A 33-year NPP monitoring study in southwest China by the fusion of multi-source remote sensing and station data

Knowledge of regional net primary productivity (NPP) is important for the systematic understanding of the global carbon cycle. In this study, multi-source data were employed to conduct a 33-year regional NPP study in southwest China, at a 1-km scale. A multi-sensor fusion framework was applied to obtain a new normalized difference vegetation index (NDVI) time series from 1982 to 2014, combining the respective advantages of the different remote sensing datasets. As another key parameter for NPP modeling, the total solar radiation was calculated by the improved Yang hybrid model (YHM), using meteorological station data. The verification described in this paper proved the feasibility of all the applied data processes, and a greatly improved accuracy was obtained for the NPP calculated with the final processed NDVI. The spatio-temporal analysis results indicated that 68.07% of the study area showed an increasing NPP trend over the past three decades. Significant heterogeneity was found in the correlation between NPP and precipitation at a monthly scale, specifically, the negative correlation in the growing season and the positive correlation in the dry season. The lagged positive correlation in the growing season and no lag in the dry season indicated the important impact of precipitation on NPP.Comment: 20 pages, 11 figure

MTHFR C677T and MTR A2756G polymorphisms and the homocysteine lowering efficacy of different doses of folic acid in hypertensive Chinese adults

<p>Abstract</p> <p>Background</p> <p>This study aimed to investigate if the homocysteine-lowering efficacy of two commonly used physiological doses (0.4 mg/d and 0.8 mg/d) of folic acid (FA) can be modified by individual methylenetetrahydrofolate reductase (MTHFR) C677T and/or methionine synthase (MTR) A2756G polymorphisms in hypertensive Chinese adults.</p> <p>Methods</p> <p>A total of 480 subjects with mild or moderate essential hypertension were randomly assigned to three treatment groups: 1) enalapril only (10 mg, control group); 2) enalapril-FA tablet [10:0.4 mg (10 mg enalapril combined with 0.4 mg of FA), low FA group]; and 3) enalapril-FA tablet (10:0.8 mg, high FA group), once daily for 8 weeks.</p> <p>Results</p> <p>After 4 or 8 weeks of treatment, homocysteine concentrations were reduced across all genotypes and FA dosage groups, except in subjects with MTR 2756AG /GG genotype in the low FA group at week 4. However, compared to subjects with MTHFR 677CC genotype, homocysteine concentrations remained higher in subjects with CT or TT genotype in the low FA group (<it>P </it>< 0.05 for either of these genotypes) and TT genotype in the high FA group (<it>P </it>< 0.05). Furthermore, subjects with TT genotype showed a greater homocysteine-lowering response than did subjects with CC genotype in the high FA group (mean percent reduction of homocysteine at week 8: CC 10.8% vs. TT: 22.0%, <it>P </it>= 0.005), but not in the low FA group (CC 9.9% vs. TT 11.2%, <it>P </it>= 0.989).</p> <p>Conclusions</p> <p>This study demonstrated that MTHFR C677T polymorphism can not only affect homocysteine concentration at baseline and post-FA treatment, but also can modify therapeutic responses to various dosages of FA supplementation.</p

Co-evolution of a broadly neutralizing HIV-1 antibody and founder virus

Current HIV-1 vaccines elicit strain-specific neutralizing antibodies. However, cross-reactive neutralizing antibodies arise in ~20% of HIV-1-infected individuals, and details of their generation could provide a roadmap for effective vaccination. Here we report the isolation, evolution and structure of a broadly neutralizing antibody from an African donor followed from time of infection. The mature antibody, CH103, neutralized ~55% of HIV-1 isolates, and its co-crystal structure with gp120 revealed a novel loop-based mechanism of CD4-binding site recognition. Virus and antibody gene sequencing revealed concomitant virus evolution and antibody maturation. Notably, the CH103-lineage unmutated common ancestor avidly bound the transmitted/founder HIV-1 envelope glycoprotein, and evolution of antibody neutralization breadth was preceded by extensive viral diversification in and near the CH103 epitope. These data elucidate the viral and antibody evolution leading to induction of a lineage of HIV-1 broadly neutralizing antibodies and provide insights into strategies to elicit similar antibodies via vaccination

Global continuous 0.05 degree atmospheric carbon dioxide dataset (GCXCO2) based OCO-2 satellite, CAMS and CarbonTracker simulation data from 2000 to 2020

&lt;p&gt;This dataset provides global seamless 8-day XCO2 (column-averaged CO2 dry air mole fraction) with a spatial resolution of 0.05 degree from 2000 to 2020. The unit is ppm.&lt;/p&gt

Multispectral and SAR Image Fusion Based on Laplacian Pyramid and Sparse Representation

Complementary information from multi-sensors can be combined to improve the availability and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful spectral information of the Earth&rsquo;s surface that is beneficial for identifying land cover types, while synthetic aperture radar (SAR) images can provide abundant information on the texture and structure of target objects. Therefore, this paper presents a fusion framework to integrate the information from MS and SAR images based on the Laplacian pyramid (LP) and sparse representation (SR) theory. LP is performed to decompose both the multispectral and SAR images into high-frequency components and low-frequency components, so that different processing strategies can be applied to multi-scale information. Low-frequency components are merged based on SR theory, whereas high-frequency components are combined based on a certain activity-level measurement, identifying salient features. Finally, LP reconstruction is performed to obtain the integrated image. We conduct experiments on several datasets to verify the effectiveness of the proposed method. Both visual interpretation and statistical analyses demonstrate that the proposed method strikes a satisfactory balance between spectral information preservation and the enhancement of spatial and textual characteristics. In addition, a further discussion regarding the adjustability property of the proposed method shows its flexibility for further application scenarios

A Two-Stage Fusion Framework to Generate a Spatio–Temporally Continuous MODIS NDSI Product over the Tibetan Plateau

The Tibetan Plateau (TP) is an important component of the global environmental system, on which the snow cover greatly affects the regional climate and ecology. Moderate resolution imaging spectroradiometer (MODIS) snow cover products have been demonstrated to be appropriate for investigating the snow cover over the TP. However, they are subject to cloud obscuration, and the TP&rsquo;s extremely complex terrain makes the snow monitoring difficult. Therefore, in this paper, we propose a two-stage spatio&ndash;temporal fusion framework for the cloud removal of MODIS C6 snow products, including an adjusted Terra and Aqua combination (TAC) and a spatio&ndash;temporal fusion based on Gaussian kernel function and error correction (STF-GKF-EC). To the best of our knowledge, this is the first time that a spatio&ndash;temporally continuous daily 500-m MODIS normalized difference snow index (NDSI) product has been generated for the TP, which greatly improves the spatial and temporal resolutions of the current snow cover products. The main stage, STF-GKF-EC, adaptively weights the spatial and temporal correlations by the Gaussian kernel function, and further takes the rapid changes of snow cover into consideration through the error correction. The experiments indicated that STF-GKF-EC removes clouds completely, achieving an overall accuracy (OA) and mean absolute error (MAE) of 91.48% and 3.88, respectively. Based on the cloud-removed results, during 2001&ndash;2017, as far as the intra-annual variation is concerned, a large proportion of the snow cover appears between October and May, with a peak in February/March, and the variation is mainly controlled by temperature. For the inter-annual variation, an obvious increasing trend of 0.68/year for NDSI is observed before 2005, followed by a slight decreasing trend of 0.16/year, in which precipitation is a better explanation factor than temperature