Potentialities of Ganoderma lucidum extracts as functional ingredients in food formulation.

Owing to the recognized therapeutic characteristics of G. lucidum, it is one of the most extensively researched mushrooms as a chemopreventive agent and as a functional food. It is a known wood-degrading basidiomycete possessing numerous pharmacological functions and is termed a natural pharmacy store due to its rich number of active compounds which have proved to portray numerous therapeutic properties. This current review highlights studies on the potentialities of G. lucidum extracts as functional ingredients on organoleptic and nutritional properties of food products (e.g., dairy, wine, beverage, bakery, meat, and other products). In addition, the study delved into various aspects of encapsulated G. lucidum extracts, their morphological and rheological characteristics, prebiotic and immunomodulatory importance, the effects on apoptosis, autophagy, cancer therapy, inflammatory responses, oxidative stress, antioxidant activities, and safety concerns. These findings have significant implications for the development of new products in the food and pharmaceutical industries. On the other hand, the various active compounds extracted from G. lucidum exhibited no toxic or adverse effects, and the appeal for it as a dietary food, natural remedy, and health-fortifying food is drastically increasing as well as attracting the interest of both the industrial and scientific communities. Furthermore, the formation of functional foods based on G. lucidum appears to have actual promise and exciting prospects in nutrition, food, and pharmaceutical sciences.

Investigating non-point pollution mitigation strategies in response to changing environments: A cross-regional study in China and Germany.

Climate change and urbanization have altered regional hydro-environments. Yet, the impact of future changes on the pollution risk and associated mitigation strategies requires further exploration. This study proposed a hydraulic and water-quality modeling framework, to investigate the spatiotemporal characteristics of pollution risk mitigation by low impact development (LID) strategies under future Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP) scenarios. Results demonstrated that the LID strategies exhibited an effective performance of pollutant removal in the current hydro-environment, with the removal rates ranging from 33% to 56%. In future climate and urbanization scenarios, the LID performance declined and turned to be uncertain as the greenhouse gas (GHG) emissions increased, with the removal rates ranging from 12% to 59%. Scenario analysis suggested that the LID performance was enhanced by a maximum of 73% through the diversified implementation of LID practices, and the performance uncertainty was reduced by a maximum of 67% through the increased LID deployment. In addition, comparative analysis revealed that the LID strategies in a well-developed region (Dresden, Germany) were more resilient in response to changing environments, while the LID strategy in a high-growth region (Chaohu, China) exhibited a better pollutant removal performance under low-GHG scenarios. The methods and findings in this study could provide additional insights into sustainable water quality management in response to climate change and urbanization.

Bayesian-Based Approaches to Exploring the Long-Term Alteration in Trace Metals of Surface Water and Its Driving Forces.

Trace metal pollution poses a serious threat to the aquatic ecosystem. Therefore, characterizing the long-term environmental behavior of trace metals and their driving forces is essential for guiding water quality management. Based on a long-term data set from 1990 to 2019, this study systematically conducted the spatiotemporal trend assessment, influential factor analysis, and source apportionment of trace elements in the rivers of the German Elbe River basin. Results show that the mean concentrations of the given elements in the last 30 years were found in the order of Fe (1179.5 ± 1221 µg·L-1) ≫ Mn (209.6 ± 181.7 µg·L-1) ≫ Zn (52.5 ± 166.2 µg·L-1) ≫ Cu (5.3 ± 5.5 µg·L-1) > Ni (4.4 ± 8.3 µg·L-1) > Pb (3.3 ± 4.4 µg·L-1) > As (2.9 ± 2.3 µg·L-1) > Cr (1.8 ± 2.4 µg·L-1) ≫ Cd (0.3 ± 1.1 µg·L-1) > Hg (0.05 ± 0.12 µg·L-1). Wavelet analyses show that river flow regimes and flooding dominated the periodic variations in metal pollution. Bayesian network suggests that the hydrochemical factors (i.e., TOC, TP, TN, pH, and EC) chemically influenced the metal mobility between water and sediments. Furthermore, the source apportionment computed by the Bayesian multivariate receptor model shows that the given element contamination was typically attributed to the geogenic sources (17.5, 95% confidence interval: 13.1-17.6%), urban and industrial sources (22.1, 18.0-27.2%), arable soil erosion (24.2, 16.4-31.5%), and historical anthropogenic activities (35.2, 32.8-43.3%). The results provided herein reveal that both the hydrochemical influence on metal mobility and the chronic disturbance from anthropogenic activities caused the long-term variation in trace metal pollution.

Discovery of Spiro[pyrrolidine-3,3'-oxindole] LXRß Agonists for the Treatment of Osteoporosis.

Osteoclasts have an additional demand for cholesterol compared to normal cells. Liver X receptors (LXRs) are famous for regulation of lipid and cholesterol metabolism. Therefore, we propose that the LXR ß agonist can regulate the cholesterol balance in osteoclasts to inhibit osteoclast differentiation. Here, we designed and synthesized a novel LXRß agonist by introduction of the privileged fragments from anti-osteoporosis agents to the spiro[pyrrolidine-3,3'-oxindole] scaffold which is a novel scaffold of LXR agonists in our previous research. As a result, seven LXRß agonists inhibited osteoclastogenesis with IC50 values ranging from 0.078 to 0.36 µM. Especially, the most potent LXRß agonist B9 significantly inhibited RANKL-induced osteoclast differentiation and bone resorption in vitro and in vivo. Furthermore, B9 selectively activated LXRß to promote intracellular cholesterol exclusion in osteoclasts and reduce extracellular cholesterol uptake and thereby inhibited osteoclast production. This study provides a new strategy to develop LXRß agonists for osteoporosis.

[Differential expressions of seminal plasma piRNAs in men and its significance].

OBJECTIVE: To study the differential expressions of piRNAs in the seminal plasma of men and the role of piRNAs in spermatogenesis. METHODS: We sequenced the seminal plasma samples collected from 187 male infertility patients and 58 normal healthy men, obtained differentially expressed piRNAs, and detected the relative expressions of piRNAs in different types of sperm by RT-qPCR to explore their significance in the diagnosis of male infertility. Using histopathology, RNA-protein pull-down and Western blot, we investigated the action mechanism of piRNAs in spermatogenesis in the mouse model. RESULTS: RT-qPCR of the seminal plasma samples revealed a high expression of hsa_piR_000478 in teratozoospermia and ROC curve analysis showed an auxiliary significance of hsa_piR_000478 in the diagnosis of the disease (AUC = 0.7549). Transfection of hsa_piR_000478 and its homologous sequence piR_mmu_54800729 into the seminiferous tubules of the mouse model significantly decreased sperm motility, increased the percentage of morphologically abnormal sperm and destroyed the testicular structure. Molecular biological experiments exhibited a close correlation between piRNAs and the energy metabolism-related pathway, which elevated the level of cell glycolysis and interfered with normal spermatogenesis. CONCLUSION: hsa_piR_000478 has an auxiliary significance in the diagnosis of male infertility, and piRNAs may interfere with spermatogenesis by affecting the glycolysis-related pathway in the spermatogenic microenvironment of the testis.

A MALDI-MS-based impact assessment of ZnO nanoparticles, nanorods and quantum dots on the lipid profile of bacterial pathogens.

MALDI-MS was used for studying the impact of zinc oxide (ZnO) nanomaterials on Pseudomonas aeruginosa and Staphylococcus aureus. The growth patterns of both these bacterial pathogens in the presence of the ZnO nanomaterials and the subsequent lipidomic changes were assessed using an optimized simple, rapid MALDI-MS based methodology. All three nanostructures tested exhibited differential bactericidal activity unique to P. aeruginosa and S. aureus. The results indicated that the ZnO nanomaterials were highly inhibitory to S. aureus even at 70 mg L-1, while in the case of P. aeruginosa, the ZnO nanomaterials were compatible for up to 10 h and beyond 10 h only marginal growth inhibition was observed. The results proved that the shapes of the ZnO nanomaterials did not affect their toxicity properties. MALDI-MS was applied to study the lipidomic changes of P. aeruginosa and S. aureus after nanomaterial treatment, in order to throw light on the mechanism of growth inhibition. The results from the MALDI-MS studies showed that the ZnO nanostructures exhibited only marginal changes in the lipidomic profile both in the case of P. aeruginosa and S. aureus. These preliminary results indicate that the mechanism of growth inhibition by the ZnO nanomaterial is not through lipid-based interactions, but apparently more so via protein inhibitions.

Occurrences, transport drivers, and risk assessments of antibiotics in typical oasis surface and groundwater.

Intensive use of antibiotics affects biogeochemical cycles and stimulates the evolution of antibiotic resistance, thus threatening global health and social development. The spatiotemporal distributions of antibiotics in single aqueous matrices have been widely documented; however, their occurrence in surface-groundwater systems has received less attention, especially in arid regions that usually have fragile ecosystems. Therefore, we investigated the occurrence of thirty-one antibiotics in the surface water and adjacent groundwater in the Xinjiang Uygur Autonomous Region, China. The results showed that the total concentrations of detected antibiotics varied from 17.37 to 84.09 ng L-1 and from 16.38 to 277.41 ng L-1 in surface and groundwater, respectively. The median concentration of antibiotics showed the pattern of norfloxacin (4.86 ng L-1) > ciprofloxacin (3.93 ng L-1) > pefloxacin (3.39 ng L-1) in surface water; whereas in groundwater, this was in the order of pefloxacin (6.30 ng L-1) > norfloxacin (4.33 ng L-1) > ciprofloxacin (2.68 ng L-1). Heatmap analysis indicated that vertical infiltration had limited effects on antibiotic exchange in surface-ground water systems because of the high potential evaporation and low water storage. Redundancy analysis suggested that the oxidation-reduction potential (p < 0.01) and dissolved oxygen (p < 0.05) jointly affected the distribution of antibiotics in surface water. Ecological risk assessment showed that antibiotics in 98.9% of surface water and 99.1% of groundwater did not pose significant risks to aquatic species. The findings of this study will help develop effective mitigation strategies for antibiotics in aquatic environments.

Extraction of multi-scale features enhances the deep learning-based daily PM2.5 forecasting in cities.

Characterising the daily PM2.5 concentration is crucial for air quality control. To govern the status of the atmospheric environment, a novel hybrid model for PM2.5 forecasting was proposed by introducing a two-stage decomposition technology of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD); subsequently, a deep learning approach of long short-term memory (LSTM) was proposed. Five cities with unique meteorological and economic characteristics were selected to assess the predictive ability of the proposed model. The results revealed that PM2.5 pollution was generally more severe in inland cities (66.98 ± 0.76 µg m-3) than in coastal cities (40.46 ± 0.40 µg m-3). The modelling comparison showed that in each city, the secondary decomposition algorithm improved the accuracy and prediction stability of the prediction models. When compared with other prediction models, LSTM effectively extracted featured information and achieved relatively accurate time-series prediction. The hybrid model of CEEMDAN-VMD-LSTM achieved a better prediction in the five cities (R2 = 0.9803 ± 0.01) compared with the benchmark models (R2 = 0.7537 ± 0.03). The results indicate that the proposed approach can identify the inherent correlations and patterns among complex datasets, particularly in time-series analysis.

Formation of halogenated disinfection byproducts in chlorinated real water during making hot beverage: Effect of sugar addition.

Chlorine disinfection is widely applied in drinking water treatment plant to inactivate pathogens in drinking water, but it unintentionally reacts with organic matter present in source waters and generates halogenated disinfection byproducts (DBPs). Sugar is one of the most commonly used seasoning in our diet. The addition of sugar could significantly improve the taste of the beverages; however, the effects of sugar on DBP formation and transformation remain unknown. In this study, the effects of sugar type and dose on the halogenated DBP formation in chlorinated boiled real tap water were evaluated during making hot beverages. We found that sugar can react with chlorine residual in tap water and generate halogenated DBPs. As the most commonly used table sugar, the addition of sucrose in the water sample at 100 or 500 mg/L as C could increase the level of total organic halogen (TOX) by ∼35%, when compared with the boiled tap water sample without sugar addition. In addition, fifteen reported and new polar brominated and chlorinated DBPs were detected and proposed from the reaction between chlorine and sucrose; accordingly, the corresponding transformation pathways were also proposed. Moreover, the DBP formation in the chlorinated boiled real tap water samples with the addition of xylose, glucose, sucrose, maltose and lactose were also investigated. By comparing with the TOX levels in the water samples with different sugar addition and their calculated TOX risk indexes, it was suggested that applying xylose as a sweetener in beverages could not only obtain a relatively high sweetness but also minimize the adverse effect inducing by halogenated DBPs during making hot beverages.

Ecological risk and machine learning based source analyses of trace metals in typical surface water.

Surface water is threatened by trace metal pollution due to increasing anthropogenic activities. Therefore, an appropriate source identification was essential to reduce the ecological risk posed by the given pollutants. In this study, shallow and deep learning approaches trained by a registered environmental dataset of discharge sources were employed to classify the potential emission sources of trace metals in the Elbe River, Germany. The results showed that the overall concentration rank of the given metals was Zn (226.5 ± 526.5 µg·L-1) > Ni (5.6 ± 4.7 µg·L-1) > Cu (5.3 ± 5.8 µg·L-1) > As (3.3 ± 3.7 µg·L-1) > Pb (2.9 ± 5.2 µg·L-1) > Cr (1.8 ± 2.5 µg·L-1) > Cd (1.3 ± 3.1 µg·L-1) in seven tributaries and the mainstream of the Elbe River, among which the tributary Triebisch had the highest risk quotient over 86. Random Forest outperformed other algorithms with the highest Kappa median values of 0.59 and the lowest Hamming-loss values of 0.22 in extraction of the majority voted class. Then, the source apportionment conducted by random forest suggested that wastewater disposal and metal industrial emissions were the source contributors in the tributary Triebisch (probabilities: 0.39, 0.3), upstream segment (0.45, 0.25), and downstream segment (0.32, 0.23) of the given river. Additional sources of mineral industry emissions were found in the upstream segment (0.21) and downstream segment (0.22). The data provided herein suggest that random forest would be an effective approach to identify pollutants in aquatic environments and could assist source-oriented adaptive management.

[Factor Analysis of Disinfection Byproduct Formation in Drinking Water Distribution Systems Through the Bayesian Network].

Disinfection byproducts (DBPs) in drinking water distribution systems are affected by multi-factors, such as basic water quality parameters, microbial community structures, and residual organic pollutants that cannot be removed by the water treatment process. The relationship between the above-mentioned factors that forms a complicated network structure, which causes the dominating factor that affects DBPs formation unclear. This study investigated the water quality in regional tap water in January-February 2021. Trihalomethanes were determined using P&T-GC-MS, and antibiotics and nitrosamines were determined using UPLC-MS/MS. Microbial communities were determined using Illumina 16S rRNA gene sequencing. A Bayesian network was constructed to evaluate the intercorrelation between the factors. Three species of trihalomethanes, six species of nitrosamines, 23 types of antibiotics, and 236 OTUs were detected in the tap water. The mass concentrations of trihalomethanes, nitrosamines, and antibiotics were 18.33-32.09 µg·L-1, 13.08-53.50 ng·L-1, and 47.92-210.33 ng·L-1, respectively. The dominant microbial orders were Rhizobiales and Caulobacterales. Based on the Bayesian-network inference, tetracycline, sulfonamides, and macrocyclic antibiotics were precursors of trihalomethanes, whereas tetracyclines were the nitrosamine precursor. The abundances of Caulobacterales and Corynebacteriales were both affected by antibiotics and associated with DBPs formation. The extracellular polymeric substances of these bacteria were highly suspected to be important DBPs precursors. The results of the proposed project revealed the internal relationship between multi-water-quality parameters and DBPs formation, which could provide a theoretical support to guarantee the safety of drinking water.

Transmission risk of SARS-CoV-2 in the watershed triggered by domestic wastewater discharge.

The outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has already become an unprecedented global pandemic. However, the transmission of SARS-CoV-2, especially the protected SARS-CoV-2 RNA (pRNA) with infectious particles in waterways, is still largely unexplored. In this study, we developed a model to estimate SARS-CoV-2 transmission from the risk source in the excretion of patients to the final exposure in surface water. The model simulated the spatial and temporal distribution of the viral pRNA concentrations in the surface water of the Elbe watershed from March 2020 to January 2021. The results show that the WWTPs with the maximum capacity of >10,000 population equivalents were responsible for 95% of the viral load discharged into the surface water. We estimated the pRNA concentrations in surface water to be 1.33 × 10-2 copies·L-1 on average in the watershed based on the model simulation on viral transmission. It had considerable variations in spatial and temporal scales, which are dominantly controlled by epidemic situations and virus transport with decay in water, respectively. A quantitative microbial risk assessment was conducted to estimate the viral infection probability from surface water ingestion with consideration of the influence of toilet usage frequency and gender/age population groups. All the infection probabilities in the study period were lower than the reference risk levels of 10-4 and 10-5. The individuals aged 15-34 years had the highest infection probability of 4.86 × 10-9 on average from surface water ingestion during swimming activities. The data provided herein suggest that the low pRNA concentrations and infection probability reflected that the waterways were unlikely to be a significant transmission route for SARS-CoV-2.

Global Trends and Drivers in Consumption- and Income-Based Emissions of Polycyclic Aromatic Hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) are a class of the most hazardous substances. As unavoidable byproducts of petrogenic and pyrogenic processes, their emissions are dominantly linked to various economic sectors. In international trade, not only final consumption but also primary input can transfer the emissions among regions. Therefore, a long-term impact assessment of the international trade on PAH global emissions based on the final consumption and primary input could significantly benefit worldwide PAH mitigation strategies. This study investigated the changes in consumption- and income-based PAH emissions and interregional flows of worldwide regions, using the latest available data from 1999 to 2014. Results show that in 2014, 16.8 and 10.1% of global PAH emissions were transferred by consumption and primary input through international trade. Meanwhile, the production-, consumption-, and income-based emissions in most regions were decreasing. Furthermore, from the consumption-based perspective, sub-Saharan Africa surpassed China and became the largest net exporter of consumption-based emissions. From the income-based perspective, the net income-based outflows of India and the rest of Asia increased significantly, indicating the income-based emission leakage in emerging markets. From the socioeconomic perspective, emission intensity dominated the global decline in PAH emissions. As the two main factors driving the increase in emissions, the primary input structure (41%) had a larger effect than the final demand level (28%) from 1999 to 2014. Therefore, global cooperation, through the mitigation strategies of reducing emission factors and improving international trade patterns, is posited as an efficient strategy to reduce PAH pollution and related health risks.

Modeling and elucidation the effects of iron deposits on chlorine decay and trihalomethane formation in drinking water distribution system.

Iron deposits stimulate chlorine consumption and trihalomethane (THM) formation in drinking water distribution systems through distinct mechanisms. In this study, a second-order chlorine decay model with a variable reaction-rate coefficient was developed to quantitatively evaluate the influences of iron deposits on chlorine reactions by considering the characteristics of dissolved organic matter (DOM), the type and dosages of deposits, as well as the initial chlorine concentrations. Based on a reliable prediction of residual chlorine, the concept that THM formation had a linear relationship with chlorine consumption was further validated by chlorination of DOM in the presence of iron deposits. Due to the catalysis influences, the reactivity of DOM towards chlorine decay or THM formation was accelerated. Although iron deposits activated the reactivity of DOM with bromine and chlorine, THM slightly shifted toward chlorinated species. Due to the adsorption influences, the maximum chlorine demand increased with the increasing deposit dosages whereas the extent of enhancement mainly relied on the DOM properties. Low-molecular-weight DOM with a hydrophilic characteristic was prone to be elevated by iron deposits. Based on the model simulation, approximately 20% of chlorine consumption and 37% of THM formation were contributed by deposits after 168 h reaction. The data provided herein emphasize the role of iron deposits in chlorine consumption and THM formation, which assist the water quality management in drinking water distribution systems.

Impact of green infrastructure on the mitigation of road-deposited sediment induced stormwater pollution.

As a vital stormwater pollution source, the pollutants associated with road-deposited sediment (RDS) have become a growing concern in urban water management. Green infrastructure has exhibited great potential in stormwater pollution mitigation, but is not comprehensively understood yet due to the influences of complex RDS-associated pollutant migration processes (i.e., build-up, wash-off, and discharge). In this study, a city-scale hydraulic and water quality model was used to analyze the migration and removal processes of four RDS-associated pollutants (total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP)) under different hydrological patterns, land-cover types, and green infrastructure installation locations. Results show that the antecedent dry-weather period was the main factor influencing RDS build-up, while the precipitation pattern strongly impacted RDS wash-off, discharge, and removal. The downstream-installed green infrastructures reduced the RDS-induced stormwater pollution by up to 68% and relieved the pollution-mitigation pressure of the studied drainage networks by almost 50%. The TSS and COD removal rates were higher (62.22-68.09%) near green space, while those of TN and TP were higher around buildings and roads (40.00-62.50%). Sensitivity analysis indicated that seven parameters regarding the surface layer characteristics and soil texture class strongly impacted the pollution-mitigation performance among the 31 technical parameters of green infrastructure. The results of this study would assist urban water management by optimizing green infrastructure for stormwater pollution mitigation.

Environmental behavior and potential driving force of bisphenol A in the Elbe River: A long-term trend study.

As an endocrine disruptor, a deep understanding of the environmental behavior and potential driving force of bisphenol A (BPA) is helpful for developing a mitigation strategy and reducing the exposure risk to the public. Based on long-term monitoring data from 2004 to 2016, this study systematically evaluated the long-term trend, periodic characteristics, and potential risks of BPA in the Elbe River in the state of Saxony, Germany. Multiple advanced statistical approaches were employed for data mining. Pettitt's test was used to determine the main change points of BPA that occurred from 2008 to 2011. The Mann-Kendall test showed a decreasing trend in BPA concentrations (slope: -0.087 to -0.112, P < 0.05) over the past 13 years, particularly in the wet seasons (slope: -0.730 to -0.038, P < 0.05). Wavelet analysis revealed similar periodicities of BPA among stations (which experienced 4-5 oscillations in the first major period). The ARIMA model forecasted the mean BPA concentration as ranging from 9 to 41 ng L-1 in the subsequent 3 months, which was similar to that in the last 3 months (20-42 ng L-1). Besides, the highest hazard quotients (>0.3) were documented for Chironomus riparius, Oryzias latipes, Potamopyrgus antipodarum, and Hydra vulgar, which indicates that BPA may threaten their growth and development. The hazard index values for non-cancer risk of BPA no greater than 6.47 × 10-9 (HQ far below 1), which suggests that BPA did not pose a significant threat to human health. Because BPA pollution is closely related to industrial activities, a long-term decline in BPA concentrations could be attributed to the reduced number of factories, limited discharge, and improved decontamination efficiency. However, the minimal change in the BPA concentration in the near future could reflect periodic fluctuations.

Expert consensus on Tongsaimai Tablets/Capsules in treatment of peripheral vascular diseases in clinical practice / 中国中药杂志

Tongsaimai Tablets/Capsules are composed of Lonicerae Japonicae Flos, Angelicae Sinensis Radix, Achyranthis Bidentatae Radix, Codonopsis Radix, Dendrobii Caulis, Astragali Radix, Scrophulariae Radix, and Glycyrrhizae Radix et Rhizoma, and are effective in promoting blood circulation, removing blood stasis, supplementing Qi, and nourishing Yin. It is widely used in the treatment of peripheral vascular diseases. With 40 years of clinical application, it has accumulated substantial research data and application experience. Its good clinical efficacy and pharmacoeconomic benefits in improving the clinical symptoms of peripheral vascular diseases have been confirmed by relevant research. Meanwhile, this drug has also been recommended by many expert consensus, guidelines, and teaching materials, serving as one of the most commonly used Chinese patent medicines in clinical practice. To further improve the understanding of the drug among clinicians and properly guide its clinical medication, the China Association of Chinese Medicine took the lead and organized experts to jointly formulate this expert consensus. Based on the questionnaire survey of clinicians and the systematic review of research literature on Tongsaimai Tablets/Capsules with clinical problems in the PICO framework, the consensus, combined with expert experience, concludes recommendations or consensus suggestions by GRADE system with the optimal evidence available through the nominal group technique. This consensus defines the indications, usage, dosage, course of treatment, medication time, combined medication, and precautions of Tongsaimai Tablets/Capsules in the treatment of peripheral vascular diseases, and explains the safety of its clinical application. It is recommended for clinicians and pharmacists in the peripheral vascular department(vascular surgery), traditional Chinese medicine surgery(general surgery), and endocrinology department of hospitals at all levels in China.

Pharmacological Mechanism of Wumeiwan in Treating Lung Metastasis of Breast Cancer / 中国实验方剂学杂志

Objective:To explore the potential target and mechanism of Wumeiwan in the treatment of lung metastasis of breast cancer by network pharmacological analysis and experimental verification. Method:The databases of active ingredients and targets of Wumeiwan were established through Traditional Chinese Medicine Systems Pharmacology（TCMSP） Database and Analysis Platform，and the targets of lung metastasis of breast cancer were established through the GeneCards database and Online Mendelian Inheritance in Man（OMIM） database，and the data of Chinese medicine targets and disease targets were matched. Cytoscape 3.6.0 software was used to establish the network analysis of traditional Chinese medicine-active ingredients-therapeutic targets，and the interaction relationship between key target proteins was analyzed by STRING database. Target gene ontology（GO） analysis and Kyoto Encyclopedia of Genes and Genomes（KEGG） signal pathway enrichment analysis were performed by using the Biological Information Annotation Database. Result:A total of 108 possible important targets for Wumeiwan in the treatment of lung metastasis of breast cancer were found，including interleukin 6（IL6），cysteine aspartate-specific protease-3（CASP3），vascular endothelial growth factor A（VEGFA），epidermal growth factor receptor（EGFR），mitogen-activated protein kinase（MAPK8）， and others. GO enrichment analysis yielded 29 cell components（CC），1 218 biological processes（BP） and 125 molecular functions（MF） related to lung metastasis of breast cancer，and KEGG enrichment analysis yielded 118 pathways related to lung metastasis of breast cancer（<italic>P<</italic>0.05），including MAPK signaling pathway and apoptosis pathway. <italic>In vitro</italic> experiments showed that cinnamaldehyde， the active ingredient of Wumeiwan， could induce apoptosis，inhibit proliferation and migration of MCF7 cells，partially validating the predicted results of network pharmacology to a certain extent. Conclusion:The therapeutic effect of Wumeiwan on lung metastasis of breast cancer may be multi-target，multi-pathway and multi-mechanism. The results of this study provide more evidence for the clinical application of Wumeiwan.

[Systematic review and trial sequential analysis of randomized clinical trial of Hongjin Xiaojie Capsules for treatment of hyperplastic disease of breast].

To systemically evaluate the clinical efficacy and safety of Hongjin Xiaojie Capsules for hyperplastic disease of breast(HDBA), so as to provide the evidence for its clinical application. The inclusion criteria are the RCT of single administration of Hongjin Xiaojie Capsules for treatment of HDBA. We retrieved following databases(CNKI, WanFang, VIP, SinoMed, Cochrane Library and PubMed) from their inception to October 1, 2019. Two researchers independently screened out literatures and extracted data, and assessed the methodological quality of eligible RCT according to the criteria in Cochrane Handbook for Systematic Reviews of Interventions. RevMan 5.3 was used for data analysis, binary data was summarized by risk ratio(RR) with confidence intervals(CI) of 95%, and continuous data were summarized by mean difference(MD) with CI of 95%. To estimate the sample size of systematic review, trial sequential analysis(TSA) was performed base on software TSA v0.9 version. Totally 14 RCTs were included, involving 3 057 patients. The results of Meta-analysis showed a significantly higher cure rate(RR=1.13, 95%CI[1.03, 1.25], P=0.01) and higher total effective rate(RR=1.09, 95%CI[1.05, 1.13], P<0.000 1) in Hongjin Xiaojie Capsules group than those in the Juyuansuan Tamoxifen group. The incidence of adverse events was significantly higher in Juyuansuan Tamoxifen group than that in Hongjin Xiaojie Capsules group(RR=0.28 95%CI[0.16, 0.49], P<0.001), and the adverse events included nausea, vomiting, abdominal pain, diarrhea, irregular menstruation, amenorrhea, unclear vision, dizziness and headache. The TSA for the cure rate demonstrated that the current available data reached the expected value. However, due to the low effect intensity of evidence, the pooled results might be affected by high risk bias of trials. The quality of evidence of included trials was generally low or very low. Inverted funnel diagram showed possible publication bias. This review suggested that Hongjin Xiaojie Capsules were potentially effective and safe in treatment of HDBA, especially, the incidences of drug-related adverse events from Hongjin Xiaojie Capsules were significantly lower than those from tamoxifen. However, because of lack of high-quality evidence for drawing a conclusion, more rigorously designed and high-quality trials are needed to confirm the efficacy and safety of Hongjin Xiaojie Capsules.

Characterizing the anthropogenic-induced trace elements in an urban aquatic environment: A source apportionment and risk assessment with uncertainty consideration.

The spatial distribution of water quality status, especially in water bodies near intensively urbanized areas, is tightly associated with patterns of human activities. For establishing a robust assessment of the sediment quality in an urban aquatic environment, the source apportionment and risk assessment of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg, and Pb in sediments from an anthropogenic-influenced lake were carried out with considering uncertainties from the analysis methods, random errors in the sample population and the spatial sediment heterogeneity. The distribution analysis of the trace metals with inverse distance weighting-determined method showed that the pollutants were concentrated in the middle and southern areas of the lake. According to the self-organizing map and constrained positive matrix factorization receptor model, agricultural sources (24.8%), industrial and vehicular sources (42.5%), and geogenic natural sources (32.7%) were the primary contributors to the given metals. The geogenic natural had the largest random errors, but the overall result was reliable according to the uncertainty analysis. Furthermore, the stochastic contamination and ecological risk models identified a moderate/considerable contamination level and a moderate ecological risk to the urban aquatic ecosystem. With consideration of uncertainties from the spatial heterogeneity, the contamination level of Hg, and the ecological risk of Cd in had a 20-30% probability of the increase.