Assessing the impacts of phosphorus inactive clay on phosphorus release control and phytoplankton community structure in eutrophic lakes

Addressing the challenge that phosphorus is the key factor and cause for eutrophication, we evaluated the phosphorus release control performance of a new phosphorus inactive clay (PIC) and compared with Phoslock(®). Meanwhile, the impacts of PIC and Phoslock(®) on phytoplankton abundance and community structure in eutrophic water were also discussed. With the dosage of 40 mg/L, PIC effectively removed 97.7% of total phosphorus (TP) and 98.3% of soluble reactive phosphorus (SRP) in eutrophic waters. In sediments, Fe/Al-phosphorus and organic phosphorus remained stable whereas Ca-phosphorus had a significant increase of 13.1%. The results indicated that PIC may form the active overlay at water-sediment interface and decrease the bioavailability of phosphorus. The phytoplankton abundance was significantly reduced by PIC and decreased from (1.0-2.4) × 10(7) cells/L to (1.3-4.3) × 10(6) cells/L after 15 d simultaneous experiment. The phytoplankton community structure was also altered, where Cyanobacteria and Bacillariophyceae were the most inhibited and less dominant due to their sensitivity to phosphorus. After PIC treatment, the residual lanthanum concentration in water was 1.44-3.79 μg/L, and the residual aluminium concentration was low as 101.26-103.72 μg/L, which was much less than the recommended concentration of 200 μg/L. This study suggests that PIC is an appropriate material for phosphorus inactivation and algal bloom control, meaning its huge potential application in eutrophication restoration and management

Recruitment of cyanobacteria from the sediments in the eutrophic Shanzi Reservoir

This study investigated the impact of four environmental factors on the recruitment of cyanobacteria from bottom sediments in the eutrophic Shanzi Reservoir. Temperature and light were identified as the key determinants for the recruitment of Microcystis and Oscillatoria. Cyanobacteria became dominant at higher temperature (20°C) and light intensity (2000 lx) and Microcystis and Oscillatoria were the major species. Detailed recruitment simulation undertaken with the respective gradients of temperature and light suggested that both Microcystis and Oscillatoria are temperature sensitive and that their critical temperature point was 10°C. However, distinct light impacts were observed only on Microcystis. The recruitment of Oscillatoria was light independent, whereas Microcystis had a positive relationship with light intensity. Physical disturbance promoted Microcystis recruitment and also affected the structure of the recruited cyanobacterial community at the water–sediment interface, based on quantitative polymerase chain reaction (qPCR) and phylogenetic analysis

Critical review on unraveling uncultivable pesticide degraders via stable isotope probing (SIP)

Uncultivable microorganisms account for over 99% of all species on earth, playing essential roles in ecological processes such as carbon/nitrogen cycle and chemical mineralization. Their functions remain unclear in ecosystems and natural habitats, requiring cutting-edge biotechnologies for a deeper understanding. Stable isotope probing (SIP) incorporates isotope-labeled elements, e.g. 13 C, 18 O or 15 N, into the cellular components of active microorganisms, serving as a powerful tool to link phylogenetic identities to their ecological functions in situ. Pesticides raise increasing attention for their persistence in the environment, leading to severe damage and risks to the ecosystem and human health. Cultivation and metagenomics help to identify either cultivable pesticide degraders or potential pesticide metabolisms within microbial communities, from various environmental media including the soil, groundwater, activated sludge, plant rhizosphere, etc. However, the application of SIP in characterizing pesticide degraders is limited, leaving considerable space in understanding the natural pesticide mineralization process. In this review, we try to comprehensively summarize the fundamental principles, successful cases and technical protocols of SIP in unraveling functional-yet-uncultivable pesticide degraders, by raising its shining lights and shadows. Particularly, this study provides deeper insights into various feasible isotope-labeled substrates in SIP studies, including pesticides, pesticide metabolites, and similar compounds. Coupled with other techniques, such as next-generation sequencing, nanoscale secondary ion mass spectrometry (NanoSIMS), single cell genomics, magnetic-nanoparticle-mediated isolation (MMI) and compound-specific isotope analysis (CSIA), SIP will significantly broaden our understanding of pesticide biodegradation process in situ

ACE (I/D) polymorphism and response to treatment in coronary artery disease: a comprehensive database and meta-analysis involving study quality evaluation

<p>Abstract</p> <p>Background</p> <p>The role of angiotensin-converting enzyme (<it>ACE</it>) gene insertion/deletion (<it>I/D</it>) polymorphism in modifying the response to treatment modalities in coronary artery disease is controversial.</p> <p>Methods</p> <p>PubMed was searched and a database of 58 studies with detailed information regarding <it>ACE I/D </it>polymorphism and response to treatment in coronary artery disease was created. Eligible studies were synthesized using meta-analysis methods, including cumulative meta-analysis. Heterogeneity and study quality issues were explored.</p> <p>Results</p> <p>Forty studies involved invasive treatments (coronary angioplasty or coronary artery by-pass grafting) and 18 used conservative treatment options (including anti-hypertensive drugs, lipid lowering therapy and cardiac rehabilitation procedures). Clinical outcomes were investigated by 11 studies, while 47 studies focused on surrogate endpoints. The most studied outcome was the restenosis following coronary angioplasty (34 studies). Heterogeneity among studies (p < 0.01) was revealed and the risk of restenosis following balloon angioplasty was significant under an additive model: the random effects odds ratio was 1.42 (95% confidence interval:1.07–1.91). Cumulative meta-analysis showed a trend of association as information accumulates. The results were affected by population origin and study quality criteria. The meta-analyses for the risk of restenosis following stent angioplasty or after angioplasty and treatment with angiotensin-converting enzyme inhibitors produced non-significant results. The allele contrast random effects odds ratios with the 95% confidence intervals were 1.04(0.92–1.16) and 1.10(0.81–1.48), respectively. Regarding the effect of <it>ACE I/D </it>polymorphism on the response to treatment for the rest outcomes (coronary events, endothelial dysfunction, left ventricular remodeling, progression/regression of atherosclerosis), individual studies showed significance; however, results were discrepant and inconsistent.</p> <p>Conclusion</p> <p>In view of available evidence, genetic testing of <it>ACE I/D </it>polymorphism prior to clinical decision making is not currently justified. The relation between <it>ACE </it>genetic variation and response to treatment in CAD remains an unresolved issue. The results of long-term and properly designed prospective studies hold the promise for pharmacogenetically tailored therapy in CAD.</p

Evolutionary Game Analysis of Blockchain Technology Preventing Supply Chain Financial Risks

Because of the risks existing in supply chain finance, taking accounts receivable factoring business as the research object, this paper uses the evolutionary game method to analyzes the factors affecting the decision-making of the participants in supply chain finance, constructs an evolutionary game model between small and medium-sized enterprises and financial institutions, and analyzes the mechanism of blockchain to solve the financial risks of the supply chain by comparing the changes of evolutionary stability strategies before and after the introduction of blockchain technology. This paper aims to reduce financing risks by analyzing the mechanism of blockchain technology in supply chain finance. It is found that, firstly, blockchain technology can reduce the credit risk of financial institutions and solve financing problem. Credit risk plays a decisive role in whether financial institutions accept financing business decisions. Blockchain technology can reduce the operational risk of financial institutions and improve the business income of financial institutions. Secondly, the strict regulatory environment formed by blockchain technology makes the default behavior of small and medium-sized enterprises and core enterprises in a high-risk state at all times. No matter the profit distribution proportion that small and medium-sized enterprises can obtain through collusion, they will not choose to default, which effectively solves the paradox that small and medium-sized enterprises cannot obtain loans from financial institutions despite the increased probability of compliance. Then, the evolutionary game between financial institutions and small and medium-sized enterprises is balanced in that financial institutions accept business applications, small and medium-sized enterprises abide by the contract, and the convergence effect is better. Therefore, blockchain technology not only reduces the financing risk of financial institutions but also helps to solve the financing problems of small and medium-sized enterprises

Evolutionary Game Analysis of Blockchain Technology Preventing Supply Chain Financial Risks

Because of the risks existing in supply chain finance, taking accounts receivable factoring business as the research object, this paper uses the evolutionary game method to analyzes the factors affecting the decision-making of the participants in supply chain finance, constructs an evolutionary game model between small and medium-sized enterprises and financial institutions, and analyzes the mechanism of blockchain to solve the financial risks of the supply chain by comparing the changes of evolutionary stability strategies before and after the introduction of blockchain technology. This paper aims to reduce financing risks by analyzing the mechanism of blockchain technology in supply chain finance. It is found that, firstly, blockchain technology can reduce the credit risk of financial institutions and solve financing problem. Credit risk plays a decisive role in whether financial institutions accept financing business decisions. Blockchain technology can reduce the operational risk of financial institutions and improve the business income of financial institutions. Secondly, the strict regulatory environment formed by blockchain technology makes the default behavior of small and medium-sized enterprises and core enterprises in a high-risk state at all times. No matter the profit distribution proportion that small and medium-sized enterprises can obtain through collusion, they will not choose to default, which effectively solves the paradox that small and medium-sized enterprises cannot obtain loans from financial institutions despite the increased probability of compliance. Then, the evolutionary game between financial institutions and small and medium-sized enterprises is balanced in that financial institutions accept business applications, small and medium-sized enterprises abide by the contract, and the convergence effect is better. Therefore, blockchain technology not only reduces the financing risk of financial institutions but also helps to solve the financing problems of small and medium-sized enterprises

Gender Disparities in Lipid Goal Attainment among Type 2 Diabetes Outpatients with Coronary Heart Disease: Results from the CCMR-3B Study

Abstract Our study was aimed to investigate the gender disparities in lipid goal attainment among type 2 diabetes outpatients with concomitant coronary heart disease (CHD) and explore potential risk factors. We performed the present analysis using data from a nationally representative epidemiologic study. The therapeutic goal was defined as achieving a low-density lipoprotein cholesterol (LDL-C) <1.8 mmol/L. A total of 1721 male and 2072 female type 2 diabetes outpatients with established CHD were identified. Compared with men, women had higher levels of total cholesterol (4.98 vs. 4.46 mmol/L; p < 0.001), LDL-C (2.82 vs. 2.54 mmol/L; p < 0.001), and triglycerides (2.02 vs. 1.79 mmol/L; p < 0.001), but not hemoglobin A1c (7.47% vs. 7.50%; p = 0.597). The proportion of women received lipid-lowering therapy was lower (38.1% vs. 48.2%; p < 0.001). The percentages of patients who achieved the LDL-C goal were higher among men. Multivariable regression analysis indicated that the odds ratio for lipid goal attainment due to the gender difference was 0.61 after adjusting confounders. The inability to achieve LDL-C goals in women with type 2 diabetes and CHD is apparently greater than that in men. This finding underscores the importance of initiatives to establish a more aggressive lipid management strategy for women to overcome gender imbalances

Prevalence of Obesity and Its Influence on Achievement of Cardiometabolic Therapeutic Goals in Chinese Type 2 Diabetes Patients: An Analysis of the Nationwide, Cross-Sectional 3B Study.

BACKGROUND:There are few data on the prevalence of obesity and its influence on achieving blood glucose, blood pressure, and blood lipid (3B) goals in Chinese type 2 diabetes outpatients. METHODS:Patient demographic data, anthropometric measurements, medications, and blood glucose and lipid profiles of 24,512 type 2 diabetes patients from a large, geographically diverse study (CCMR-3B) were analyzed. Using cut-points for body mass index (BMI) and waist circumference (WC) recommended by the Working Group on Obesity in China, overweight and obesity were defined as BMIs of 24-27.9 kg/m2 and ≥28.0 kg/m2. Central obesity was defined as a waist circumference ≥80 cm in women and ≥85 cm in men. The 3B therapeutic goals were HbA1c<7.0%, BP<140/90 mmHg and LDL-C<2.6 mmol/L. RESULTS:Overall, 43.0% of type 2 diabetes patients were overweight and 16.7% were obese; 13.3% of overweight and and 10.1% of obese patients achieved all the 3B target goals. Overweight or obese patients were less likely to achieve 3B goals than those with normal BMIs. More than a half the overweight or obese patients (69.6%) were centrally obese. Patients with abdominal obesity were less likely to achieve cardiometabolic targets than those without abdominal obesity. In multivariate logistic regression analysis, female, higher BMI and waist circumference, smoking, drinking, sedentary lifestyle, and longer diabetes duration were significantly correlated with failure to achieve 3B control goals. CONCLUSIONS:Obesity is highly prevalent and associated with poor 3B control in Chinese type 2 diabetes patients. In clinical practice, more attention and resources should focus on weight loss for such patients