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Background: Nanoparticle albumin-bound paclitaxel (nab-PTX) has exhibited clinical efficacy in breast cancer treatment, but toxicities can be yielded more at the same time. We did this meta-analysis aiming to unambiguously compare nab-PTX with conventional solvent-based paclitaxel (sb-PTX) in breast cancer patients of all stages. Method: Pubmed, Embase and Cochrane Library were searched for head-to-head randomized controlled trials of nab-PTX and sb-PTX in breast cancer. Risk ratio (RR) with 95% confidence interval was used for dichotomous variables while Hazard ratio (HR) was used for time-to-event outcomes. Results: Our review finally included 9 studies with 3508 patients. Nab-PTX showed a benefit on objective response rate (ORR) (RR=1.22 [1.04-1.43], P=0.01) as well as non-inferiority compared with sb-PTX in disease control rate (DCR) (RR=1.01 [0.98-1.04], P=0.44), overall survival (OS) (HR=0.99 [0.93-1.05], P=0.81) and disease free survival/progression free survival (DFS/PFS) (HR=0.92 [0.81-1.05], P=0.21). However, when it comes to toxicities (fatigue, nausea or vomiting, peripheral sensory neuropathy and adverse event related discontinuation), results favored sb-PTX (RR=2.89 [1.07-7.8], 3.15 [1.78-5.59], 2.11 [1.32-3.37], 2.02 [1.61-2.53]; P

The admixture of loess in soils formed in sandy parent materials has considerable impact on pedogenesis and soil ecological functions. This study aimed to evaluate these effects on soil hydrology by quantifying the relationships between loess content and soil hydrological properties in a sandstone landscape covered by Pleistocene periglacial slope deposits in central Europe. Studied properties were saturated soil water capacity, field capacity, permanent wilting point, available water capacity, macro-porosity, matrix porosity and saturated hydraulic conductivity. The effect of loess addition on soil hydrological properties differed between topsoil (pedogenic A horizons) and subsoil (pedogenic B and C horizons). In the subsoil, the studied soil hydrological properties were mainly controlled by loess content. By contrast, in the topsoil the effects of loess content on soil hydrological properties were largely masked by the effects of soil organic matter (reflected by soil organic carbon, SOC). The enhancing effect of SOC on soil hydrological properties was most prominent for saturated soil water capacity and was also significant for all other parameters except permanent wilting point. After the effects of SOC were accounted for, the residual effects of loess on soil hydrological properties were the same in both topsoils and subsoils, with one exception: Saturated hydraulic conductivity decreased with increasing loess content for subsoils, but not for topsoils. This study highlighted the ecohydrological significance of loess admixture in coarse-textured soils, especially for subsoils with low SOC contents. However, for coarse-textured topsoils, SOC content plays the dominant role in affecting soil hydrological properties.

The current criteria for defining the recurrence risks of stage II colorectal cancer (CRC) are not robust; therefore, we aimed to explore novel gene signatures to predict recurrence risks and to reveal the underlying mechanisms of stage II CRC. First, the gene expression profiles of 124 patients with stage II CRC from The Cancer Genome Atlas (TCGA) database were obtained to screen differentially expressed genes (DEGs). A total of 202 DEGs, including 128 upregulated and 74 downregulated, were identified in the recurrence group (n = 24) compared to the nonrecurrence group (n = 100). Furthermore, the top 5 DEGs (ZNF561, WFS1, SLC2A1, MFI2, and PTGR1) were identified by random forest variable hunting, and four (ZNF561, WFS1, SLC2A1, and PTGR1) were selected to create a four‐gene recurrent model (GRM), with an area under the curve (AUC) of 0.882 according to the receiver operating characteristic curve, and the robust diagnostic effectiveness of the GRM was further validated with another gene expression profiling dataset (GSE12032), with an AUC of 0.943. The diagnostic effectiveness of the GRM regarding recurrence was associated with poor disease‐free survival in all stages of CRC. In addition, gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed 18 enriched functions and 6 enriched pathways. Four genes, ABCG2, CACNA1F, CYP19A1, and TF, were identified as hub genes by the protein‐protein interaction network, which further validated that these genes were correlated with a poor pathologic stage and overall survival in all stages of CRC. In conclusion, the GRM can effectively classify stage II CRC into groups of high and low risks of recurrence, thereby making up for the prognostic value of the traditional clinicopathological risk factors defined by the National Comprehensive Cancer Network guidelines. The hub genes may be useful therapeutic targets for recurrence. Thus, the GRM and hub genes could offer clinical value in directing individualized and precision therapeutic regimens for stage II CRC patients., This study finds indicators for predicting postoperative recurrence in patients with stage II colorectal cancer (CRC). Moreover, the gene recurrent model and hub genes potentially offer clinical values in directing individualized and precision therapeutic regimen be selection for stage II CRC.

To deal with the global and regional issues including food security, climate change, land degradation, biodiversity loss, water resource management, and ecosystem health, detailed accurate spatial soil information is urgently needed. This drives the worldwide development of digital soil mapping. In recent years, significant progresses have been made in different aspects of digital soil mapping. The main purpose of this paper is to provide a review for the major progresses of digital soil mapping in the last decade. First, we briefly described the rise of digital soil mapping and outlined important milestones and their influence, and main paradigms in digital soil mapping. Then, we reviewed the progresses in legacy soil data, environmental covariates, soil sampling, predictive models and the applications of digital soil mapping products. Finally, we summarized the main trends and future prospect as revealed by studies up to now. We concluded that although the digital soil mapping is now moving towards mature to meet various demands of soil information, challenges including new theories, methodologies and applications of digital soil mapping, especially for highly heterogeneous and human-affected environments, still exist and need to be addressed in the future.

Soil colour can indicate soil physical, chemical and biological properties and processes, and is an important indicator for soil classification, soil quality evaluation and soil management. It varies in both horizontal and vertical dimensions, and thus regional maps of soil colour can reveal spatial patterns of these properties, processes, and indicators. However, although soil regions are sometimes named for their dominant soil colour, it is directly measured only at “point” support, i.e., during soil profile description, whereas it is desirable to know soil colour over the entire soilscape. To achieve this for China we used predictive soil mapping methods to produce soil colour maps (dry and moist colours) at 1 km2 grid cell size and over multiple depths from a consistent dataset of approximately 4 600 full profile descriptions taken as part of a national survey to define soil series in Chinese Soil Taxonomy, and a set of environmental covariates covering the national territory. The covariates characterized soil forming factors including climate, parent materials, terrain, vegetation, land surface water and thermal conditions. Soil colour descriptions in the Munsell system were extracted from the genetic horizon descriptions at the selected depths and converted to the sRGB and L*a*b* colour spaces. Dry and moist colour separates were not well-correlated in either space ( r 0.76 ). Random forest models were constructed in both spaces, for dry and moist colours separately. Models in sRGB space were moderately successful ( R 2 ≈ 0.43 , RMSE ≈ 26 / 255 ) at 5 cm, with success decreasing with depth. Models smoothed the colour space and thus did not predict the more extreme values or chromas, nor the rarer hues. Models in L*a*b* space were less successful. The fitted sRGB models were used to produce predictive maps over all of China. Regional patterns as well as local detail are clearly shown. Solar radiation, wind exposure, regolith thickness, and Landsat TM bands 7 and 5 contributed most to the predictions, followed by elevation, mean annual precipitation, terrain wetness index, air temperature seasonality, precipitation standard deviation and standard deviation of NDVI. These suggest pedological processes acting on the development of soil colours, including weathering of parent materials, oxidation-reduction chemistry and biochemistry of the decomposing of organic matter. This study shows that predictive methods from points using suitable covariates are an alternative to spatial predictions over map units from their representative profiles.

Triple‑negative breast cancer (TNBC), which is characterized by inherently aggressive behavior and lack of recognized molecular targets for therapy, poses a serious threat to women's health worldwide. However, targeted treatments have yet to be made available. A crosstalk between tumor cells and platelets (PLT) contributing to growth, angiogenesis and metastasis has been reported in numerous cancers. Heparanase (Hpa), the only mammalian endoglycosidase that cleaves heparan sulfate, has been demonstrated to contribute to the growth, angiogenesis and metastasis of numerous cancers. Hypoxia affects the growth, angiogenesis and metastasis of nearly all solid tumors, and the ability of Hpa to promote invasion is enhanced in hypoxia. However, whether Hpa can strengthen the crosstalk between tumor cells and PLT, and whether enhancing the biological function of Hpa in TNBC promotes malignant progression, have yet to be fully elucidated. The present study, based on bioinformatics analysis and experimental studies in vivo and in vitro, demonstrated that Hpa enhanced the crosstalk between TNBC cells and PLT to increase the supply of oxygen and nutrients, while also conferring tolerance of TNBC cells to oxygen and nutrient shortage, both of which are important for overcoming the stress of hypoxia and nutritional deprivation in the tumor microenvironment, thereby promoting malignant progression, including growth, angiogenesis and metastasis in TNBC. In addition, the hypoxia‑inducible factor‑1a (HIF-1a)/vascular endothelial growth factor‑a (VEGF- a)/phosphorylated protein kinase B (p-)Akt axis may be the key pathway involved in the effects of Hpa on the biological processes mentioned above. Therefore, improving local hypoxia, anti‑Hpa treatment and inhibiting PLT activation may improve the prognosis of TNBC.

Water storage and flow in shallow subsurface drives runoff generation, vegetation water use and nutrient cycling. Modelling these processes under non-steady state conditions is challenging, particularly in regions like the subtropics that experience extreme wet and dry periods. At the catchment-scale, physically-based equations (e.g., Richards equation) are impractical due to their complexity, while conceptual models typically rely on steady state assumptions not found in daily hydrological dynamics. We addressed this by developing a simple modelling framework for shallow subsurface water dynamics based on physical relationships and a proxy parameter for the fluxes induced by non-unit hydraulic gradients. We demonstrate its applicability for six generic soil textures and for an Acrisol in subtropical China. Results showed that our new approach represents top soil daily fluxes and storage better than, and as fast as, standard conceptual approaches. Moreover, it was less complex and up to two orders of magnitude faster than simulating Richards equation, making it easy to include in existing hydrological models.

Metastasis is the leading lethal factor severely restraining the effectiveness of clinical treatment. TGF-beta is the key regulator for metastasis and influences paradoxically on cancer progression. The known TGF-beta blockers exert little selectivity on its functions, indiscriminately causing the anti-metastatic and pro-growth effects. Under such circumstances, specifically rebalancing the oncological function of TGF-beta provides a crucial oncotarget against metastasis. In our study, we established the screening platform targeting cell motility and identified a potential flavonoid, Chamaejasmenin B (ICJ), extracted from Stellera chamaejasme L..It suppressed the migration and invasion in breast cancer cells in vitro. Moreover, by dynamical quantification of breast cancer progression in small-animal imaging system, ICJ was proved to be a potent inhibitor of metastasis with minimal toxic side effects. Mechanism study further revealed that ICJ efficiently blocked TGF-beta induced EMT, disrupted the interaction between β3 integrin-TβRII complex and, consequently, resulted in the selective inhibition of FAK:Src:p38 pathway. Meanwhile, specific blockage of this pathway largely attenuated the anti-metastatic function of ICJ. Importantly, in contrast with the antagonistic effects on TGF-beta induced metastasis, ICJ obviously sensitized its cytostatic activity, suggesting that it was not a pan-blocker but a rebalancer for the functional output of TGF-beta. Collectively, by targeting TGF-beta Paradox, we experimentally provided a promising candidate for metastatic intervention.

Ancillary data, such as soil type, may improve the visible and near-infrared (vis-NIR) estimation of soil organic carbon (SOC); however, they require data collection or expert knowledge. The application of a national soil spectral library to local SOC estimations usually requires soil type information, because the relationships between vis-NIR spectra and SOC from different populations may vary. Using 515 samples of five soil types (genetic soil classification of China, GSCC) from the Chinese soil spectral library (CSSL), we compared three strategies in the vis-NIR estimation of SOC. Different regression models were calibrated using the entire dataset (Strategy I, without using soil type as ancillary data) and the subsets stratified by soil type from CSSL as ancillary data (strategies II and III). In Strategy II, the subsets were stratified by soil type from the CSSL for validation. In Strategy III, the subsets were stratified by spectrally derived soil type for validation. The results showed that 86.72% of the samples were successfully discriminated for the soil types by using the vis-NIR spectra. The coefficients of determination in the prediction ( R p 2 ) of SOC estimation by strategies I, II, and III were 0.74, 0.83, and 0.82, respectively. The stratified calibration strategies (strategies II and III) improved the vis-NIR estimation of SOC. The misclassification of the soil type in the application of Strategy III slightly affected the SOC estimations. Nevertheless, this strategy is inexpensive and beneficial when expert knowledge on soil classification is lacking. We concluded that vis-NIR spectroscopy could be applied to distinguish some soil types in terms of GSCC, which further provided essential and easily accessible ancillary data for the application of stratified calibration strategies in the vis-NIR estimation of SOC.

BACKGROUND: Mammalian cells express a single functional heparanase, an endoglycosidase that cleaves heparan sulfate and thereby promotes tumor metastasis, angiogenesis, and inflammation. Malignant mesothelioma is highly aggressive and has a poor prognosis because of the lack of markers for early diagnosis and resistance to conventional therapies. The purpose of this study was to elucidate the mode of action and biological significance of heparanase in mesothelioma and test the efficacy of heparanase inhibitors in the treatment of this malignancy. METHODS: The involvement of heparanase in mesothelioma was investigated by applying mouse models of mesothelioma and testing the effect of heparanase gene silencing (n = 18 mice per experiment; two different models) and heparanase inhibitors (ie, PG545, defibrotide; n = 18 per experiment; six different models). Synchronous pleural effusion and plasma samples from patients with mesothelioma (n = 35), other malignancies (12 non–small cell lung cancer, two small cell lung carcinoma, four breast cancer, three gastrointestinal cancers, two lymphomas), and benign effusions (five patients) were collected and analyzed for heparanase content (enzyme-linked immunosorbent assay). Eighty-one mesothelioma biopsies were analyzed by H-Score for the prognostic impact of heparanase using immunohistochemistry. All statistical tests were two-sided. RESULTS: Mesothelioma tumor growth, measured by bioluminescence or tumor weight at termination, was markedly attenuated by heparanase gene silencing (P = .02) and by heparanase inhibitors (PG545 and defibrotide; P < .001 and P = .01, respectively). A marked increase in survival of the mesothelioma-bearing mice (P < .001) was recorded. Heparanase inhibitors were more potent in vivo than conventional chemotherapy. Clinically, heparanase levels in patients’ pleural effusions could distinguish between malignant and benign effusions, and a heparanase H-score above 90 was associated with reduced patient survival (hazard ratio = 1.89, 95% confidence interval = 1.09 to 3.27, P = .03). CONCLUSIONS: Our results imply that heparanase is clinically relevant in mesothelioma development. Given these preclinical and clinical data, heparanase appears to be an important mediator of mesothelioma, and heparanase inhibitors are worthy of investigation as a new therapeutic modality in mesothelioma clinical trials.

Long-term environmental research networks are one approach to advancing local, regional, and global environmental science and education. A remarkable number and wide variety of environmental research networks operate around the world today. These are diverse in funding, infrastructure, motivating questions, scientific strengths, and the sciences that birthed and maintain the networks. Some networks have individual sites that were selected because they had produced invaluable long-term data, while other networks have new sites selected to span ecological gradients. However, all long-term environmental networks share two challenges. Networks must keep pace with scientific advances and interact with both the scientific community and society at large. If networks fall short of successfully addressing these challenges, they risk becoming irrelevant. The objective of this paper is to assert that the biogeosciences offer environmental research networks a number of opportunities to expand scientific impact and public engagement. We explore some of these opportunities with four networks: the International Long-Term Ecological Research Network programs (ILTERs), critical zone observatories (CZOs), Earth and ecological observatory networks (EONs), and the FLUXNET program of eddy flux sites. While these networks were founded and expanded by interdisciplinary scientists, the preponderance of expertise and funding has gravitated activities of ILTERs and EONs toward ecology and biology, CZOs toward the Earth sciences and geology, and FLUXNET toward ecophysiology and micrometeorology. Our point is not to homogenize networks, nor to diminish disciplinary science. Rather, we argue that by more fully incorporating the integration of biology and geology in long-term environmental research networks, scientists can better leverage network assets, keep pace with the ever-changing science of the environment, and engage with larger scientific and public audiences. Fil: Richter, Daniel D.. University of Duke; Estados Unidos Fil: Billings, Sharon A.. University of Kansas; Estados Unidos Fil: Groffman, Peter M.. Brooklyn College; Estados Unidos Fil: Kelly, Eugene F.. State University of Colorado - Fort Collins; Estados Unidos Fil: Lohse, Kathleen A.. Idaho State University; Estados Unidos Fil: McDowell, William H.. University Of New Hampshire; Estados Unidos Fil: White, Timothy S.. State University of Pennsylvania; Estados Unidos Fil: Anderson, Suzanne. State University of Colorado at Boulder; Estados Unidos Fil: Baldocchi, Dennis D.. University of California at Berkeley; Estados Unidos Fil: Banwart, Steve. University Of Leeds; Reino Unido Fil: Brantley, Susan. State University of Pennsylvania; Estados Unidos Fil: Braun, Jean J.. University of Yaounide; Camerún. Universite de Toulouse; Francia Fil: Brecheisen, Zachary S.. University of Duke; Estados Unidos Fil: Cook, Charles S.. University of Duke; Estados Unidos Fil: Hartnett, Hilairy E.. Arizona State University; Estados Unidos Fil: Hobbie, Sarah E.. University of Minnesota; Estados Unidos Fil: Gaillardet, Jerome. Institut Universitaire de France. Institut de Physique du Globe de Paris; Francia Fil: Jobbagy Gampel, Esteban Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina Fil: Jungkunst, Hermann F.. Universitat Koblenz; Alemania Fil: Kazanski, Clare E.. University of Minnesota; Estados Unidos Fil: Krishnaswamy, Jagdish. Ashoka Trust For Research In Ecology And The Environment; India Fil: Markewitz, Daniel. University of Georgia; Estados Unidos Fil: O'Neill, Katherine. Roanoke College; Estados Unidos Fil: Riebe, Clifford S.. University Of Wyoming; Fil: Schroeder, Paul. University of Georgia; Estados Unidos Fil: Siebe, Christina. Universidad Nacional Autónoma de México; México Fil: Silver, Whendee L.. University of California at Berkeley; Estados Unidos Fil: Thompson, Aaron. University of Georgia; Estados Unidos Fil: Verhoef, Anne. University of Reading; Reino Unido Fil: Zhang, Ganlin. Chinese Academy of Sciences; República de China

The biogeochemical cycles of nitrogen (N) and base cations (BCs), (i.e., K+, Na+, Ca2+, and Mg2+), play critical roles in plant nutrition and ecosystem function. Empirical correlations between large experimental N fertilizer additions to forest ecosystems and increased BCs loss in stream water are well demonstrated, but the mechanisms driving this coupling remain poorly understood. We hypothesized that protons generated through N transformation (PPRN)—quantified as the balance of NH4+ (H+ source) and NO3− (H+ sink) in precipitation versus the stream output will impact BCs loss in acid-sensitive ecosystems. To test this hypothesis, we monitored precipitation input and stream export of inorganic N and BCs for three years in an acid-sensitive forested watershed in a granite area of subtropical China. We found the precipitation input of inorganic N (17.71 kg N ha−1 year−1 with 54% as NH4+–N) was considerably higher than stream exported inorganic N (5.99 kg N ha−1 year−1 with 83% as NO3−–N), making the watershed a net N sink. The stream export of BCs (151, 1518, 851, and 252 mol ha−1 year−1 for K+, Na+, Ca2+, and Mg2+, respectively) was positively correlated (r = 0.80, 0.90, 0.84, and 0.84 for K+, Na+, Ca2+, and Mg2+ on a monthly scale, respectively, P

Accurate estimates of the spatial variability of soil organic matter (SOM) are necessary to properly evaluate soil fertility and soil carbon sequestration potential. In plains and gently undulating terrains, soil spatial variability is not closely related to relief, and thus digital soil mapping (DSM) methods based on soil–landscape relationships often fail in these areas. Therefore, different predictors are needed for DSM in the plains. Time-series remotely sensed data, including thermal imagery and vegetation indices provide possibilities for mapping SOM in such areas. Two low-relief agricultural areas (Peixian County, 28 km × 28 km and Jiangyan County, 38 km × 50 km) in northwest and middle Jiangsu Province, east China, were chosen as case study areas. Land surface diurnal temperature difference (DTD) extracted from moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), and soil-adjusted vegetation index (SAVI) at the peak of growing season calculated from Landsat ETM+ image were used as predictors. Regression kriging (RK) with a mixed linear model fitted by residual maximum likelihood (REML) and residuals interpolated by simple kriging (SK) were used to model and map SOM spatial distribution; ordinary kriging (OK) was used as a baseline comparison. The root mean squared error, mean error and mean absolute error calculated from leave-one-out cross-validation were used to assess prediction accuracy. Results showed that the proposed covariates provided added value to the observations. SAVI aggregated to MODIS resolution was able to identify local highs and lows not apparent from the DTD imagery alone. Despite the apparent similarity of the two areas, the spatial structure of residuals from the linear mixed models were quite different; ranges on the order of 3 km in Jiangyan but 16 km in Peixian, and accuracy of best models differed by a factor of two (3.3 g/kg and 6.3 g/kg SOM, respectively). This suggests that time-series remotely sensed data can provide useful auxiliary variable for mapping SOM in low-relief agricultural areas, with three important cautions: (1) image dates must be carefully chosen; (2) vegetation indices should supplement diurnal temperature differences, (3) model structure must be calibrated for each area.

The Intergovernmental Technical Panel on Soils has completed the first State of the World’s Soil Resources Report. Globally soil erosion was identified as the gravest threat, leading to deteriorating water quality in developed regions and to lowering of crop yields in many developing regions. We need to increase nitrogen and phosphorus fertilizer use in infertile tropical and semi-tropical soils - the regions where the most food insecurity among us are found - while reducing global use of these products overall. Stores of soil organic carbon are critical in the global carbon balance, and national governments must set specific targets to stabilize or ideally increase soil organic carbon stores. Finally the quality of soil information available for policy formulation must be improved - the regional assessments in the State of the World’s Soil Resources Report frequently base their evaluations on studies from the 1990s based on observations made in the 1980s or earlier. Fil: Montanarella, Luca. European Commission Joint Research Centre; Fil: Pennock, Daniel Jon. University of Saskatchewan; Canadá Fil: McKenzie, Neil. Csiro Agriculture Flagship, Brisbane; Australia Fil: Badraoui, Mohamed. Institut National de la Recherche Agronomique, Morocco; Fil: Chude, Victor. National Programme For Food Security; Nigeria Fil: Baptista, Isaurinda. Instituto Nacional de Investigação e Desenvolvimento Agrário; Cabo Verde Fil: Mamo, Tekalign. Ministry of Agriculture; Etiopía Fil: Yemefack, Martin. International Institute Of Tropical Agriculture Yaounde; Fil: Aulakh, Mikha Singh. Banda University Of Agriculture And Technology; India Fil: Yagi, Kazuyuki. Institute For Agro-environmental Sciences, Naro; Fil: Hong, Suk Young. Rural Development Administration; Fil: Vijarnsorn, Pisoot. Chaipattana Foundation; Fil: Zhang, Gan-Lin. Chinese Academy of Sciences; República de China Fil: Arrouays, Dominique. Institut National de la Recherche Agronomique. InfoSol Unit; Francia Fil: Black, Helaina. The James Hutton Institute; Reino Unido Fil: Krasilnikov, Pavel. Lomonosov Moscow State University; Fil: Sobocká, Jaroslava. National Agricultural And Food Centre; Fil: Alegre, Julio. Fil: Henriquez, Carlos Roberto. Universidad de Costa Rica; Costa Rica Fil: Mendonça-Santos, Maria de Lourdes. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Taboada, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Suelos; Argentina Fil: Espinosa-Victoria, David. Colegio de Postgraduados; México Fil: AlShankiti, Abdullah. International Center For Biosaline Agriculture; Fil: AlaviPanah, Sayed Kazem. University Of Tehran; Irán Fil: Mustafa Elsheikh, Elsiddig Ahmed El. Khartoum University; Sudán Fil: Hempel, Jon. United States Department of Agriculture; Estados Unidos Fil: Arbestain, Marta Camps. Institute Of Agriculture And Environment; Fil: Nachtergaele, Freddy. Food And Agriculture Organization Of The United Nations; Fil: Vargas, Ronald. Food And Agriculture Organization Of The United Nations

// Xu Sun 1 , Ganlin Zhang 1 , Jiayun Nian 1,2 , Mingwei Yu 1 , Shijian Chen 3 , Yi Zhang 1 , Guowang Yang 1 , Lin Yang 1 , Peiyu Cheng 1 , Chen Yan 1,2 , Yunfei Ma 1 , Hui Meng 1,2 , Xiaomin Wang 1 and Jin-Ping Li 1,4 1 Department of Oncology, Beijing Hospital of Traditional Chinese Medicine Affiliated to Capital Medical University, Beijing, China 2 School of Graduates, Beijing University of Chinese Medicine, Beijing, China 3 Department of Neurology, Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China 4 Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden Correspondence to: Xiaomin Wang, email: // Keywords : heparanase, breast cancer, prognosis Received : September 09, 2016 Accepted : March 10, 2017 Published : March 25, 2017 Abstract Heparanase promotes tumorigenesis, angiogenesis, and metastasis. Here, we conducted a study based on systematic review and the Cancer Genome Atlas (TCGA) data that examined heparanase expression in clinical samples to determine its prognostic value. According to the meta-analysis and TCGA data, we found that heparanase expression was up-regulated in most breast cancer specimens, and elevated heparanase expression was associated with increased lymph node metastasis, larger tumor size, higher histological grade, and poor survival. These results suggest that targeting heparanase might improve treatments for breast cancer patients.

Soil Sci. Soc. Am. J. 77:2078–2088 doi:10.2136/sssaj2013.01.0033 Received 23 Jan. 2013. *Corresponding author: (glzhang@issas.ac.cn). © Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Pedogenic Transformation of Phosphorus during Paddy Soil Development on Calcareous and Acid Parent Materials Pedology

Although Chinese herbal compounds have long been alternatively applied for cancer treatment in China, their treatment effects have not been sufficiently investigated. The Chinese herbSpatholobus suberectusis commonly prescribed to cancer patients. HPLC analysis has shown that the main components ofSpatholobus suberectusare flavonoids that can be classified as phytoestrogens, having a structure similar to estrogen. This study was designed to investigate the effects ofSpatholobus suberectuscolumn extract (SSCE) on the estrogen receptor-positive (ER+) breast cancer cell line MCF-7 and its possible molecular mechanism. In our study, MTT assay was performed to evaluate cell viability. The results show that SSCE (80, 160, and 320 μg/ml) significantly decreased the viability of MCF-7 cells. SSCE also triggered apoptosis, arrested the cell cycle at the G0/G1 phase, and inhibited cell migration. A dual-luciferase reporter system showed that SSCE suppressed intranuclear p-ER activity; Western blot analysis confirmed the repressed expression of phosphorylated-ER alpha (p-ERα), ERK1/2, p-ERK1/2, AKT, p-AKT, p-mTOR, PI3K, and p-PI3K, indicating that SSCE suppressed the MAPK PI3K/AKT signaling pathway. Collectively, our results suggest that SSCE causes apoptosis, an arrest in the G0/G1 phase, and a decrease in migration in ER+ MCF-7 cells via hypoactivity of the ER and suppression of the MAPK PI3K/AKT pathway.

Chinese herbal medicine (CHM) has been increasingly employed during therapy for breast cancer, but its efficacy remains a matter of debate. This systematic review examined randomized controlled trials to provide a critical evaluation of this treatment. The results demonstrated that the combined use of CHM with chemotherapy may improve the immediate tumor response and reduce chemotherapy-associated adverse events. Our findings highlight the poor quality of Chinese studies, and additional well-designed randomized controlled trials addressing the role of CHM are warranted. The lack of molecular-based evidence for CHM and Zheng has resulted in a limited understanding and acceptance of CHM and traditional Chinese medicine in Western countries. We believe that researchers should immediately explore a CHM-based cure, and CHM should be applied to routine care as soon as conclusive data are available.

There is a need for accurate estimate of soil organic carbon (SOC) stocks for understanding the role of alpine soils in the global carbon cycle. We tested a method for mapping digitally the continuous distribution of the SOC stock in three dimensions in the northeast of the Tibetan Plateau. The approach integrated the spatial distribution of the mattic epipedon which is a special surface horizon widespread and rich in organic matter in Tibetan grasslands. Prediction models resulted in high prediction accuracy. An average SOC stock in the mattic epipedon was estimated to be 4.99 kg m−2 in a mean depth of 14 cm. The amounts of SOC in the mattic epipedon, the upper 30 cm and 50 cm accounted for about 21%, 80% and 89%, respectively, of the total SOC stock in the upper 1 m depth. Compared with previous estimates, our approach resulted in more reliable predictions. The mattic epipedon was proven to be an important factor for modelling the realistic distribution of the SOC stock in Tibetan grasslands. Vegetation-related covariates have the most important influence on the distribution of the mattic epipedon and the SOC stock in the alpine grassland soils of northeast Tibetan Plateau.

Crop-residue burning and frequent paddy-soil flooding can lead to a substantial accumulation of black carbon (BC), thus contributing to long-term C sequestration. There is evidence that the turnover of BC in soils also depends on the soil mineral assembly. We studied the effects of paddy and non-paddy soil management and different major reference soil groups on BC storage. We hypothesized that overall BC storage in soil relates to paddy management and the abundance of reactive mineral phases such as Fe and Al oxides, and clay-sized minerals. Parallel to BC, black nitrogen (BN) should accumulate in soil. Paddy and non-paddy soils were sampled in three different climate zones (tropical, subtropical, and temperate). The soil profiles comprised six replicates of Andosols, Alisols and Vertisols from Java (Indonesia), and Alisols and Cambisols from China, as well as one Fluvisol and Gleysol from Northern Italy. Samples were taken by horizon down to > 1 m depth and analyzed for soil organic carbon (SOC) and BC. The latter was analyzed by oxidation to benzene polycarboxylic acids. Abundance of BN (as aromatic N) was estimated by X-ray photoelectron spectroscopic analyses of selected topsoil horizons. In topsoils BC vs. SOC accumulation was affected by management for Andosol, Alisols in China, and Vertisols. However, both flooding and crop-residue management seemed to control this. BC contents relative to SOC also differed between the reference soil groups, independent of management (p 50% of total N after combustion of rice straw. However, aromatic N was barely, or not detectable in soil, and there was no correlation to BC. We conclude that burned crop residues were not a major source for aromatic N in soil. BC and aromatic N showed no distinct relations to soil properties, such as the abundance of clay-sized minerals, and Al and Fe oxides. Differences in BC stocks between the soils were most pronounced in the subsoils, likely caused by physical processes, such as swelling and shrinking of clays and/or translocation by leaching. Climate and regional soil-adjusted management also affected BC accumulation, but this first snapshot indicates that global BC maps may be linked to global soil maps.

For mapping soil properties in three dimensions the simplest option is to choose a series of depth intervals, and to calibrate a two-dimensional (2-D) model for each interval. The alternative is to calibrate a full three dimensional (3-D) model that describes the variation in lateral and vertical direction. In 3-D modeling we must anticipate possible changes with depth of the effects of environmental covariates on the soil property of interest. This can be achieved by including interactions between the environmental covariates and depth. Also we must anticipate possible non-stationarity of the residual variance with depth. This can be achieved by fitting a 3-D correlation function, and multiplying the correlation between two points by the residual standard deviations at these two points that are a function of depth. In this paper various 3-D models of the natural logarithms of SOC are compared with 2-D depth-interval specific models. Five environmental covariates are used as predictors in modeling the lateral trend. In the 3-D models also depth was used as a predictor, either categorical, with categories equal to the depth intervals (3-Dcat), or continuous (3-Dcon). The covariance of the residuals in 3-D is modeled by a sum-metric covariance function. Both stationary and non-stationary variance models are fitted. In the non-stationary variance models the residual standard deviations are modeled either as a stepwise function or as a linear function of depth. In the 2-D models the regression coefficients differed largely between the depth intervals. In the 3-Dcat model extreme values for the regression coefficients were leveled out, and in the 3-Dcon model only the coefficients of NDVI and aspect changed with depth. The 3-Dcon model with a residual standard deviation that is a stepwise function of depth had the largest residual log-likelihood and smallest AIC among all 3-D models. Based on the cross-validation root mean squared error (RMSE) there was no single best model. Based on the mean and median of the standardized squared error (MSSE, MedSSE) the 2-D models outperformed all 3-D models. Overestimation of the prediction error variance by the kriging variance was less strong with the non-stationary variance models compared to the stationary variance models. 3-D modeling is required for realistic geostatistical simulation in spatial uncertainty analyses.

In large heterogeneous areas the relationship between soil organic carbon (SOC) and environmental covariates may vary throughout the area, bringing about difficulty for accurate modeling of the regional SOC variation. The benefit of local, geographically weighted regression (GWR) coefficients was tested in a case study on soil organic carbon mapping across a 50,810 km 2 area in northwestern China. This area is composed of an alpine ecosystem in the upper reaches and oases in the middle reaches. The benefit was quantified by comparing the quality of the maps obtained by GWR and geographically weighted ridge regression (GWRR) on the one side and multiple linear regression (MLR) on the other side. In these methods spatial dependence of model residuals is ignored. The root mean squared error (RMSE) of predictions of natural log-transformed SOC obtained with GWR was smaller than with MLR: 0.565 versus 0.618 g/kg. The use of a local ridge parameter in GWRR did not lead to an increase in accuracy. Besides we compared the quality of maps obtained by geographically weighted regression followed by simple kriging of model residuals (GWRSK) and kriging with an external drift (KED) with global regression coefficients. In these methods the spatial dependence of model residuals is incorporated in the model. The RMSE with KED was smaller than with GWRSK: 0.515 versus 0.546 g/kg. We conclude that fitting regression coefficients locally as in GWR only paid when no spatial random effect was included in the model. When a spatial random effect was included, the flexibility of local, geographically weighted regression coefficients was not needed and even undesirable as it led to less accurate predictions than KED with global regression coefficients. In comparing the accuracy of prediction methods by leave-one-out cross-validation (LOOCV) of a non-probability sample it is important to account for possible autocorrelation of pairwise differences in the prediction errors. The effective sample sizes were substantially smaller than the total number of sampling points, so that most pairwise differences in MSE were not significant at a significance level of 10% in a two-sided paired t -test.

The objective of this study was to examine the reflectance of Landsat TM imagery for mapping soil organic Carbon (SOC) content in an Alpine environment. The studied area (ca. 3*104 km2) is the upper reaches of the Heihe River at the northeast edge of the Tibetan plateau, China. A set (105) of topsoil samples were analyzed for SOC. Boosted regression tree (BRT) models using Landsat TM imagery were built to predict SOC content, alone or with topography and climate covariates (temperature and precipitation). The best model, combining all covariates, was only marginally better than using only imagery. Imagery alone was sufficient to build a reasonable model; this was a bit better than only using topography and climate covariates. The Lin’s concordance correlation coefficient values of the imagery only model and the full model are very close, larger than the topography and climate variables based model. In the full model, SOC was mainly explained by Landsat TM imagery (65% relative importance), followed by climate variables (20%) and topography (15% of relative importance). The good results from imagery are likely due to (1) the strong dependence of SOC on native vegetation intensity in this Alpine environment; (2) the strong correlation in this environment between imagery and environmental covariables, especially elevation (corresponding to temperature), precipitation, and slope aspect. We conclude that multispectral satellite data from Landsat TM images may be used to predict topsoil SOC with reasonable accuracy in Alpine regions, and perhaps other regions covered with natural vegetation, and that adding topography and climate covariables to the satellite data can improve the predictive accuracy.

Knowledge of the world soil resources is fragmented and dated. There is a need for accurate, up-to-date and spatially referenced soil information as frequently expressed by the modelling community, farmers and land users, and policy and decision makers. This need coincides with an enormous leap in technologies that allow for accurately collecting and predicting soil properties. We work on a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties. The global land surface will be mapped in 5 years and the map consists of the primary functional soil properties at a grid resolution of 90 by 90 m. It will be freely available, web-accessible and widely distributed and used. The maps will be produced by a global consortium with centres in each of the continents: NRCS for North America, Embrapa for Latin America, JRC for Europe, TSBF-CIAT for Africa, ISSAS for parts of Asia and CSIRO for Oceania. This new global soil map will be supplemented by interpretation and functionality options that aim to assist better decisions in a range of global issues like food production and hunger eradication, climate change, and environmental degradation. In November 2008, a grant has of US$ 18 million has been obtained from the Bill & Melinda Gates foundation to map most parts in Sub-Sahara Africa, and make all Sub-Saharan Africa data available. From this grant there are funds for coordinating efforts in the global consortium.

This study was carried out in the Xujiawan watershed in Sichuan Province, China. The area is characterized by easy weathering of bedrock (sedimentary sandstone and shale) and vulnerability to erosion due to coarse soil texture and weak soil structure. The objective of this study was to understand the dynamics of nitrogen (N) and phosphorus (P) losses during typical storm events. The results showed that runoff generation was sudden and ephemeral, giving rise to flash floods with sharp, narrow hydrographs and short time lags in this type of agricultural ecosystems. The time lag effect of runoff formation depended on soil conditions before storm events. Suspended solids (SS) concentration peaks occurred at the beginning of the storm flow and decreased as rainfall progressed. Meanwhile, SS losses increased at the beginning of runoff flow, then decreased due to flow volume change. Concentrations of NO 3 − -N were four times higher than NH 4 + -N in runoff. NO 3 − -N concentrations first decreased as runoff volume increased until reaching relatively low concentrations, then increased again as runoff volume decreased. Both NH 4 + -N and dissolved phosphorus (DP) in runoff remained at low concentrations with a small magnitude of variation. Suspended particulate nitrogen (SN) was the dominant N form. Losses of NO 3 − -N were higher than NH 4 + -N in the dissolved nitrogen (DN). Suspended particulate nitrogen losses were several times higher than DN in the early period of runoff formation, but the ratio of SN/DN decreased gradually as rainfall progressed, and by the end of the storm event the rate was lower than 1, indicating DN took the main form after the early physical flush. In the early period of storm events, suspended particulate phosphorus (SP)/DP was above 70 and decreased as rainfall progressed, but remained higher than 1, which showed that SP was the main form of P loss. The transport of N, and particularly P, was intimately linked to sediment in the runoff, indicating an obvious soil erosion-associated nutrient transport, especially in relation to P loss.

International audience; Soils are increasingly recognized as major contributors to ecosystem services such as food production and climate regulation (1, 2), and demand for up-to-date and relevant soil information is soaring. But communicating such information among diverse audiences remains challenging because of inconsistent use of technical jargon, and outdated, imprecise methods. Also, spatial resolutions of soil maps for most parts of the world are too low to help with practical land management. While other earth sciences (e.g., climatology, geology) have become more quantitative and have taken advantage of the digital revolution, conventional soil mapping delineates space mostly according to qualitative criteria and renders maps using a series of polygons, which limits resolution. These maps do not adequately express the complexity of soils across a landscape in an easily understandable way