pH-responsive hierarchical H2S-releasing nano-disinfectant with deep-penetrating and anti-inflammatory properties for synergistically enhanced eradication of bacterial biofilms and wound infection.

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) biofilm-associated bacterial infection is the primary cause of nosocomial infection and has long been an ongoing threat to public health. MRSA biofilms are often resistant to multiple antimicrobial strategies, mainly due to the existence of a compact protective barrier; thus, protecting themselves from the innate immune system and antibiotic treatment via limited drug penetration. RESULTS: A hierarchically structured hydrogen sulfide (H2S)-releasing nano-disinfectant was presented, which was composed of a zinc sulfide (ZnS) core as a H2S generator and indocyanine green (ICG) as a photosensitizer. This nano-disinfectant (ICG-ZnS NPs) sensitively responded to the biofilm microenvironment and demonstrated efficient eradication of MRSA biofilms via a synergistic effect of Zn2+, gas molecule-mediated therapy, and hyperthermia. Physically boosted by released H2S and a near-infrared spectroscopy-induced hyperthermia effect, ICG-ZnS NPs destroyed the compactness of MRSA biofilms showing remarkable deep-penetration capability. Moreover, on-site generation of H2S gas adequately ameliorated excessive inflammation, suppressed secretion of inflammatory cytokines, and expedited angiogenesis, therefore markedly accelerating the in vivo healing process of cutaneous wounds infected with MRSA biofilms. CONCLUSION: ICG-ZnS NPs combined with NIR laser irradiation exhibited significant anti-biofilm activity in MRSA biofilms, can accelerate the healing process through deep-penetration and anti-inflammatory effectuation. The proposed strategy has great potential as an alternative to antibiotic treatment when combating multidrug-resistant bacterial biofilms.

Estimation of the relative contributions of forest areal expansion and growth to China's forest stand biomass carbon sequestration from 1977 to 2018.

As a prominent part of global and regional terrestrial carbon (C) pools, increases in forest biomass C sinks can be attributed to either forest areal expansion (FAE) or increased biomass C density (IBCD). Accurate estimates of the relative contributions of FAE and IBCD to forest C sequestration can improve our understanding of forest C cycling processes and will help to formulate rational afforestation policies to cope with global warming. In this study, the Continuous Biomass Expansion Factor (CBEF) model and Forest Identity concept were used to map the spatiotemporal variation of the relative contribution of FAE and IBCD to the C sequestration of forest (natural and planted forests) in China and seven regions during the past 40 years. Our results suggest that: (1) total forest biomass C density and stocks of forest increased from 35.41 Mg C ha-1 and 4128.50 Tg C to 43.95 Mg C ha-1 and 7906.23 Tg C in China from 1977 to 2018, respectively; (2) for all forests, the IBCD has been a smaller contributor to C sinks than FAE in China from 1977 to 2018 (33.27 vs. 66.73%); (3) the contribution of FAE to C sinks is greater than that of IBCD in planted forests (63.99 vs. 36.01%), while in natural forests, IBCD has a larger contribution than FAE (57.82 vs. 42.18%) from 1977 to 2018 and the relative contribution of FAE has exceeded IBCD in the last decade; and (4) these patterns varied at the regional level such that the relative contribution of FAE increased for planted forests in most regions but for natural forests, IBCD gradually reached saturation and C stocks declined in northern regions in the last decade. The results from this study suggest that total biomass C sinks will keep increasing because of the increased forest area contributed by afforestation and the relatively young trees in planted forests. This study facilitates a more comprehensive assessment of forest C budgets and improves our understanding of ecological mechanisms of forest biomass carbon stock and dynamics.

Interannual variation in grassland net ecosystem productivity and its coupling relation to climatic factors in China.

Grassland, as an important part of land cover, plays an important role in the global carbon cycle and carbon balance. Net ecosystem productivity (NEP) is a key indicator of the carbon cycle process and an important factor in assessing ecosystem security and maintaining ecosystem balance. In this paper, Boreal Ecosystem Productivity Simulator (BEPS) combining meteorological data, leaf area index, and land cover type data were used to simulate the grassland NEP of China from 1979 to 2008. This model was also used to analyze the responses to changes in climate factors, interannual variation in carbon conversion efficiency, drought stress coefficient, and water use efficiency of grassland in China. Results showed that from 1979 to 2008, the mean annual grassland NEP was 13.6 g C/m2 with weak carbon sinks. The grassland NEP distribution increased from northwest to southeast across China. Regions with NEP of > 0 (C sink) accounted for 73.1% of the total grassland area of China. The total C sequestration reached 26.6 Tg yearly, and grassland NEP was positive from 1979 to 2008. The annual changing characteristics were analyzed. Grassland NEP was positive with carbon sink from June to September, which was negative with carbon source in the remaining months. The carbon conversion efficiency and water use efficiency of the grassland increased significantly within 30 years. NEP showed positive correlation with precipitation (accounting for 74.2% of the total grassland area was positively correlated) but weakly positive correlation with temperature (50.2% of the case). Furthermore, significant positive correlation was found between grassland NEP and precipitation, especially in northeastern and central Inner Mongolia, northern Tianshan of Xinjiang, southwestern Tibet, and southern Qinghai Lake.

Surface water areas significantly impacted 2014 dengue outbreaks in Guangzhou, China.

Dengue transmission in urban areas is strongly influenced by a range of biological and environmental factors, yet the key drivers still need further exploration. To better understand mechanisms of environment-mosquito-urban dengue transmission, we propose an empirical model parameterized and cross-validated from a unique dataset including viral gene sequences, vector dynamics and human dengue cases in Guangzhou, China, together with a 36-year urban environmental change maps investigated by spatiotemporal satellite image fusion. The dengue epidemics in Guangzhou are highly episodic and were not associated with annual rainfall over time. Our results indicate that urban environmental changes, especially variations in surface area covered by water in urban areas, can substantially alter the virus population and dengue transmission. The recent severe dengue outbreaks in Guangzhou may be due to the surge in an artificial lake construction, which could increase infection force between vector (mainly Aedes albopictus) and host when urban water area significantly increased. Impacts of urban environmental change on dengue dynamics may not have been thoroughly investigated in the past studies and more work needs to be done to better understand the consequences of urbanization processes in our changing world.

Camouflaging nanoreactor traverse the blood-brain barrier to catalyze redox cascade for synergistic therapy of glioblastoma.

The blood-brain barrier (BBB) is a complex and highly restrictive barrier that prevents most biomolecules and drugs from entering the brain. However, effective strategies for delivering drugs to the brain are urgently needed for the treatment of glioblastoma. Based on the efficient BBB penetration properties of exosomes derived from brain metastatic breast cancer cells (EB), this work prepared a nanoreactor (denoted as MAG@EB), which was constructed by self-assembly of Mn2+, arsenate and glucose oxidase (GOx) into nanoparticles wrapped with EB. MAG@EB can enhance the efficiency of traversing the BBB, target and accumulate at in situ glioblastoma sites. The GOx-driven glycolysis effectively cuts off the glucose supply while also providing an abundance of H2O2 and lowering pH. Meanwhile, the released Mn2+ mediated Fenton-like reaction converts elevated H2O2 into highly toxic ·OH. Besides, AsV was reduced to AsIII by glutathione, and the tumor suppressor gene P53 was activated by AsIII to kill glioblastoma cells. Glioblastoma succumbed to the redox cascade triggered by MAG@EB, as the results demonstrated in vivo and in vitro, yielding a remarkable therapeutic effect. This work provides a promising therapeutic option mediated by cascaded nanoreactors for the future treatment of glioblastoma.

Global future population exposure to heatwaves.

The increasing exposure to extreme heatwaves in urban areas from both climate change and the urban heat island (UHI) effect poses multiple threats and challenges to human society. Despite a growing number of studies focusing on extreme exposure, research advances are still limited in some aspects such as oversimplification of human exposure to heatwaves and neglect of perceived temperature as well as actual body comfort, resulting in unreliable and unrealistic estimates of future results. In addition, little research has performed comprehensive and fine-resolution global analyses in future scenarios. In this study, we present the first global fine-resolution projection of future changing urban population exposure to heatwaves by 2100 under four shared socioeconomic pathways (SSPs) considering urban expansion at global, regional, and national scales. Overall, global urban population exposure to heatwaves is rising under the four SSPs. Temperate and tropical zones predictably have the greatest exposure among all climate zones. Coastal cities are projected to have the greatest exposure, followed closely by cities at low altitudes. Middle-income countries have the lowest exposure and the lowest inequality of exposure among countries. Individual climate effects contributed the most (approximately 46.4%) to future changes in exposure, followed by the interactive effect between climate and urbanization (approximately 18.5%). Our results indicate that more attention needs to be paid to policy improvements and sustainable development planning of global coastal cities and some low-altitude cities, especially in low- and high-income countries. Meanwhile, this study also highlights the impact of continued future urban expansion on population exposure to heatwaves.

Recent Advances in Mesoporous Silica Nanoparticles Delivering siRNA for Cancer Treatment.

Silencing genes using small interfering (si) RNA is a promising strategy for treating cancer. However, the curative effect of siRNA is severely constrained by low serum stability and cell membrane permeability. Therefore, improving the delivery efficiency of siRNA for cancer treatment is a research hotspot. Recently, mesoporous silica nanoparticles (MSNs) have emerged as bright delivery vehicles for nucleic acid drugs. A comprehensive understanding of the design of MSN-based vectors is crucial for the application of siRNA in cancer therapy. We discuss several surface-functionalized MSNs' advancements as effective siRNA delivery vehicles in this paper. The advantages of using MSNs for siRNA loading regarding considerations of different shapes, various options for surface functionalization, and customizable pore sizes are highlighted. We discuss the recent investigations into strategies that efficiently improve cellular uptake, facilitate endosomal escape, and promote cargo dissociation from the MSNs for enhanced intracellular siRNA delivery. Also, particular attention was paid to the exciting progress made by combining RNAi with other therapies to improve cancer therapeutic outcomes.

A comparative mapping of plant species diversity using ensemble learning algorithms combined with high accuracy surface modeling.

Plant species diversity (PSD) has always been an essential component of biodiversity and plays an important role in ecosystem functions and services. However, it is still a huge challenge to simulate the spatial distribution of PSD due to the difficulties of data acquisition and unsatisfactory performance of predicting algorithms over large areas. A surge in the number of remote sensing imagery, along with the great success of machine learning, opens new opportunities for the mapping of PSD. Therefore, different machine learning algorithms combined with high-accuracy surface modeling (HASM) were firstly proposed to predict the PSD in the Xinghai, northeastern Qinghai-Tibetan Plateau, China. Spectral reflectance and vegetation indices, generated from Landsat 8 images, and environmental variables were taken as the potential explanatory factors of machine learning models including least absolute shrinkage and selection operator (Lasso), ridge regression (Ridge), eXtreme Gradient Boosting (XGBoost), and Random Forest (RF). The prediction generated from these machine learning methods and in situ observation data were integrated by using HASM for the high-accuracy mapping of PSD including three species diversity indices. The results showed that PSD was closely associated with vegetation indices, followed by spectral reflectance and environmental factors. XGBoost combined with HASM (HASM-XGBoost) showed the best performance with the lowest MAE and RMSE. Our results suggested that the fusion of heterogeneous data and the ensemble of heterogeneous models may revolutionize our ability to predict the PSD over large areas, especially in some places limited by sparse field samples.

The Influence of Short-Term Heavy Rainfall on Hydraulic Characteristics and Rill Formation in the Yuanmou Dry-Hot Valley.

Rill erosion is one of the major environmental problems in the world; it is an important factor with regard to land degradation and has a serious impact on production and daily life in the region. The widely distributed Yuanmou group stratum promotes the development of rill erosion, whereby the strong time-concentrated rainfall and the alternating arid-humid climate prepare the ground for the development of rills in soils. Therefore, a study of the processes of slope rill erosion was carried out, and a gravel-soil slope in the Yuanmou dry-hot valley was chosen to simulate short-term heavy rainfall (25 mm/h) (No. 1 plot) and moderate rainfall (15 mm/h) (No. 2 plot), to study the erosion processes of soil and the dynamic characteristics of runoff involved in erosion. The study results showed that the width of runoff was significantly different between the two plots, while the depth of runoff was not significantly different. During the rill formation process, the width of the two plots first decreased and then increased with increasing washout duration, while its depth did not change significantly. Flow was the key factor in determining the hydraulic characteristics of runoff, and it had a significant or extremely significant positive correlation with hydraulic characteristics parameters, except in the case of Fr (Froude number) (r = 0.039). The total sediment content (CS) of plot No. 1 (0.158 g/cm3) was significantly different from that of plot No. 2 (0.153 g/cm3), and both CSs in the two plots decreased with increasing washout duration. The CS had an extremely significant negative correlation with τ (runoff shear force) (r = -0.863 **) and DW-f (Darcy-Weisbach drag coefficient) (r = -0.863 **) and a significant negative correlation with Re (Reynolds number) (r = -0.735 *) in the short-term heavy rainfall experiment, while the CS had a significant positive correlation with V (velocity) (r = 0.814 *), R (hydraulic radius) (r = 0.811 *) and P (unit stream power) (r = 0.811 *) in the moderate rainfall experiment. The results of this study will help guide further examination of the processes involved in the dynamic mechanisms of rill erosion on slopes under short-term heavy rainfall conditions.

Lignin-assisted construction of sub-10 nm supramolecular self-assembly for photothermal immunotherapy and potentiating anti-PD-1 therapy against primary and distant breast tumors.

Photothermal therapy (PTT) has brought hope for cancer treatments, with hyperthermia-induced immunogenic cell death (ICD), which is a critical part of therapeutically induced antitumor immune responses. Limited immune stimulation response in PTT is the primary reason for incomplete tumor ablation, therefore demonstrating urgent requirements for ICD amplifier. Herein, a sub-10 nm supramolecular nanoassembly was formed by co-assembly of clinically approved aluminum adjuvant and commonly used indocyanine green (ICG) under the assistance of lignosulfonate (LS, a green and sustainable multifunctional lignin derivative) for localized photothermal-immunotherapy of breast cancer. The overall results revealed that LS-Al-ICG is capable of inducing amplified ICD, efficiently eliciting solid immune responses through dendritic cells (DCs) activation and cytotoxic T-cell responses initiation for tumor killing. Moreover, anti-PD-1 therapy blocked the PD-1 pathway and led to remarkable anti-tumor efficacy against laser-irradiated primary tumors and distant tumors by potentiating systemic tumor specific T cell immunity. The results of this study demonstrate a handy and extensible approach for engineering green natural lignin nanoparticles for cancer immunotherapy, which shows promise for delivering other therapeutics in biomedical applications.

Hydroxy-safflower yellow A composites: An effective strategy to enhance anti-myocardial ischemia by improving intestinal permeability.

Hydroxy-safflower yellow A (HSYA) is the chief component of safflower against myocardial ischemia (MI), and belongs to biopharmaceutics classification system (BCS) III drugs. Its structure contains multiple hydroxyl groups, contributing to its high polarity and poor oral bioavailability. The main objective of this study was to probe the potential of oral penetration enhancer n-[8-(2-hydroxybenzoyl) amino] sodium octanoate (SNAC) and cationic copolymer Eudragit®EPO (EPO) to promote absorption of HSYA. HSYA composites (SNAC-HSYA-EPO) were formed by hydrogen bonding and van der Waals force. SNAC-HSYA-EPO has biocompatibility, and can improve the membrane fluidity, uptake, transport, and penetration of Caco-2 cells. The mechanism of promoting of SNAC-HSYA-EPO may be related to energy and P-glycoprotein (P-gp) when compared with the inhibitor NaN3 and verapamil group. In the pharmacokinetic (PK) results, SNAC-HSYA-EPO significantly improved oral bioavailability. Pharmacodynamics (PD) results determined that SNAC-HSYA-EPO could improve the symptoms of MI. The mechanism of the SNAC-HSYA-EPO anti-MI is related to alleviating inflammation and anti-apoptosis to protect the heart. In summary, SNAC-HSYA-EPO prepared in this study possessed a complete appearance, high recombination rate and excellent oral permeability promoting ability. SNAC-HSYA-EPO has the potential to improve oral bioavailability and further enhance the anti-MI effect of HSYA.

MMP2-responsive dual-targeting drug delivery system for valence-controlled arsenic trioxide prodrug delivery against hepatic carcinoma.

Arsenic trioxide (ATO) is the active ingredient in traditional Chinese medicine, i.e., Arsenic, which has shown excellent therapeutic effects on hepatocellular carcinoma. However, due to its poor tumor distribution and high toxicity, the mass adoption of ATO in clinical applications has been severely impeded. In this study, matrix metalloproteinase 2 (MMP2)-responsive cleaved cell-penetrating peptide (PF) and folate (FA) co-modified liposome coated calcium arsenate nanoparticles (FA/PF-LP-CaAs) were fabricated based on these two considerations: (1) The tumor microenvironment characterized by overexpressed MMP2 in extracellular matrix and folate receptor on the cell membrane can enhance drug accumulation and accelerate endocytosis; (2) leveraging different toxicity of arsenic in different valence states, i.e., AsV can be reduced to more toxic AsIII by glutathione in tumor cells. Furthermore, FA/PF-LP-CaAs could be responsively degraded by the mild acidic tumor environment, and the degraded product could escape from lysosomes after endocytosis. More importantly, in light of the in vivo biodistribution and pharmacodynamic studies, the vehicle was able to accumulate in the tumor efficiently. Also, it was able to exhibit excellent anti-tumor efficacy with minimized side effects when compared to single-modified counterparts. Thus, the novel strategy based on the tumor microenvironment proposed in this work can enhance the tumor-targeting efficiency and intratumor toxicity.

Estimating the effect of urbanization on extreme climate events in the Beijing-Tianjin-Hebei region, China.

Quantifying the impact of urbanization on extreme climate events is significant for ecosystem responses, flood control, and urban planners. This study aimed to examine the urbanization effects on a suite of 36 extreme temperature and precipitation indices for the Beijing-Tianjin-Hebei (BTH) region by classifying the climate observations into three different urbanization levels. A total of 176 meteorological stations were used to identify large cities, small and medium-size cities and rural environments by applying K-means cluster analysis combined with spatial land use, nighttime light remote sensing, socio-economic data and Google Earth. The change trends of the extreme events during 1980-2015 were detected by using Mann-Kendall (MK) statistical test and Sen's slope estimator. Urbanization effects on those extreme events were calculated as well. Results indicated that the cool indices generally showed decreasing trends over the time period 1980-2015, while the warm indices tended to increase. Larger and more significant changes occurred with indices related to the daily minimum temperature. The different change rates of temperature extremes in urban, suburban and rural environments were mainly about the cool and warm night indices. Urbanization in medium-size cities tended to have a negative effect on cool indices, while the urbanization in large cities had a positive effect on warm indices. The significant difference of urbanization effect between large and medium-size cities lay in the daily maximum temperature. Results also demonstrated the scale effect of the urbanization on the extreme temperature events. However, the results showed little evidence of the urban effect on extreme precipitation events in the BTH region. This paper explored the changes in temperature and precipitation extremes and qualified the urbanization effects on those extreme events in the BTH region. The findings of this research can provide new insights into the future urban agglomeration development projects.

Simulation and analysis of XCO2 in North China based on high accuracy surface modeling.

As an important cause of global warming, CO2 concentrations and their changes have aroused worldwide concern. Establishing explicit understanding of the spatial and temporal distributions of CO2 concentrations at regional scale is a crucial technical problem for climate change research. High accuracy surface modeling (HASM) is employed in this paper using the output of the CO2 concentrations from weather research and forecasting-chemistry (WRF-CHEM) as the driving fields, and the greenhouse gases observing satellite (GOSAT) retrieval XCO2 data as the accuracy control conditions to obtain high accuracy XCO2 fields. WRF-CHEM is an atmospheric chemical transport model designed for regional studies of CO2 concentrations. Verified by ground- and space-based observations, WRF-CHEM has a limited ability to simulate the conditions of CO2 concentrations. After conducting HASM, we obtain a higher accuracy distribution of the CO2 in North China than those calculated using the classical Kriging and inverse distance weighted (IDW) interpolation methods, which were often used in past studies. The cross-validation also shows that the averaging mean absolute error (MAE) of the results from HASM is 1.12 ppmv, and the averaging root mean square error (RMSE) is 1.41 ppmv, both of which are lower than those of the Kriging and IDW methods. This study also analyses the space-time distributions and variations of the XCO2 from the HASM results. This analysis shows that in February and March, there was the high value zone in the southern region of study area relating to heating in the winter and the dense population. The XCO2 concentration decreased by the end of the heating period and during the growing period of April and May, and only some relatively high value zones continued to exist.

Surface modeling of soil antibiotics.

Large numbers of livestock and poultry feces are continuously applied into soils in intensive vegetable cultivation areas, and then some veterinary antibiotics are persistent existed in soils and cause health risk. For the spatial heterogeneity of antibiotic residues, developing a suitable technique to interpolate soil antibiotic residues is still a challenge. In this study, we developed an effective interpolator, high accuracy surface modeling (HASM) combined vegetable types, to predict the spatial patterns of soil antibiotics, using 100 surface soil samples collected from an intensive vegetable cultivation area located in east of China, and the fluoroquinolones (FQs), including ciprofloxacin (CFX), enrofloxacin (EFX) and norfloxacin (NFX), were analyzed as the target antibiotics. The results show that vegetable type is an effective factor to be combined to improve the interpolator performance. HASM achieves less mean absolute errors (MAEs) and root mean square errors (RMSEs) for total FQs (NFX+CFX+EFX), NFX, CFX and EFX than kriging with external drift (KED), stratified kriging (StK), ordinary kriging (OK) and inverse distance weighting (IDW). The MAE of HASM for FQs is 55.1 µg/kg, and the MAEs of KED, StK, OK and IDW are 99.0 µg/kg, 102.8 µg/kg, 106.3 µg/kg and 108.7 µg/kg, respectively. Further, RMSE simulated by HASM for FQs (CFX, EFX and NFX) are 106.2 µg/kg (88.6 µg/kg, 20.4 µg/kg and 39.2 µg/kg), and less 30% (27%, 22% and 36%), 33% (27%, 27% and 43%), 38% (34%, 23% and 41%) and 42% (32%, 35% and 51%) than the ones by KED, StK, OK and IDW, respectively. HASM also provides better maps with more details and more consistent maximum and minimum values of soil antibiotics compared with the measured data. The better performance can be concluded that HASM takes the vegetable type information as global approximate information, and takes local sampling data as its optimum control constraints.

[Effects of China future land use change on aboveground vegetation biomass].

Land use change has significant effects on vegetation biomass via altering ecosystem structure. By adopting a spatially explicit land use change model, this paper simulated the spatiotemporal pattern of land use change in China till 2030, based on the historical scenario (in this scenario, the land use trend in 1988-2005 was extrapolated to obtain the area of each land use type in the future) and the planned scenario (in this scenario, the area of each land use type in the future was based on the national scale land use planning). On the basis of this simulation and using a biomass density approach, the spatial pattern of vegetation biomass change in China was estimated. The simulation showed that under the historical scenario, the forest area would be decreased but the forest age would be in adverse, and accordingly, the forest biomass density would have an increase. Till 2030, the overall vegetation biomass in China would be 14619 Tg, with an increase of 251.19 Tg as compared to the situation in 2005. Under the planned scenario, the forest area would be increased, and the overall vegetation biomass in 2030 would be 15468 Tg, with an increase of 1100 Tg as compared to the situation in 2005. In the planned scenario, the planted forest area would be larger while the forest age would be younger, resulting in a much lower vegetation biomass density in 2030 than that in the historical scenario, and thus, the China's vegetation in the planned scenario would have a higher potential to act as a carbon sink.