetation index (NDVI) and normalised difference built-up index (NDBI). A household survey involving the administration of a semi-structured questionnaire to 1552 participants was conducted. Diminishing NDVI and increasing NDBI were observed due to the rising trend of urban expansion, corroborating the perception of over 54% of the respondents who noted a decline in landscape ecological health. Residential expansion, agricultural practices, transport and infrastructural development, and fuelwood production were recognised as the principal drivers of landscape changes. Climate variability/change reportedly makes a 28.5%-34.4% (Negelkerke R2) contribution to the changing status of natural landscapes in Akure and Makurdi as modelled by multinomial logistic regression, while population growth/in-migration and economic activities reportedly account for 19.9%-36.3% in Owerri and Minna. Consequently, ecosystem services were perceived to have declined in their potential to regulate air and water pollution, reduce soil erosion and flooding, and mitigate urban heat stress, with a corresponding reduction in access to social services. We recommend that urban residents be integrated into management policies geared towards effectively developing and enforcing urban planning regulations, promoting urban afforestation, and establishing sustainable waste management systems.

Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling.

Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000-2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region's area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds = 330 %), land-use intensity (odds = 103 %), low soil quality (odds = 49 %), slope (odds = 29 %), and salinity of the groundwater (odds = 26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.

Mapping potentially groundwater-dependent vegetation in the Mediterranean biome using global geodata targeting site conditions and vegetation characteristics.

Groundwater-dependent vegetation (GDV) is essential for maintaining ecosystem functions and services, providing critical habitat for species, and sustaining human livelihoods. However, climate and land-use change are threatening GDV, highlighting the need for harmonised, global mapping of the distribution and extent of GDV. This need is particularly crucial in vulnerable biodiversity hotspots such as the Mediterranean biome. This study presents a novel multicriteria index to identify areas in the Mediterranean biome that provide suitable environmental conditions to support potentially groundwater-dependent vegetation (pGDV) where vegetation behaviour is also indicative of groundwater use. Global datasets targeting 1) groundwater vegetation interaction; 2) soil water holding capacity; 3) topographical landscape wetness potential; 4) land use land cover and 5) hydraulic conductivity of rocks have been combined for the first time in an easy-to-use index. Layer weightings from Analytical Hierarchy Process and Random Forest showed limited applicability on biome scale, but an unweighted overlay of eleven thematic layers produced plausible results. The final pGDV map indicates that 31 % of the natural vegetation in the Mediterranean biome likely depend on groundwater. Moreover, moderate to good agreement was found compared to actual GDV locations in Campania, Italy (91 % with at least moderate potential) and California, USA (87 % with at least moderate potential). The results provide valuable information for identifying regions with a substantial presence of pGDV in the Mediterranean biome and can be used for decision making, e.g. to prioritise field surveys and high-resolution remote sensing for GDV mapping. It can therefore support effective groundwater resource management and the conservation of biodiversity hotspots.

SORCS1 alters amyloid precursor protein processing and variants may increase Alzheimer's disease risk.

OBJECTIVE: Sorting mechanisms that cause the amyloid precursor protein (APP) and the ß-secretases and γ-secretases to colocalize in the same compartment play an important role in the regulation of Aß production in Alzheimer's disease (AD). We and others have reported that genetic variants in the Sortilin-related receptor (SORL1) increased the risk of AD, that SORL1 is involved in trafficking of APP, and that underexpression of SORL1 leads to overproduction of Aß. Here we explored the role of one of its homologs, the sortilin-related VPS10 domain containing receptor 1 (SORCS1), in AD. METHODS: We analyzed the genetic associations between AD and 16 SORCS1-single nucleotide polymorphisms (SNPs) in 6 independent data sets (2,809 cases and 3,482 controls). In addition, we compared SorCS1 expression levels of affected and unaffected brain regions in AD and control brains in microarray gene expression and real-time polymerase chain reaction (RT-PCR) sets, explored the effects of significant SORCS1-SNPs on SorCS1 brain expression levels, and explored the effect of suppression and overexpression of the common SorCS1 isoforms on APP processing and Aß generation. RESULTS: Inherited variants in SORCS1 were associated with AD in all datasets (0.001 < p < 0.049). In addition, SorCS1 influenced APP processing. While overexpression of SorCS1 reduced γ-secretase activity and Aß levels, the suppression of SorCS1 increased γ-secretase processing of APP and the levels of Aß. INTERPRETATIONS: These data suggest that inherited or acquired changes in SORCS1 expression or function may play a role in the pathogenesis of AD.

Quantifying and mapping ecosystem services supplies and demands: a review of remote sensing applications.

Ecosystems provide services necessary for the livelihoods and well-being of people. Quantifying and mapping supplies and demands of ecosystem services is essential for continuous monitoring of such services to support decision-making. Area-wide and spatially explicit mapping of ecosystem services based on extensive ground surveys is restricted to local scales and limited due to high costs. In contrast, remote sensing provides reliable area-wide data for quantifying and mapping ecosystem services at comparatively low costs, and with the option of fast, frequent, and continuous observations for monitoring. In this paper, we review relevant remote sensing systems, sensor types, and methods applicable in quantifying selected provisioning and regulatory services. Furthermore, opportunities, challenges, and future prospects in using remote sensing for supporting ecosystem services' quantification and mapping are discussed.

Saitohin, which is nested within the tau gene, interacts with tau and Abl and its human-specific allele influences Abl phosphorylation.

Saitohin (STH) is a gene unique to humans and their closest relatives whose function is not yet known. STH contains a single polymorphism (Q7R); the Q allele is human-specific and confers susceptibility to several neurodegenerative diseases. In previous work, we discovered that STH interacts with Peroxiredoxin 6 (Prdx6), a unique member of that family which is bifunctional and whose levels increase in Pick's disease. In this study, we report that STH also interacts with tau and the non-receptor tyrosine kinase c-Abl (Abl). Furthermore, Abl phosphorylates STH on its single tyrosine residue and STH increases tyrosine phosphorylation by Abl. The effect of Saitohin on Abl-mediated phosphorylation appears to be allele-specific, providing evidence for a new cellular function for STH.

Inhibition of tau polymerization with a cyanine dye in two distinct model systems.

In a host of neurodegenerative diseases Tau, a microtubule-associated protein, aggregates into insoluble lesions within neurons. Previous studies have utilized cyanine dyes as Tau aggregation inhibitors in vitro. Herein we utilize cyanine dye 3,3'-diethyl-9-methyl-thiacarbocyanine iodide (C11) to modulate Tau polymerization in two model systems, an organotypic slice culture model derived from Tau transgenic mice and a split green fluorescent protein complementation assay in Tau-expressing cells. In slice cultures, submicromolar concentrations (0.001 microm) of C11 produced a significant reduction of aggregated Tau and a corresponding increase in unpolymerized Tau. In contrast, treatment with a 1 microm dose promoted aggregation of Tau. These results were recapitulated in the complementation assay where administration of 1 microm C11 produced a significant increase in polymerized Tau relative to control, whereas treatment of cells with 0.01 microm C11 resulted in a marked reduction of aggregated Tau. In the organotypic slice cultures, modulation of Tau aggregation was independent of changes in phosphorylation at disease and microtubule binding relevant epitopes for both dosing regimes. Furthermore, treatment with 0.001 microm C11 resulted in a decrease in both total filament mass and number. There was no evidence of apoptosis or loss of synaptic integrity at either dose, however, whereas submicromolar concentrations of C11 did not interfere with microtubule binding, higher doses resulted in a decrease in the levels of microtubule-bound Tau. Overall, a cyanine dye can dissociate aggregated Tau in an ex vivo model of tauopathy with little toxicity and exploration of the use of these type of dyes as therapeutic agents is warranted.

A crop type dataset for consistent land cover classification in Central Asia.

Land cover is a key variable in the context of climate change. In particular, crop type information is essential to understand the spatial distribution of water usage and anticipate the risk of water scarcity and the consequent danger of food insecurity. This applies to arid regions such as the Aral Sea Basin (ASB), Central Asia, where agriculture relies heavily on irrigation. Here, remote sensing is valuable to map crop types, but its quality depends on consistent ground-truth data. Yet, in the ASB, such data are missing. Addressing this issue, we collected thousands of polygons on crop types, 97.7% of which in Uzbekistan and the remaining in Tajikistan. We collected 8,196 samples between 2015 and 2018, 213 in 2011 and 26 in 2008. Our data compile samples for 40 crop types and is dominated by "cotton" (40%) and "wheat", (25%). These data were meticulously validated using expert knowledge and remote sensing data and relied on transferable, open-source workflows that will assure the consistency of future sampling campaigns.

Biomass Assessment of Agricultural Crops Using Multi-temporal Dual-Polarimetric TerraSAR-X Data.

The biomass of three agricultural crops, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), was studied using multi-temporal dual-polarimetric TerraSAR-X data. The radar backscattering coefficient sigma nought of the two polarization channels HH and VV was extracted from the satellite images. Subsequently, combinations of HH and VV polarizations were calculated (e.g. HH/VV, HH + VV, HH × VV) to establish relationships between SAR data and the fresh and dry biomass of each crop type using multiple stepwise regression. Additionally, the semi-empirical water cloud model (WCM) was used to account for the effect of crop biomass on radar backscatter data. The potential of the Random Forest (RF) machine learning approach was also explored. The split sampling approach (i.e. 70% training and 30% testing) was carried out to validate the stepwise models, WCM and RF. The multiple stepwise regression method using dual-polarimetric data was capable to retrieve the biomass of the three crops, particularly for dry biomass, with R2 > 0.7, without any external input variable, such as information on the (actual) soil moisture. A comparison of the random forest technique with the WCM reveals that the RF technique remarkably outperformed the WCM in biomass estimation, especially for the fresh biomass. For example, the R 2 > 0.68 for the fresh biomass estimation of different crop types using RF whereas WCM show R 2 < 0.35 only. However, for the dry biomass, the results of both approaches resembled each other.

Impaired Mitochondrial Dynamics and Mitophagy in Neuronal Models of Tuberous Sclerosis Complex.

Tuberous sclerosis complex (TSC) is a neurodevelopmental disease caused by TSC1 or TSC2 mutations and subsequent activation of the mTORC1 kinase. Upon mTORC1 activation, anabolic metabolism, which requires mitochondria, is induced, yet at the same time the principal pathway for mitochondrial turnover, autophagy, is compromised. How mTORC1 activation impacts mitochondrial turnover in neurons remains unknown. Here, we demonstrate impaired mitochondrial homeostasis in neuronal in vitro and in vivo models of TSC. We find that Tsc1/2-deficient neurons accumulate mitochondria in cell bodies, but are depleted of axonal mitochondria, including those supporting presynaptic sites. Axonal and global mitophagy of damaged mitochondria is impaired, suggesting that decreased turnover may act upstream of impaired mitochondrial metabolism. Importantly, blocking mTORC1 or inducing mTOR-independent autophagy restores mitochondrial homeostasis. Our study clarifies the complex relationship between the TSC-mTORC1 pathway, autophagy, and mitophagy, and defines mitochondrial homeostasis as a therapeutic target for TSC and related diseases.

Unveiling Undercover Cropland Inside Forests Using Landscape Variables: A Supplement to Remote Sensing Image Classification.

The worldwide demand for food has been increasing due to the rapidly growing global population, and agricultural lands have increased in extent to produce more food crops. The pattern of cropland varies among different regions depending on the traditional knowledge of farmers and availability of uncultivated land. Satellite images can be used to map cropland in open areas but have limitations for detecting undergrowth inside forests. Classification results are often biased and need to be supplemented with field observations. Undercover cropland inside forests in the Bale Mountains of Ethiopia was assessed using field observed percentage cover of land use/land cover classes, and topographic and location parameters. The most influential factors were identified using Boosted Regression Trees and used to map undercover cropland area. Elevation, slope, easterly aspect, distance to settlements, and distance to national park were found to be the most influential factors determining undercover cropland area. When there is very high demand for growing food crops, constrained under restricted rights for clearing forest, cultivation could take place within forests as an undercover. Further research on the impact of undercover cropland on ecosystem services and challenges in sustainable management is thus essential.

Application of an adaptive control grid interpolation technique to morphological vascular reconstruction.

The problem of interslice magnetic resonance (MR) image reconstruction arises in a broad range of medical applications. In such cases, there is a need to approximate information present in the original subject that is not reflected in contiguously acquired MR images because of hardware sampling limitations. In the context of vascular morphology reconstruction, this information is required in order for subsequent visualization and computational analysis of blood vessels to be most effective. Toward that end we have developed a method of vascular morphology reconstruction based on adaptive control grid interpolation (ACGI) to function as a precursor to visualization and computational analysis. ACGI has previously been implemented in addressing various problems including video coding and tracking. This paper focuses on the novel application of the technique to medical image processing. ACGI combines features of optical flow-based and block-based motion estimation algorithms to enhance insufficiently dense MR data sets accurately with a minimal degree of computational complexity. The resulting enhanced data sets describe vascular geometries. These reconstructions can then be used as visualization tools and in conjunction with computational fluid dynamics (CFD) simulations to offer the pressure and velocity information necessary to quantify power loss. The proposed ACGI methodology is envisioned ultimately to play a role in surgical planning aimed at producing optimal vascular configurations for successful surgical outcomes.

Needle decompression in appalachia do obese patients need longer needles?

INTRODUCTION: Needle decompression of a tension pneumothorax can be a lifesaving procedure. It requires an adequate needle length to reach the chest wall to rapidly remove air. With adult obesity exceeding one third of the United States population in 2010, we sought to evaluate the proper catheter length that may result in a successful needle decompression procedure. Advance Trauma Life Support (ATLS) currently recommends a 51 millimeter (mm) needle, while the needles stocked in our emergency department are 46 mm. Given the obesity rates of our patient population, we hypothesize these needles would not have a tolerable success rate of 90%. METHODS: We retrospectively reviewed 91 patient records that had computed tomography of the chest and measured the chest wall depth at the second intercostal space bilaterally. RESULTS: We found that 46 mm needles would only be successful in 52.7% of our patient population, yet the ATLS recommended length of 51 mm has a success rate of 64.8%. Therefore, using a 64 mm needle would be successful in 79% percent of our patient population. CONCLUSION: Use of longer length needles for needle thoracostomy is essential given the extent of the nation's adult obesity population.

Effect of genetic variation in LRRTM3 on risk of Alzheimer disease.

OBJECTIVE: To explore the role of leucine-rich repeat transmembrane 3 (LRRTM3) in late-onset Alzheimer disease (AD) by independent genetic epidemiologic and functional studies. METHODS: First, we explored associations between LRRTM3 single-nucleotide polymorphisms and AD in the National Institute on Aging Late-Onset Alzheimer's Disease case-control data set (993 patients and 884 control subjects) and a cohort of Caribbean Hispanics (549 patients and 544 controls) using single-marker and haplotype analyses. Then we explored the effect of LRRTM3 small-hairpin RNAs on amyloid precursor protein processing. RESULTS: One single-nucleotide polymorphism in the promoter region (rs16923760; C allele: odds ratio, -0.74, P=.03), and a block of 4 single-nucleotide polymorphisms in intron 2 (rs1925608, C allele: 0.84, P=.04; rs7082306, A allele: 0.75, P=.04; rs1925609, T allele: 1.2, P=.03; and rs10997477, T allele: 0.88, P=.05) were associated with AD in the National Institute on Aging Late-Onset Alzheimer's Disease data set or the Caribbean Hispanic data set. The corresponding haplotypes were also associated with AD risk (.01 < P < .05). In addition, LRRTM3 knockdown with small-hairpin RNAs caused a significant decrease in amyloid precursor protein processing (P < .05 to P < .01) compared with the scrambled small-hairpin RNA condition. CONCLUSIONS: These complementary findings support the notions that genetic variation in LRRTM3 is associated with AD risk and that LRRTM3 may modulate γ-secretase processing of amyloid precursor protein. Additional studies are needed to determine whether the specific alleles associated with differential risk for AD indeed confer this risk through an effect of LRRTM3 expression levels that in turn modulates amyloid precursor protein processing.

Saitohin, which is nested in the tau locus and confers allele-specific susceptibility to several neurodegenerative diseases, interacts with peroxiredoxin 6.

Saitohin is a gene unique to humans and their closest relatives, the function of which is not yet known. Saitohin contains a single polymorphism (Q7R), and its Q and R alleles belong to the H1 and H2 tau haplotype, respectively. The Saitohin Q allele confers susceptibility to several neurodegenerative diseases. To get a handle on Saitohin function, we used it as a bait in a yeast two-hybrid screen. By this assay and subsequent co-immunoprecipitation and glutathione S-transferase pull-down assays, we discovered and confirmed that Saitohin interacts with peroxiredoxin 6, a unique member of that family that is bifunctional and the levels of which increase in Pick disease. The strength of the interaction appeared to be allele-specific, giving the first distinction between the two forms of Saitohin.