Search Results (5)

Malaria remains an important and challenging infectious disease, and novel antimalarials are required. Benzyl isothiocyanate (BITC), the main breakdown product of benzyl glucosinolate, is present in all parts of Tropaeolum majus L. (T. majus) and has antibacterial and antiparasitic activities. To our knowledge, there is no information on the effects of BITC against malaria. The present study evaluates the antimalarial activity of aqueous extracts of BITC and T. majus seeds, leaves, and stems. We used flow cytometry to calculate the growth inhibition (GI) percentage of the extracts and BITC against unsynchronized cultures of the chloroquine-susceptible Plasmodium falciparum 3D7 − GFP strain. Extracts and/or compounds with at least 70% GI were validated by IC50 estimation against P. falciparum 3D7 − GFP and Dd2 (chloroquine-resistant strain) unsynchronized cultures by flow cytometry, and the resistance index (RI) was determined. T. majus aqueous extracts showed some antimalarial activity that was higher in seeds than in leaves or stems. BITC’s GI was comparable to chloroquine’s. BITC’s IC50 was similar in both strains; thus, a cross-resistance absence with aminoquinolines was found (RI < 1). BITC presented features that could open new avenues for malaria drug discovery. Full article

Vehicle emissions have become a significant source of air pollution in urban cities, especially in China. Mobile sources account for 45% of local fine particle emissions in the Chinese capital Beijing. The Beijing–Tianjin–Hebei (BTH) area, one of China’s most representative urban clusters, is suffering from severe air pollution. With the rapid growth of vehicle ownership in the past two decades, vehicle emissions in China have also undergone great changes under various management measures. The BTH region is also a place where mobile source emission management was carried out earlier. It is of important research value to understand the evolution trend of the vehicle ownerships in the BTH region and the actual effects of various management measures for the control of vehicle emissions. Due to the imperfect evaluation of the current vehicle emission limitation measures from 2000 to 2019, the vehicle emission inventory of the BTH region was established, and the major control measures in the BTH region were evaluated. Results showed that the vehicle ownership has been increasing year by year over the past 20 years, from 2.39 million in 2000 to 25.32 million in 2019, with an average annual growth rate of 13.24%. However, the pollutants discharged by motor vehicles showed a trend of first rising and then falling due to various measures except CO₂. The unsynchronized control measures have resulted in huge differences in vehicle growth trends and emissions among Beijing, Tianjin and Hebei. The emissions of carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NO_X), and particulate matter (PM₁₀) in Beijing showed a trend of increasing first and then decreasing. The changes in these pollutants in Tianjin were similar to those in Beijing, but there was a secondary increase for NO_X and PM₁₀ in the later period. The discharge of all pollutants in Hebei Province showed a growing trend except sulfur dioxide (SO₂). The major emission source of CO and VOCs in BTH was PCs, and the contribution rate of PCs to VOCs, reached 86.0–89.6% in 2019. Heavy-duty trucks (HDTs) and buses were the main sources of NO_X emissions, contributing 78.2–85.4% of NO_X in 2019. Eliminating high emission vehicles was the best control measure in the BTH Region, which had a good emission reduction effect on all pollutants. For sustainable development of the BTH region, it is suggested that Beijing, Tianjin and Hebei province implement vehicle control policies simultaneously and establish a joint management mechanism. Full article

Ever-increasing consumer demand for sea cucumbers mainly leads to huge damage to wild sea cucumber resources, including Stichopus monotuberculatus, which in turn exerts negative impacts on marine environments due to the lack of ecological functions performed by sea cucumbers. Aquaculture of sea cucumbers is an effective way to meet consumer demand and restore their resources. Unsynchronous growth is a prominent problem in the aquaculture of sea cucumbers which has concealed unelucidated molecular mechanisms until now. In this study, we carried out an integrative analysis of transcriptomics and metabolomics on fast-growing (SMF) and slow-growing (SMS) groups of S. monotuberculatus cultured in the same environmental conditions. The results revealed that a total of 2054 significantly differentially expressed genes (DEGs) were identified, which are mainly involved in fat digestion and absorption, histidine metabolism, arachidonic acid metabolism, and glutathione metabolism. 368 differential metabolites (DMs) were screened out between the SMF group and the SMS group; these metabolites are mainly involved in glycerophospholipid metabolism, purine metabolism, biosynthesis of unsaturated fatty acids, pyrimidine metabolism, arachidonic acid metabolism, and other metabolic pathways. The integrative analysis of transcriptomics and metabolomics of S. monotuberculatus suggested that the SMF group had a higher capacity for lipid metabolism and protein synthesis, and had a more frequent occurrence of apoptosis events, which are likely to be related to coping with environmental stresses. The results of this study provide potential values for the aquaculture of sea cucumbers which may promote their resource enhancement. Full article

(1) Background: China is beginning to see increasingly complex real estate development dynamics as urbanization, industrialization and globalization advance. As a key driver of economic and social development in China’s cities, real estate has created prosperity while facing the risk of capitalization and a “hard landing”, making it increasingly difficult to bring it under control. (2) Methods: a new approach that integrates “evolution dynamics–driving mechanism–policy design” is constructed based on the Boston Consulting Group matrix, exploratory spatial data analysis, GIS and Geodetector, and this paper empirically studies the dynamics and driving mechanism of real estate development based on the case study of small county-level cities in Gansu, China. (3) Results: Firstly, real estate development in Gansu is characterized by significant spatial differentiation, heterogeneity and autocorrelation, and its distribution pattern comes into being from unsynchronized macroeconomic, population, social, industrial, institutional and policy development interweaved with the real estate control. Secondly, the real estate is diversified in spatiotemporal evolution models, and the cold and hot cities of different models are in quite different geographical patterns with high spatial agglomeration. Thirdly, there are many driving factors affecting the distribution patterns in real estate. These factors are in complex relationships and they are classified into three categories of “Scale–Contribution–Comprehensive”-oriented driving factor and three sub-categories of “Key–Important–Auxiliary” factors. Fourthly, the factors show large differences in the interaction effects, with the real estate industry scale influencing factors being dominated by bifactor enhancement and the economic contribution influencing factors being dominated by non-linear enhancement. Notably, factors such as permanent resident population, urbanization and government revenue have a strong direct influence on the industry scale and economic contribution of real estate, and factors such as expenditure, output value of industry, urbanization rate and number of secondary schools all have a strong interactive influence. (4) Conclusions: The cities are divided into four policy areas of comprehensive development, contribution improvement, scale growth and free decision. Furthermore, differentiated and adaptive measures are proposed for each zoning, which significantly improves the accuracy and synergy of urban real estate management. Full article

The tassel development status and its branch number in maize flowering stage are the key phenotypic traits to determine the growth process, pollen quantity of different maize varieties, and detasseling arrangement for seed maize production fields. Rapid and accurate detection of tassels is of great significance for maize breeding and seed production. However, due to the complex planting environment in the field, such as unsynchronized growth stage and tassels vary in size and shape caused by varieties, the detection of maize tassel remains challenging problem, and the existing methods also cannot distinguish the early tassels. In this study, based on the time series unmanned aerial vehicle (UAV) RGB images with maize flowering stage, we proposed an algorithm for automatic detection of maize tassels which is suitable for complex scenes by using random forest (RF) and VGG16. First, the RF was used to segment UAV images into tassel regions and non-tassel regions, and then extracted the potential tassel region proposals by morphological method; afterwards, false positives were removed through VGG16 network with the ratio of training set to validation set was 7:3. To demonstrate the performance of the proposed method, 50 plots were selected from UAV images randomly. The precision, recall rate and F1-score were 0.904, 0.979 and 0.94 respectively; 50 plots were divided into early, middle and late tasseling stages according to the proportion of tasseling plants and the morphology of tassels. The result of tassels detection was late tasseling stage > middle tasseling stage > early tasseling stage, and the corresponding F1-score were 0.962, 0.914 and 0.863, respectively. It was found that the model error mainly comes from the recognition of leaves vein and reflective leaves as tassels. Finally, to show the morphological characteristics of tassel directly, we proposed an endpoint detection method based on the tassel skeleton, and further extracted the tassel branch number. The method proposed in this paper can well detect tassels of different development stages, and support large scale tassels detection and branch number extraction. Full article