"Bowling Collision Effect" of CoMo6 Polyoxometalate Units Enables Wide Temperature Range from -20 to 60 °C and Dendrite Mitigation Li-S Batteries.

To improve the performance of Lithium-Sulfur (Li-S) batteries, the reaction catalysts of lithium polysulfides (LiPSs) reactions should have the characteristics of large surface area, efficient atomic utilization, high conductivity, small size, good stability, and strong adjustability. Herein, Anderson-type polyoxometalate ([TMMo6O24]n-, TM = Co, Ni, Fe, represented by TMMo6 POMs) are used as the modified materials for Li-S battery separator. By customizing the central metal atoms, this work gains insights into the layer-by-layer electron transfer mechanism between TMMo6 units and LiPSs, similar to the collision effect of a bowling ball. Theoretical analysis and in situ experimental characterization show that the changes of CoMo6 units with moderate binding energy and lowest Gibbs free energy result in the formation of robust polar bonds and prolonged S─S bonds after adsorption. Hence, the representative Li-S battery with CoMo6 and graphene composite modified separator has a high initial capacity of 1588.6 mA h g-1 at 0.2 C, excellent cycle performance of more than 3000 cycles at 5 C, and uniform Li+ transport over 1900 h. More importantly, this work has revealed the inherent contradiction between the kinetics and thermodynamics, achieving a stable cycle in the temperature range of -20 to 60 °C.

The dynamic-static dual-branch deep neural network for urban speeding hotspot identification using street view image data.

The visual information regarding the road environment can influence drivers' perception and judgment, often resulting in frequent speeding incidents. Identifying speeding hotspots in cities can prevent potential speeding incidents, thereby improving traffic safety levels. We propose the Dual-Branch Contextual Dynamic-Static Feature Fusion Network based on static panoramic images and dynamically changing sequence data, aiming to capture global features in the macro scene of the area and dynamically changing information in the micro view for a more accurate urban speeding hotspot area identification. For the static branch, we propose the Multi-scale Contextual Feature Aggregation Network for learning global spatial contextual association information. In the dynamic branch, we construct the Multi-view Dynamic Feature Fusion Network to capture the dynamically changing features of a scene from a continuous sequence of street view images. Additionally, we designed the Dynamic-Static Feature Correlation Fusion Structure to correlate and fuse dynamic and static features. The experimental results show that the model has good performance, and the overall recognition accuracy reaches 99.4%. The ablation experiments show that the recognition effect after the fusion of dynamic and static features is better than that of static and dynamic branches. The proposed model also shows better performance than other deep learning models. In addition, we combine image processing methods and different Class Activation Mapping (CAM) methods to extract speeding frequency visual features from the model perception results. The results show that more accurate speeding frequency features can be obtained by using LayerCAM and GradCAM-Plus for static global scenes and dynamic local sequences, respectively. In the static global scene, the speeding frequency features are mainly concentrated on the buildings and green layout on both sides of the road, while in the dynamic scene, the speeding frequency features shift with the scene changes and are mainly concentrated on the dynamically changing transition areas of greenery, roads, and surrounding buildings. The code and model used for identifying hotspots of urban traffic accidents in this study are available for access: https://github.com/gwt-ZJU/DCDSFF-Net.

Akkermansia muciniphila ameliorates colonic injury in mice with DSS-induced acute colitis by blocking macrophage pro-inflammatory phenotype switching via the HDAC5/DAB2 axis.

Akkermansia muciniphila (A. muciniphila), a probiotic, has been linked to macrophage phenotypic polarization in different diseases. However, the role and mechanisms of A. muciniphila in regulating macrophage during ulcerative colitis (UC) are not clear. This research aimed to examine the impact of A. muciniphila on dextran sulfate sodium (DSS)-induced acute colitis and elucidate the underlying mechanism related to macrophage phenotypic polarization. A. muciniphila inhibited weight loss, increased disease activity index, and ameliorated inflammatory injury in colonic tissues in mice induced with DSS. Furthermore, A. muciniphila reduced macrophage M1 polarization and ameliorated epithelial barrier damage in colonic tissues of DSS-induced mice through inhibition of histone deacetylase 5 (HDAC5). In contrast, the effect of A. muciniphila was compromised by HDAC5 overexpression. HDAC5 deacetylated H3K9ac modification of the disabled homolog 2 (DAB2) promoter, which led to repressed DAB2 expression. DAB2 overexpression blocked HDAC5-induced pro-inflammatory polarization of macrophages, whereas knockdown of DAB2 resulted in the loss of effects of A. muciniphila against colonic injury in DSS-induced mice. Taken together, A. muciniphila-induced loss of HDAC5 hampered the deacetylation of DAB2 and enhanced the expression of DAB2. Our findings propose that A. muciniphila may be a possible probiotic agent for alleviating DSS-induced acute colitis.

Effects of grazing exclusion on soil microbial diversity and its functionality in grasslands: a meta-analysis.

Grazing exclusion (GE) is considered an effective strategy for restoring the degradation of overgrazed grasslands on the global scale. Soil microbial diversity plays a crucial role in supporting multiple ecosystem functions (multifunctionality) in grassland ecosystems. However, the impact of grazing exclusion on soil microbial diversity remains uncertain. Here, we conducted a meta-analysis using a dataset comprising 246 paired observations from 46 peer-reviewed papers to estimate how GE affects microbial diversity and how these effects vary with climatic regions, grassland types, and GE duration ranging from 1 to 64 years. Meanwhile, we explored the relationship between microbial diversity and its functionality under grazing exclusion. Overall, grazing exclusion significantly increased microbial Shannon (1.9%) and microbial richness (4.9%) compared to grazing group. For microbial groups, GE significantly increased fungal richness (8.6%) and bacterial richness (5.3%), but decreased specific microbial richness (-11.9%). The responses of microbial Shannon to GE varied among climatic regions, grassland types, and GE duration. Specifically, GE increased microbial diversity in in arid, semi-arid, and dry sub-humid regions, but decreased it in humid regions. Moreover, GE significantly increased microbial Shannon in semidesert grasslands (5.9%) and alpine grasslands (3.0%), but not in temperate grasslands. Long-term (>20 year) GE had greater effects on microbial diversity (8.0% for Shannon and 6.7% for richness) compared to short-term (<10 year) GE (-0.8% and 2.4%). Furthermore, grazing exclusion significantly increased multifunctionality, and both microbial and plant Shannon positively correlated with multifunctionality. Overall, our findings emphasize the importance of considering climate, GE duration, and grassland type for biodiversity conservation and sustainable grassland ecosystem functions.

Functional Optical Fiber Sensors Detecting Imperceptible Physical/Chemical Changes for Smart Batteries.

The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist. Now the battery is still a "black box", thus requiring a deep understanding of its internal state. The battery should "sense its internal physical/chemical conditions", which puts strict requirements on embedded sensing parts. This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed, focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition, electrolyte degradation, electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution. The paper contributes to understanding how to use optical fiber sensors to achieve "real" and "embedded" monitoring. Through the inherent advantages of the advanced optical fiber sensor, it helps clarify the battery internal state and reaction mechanism, aiding in the establishment of more detailed models. These advancements can promote the development of smart batteries, with significant importance lying in essentially promoting the improvement of system consistency. Furthermore, with the help of smart batteries in the future, the importance of consistency can be weakened or even eliminated. The application of advanced optical fiber sensors helps comprehensively improve the battery quality, reliability, and life.

Experimental study of the fast scintillating behavior of ZnO:Ga crystal under MeV electron beam.

An experimental study on the scintillating behavior of ZnO:Ga crystals was conducted using a 7-MeV electron accelerator. The ZnO:Ga crystals were grown using both hydrothermal and chemical vapor transport methods. One of the ZnO:Ga crystals grown via the hydrothermal method exhibited a 1.5-ns afterglow time when excited by an MeV electron beam. The ultra-short scintillation was captured using both an ultrafast streak camera and a framed camera. The experimental results also confirm its potential for diagnosing electron beam trains with a repetition rate of hundreds of MHz.

Small extracellular vesicles-mediated cellular interactions between tumor cells and tumor-associated macrophages: Implication for immunotherapy.

The tumor microenvironment consists of cancer cells and various stromal cells, including macrophages, which exhibit diverse phenotypes with either pro-inflammatory (M1) or anti-inflammatory (M2) effects. The interaction between cancer cells and macrophages plays a crucial role in tumor progression. Small extracellular vesicles (sEVs), which facilitate intercellular communication, are known to play a vital role in this process. This review provides a comprehensive summary of how sEVs derived from cancer cells, containing miRNAs, lncRNAs, proteins, and lipids, can influence macrophage polarization. Additionally, we discuss the impact of macrophage-secreted sEVs on tumor malignant transformation, including effects on proliferation, metastasis, angiogenesis, chemoresistance, and immune escape. Furthermore, we address the therapeutic advancements and current challenges associated with macrophage-associated sEVs, along with potential solutions.

Positive Effects of Organic Amendments on Soil Microbes and Their Functionality in Agro-Ecosystems.

Soil microbial characteristics are considered to be an index for soil quality evaluation. It is generally believed that organic amendments replacing chemical fertilizers have positive effects on changing microbial activity and community structure. However, their effects on different agro-ecosystems on a global scale and their differences in different environmental conditions and experimental durations are unclear. This study performed a meta-analysis based on 94 studies with 204 observations to evaluate the overall effects and their differences in different experimental conditions and duration. The results indicated that compared to chemical fertilizer, organic amendments significantly increased total microbial biomass, bacterial biomass, fungal biomass, Gram-positive bacterial biomass and Gram-negative bacterial biomass, and had no effect on the ratio of fungi to bacteria and ratio of Gram-positive bacteria to Gram-negative bacteria. Meanwhile, land use type, mean annual precipitation and soil initial pH are essential factors affecting microbial activity response. Organic-amendment-induced shifts in microbial biomass can be predominantly explained by soil C and nutrient availability changes. Additionally, we observed positive relationships between microbial functionality and microbial biomass, suggesting that organic-amendment-induced changes in microbial activities improved soil microbial functionality.

Meta-Analysis of Organic Fertilization Effects on Soil Bacterial Diversity and Community Composition in Agroecosystems.

Application of organic fertilizers or their combination with chemical fertilizers is a feasible practice for improving soil fertility and reducing soil degradation in agroecosystems, and these regulations are mainly mediated though soil microbial communities. Despite bacteria ranking among the most abundant and diverse groups of soil microorganisms, the effects of long-term organic fertilization (OF) and chemical-organic fertilization (COF) on soil bacterial diversity and community composition remain unclear. In this study, we conducted a meta-analysis and demonstrated that OF had no significant effect on bacterial alpha diversity. Application of chemical fertilizer and crop residue significantly decreased bacterial Richness index. Both OF and COF significantly altered bacterial community structure, with these changes being predominately attributed to shifts in soil pH. For bacterial phyla, both OF and COF significantly increased the relative abundance of Proteobacteria and Bacteroidetes, suggesting that OF and COF may cause the enrichment of copiotrophic taxa. In addition, COF significantly increased the relative abundance of Gammaproteobacteria but decreased the relative abundance of Acidobacteria. Overall, our results suggest that organic and chemical-organic fertilization can effectively maintain bacterial diversity and enhance soil fertility in agroecosystems, and the alteration of soil bacterial community structure is closely intertwined with soil pH.

A critical role for CaMKII in behavioral timescale synaptic plasticity in hippocampal CA1 pyramidal neurons.

Behavioral timescale synaptic plasticity (BTSP) is a type of non-Hebbian synaptic plasticity reported to underlie place field formation. Despite this important function, the molecular mechanisms underlying BTSP are poorly understood. The α-calcium-calmodulin-dependent protein kinase II (αCaMKII) is activated by synaptic transmission-mediated calcium influx, and its subsequent phosphorylation is central to synaptic plasticity. Because the activity of αCaMKII is known to outlast the event triggering phosphorylation, we hypothesized that it could mediate the extended timescale of BTSP. To examine the role of αCaMKII in BTSP, we performed whole-cell in vivo and in vitro recordings in CA1 pyramidal neurons from mice engineered with a point mutation at the autophosphorylation site (T286A) causing accelerated signaling kinetics. Here, we demonstrate a profound deficit in synaptic plasticity, strongly suggesting that αCaMKII signaling is required for BTSP. This study elucidates part of the molecular mechanism of BTSP and provides insight into the function of αCaMKII in place cell formation and ultimately learning and memory.

Log odds of positive lymph nodes as a novel prognostic predictor for gastric cancer: a systematic review and meta-analysis.

BACKGROUND: We conducted a systematic review and meta-analysis to summarize the predictive and prognostic ability of the log odds of positive lymph nodes (LODDS) staging system and compare it with pathological N (pN) classification and the ratio-based lymph node system (rN) for the overall survival (OS) of gastric cancer (GC). METHODS: Through a systematic review till March 7, 2022, we identified population-based studies that reported the prognostic effects of LODDS in patients with GC. We compare the predictive effectiveness of the LODDS staging system with that of the rN and pN classification systems for the OS of GC. RESULTS: Twelve studies comprising 20,312 patients were included in this systematic review and meta-analysis. The results showed that LODDS1, LODDS2, LODDS3, and LODDS4 in GC patients were correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.62, 95% CI (1.42, 1.85); LODDS2 vs. LODDS0: HR = 2.47, 95% CI (2.02, 3.03); LODDS3 vs. LODDS0: HR = 3.15, 95% CI (2.50, 3.97); LODDS4 vs. LODDS0: HR = 4.55, 95% CI (3.29, 6.29)). Additionally, significant differences in survival were observed among patients with different LODDS classifications (all P-values were < 0.001) with the same rN and pN classifications. Meanwhile, for patients with different pN or rN classifications with the same LODDS classification, prognosis was highly similar. CONCLUSION: The findings show that LODDS is correlated with the prognosis of GC patients and is superior to the pN and rN classifications for prognostic assessment.

Development and validation of a ligand-receptor pairs signature to predict outcome and provide a therapeutic strategy in gastric cancer.

BACKGROUND: An important factor in tumor development and progression is the tumor microenvironment (TME), which is heterogeneous. Previous studies have mainly investigated the expression profile and prognostic values of genes in gastric cancer (GC) at the cell population level but neglected the interactions and heterogeneity between cells. METHODS: The pattern of ligand-receptor (LR) interactions was delineated on a scRNA-seq dataset containing 44,953 cells from nine GC patients and a fourth bulk RNA-seq dataset including data from 1159 GC patients. We then constructed an LR.Score scoring model to comprehensively evaluate the influence of LR-pairs on the TME, overall survival, and immunotherapy response in GC patients from several cohorts. RESULTS: Cell communication network among 13 cell types was constructed based on the LR-pairs. We proposed a new molecular subtyping model for GC based on the LR-pairs and revealed the differences in prognosis, pathophysiologic features, mutation characteristics, function enrichment, and immunological characteristics among the three subtypes. Finally, an LR.Score model based on LR-pairs was developed and validated on several datasets. CONCLUSIONS: Based on the selected LR-pairs, we successfully constructed a novel prediction model and observed its well performance on molecular subtyping, target and pathway screening, prognosis judging, and immunotherapy response predicting.

Developing Insoluble Polyoxometalate Clusters to Bridge Homogeneous and Heterogeneous Water Oxidation Photocatalysis.

Cluster catalysts are attractive for their atomically precise structures, defined compositions, tunable coordination environments, uniform active sites, and their ability to transfer multiple electrons, but they suffer from poor stability and recyclability. Here, we report a general approach to the direct insolubilization of a water soluble polyoxometalate (POM) [{(B-α-PW9 O34 )Co3 (OH)(H2 O)2 (O3 PC(O)-(C3 H6 NH3 )PO3 )}2 Co]14- (Co7 ) and formation of a series of POM-based solid catalysts with the counter-cations Ag+ , Cs+ , Sr2+ , Ba2+ , Pb2+ , Y3+ , and Ce3+ . They exhibit improved catalytic activities for visible-light-driven water oxidation following the trend CsCo7 >SrCo7 >AgCo7 >CeIII Co7 >BaCo7 >YCo7 >PbCo7 . While CsCo7 exhibits mainly homogeneous catalysis, the others are predominantly heterogeneous catalysts. An optimal oxygen yield of 41.3 % and a high apparent quantum yield (AQY) of 30.6 % for SrCo7 is obtained, which is comparable to that of the parent homogeneous POM. Band gap structures, UV/Vis spectra, and real-time laser flash photolysis experiments collectively suggest that easier electron transfer from the solid POM catalyst to the photosensitizer promotes photocatalytic water oxidation performance. These solid POM catalysts exhibit good stability, which is directly confirmed by a combination of Fourier-transform infrared spectroscopy, electron microscopy, X-ray diffraction patterns, Raman spectroscopy, X-ray photoelectron spectroscopy, five cycles of tests, and poisoning experiments.

Prognostic role and immune infiltration characteristics of EI24 in multiple cancer types.

BACKGROUND: The autophagy-associated transmembrane protein EI24 is associated with cancer growth and patient survival. We aimed to explore the prognostic role and immune infiltration characteristics of EI24 at a pan-cancer level. METHODS: We collected data from multiple databases to explore the expression and prognostic role of EI24 in various cancers. Correlations between EI24 expression and DNA methylation, RNA modification, tumor mutation burden (TMB), microsatellite instability (MSI), immune moderator, immune checkpoint-related genes, the tumor immune microenvironment, and clinicopathological characteristics were analyzed. Finally, immunohistochemistry and western blotting were performed to validate the protein levels of EI24 in different tumors. RESULTS: Differential expression of EI24 was observed in most cancer types compared to non-cancerous tissues. EI24 showed a significant association with prognosis and may represent a new indicator of prognosis in patients with cancer. In most cancers, EI24 is closely associated with tumor immunity and interacts with various immune cells. Moreover, significant correlations were observed between EI24 expression and RNA modification, TMB, MSI, immune moderators, and immune checkpoint-related genes. CONCLUSION: This study provides new insights into the functions and clinical value of EI24 in different tumors and suggests that EI24 may serve as a promising biomarker or therapeutic target for cancer management.

Development and validation of an RBP gene signature for prognosis prediction in colorectal cancer based on WGCNA.

BACKGROUND: RNA binding proteins (RBPs) have been implicated in oncogenesis and progression in various cancers. However, the potential value of RBPs as prognostic indicators and therapeutic targets in colorectal cancer (CRC) requires further investigation. METHODS: Four thousand eighty two RBPs were collected from literature. The weighted gene co-expression network analysis (WGCNA) was performed to identify prognosis-related RBP gene modules based on the data attained from the TCGA cohorts. LASSO algorithm was conducted to establish a prognostic risk model, and the validity of the proposed model was confirmed by an independent GEO dataset. Functional enrichment analysis was performed to reveal the potential biological functions and pathways of the signature and to estimate tumor immune infiltration. Potential therapeutic compounds were inferred utilizing CMap database. Expressions of hub genes were further verified through the Human Protein Atlas (HPA) database and RT-qPCR. RESULTS: One thousand seven hundred thirty four RBPs were differently expressed in CRC samples and 4 gene modules remarkably linked to the prognosis were identified, based on which a 12-gene signature was established for prognosis prediction. Multivariate Cox analysis suggested this signature was an independent predicting factor of overall survival (P < 0.001; HR:3.682; CI:2.377-5.705) and ROC curves indicated it has an effective predictive performance (1-year AUC: 0.653; 3-year AUC:0.673; 5-year AUC: 0.777). GSEA indicated that high risk score was correlated with several cancer-related pathways, including cytokine-cytokine receptor cross talk, ECM receptor cross talk, HEDGEHOG signaling cascade and JAK/STAT signaling cascade. ssGSEA analysis exhibited a significant correlation between immune status and the risk signature. Noscapine and clofazimine were screened as potential drugs for CRC patients with high-risk scores. TDRD5 and GPC1 were identified as hub genes and their expression were validated in 15 pairs of surgically resected CRC tissues. CONCLUSION: Our research provides a depth insight of RBPs' role in CRC and the proposed signature are helpful to the personalized treatment and prognostic judgement.

Effects of marital status on survival of retroperitoneal liposarcomas stratified by age and sex: A population-based study.

BACKGROUND: Previous studies have shown that marital status is associated with survival in patients with a variety of cancer types, including lung cancer, prostate cancer, and bladder cancer. However, to date, the impact of marital status on the survival of patients with retroperitoneal liposarcomas (RPLs) has not been established. METHODS: A total of 1211 eligible patients diagnosed with RPLs were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The relationships between marital status and survival in patients with RPLs were assessed. Patients were stratified by age to determine whether an association exists between marital status and age. We also probed the association between marital status and survival in males and females. RESULTS: Our findings suggest that divorced, separated, or widowed patients have more advanced cancer stages, and more of these patients do not undergo surgery. Meanwhile, divorced, separated, or widowed patients have worse survival outcomes than married patients (overall survival (OS): HR = 1.66 (95% CI, 1.12, 2.46)); cancer-specific survival (CSS): HR = 1.90 (95% CI, 1.13, 3.19)). OS does not differ between single patients and married patients (HR = 1.21 [95% CI, 0.81, 1.81]) or CSS (HR = 1.36 [95% CI, 0.80, 2.29]). In addition, these results demonstrate that being divorced, separated, or widowed can play a significant detrimental role in mortality in older and female patients. CONCLUSION: Married patients have earlier disease stages at diagnosis and better survival outcomes than divorced, separated, or widowed patients with RPLs. In addition, this effect is especially pronounced in older people and females.

Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study.

Background: Colorectal gastrointestinal stromal tumors (GISTs), mesenchymal malignancy, only accounts for about 6% of GISTs, but prognosis is generally poor. Given the rarity of colorectal GISTs, the prognostic values of clinicopathological features in the patients remain unclear. Nomograms can provide a visual interface to help calculate the predicted probability of a patient meeting a specific clinical endpoint and communicate it to the patient. Methods: We included a total of 448 patients with colorectal GISTs diagnosed between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. For nomogram construction and validation, patients in the SEER database were divided randomly into the training cohort and internal validation cohort at a ratio of 7:3, while 44 patients with colorectal GISTs from our hospital patient data set between 2010 to 2016 served as the external validation cohort. The OS curves were drawn using the Kaplan-Meier method and assessed using the log-rank test. And, Fine and Gray's competing-risks regression models were conducted to assess CSS. We performed univariate and multivariate analyses to select prognostic factors for survival time and constructed a predictive nomogram based on the results of the multivariate analysis. Results: Through univariate and multivariate analyses, it is found that age, primary site, SEER stage, surgery, and tumor size constitute significant risk factors for OS, and age, primary site, histological grade, SEER stage, American Joint Committee for Cancer (AJCC) stage, surgery, and tumor size constitute risk factors for CSS. We found that the nomogram provided a good assessment of OS and CSS at 1-, 3- and 5- year in patients with colorectal GISTs. The calibration plots for the training, internal validation and external validation cohorts at 1-, 3- and 5- year OS and CSS indicated that the predicted survival rates closely correspond to the actual survival rates. Conclusion: We constructed and validated an unprecedented nomogram to predict OS and CSS in patients with colorectal GISTs. The nomogram had the potential as a clinically predictive tool for colorectal GISTs prognosis, and can be used as a potential, objective and additional tool for clinicians in predicting the prognosis of colorectal GISTs patients worldwide. Clinicians could wield the nomogram to accurately evaluate patients' OS and CSS, identify high-risk patients, and provide a baseline to optimize treatment plans.

Divergent responses of cropland soil organic carbon to warming across the Sichuan Basin of China.

Cropland soils are considered to have the potential to sequester carbon (C). Warming can increase soil organic C (SOC) by enhancing primary production, but it can also cause carbon release from soils. However, the role of warming in governing cropland SOC dynamics over broad geographic scales remains poorly understood. Using over 4000 soil samples collected in the 1980s and 2010s across the Sichuan Basin of China, this study assessed the warming-induced cropland SOC change and the correlations with precipitation, cropland type and soil type. Results showed mean SOC content increased from 11.10 to 13.85 g C kg-1. Larger SOC increments were observed under drier conditions (precipitation < 1050 mm, dryland and paddy-dryland rotation cropland), which were 1.67-2.23 times higher than under wetter conditions (precipitation > 1050 mm and paddy fields). Despite the significant associations of SOC increment with crop productivity, precipitation, fertilization, cropland type and soil type, warming also acted as one of major contributors to cropland SOC change. The SOC increment changed parabolically with the rise in temperature increase rate under relatively drier conditions, while temperature increase had no impact on cropland SOC increment under wetter conditions. Meanwhile, the patterns of the parabolical relationship varied with soil types in drylands, where the threshold of temperature increase rate, the point at which the SOC increment switched from increasing to decreasing with warming, was lower for clayey soils (Ali-Perudic Argosols) than for sandy soils (Purpli-Udic Cambosols). These results illustrate divergent responses of cropland SOC to warming under different environments, which were contingent on water conditions and soil types. Our findings emphasize the importance of formulating appropriate field water management for sustainable C sequestration and the necessity of incorporating environment-specific mechanisms in Earth system models for better understanding of the soil C-climate feedback in complex environments.