Plant communities in the zone of gas field development and heavy metal accumulation by them

Heavy metal accumulation by plant communities has been studied in different zones of impact of gas field development. The contents of heavy metals in different blocks of plant communities has proved to depend not only on the location of phytocenosis but also on its species composition. Communities dominated by species of the family Poaceae contain smaller amounts of heavy metals than those dominated by species of the family Asteraceae, especially of the genus Artemisia. The order of precedence in the accumulation of heavy metals in different blocks of plant communities has been revealed.     

Carbonyl emissions from vehicular exhausts sources in Hong Kong

Vehicular emission (VE) is one of the important anthropogenic sources for airborne carbonyls in urban area. Six types of VE-dominated samples were collected at representative locations in Hong Kong where polluted by a particular fueled type of vehicles, including (i) a gas refilling taxis station (liquefied petroleum gas [LPG] emission); (ii) a light-duty passenger car park (gasoline emission); (iii) a minibus station (diesel emission); (iv) a single-deck-bus depot (diesel emission); (v) a double-deck-bus depot (diesel emission); and (vi) a whole-food market entrance for light- and heavy-duty vehicles (diesel emission). A total of 15 carbonyls in the samples were quantified. Formaldehyde was the most abundant carbonyl among the VE-dominated samples, and its contribution to the total quantified amount on a molar basis ranged from 54.8% to 60.8%. Acetaldehyde and acetone were the next two abundant carbonyls. The carbonyls were quantified at three roadside locations in Hong Kong. The highest concentrations of formaldehyde and acetaldehyde, 22.7 +/- 8.4 and 6.0 +/- 2.8 microg/m3, respectively, were determined in the samples collected at a main transportation gate for goods between Hong Kong and Mainland China. The total quantified carbonyl concentration, 37.9 +/- 9.3 microg/m3, was the highest at an entrance of a cross-harbor tunnel in downtown area. The theoretical carbonyls compositions of the three roadside locations were estimated according to the VE-dominated sample profiles and the statistics on vehicle numbers and types during the sampling period. The measured compositions of formaldehyde were much higher than the theoretical compositions in summer, demonstrating that photochemical reactions significantly contributed to the formaldehyde production in the roadsides.     

Discordant results between fetal karyotyping and non-invasive prenatal testing by maternal plasma sequencing in a case of uniparental disomy 21 due to trisomic rescue

Uniparental disomy (UPD) is an uncommon chromosome condition, but UPD involving chromosome 21 is rarely reported. We reported here a case who had first trimester screening test for Down syndrome, chorionic villus sampling for fetal karyotyping, quantitative fluorescence polymerase chain reaction (QF-PCR), as well as non-invasive prenatal testing (NIPT) by maternal plasma sequencing. There were discordant results between fetal karyotyping and NIPT due to UPD 21combined with confined placental mosaicism of trisomy 21. This demonstrated that it is possible to detect placental mosaicism by NIPT, but further studies are required to confirm its sensitivity. Therefore, all positive NIPT results must be confirmed by conventional invasive test and karyotyping. QF-PCR has the additional benefit in diagnosing UPD. © 2013 John Wiley & Sons, Ltd.     

Modelling and Prediction of Diesel Engine Performance using Relevance Vector Machine

Diesel engines are being increasingly adopted by many car manufacturers today, yet no exact mathematical diesel engine model exists due to its highly nonlinear nature. In the current literature, black-box identification has been widely used for diesel engine modelling and many artificial neural network (ANN) based models have been developed. However, ANN has many drawbacks such as multiple local minima, user burden on selection of optimal network structure, large training data size, and over-fitting risk. To overcome these drawbacks, this article proposes to apply an emerging machine learning technique, relevance vector machine (RVM), to model and predict the diesel engine performance. The property of global optimal solution of RVM allows the model to be trained using only a few experimental data sets. In this study, the inputs of the model are engine speed, load, and cooling water temperature, while the output parameters are the brake-specific fuel consumption and the amount of exhaust emissions like nitrogen oxides and carbon dioxide. Experimental results show that the model accuracy is satisfactory even the training data is scarce. Moreover, the model accuracy is compared with that using typical ANN. Evaluation results also show that RVM is superior to typical ANN approach.     

An integrative analysis of miRNA and mRNA expression in the brains of Alzheimer's disease transgenic mice after real-world PM2.5 exposure

Fine particulatematter (PM2.5) is associated with increased risks of Alzheimer’s disease (AD),yet the toxicologicalmechanisms of PM2.5 promoting AD remain unclear. In this study,wildtype and APP/PS1 transgenic mice (AD mice) were exposed to either filtered air (FA) or PM2.5 for eight weeks with a real-world exposure system in Taiyuan, China (mean PM2.5 concentration in the cage was 61 μg/m3). We found that PM2.5 exposure could remarkably aggravate AD mice’s ethological and brain ultrastructural damage, along with the elevation of the pro-inflammatory cytokines (IL-6 and TNF-α), Aβ-42 and AChE levels and the decline of ChAT levels in the brains. Based on high-throughput sequencing results, some differentially expressed (DE) mRNAs and DE miRNAs in the brains of AD mice after PM2.5 exposure were screened.Using RT-qPCR, seven DEmiRNAs (mmu-miR-193b-5p, 122b-5p, 466h-3p, 10b-5p, 1895, 384–5p, and 6412) and six genes (Pcdhgb8, Unc13b, Robo3, Prph, Pter, and Tbata) were evidenced the and verified. Two miRNA-target gene pairs (miR-125b-Pcdhgb8 pair and miR-466h-3p-IL-17Rα/TGF-βR2/Aβ-42/AChE pairs) were demonstrated that they were more related to PM2.5-induced brain injury. Results of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways predicted that synaptic and postsynaptic regulation, axon guidance, Wnt, MAPK, and mTOR pathways might be the possible regulatory mechanisms associated with pathological response. These revealed that PM2.5- elevated pro-inflammatory cytokine levels and PM2.5-altered neurotransmitter levels in AD mice could be the important causes of brain damage and proposed the promising miRNA andmRNA biomarkers and potentialmiRNA-mRNA interaction networks of PM2.5-promoted AD.     

Oxidation of organic impurities in the recycle and reclaim loops of ultra-pure water plants

 The oxidation of trace organic impurities in ultrapure water by ultraviolet light (UV), ozone, and the combination of UV/ozone is investigated. The emphasis is on the development of a global model to simulate the process that take place in the typical oxidation reactors used in ultrapure water plants. The study also focuses on reaction mechanism for oxidation of multi-component organic impurities. Eighteen organic model compounds are chosen as representative contaminants. The results demonstrate and confirm a significant synergistic effect between UV and ozone oxidation. A mechanism for the synergistic oxidation of organic impurities is proposed and validated with experimental data. The combination of the reaction and the reactor models is used to determine the fundamental kinetic parameters involved in the three oxidation processes. Received: 3 July 1998 / Accepted: 4 September 1998