Driving forces and recovery potential of the macrophyte decline in East Taihu Lake.

Macrophytes are of key importance to the structure and ecological services of shallow lakes and are sensitive to anthropogenic and natural perturbations. Ongoing eutrophication and hydrological regime change affect macrophytes through changes in water transparency and water level, which lead to a dramatic decrease in bottom light availability. Here an integrated dataset (2005-2021) of multiple environmental factors is used to demonstrate the driving forces and recovery potential of the macrophyte decline in East Taihu Lake by using a critical indicator, which is the ratio of the Secchi disk depth to the water depth (SD/WD). The macrophyte distribution area showed a remarkable decrease from 136.1 ± 9.7 km2 (2005-2014) to 66.1 ± 6.5 km2 (2015-2021). The macrophyte coverage in the lake and in the buffer zone decreased by 51.4% and 82.8%, respectively. The structural equation model and correlation analysis showed that the distribution and coverage of macrophytes decreased with the decrease in the SD/WD over time. Moreover, an extensive hydrological regime change, which caused a sharp decrease in SD and an increase in the water level, is likely to be the driving force that brought about the decline of macrophytes in this lake. The proposed recovery potential model shows that the SD/WD has been low in recent years (2015-2021), and that this SD/WD cannot ensure the growth of submerged macrophytes and is unlikely to ensure the growth of floating-leaved macrophytes, especially in the buffer zone. The approach developed in the present study provides a basis for the assessment of macrophyte recovery potential and the management of ecosystems in shallow lakes that suffer from macrophyte loss.

Anti-inflammatory and antibacterial activities of Pyrrosia petiolosa ethyl acetate (PPEAE) against Staphylococcus aureus in mice.

P. petiolosa as a typical Chinese herbal medicine has been generally utilized as Chinese native medicine formulation for treatment of chronic bronchitis, bronchial asthma and pneumoconiosis. The objective of this study was to evaluate the anti-inflammatory and antibacterial activities of P. petiolosa ethyl acetate extract (PPEAE) against S. aureusin mice. In our study, mice were infected pneumonia by S. aureus, colonization of S. aureus in lung tissue was calculated and the number of white blood cells (WBC) in blood was measured. Meanwhile, the hematoxylin-eosin staining (H&E) was observed and the Real-time PCR was employed to determine the relative mRNA expression. The results showed that, after treated with PPEAE the wet/dry (W/D) weight ratio and the number of WBC decreased dramatically, the number of S. aureus was significantly reduced. Furthermore, H&E staining showed that PPEAE obviously relieved the inflammation of infected mice and real-time PCR results indicated that PPEAE significantly down regulated the inflammatory iNOS, TNF-α and up regulated the anti-inflammatory HO-1 mRNA. In summary, our study revealed that application of crude product PPEAE had prominent antibacterial activity against S. aureus. PPEAE significantly reduced the biomass of S. aureus and effectively relieved the inflammation of S. aureus-induced pneumonia.

A probabilistic modeling framework for assessing the impacts of large reservoirs on river thermal regimes - A case of the Yangtze River.

Hydrological and thermal river regimes have changed greatly due to the construction of reservoirs and dams. Water temperature changes have important significance for aquatic habitats and freshwater ecosystems. To investigate the impact of large reservoirs on the water temperature regime along the middle reach of the Yangtze River, we present a probabilistic modeling framework to ascertain the joint dependence structures of air-water temperature and discharge-water temperature between pre-reservoir and post-reservoir periods based on the copula theory. The results show that the principle of maximum entropy (POME) method can better estimate the marginal distributions of temperature regimes. Reservoir operation disturbed the dependence structures of air-water temperature, especially after the Three Gorges Reservoir (TGR) was put into operation. Different shifts in the occurrence probabilities of high or low water temperatures at the downstream and upstream stations under extreme air temperature and discharge are observed, indicating the great effects of reservoirs on the dependence structures of the downstream river flow and thermal regime. Relying on the developed model, we propose the appropriate ranges of air temperature and discharge to maintain a suitable water temperature for Chinese sturgeon (Acipenser sinensis) spawning activity. The results of this study demonstrate the influence of dams on the thermal regime and can be helpful for optimizing reservoir operations to enhance biological conservation in the Yangtze River.

Vine copula selection using mutual information for hydrological dependence modeling.

Hydrological risk analysis and management entails multivariate modeling which requires modeling the structure of dependence among different variables. Vine copulas have been increasing applied in multivariate modeling wherein the selection of vine copula structure plays a critical role. Inspired by the relationship between Mutual information (MI) and copula entropy (CE), this study discussed the connection between conditional mutual information (CMI) and CE and developed a mutual information-based sequential approach to select a vine structure which was based on original observations, and model-independent. Then, to reduce the complexity of R-vine copulas, a statistical method-based truncation procedure was applied. Finally, an MI-based approach for hydrological dependence modeling was developed. Two types of hydrological processes with different dependence structures were utilized to show the performance of the proposed approach: (i) drought characterization: showing a D-vine structure; and (ii) multi-site streamflow dependence: showing a C-vine structure. Results indicated that the MI-based approach satisfactorily modeled different kinds of dependence structure and yielded more information on variables in comparison with traditional tau-based approach.

Quantifying the change in streamflow complexity in the Yangtze River.

Hydrological processes of the Yangtze River have changed over the past decades due to environmental change and human activity. This paper uses sample entropy to investigate the spatial distribution and dynamic change in streamflow series complexity in the Yangtze River, China. In this study, the complexity of the streamflow series is quantified by entropy analysis. Daily streamflow series for four stations located in the mainstem and two control stations of the two largest freshwater lakes were analysed for the past 60 years. The results showed that the complexity of the streamflow series showed an obvious spatial difference and an increasing trend from upstream to downstream in the Yangtze River. There was a negative relationship between the annual streamflow and the corresponding sample entropy, and their peak-to-valley values showed well-corresponding relationships. The complexity of the runoff series at the Cuntan, Yichang, and Datong stations showed a continuous increasing trend, while that of the Hankou station showed a decreasing trend. The Three Gorges Dam changed the streamflow series complexity in the middle reach of the Yangtze River during the initial impoundment stage, while it had only slight impacts during the fully operational stage. Compared to the mainstem reaches, the streamflow series complexity of the two lakes showed no obvious change. The complexity of the streamflow series in the mainstem of the Yangtze River has been influenced by dam construction. The study could provide a scientific reference for understanding the flow dynamic evolution in the Yangtze River.

Improved comprehensive ecological risk assessment method and sensitivity analysis of polycyclic aromatic hydrocarbons (PAHs).

Based on the existing comprehensive ecological risk assessment methods of PAHs, this paper proposed an improved hierarchical Archimedean copula integral assessment (HACIA) model with the optimization in the model selection mechanism and accelerating the calculation speed, and according to which performed the sensitivity analysis of the integrated risk relative to the underlying grouped risk probability. Taihu Lake in China and the Bay of Santander in Spain were taken as study areas, whose samples were obtained and extracted concentrations of 16 priority polycyclic aromatic hydrocarbons (PAHs). After briefly analyzing their concentration characteristics and source, their comprehensive ecological risks were evaluated by the improve HACIA model and their sensitivity was also analyzed. The results proved that, for Taihu Lake, pyrogenic sources occupied the dominance, especially grass, coal and wood combustion, while the risk proportion of 5-rings PAHs was the lowest indeed based on the improved HAICA model. For the Bay of Santander, source apportionment indicated both petrogenic and pyrogenic sources, mainly from vehicle emissions including gasoline and diesel engines, and 4-ring PAHs were urgently needed to be managed. However, the sensitivity analysis results of two study areas showed that the most effective control target for reducing integral risk has no obvious relationship with the maximum grouped risk. And a clear linear relationship between the maximum sensitivity range and the logarithm of the initial overall risk only presented in one of study areas, which required further research to clarify. In brief, the improved HACIA model is helpful to evaluate the comprehensive ecological risk of 16 PAHs, and formulate risk management strategies based on grouped risk assessment and sensitivity analysis, with the former points out the admonitory risk and the latter helps to find the most effective mitigation measures.

Anti-inflammatory and antibacterial activities of P. petiolosa (Christ) Ching ethyl acetate extract against S. aureus in mice.

P. petiolosa as a typical Chinese herbal medicine has been generally utilized as Chinese native medicine formulation for treatment of chronic bronchitis, bronchial asthma and pneumoconiosis. The objective of this study was to evaluate the anti-inflammatory and antibacterial activities of P. petiolosa ethyl acetate extract (PPEAE) against S. aureus in mice. The air-dried leaves were extracted with ethyl acetate, mice were infected pneumonia by S. aureus. Colonization of S. aureus in lung tissue was calculated by plate colony count. The number of white blood cells (WBC) in blood was measured by blood cell automatic analyzer. The histopathological analysis of hematoxylin-eosin staining (H&E) of lung tissue was observed under microscope. Real-time PCR assay was employed to determine the relative mRNA expression of HO-1, iNOS and TNF-α. The results showed that, compared with control, after treated with PPEAE the wet/dry (W/D) weight ratio of mice lung tissue (decreased from 5.371 to 4.9) and the number of white blood cells (WBC) (decreased by 3.13×109/mL) decreased dramatically. The number of S. aureus was significantly reduced (from 1.93×105 CFU/mL to 26×103 CFU/mL) in lung tissue after treated with PPEAE. Furthermore, H&E staining showed that PPEAE obviously relieved the inflammation of lung tissue of infected mice. Meanwhile, real-time PCR results indicated that PPEAE down regulated the expression of inflammatory iNOS, TNF-α mRNA and up regulated the expression of anti-inflammatory HO-1 mRNA. In summary, this study revealed that application of crude product PPEAE had prominent antibacterial activity against S. aureus. PPEAE significantly reduced the biomass of S. aureus in lung tissue and effectively relieved the inflammation of S. aureus-induced pneumonia.

Effects of the RNA-binding protein, KSRP, on innate immune response against Helicobacter pylori infection in mice.

Helicobacter pylori (H. pylori) contributes to various gastric diseases such as chronic gastritis, gastric ulcer, and gastric carcinoma. Host innate immune response against the pathogen plays a significant role in elimination of pathogen infection. Importantly, pathogen elimination is closely related to numerous inflammatory-related genes that participate in complex biological response of cells to harmful stimuli. Here we studied effects of the KH-type splicing regulatory protein (KSRP), a RNA-binding protein, on innate immune response against H. pylori infection. We found that H. pylori infection downregulated KSRP expression directly, and that KSRP overexpression repressed upregulation of CXCL-2 expression induced by H. pylori and facilitated H. pylori proliferation in vitro. Similarly, KSRP overexpression in H. pylori mice also facilitated H. pylori proliferation and colonization, and induced more severe gastric mucosal damage. Intriguingly, CXCL-2 and HMOX-1 were upregulated in H. pylori infected mice after KSRP overexpression. This difference in expression of these genes implicated that KSRP was closely associated with and directly participated in the innate immune response against H. pylori. These results were beneficial for understanding the in vivo function of KSRP on innate immune response against pathogen infection.

Lymphotoxin-ß promotes breast cancer bone metastasis colonization and osteolytic outgrowth.

Bone metastasis is a lethal consequence of breast cancer. Here we used single-cell transcriptomics to investigate the molecular mechanisms underlying bone metastasis colonization-the rate-limiting step in the metastatic cascade. We identified that lymphotoxin-ß (LTß) is highly expressed in tumour cells within the bone microenvironment and this expression is associated with poor bone metastasis-free survival. LTß promotes tumour cell colonization and outgrowth in multiple breast cancer models. Mechanistically, tumour-derived LTß activates osteoblasts through nuclear factor-κB2 signalling to secrete CCL2/5, which facilitates tumour cell adhesion to osteoblasts and accelerates osteoclastogenesis, leading to bone metastasis progression. Blocking LTß signalling with a decoy receptor significantly suppressed bone metastasis in vivo, whereas clinical sample analysis revealed significantly higher LTß expression in bone metastases than in primary tumours. Our findings highlight LTß as a bone niche-induced factor that promotes tumour cell colonization and osteolytic outgrowth and underscore its potential as a therapeutic target for patients with bone metastatic disease.

Influence of the impoundment of the Three Gorges Reservoir on hydrothermal conditions for fish habitat in the Yangtze River.

The thermal regimes of rivers play an important role in the overall health of aquatic ecosystems. Modifications to water temperature regimes resulting from dams and reservoirs have important consequences for river ecosystems. This study investigates the impacts of the impoundment of the Three Gorges Reservoir (TGR) on the water temperature regime of fish spawning habitats in the middle reach of the Yangtze River, China. Mike 11 model is used to analyze the temporal and spatial variation of water temperatures of the expanse of 400 km along the river, from Yichang to Chenglingji. The water temperature alterations caused by the operation of the TGR are assessed with river temperature metrics. The impact on spawning habitats due to water temperature variation was also discussed in different impoundments of the TGR. The results show that the TGR has significantly altered the downstream water temperature regime, affecting the baseline deviation and phase shift of the water temperature. Such impacts on the thermal regime of the river varied with the impoundment level. The effects of the TGR on the water temperature regime decreased as the distance from the structure to the sample site increased. The water temperature regime alterations have led to the delay of the spawning times of the four famous major carp (FFMC) species. The results could be used to identify the magnitudes of water temperature alterations induced by reservoirs in the Yangtze River and provide useful information to design ecological operations for the protection of river ecosystem integrity in regulated rivers.

Effect of A, B-site cation on the catalytic activity of La1-xAxMn1-yByO3 (A = Ce, B = Ni) perovskite-type oxides for toluene oxidation.

ABO3-type perovskites (A = La, Ce; B = Mn, Ni) were prepared by sol-gel method, and applied for catalytic oxidation of toluene. The activity test results show that the activity of LaMnO3 can be improved when a small amount of Ce and Ni are doped into the A and B sites of LaMnO3, respectively. The effects of different calcination temperatures and different calcination time on the preparation of La-based perovskites were also investigated. The results illustrate that the toluene conversion of La0.8Ce0.2Mn0.8Ni0.2O3 is the highest when the calcination temperature is 700 °C and the calcination time is 4 h in La1-xCexMn1-yNiyO3 perovskites, and it requires lower reaction temperature when the conversion rate of toluene reaches 100% as compared to other catalysts, the T90 is 295 °C (T90, the temperature corresponding to the 90% of toluene conversion). Importantly, the mechanism of catalytic oxidation was also discussed. Therefore, the catalyst has potential prospects in the volatile organic compounds (VOCs) degradation.

CeO2 supported MOFs derived LaBxFeyO3 (B=Mn, Co) perovskite catalysts for degradation of toluene.

In this work, LaCoO3 and LaMnO3 perovskites with the higher specific surface area were synthesized using MOFs as precursor, then, the composite catalysts CeO2-LaCoxFeyO3 and CeO2-LaMnxFeyO3 were prepared by using CeO2 as support and Fe element doping LaCoO3 and LaMnO3, respectively. The as-prepared samples were characterized by XRD, SEM, XPS, H2-TPR, and N2 physisorption techniques. Subsequently, toluene was used as the probe molecule for volatile organic compounds (VOCs) to test the catalytic activity of these as-prepared catalysts. The results show that the initial reaction temperature for toluene oxidation on supported perovskite catalysts is lower. Among which, CeO2-LaCo0.25Fe0.75O3 (T90=215 °C, T90: the temperature corresponding to 90% conversion of toluene) and CeO2-LaMn0.25Fe0.75O3 (T90=205 °C) catalysts show the best catalytic performance. Therefore, the supported perovskite prepared in this study has the advantages of high specific surface area, abundant oxygen vacancies, and excellent oxygen mobility, which makes it exhibit better performance in VOCs catalytic oxidation.

Tumor-derived Jagged1 promotes cancer progression through immune evasion.

Immune checkpoint inhibitor (ICI) therapy is generating remarkable responses in individuals with cancer, but only a small portion of individuals with breast cancer respond well. Here we report that tumor-derived Jagged1 is a key regulator of the tumor immune microenvironment. Jagged1 promotes tumorigenesis in multiple spontaneous mammary tumor models. Through Jagged1-induced Notch activation, tumor cells increase expression and secretion of multiple cytokines to help recruit macrophages into the tumor microenvironment. Educated macrophages crosstalk with tumor-infiltrating T cells to inhibit T cell proliferation and tumoricidal activity. In individuals with triple-negative breast cancer, a high expression level of Jagged1 correlates with increased macrophage infiltration and decreased T cell activity. Co-administration of an ICI PD-1 antibody with a Notch inhibitor significantly inhibits tumor growth in breast cancer models. Our findings establish a distinct signaling cascade by which Jagged1 promotes adaptive immune evasion of tumor cells and provide several possible therapeutic targets.

Water temperature forecasting based on modified artificial neural network methods: Two cases of the Yangtze River.

Water temperature is a controlling indicator of river habitat since many physical, chemical and biological processes in rivers are temperature dependent. Highly precise and reliable predictions of water temperature are important for river ecological management. In this study, a hybrid model named BP_PSO3, based on the BPNN (back propagation neural network) optimized by the PSO (particle swarm optimization) algorithm, is proposed for water temperature prediction using air temperature (Ta), discharge (Q) and day of year (DOY) as input variables. The performance of the BP_PSO3 model was compared with that of the BP_PSO1 (with Ta as the input) and BP_PSO2 (with Ta and Q as the inputs) models to evaluate the importance of the inputs. In addition, a comparison among the BPNN, RBFNN (radial basis function neural network), WNN (wavelet neural network), GRNN (general regression neural network), ELMNN (Elman neural network), and BP_PSO-based models was carried out based on the MAE, RMSE, NSE and R2. The eight artificial intelligence models were examined to predict the water temperature at the Cuntan and Datong stations in the Yangtze River. The results indicated that the hybrid BPNN-PSO3 model had a stronger ability to forecast water temperature under both normal and extreme drought conditions. Optimization by the PSO algorithm and the inclusion of Q and DOY could help capture river thermal dynamics more accurately. The findings of this study could provide scientific references for river water temperature forecasting and river ecosystem protection.

A novel high-performance CeO2-CuMn2O4 catalyst for toluene degradation.

A series of spinel CuM2O4 (M = Mn, Fe, and Al) was used as the catalyst to investigate the effective degradation of toluene, and then CuMn2O4 with better catalytic activity was selected as the research object to study its activity at different ratios of Cu and Mn. Meanwhile, CeO2 was introduced to modify CuMn bimetallic oxide to improve its catalytic performance. The structure, morphology, and valence states of surface elements of as-prepared catalysts were characterized by XRD, TEM, SEM, N2 adsorption-desorption, XPS, and H2-TPR. Using toluene as a probe molecule, the catalytic activity of the catalyst was tested and the results showed that the conversion rate of toluene catalyzed by CeO2-CuMn2O4 catalyst can reach 90% at 200 °C (T90) and 100% at 240 °C (T100). The CO2 yield can also reach 100% at 248 °C. Moreover, the possible catalytic mechanism for toluene by the CeO2-CuMn2O4 was briefly explored. The catalytic oxidation of toluene over the oxide follows the Mars-van Krevelen mechanism.

Direct Z-scheme La1-xCexMnO3 catalyst for photothermal degradation of toluene.

A series of Ce-doped LaMnO3 (La1-xCexMnO3) were prepared and were tested for gaseous toluene oxidation in order to investigate the effect of cerium doping in LaMnO3 on activity under photothermal conditions. It was found that the activity and CO2 yield of the catalyst can be effectively increased when x = 0.25. A group of characterization is used to characterize the morphology, composition, and physical properties of the as-prepared catalysts. Results show that the Ce-doped LaMnO3 can form coexistence of La1-xCexMnO3 and CeO2, the reaction of CeO2/La1-xCexMnO3 under photothermal conditions follows the Mars-van Krevelen redox cycle mechanism, and the prepared CeO2/La1-xCexMnO3 can form a highly efficient Z-scheme heterojunction, which can enhance the electrons transfer speed of the catalyst. Moreover, in the photothermal catalytic degradation, lattice oxygen is the most important active substance, a small amount of cerium doping can increase the lattice oxygen content of perovskite and increase the activity of the reaction.