Causal effects between circulating immune cells and heart failure: evidence from a bidirectional Mendelian randomization study.

BACKGROUND: Heart failure (HF) is a prevalent cardiac condition characterized by high mortality and morbidity rates. Immune cells play a pivotal role as crucial biomarkers in assessing the overall immune status of individuals. However, the causal relationship between circulating immune cells and the pathogenesis of HF remains an area requiring further investigation. OBJECTIVES: The aim of this study was to investigate the genetic interactions between circulating immune cells and HF, and to further elucidate the genetic associations between different lymphocyte subsets and HF. METHODS: We obtained genetic variants associated with circulating immune cells as instrumental variables (IVs) from the Blood Cell Consortium and publicly available HF summary data. We conducted additional subsets analyses on lymphocyte counts. Our study utilized two-sample and multivariate Mendelian randomization (MVMR) analysis to investigate the causal effect of immune cells on HF. The primary analysis employed inverse variance weighting (IVW) and was complemented by a series of sensitivity analyses. RESULTS: The findings of the study showed that the IVW model demonstrated a significant correlation between an elevation in lymphocyte count and a decreased risk of HF (OR = 0.97, 95% CI, 0.94 - 1.00, P = 0.032). However, no such correlation was evident in the MVMR analysis for lymphocytes and HF. Furthermore, the examination of the lymphocyte subsets indicated that an increase in CD39+ CD4+ T-cell counts was notably linked to a reduced risk of HF (OR = 0.96, 95% CI, 0.95 - 0.98, P = 0.0002). The MVMR results confirmed that the association between CD39+ CD4+ T-cell counts and HF remained significant. There was no substantial evidence of reverse causality observed between circulating immune cells and HF. CONCLUSION: Our MR research provided evidence for a causal relationship between lymphocyte cell and HF. Subsets analyses revealed a causal relationship between CD39+ CD4+ T lymphocytes and HF. These findings will facilitate a future understanding of the mechanisms underlying HF.

Potential Value of Probiotics on Lipid Profiles in Hyperlipidemia and Healthy Participants: Systematic Review and Meta-Analysis.

Objective: Many randomized controlled trials (RCTs) have reported the effect of probiotics on reducing plasma lipids with inconsistent results. An explicit systematic review and meta-analysis were conducted in this study to evaluate the effect of probiotics on the lipid profile of healthy and hyperlipidemia participants. Methods: A comprehensive literature search of RCTs was conducted using PubMed, Embase, World Health Organization (WHO) Global Index Medicus, WHO clinical trial registry, and Clinicaltrials.gov. Inclusion criteria included RCTs comparing the use of any strain of a specified probiotic with the placebo control group. The change in lipid profiles was analyzed. Results: The probiotics can decrease the total cholesterol (TC) level in hyperlipidemia participants but not healthy persons (MD = -0.43, 95% CI -0.60 - -0.25, P < .01; MD = -0.09, 95% CI -0.26 - 0.08, P > .05). Probiotics did not reduce high-density lipoprotein cholesterol (HDL-C) in patients with hyperlipidemia or healthy people (MD = -0.01, 95% CI -0.09 - 0.07, P > .05; MD = 0.02, 95% CI -0.04 - 0.09, P > .05). Furthermore, probiotics can reduce the low-density lipoprotein cholesterol (LDL-C) level both in hyperlipidemia and healthy persons (MD = -0.34, 95% CI -0.43 - -0.26, P < .01; MD = -0.15, 95% CI -0.28 - -0.02, P < .05). Lastly, the effect of probiotics on reducing triglyceride (TG) levels was significant in hyperlipidemia persons but not in the healthy population (MD = -0.20, 95% CI -0.37 - -0.04, P < .01; MD = -0.01, 95% CI -0.02 - 0.04, P > .05). Conclusions: Through our analysis, the effect of probiotics on lowering plasma lipid was more obvious in hyperlipidemia participants than healthy population. However, further studies are required to confirm the findings due to pronounced clinical heterogeneity.

Identification of cuproptosis-related biomarkers in dilated cardiomyopathy and potential therapeutic prediction of herbal medicines.

Background: Dilated cardiomyopathy (DCM) is one of the significant causes of heart failure, and the mechanisms of metabolic ventricular remodelling due to disturbances in energy metabolism are still poorly understood in cardiac pathology. Understanding the biological mechanisms of cuproptosis in DCM is critical for drug development. Methods: The DCM datasets were downloaded from Gene Expression Omnibus, their relationships with cuproptosis-related genes (CRGs) and immune signatures were analyzed. LASSO, RF, and SVM-RFE machine learning algorithms were used to identify signature genes and the eXtreme Gradient Boosting (XGBoost) model was used to assess diagnostic efficacy. Molecular clusters of CRGs were identified, and immune Infiltration analysis was performed. The WGCNA algorithm was used to identify specific genes in different clusters. In addition, AUCell was used to analyse the cuproptosis scores of different cell types in the scRNA-seq dataset. Finally, herbal medicines were predicted from an online database, and molecular docking and molecular dynamics simulations were used to support the confirmation of the potential of the selected compounds. Results: We identified dysregulated cuproptosis genes and activated immune responses between DCM and healthy controls. Two signature genes (FDX1, SLC31A1) were identified and performed well in an external validation dataset (AUC = 0.846). Two molecular clusters associated with cuproptosis were further defined in DCM, and immune infiltration analysis showed B-cell naive, Eosinophils, NK cells activated and T-cell CD4 memory resting is significant immune heterogeneity in the two clusters. AUCell analysis showed that cardiomyocytes had a high cuproposis score. In addition, 19 and 3 herbal species were predicted based on FDX1 and SLC31A1. Based on the molecular docking model, the natural compounds Rutin with FDX1 (-9.3 kcal/mol) and Polydatin with SLC31A1 (-5.5 kcal/mol) has high stability and molecular dynamics simulation studies further validated this structural stability. Conclusion: Our study systematically illustrates the complex relationship between cuproptosis and the pathological features of DCM and identifies two signature genes (FDX1 and SLC31A1) and two natural compounds (Rutin and Polydatin). This may enhance our diagnosis of the disease and facilitate the development of clinical treatment strategies for DCM.

Construction and Evaluation of Neural Network Correlation Model between Syndrome Elements and Physical and Chemical Indexes of Unstable Angina Pectoris Complicated with Anxiety.

Objective: Syndrome elements are regarded as the smallest unit of syndrome differentiation, which is characterized by indivisibility and random combination. Therefore, it can well fit the goal of syndrome differentiation and unity. Methods: Clinical physicochemical indicators are important references for disease diagnosis, but they are often not used too much in the process of TCM syndrome differentiation. In the era of intelligence, communicating TCM syndrome differentiation at the macro level with physiological and pathological processes at the micro level (i.e., these clinical physicochemical indicators) is an effective tool to realize intelligent medicine. Taking the collected relevant clinical physical and chemical indexes as the research object, on the basis of routine t-test and nonparametric test, logistic regression model is used to mine the main syndrome elements, and neural network multilayer perceptron is used to predict the feature model. Results: Compared with non-blood stasis patients, there were significant differences in HGB, PLT, Pt, PTA, Na+, TG, LDL, BNP, LVEDd, and EF in blood stasis patients. Taking blood stasis as the dependent variable and the above physical and chemical indexes with statistical significance (P < 0.05) as independent variables. Compared with non-qi depression patients, there were significant differences in atpp, TG, TC, LDL, LVESD, and FS in qi depression patients (P < 0.05). Taking Yin deficiency as dependent variable and the above physical and chemical indexes (Hgb, APTT, CKMB, LVEDd, and LVPW) with statistical significance (P < 0.05) as independent variables, binary logistic regression analysis was carried out. Conclusion: The combination pattern of physical and chemical indexes obtained from the neural network model provides a clinical reference basis for identifying the syndrome elements of unstable angina pectoris complicated with anxiety, such as blood stasis, qi depression, Qi deficiency, yin deficiency, phlegm turbidity, and qi stagnation.

Unraveling the molecular mechanisms of hyperlipidemia using integrated lncRNA and mRNA microarray data.

Long non-coding RNAs (lncRNAs) have key roles in various diseases; however, their functions in hyperlipidemia (HLP) have remained elusive. In the present study, microarray technology was utilized to analyze the differential expression of lncRNAs and mRNAs in liver tissues of apolipoprotein E-/- mice as a model of HLP compared with control mice. A total of 104 and 96 differentially expressed lncRNAs and mRNAs, respectively, were identified. Differentially expressed genes were significantly enriched in biological processes such as nitric oxide biosynthesis, innate immune response and inflammatory response. Finally, two pairs of target genes and 38 transcription factors with regulatory functions in HLP were predicted based on the lncRNA and mRNA co-expression network. The lncRNA expression profile was significantly altered in liver tissues of the mouse model of HLP and may provide novel targets for research into treatments.

Uncovering the molecular mechanisms between heart failure and end-stage renal disease via a bioinformatics study.

Background: Heart failure (HF) is not only a common complication in patients with end-stage renal disease (ESRD) but also a major cause of death. Although clinical studies have shown that there is a close relationship between them, the mechanism of its occurrence is unclear. The aim of this study is to explore the molecular mechanisms between HF and ESRD through comprehensive bioinformatics analysis, providing a new perspective on the crosstalk between these two diseases. Methods: The HF and ESRD datasets were downloaded from the Gene Expression Omnibus (GEO) database; we identified and analyzed common differentially expressed genes (DEGs). First, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVA) were applied to explore the potential biological functions and construct protein-protein interaction (PPI) networks. Also, four algorithms, namely, random forest (RF), Boruta algorithm, logical regression of the selection operator (LASSO), and support vector machine-recursive feature elimination (SVM-RFE), were used to identify the candidate genes. Subsequently, the diagnostic efficacy of hub genes for HF and ESRD was evaluated using eXtreme Gradient Boosting (XGBoost) algorithm. CIBERSORT was used to analyze the infiltration of immune cells. Thereafter, we predicted target microRNAs (miRNAs) using databases (miRTarBase, TarBase, and ENOCRI), and transcription factors (TFs) were identified using the ChEA3 database. Cytoscape software was applied to construct mRNA-miRNA-TF regulatory networks. Finally, the Drug Signatures Database (DSigDB) was used to identify potential drug candidates. Results: A total of 68 common DEGs were identified. The enrichment analysis results suggest that immune response and inflammatory factors may be common features of the pathophysiology of HF and ESRD. A total of four hub genes (BCL6, CCL5, CNN1, and PCNT) were validated using RF, LASSO, Boruta, and SVM-RFE algorithms. Their AUC values were all greater than 0.8. Immune infiltration analysis showed that immune cells such as macrophages, neutrophils, and NK cells were altered in HF myocardial tissue, while neutrophils were significantly correlated with all four hub genes. Finally, 11 target miRNAs and 10 TFs were obtained, and miRNA-mRNA-TF regulatory network construction was performed. In addition, 10 gene-targeted drugs were discovered. Conclusion: Our study revealed important crosstalk between HF and ESRD. These common pathways and pivotal genes may provide new ideas for further clinical treatment and experimental studies.

Immune Mechanism, Gene Module, and Molecular Subtype Identification of Astragalus Membranaceus in the Treatment of Dilated Cardiomyopathy: An Integrated Bioinformatics Study.

Astragalus membranaceus has complex components as a natural drug and has multilevel, multitarget, and multichannel effects on dilated cardiomyopathy (DCM). However, the immune mechanism, gene module, and molecular subtype of astragalus membranaceus in the treatment of DCM are still not revealed. Microarray information of GSE84796 was downloaded from the GEO database, including RNA sequencing data of seven normal cardiac tissues and ten DCM cardiac tissues. A total of 4029 DCM differentially expressed genes were obtained, including 1855 upregulated genes and 2174 downregulated genes. GO/KEGG/GSEA analysis suggested that the activation of T cells and B cells was the primary cause of DCM. WGCNA was used to obtain blue module genes. The blue module genes are primarily ADCY7, BANK1, CD1E, CD19, CD38, CD300LF, CLEC4E, FLT3, GPR18, HCAR3, IRF4, LAMP3, MRC1, SYK, and TLR8, which successfully divided DCM into three molecular subtypes. Based on the CIBERSORT algorithm, the immune infiltration profile of DCM was analyzed. Many immune cell subtypes, including the abovementioned immune cells, showed different levels of increased infiltration in the myocardial tissue of DCM. However, this infiltration pattern was not obviously correlated with clinical characteristics, such as age, EF, and sex. Based on network pharmacology and ClueGO, 20 active components of Astragalus membranaceus and 40 components of DMCTGS were obtained from TCMSP. Through analysis of the immune regulatory network, we found that Astragalus membranaceus effectively regulates the activation of immune cells, such as B cells and T cells, cytokine secretion, and other processes and can intervene in DCM at multiple components, targets, and levels. The above mechanisms were verified by molecular docking results, which confirmed that AKT1, VEGFA, MMP9, and RELA are promising potential targets of DCM.

Assessment ecological risk of heavy metal caused by high-intensity land reclamation in Bohai Bay, China.

The article examines the detailed spatial and temporal distributions of coastal reclamation in the northwest coast of Bohai Bay experiencing rapid coastal reclamation in China from 1974 to 2010 in annual intervals. Moreover, soil elements properties and spatial distribution in reclaimed area and inform the future coastal ecosystems management was also analyzed. The results shows that 910.7 km2 of coastal wetlands have been reclaimed and conversed to industrial land during the past 36 years. It covers intertidal beach, shallow sea and island with a percentage of 76.0%, 23.5% and 0.5%, respectively. The average concentration of Mn is 686.91mg/kg and the order of concentration of heavy metal are Cr>Zn>As>Ni>Cu>Pb>Cd>Hg. We used the "space for time substitution" method to test the soil properties changes after reclamation. The potential ecological risk of heavy metal is in low level and the risk of Cd and As is relatively higher. The ecosystem-based coastal protection and management are urgent to support sustainable coastal ecosystems in Bohai bay in the future.

Metabolomics and Its Application in the Development of Discovering Biomarkers for Osteoporosis Research.

Osteoporosis is a progressive skeletal disorder characterized by low bone mass and increased risk of fracture in later life. The incidence and costs associated with treating osteoporosis cause heavy socio-economic burden. Currently, the diagnosis of osteoporosis mainly depends on bone mineral density and bone turnover markers. However, these indexes are not sensitive and accurate enough to reflect the osteoporosis progression. Metabolomics offers the potential for a holistic approach for clinical diagnoses and treatment, as well as understanding of the pathological mechanism of osteoporosis. In this review, we firstly describe the study subjects of osteoporosis and bio-sample preparation procedures for different analytic purposes, followed by illustrating the biomarkers with potentially predictive, diagnosis and pharmaceutical values when applied in osteoporosis research. Then, we summarize the published metabolic pathways related to osteoporosis. Furthermore, we discuss the importance of chronological data and combination of multi-omics in fully understanding osteoporosis. The application of metabolomics in osteoporosis could provide researchers the opportunity to gain new insight into the metabolic profiling and pathophysiological mechanisms. However, there is still much to be done to validate the potential biomarkers responsible for the progression of osteoporosis and there are still many details needed to be further elucidated.

Triptolide Modulates TREM-1 Signal Pathway to Inhibit the Inflammatory Response in Rheumatoid Arthritis.

Triptolide (TP), an active component isolated from Tripterygiumwilfordii Hook F, has therapeutic potential against rheumatoid arthritis (RA). However, the underlying molecular mechanism has not been fully elucidated. The aim of this study is to investigate the mechanisms of TP acting on RA by combining bioinformatics analysis with experiment validation. The human protein targets of TP and the human genes of RA were found in the PubChem database and NCBI, respectively. These two dataset were then imported into Ingenuity Pathway Analysis (IPA) software online, and then the molecular network of TP on RA could be set up and analyzed. After that, both in vitro and in vivo experiments were done to further verify the prediction. The results indicated that the main canonical signal pathways of TP protein targets networks were mainly centered on cytokine and cellular immune signaling, and triggering receptors expressed on myeloid cells (TREM)-1 signaling was searched to be the top one shared signaling pathway and involved in the cytokine and cellular immune signaling. Further in vitro experiments indicated that TP not only remarkably lowered the levels of TREM-1 and DNAX-associated protein (DAP)12, but also significantly suppressed the activation of janus activating kinase (JAK)2 and signal transducers and activators of transcription (STAT)3. The expression of tumor necrosis factor (TNF)-α, interleukin (IL)-1ß and IL-6 in lipopolysaccharides (LPS)-stimulated U937 cells also decreased after treatment with TP. Furthermore, TREM-1 knockdown was able to interfere with the inhibition effects of TP on these cytokines production. In vivo experiments showed that TP not only significantly inhibited the TREM-1 mRNA and DAP12 mRNA expression, and activation of JAK2 and STAT3 in ankle of rats with collagen-induced arthritis (CIA), but also remarkably decreased production of TNF-α, IL-1ß and IL-6 in serum and joint. These findings demonstrated that TP could modulate the TREM1 signal pathway to inhibit the inflammatory response in RA.

In Vivo Delivery Systems for Therapeutic Genome Editing.

Therapeutic genome editing technology has been widely used as a powerful tool for directly correcting genetic mutations in target pathological tissues and cells to cure of diseases. The modification of specific genomic sequences can be achieved by utilizing programmable nucleases, such as Meganucleases, zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly-interspaced short palindromic repeat-associated nuclease Cas9 (CRISPR/Cas9). However, given the properties, such as large size, negative charge, low membrane penetrating ability, as well as weak tolerance for serum, and low endosomal escape, of these nucleases genome editing cannot be successfully applied unless in vivo delivery of related programmable nucleases into target organisms or cells is achieved. Here, we look back at delivery strategies having been used in the in vivo delivery of three main genome editing nucleases, followed by methodologies currently undergoing testing in clinical trials, and potential delivery strategies provided by analyzing characteristics of nucleases and commonly used vectors.

Molecular Selection, Modification and Development of Therapeutic Oligonucleotide Aptamers.

Monoclonal antibodies are the dominant agents used in inhibition of biological target molecules for disease therapeutics, but there are concerns of immunogenicity, production, cost and stability. Oligonucleotide aptamers have comparable affinity and specificity to targets with monoclonal antibodies whilst they have minimal immunogenicity, high production, low cost and high stability, thus are promising inhibitors to rival antibodies for disease therapy. In this review, we will compare the detailed advantages and disadvantages of antibodies and aptamers in therapeutic applications and summarize recent progress in aptamer selection and modification approaches. We will present therapeutic oligonucleotide aptamers in preclinical studies for skeletal diseases and further discuss oligonucleotide aptamers in different stages of clinical evaluation for various disease therapies including macular degeneration, cancer, inflammation and coagulation to highlight the bright commercial future and potential challenges of therapeutic oligonucleotide aptamers.

[A correlation research on Chinese medical syndromes of chronic heart failure and various complications].

OBJECTIVE: To study the correlation between various complications of chronic heart failure (CHF) patients and Chinese medical syndromes, thus indicating distribution laws of Chinese medical syndromes in various complications of CHF patients. METHODS: Chinese medical syndrome typing was performed in 630 CHF patients by cross-sectional study of the demographic data, history of present diseases, related information on Chinese medical four diagnostic methods, and the distribution of complications. Logistic regression analysis was used to determine the correlation of various complications of CHF patients and Chinese medical syndromes. RESULTS: In this study, recruited were common complications such as hypertension, diabetes, arrhythmia, hyperlipemia, and cerebral vascular accident, and so on. Main syndromes were sequenced as qi deficiency syndrome, blood stasis syndrome, water retention syndrome, yin deficiency syndrome, phlegm turbid syndrome, yang deficiency syndrome. Results of Logistic regression analysis indicated that correlation existed between common complications and Chinese medical syndromes. In CHF complicated hypertension patients, Logistic regression analysis showed qi deficiency syndrome and yang deficiency syndrome were negatively correlated with hypertension (P < 0.05). In CHF complicated diabetes patients, Logistic regression analysis showed phlegm turbid syndrome and water retention syndrome were positively correlated with diabetes (P < 0.05). In CHF complicated arrhythmia patients, there was no statistical difference in the distribution of each syndrome (P > 0.05). In CHF complicated hyperlipemia patients, Logistic regression analysis showed qi deficiency syndrome and water retention syndrome were negatively correlated with hyperlipemia (P < 0.05), while blood stasis syndrome, yin deficiency syndrome, and phlegm turbid syndrome were positively correlated with hyperlipemia (P < 0.01). In CHF complicated cerebral vascular accident patients, Logistic regression analysis showed qi deficiency syndrome and yang deficiency syndrome were negatively correlated with cerebral vascular accident (P < 0.01, P < 0.05). CONCLUSIONS: There existed certain correlations between complications of CHF and the distribution of main Chinese medical syndromes. It could be used as guidance for treating CHF and its various complications by Chinese medicine and pharmacy.

Triterpenoid resinous metabolites from the genus Boswellia: pharmacological activities and potential species-identifying properties.

The resinous metabolites commonly known as frankincense or olibanum are produced by trees of the genus Boswellia and have attracted increasing popularity in Western countries in the last decade for their various pharmacological activities. This review described the pharmacological specific details mainly on anti-inflammatory, anti-carcinogenic, anti-bacterial and apoptosis-regulating activities of individual triterpenoid together with the relevant mechanism. In addition, species-characterizing triterpenic markers with the methods for their detection, bioavailability, safety and other significant properties were reviewed for further research.

Metabolomic identification of diagnostic plasma biomarkers in humans with chronic heart failure.

Chronic heart failure (CHF), as a progressive clinical syndrome, is characterized by failure of enough blood supply from the heart to meet the body's metabolic demands, and there is intense interest in identifying novel biomarkers that could make contributions to the diagnosis of CHF. Metabolomics, compared with current diagnostic approaches, could investigate many metabolic perturbations within biological systems. The overarching goal of the work discussed here is to apply a high-throughput approach to identify metabolic signatures and plasma diagnostic biomarkers underlying CHF by 1H-NMR spectroscopy. Plasma samples from 39 patients with CHF and 15 controls were analyzed by NMR spectroscopy. After processing the data, orthogonal partial least square discriminant analysis (OPLS-DA) was performed. The statistical model revealed good explained variance and predictability, and the diagnostic performance assessed by leave-one-out analysis exhibited 92.31% sensitivity and 86.67% specificity. The OPLS-DA score plots of spectra revealed good separation between case and control on the level of metabolites, and multiple biochemical changes indicated hyperlipidemia, alteration of energy metabolism and other potential biological mechanisms underlying CHF. It was concluded that the NMR-based metabolomics approach demonstrated good performance to identify diagnostic plasma markers and provided new insights into metabolic process related to CHF.

Application of plant metabonomics in quality assessment for large-scale production of traditional Chinese medicine.

The curative effects of traditional Chinese medicines are principally based on the synergic effect of their multi-targeting, multi-ingredient preparations, in contrast to modern pharmacology and drug development that often focus on a single chemical entity. Therefore, the method employing a few markers or pharmacologically active constituents to assess the quality and authenticity of the complex preparations has a number of severe challenges. Metabonomics can provide an effective platform for complex sample analysis. It is also reported to be applied to the quality analysis of the traditional Chinese medicine. Metabonomics enables comprehensive assessment of complex traditional Chinese medicines or herbal remedies and sample classification of diverse biological statuses, origins, or qualities in samples, by means of chemometrics. Identification, processing, and pharmaceutical preparation are the main procedures in the large-scale production of Chinese medicinal preparations. Through complete scans, plants metabonomics addresses some of the shortfalls of single analyses and presents a considerable potential to become a sharp tool for traditional Chinese medicine quality assessment.

[Thirty years of US long-term ecological research: characteristics, results, and lessons learned of--taking the Virginia Coast Reserve as an example].

In order to observe and understand long-term and large-scale ecological changes, the US National Science Foundation initiated a Long-Term Ecological Research (LTER) program in 1980. Over the past 30 years, the US LTER program has achieved advances in ecological and social science research, and in the development of site-based research infrastructure. This paper attributed the success of the program to five characteristics, i.e., 1) consistency of research topics and data across the network, 2) long-term time scale of both the research and the program, 3) flexibility in research content and funding procedures, 4) growth of LTER to include international partners, new disciplines such as social science, advanced research methods, and cooperation among sites, and 5) sharing of data and educational resources. The Virginia Coast Reserve LTER site was taken as an example to illustrate how the US LTER works at site level. Some suggestions were made on the China long-term ecological research, including strengthening institution construction, improving network and inter-site cooperation, emphasizing data quality, management, and sharing, reinforcing multidisciplinary cooperation, and expanding public influence.

Green space changes and planning in the capital region of China.

Green space plays an important role in complex urban ecosystems and provides significant ecosystem services with environmental, aesthetic, recreational and economic benefits. Beijing is the capital city of China and has a large population of about 15.81 million. Construction of green spaces is an important part of sustainable development in Beijing. To attain the sustainable development of Beijing as a capital city, an international city, a historical cultural city, and a living amenity city, this article attempts to develop a comprehensive plan of green space development both at the municipal and regional levels. At the municipal level of Beijing, based on the study of green space changes, and taking physical geographic conditions and historical context into account, we propose to establish green barriers in the mountainous area, and plan a comprehensive green space pattern composed of one city, two rings, three networks, eight water areas, nine fields, and several patches in the plain area. At the regional level of the Capital Circle Region, integrating the characteristics and causes of main environmental issues, we design a macroscopic pattern--"barriers by mountains in the northwest," "seaward open spaces in the southeast," "grassland-forest-field-coast zones," and "green-blue symphony"--for ecological restoration and green space construction. Finally, we discuss the principles necessary to implement green space planning considering adaptation to local conditions, composite function exploitation, interregional equity and integrated planning.

Probe into the method of regional ecological risk assessment-a case study of wetland in the Yellow River Delta in China.

Ecological risk assessment (ERA) is a new field of study for evaluating the risks associated with a possible eco-environmental hazard under uncertainty. Regional ERA is more complex than general ERA, as it requires that risk receptors, risk sources, risk exposure, uncertainty and especially spatial heterogeneity all be taken into account. In this paper, a five-step process of regional ERA is developed and tested through a wetland case study in the Yellow River Delta in China. First, indices and formulas are established for measuring degrees of ecological risk and damage to ecosystems. Using a combination of remote sensing data, historical records and survey data, and with the assistance of GIS techniques, the indices and formulas are then applied to the wetland in the study area. On the basis of the assessment results, we propose a number of countermeasures for the various risk zones in the Yellow River Delta.