JAK2 V617F stimulates proliferation of erythropoietin-dependent erythroid progenitors and delays their differentiation by activating Stat1 and other nonerythroid signaling pathways

JAK2 V617F is a mutant-activated JAK2 kinase found in most polycythemia vera (PV) patients; it skews normal proliferation and differentiation of hematopoietic stem and progenitor cells and simulates aberrant expansion of erythroid progenitors. JAK2 V617F is known to activate some signaling pathways not normally activated in mature erythroblasts, but there has been no systematic study of signal transduction pathways or gene expression in erythroid cells expressing JAK2 V617F undergoing erythropoietin (Epo)-dependent terminal differentiation. Here we report that expression of JAK2 V617F in murine fetal liver Epo-dependent progenitors allows them to divide approximately six rather than the normal approximately four times in the presence of Epo, delaying their exit from the cell cycle. Over time, the number of red cells formed from each Epo-dependent progenitor increases fourfold, and these cells eventually differentiate into normal enucleated reticulocytes. We report that purified fetal liver Epo-dependent progenitors express many cytokine receptors additional to the EpoR. Expression of JAK2 V617F triggers activation of Stat5, the only STAT normally activated by Epo, as well as activation of Stat1 and Stat3. Expression of JAK2 V617F also leads to transient induction of many genes not normally activated in terminally differentiating erythroid cells and that are characteristic of other hematopoietic lineages. Inhibition of Stat1 activation blocks JAK2 V617F hyperproliferation of erythroid progenitors, and we conclude that Stat1-mediated activation of nonerythroid signaling pathways delays terminal erythroid differentiation and per mits extended cell divisions.National Institutes of Health (U.S.) (Grant P01 HL 32262

Resistance-gene-directed discovery of a natural-product herbicide with a new mode of action.

Bioactive natural products have evolved to inhibit specific cellular targets and have served as lead molecules for health and agricultural applications for the past century1-3. The post-genomics era has brought a renaissance in the discovery of natural products using synthetic-biology tools4-6. However, compared to traditional bioactivity-guided approaches, genome mining of natural products with specific and potent biological activities remains challenging4. Here we present the discovery and validation of a potent herbicide that targets a critical metabolic enzyme that is required for plant survival. Our approach is based on the co-clustering of a self-resistance gene in the natural-product biosynthesis gene cluster7-9, which provides insight into the potential biological activity of the encoded compound. We targeted dihydroxy-acid dehydratase in the branched-chain amino acid biosynthetic pathway in plants; the last step in this pathway is often targeted for herbicide development10. We show that the fungal sesquiterpenoid aspterric acid, which was discovered using the method described above, is a sub-micromolar inhibitor of dihydroxy-acid dehydratase that is effective as a herbicide in spray applications. The self-resistance gene astD was validated to be insensitive to aspterric acid and was deployed as a transgene in the establishment of plants that are resistant to aspterric acid. This herbicide-resistance gene combination complements the urgent ongoing efforts to overcome weed resistance11. Our discovery demonstrates the potential of using a resistance-gene-directed approach in the discovery of bioactive natural products

Innovation in environmental technologies in China: the case of Feida’s power plant pollution control equipment

Innovation is important for developing a strong brand. This chapter introduces a leading provider of environmental solutions for power plants in China. Feida is a company located in the Zhejiang province in China that develops products and technology to remove small particles from the exhausts of coal-fired power plants. The chapter describes the company’s evolution towards a leading company in environmental technology in China and analyzes the role of R&D and innovation in its brand development. The chapter further assesses how the nature of the company’s innovation is connected to the production and functional/user side of the innovation system and institutional environment in which it operates. Feida’s strategy is to expand internationally to foreign markets but it is facing significant challenges in that process

Electric Power Investment Risk Assessment for Belt and Road Initiative Nations

In recent years, Chinese companies’ investment in overseas electric power has grown rapidly. Chinese enterprises with matured technology and abundant talent in the field of electric power and electric power investment are becoming the focus of Chinese enterprise investment. However, just like any other energy investment, electric power investment has various potential risks, including economic risk, financial risk, social risk, political risk, electric power foreground risk, resource risk, and environmental risk. To specifically measure electric power investment risk, this article proposed a nine-dimensional indicator system for countries along China’s ‘Belt and Road Initiative’. Moreover, a fuzzy integrated evaluation model ground on the entropy weight was established to evaluate the electric power investment risk of 21 countries along China’s Belt and Road Initiative. The result of research shows that electric power foreground and Chinese factors have become the major underlying determinants of electric power investment risk, while coal power economy, renewable power economy, and political risk should also be attached enough attention when making investing decisions. In conclusion, the optimal choices for China’s electricity investment are determined after balancing electric power foreground and basic factors. After analyzing investment risks of various countries, this paper puts forward policy suggestions, which can help Chinese enterprises avoid electric power investment risks and improve investment efficiency

Low carbon electricity development in China--An IRSP perspective based on Super Smart Grid

Low carbon electricity is essential for China's low carbon development. In the paper low carbon electricity is defined as an economy body manages to realize its potential economic growth fueled by less electricity consumption, which can be characterized by indexes of GDP electricity intensity and CO2 emissions per unit electricity generation. IRSP is proposed by Hu [11] to implement power planning on state level in deregulated power sector and is used in the paper to study China's power planning into 2030. A business-as-usual scenario is projected as baseline for comparison while low carbon electricity development based on IRSP is studied. Results show that, with IRSP, China could save energy by 1.5 billion toes and reduce CO2 emission by 5.7 billion tons, during 2010-2030. Super Smart Grid (SSG) must be constructed as the physical foundation of IRSP. The main components of developing SSG in China are discussed.Low carbon electricity Integrated resource strategic planning Super Smart Grid China

Will the Steam Coal Price Rebound under the New Economy Normalcy in China?

The steam coal price in China has been continuously decreasing since the second half of 2012. Constant low price of coal will accelerate the development of thermal power, cause more serious air pollution problems, and bring adverse influence to China’s energy reformation in the future. Therefore, analyzing the factors underlying the phenomenon of the decreasing steam coal price is significant. In this study, we first qualitatively analyze five main factors, namely, economy, supply, demand, substitutes, and port stocks. On the basis of the relationships among these five factors, we obtain the causality diagram and the system flow diagram of coal price for further quantitative research. Then, we conduct an empirical analysis using the system dynamics (SD) method and determine the simulated price from 2012 to 2017. Finally, we discuss the running results and come to the conclusion that the steam coal price will continue to decrease under the combined actions of the five main factors and it will not rebound in the near future

Impact Analysis of Air Pollutant Emission Policies on Thermal Coal Supply Chain Enterprises in China

Spurred by the increasingly serious air pollution problem, the Chinese government has launched a series of policies to put forward specific measures of power structure adjustment and the control objectives of air pollution and coal consumption. Other policies pointed out that the coal resources regional blockades will be broken by improving transportation networks and constructing new logistics nodes. Thermal power takes the largest part of China’s total installed power generation capacity, so these policies will undoubtedly impact thermal coal supply chain member enterprises. Based on the actual situation in China, this paper figures out how the member enterprises adjust their business decisions to satisfy the requirements of air pollution prevention and control policies by establishing system dynamic models of policy impact transfer. These dynamic analyses can help coal enterprises and thermal power enterprises do strategic environmental assessments and find directions of sustainable development. Furthermore, the policy simulated results of this paper provide the Chinese government with suggestions for policy-making to make sure that the energy conservation and emission reduction policies and sustainable energy policies can work more efficiently

Hybrid Energy Scheduling in a Renewable Micro Grid

In this paper, we address the energy scheduling issue in a hybrid energy micro grid, which consists of photovoltaic (PV), wind power, combined heat and power (CHP), energy storage and electric vehicles (EVs). The optimal scheduling model of these power sources is presented with consideration of the demand response. The objective function is minimum total operation costs, including gas cost, electric power purchase from the main grid and storage and EV charging-discharging costs. In the process of optimization, multi-team particle swarm optimization (MTPSO) is proposed, which uses units, groups and swarm information to update the velocity (position) with faster and more stable convergence. With simulation analysis, it is found that the proposed model is effective, and the presented MTPSO has a better global search ability than PSO