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Soil spatial information has traditionally been presented as polygon maps at coarse scales. Solving global and local issues, including food security, water regulation, land degradation, and climate change requires higher quality, more consistent and detailed soil information. Accurate prediction of soil variation over large and complex areas with limited samples remains a challenge, which is especially significant for China due to its vast land area which contains the most diverse soil landscapes in the world. Here, we integrated predictive soil mapping paradigm with adaptive depth function fitting, state-of-the-art ensemble machine learning and high-resolution soil-forming environment characterization in a high-performance parallel computing environment to generate 90-m resolution national gridded maps of nine soil properties (pH, organic carbon, nitrogen, phosphorus, potassium, cation exchange capacity, bulk density, coarse fragments, and thickness) at multiple depths across China. This was based on approximately 5000 representative soil profiles collected in a recent national soil survey and a suite of detailed covariates to characterize soil-forming environments. The predictive accuracy ranged from very good to moderate (Model Efficiency Coefficients from 0.71 to 0.36) at 0–5 cm. The predictive accuracy for most soil properties declined with depth. Compared with previous soil maps, we achieved significantly more detailed and accurate predictions which could well represent soil variations across the territory and are a significant contribution to the GlobalSoilMap.net project. The relative importance of soil-forming factors in the predictions varied by specific soil property and depth, suggesting the complexity and non-stationarity of comprehensive multi-factor interactions in the process of soil development.

Background. The hypercoagulable status, which forms a vicious cycle with hematogenous metastasis, is a common systemic alteration in cancers. As modeling is a key approach in research, a model which is suitable for studying how the hypercoagulable status promotes hematogenous metastasis in breast cancer is urgently needed. Methods. Based on the tumor-bearing period (TBP) and postoperative incubation period (PIP), 4T1-breast cancer models were constructed to evaluate coagulation and tumor burden to generate multiple linear regression-based lung metastasis prediction formula. Platelets and 4T1 cells were cocultured for 30 min or 24 h in vitro to evaluate the early and late phases of their crosstalk, and then the physical characteristics (concentration and size) and procoagulant activity of the coculture supernatants were assayed. Results. The multiple linear regression model was constructed as log 10 photon number = 0.147 TBP + 0.14 PIP + 3.303 ( TBP ≤ 25 and PIP ≤ 17 ) to predict lung metastasis. Coculture of platelets and 4T1 cells contributed to the release of extracellular vesicles (EVs) and the development of the hypercoagulable status. Conclusions. In vivo and in vitro hypercoagulable status models were developed to explore the mechanism of hypercoagulable status which is characterized by platelet activation and promotes hematogenous metastasis in breast cancer.

As the thin layer at the Earth’s terrestrial surface, the critical zone (CZ) ranges from the vegetation canopy to the aquifer or the interface between saprolite and bedrock and varies greatly in space. In the last decade, much attention has been paid to the establishment of Critical Zone Observatories (CZOs) that focus on various aspects of CZ science over different time scales. However, to the best of our knowledge, few studies have explicitly contributed to CZ classification or regionalization; thus, the spatial patterns of similar CZs have not been clearly identified. This study proposed a three-category CZ classification scheme by integrating environmental factors that greatly affect the transfer of energy and mass in the Earth’s near-surface environment and thus dominate CZ formation and evolution, i.e., climate, parent material, soil type, groundwater table depth, geomorphology and land use. The main goal was to highlight the zonality of these driving forces, of which the high-category classification units were overlaid to delineate the CZ boundaries. The CZ regionalization of China was performed as a case study, resulting in 44 major regions (1st category), 100 submajor regions (2nd category) and 1448 regions (3rd category). The spatial distributions and driving factors of the ten largest regions were identified, followed by a simple comparison of the CZO network. Then, the proposed CZ regionalization was compared with recent studies on regionalization in China to evaluate its successes and weaknesses. By linking together CZ studies from the last decade, we advocate that a theoretical framework integrating the CZ evolution processes with ecological functions acts as one of the frontiers of CZ science. Our study demonstrates that the proposed three-category CZ classification scheme effectively identifies the spatial variations in CZs and could thus be further applied in other areas to advance terrestrial environmental research and provide decision support for the sustainable management of natural resources.

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

Clay CEC is one of identification indexes of the LAC-ferric horizon which is the diagnostic horizon of ferrosols in Chinese Soil Taxonomy, and it is defined as soil CEC × 1000/clay content, rather than the measured CEC of the extracted clays; however, such a calculation method would definitely lead to an overestimation of clay CEC because it doesn’t remove the contribution to soil CEC from other soil parameters. In this study, the physiochemical data of the subhorizons from 82 soil series in the tropical and subtropical regions in south China were used, clay CEC was calculated according to the current formula and measured after clays being extracted, the measured and calculated clay CEC were compared, the influencing factors were analyzed for their difference, and the new algorithms were established for clay CEC. The results showed that the measured clay CEC was 21.86% - 99.53% with a mean of 66.88% of the calculated one (significantly lower at p 2O3 (the contribution was 52.51% and 25.36%, respectively). By comparison of established regression models of clay CEC with other soil parameters, two new algorithms were recommended for clay CEC as follows: 1) Clay CEC = 10.32 − 0.14pH − 0.05OM − 0.11Fe2O3 + 0.01Silt − 0.01Clay + 1.17CECsoil, R2 = 0.705, P −3.40 + 0.01Sand + 0.02Silt + 1.05CECsoil, R2 = 0.589, P < 0.01).

Cation exchange capacity (CEC) is one of the most important properties of soils. The NH4OAc (pH = 7.0) exchange method is usually recommended to determine CEC (CEC1) of all soils with different pH values, particularly for studies on soil taxonomy. But comparatively the BaCl2-MgSO4 forced-exchange method is more authentic in determining CEC (CEC2) of tropical and subtropical highly-weathered acid soils. But so far little is known about the difference between CEC1 and CEC2. In this study, the physiochemical data of 114 acid B horizon soils from 112 soil series of tropical and subtropical China were used, CEC1 and CEC2 were determined and compared, the influencing factors were analyzed for the difference between CEC1 and CEC2, and then a regression model was established between CEC1 and CEC2. The results showed that CEC2 was significantly lower than CEC1 (p 2 was 14.76% - 63.31% with a mean of 36.32% of CEC1. In view of the contribution to CEC from other properties, CEC2 was mainly determined by pH (45.92%), followed by silt (21.05%), free Fe2O3 (17.35%) and clay contents (12.76%), CEC1 was mainly decided by free Fe2O3 content (40.38%), followed by pH (28.39%) and silt content (27.29%; and the difference between CEC1 and CEC2 was mainly affected by free Fe2O3 (50.92%), followed by silt content (26.46%) and pH (21.80%). The acceptable optimal regression model between CEC2 and CEC1 was established as CEC2 = 2.3114 × CEC11.1496 (R2 = 0.410, P 2-MgSO4 forced-exchange method is recommended in determining CEC of the highly-weathered acid soils in the tropical and subtropical regions.

The removal of organic matter and iron oxides could increase and decrease soil CEC in tropical and subtropical regions, but the quantitative information is insufficient so far about the change of soil CEC, the influence factors and their contribution. In this study, the subhorizon soils of 24 soil series in the tropical and subtropical China were used, pH, particle size composition, organic matter, iron oxides of these samples were measured, and also CECs were measured and compared for the original soils and after the removal of organic matter and iron oxides. The results showed that, compared with CEC of the original soil, the eliminating organic matter increased soil CEC significantly by 2.28% - 56.50% with a mean of 24.02%, but the further obliterating iron oxides decreased soil CEC significantly by 0.75% - 20.30% with a mean of 7.73%. CEC after the removal of organic matter and iron oxides had positive correlation with iron oxides (p − 0.546pH − 0.024OM + 0.053FexOy − 0.001Silt + 0.007Clay + 0.972CECoriginal (R2 was 0.923, RSME was 1.55 cmol(+)∙kg−1, p − 0.546pH − 0.024OM + 0.053FexOy − 0.001Silt + 0.007Clay + 0.972CECoriginal (R2 was 0.923, RMSE was 1.55 cmol(+)∙kg−1, p < 0.01). Further research is needed in the future as for exploring internal functional mechanism in view of soil electrochemistry and mineralogy.

Targeting EGFR, epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs), brings lights to the treatment of non-small cell lung cancer (NSCLC). Although T790M mutation responded as one of the main reasons of acquired resistance, still 15% of the resistance patients can't be explained by the known mechanisms. The purpose of this research was to identify some new mechanisms of gefitinib acquired resistance, and to predict small molecules drugs which may reverse drug resistance by integrated bioinformatics analysis. The GSE34228 data package containing the microarray data of acquired gefitinib-resistant cell line (PC9GR) and gefitinib-sensitive cell line (PC9) from the GEO database were downloaded, and gene co-expression networks by weighted gene co-expression network analysis (WGCNA) were constructed to identified key modules and key genes related to gefitinib resistance. Furthermore, the significantly differentially expressed genes (DEGs) between the two cell types were screened out, and a protein-protein interaction (PPI) network to obtain the key genes of DEGs was accordingly constructed. Through the above two methods, 4 hub genes, PI3, S100A8, AXL and PNPLA4 were mined as the most relevant to gefitinib resistance. Among them, PI3, S100A8 were down-regulated in PC9GR cell samples, while AXL, PNPLA4 were up-regulated. The gene set enrichment analysis (GSEA) for single gene showed that the four hub genes were mainly correlated with cell proliferation and cycle. Besides, small molecule drugs with the potential to overcome resistance, such as Emetine and cephaeline, were screened by CMap database. Consistent with this, in vitro experiments results have shown that emetine and cephaeline can increase the sensitivity of drug-resistant cells to gefitinib, and the mechanism may be related to the regulation of PI3 and S100A8. In conclusion, 4 hub genes were found to be related to the occurrence of gefitinib resistance in non-small cell lung cancer, and several small molecule drugs were screened out as potential therapeutic agents to overcome gefitinib resistance, which may lead a new way for the treatment of NSCLC of acquired resistance to gefitinib.

The anti-angiogenic drug Bevacizumab (Bev) is engaged in neoadjuvant therapy for non-metastatic breast cancer (NMBC). However, whether neoadjuvant Bev providing a greater benefit to patients is debatable. Our study aimed to review Bev's role in Neoadjuvant therapy (NAT) in NMBC and identify predictive markers associated with its efficacy by systemic review and meta-analysis. Eligible trials were retrieved from the Pubmed, Embase, and Cochrane Library, and random or fixed effects models were applied to synthesize data. Power of pCR to predict DFS or OS was evaluated by nonlinear mixed effect model. In NMBC, Bev significantly improved the rate of patients achieving pCR, but this benefit discontinued in DFS or OS. Biomarkers such as PAM50 intrinsic subtype, VEGF overexpression, regulation of VEGF signaling pathway, hypoxia-related genes, BRCA1/2 mutation, P53 mutation and immune phenotype can be used to predict Bev-inducing pCR and/or DFS/OS. Unfortunately, although patients with pCR survived longer than those without pCR when ignoring the use of Bev, but patients achieving pCR with Bev might survive shorter than those achieving pCR without Bev. Subgroup analyses found Bev prolonged patients' OS when given pre- and post-surgery. Lastly, adding Bev increased adverse effects. Overall, Bev offered limited effect for patients with NMBC in an unscreened population. However, in biomarkers - identified subgroup, Bev could be promising to ameliorate the prognosis of specific patients with NMBC.

With increasing urban area and population, global cities are playing a more important role in the alteration of the global biogeochemical cycles. The aims of this study are to understand the concentrations and stoichiometric relations of biogenic elements (C, N, and P) in urban soils, further to reveal the effects of C, N, and P accumulation on the urban environment. We collected 317 surface (0–10 cm) soil samples taken from Nanjing, China, a typical city with more than 2000 years of history. These soil samples were located in different urban zones of Nanjing with different land use histories. The soil C, N, and P concentrations were determined. The stoichiometric relations of soil C, N, and P were investigated in urban soils. Meanwhile, some studies on sources of C, N, and P in diverse urban settings from literature were combined to explore the universal rule of C, N, and P cycling and their ecological and environmental effects in urban area. Compared to rural soils, more C, N, and P are accumulated in the urban soils, which also change their stoichiometric relations. The concentrations of OC, TN, and TP in urban top soils are 17.0 ± 9.69 g kg−1, 1.53 ± 0.92 g kg−1, and 1.31 ± 0.67 g kg−1, respectively. The mean atomic ratio of C:N:P is 37:3:1 in the surface of urban soils that strictly differs from natural soils in China and the whole world. The mean of C:N ratio in urban soils is similar to that of agriculture, grassland, and forest soils. However, the ratios of C:P and N:P in urban soils are much lower than that in agricultural, forest, and grassland soils. This implies that P is extremely enriched in the urban soils. The high C in urban soils are considered coming from natural and anthropogenic sources. The high N and P mainly come from anthropogenic sources. The well-constrained C:N:P ratio in rural soils does not apply for urban soils. The abnormal C:N:P ratio of urban soils is the result of unbalanced accumulation of C, N, and P from human activities. Urban soils are already an important storage of carbon. High N and P in urban soils may bring threat of surface water eutrophication and ground water contamination. These effects are expected to increase with the city development time.

Heparanase, the sole heparan sulfate degrading endoglycosidase, regulates multiple biological activities that enhance tumor growth, angiogenesis and metastasis. Much of the impact of heparanase on tumor progression is related to its function in mediating tumor-host crosstalk, priming the tumor microenvironment to better support tumor growth and metastasis. We have utilized mice over-expressing (Hpa-tg) heparanase to reveal the role of host heparanase in tumor initiation, growth and metastasis. While in wild type mice tumor development in response to DMBA carcinogenesis was restricted to the mammary gland, Hpa-tg mice developed tumors also in their lungs and liver, associating with reduced survival of the tumor-bearing mice. Consistently, xenograft tumors (lymphoma, melanoma, lung carcinoma, pancreatic carcinoma) transplanted in Hpa-tg mice exhibited accelerated tumor growth and shorter survival of the tumor-bearing mice compared with wild type mice. Hpa-tg mice were also more prone to the development of metastases following intravenous or subcutaneous injection of tumor cells. In some models, the growth advantage was associated with infiltration of heparanase-high host cells into the tumors. However, in other models, heparanase-high host cells were not detected in the primary tumor, implying that the growth advantage in Hpa-tg mice is due to systemic factors. Indeed, we found that plasma from Hpa-tg mice enhanced tumor cell migration and invasion attributed to increased levels of pro-tumorigenic factors (i.e., RANKL, SPARC, MIP-2) in the plasma of Hpa-Tg vs. wild type mice. Furthermore, tumor aggressiveness and short survival time were demonstrated in wild type mice transplanted with bone marrow derived from Hpa-tg but not wild type mice. These results were attributed, among other factors, to upregulation of pro-tumorigenic (i.e., IL35(+)) and downregulation of anti-tumorigenic (i.e., IFN-γ(+)) T-cell subpopulations in the spleen, lymph nodes and blood of Hpa-tg vs. wild type mice and their increased infiltration into the primary tumor. Collectively, our results emphasize the significance of host heparanase in mediating the pro-tumorigenic and pro-metastatic interactions between the tumor cells and the host tumor microenvironment, immune cells and systemic factors.

The black soil region in northeastern China is one of the most important grain production areas in the country, and plays a key role in food security. Large lands have been brought into cultivation in the last 100 years. Because these lands have lesser slope gradients compared to those in the loess plateau and other regions in China, soil erosion has been ignored in this area for a long time. Few soil conservation practices have been implemented. Serious soil erosion problems due to long slope lengths have been identified based on recent research and observations in the study area. The government has realized the necessity and urgency of soil conservation. However, to create policies and plans for black soil conservation, questions such as how much of the black soil region, and where in the region, erosion is a problem must be addressed. Currently, the black soil region of northeastern China is regarded as having a total area of 1.09 million square kilometers, including Heilongjiang, Jilin, the north part of Liaoning, and the east part of Inner Mongolia, in which there are also many non-black soils in mountain regions of Daxingan, Xiaoxingan, and Changbaishan. Therefore, it is difficult to determine precisely the conservation priorities for this large area. In this study, the black soils were defined and their concentrated area was delineated in northeastern China. The black soils were defined as soils with the “mollic epipedon”, which were classified as Isohumosols in Chinese Soil Taxonomy or Mollisols in the USDA Soil Taxonomy, and classified as Phaezoems, Chernozems, Kastanozems and Grayzems soils according to the Genetic Soil Classification of China (GSCC). The region dominated by these four soils in GSCC was defined as the black soil region. Because Phaezoems and Chernozems have higher organic matter contents and deeper mollic epipedon depths, and are distributed in the center of the study area, these two soils were defined as the typical black soil, and their dominate area was defined as the typical black soil region. A soil map in the scale of 1:1000000, made from the second national soil survey, was used with ArcGIS 10.2 software to delineate both black soil and typical black soil regions. A method called “central gravitational agglomeration” was developed. All of the soil polygons were selected, and the farthest and the smallest polygon were merged into its closest adjacent one if its radius was larger than the distance between it and its closest one. Otherwise it was abandoned. The same process was repeated until only a few small polygons were left and a regional outline appeared. Four soils were used to determine the exact boundaries of the black soil region, and two soils were used to determine the exact boundaries of the typical black soil region. The results showed that the area of the black soil region was 556000 km2, including 146 counties in which 33.0% was cultivated land. The area of the typical soil region was 333000 km2, including 138 counties in which 50.2% was cultivated land. Due to the long slopes, the soil erosion rate from the cropland with slope greater than 0.25° is estimated to be larger than soil loss tolerance of 200 t/km2. The cultivated lands with slope greater than 0.25° were regarded as sloped cultivated land or sloped cropland, which totaled 89000 km2, or 16.0% of the total land for the black soil region, and 78000 km2, or 23.4% of the total land for the typical black soil region. The sloped cultivated land in both the black soil region and typical black soil region should be targeted as key areas for soil erosion control in northeastern China.

Objective: To study the effect and mechanism of Huayu Wan (化瘀丸, HYW) in combination of chemotherapy of tumor treatment. Methods: HYW serum was added in Lewis cells to assess its impact on fluorescent doxorubicin delivery in vitro. Then, Lewis tumor cells was implanted in C57BL/6 mice via xenograft transplantation. Tumor growth was measured and signal intensity corresponding to blood flow was assessed by laser doppler perfusion imaging (LDPI). Finally, the effect of HYW on the effificacy of doxorubicin was studied. Results: HYW can improve the transfer of fluorescent doxorubicin into cells. The blood flow signal in the tumor tissues of the HYW group was higher than that of the control group (P

Accumulation of soluble organic nitrogen (SON) in soil poses a significant threat to groundwater quality and plays an important role in regulating the global nitrogen cycle; however, most related studies have focused only on the upper 100-cm soil layers. Surface land-use management and soil properties may affect the vertical distribution of SON; however, their influence is poorly understood in deep soil layers. Therefore, this study assessed the response of SON concentration, pattern, and storage in deep regoliths to land-use conversion from woodlands to orchards in a subtropical hilly region. Our results showed that the SON stocks of the entire soil profile (up to 19.5 m) ranged from 254.5 kg N ha

Liver is the most common site of metastases of colorectal cancer, and liver metastases present with distinct histopathological growth patterns (HGPs), including desmoplastic, pushing and replacement HGPs and two rare HGPs. HGP is a miniature of tumor-host reaction and reflects tumor biology and pathological features as well as host immune dynamics. Many studies have revealed the association of HGPs with carcinogenesis, angiogenesis, and clinical outcomes and indicates HGP functions as bond between microscopic characteristics and clinical implications. These findings make HGP a candidate marker in risk stratification and guiding treatment decision-making, and a target of imaging observation for patient screening. Of note, it is crucial to determine the underlying mechanism shaping HGP, for instance, immune infiltration and extracellular matrix remodeling in desmoplastic HGP, and aggressive characteristics and special vascularization in replacement HGP (rHGP). We highlight the importance of aggressive features, vascularization, host immune and organ structure in formation of HGP, hence propose a novel "advance under camouflage" hypothesis to explain the formation of rHGP.

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.

Increased soil organic carbon (OC) in China has been reported in the past two decades, suggesting the sequestration of atmospheric carbon dioxide into soil, mitigating climate change and improving soil health. On the other hand, soil pH decrease had also been reported nationwide. If the two are related, the strategy of increasing soil OC could negatively affect soil quality for food production and the environment. We investigate this thread based on large-scale soil survey data from two provinces with typical soil and cropping patterns in the east and south of China, Jiangsu (102,600 km

Nitrogen (N)-induced soil acidification has received much attention worldwide. Nitrification and soil N mineralization are two key N cycle processes that affect soil acidification. However, the seasonal dynamics of soil pH under their combined influence is unclear. We studied the effect of N fertilization on soil pH and N transformations using

Purple paddy soils cover about 66% of the paddy soils in Sichuan Basin. Complex interactions made the effects of potassium fertilizer application on NH4+ adsorption more complicated and the behavior of NH4+ and K+ interaction in purple paddy soils has rarely been evaluated. We hypothesize that correct management of these soils can enhance the efficiency of ammonium and potassium fertilizers. In order to determine correct management methods, it is important to understand the interaction of main nutrient cations NH4+ and K+ and maturation hydroponics in purple paddy soils with different paddy cultivation times. A purple paddy soil chronosequence with cultivation history from 0 to 300 years was studied to understand the respective effects of SOM and mineralogy on NH4+ and K+ sorption behavior by adsorption experiments using samples both before and after H2O2 oxidation. The study shows that maturation hydroponics influenced NH4+ and K+ adsorption mainly through changing clay mineralogy and enhancing SOM accumulation. SOM and smectite play positive effects for NH4+ adsorption. The K+ adsorption, however, is mainly affected by the smectite changes. The adsorption percentages are obviously higher at 25–50 mg L−1 for each NH4+ solution and higher at 50–100 mg L−1 for each K+ solution. When ammonium and potassium were applied together, NH4+ and K+ adsorption are mutually weakened. In addition, the percentage of K+ adsorption increased from 49.7–57.7% for the 100 mg L−1 K+ solution to 50.9–58.5% for the 200 mg L−1 K+ solution at 200 mg L−1 of added NH4+. SOM enrichments could be a positive way to improve the ammonium fertilizer utilization efficiency in purple paddy soils. Potassium may be more vulnerable to loss at low K+ concentrations given that ammonium and potassium fertilizers were applied together and it should be separately applied to enhance the utilization efficiency of applied fertilizer.

Depth patterns of soil microbial distribution have not been well characterized and little is known about the balance between stochastic and deterministic processes in shaping microbial community th...

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 probe Fe isotopic signatures of the Quaternary Red Clay (QRC) in subtropical southeastern China, two QRC profiles located in southern Anhui Province, Southeast China, were studied. The whole profiles were generally in a narrow range in δ 56 Fe of −0.040 ± 0.061‰—0.117 ± 0.048‰. The Yellow-brown Earth (YBE) and Uniform Red Clay (URC) of the upper profiles were similar in δ 56 Fe to the Xiashu Loess along the Yangtze River, Southeast China, and the loess, paleosols and Tertiary red clay in the Chinese Loess Plateaus, Northwest China, as well as the baseline of terrestrial igneous rocks. The slight variation of δ 56 Fe from the YBE to the URC suggests that the chemical weathering and rubification on the aerobic surface did not fractionate Fe isotopes significantly. The Reticulate Red Clay (RRC) underlying the YBE and URC fluctuated in δ 56 Fe to some extent. The white veins separated from the lower RRC were depleted of Fe oxides and heavier in Fe isotopes, and the red veins, on the contrary, were isotopically lighter in Fe. δ 56 Fe of the white veins, 0.345 ± 0.053‰ on average, was significantly higher than the bulk samples, 0.033 ± 0.044‰ on average, and the red veins, −0.021 ± 0.046‰ on average. This suggests that the reticulate textures of the RRC were formed by the reductive removal/re-precipitation of Fe due to the cyclical changes of redoxic conditions. Fe isotopic composition of the QRC was dominantly controlled by the redoxic mobility of Fe, rather than the degree of weathering. δ 56 Fe of the profiles was not correlated with the paleoclimatic events, and thus cannot be used as a paleoclimatic proxy. The fractionation of Fe isotopes in the lower RRC, however, indicated the occurrence of over-humid paleoclimate with alternations between drought and wetness in Southern China during the Pleistocene.

Spatial prediction is an important approach to obtain location-specific values of soil electrical conductivity (EC), which is a proxy of soil salinity and important for agricultural management in arid and semi-arid areas. Linear regression models assume that the relation between soil EC and environmental covariates is constant over the area to be predicted. This is problematic at the regional scale, at which some of the regression parameters may indeed be globally constant, whereas others may vary locally. Moreover, model residuals often exhibit spatial dependence, which invalidates the ordinary least squares linear regression. This study examined the combination of a mixed geographically weighted regression model with simple kriging of the residuals (MGWGK) for mapping soil EC in the Heihe River Basin, an inland river basin in arid northwest China. We compared the performance of MGWRK with those of multiple linear regression (MLR), regression kriging (RK), geographically weighted regression (GWR), geographically weighted regression kriging (GWRK) and mixed geographically weighted regression (MGWR). Environmental covariates were developed from spatial information on topography, climate, vegetation, and geographic position. A ten-fold cross-validation was applied to evaluate predictive accuracy of the various methods. Soil EC ranged from 0.031 to 182.100 dS m−1, exhibiting a contrasting distribution of soil EC in the upper, middle, and lower river reaches. The MGWRK method outperformed other methods. The effects of different environmental covariates on soil EC were revealed by the fixed and geographically varying parameters of MGWRK. The nugget-to-sill ratios of fitted variogram models all fell between 25 and 32%, exhibiting moderate spatial autocorrelation of models residuals. Predictive accuracy was improved by MGWRK, as the spatial dependence of model residuals were included in the prediction. When selecting an optimal linear regression model, covariates should be tested to see if they are constant (as in MLR) or spatially varying (as in GWR) or semi-varying (as in MGWR), and model residuals should be tested for spatial dependence (as in MGWRK).

Organic carbon (OC) plays a pivotal role in earth surface systems. However, current three-dimensional (3D) mapping studies usually focus on a soil depth of 1 m rather than the depth to the bedrock. A top-down method using piecewise depth functions was proposed to fit the OC vertical decline patterns in a subtropical catchment in southern China. The vertical variation in OC was greatly affected by the heterogeneous topsoil due to natural processes and anthropogenic disturbances. Thus, topsoil OC maps were produced and utilized as covariates to indicate the OC decline rates and to benefit the 3D OC simulation. A distribution map of the underground critical zone thickness (UCZT) was applied as a lower boundary for the 3D simulation. Six widely used mapping techniques were performed to predict the spatial distribution of topsoil OC and depth function parameters. The overall cross-validation results showed a root mean squared error (RMSE) of 1.7 g kg–¹ and a ratio of performance to deviation (RPD) of 1.82. Given limited boreholes, validation showed that the depth function performed better in the lower part (>1 m) than in the upper part (

Nitrate accumulation has been reported in the top 1 m and subsurface soil (> 1 m) across arid to semi-humid regions, but not in humid regions. Nitrate inventories through the whole regolith, referred to collectively as soil and saprolite, in humid regions have received little attention to date, likely due to previously assumed low nitrification rates and large nitrogen (N) losses by severe surface runoff and erosion. In order to understand if and how reactive N exists in the below ground (soil and saprolite) in humid environment, the amount of NO3--N, NH4+-N and dissolved organic N (DON) present in the regolith to a depth of 9 m in a typical red soil Critical Zone was investigated under different land uses (upland, woodland and paddy field). The Red Soil Critical Zone Observatory is located in the subtropical Jiangxi Province, China, with a mean annual precipitation of 1795 mm and mean annual potential evapotranspiration of 1229 mm. The examined regoliths were acidic, highly weathered, and mainly clay loam in texture. Results showed that on average 92% (827 ± 97 kg N ha-1) of NO3--N and 82% (521 ± 153 kg N ha-1) of DON were stored at depth (from a depth of 1 m to the bedrock surface) in the upland regolith, while 92% (283 kg N ha-1) of NO3--N and 78% (820 kg N ha-1) of DON were stored at depth in the woodland regolith. Nitrate N significantly accumulated with depth in the upland regolith from the 1- to 4-m depth interval (p < 0.01), while the inventory (632 ± 75 kg N ha-1) in the top 3-m zone accounted for on average 71% of the total. Dissolved organic N significantly accumulated with depth in the upland regolith from the 0- to 3-m depth interval (p < 0.01), while the inventory (408 ± 75 kg N ha-1) in the top 3-m zone accounted for on average 64% of the total. There was no significant accumulation for NH4+-N throughout the upland regolith (p = 0.35). No substantial accumulation of dissolved N was measured at depth in paddy field regoliths with different cultivation ages. The finding that large reservoirs of reactive N can exist in deep regolith rather than in the routinely investigated solum of subtropical regions shows a missing part of the terrestrial N budget and raises concerns about potential 34 groundwater nitrate pollution.

The soil's pH is the single most important indicator of the soil's quality, whether for agriculture, pollution control or environmental health and ecosystem functioning. Well documented data on soil pH are sparse for the whole of China — data for only 4700 soil profiles were available from China's Second National Soil Inventory. By combining those data, standardized for the topsoil (0–20 cm), with 17 environmental covariates at a fine resolution (3 arc-second or 90 m) we have predicted the soil's pH at that resolution, that is at more than 109 points. We did so by parallel computing over tiles, each 100 km × 100 km, with two machine learning techniques, namely Random Forest and XGBoost. The predictions for the tiles were then merged into a single map of soil pH for the whole of China. The quality of the predictions were assessed by cross-validation. The root mean squared error (RMSE) was an acceptable 0.71 pH units per point, and Lin's Concordance Correlation Coefficient was 0.84. The hybrid model revealed that climate (mean annual precipitation and mean annual temperature) and soil type were the main factors determining the soil's pH. The pH map showed acid soil mainly in southern and north-eastern China, and alkaline soil dominant in northern and western China. This map can provide a benchmark against which to evaluate the impacts of changes in land use and climate on the soil's pH, and it can guide advisors and agencies who make decisions on remediation and prevention of soil acidification, salinization and pollution by heavy metals, for which we provide examples for cadmium and mercury.

Widespread soil acidification due to atmospheric acid deposition and agricultural fertilization may greatly accelerate soil carbonate dissolution and CO2 release. However, to date, few studies have addressed these processes. Here, we use meta-analysis and nationwide-survey datasets to investigate changes in soil inorganic carbon (SIC) stocks in China. We observe an overall decrease in SIC stocks in topsoil (0–30 cm) (11.33 g C m–2 yr–1) from the 1980s to the 2010s. Total SIC stocks have decreased by ∼8.99 ± 2.24% (1.37 ± 0.37 Pg C). The average SIC losses across China (0.046 Pg C yr–1) and in cropland (0.016 Pg C yr–1) account for ∼17.6%–24.0% of the terrestrial C sink and 57.1% of the soil organic carbon sink in cropland, respectively. Nitrogen deposition and climate change have profound influences on SIC cycling. We estimate that ∼19.12%–19.47% of SIC stocks will be further lost by 2100. The consumption of SIC may offset a large portion of global efforts aimed at ecosystem carbon sequestration, which emphasizes the importance of achieving a better understanding of the indirect coupling mechanisms of nitrogen and carbon cycling and of effective countermeasures to minimize SIC loss.

Nitrate (NO3−) loss and enrichment in water bodies caused by fertilization are a major environmental problem in agricultural areas. However, the quantitative contribution of different NO3− sources, especially chemical fertilizers (CF) and soil organic nitrogen (SON), to NO3− runoff loss remains unclear. In this study, a systematic investigation of NO3− runoff and its sources was conducted in a subtropical agricultural watershed located in Yujiang County, Jiangxi Province, China. A semi-monthly sampling was performed at the inlet and outlet from March 2018 to February 2019. Hydrochemical and dual NO3− isotope (15 N and 18O) approaches were combined to estimate the NO3− runoff loss and quantify the contribution of different sources with a Bayesian isotope mixing model. Source apportionment by Stable Isotope Analysis in R (SIAR) suggested that NO3− in runoff was mainly derived from nitrification of ammonium (NH4+) mineralized from SON (37–52%) and manure/sewage (M&S) (25–47%), while the contribution of CF was relatively small (14–25%). The contribution of various sources showed seasonal variations, with a greater contribution of CF in the wet growing season (March to August). Compared with the inlet which contributed 37–40% to runoff NO3−, SON contributed more at the outlet (49–52%). Denitrification in the runoff was small and appeared to be confined to the dry season (September to February), with an estimated NO3− loss of 2.73 kg N ha−1. The net NO3− runoff loss of the watershed was 34.5 kg N ha−1 yr−1, accounting for 15% of the annual fertilization rate (229 kg N ha−1 yr−1). Besides M&S (22%), fertilization and remineralization of SON (CF + SON) were the main sources for the NO3− runoff loss (78%), suggesting accelerated nitrification of NH4+ from CF (24%) and SON mineralization (54%). Our study indicates that NO3− runoff loss in subtropical agricultural watersheds is dominated by nonpoint source pollution from fertilization. SON played a more important role than CF. Besides, the contribution of sewage should not be neglected. Our data suggest that a combination of more rational fertilizer N application (CF), better management of SON, and better treatment of domestic sewage could alleviate NO3− pollution in subtropical China.

Soil acidification along with base cations loss degrades soil quality and is a major environmental problem, especially in agroecosystems with extensive nitrogen (N) fertilization. So far, the rates of proton (H

Plant root-derived carbon (C) inputs (Iroot) are the primary source of C in mineral bulk soil. However, a fraction of Iroot may lose directly (Iloss, e.g., via rhizosphere microbial respiration, leaching and fauna feeding) without contributing to bulk soil C pool. This loss has never been quantified, particularly at global scale, inhibiting reliable estimation of soil C dynamics. Here we integrate three observational global datasets including radiocarbon content, allocation of photosynthetically assimilated C, and root biomass distribution in 2,034 soil profiles to quantify Iroot and its contribution to the bulk soil C pool. We show that global average Iroot in the 0-200 cm soil profile is 3.5 Mg ha-1 yr-1, ~80% of which (i.e., Iloss) is lost rather than entering bulk soil. If ignoring Iloss, bulk soil C turnover will be incorrectly estimated to be four times faster. This can explain why Earth system models (in which all Iroot enters bulk soil C pools) predict much faster soil C turnover than radiocarbon-constrained estimates. Iroot decreases exponentially with soil depth, and the top 20 cm soil contains >60% of total Iroot. Actual C input to bulk soil (i.e., Iroot – Iloss) shows a similar depth distribution to Iroot. We also map Iloss and its depth distribution across the globe. Our results demonstrate the global significance of direct C losses which limit the contribution of Iroot to bulk soil C storage; and provide spatially explicit data to facilitate reliable soil C predictions via separating direct C losses from total root-derived C inputs.

Nitrate accumulated deep (>100 cm) in the regolith (soil and saprolite) threatens groundwater quality, but most studies focus only on nitrate nearer the surface (

Modern monothetic hierarchical soil classification systems such as the Chinese Soil Taxonomy (CST) are semi‐quantitative and their future development is likely to trend towards a fully quantitative system using the concepts of numerical taxonomy. Previous researchers have calculated the taxonomic distances between individual soils based on soil physiochemical properties, not, however, based on spectra of full soil profiles with different horizons. We hypothesized that numerical taxonomy implemented by cluster analysis of the taxonomic distance matrix based on vis–NIR spectra would accord with some CST Orders assigned by pedologists, and not with others, depending on how closely spectral features represent the diagnostic features used in the classification. Taxonomic distances in spectral space were computed for all pairs of 191 profiles, resulting in a distance matrix on which hierarchical cluster analysis was performed. Different indices were calculated to determine the optimum number of clusters, resulting in four spectral soil classes. These were then compared with CST Orders assigned to the profiles by expert allocation. The numerical classes and CST Orders matched poorly because of the completely different classification philosophies behind numerical taxonomy and the CST, which is based largely on presumed genesis and uses sharp thresholds leading to very similar soils being allocated to different classes. Thus, we consider the numerical classification as information that is complementary to the monothetic hierarchical system. Numerical classification can reveal the taxonomic objective aspects of the relation between the defined classes and can suggest new groupings. HIGHLIGHTS: Taxonomic distances can serve as an objective measure of soil similarity. Soil spectra are a good candidate for numerical classification based on taxonomic distances. The conceptual basis of Chinese Soil Taxonomy (CST) does not match that of taxonomic distance. Numerical classification based on spectra can suggest revisions to the CST.

The concentration of soil organic carbon (SOC) is one of the most important soil properties, and its spatio-temporal variability greatly affects the global climate and agroecology. To investigate the effects of land use and climate change on SOC, a heuristic cellular automaton (HCA) model was proposed and applied to a plains area in eastern China with a high population density and rapid urbanization rate. The HCA model was designed to simulate the geographical variation in SOC dynamics over the long term (2080), and lateral carbon (C) migration is represented by revised neighbourhood variables at the macro scale. Three widely used soil mapping techniques were applied for comparison: multiple linear regression (MLR), support vector machine (SVM) and kriging with external drift (KED). The HCA model enhanced the accuracy of the predicted SOC by 15.27% over MLR, 12.31% over SVM and 10.98% over KED. Future land use maps were produced using legacy land use data and artificial neural network-based cellular automata (CA), and the simulation results showed the rapid urbanization of this area, where the percentage of cropland declined by 23.75% and that of village/urban areas increased by 22.90% from 2010 to 2080. The overall SOC concentrations are anticipated to increase by 2080 given the rising mean annual air temperature and mean annual precipitation. Our results also suggested that land use change clearly influenced the change in soil C, with village/urban areas exhibiting higher SOC than cropland. To provide stakeholders with accurate soil information, it is important to understand the comprehensive impacts of land use and climate change on soil evolution; this study illustrates the value of integrating pedogenetic information in soil C simulation models.