PI3K/HSCB axis facilitates FOG1 nuclear translocation to promote erythropoiesis and megakaryopoiesis.

Erythropoiesis and megakaryopoiesis are stringently regulated by signaling pathways. However, the precise molecular mechanisms through which signaling pathways regulate key transcription factors controlling erythropoiesis and megakaryopoiesis remain partially understood. Herein, we identified heat shock cognate B (HSCB), which is well known for its iron-sulfur cluster delivery function, as an indispensable protein for friend of GATA 1 (FOG1) nuclear translocation during erythropoiesis of K562 human erythroleukemia cells and cord-blood-derived human CD34+CD90+hematopoietic stem cells (HSCs), as well as during megakaryopoiesis of the CD34+CD90+HSCs. Mechanistically, HSCB could be phosphorylated by phosphoinositol-3-kinase (PI3K) to bind with and mediate the proteasomal degradation of transforming acidic coiled-coil containing protein 3 (TACC3), which otherwise detained FOG1 in the cytoplasm, thereby facilitating FOG1 nuclear translocation. Given that PI3K is activated during both erythropoiesis and megakaryopoiesis, and that FOG1 is a key transcription factor for these processes, our findings elucidate an important, previously unrecognized iron-sulfur cluster delivery independent function of HSCB in erythropoiesis and megakaryopoiesis.

Correlation between CCL2, CALCA, and CX3CL1 gene polymorphisms and chronic pain after cesarean section in Chinese Han women: A case control study.

OBJECTIVE: Postoperative chronic pain is characterized by high incidence, long duration, and complex pathogenesis. The purpose of this study was to investigate the correlation between the single nucleotide polymorphisms of the CCL2 gene rs4586 (g.5974T>C), CALCA rs3781719 (-692T>C), CX3CL1 rs614230 (2342C>T), and the risk of postoperative chronic pain in Chinese Han women. METHODS: We analyzed the CCL2 gene rs4586, CALCA rs3781719, CX3CL1 rs614230 single nucleotide polymorphism (SNPs) of 350 Chinese Han women with chronic postsurgical pain (CPSP) 6 months after cesarean section and 350 healthy women without chronic pain (HC). The levels of CCL2, CALCA, and CX3CL1 in serum were detected by enzyme-linked immunosorbent assay (ELISA). RESULTS: The CCL2 rs4586 T allele and the CX3CL1 gene rs614230C allele were protective factors for CPSP risk (adjusted OR = 0.766, 95% CI: 0.675-0.865 and OR = 0.336, 95% CI: 0.644-0.835). The CALCA gene rs3781719C allele was a risk factor for CPSP (adjusted OR = 1.273, 95% CI: 1.125-1.424). CCL2 rs4586, CX3CL1 gene rs614230, and CALCA gene rs3781719 locus gene polymorphisms were associated with serum CCL2, CX3CL1, and CALCA protein levels. CONCLUSION: Our results support that CCL2 gene rs4586, CALCA rs3781719, CX3CL1 rs614230 gene polymorphism are associated with the occurrence of chronic pain after cesarean section in Chinese Han women.

Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A geospatial modeling approach - Part 1.

Headwater wetlands affect ecosystem integrity of downstream waters; however, many wetlands - particularly geographically isolated wetlands (GIWs) - continue to be at risk. A significant portion of US federal policy is based on the jurisdictional status of wetlands, which is partly determined by the relationship between wetlands and downstream waters, including the cumulative impact of wetlands on those waters. We present a novel multi-phase geospatial modeling method to help elucidate hydrological relationship between GIWs and downstream waters at the landscape scale. The presented approach in this study used inundation maps derived from time series remotely sensed data between 1985 and 2010, weather and hydrological records, and ancillary geospatial data including information from the US Fish and Wildlife Service National Wetlands Inventory (NWI). The study site was a headwater catchment (292 km2) of the Choptank River Basin, located in the Mid-Atlantic region of USA, which contained a large number of Delmarva bays. The results showed inundation extent within GIWs varied, in aggregate, in response to weather variability (r = 0.58; p-value = 0.05), and was well correlated with streamflow (r = 0.81; p-value < 0.01) and base flow (r = 0.57; p-value < 0.1) conditions. The relationship between inundation patterns and stream discharge also varied with NWI hydrologic modifiers. The GIWs with water regime characterized by longer durations of flooding exhibited stronger correlations with stream discharge, but those GIWs with shorter durations of flooding were less correlated with stream discharge. This analysis suggests the mutual reliance (i.e., connection) of wetlands and streams on groundwater. GIWs appeared to function in aggregate, and it is likely that the combined effect of these wetlands significantly influenced the functioning of downstream waters.

Assessing the Effects of Fire Disturbances and Timber Management on Carbon Storage in the Greater Yellowstone Ecosystem.

Accurate characterization of Carbon (C) consequences of forest disturbances and management is critical for informed climate mitigation and adaptation strategies. While research into generalized properties of the forest C cycle informs policy and provides abstract guidance to managers, most management occurs at local scales and relies upon monitoring systems that can consistently provide C cycle assessments that explicitly apply to a defined time and place. We used an inventory-based forest monitoring and simulation tool to quantify C storage effects of actual fires, timber harvests, and forest regeneration conditions in the Greater Yellowstone Ecosystem (GYE). Results show that (1) the 1988 fires had a larger impact on GYE's C storage than harvesting during 1985-2011; (2) continuation of relatively high harvest rates of the region's National Forest land, which declined after 1990, would have shifted the disturbance agent primary importance on those lands from fire to harvest; and (3) accounting for local heterogeneity of post-disturbance regeneration patterns translates into large regional effects on total C storage. Large fires in 1988 released about 8.3 ± 0.3 Mg/ha of C across Yellowstone National Park (YNP, including both disturbed and undisturbed area), compared with total C storage reductions due to harvest of about 2.3 ± 0.3 Mg/ha and 2.6 ± 0.2 Mg/ha in adjacent Caribou-Targhee and Gallatin National Forests, respectively, from 1985-2011. If the high harvest rates observed in 1985-1989 had been maintained through 2011 in GYE National Forests, the C storage effect of harvesting would have quintupled to 10.5 ± 1.0 Mg/ha, exceeding the immediate losses associated with YNP's historic fire but not the longer-term net loss of carbon (16.9 ± 0.8 Mg/ha). Following stand-replacing disturbance such as the 1988 fires, the actual regeneration rate was slower than the default regional average rate assumed by empirically calibrated forest growth models. If regeneration following the 1988 fire had reached regionally average rates, either through different natural circumstances or through more active management, YNP would have had approximately 4.1 Mg/ha more forest carbon by year 2020. This study highlights the relative effects of fire disturbances and management activities on regional C storage, and demonstrates a forest carbon monitoring system that can be both applied consistently across the US and tailored to questions of specific local management interest.

Multi-view L2-SVM and its multi-view core vector machine.

In this paper, a novel L2-SVM based classifier Multi-view L2-SVM is proposed to address multi-view classification tasks. The proposed Multi-view L2-SVM classifier does not have any bias in its objective function and hence has the flexibility like µ-SVC in the sense that the number of the yielded support vectors can be controlled by a pre-specified parameter. The proposed Multi-view L2-SVM classifier can make full use of the coherence and the difference of different views through imposing the consensus among multiple views to improve the overall classification performance. Besides, based on the generalized core vector machine GCVM, the proposed Multi-view L2-SVM classifier is extended into its GCVM version MvCVM which can realize its fast training on large scale multi-view datasets, with its asymptotic linear time complexity with the sample size and its space complexity independent of the sample size. Our experimental results demonstrated the effectiveness of the proposed Multi-view L2-SVM classifier for small scale multi-view datasets and the proposed MvCVM classifier for large scale multi-view datasets.

[An Improved DDV Method to Retrieve AOT for HJ CCD Image in Typical Mountainous Areas].

Domestic HJ CCD imaging applications in environment and disaster monitoring and prediction has great potential. But, HJ CCD image lack of Mid-Nir band can not directly retrieve Aerosol Optical Thickness (AOT) by the traditional Dark Dense Vegetation (DDV) method, and the mountain AOT changes in space-time dramatically affected by the mountain environment, which reduces the accuracy of atmospheric correction. Based on wide distribution of mountainous dark dense forest, the red band histogram threshold method was introduced to identify the mountainous DDV pixels. Subsequently, the AOT of DDV pixels were retrieved by lookup table constructed by 6S radiative transfer model with assumption of constant ratio between surface reflectance in red and blue bands, and then were interpolated to whole image. MODIS aerosol product and the retrieved AOT by the proposed algorithm had very good consistency in spatial distribution, and HJ CCD image was more suitable for the remote sensing monitoring of aerosol in mountain areas, which had higher spatial resolution. Their fitting curve of scatterplot was y = 0.828 6x-0.01 and R2 was 0.984 3 respectively. Which indicate the improved DDV method can effectively retrieve AOT, and its precision can satisfy the atmospheric correction and terrain radiation correction for Hj CCD image in mountainous areas. The improvement of traditional DDV method can effectively solve the insufficient information problem of the HJ CCD image which have only visible light and near infrared band, when solving radiative transfer equation. Meanwhile, the improved method fully considered the influence of mountainous terrain environment. It lays a solid foundation for the HJ CCD image atmospheric correction in the mountainous areas, and offers the possibility for its automated processing. In addition, the red band histogram threshold method was better than NDVI method to identify mountain DDV pixels. And, the lookup table and ratio between surface reflectance between red and blue bands were the important influence factor for AOT retrieval. These will be the important research directions to further improve algorithm and improve the retrieve accuracy.

Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010.

Reducing emissions from deforestation and forest degradation (REDD+) is considered one of the most cost-effective strategies for mitigating climate change. However, historical deforestation and emission rates-critical inputs for setting reference emission levels for REDD+-are poorly understood. Here we use multi-source, time-series satellite data to quantify carbon emissions from deforestation in the Amazon basin on a year-to-year basis between 2000 and 2010. We first derive annual deforestation indicators by using the Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) product. MODIS indicators are calibrated by using a large sample of Landsat data to generate accurate deforestation rates, which are subsequently combined with a spatially explicit biomass dataset to calculate committed annual carbon emissions. Across the study area, the average deforestation and associated carbon emissions were estimated to be 1.59 ± 0.25 M ha•yr(-1) and 0.18 ± 0.07 Pg C•yr(-1) respectively, with substantially different trends and inter-annual variability in different regions. Deforestation in the Brazilian Amazon increased between 2001 and 2004 and declined substantially afterwards, whereas deforestation in the Bolivian Amazon, the Colombian Amazon, and the Peruvian Amazon increased over the study period. The average carbon density of lost forests after 2005 was 130 Mg C•ha(-1), ~11% lower than the average carbon density of remaining forests in year 2010 (144 Mg C•ha(-1)). Moreover, the average carbon density of cleared forests increased at a rate of 7 Mg C•ha(-1)•yr(-1) from 2005 to 2010, suggesting that deforestation has been progressively encroaching into high-biomass lands in the Amazon basin. Spatially explicit, annual deforestation and emission estimates like the ones derived in this study are useful for setting baselines for REDD+ and other emission mitigation programs, and for evaluating the performance of such efforts.

Conservation of forest birds: evidence of a shifting baseline in community structure.

BACKGROUND: Quantifying changes in forest bird diversity is an essential task for developing effective conservation actions. When subtle changes in diversity accumulate over time, annual comparisons may offer an incomplete perspective of changes in diversity. In this case, progressive change, the comparison of changes in diversity from a baseline condition, may offer greater insight because changes in diversity are assessed over longer periods of times. Our objectives were to determine how forest bird diversity has changed over time and whether those changes were associated with forest disturbance. METHODOLOGY/PRINCIPAL FINDINGS: We used North American Breeding Bird Survey data, a time series of Landsat images classified with respect to land cover change, and mixed-effects models to associate changes in forest bird community structure with forest disturbance, latitude, and longitude in the conterminous United States for the years 1985 to 2006. We document a significant divergence from the baseline structure for all birds of similar migratory habit and nest location, and all forest birds as a group from 1985 to 2006. Unexpectedly, decreases in progressive similarity resulted from small changes in richness (<1 species per route for the 22-year study period) and modest losses in abundance (-28.7 - -10.2 individuals per route) that varied by migratory habit and nest location. Forest disturbance increased progressive similarity for Neotropical migrants, permanent residents, ground nesting, and cavity nesting species. We also documented highest progressive similarity in the eastern United States. CONCLUSIONS/SIGNIFICANCE: Contemporary forest bird community structure is changing rapidly over a relatively short period of time (e.g., approximately 22 years). Forest disturbance and forest regeneration are primary factors associated with contemporary forest bird community structure, longitude and latitude are secondary factors, and forest loss is a tertiary factor. Importantly, these findings suggest some regions of the United States may already fall below the habitat amount threshold where fragmentation effects become important predictors of forest bird community structure.