Latest Research More

Article  |  2020-04-02

Synthesis, Characterization, and Antifungal Evaluation of Thiolactomycin Derivatives

5-Substituted benzylidene 3-acylthiotetronic acids are antifungal. A series of 3-acylthiotetronic acid derivatives with varying substitutions at the 5-position were designed, synthesized, and characterized, based on the binding pose of 3-acyl thiolactone with the protein C171Q KasA. Fungicidal activities of these compounds were screened against Valsa Mali, Curvularia lunata, Fusarium graminearum, and Fusarium oxysporum f. sp. lycopersici. Most target compounds exhibited excellent fungicidal activities against target fungi at the concentration of 50 μg·mL−1. Compounds 11c and 11i displayed the highest activity with a broad spectrum. The median effective concentration (EC50) values of 11c and 11i were 1.9–10.7 and 3.1–7.8 μg·mL−1, respectively, against the tested fungi, while the EC50 values of the fungicides azoxystrobin, carbendazim, and fluopyram were respectively 0.30, 4.22, and > 50 μg·mL−1 against V. Mali; 6.7, 41.7, and 0.18 μg·mL1 against C. lunata; 22.4, 0.42, and 0.43 μg·mL−1 against F. graminearum; and 4.3, 0.12, and > 50 μg·mL−1 against F. oxysporum f. sp. Lycopersici. The structures and activities of the target compounds against C. lunata were analyzed to obtain a statistically significant comparative molecular field analysis (CoMFA) model with high prediction abilities (q2 = 0.9816, r2 = 0.8060), and its reliability was verified. The different substituents on the benzylidene at the 5-position had significant effects on the activity, while the introduction of a halogen atom at the benzene ring of benzylidene was able to improve the activity against the tested fungi.

Pei Lv

Perspective  |  2020-03-31

Discovery for New Herbicide Sites of Action by Quantification of plant Primary Metabolite and Enzyme Pools

No herbicide with a new molecular site of action (SOA) has been introduced since the 1980s. Since then, the widespread evolution of resistance of weeds to most commercial herbicides has greatly increased the need for herbicides with new SOAs. Two untried strategies for the discovery on new herbicide SOAs are discussed. Some primary metabolism intermediates are phytotoxic (e.g., protoporphyrin IX and sphingoid bases), and, because of this, the in vivo concentrations of these compounds are maintained at very low levels by plants. The determination of all primary metabolite phytotoxicities and pool sizes will identify targets of interest. Targeting SOAs that result in accumulation of phytotoxic compounds is the first novel approach to herbicide discovery. The second approach is to identify potential SOAs with very low in vivo enzyme levels. We know that higher numbers of enzyme molecules for a SOA requires more herbicide to kill a plant. Modern proteomic methods can identify low enzyme level SOAs for biorational herbicide discovery. These approaches might be useful in discovery of herbicides more closely related to natural compounds and that can be used in lower doses.

Franck E. Dayan

Article  |  2020-04-03

Multi-Domain Knowledge Convergence Trajectory Analysis of Strategic Emerging Industries Based on Citation Network and Text Information

 The analysis of technology convergence process for strategic emerging industries is helpful to deeply understand the generation process and development law of industrial technology, thereby helping master the development trend of the field and promoting the healthy development of the industry. To identify the trajectory and degree of technology convergence of the strategic emerging industries, this study conducts a multi-case study on four fields which present a trend of convergence and attract social attention, namely, high-end equipment manufacturing, new-generation information technology, new medicine, and new energy. This study adopts a knowledge convergence trajectory analysis method based on citation network and text information. It utilizes a graph neural network model and encodes the citation network, title, and abstract of the publications as vectors. Five knowledge convergence trajectories are identified, after analyzing the data of the selected four technical fields. The research results show that information technology and numerical control equipment, biomedicine and solar photovoltaic technology have shown a trend of deep convergence, respectively; and the convergence of the information technology and numerical control equipment is deeper. Numerical control equipment and solar photovoltaic technology, information technology and solar photovoltaic technology have shown a converging trend, respectively; however, the current degree of convergence is still insufficient, due to the late start of convergence. Numerical control equipment and biomedicine have not shown any trend of convergence.

Liu Yufei

Article  |  2020-04-03

Research on the Development of Machine Tool Industry in China

This study focuses on the development of the high-end manufacturing equipment industry in China, represented by machine tools. The machine tool referred to herein includes not only the machine tools in traditional definition, such as lathes, milling machines, planers, drilling machines, boring machines, grinders, and gear making machines, but also additive manufacturing equipment and additive-subtractive hybrid manufacturing equipment. This study analyzes the development trends of the machine tool industry in China and the globe, and then studies the problems existing in China’s machine tool industry. Compared with world’s advanced level, China’s machine tool industry still has weaknesses in (1) basic research and key technologies for ultra-precision machine tools, (2) the machining accuracy and efficiency of large-scale machine tools, (3) the reliability and accuracy retention of the whole machine performance, (4) the research and development of common technologies of the advanced additive manufacturing and hybrid manufacturing equipment, and (5) the level of intelligence of high-end machine tools. Furthermore, we propose the key direction of China’s machine tool industry during the 14th Five-Year Plan and the following five to ten years, and put forward some policy measures for the development of machine tool industry in China, including coordinating national science and technology plans with national policy supporting and evaluation systems, and establishing and strengthening the common technology collaborative innovation system for the high-end manufacturing equipment represented by machine tools.

Wang Lei

Article  |  2020-04-02

NOx and H2S formation in the reductive zone of air-staged combustion of pulverized blended coals

Low NO combustion of blended coals is widely used in coal-fired boilers in China to control NO emission; thus, it is necessary to understand the formation mechanism of NO and H S during the combustion of blended coals. This paper focused on the investigation of reductive gases in the formation of NO and H S in the reductive zone of blended coals during combustion. Experiments with Zhundong (ZD) and Commercial (GE) coal and their blends with different mixing ratios were conducted in a drop tube furnace at 1200°C–1400°C with an excessive air ratio of 0.6–1.2. The coal conversion and formation characteristics of CO, H S, and NO in the fuel-rich zone were carefully studied under different experimental conditions for different blend ratios. Blending ZD into GE was found to increase not only the coal conversion but also the concentrations of CO and H S as NO reduction accelerated. Both the CO and H S concentrations inblended coal combustion increase with an increase in the combustion temperature and a decrease in the excessive air ratio. Based on accumulated experimental data, one interesting finding was that NO and H S from blended coal combustion were almost directly dependent on the CO concentration, and the CO concentration of the blended coal combustion depended on the single char gasification conversion.Thus, CO, NO , and H S formation characteristics from blended coal combustion can be well predicted by single char gasification kinetics.

Jinzhi CAI