Effect of ambient polycyclic aromatic hydrocarbons and nicotine on the structure of Aβ42 protein

● B[a]P, nicotine and phenanthrene molecules altered the secondary structure of Aβ₄₂. ● β-content of the peptide was significantly enhanced in the presence of the PAHs. ● Nicotine made stable cluster with Aβ₄₂ peptide via hydrogen bonds. ● Phenanthrene due to its small size, interfered with the Aβ₄₂ monomer more strongly. Recent studies have correlated the chronic impact of ambient environmental pollutants like polycyclic aromatic hydrocarbons (PAHs) with the progression of neurodegenerative disorders, either by using statistical data from various cities, or via tracking biomarkers during in-vivo experiments. Among different neurodegenerative disorders, PAHs are known to cause increased risk for Alzheimer’s disease, related to the development of amyloid beta (Aβ) peptide oligomers. However, the complex molecular interactions between peptide monomers and organic pollutants remains obscured. In this work, we performed an atomistic molecular dynamics study via GROMACS to investigate the structure of Aβ₄₂ peptide monomer in the presence of benzo[a]pyrene, nicotine, and phenanthrene. Interestingly the results revealed strong hydrophobic, and hydrogen-bond based interactions between Aβ peptides and these environmental pollutants that resulted in the formation of stable intermolecular clusters. The strong interactions affected the secondary structure of the Aβ₄₂ peptide in the presence of the organic pollutants, with almost 50 % decrease in the α-helix and 2 %–10 % increase in the β-sheets of the peptide. Overall, the undergoing changes in the secondary structure of the peptide monomer in the presence of the pollutants under the study indicates an enhanced formation of Aβ peptide oligomers, and consequent progression of Alzheimer’s disease.     

Considering science needs to deliver actionable science

Conservation practitioners, natural resource managers, and environmental stewards often seek out scientific contributions to inform decision-making. This body of science only becomes actionable when motivated by decision makers considering alternative courses of action. Many in the science community equate addressing stakeholder science needs with delivering actionable science. However, not all efforts to address science needs deliver actionable science, suggesting that the synonymous use of these two constructs (delivering actionable science and addressing science needs) is not trivial. This can be the case when such needs are conveyed by people who neglect decision makers responsible for articulating a priority management concern and for specifying how the anticipated scientific information will aid the decision-making process. We argue that the actors responsible for articulating these science needs and the process used to identify them are decisive factors in the ability to deliver actionable science, stressing the importance of examining the provenance and the determination of science needs. Guided by a desire to enhance communication and cross-literacy between scientists and decision makers, we identified categories of actors who may inappropriately declare science needs (e.g., applied scientists with and without regulatory affiliation, external influencers, reluctant decision makers, agents in place of decision makers, and boundary organization representatives). We also emphasize the importance of, and general approach to, undertaking needs assessments or gap analyses as a means to identify priority science needs. We conclude that basic stipulations to legitimize actionable science, such as the declaration of decisions of interest that motivate science needs and using a robust process to identify priority information gaps, are not always satisfied and require verification. To alleviate these shortcomings, we formulated practical suggestions for consideration by applied scientists, decision makers, research funding entities, and boundary organizations to help foster conditions that lead to science output being truly actionable.     

基于环境监测实验室的高校实验室安全准入制度信息系统功能优化研究

梳理了高校实验室环境-安全-健康准入制度包含的管理内容,从人员管理、设备管理、试剂管理、实验环境管理角度进行了分析。根据现有实验室安全信息化系统运行情况,探讨了将实验室安全信息化系统与实验室信息化系统、设备管理信息化系统进行数据融合和功能优化的要点,重点分析了设备采购及管理系统、实验室安全教育与考试系统、实验室安全检查系统、试剂管理平台、实验室门禁管理系统在功能上的内在关联,从而通过试剂管理平台、实验室门禁控制系统、设备采购系统实现实验室环境-安全-健康准入制度的强制执行。研究发现,高校与环境监测实验室、院系实验室安全管理部门联合促进实验室安全信息化系统、实验室信息化系统、设备管理信息化系统的数据共享与功能升级,可以丰富实验室安全准入制度的内涵和管理手段,加强实验室安全准入制度的强制执行力,提高实验室安全管理效率。     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

基于火探管式的锂离子电池灭火技术研究

为研究锂离子电池灭火方案,基于火探管灭火技术同时利用新型清洁灭火剂Novec 1230,组装成火探管灭火系统。在灭火测试平台上以功率为200 W的电热管作为外热源引发单电池或电池模组热失控,通过改变火探管的布置位置,记录相应的灭火行为以及灭火效率,并对实验结果进行了分析。研究结果表明,当火探管灭火系统直接布置在电池正上方时,在起火后的5.6s内控制火情;随着灭火剂用量增加可以显著降低体系温度,防止电池复燃以及连锁热失控现象发生;火探管有效覆盖区域外的失控电池作为热源将继续加热临近电池,引发连锁热失控,造成灭火系统失效;根据电池热失控后的燃烧行为以及传热行为,提出相应的火探管灭火系统复合方案。     

Enhanced debromination of 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) by zero-valent zinc with ascorbic acid

• Highly efficient debromination of BDE-47 was achieved in the ZVZ/AA system. • BDE-47 debromination by the ZVZ/AA can be applied to a wide range of pH. • AA inhibits the formation of (hydr)oxide and accelerates the corrosion of ZVZ. • Reduction mechanism of BDE-47 debromination by the ZVZ/AA system was proposed. A new technique of zero-valent zinc coupled with ascorbic acid (ZVZ/AA) was developed and applied to debrominate the 2,2′,4,4′-Tetrabromodiphenyl ether (BDE-47), which achieved high conversion and rapid debromination of BDE-47 to less- or non-toxic forms. The reaction conditions were optimized by the addition of 100 mg/L ZVZ particles and 3 mmol/L AA at original solution pH= 4.00 using the solvent of methanol/H₂O (v:v= 4:6), which could convert approximately 94% of 5 mg/L BDE-47 into lower-brominated diphenyl ethers within a 90 min at the ZVZ/AA system. The high debromination of BDE-47 was mainly attributed to the effect of AA that inhibits the formation of Zn(II)(hydr)oxide passivation layers and promotes the corrosion of ZVZ, which leads to increase the reactivity of ZVZ. Additionally, ion chromatography and gas chromatography mass spectrometry analyses revealed that bromine ion and lower-debromination diphenyl ethers formed during the reduction of BDE-47. Furthermore, based on the generation of the intermediates products, and its concentration changes over time, it was proposed that the dominant pathway for conversion of BDE-47 was sequential debromination and the final products were diphenyl ethers. These results suggested that the ZVZ/AA system has the potential for highly efficient debromination of BDE-47 from wastewater.     

Inherent thermal runaway hazard evaluation method of chemical process based on fire and explosion index

Thermal runaway hazard assessment provides the basis for comparing the hazard levels of different chemical processes. To make an overall evaluation, hazard of materials and reactions should be considered. However, most existing methods didn't take the both into account simultaneously, which may lead the assessment to a deviation from the actual hazard. Therefore, an integrated approach called Inherent Thermal-runaway Hazard Index (ITHI) was developed in this paper. Similar to Dow Fire and Explosion Index(F&EI) function, thermal runaway hazard of chemical process in ITHI was the product of material factor (MF) and risk index (RI) of reaction. MF was an indicator of material thermal hazards, which can be determined by initial reaction temperature and maximum power density. RI, which was the product of probability and severity, indicated the risk of thermal runaway during the reaction stage. Time to maximum rate under adiabatic conditions and criticality classes of scenario were used to indicate the runaway probability of the chemical process. Adiabatic temperature rise and heat of the desired reaction and secondary reaction were used to determine the severity of runaway reaction. Finally, predefined hazard classification criteria was used to classify and interpret the results obtained by this method. Moreover, the method was validated by case studies.     

Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.     

Efficiency of mercapto flavor compounds in removing acrylamide under high temperature and low humidity conditions

Acrylamide (AA) is a potential human carcinogen, genotoxicant, and neurotoxicant. Thus, the aim of this study was to examine the ability of mercapto flavor compounds to remove AA released from consumer packaging into food products. Four mercapto flavor compounds including 1,2-ethanedithiol, 1-butanethiol, 2-methyl-3-furanthiol, and 2-furanmethanethiol were employed to extract AA in model system using high temperature and low humidity. Our study showed that mercaptans were effective in eliminating AA in our model system. In order to remove 0.2 μmol AA, the optimal conditions in the reaction system were mercaptan flavor chemicals at 5 μmol, temperature 180 °C, and reaction time 25 min. In the presence of a higher pH, the greater was the amount of AA eliminated. Evidence indicates that employment of mercapto flavor chemicals under certain temperature and pH conditions is a reliable method to remove any unwanted AA from food products.     

南京市农用地土壤中重金属形态特征分析

以南京市农用地土壤为研究对象,采用顺序提取的方法对Cu、Zn、Pb、Cd做化学形态分析,了解不同元素各形态下空间赋存的含量与占比。结果表明,在农用地土壤中,上述4种金属元素所赋存的化学形态活泼性顺序为CdPbCuZn,其中Cd主要为醋酸提取态,Pb主要为可还原态,各占总量的40%以上,具有较高的生物有效性和潜在危害性;Cu与Zn主要为残渣态,占总量的60%左右,生物可利用性较低。由因子分析法可知,土壤p H值越大,Zn与Cd就越趋于向稳定的化学形态转化,土壤有机质含量越高,对Cu与Pb的络合能力就越强,可以降低其环境危害性。