Search

Electroreduction of Cr(VI) coupled with in-situ precipitation of Cr(III) on the cathode is a promising method for removing Cr(VI) from wastewaters. However, the influence of coexisting anions in wastewaters on the electrochemical removal process remains unclear. This study investigated the impact of common inorganic anions, including nitrate (NO 3 - ), chloride (Cl - ), phosphate (PO 4 3- ) and sulfate (SO 4 2- ), on the electrochemical removal processes of Cr(VI). The results indicated that HCrO 4 - was directly electrochemically reduced to Cr 3+ , and the OH - generated through electro-mediated water reduction could complex with Cr 3+ , thereby transforming Cr 3+ into chromium hydroxide (Cr(OH) 3 ) coated at cathode. Coexisting anions would partially penetrate the alkaline Cr(III) complexes, inhibiting the formation of Cr(OH) 3 passivation layer and promoting the electroreduction of Cr(VI), whose penetration ability followed the order of SO 4 2-  > PO 4 3-  > Cl -  > NO 3 - . Both the inhibitory effect on Cr(III) precipitation and promoting effect on Cr(VI) reduction were intensified with increasing concentrations of these anions in the range of 1-100 mmol L -1 . Accordingly, after electrolysis of 10 mg L -1 Cr(VI) at an initial pH of 3.0 and -0.2 V (vs. Ag/AgCl), the highest electrochemical reduction ratio of Cr(VI) (99.9%) was achieved in the presence of 100 mmol L -1 SO 4 2- , while the total Cr removal ratio was minimal (3.3%). In contrast, the presence of NO 3 - at 1 mmol L -1 resulted in a nearly lowest reduction ratio of Cr(VI) (92.9%), with the maximum total Cr removal ratio (92.8%). These findings provide new insights into the electrochemical removal mechanisms of Cr(VI) in complex solution environments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Urban greenspaces typically refer to urban wetland, urban forest and urban turfgrass. They play a critical role in carbon sequestration by absorbing carbon from the atmosphere; however, their capacity to retain and store carbon in the form of soil organic carbon (SOC) varies significantly. This study provides a systematic analysis and review on the capacity of different urban greenspace types in retaining and storing SOC in 30 cm soil depth on a global scale. Data came from 78 publications on the subject of SOC stocks, covering different countries and climate zones. Overall, urban greenspace types exerted significant influences on the spatial pattern of SOC stocks, with the highest value of 18.86 ± 11.57 kg m -2 (mean ± standard deviation) in urban wetland, followed by urban forest (6.50 ± 3.65 kg m -2 ), while the lowest mean value of 4.24 ± 3.28 kg m -2 was recorded in urban turfgrass soil. Soil organic carbon stocks in each urban greenspace type were significantly affected by climate zones, management/environmental settings, and selected soil properties (i.e. soil bulk density, pH and clay content). Furthermore, our analysis showed a significantly negative correlation between SOC stocks and human footprint in urban wetland, but a significantly positive relationship in urban forest and urban turfgrass. A positive correlation between SOC stocks and human footprint indicates that increased human activity and development can enhance SOC stocks through effective management and green infrastructure. Conversely, a negative correlation suggests that improper management of human activities can degrade SOC stocks. This highlights the need for sustainable practices to maintain or enhance SOC accumulation in urban greenspaces., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Over the past decade, there has been a growing emphasis on investigating the role of immunotherapy in cancer treatment. However, it faces challenges such as limited efficacy, a diminished response rate, and serious adverse effects. Nanozymes, a subset of nanomaterials, demonstrate boundless potential in cancer catalytic therapy for their tunable activity, enhanced stability, and cost-effectiveness. By selectively targeting the metabolic vulnerabilities of tumors, they can effectively intensify the destruction of tumor cells and promote the release of antigenic substances, thereby eliciting immune clearance responses and impeding tumor progression. Combined with other therapies, they synergistically enhance the efficacy of immunotherapy. Hence, a large number of metabolism-regulating nanozymes with synergistic immunotherapeutic effects have been developed. This review summarizes recent advancements in cancer immunotherapy facilitated by nanozymes, focusing on engineering nanozymes to potentiate antitumor immune responses by disturbing tumor metabolism and performing synergistic treatment. The challenges and prospects in this field are outlined. We aim to provide guidance for nanozyme-mediated immunotherapy and pave the way for achieving durable tumor eradication.

As the global population ages, bone diseases have become increasingly prevalent in clinical settings. These conditions often involve detrimental factors such as infection, inflammation, and oxidative stress that disrupt bone homeostasis. Addressing these disorders requires exogenous strategies to regulate the osteogenic microenvironment (OME). The exogenous regulation of OME can be divided into four processes: induction, modulation, protection, and support, each serving a specific purpose. To this end, metal-organic frameworks (MOFs) are an emerging focus in nanomedicine, which show tremendous potential due to their superior delivery capability. MOFs play numerous roles in OME regulation such as metal ion donors, drug carriers, nanozymes, and photosensitizers, which have been extensively explored in recent studies. This review presents a comprehensive introduction to the exogenous regulation of OME by MOF-based nanomaterials. By discussing various functional MOF composites, this work aims to inspire and guide the creation of sophisticated and efficient nanomaterials for bone disease management., (© 2024 Wiley‐VCH GmbH.)

Van der Waals (vdW) interfaces can be formed via layer stacking regardless of the lattice constant or symmetry of the individual building blocks. Herein, we constructed a vdW interface of layered Ta 2 NiS 5 and CrOCl, which exhibited remarkably enhanced in-plane anisotropy via polarized Raman spectroscopy and electrical transport measurements. Compared with pristine Ta 2 NiS 5 , the anisotropy ratio of the Raman intensities for the B 2g , 2 A g , and 3 A g modes increased in the heterostructure. More importantly, the anisotropy ratios of conductivity and mobility in the heterostructure increased by one order of magnitude. Specifically speaking, the conductivity ratio changed from ~2.1 (Ta 2 NiS 5 ) to ~15 (Ta 2 NiS 5 /CrOCl), while the mobility ratio changed from ~2.7 (Ta 2 NiS 5 ) to ~32 (Ta 2 NiS 5 /CrOCl). Such prominent enhancement may be attributed to the symmetry reduction caused by lattice mismatch at the heterostructure interface and the introduction of strain into the Ta 2 NiS 5 . Our research provides a new perspective for enhancing artificial anisotropy physics and offers feasible guidance for future functionalized electronic devices.

Polyetheretherketone (PEEK) has emerged as a highly promising orthopedic implantation material due to its elastic modulus which is comparable to that of natural bone. This polymer exhibits impressive properties for bone implantation such as corrosion resistance, fatigue resistance, self-lubrication and chemical stability. Significantly, compared to metal-based implants, PEEK implants have mechanical properties that are closer to natural bone, which can mitigate the "stress shielding" effect in bone implantation. Nevertheless, PEEK is incapable of inducing osteogenesis due to its bio-inert molecular structure, thereby hindering the osseointegration process. To optimize the clinical application of PEEK, researchers have been working on promoting its bioactivity and endowing this polymer with beneficial properties, such as antibacterial, anti-inflammatory, anti-tumor, and angiogenesis-promoting capabilities. Considering the significant growth of research on PEEK implants over the past 5 years, this review aims to present a timely update on PEEK's modification methods. By highlighting the latest advancements in PEEK modification, we hope to provide guidance and inspiration for researchers in developing the next generation bone implants and optimizing their clinical applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The modeling and mapping of soil organic carbon (SOC) has advanced through the rapid growth of Earth observation data (e.g., Sentinel) collection and the advent of appropriate tools such as the Google Earth Engine (GEE). However, the effects of differing optical and radar sensors on SOC prediction models remain uncertain. This research aims to investigate the effects of different optical and radar sensors (Sentinel-1/2/3 and ALOS-2) on SOC prediction models based on long-term satellite observations on the GEE platform. We also evaluate the relative impact of four synthetic aperture radar (SAR) acquisition configurations (polarization mode, band frequency, orbital direction and time window) on SOC mapping with multiband SAR data from Spain. Twelve experiments involving different satellite data configurations, combined with 4027 soil samples, were used for building SOC random forest regression models. The results show that the synthesis mode and choice of satellite images, as well as the SAR acquisition configurations, influenced the model accuracy to varying degrees. Models based on SAR data involving cross-polarization, multiple time periods and "ASCENDING" orbits outperformed those involving copolarization, a single time period and "DESCENDING" orbits. Moreover, combining information from different orbital directions and polarization modes improved the soil prediction models. Among the SOC models based on long-term satellite observations, the Sentinel-3-based models (R 2  = 0.40) performed the best, while the ALOS-2-based model performed the worst. In addition, the predictive performance of MSI/Sentinel-2 (R 2  = 0.35) was comparable with that of SAR/Sentinel-1 (R 2  = 0.35); however, the combination (R 2  = 0.39) of the two improved the model performance. All the predicted maps involving Sentinel satellites had similar spatial patterns that were higher in northwest Spain and lower in the south. Overall, this study provides insights into the effects of different optical and radar sensors and radar system parameters on soil prediction models and improves our understanding of the potential of Sentinels in developing soil carbon mapping., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Hepatitis B virus (HBV) infection is a major global health problem that puts people at high risk of death from cirrhosis and liver cancer. The presence of covalently closed circular DNA (cccDNA) in infected cells is considered to be the main obstacle to curing chronic hepatitis B. At present, the cccDNA cannot be completely eliminated by standard treatments. There is an urgent need to develop drugs or therapies that can reduce HBV cccDNA levels in infected cells. We summarize the discovery and optimization of small molecules that target cccDNA synthesis and degradation. These compounds are cccDNA synthesis inhibitors, cccDNA reducers, core protein allosteric modulators, ribonuclease H inhibitors, cccDNA transcriptional modulators, HBx inhibitors and other small molecules that reduce cccDNA levels., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Nonalcoholic steatohepatitis (NASH) is a rising public health burden, and there is a lack of effective therapeutic drugs in clinical practice. Sustained hepatic inflammation is considered as the key histopathological feature and dangerous fact for NASH. Different causes vary from one NASH patient to another, while sustained hepatic inflammation affects all NASH patients. AdipoRon is the first small-molecule AdipoR agonist, exerting antidiabetic and anti-inflammatory effect. In order to find novel AdipoRon analogues with more potent anti-inflammatory activity, we designed, synthesized and biologically evaluated 32 analogues. Among them, Q7 exerted potent anti-inflammatory activity and less cytotoxicity. Q7 could dose-dependently stimulate the increasing of AMPK phosphorylation, the widely recognized downstream effector of AdipoR1 activation. In NASH model mice, Q7 showed significant anti-inflammatory, anti-fibrotic and lipid-lowering effect in mice liver, and was superior to AdipoRon. Together, Q7 holds promise for developing anti-inflammatory and anti-NASH agents., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Masson SAS. All rights reserved.)

The carbon-nutrient-water cycles of farmland ecosystem not only provides support for crop production, but also has an impact on the environment. Comprehensively quantifying the impact of crop production on the environment can provide a basis for crop sustainable production. A series of environmental footprint approaches, including carbon footprint (CF), nitrogen footprint (NF) and water footprint (WF), were optimized to evaluate greenhouse gas (GHG) emissions, reactive nitrogen (Nr) loss and water resource consumption in crop production, and a comprehensive footprint method based on Endpoint modeling was proposed to evaluate the overall environmental impact of crop production in China. The CF, NF and WF of 28 forms of crop production varied from 1206.29 kg CO 2 equivalent (CO 2 -eq) ha -1 of oil crops to 7326.37 kg CO 2 -eq ha -1 of fiber crops, 16.07 kg Nr-eq ha -1 of oil crops to 60.70 kg Nr-eq ha -1 of sugar crops, and 4032.04 m 3 ha -1 oil crops to 12,476.28 m 3 ha -1 of sugar crops, respectively. The contribution of each component to footprints varied greatly among different crops, and fertilizer manufacture, NH 3 volatilization and green WF were generally the main contributors of CF, NF and WF, respectively. The total GHG emissions, Nr loss and water consumption were estimated to be 670.11 Tg CO 2 -eq, 5.50 Tg Nr-eq and 837.06 G m 3 for all crop production of China. The greenhouse vegetable with the highest area-scaled comprehensive footprint was 4.5 times that of the oil crops which had the lowest one. The contribution of crop production to the corresponding environmental impact in China was as low as 3.7%, of which NH 3 volatilization contributed 48% and grain production contributed 72%. Mineral N fertilization was the main driver of the variation of comprehensive footprint between provinces, with reduction of N fertilizer application as an important way to reduce the environmental impact of crop production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Peroxisome proliferator-activator receptors α/δ (PPARα/δ) are regarded as potential therapeutic targets for nonalcoholic steatohepatitis (NASH). However, PPARα/δ dual agonist GFT-505 exhibited poor anti-NASH effects in a phase III clinical trial, probably due to its weak PPARα/δ agonistic activity and poor metabolic stability. Other reported PPARα/δ dual agonists either exhibited limited potency or had unbalanced PPARα/δ agonistic activity. Herein, we report a series of novel triazolone derivatives as PPARα/δ dual agonists. Among them, compound H11 exhibited potent and well-balanced PPARα/δ agonistic activity (PPARα EC 50 = 7.0 nM; PPARδ EC 50 = 8.4 nM) and a high selectivity over PPARγ (PPARγ EC 50 = 1316.1 nM) in PPAR transactivation assays. The crystal structure of PPARδ in complex with H11 revealed a unique PPARδ-agonist interaction. H11 , which had excellent PK properties and a good safety profile, showed potent in vivo anti-NASH effects in preclinical models. Together, H11 holds a great promise for treating NASH or other inflammatory and fibrotic diseases.

Despite research into the response of ammonia (NH 3 ) volatilization in farmland to various meteorological factors, the potential impact of future climate change on NH 3 volatilization is not fully understood. Based on a database consisting of 1063 observations across China, nonlinear NH 3  models considering crop type, meteorological, soil and management variables were established via four machine learning methods, including support vector machine, multi-layer perceptron, gradient boosting machine and random forest (RF). The RF model had the highest R 2 of 0.76 and the lowest RMSE of 0.82 kg NH 3 -N ha - 1 , showing the best simulation capability. Results of model importance indicated that NH 3 volatilization was mainly controlled by total input of N fertilizer, followed by meteorological factors, human managements and soil characteristics. The NH 3 emissions of China's cereal production (paddy rice, wheat and maize) in 2018 was estimated to be 3.3 Mt NH 3 -N. By 2050, NH 3 volatilization will increase by 23.1-32.0% under different climate change scenarios (Representative Concentration Pathways, RCPs), and climate change will have the greatest impact on NH 3 volatilization in the Yangtze river agro-region of China due to high warming effects. However, the potential increase in NH 3 volatilization under future climate change can be mitigated by 26.1-47.5% through various N fertilizer management optimization options., (© 2021 John Wiley & Sons Ltd.)

Water quality regulation is an important ecosystem service function of soil. In this study, the mechanism by which soil regulates water quality was reviewed, and the effects of soil management on water quality were explored. A scientometrics analysis was also conducted to explore the research fields and hotspots of water quality regulation of soil in the past 5 years. This review found that the pollutants entering the soil can be mitigated by precipitation, adsorption and desorption, ion exchange, redox and metabolic decomposition. As an optimal substrate, soil in constructed wetlands has perfect performance in the adsorption and passivation of pollutants such as nitrogen, phosphorus and heavy metals in water, and degradation of pesticides and emerging contaminants. Mangrove wetlands play an important role in coastal zone protection and coastal water quality restoration. However, the excessive application of agricultural chemicals causes soil overload, which leads to the occurrence of agricultural non-point source pollution. Under the dual pressures of climate change and food insecurity in the future, developing environmentally friendly and economically feasible sustainable soil management measures is crucial for maintaining the water purification function of soil by relying on the accurate quantification of soil function based on big data and modelling. This article is part of the theme issue 'The role of soils in delivering Nature's Contributions to People'.

Soil organic carbon (SOC) and soil carbon-to-nitrogen ratio (C:N) are the main indicators of soil quality and health and play an important role in maintaining soil quality. Together with Landsat, the improved spatial and temporal resolution Sentinel sensors provide the potential to investigate soil information on various scales. We analyzed and compared the potential of satellite sensors (Landsat-8, Sentinel-2 and Sentinel-3) with various spatial and temporal resolutions to predict SOC content and C:N ratio in Switzerland. Modeling was carried out at four spatial resolutions (800 m, 400 m, 100 m and 20 m) using three machine learning techniques: support vector machine (SVM), boosted regression tree (BRT) and random forest (RF). Soil prediction models were generated in these three machine learners in which 150 soil samples and different combinations of environmental data (topography, climate and satellite imagery) were used as inputs. The prediction results were evaluated by cross-validation. Our results revealed that the model type, modeling resolution and sensor selection greatly influenced outputs. By comparing satellite-based SOC models, the models built by Landsat-8 and Sentinel-2 performed the best and the worst, respectively. C:N ratio prediction models based on Landsat-8 and Sentinel-2 showed better results than Sentinel-3. However, the prediction models built by Sentinel-3 had competitive or better accuracy at coarse resolutions. The BRT models constructed by all available predictors at a resolution of 100 m obtained the best prediction accuracy of SOC content and C:N ratio; their relative improvements (in terms of R 2 ) compared to models without remote sensing data input were 29.1% and 58.4%, respectively. The results of variable importance revealed that remote sensing variables were the best predictors for our soil prediction models. The predicted maps indicated that the higher SOC content was mainly distributed in the Alps, while the C:N ratio shared a similar distribution pattern with land use and had higher values in forest areas. This study provides useful indicators for a more effective modeling of soil properties on various scales based on satellite imagery., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Quantifying methane (CH 4 ) emissions from paddy fields is essential for evaluating the environmental risks of the paddy rice production system, and improving the accuracy of CH 4 modeling is a key issue that needs to be addressed. Based on a database containing 835 field measurements, both single national and region-specific models were established to estimate CH 4 emissions from paddy fields considering different environmental factors and management patterns using 70% of the measurements. The remaining 30% of the measurements were then used for model evaluation. The performance of the region-specific model was better than that of the single national model. The region-specific model could simulate CH 4 emissions in an unbiased manner with R 2 values of 0.15-0.70 and efficiency values of 11-60%. The paddy rice type, water regime, organic amendment, latitude, and soil characteristics (pH and bulk density) were identified as the main drivers in the models. By inputting the high-resolution spatial data of these drivers into the established model, the CH 4 emissions from China's paddy fields were estimated to be 4.75 Tg in 2015, with a 95% confidence interval of 4.19-5.61 Tg. The results indicated that establishing and driving a region-specific model with high-resolution data can improve the estimation accuracy of CH 4 emissions from paddy fields., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Updating and refining the N 2 O emission factors (N 2 O-EFs) are vital to reduce the uncertainty in estimates of direct N 2 O emissions. Based on a database with 1151 field measurements across China, the N 2 O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N 2 O-EFs. The third method had the highest R 2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N 2 O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N 2 O-EFs in maize and wheat seasons than other regions, and the highest N 2 O-EFs of 0.66-0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N 2 O-EFs. Based on the best estimation by the selected method, direct N 2 O emissions from China's crop cultivation were estimated to be 194 Gg N 2 O-N with a 95% confidence interval of 180-208 Gg N 2 O-N in the year 2016.