Global health effects of future atmospheric mercury emissions

Mercury is a potent neurotoxin that poses health risks to the global population. Anthropogenic mercury emissions to the atmosphere are projected to decrease in the future due to enhanced policy efforts such as the Minamata Convention, a legally-binding international treaty entered into force in 2017. Here, we report the development of a comprehensive climate-atmosphere-land-ocean-ecosystem and exposure-risk model framework for mercury and its application to project the health effects of future atmospheric emissions. Our results show that the accumulated health effects associated with mercury exposure during 2010–2050 are $19 (95% confidence interval: 4.7–54) trillion (2020 USD) realized to 2050 (3% discount rate) for the current policy scenario. Our results suggest a substantial increase in global human health cost if emission reduction actions are delayed. This comprehensive modeling approach provides a much-needed tool to help parties to evaluate the effectiveness of Hg emission controls as required by the Minamata Convention

Simultaneous Formation of CH₃NH₃PbI₃ and electron transport layers using antisolvent method for efficient perovskite solar cells

A new antisolvent method was developed to prepare CH₃NH₃PbI₃ and electron transport layers for making efficient hybrid perovskite solar cells. By directly using [6,6]-phenyl-C61-butyric acid methyl ester in chlorobenzene solution as antisolvent, CH₃NH₃PbI₃ and electron transport layers were simultaneously formed in the films. This method not only simplifies the fabrication process of devices, but also produces uniform perovskite films and improves the interfacial structures between CH₃NH₃PbI₃ and electron transport layers. Large perovskite grains were observed in these films, with the average grain size of >1 μm. The so-formed CH₃NH₃PbI₃/electron transport layers demonstrated good optical and charge transport properties. And perovskite solar cells fabricated using these simultaneously-formed layers achieved a higher power conversion efficiency of 16.58% compared to conventional antisolvent method (14.92%). This method reduces nearly 80% usage of chlorobenzene during the fabrication, offering a more facile and environment-friendly approach to fabricate efficient perovskite solar cells than the conventional antisolvent method

Dynamic distribution and expression in vivo of the human interferon gamma gene delivered by adenoviral vector

<p>Abstract</p> <p>Background</p> <p>We previously found that r-hu-IFNγ exerts a potent anti-tumor effect on human nasopharyngeal carcinoma xenografts <it>in vivo</it>. Considering the fact that the clinical use of recombinant IFNγ is limited by its short half-life and systemic side effects, we developed a recombinant adenovirus, Ad-IFNγ.</p> <p>Methods</p> <p>Dynamic distribution of the adenovirus vector and expression of IFNγ were evaluated by Q-PCR and ELISA after intratumoral administration of Ad-IFNγ into CNE-2 xenografts.</p> <p>Results</p> <p>Ad-IFNγ DNA was mainly enriched in tumors where the Ad-IFNγ DNA was injected (<it>P </it>< 0.05, compared to blood or parenchymal organs), as well as in livers (<it>P </it>< 0.05). Concentrations of Ad-IFNγ DNA in other organs and blood were very low. Intratumoral Ad-IFNγ DNA decreased sharply at high concentrations (9 × 10⁵copies/μg tissue DNA), and slowly at lower concentrations (1.7–2.9 × 10⁵copies/μg tissue DNA). IFNγ was detected in the tumors and parenchymal organs. The concentration of IFNγ was highest in the tumor (<it>P </it>< 0.05), followed by the liver and kidney (<it>P </it>< 0.05). High-level intratumoral expression of IFNγ was maintained for at least 7 days, rapidly peaking on day 3 after injection of Ad-IFNγ DNA.</p> <p>Conclusion</p> <p>An IFNγ gene delivered by an adenoviral vector achieved high and consistent intratumoral expression. Disseminated Ad-IFNγ DNA and the transgene product were mainly enriched in the liver.</p

Genome Characterization of the Oleaginous Fungus Mortierella alpina

Mortierella alpina is an oleaginous fungus which can produce lipids accounting for up to 50% of its dry weight in the form of triacylglycerols. It is used commercially for the production of arachidonic acid. Using a combination of high throughput sequencing and lipid profiling, we have assembled the M. alpina genome, mapped its lipogenesis pathway and determined its major lipid species. The 38.38 Mb M. alpina genome shows a high degree of gene duplications. Approximately 50% of its 12,796 gene models, and 60% of genes in the predicted lipogenesis pathway, belong to multigene families. Notably, M. alpina has 18 lipase genes, of which 11 contain the class 2 lipase domain and may share a similar function. M. alpina's fatty acid synthase is a single polypeptide containing all of the catalytic domains required for fatty acid synthesis from acetyl-CoA and malonyl-CoA, whereas in many fungi this enzyme is comprised of two polypeptides. Major lipids were profiled to confirm the products predicted in the lipogenesis pathway. M. alpina produces a complex mixture of glycerolipids, glycerophospholipids and sphingolipids. In contrast, only two major sterol lipids, desmosterol and 24(28)-methylene-cholesterol, were detected. Phylogenetic analysis based on genes involved in lipid metabolism suggests that oleaginous fungi may have acquired their lipogenic capacity during evolution after the divergence of Ascomycota, Basidiomycota, Chytridiomycota and Mucoromycota. Our study provides the first draft genome and comprehensive lipid profile for M. alpina, and lays the foundation for possible genetic engineering of M. alpina to produce higher levels and diverse contents of dietary lipids

Characteristics of Ground Pressure Disaster and Rockburst Proneness in Deep Gold Mine

AbstractTo obtain rockburst characteristics at rock engineering, the rockburst event, in situ stress characteristics, and rockburst proneness are studied in a deep gold mine. The severity of rockburst increases with cover depth at the mine. The main locations of spalling and rockburst events include roof and sidewall. The in situ stress measurement results show this area that is controlled by horizontal constructional pressure, and the self-weight stress also has an important influence. The rockburst mechanism is analyzed from the principal stress and tangential stress. When the maximum tangential stress (MTS) does not exceed 0.4 times UCS of surrounding rock, no obvious disaster in tunnel is found. When the MTS of tunnel is between about 0.4 ~ 0.55 times UCS of rock, the tunnel may suffer spalling. When the MTS of tunnel exceeds 0.55 times UCS of rock, serious failure may occur in tunnel, such as rockburst and large roof collapse. When surrounding rock is relatively hard and complete (high impact energy index, elastic strain energy index, linear elastic energy index, and RQD index), the tangential stress plays a very important role in the rockburst at the mine

Failure Transition and Validity of Brazilian Disc Test under Different Loading Configurations: A Numerical Study

The Brazilian disc test is a popular tensile strength test method for engineering materials. The fracture behavior of specimens in the Brazilian disc test is closely related to the validity of the test results. In this paper, the fracture process of granite discs under different loading configurations is simulated by using a coupled finite–discrete element method. The results show that the maximum tensile stress value is located within 18 mm (0.7 times the disc radius) of the vertical range of the disc center under different loading configurations. In small diameter rods loading, the invalid tensile strength is obtained because the crack initiation and plastic strain is at the end of the disc. The crack initiation points of flat platen loading and curved jaws loading are all within the center of the disc, and the valid tensile strength can be obtained. The tensile strength test results under different loading configurations show that the error of small diameter rods loading is 13%, while the errors of flat platen loading and curved jaws loading are both 1%. The curved jaws loading is the most suitable for measuring the tensile strength of brittle materials such as rock, followed by flat platen loading. The small diameter rods loading is not recommended for the Brazilian test

Ensemble Tree Model for Long-Term Rockburst Prediction in Incomplete Datasets

The occurrence of rockburst can seriously impact the construction and production of deep underground engineering. To prevent rockburst, machine learning (ML) models have been widely employed to predict rockburst based on some related variables. However, due to the costs and complicated geological conditions, complete datasets to evaluate rockburst cannot always be obtained in rock engineering. To fill this limitation, this study proposed an ensemble tree model suitable for incomplete datasets, i.e., the histogram gradient boosting tree (HGBT), to build intelligent models for rockburst prediction. Three hundred fourteen rockburst cases were employed to develop the HGBT model. The hunger game search (HGS) algorithm was implemented to optimize the HGBT model. The established HGBT model had an excellent testing performance (accuracy of 88.9%). An incomplete database with missing values was applied to compare the performances of HGBT and other ML models (random forest, artificial neural network, and so on). HGBT received an accuracy of 78.8% in the incomplete database, and its capacity was better than that of other ML models. Additionally, the importance of input variables in the HGBT model was analyzed. Finally, the feasibility of the HGBT model was validated by rockburst cases from Sanshandao Gold Mine, China

Distance Measures of Polarimetric SAR Image Data: A Survey

Distance measure plays a critical role in various applications of polarimetric synthetic aperture radar (PolSAR) image data. In recent decades, plenty of distance measures have been developed for PolSAR image data from different perspectives, which, however, have not been well analyzed and summarized. In order to make better use of these distance measures in algorithm design, this paper provides a systematic survey of them and analyzes their relations in detail. We divide these distance measures into five main categories (i.e., the norm distances, geodesic distances, maximum likelihood (ML) distances, generalized likelihood ratio test (GLRT) distances, stochastics distances) and two other categories (i.e., the inter-patch distances and those based on metric learning). Furthermore, we analyze the relations between different distance measures and visualize them with graphs to make them clearer. Moreover, some properties of the main distance measures are discussed, and some advice for choosing distances in algorithm design is also provided. This survey can serve as a reference for researchers in PolSAR image processing, analysis, and related fields