Identification of a sub-micromolar, non-peptide inhibitor of β-secretase with low neural cytotoxicity through in silico screening

Nowadays identification of novel non-peptide β-secretase (BACE-1, hereinafter) inhibitors with low cytotoxicity and good blood–brain barrier (BBB) property holds common interest of drug discovery for Alzheimer’s disease. Twenty SPECS compounds were tested in BACE-1 FRET assays and methylthiazoletetrazolium (MTT) cytotoxicity experiment. Two compounds: 2 and 15 demonstrated IC50 values of 0.53 and 9.4 μM. In addition, 2 showed least toxic effect to the neuroblastoma cells. The results from both in silico and in vitro studies provided new pharmacophoric entities for chemical synthesis and optimization on the current discovered BACE-1 small molecule inhibitors

Molecular docking and structure-activity relationship studies on benzothiazole based non-peptidic BACE-1 inhibitors

A similarity search on the structural analogs of an inhibitor of BACE-1 with IC50 2.8 μM, which contained a P1 benzothiazole group together with a triazine ring linked by a secondary amine group, was described in this Letter and some more potent inhibitors against BACE-1 were identified. The most potent compound 5 (IC50 = 0.12 μM) increases the inhibitory potency by 24 folds. Our results suggest that a pyrrolidinyl side group at the P3′ and P4′ of the inhibitors are favored for strong inhibition and a small aromatic group at the P4 position is also essential to the potency

3D-QSAR studies of checkpoint kinase 1 inhibitors based on molecular docking and CoMFA

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q 2 value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r 2 value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r 2 value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis

Evolution and vulnerability analysis of the global trade pattern in the lithium industry chain

[Objective] This study aims to simulate the vulnerability of the lithium industry trade network in the event of interruption risks. The goal is to effectively identify key nodes and potential risks in the network, providing decision support for optimizing trade patterns and avoiding interruption risks. [Methods] Analyzing the evolution of the lithium industry trade pattern based on trade flow methods, intentional attack simulations were conducted to assess the vulnerability of the lithium industry trade network after trade interruptions occurred in the top 10% of nodes by PageRank centrality. [Results] The research reveals: (1) The global trade pattern of the lithium industry chain is undergoing profound restructuring and transformation, with China’s position highlighted in the global trade network. (2) Invulnerability in the upstream network of the lithium industry chain has improved during the sample period, while the risk resistance capabilities of the midstream and downstream networks are relatively stable. (3) The vulnerability ranking of the lithium industry chain is downstream < midstream < upstream. When trade interruptions occur in the top 10% of global key nodes, the overall performance of the upstream, midstream, and downstream trade networks decreases by an average of 60%, 35%, and 23.5%, respectively. [Conclusion] To maintain the security and stability of China’s and the global lithium industry, the following measures should be implemented: enhance and refine safety risk warning and emergency support mechanisms within the lithium industry chain; establish a cooperative, win-win framework among key stakeholders in the lithium industry chain to bolster positive response capabilities across the industry, supply chain, and value chain; and improve domestic self-sufficiency and global allocation capabilities for lithium resources

Impact of a water-sediment regulation scheme on nutrient variations at the Lijin station of the Yellow River

The water-sediment regulation scheme (WSRS) imposed on dams throughout the Yellow River not only alleviates siltation in the downstream section but also alters the nutrient characteristics, which indirectly affects the enrichment of nutrients in the estuary. Nevertheless, the long-term changes in the nutrient contents and their causes in the lower Yellow River (LYR) remain unclear, and the nutrients characteristics during the years with and without WSRS have yet to be compared. Therefore, the purpose of this study was to explore the variations in the nutrient contents and limitations at the Lijin station on the LYR over the past decade, especially during the annual WSRS period, and to compare the water quality characteristics at Lijin between the years with and without WSRS. The results reveal that WSRS significantly changed the seasonal nutrient concentrations (nitrogen, phosphorus and silicon) at the Lijin station. The fluxes of these nutrients during WSRS (excluding 2016 and 2017) accounted for 11.64–40.63% of the total annual fluxes. The N concentration in the LYR was higher than that in some global rivers, while the concentrations of dissolved inorganic phosphorus (DIP) and dissolved silica (DSi) were lower than the average levels in other rivers. In addition, higher values of dissolved inorganic nitrogen (DIN), DSi and the Redfield ratio indicated that the growth of phytoplankton at the Lijin station was strongly restricted by P. However, during the 2 years without WSRS (2016 and 2017), the proportions of the nutrient fluxes in June were less than 66% of those in the WSRS period in other years. Additionally, there was a potential Si limitation in June in these 2 years. Furthermore, due to the occurrence of floods upstream of the Yellow River and the low-level operation of the Xiaolangdi Reservoir, the fluxes of nutrients during WSRS in 2018 were approximately 0.90–4.20 times those during the same period in 2009–2015 and 6.30–35.76 times those in June 2016 and June 2017. This study shows that WSRS effectively changes the nutrient balance in the LYR and provides a reference for the multi-objective collaborative optimization of WSRS to improve siltation and control flood in the LYR

Measurement and filtration of virus aerosols

University of Minnesota Ph.D. dissertation. June 2014. Major: Mechanical Engineering. Advisors: Dr. Thomas H. Kuehn, Dr. David Y.H. Pui, 1 computer file (PDF); xi, 129 pages; appendices p. 127-129.The potential involvement of virus aerosols (i.e., airborne virus-carrying particles) in the transmission of human respiratory diseases has led to increased public concern. This dissertation focuses on 1) measurement of laboratory generated virus aerosols as a function of particle size, virus type, and composition of nebulizer suspensions (Chapter 2 and 3) and 2) performance evaluation of filtering facepiece respirators against virus aerosols (Chapter 4 and 5) with the long term goal to better understand and better control the airborne transmission of viral diseases

An LSTM-STRIPAT model analysis of China’s 2030 CO2 emissions peak

To achieve China’s CO2 emissions targets, all Chinese provinces need to ensure that their CO2 emissions are maintained at a reasonable level to avoid the shortboard effect. This paper proposed an integrated method, the LSTM-STIRPAT, to predict the CO2 emissions in 30 provinces, and assess the drivers of a different region. We divide 30 provinces according to the prediction result into provinces with peak value(PWP) and provinces without peak value(PWTP) and found that (i) Inner Mongolia, Jiangxi, Shandong, Hainan, Chongqing, Guizhou, Qinghai, Xinjiang are failed to reach their CO2 emissions peak by 2030, but almost all provinces experienced a small peak in their carbon emissions from 2008 to 2013; (ii) The ranking of CO2 emissions influencing factors in the PWTP is energy intensity (+) > population density (+) > energy consumption (+) > urbanization rate (−) > GDP per capita (+) > ratio of secondary industry (+); the ranking of CO2 emissions influencing factors in the PWP is energy intensity (+) > ratio of secondary industry (+) > urbanization rate (−) > population density (+) > energy consumption (+) > GDP per capita (−); (iii) PWTP's CO2 emissions show a significant lag effect, of which the ratio of secondary industry accounts for the most significant impact. According to the research results, we put forward relevant targeted measures to achieve China's carbon emissions peak commitments in 2030: (1) PWTP should give priority to encouraging the development of technology and strengthening the utilization of new energy and renewable energy; (2) PWP should give priority to reducing energy intensity, optimizing the industrial structure and accelerating the process of urbanization; (3) CO2 emission reduction in PWTP is a long-term task, it is necessary to adhere to the optimization and adjustment of the industrial structure