Synergizing economic growth and carbon emission reduction in China: A path to coupling the MFLP and PLUS models for optimizing the territorial spatial functional pattern.

Carbon emissions caused by economic growth are the main cause of global warming, but controlling economic growth to reduce carbon emissions does not meet China's conditions. Therefore, how to synergize economic growth and carbon emission reduction is not only a sustainable development issue for China, but also significant for mitigating global warming. The territorial spatial functional pattern (TSFP) is the spatial carrier for coordinating economic development and carbon emissions, but how to establish the TSFP to synergize economic growth and carbon emission reduction remains unresolved. We propose a decision framework for optimizing TSFP coupled with the multi-objective fuzzy linear programming and the patch-generating land use simulation model, to provide a new path to synergize economic growth and carbon emission reduction in China. To confirm the reliability, we took Qionglai City as the demonstration. The results found a significant spatiotemporal coupling between TSFP and the synergistic effect between economic growth and carbon emission reduction (q ≥ 0.8220), which resolves the theoretical uncertainty about synergizing economic growth and carbon emission reduction through optimizing TSFP. The urban space of Qionglai City in 2025 and 2030 obtained by the decision framework was 6497.57 hm2 and 6628.72 hm2 respectively, distributed in the central and eastern regions; the rural space was 60,132.92 hm2 and 56,084.97 hm2, concentrated in the east, with a few located in the west; and the ecological space was 71,072.52 hm2 and 74,998.31 hm2, mainly located in the western and southeastern areas. Compared with 2020, the carbon emission intensity of the TSFP that realized the synergy (decoupling index was 0.25 and 0.21, respectively) was reduced by 0.7 and 4.7 tons/million yuan, respectively. Further confirming that optimizing TSFP is an effective way to synergize economic growth and carbon emission reduction, which can provide policy implications for coordinating economic growth and carbon emissions for China and even similar developing countries.

Composition of DOM along the depth gradients in the paddy field treated with crop straw for 10 years.

Crop straw return is a widely used agricultural management practice. The addition of crop straw significantly alters the pool of dissolved organic matter (DOM) in agricultural soils and plays a pivotal role in the global carbon (C) cycle, which is sensitive to climate change. The DOM concentration and composition at different soil depths could regulate the turnover and further storage of organic C in terrestrial systems. However, it is still unclear how crop straw return influences the change in DOM composition in rice paddy soils. Therefore, a field experiment was conducted in which paddy soil was amended with crop straw for 10 years. Two crop straw-addition treatments [NPK with 50% crop straw (NPK+1/2S) and NPK with 100% crop straw (NPK + S)], a conventional mineral fertilization control (NPK) and a non-fertilized control were included. Topsoil (0-20 cm) and subsoil (20-40 cm) samples were collected to investigate the soil DOM concentration and compositional structure of the profile. Soil nutrients, iron (Fe) fraction, microbial biomass carbon (MBC), and concentration and optical properties (UV-Vis and fluorescence spectra) of soil DOM were determined. Here, we found that the DOM in the topsoil was more humified than that in the subsoil. The addition of crop straw further decreased the humidification degree of DOM in the subsoil. In crop straw-amended topsoil, microbial decomposition controlled the composition of DOM and induced the formation of aromatic DOM. In the straw-treated subsoil, selective adsorption by poorly crystalline Fe(oxyhydr)oxides and microbial decomposition controlled the composition of DOM. In particular, the formation of protein-like compounds could have played a significant role in the microbial degradation of DOM in the subsoil. Overall, this work conducted a case study within long-term agricultural management to understand the changes in DOM composition along the soil profile, which would be further helpful for evaluating C cycling in agricultural ecosystems.

Circular RNA circWNK1 inhibits the progression of gastric cancer via regulating the miR-21-3p/SMAD7 axis.

Gastric cancer (GC) is a highly aggressive malignancy with limited treatment options for advanced-stage patients. Recent studies have highlighted the role of circular RNA (circRNA) as a novel regulator of cancer progression in various malignancies. However, the underlying mechanisms by which circRNA contributes to the development and progression of GC remain poorly understood. In this study, we utilized microarrays and real-time quantitative polymerase chain reaction (qRT-PCR) to identify and validate a downregulated circRNA, hsa_circ_0003251 (referred to as circWNK1), in paired GC and normal tissues. Through a series of in vitro and in vivo gain-of-function and loss-of-function assays, we demonstrated that circWNK1 exerts inhibitory effects on the proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) of GC cells. Additionally, we discovered that circWNK1 acts as a competitive endogenous RNA (ceRNA) for SMAD7 by sequestering miR-21-3p. Our findings were supported by comprehensive biological information analysis, as well as RNA pull-down, luciferase reporter gene, and western blot assays. Notably, the downregulation of circWNK1 in GC cells resulted in reduced SMAD7 expression, subsequently activating the TGF-ß signaling pathway. Collectively, our study reveals that circWNK1 functions as a tumor suppressor in GC by regulating the miR-21-3p/SMAD7-mediated TGF-ß signaling pathway. Furthermore, circWNK1 holds promise as a potential biomarker for the diagnosis and treatment of GC.

Coexistence of microplastics and Cd alters soil N transformation by affecting enzyme activity and ammonia oxidizer abundance.

Interactions between heavy metal and microplastics represent a serious threat to ecosystems and human health, but the effect of their coexistence on the soil N transformation processes is unclear. The mechanism in which metal-polluted soil reacts to additional microplastics stress and their toxicology interactions on soil N transformation were determined by investigating the dynamics of soil microbial N transformation in response to Cd stress and different doses of polythene (PE) microplastics by conducting a 14 days aerobic 15N microcosmic incubation experiment. The gross nitrification rates (n_gross) were decreased by 7.47% and 12.5% in the 1% and 2% (w/w) PE groups, respectively, through the direct effect on enzyme activity (ß-glucosidase, N-acetylglucosaminidase, and leucine-aminopeptidase) and the abundance and community composition of ammonia oxidizer. It also exerted indirect effect by reducing nitrification substrate concentrations. PE microplastics (>1% [w/w]) significantly increased the gross N immobilization rate, and this change could have been driven by C/N stoichiometry. Cd stress alone led to a rapid short-term mineralization-immobilization turnover (1.67 times of the control). However, such effect was offset when Cd coexisted with PE microplastics, possibly because Cd was directly adsorbed by PE microplastics, and/or microplastics satisfied the C demand by microorganisms under Cd stress. Our findings demonstrated that the coexistence of microplastics and Cd significantly altered soil N nitrification and immobilization, which would change the N bioavailability in soil and alter the effect N cycling on the ecological environment.

A bibliometric analysis of global research hotspots and progress on microplastics in soil‒plant systems.

Plastic pollution has become a global and persistent challenge, posing threats to ecosystems and organisms. In recent years, there has been a rapid increase in scientific research focused on understanding microplastics in the soil‒plant system. This surge is primarily driven by the direct impact of microplastics on agricultural productivity and their association with human activities. In this study, we conducted a comprehensive bibliometric analysis to provide an overview of the current research on microplastics in soil‒plant systems. We systematically analysed 192 articles and observed a significant rise in research interests since 2017. Notably, China has emerged as a leading contributor in terms of published papers, closely followed by Germany and the Netherlands. Through co-authorship network analysis, we identified 634 different institutions that participated in publishing papers in this field, with the Chinese Academy of Sciences having the most collaborations. In the co-occurrence keyword network, we identified four clusters focusing on the diversity of microplastics within the agroecosystem, transportation, and quantification of microplastics in soil, analysis of plastic contamination type and impact, and investigation of microplastic phytotoxicity. Furthermore, we identified ten research priorities, categorized into the effects of microplastics in "soil" and "plant". The research hotspots were found to be the effect of microplastics on soil physicochemical properties and the synergistic phytotoxicity of microplastics with other pollutants. Overall, this bibliometric analysis holds significant value, serving as an important reference point and offering valuable suggestions for future researchers in this rapidly advancing field.

Self-Reconstruction of Highly Degraded LiNi0.8 Co0.1 Mn0.1 O2 toward Stable Single-Crystalline Cathode.

The ever-growing demand for resources sustainability has promoted the recycle of spent lithium-ion batteries to a strategic position. Direct recycle outperforms either hydrometallurgical or pyrometallurgical approaches due to the high added value and facile treatment processes. However, the traditional direct recycling technologies are only applicable for Ni-poor/middle cathodes. Herein, spent Ni-rich LiNi0.8 Co0.1 Mn0.1 O2 (S-NCM) to performance-enhanced single-crystalline cathode materials is directly recycled using a simple but effective LiOH-NaCl molten salt. The evolution process of the Li-supplement and grain-recrystallization during regeneration is systematically investigated, and the successful recovery of the highly degraded microstructure is comprehensively proven, including significant elimination of Ni2+ and O vacancies. Beneficial from the favorable reconstructed single-crystalline particles, the regenerated NCM (R-NCM) represents remarkably enhanced structural stability, electrochemical activity, O2 and cracks suppression during charge/discharge, thus achieving the excellent performances in long-term cycling and high-rate tests. As a result, R-NCM maintains the 86.5% reversible capacity at 1 C after 200 cycles. Instructively, the present molten salt can be successfully applied for recycling spent NCMs with various Li and Ni compositions (e.g., LiNi0.5 Co0.2 Mn0.3 O2 ).

A prediction nomogram for hepatitis B virus-associated hepatocellular carcinoma.

BACKGROUND: The present study aimed to develop and validate a new nomogram for predicting the incidence of hepatocellular carcinoma (HCC) among chronic hepatitis B (CHB) patients receiving antiviral therapy from real-world data. METHODS: The nomogram was established based on a real-world retrospective study of 764 patients with HBV from October 2008 to July 2020. A predictive model for the incidence of HCC was developed by multivariable Cox regression, and a nomogram was constructed. The predictive accuracy and discriminative ability of the nomogram were assessed by the concordance index (C-index), calibration curves, and decision curve analysis (DCA). Risk group stratification was performed to assess the predictive capacity of the nomogram. The nomogram was compared to three current commonly used predictive models. RESULTS: A total of 764 patients with HBV were recruited for this study. Age, family history of HCC, alcohol consumption, and Aspartate aminotransferase-to-Platelet Ratio Index (APRI) were all independent risk predictors of HCC in CHB patients. The constructed nomogram had good discrimination with a C-index of 0.811. The calibration curve and DCA also proved the reliability and accuracy of the nomogram. Three risk groups (low, moderate, and high) with significantly different prognoses were identified (p < 0.001). The model's performance was significantly better than that of other risk models. CONCLUSIONS: The nomogram was superior in predicting HCC risk among CHB patients who received antiviral treatment. The model can be utilized in clinical practice to aid decision-making on the strategy of long-term HCC surveillance, especially for moderate- and high-risk patients.

Singlet oxygen induces cell wall thickening and stomatal density reducing by transcriptome reprogramming.

Singlet oxygen (1O2) has a very short half-life of 10-5 s; however, it is a strong oxidant that causes growth arrest and necrotic lesions on plants. Its signaling pathway remains largely unknown. The Arabidopsis flu (fluorescent) mutant accumulates a high level of 1O2 and shows drastic changes in nuclear gene expression. Only two plastid proteins, EX1 (executer 1) and EX2 (executer 2), have been identified in the singlet oxygen signaling. Here, we found that the transcription factor abscisic acid insensitive 4 (ABI4) binds the promoters of genes responsive to 1O2-signals. Inactivation of the ABI4 protein in the flu/abi4 double mutant was sufficient to compromise the changes of almost all 1O2-responsive-genes and rescued the lethal phenotype of flu grown under light/dark cycles, similar to the flu/ex1/ex2 triple mutant. In addition to cell death, we reported for the first time that 1O2 also induces cell wall thickening and stomatal development defect. Contrastingly, no apparent growth arrest was observed for the flu mutant under normal light/dim light cycles, but the cell wall thickening (doubled) and stomatal density reduction (by two-thirds) still occurred. These results offer a new idea for breeding stress tolerant plants.

The Impact of Various Organic Phosphorus Carriers on the Uptake and Use Efficiency in Barley.

Organic phosphorus (OP) is an essential component of the soil P cycle, which contributes to barley nutrition after its mineralization into inorganic phosphorus (Pi). However, the dynamics of OP utilization in the barley rhizosphere remain unclear. In this study, phytin was screened out from six OP carriers, which could reflect the difference in OP utilization between a P-inefficient genotype Baudin and a P-efficient genotype CN4027. The phosphorus utilization efficiency (PUE), root morphological traits, and expression of genes associated with P utilization were assessed under P deficiency or phytin treatments. P deficiency resulted in a greater root surface area and thicker roots. In barley fed with phytin as a P carrier, the APase activities of CN4027 were 2-3-fold lower than those of Baudin, while the phytase activities of CN4027 were 2-3-fold higher than those of Baudin. The PUE in CN4027 was mainly enhanced by activating phytase to improve the root absorption and utilization of Pi resulting from OP mineralization, while the PUE in Baudin was mainly enhanced by activating APase to improve the shoot reuse capacity. A phosphate transporter gene HvPHT1;8 regulated P transport from the roots to the shoots, while a purple acid phosphatase (PAP) family gene HvPAPhy_b contributed to the reuse of P in barley.

Biological and chemical nitrification inhibitors exhibited different effects on soil gross N nitrification rate and N2O production: a 15N microcosm study.

Nitrification inhibitors (NIs) are considered as an effective strategy for reducing nitrification rate and related environmental nitrogen (N) loss. However, whether plant-derived biological NIs had an advantage over chemical NIs in simultaneously inhibiting nitrification rate and N2O production remains unclear. Here, we conducted an aerobic 15N microcosmic incubation experiment to compare the effects of a biological NI (methyl 3-(4-hydroxyphenyl) propionate, MHPP) with three chemical NIs, 2-chloro-6-(trichloromethyl) pyridine (nitrapyrin), dicyandiamide (DCD), and 3,4-dimethylpyrazole phosphate (DMPP) on (i) gross N mineralization and nitrification rate and (ii) the relative importance of nitrification and denitrification in N2O emission in a calcareous soil. The results showed that DMPP significantly inhibited m_gross rate (P < 0.05), whereas DCD, nitrapyrin, and MHPP only numerically inhibited it. Gross N nitrification (n_gross) rates were inhibited by 9.48% in the DCD treatment to 51.5% in the nitrapyrin treatment. Chemical NIs primarily affected the amoA gene abundance of ammonia-oxidizing bacteria (AOB), whereas biological NIs affected the amoA gene abundance of ammonia-oxidizing archaea (AOA) and AOB. AOB's community composition was more susceptible to NIs than AOA, and NIs mainly targeted Nitrosospira clusters of AOB. Chemical NIs of DCD, DMPP, and nitrapyrin proportionally reduced N2O production from nitrification and denitrification. However, the biological NI MHPP stimulated short-term N2O emission and increased the proportion of N2O from denitrification. Our findings showed that the influence of NIs on gross N mineralization rate (m_gross) was dependent on the NI type. MHPP exhibited a moderate n_gross inhibitory capacity compared with the three chemical NIs. The mechanisms of chemical and biological NIs inhibiting n_gross can be partly attributed to changes in the abundance and community of ammonia oxidizers. A more comprehensive evaluation is needed to determine whether biological NIs have advantages over chemical NIs in inhibiting greenhouse gas emissions.

CSI Feedback Model Based on Multi-Source Characterization in FDD Systems.

In wireless communication, to fully utilize the spectrum and energy efficiency of the system, it is necessary to obtain the channel state information (CSI) of the link. However, in Frequency Division Duplexing (FDD) systems, CSI feedback wastes part of the spectrum resources. In order to save spectrum resources, the CSI needs to be compressed. However, many current deep-learning algorithms have complex structures and a large number of model parameters. When the computational and storage resources are limited, the large number of model parameters will decrease the accuracy of CSI feedback, which cannot meet the application requirements. In this paper, we propose a neural network-based CSI feedback model, Mix_Multi_TransNet, which considers both the spatial characteristics and temporal sequence of the channel, aiming to provide higher feedback accuracy while reducing the number of model parameters. Through experiments, it is found that Mix_Multi_TransNet achieves higher accuracy than the traditional CSI feedback network in both indoor and outdoor scenes. In the indoor scene, the NMSE gains of Mix_Multi_TransNet are 4.06 dB, 4.92 dB, 4.82 dB, and 6.47 dB for compression ratio η = 1/8, 1/16, 1/32, 1/64, respectively. In the outdoor scene, the NMSE gains of Mix_Multi_TransNet are 3.63 dB, 6.24 dB, 4.71 dB, 4.60 dB, and 2.93 dB for compression ratio η = 1/4, 1/8, 1/16, 1/32, 1/64, respectively.

The AMG model coupled with Rock-Eval® analysis accurately predicts cropland soil organic carbon dynamics in the Tuojiang River Basin, Southwest China.

Accurate soil organic carbon models are key to understand the mechanisms governing carbon sequestration in soil and to help develop targeted management strategies to carbon budget. The accuracy and reliability of soil organic carbon (SOC) models remains strongly limited by incorrect initialization of the conceptual kinetic pools and lack of stringent model evaluation using time-series datasets. Notably, due to legacy effects of management and land use change, the traditional spin-up approach for initial allocation of SOC among kinetic pools can bring substantial uncertainties in predicting the evolution of SOC stocks. The AMG model can fulfill these conditions as it is a parsimonious yet accurate SOC model using widely-available input data. In this study, we first evaluated the performance of AMGv2 before and after optimizing the potential mineralization rate (k0) of SOC stock following a leave-one-site-out cross-validation based on 24 long-term field experiments (LTEs) in the Southwest of China. Then, we used Rock-Eval® thermal analysis results as input variables in the PARTYSOC machine learning model to estimate the initial stable SOC fraction (CS/C0) for the 14 LTEs where soil samples were available. The results showed that initializing the CS/C0 ratio using PARTYSOC combined with the optimized k0 further improved the accuracy of model simulations (R2 = 0.87, RMSE = 0.25, d = 0.90). Combining average measured CS/C0 and k0 optimization across all 24 LTEs also improved the model predictive capability by 25% compared to using default parameterization, thus suggesting promising avenue for upscaling model applications at the regional level where only a few measurement data on SOC stability can be available. In conclusion, the new version of the AMG model developed in the Tuojiang River Basin context exhibits excellent performance. This result paves the way for further calibration and validation of the AMG model in a wider set of contexts, with the potential to significantly improve confidence in SOC predictions in croplands over regional scales.

Closed-loop recycling of spent lithium-ion batteries based on selective sulfidation: An unconventional approach.

The facile recycling of spent lithium-ion batteries (LIBs) has attracted considerable attention because of its great importance to environmental protection and resource utilization. A novel process is developed for cyclic utilization of spent LiNixCoyMnzO2 (NCM) batteries. The spent NCM was converted into water-soluble Li2CO3, acid-dissolved MnO, and nickel-cobalt sulfides through selective sulfidation, based on roasting condition optimization and thermodynamic calculation. More than 98 % of lithium is extracted preferentially from calcined NCM through water leaching, and over 99 % of manganese is extracted selectively from water leaching residue with H2SO4 solution of 0.4 mol/L in the absence of additional reductant. The nickel and cobalt sulfides were concentrated into the leaching residue without metal impurities. The obtained Li2CO3, MnSO4, and nickel-cobalt sulfides can be regenerated as new NCM, showing good electrochemical performance, and its discharge capacity is 169.8 mAh/g at 0.2C. After 100 cycles at 0.2C, the discharge specific capacity can still be maintained at 143.24 mAh/g, and its capacity retention ratio is as high as 92  %. An environmental assessment and economic evaluation indicate that the process is an economical and eco-friendly approach for green recycling of spent LIBs.

Biochemical and transcriptomic responses of buckwheat to polyethylene microplastics.

The ubiquity of microplastic is widely recognized as pollution. Microplastic can affect the growth performances of plants. Buckwheat is a potential model crop to investigate plant responses to hazardous materials. Still, little is known about the response of buckwheat to microplastics. Thus, this study investigated the effect and uptake of polyethylene (PE) in buckwheat plant growth by monitoring the morphological and photosynthetic merits, antioxidant systems and transcriptome analysis of gene expression. Results confirmed that the impacts of PE on buckwheat growth were dose-dependent, while the highest concentration (80 mg/L) exposure elicited significantly negative responses of buckwheat. PE can invade buckwheat roots and locate in the vascular tissues. PE exposure disturbed the processes of carbon fixation and the synthesis of ATP from ADP + Pi in buckwheat leaves. The promotion of photosynthesis under PE exposure could generate extra energy for buckwheat leaves to activate antioxidant systems by increasing the antioxidant enzyme activities at an expense of morphological merits under microplastic stresses. Further in-depth study is warranted about figuring out the interactions between microplastics and biochemical responses (i.e., photosynthesis and antioxidant systems), which have great implications for deciphering the defense mechanism of buckwheat to microplastic stresses.

Cyanotoxins dissipation in soil: Evidence from microcosm assays.

Cyanobacteria proliferate in warm, nutrient-rich environments, and release cyanotoxins into natural waters. If cyanotoxin-contaminated water is used to irrigate agricultural crops, this could expose humans and other biota to cyanotoxins. However, cyanotoxins may be degraded by the diverse microbial consortia, be adsorbed or otherwise dissipate in agricultural soil. This study investigates the disappearance and transformation of 9 cyanotoxins in controlled soil microcosms after 28 d. Six soil types were exposed to factorial combinations of light, redox conditions and microbial activity that influenced the recovery of anabaenopeptin-A (AP-A), anabaenopeptin-B (AP-B), anatoxin-a (ATX-a), cylindrospermopsin (CYN), and the microcystin (MC) congeners -LR, -LA, -LY, -LW, and -LF. Cyanotoxins estimated half-lives were from hours to several months, depending on the compound and soil conditions. Cyanotoxins were eliminated via biological reactions in aerobic and anaerobic soils, although anaerobic conditions accelerated the biological dissipation of ATX-a, CYN and APs. ATX-a was sensitive to photolytic degradation, but CYN, and MCs were not reduced through photochemical transformation. MC-LR and -LA were recovered after exposure to light, redox conditions and low microbial activity, suggesting that they persisted in extractable forms, compared to other cyanotoxins in soil. Cyanotoxin degradation products were identified using high-resolution mass spectrometry, revealing their potential degradation pathways in soil.

EMI and CLIL in Asian schools: A scoping review of empirical research between 2015 and 2022.

As the role of English as a global language grows, many governments in the Asian region have been promoting the use of English as medium of instruction (EMI) in universities and schools. In recent years, the use of EMI has been promoted in the form of Content Language Integrated Learning (CLIL) in many pre-primary, primary and secondary school systems in Asia. Because this focus on the school sector is relatively new, there seems to be relatively limited empirical research on the implementation of EMI and CLIL in primary and secondary schools in Asia. Using scoping review methodology, this paper aims to 'map the terrain' by providing an overview of the contexts and focus areas of empirical research conducted in the last seven years (2015-2022). The findings highlight gaps in the existing body of literature, including a lack of research in primary school and early childhood contexts, limited research in some countries in the Asian region, and a relatively narrow range of research focus areas, stakeholder perspectives and methodological approaches. These findings highlight areas that future researchers may consider as they investigate EMI and CLIL in school contexts in Asia.

QTL Mapping of Agronomic and Physiological Traits at the Seedling and Maturity Stages under Different Nitrogen Treatments in Barley.

Nitrogen (N) stress seriously constrains barley (Hordeum vulgare L.) production globally by influencing its growth and development. In this study, we used a recombinant inbred line (RIL) population of 121 crosses between the variety Baudin and the wild barley accession CN4027 to detect QTL for 27 traits at the seedling stage in hydroponic culture trials and 12 traits at the maturity stage in field trials both under two N treatments, aiming to uncover favorable alleles for N tolerance in wild barley. In total, eight stable QTL and seven QTL clusters were detected. Among them, the stable QTL Qtgw.sau-2H located in a 0.46 cM interval on the chromosome arm 2HL was a novel QTL specific for low N. Notably, Clusters C4 and C7 contained QTL for traits at both the seedling and maturity stages. In addition, four stable QTLs in Cluster C4 were identified. Furthermore, a gene (HORVU2Hr1G080990.1) related to grain protein in the interval of Qtgw.sau-2H was predicted. Correlation analysis and QTL mapping showed that different N treatments significantly affected agronomic and physiological traits at the seedling and maturity stages. These results provide valuable information for understanding N tolerance as well as breeding and utilizing the loci of interest in barley.

Construction of a miRNA-mRNA network related to exosomes in metastatic hepatocellular carcinoma.

Aims: This study aimed to construct a miRNA-mRNA network to elucidate the molecular mechanism of exosome function in metastatic HCC. Methods: We explored the Gene Expression Omnibus (GEO) database and then analyzed the RNAs of 50 samples to obtain differentially expressed miRNAs (DEMs) and mRNAs (DEGs) involved in the progression of metastatic HCC. Next, a miRNA-mRNA network related to exosomes in metastatic HCC was constructed on the basis of the identified DEMs and DEGs. Finally, the function of the miRNA-mRNA network was explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Immunohistochemistry was performed to validate expression of NUCKS1 in HCC specimens. Based on the immunohistochemistry, the score of the NUCKS1 expression was calculated, and the patients were divided into high- and low-expression patients, and the differences in survival between the two groups were compared. Results: Through our analysis, 149 DEMs and 60 DEGs were identified. In addition, a miRNA-mRNA network, including 23 miRNAs and 14 mRNAs, was constructed. Low expression of NUCKS1 was validated in the majority of HCCs compared with their matched adjacent cirrhosis specimens (P < 0.001), which was consistent with our result of differential expression analyses. HCC patients with low expression of NUCKS1 had shorter overall survival than those with high NUCKS1 expression (P = 0.0441). Conclusions: The novel miRNA-mRNA network will provide new insights into the underlying molecular mechanisms of exosomes in metastatic HCC. NUCKS1 might serve a potential therapeutic target to restrain the development of HCC.

A Nonlinear Relationship Between ALT Levels at Delivery and the Risk of Postpartum ALT Flares in Pregnant Women with Chronic Hepatitis B.

Background: The aim of the present study was to investigate the association between alanine aminotransferase (ALT) levels at delivery and postpartum ALT flares among women with chronic hepatitis B (CHB). Methods: Pregnant women with CHB from November 2008 to November 2017 were included in this retrospective study. Multivariable logistic regression analysis and a generalized additive model were performed to determine both linear and nonlinear relationships between ALT levels at delivery and postpartum ALT flares. Stratification analysis was performed to test for effect modifications in subgroups. Results: A total of 2643 women were enrolled. Multivariable analysis indicated that ALT levels at delivery were positively associated with postpartum ALT flares (odds ratio (OR) 1.02, 95% confidence interval (CI) 1.01-1.02, P < 0.0001). When ALT levels were converted to a categorical variable, the ORs and 95% CIs in quartiles 3 and 4 versus quartile 1 were 2.26 (1.43-3.58) and 5.34 (3.48-8.22), respectively (P for trend < 0.001). When ALT levels were dichotomized into a categorical variable according to clinical cutoffs (40 U/L or 19 U/L), the ORs and 95% CIs were 3.06 (2.05-4.57) and 3.31 (2.53-4.35), respectively (P < 0.0001). The ALT level at delivery was also found to have a nonlinear relationship with postpartum ALT flares. The relationship followed an inverted U-shaped curve. Conclusions: The ALT level at delivery was positively correlated with postpartum ALT flares in women with CHB when the ALT level was less than 182.8 U/L. The ALT cutoff (19 U/L) at delivery was more sensitive to predict the risk of ALT flares postpartum.

Incorporating agricultural practices in digital mapping improves prediction of cropland soil organic carbon content: The case of the Tuojiang River Basin.

Accurate mapping of soil organic carbon (SOC) in cropland is essential for improving soil management in agriculture and assessing the potential of different strategies aiming at climate change mitigation. Cropland management practices have large impacts on agricultural soils, but have rarely been considered in previous SOC mapping work. In this study, cropland management practices including carbon input (CI), length of cultivation (LC), and irrigation (Irri) were incorporated as agricultural management covariates and integrated with natural variables to predict the spatial distribution of SOC using the Extreme Gradient Boosting (XGBoost) model. Additionally, we evaluated the performance of incorporating agricultural management practice variables in the prediction of cropland topsoil SOC. A case study was carried out in a traditional agricultural area in the Tuojiang River Basin, China. We found that CI was the most important environmental covariate for predicting cropland SOC. Adding cropland management practices to natural variables improved prediction accuracy, with the coefficient of determination (R2), the root mean squared error (RMSE) and Lin's Concordance Correlation Coefficient (LCCC) improving by 16.67%, 17.75% and 5.62%, respectively. Our results highlight the effectiveness of incorporating agricultural management practice information into SOC prediction models. We conclude that the construction of spatio-temporal database of agricultural management practices derived from inventories is a research priority to improve the reliability of SOC model prediction.