Global gene expression analysis to identify molecular markers of uterine receptivity and embryo implantation

Infertility and spontaneous pregnancy losses are an enduring problem to women's health. The establishment of pregnancy depends on successful implantation, where a complex series of interactions occurs between the heterogeneous cell types of the uterus and blastocyst. Although a number of genes are implicated in embryo-uterine interactions during implantation, genetic evidence suggests that only a small number of them are critical to this process. To obtain a global view and identify novel pathways of implantation, we used a dual screening strategy to analyze the expression of nearly 10,000 mouse genes by microarray analysis. Comparison of implantation and interimplantation sites by a conservative statistical approach revealed 36 up-regulated genes and 27 down-regulated genes at the implantation site. We also compared the uterine gene expression profile of progesterone-treated, delayed implanting mice to that of mice in which delayed implantation was terminated by estrogen. The results show up-regulation of 128 genes and down-regulation of 101 genes after termination of the delayed implantation. A combined analysis of these experiments showed specific up-regulation of 27 genes both at the implantation site and during uterine activation, representing a broad diversity of molecular functions. In contrast, the majority of genes that were decreased in the combined analysis were related to host immunity or the immune response, suggesting the importance of these genes in regulating the uterine environment for the implanting blastocyst. Collectively, we identified genes with recognized roles in implantation, genes with potential roles in this process, and genes whose functions have yet to be defined in this event. The identification of unique genetic markers for the onset of implantation signifies that genome-wide analysis coupled with functional assays is a promising approach to resolve the molecular pathways required for successful implantation.     

CO2浓度升高对不同品种水稻镉吸收和根形态的影响

为了探讨CO2浓度升高下不同水稻品种荣优398 (RY)和粤杂889(YZ)吸收重金属Cd差异性的原因,利用水培试验研究了不同浓度Cd处理下两种水稻吸收Cd的差异及根形态的变化特征.结果表明:低Cd处理(5、10、20 μmol·L-1)显著增加水稻生物量;当Cd浓度高于50 μmol·L-1时,Cd胁迫效果开始显现,水稻生物量减少.CO2浓度升高显著增加了水稻的生物量,增加了YZ茎Cd含量而降低了RY茎Cd含量.在5～200 μmol·L-1的Cd浓度下,CO2浓度升高增加了YZ活性根在总根长中的比例,降低了RY活性根的比例.CO2浓度升高下不同水稻品种根形态的变化是导致其对Cd吸收差异性的原因之一.     

Production and selected fuel properties of biodiesel from promising non-edible oils: Euphorbia lathyris L., Sapium sebiferum L. and Jatropha curcas L

A comparative study on the composition, biodiesel production and fuel properties of non-edible oils from Euphorbia lathyris L. (EL), Sapium sebiferum L. (SS), and Jatropha curcas L. (JC) was conducted. Under optimal conditions, the FAME content and yield of the three oils were greater than 97.5 wt.% and 84.0%, respectively. The best biodiesel was produced from EL due to its high monounsaturation (82.66 wt.%, Cn: 1), low polyunsaturation (6.49 wt.%, Cn: 2, 3) and appropriate proportion of saturated components (8.78 wt.%, Cn: 0). Namely, EL biodiesel possessed a cetane number of 59.6, an oxidation stability of 10.4 h and a cold filter plug point of -11 °C. However, the cetane number (40.2) and oxidative stability (0.8 h) of dewaxed SS kernel oil (DSSK) biodiesel were low due to the high polyunsaturation (72.79 wt.%). In general, the results suggest that E. lathyris L. is a promising species for biodiesel feedstock.     

临泽绿洲边缘区棉花群体光合速率、蒸腾速率及水分利用效率

在甘肃河西走廊中部黑河中游绿洲边缘区,于6月下旬和8月上旬,利用Li-8100土壤碳通量测定系统与改进的同化箱联合对田间条件下早熟陆地棉(Gossypium hirsutum)品种新陆早8号的群体光合特性进行了研究.结果表明：试验地6月下旬的土壤呼吸速率和土壤蒸发速率显著高于8月上旬（P＜0.01）;棉花群体光合速率日变化均呈“单峰型”,6月下旬的群体光合速率显著高于8月上旬,其日平均值分别为（43.11±1.26）和（24.53±0.60）μmol CO₂·m^-2·s^-1, 差异极显著（P＜0.01）;群体蒸腾速率日变化也呈“单峰型”,6月下旬和8月上旬的日平均值分别为（3.10±0.34）和（1.60±0.26）mmol H₂O·m^-2·s^-1,两者存在极显著差异（P＜0.01）;6月下旬和8月上旬的群体水分利用效率日平均值分别为（15.67±1.77）和（23.08±5.54） mmol CO₂·mol^-1 H₂O,但差异不显著（P＞0.05）.两生育时期棉花群体光合速率与温度、光合有效辐射及土壤含水量均呈正相关关系.表明棉花群体光合速率在6月下旬和8月上旬均没有出现中午光合下调,8月由于土壤水分降低和植物叶片衰老,棉花群体光合速率和蒸腾速率显著降低,但水分利用效率并无显著下降.     

“共轭聚合物-产电菌”复合生物电极构建及其在微生物燃料电池中的应用

微生物燃料电池(Microbial fuel cell,MFC)作为一种生物电化学装置,在可再生能源生产和废水处理方面的巨大潜力已引起广泛关注。然而MFC面临输出功率低、欧姆内阻高以及启动时间长等问题,极大限制了其在实际工程中的应用。MFC中阳极是微生物附着的载体,对电子的产生及传递起着关键作用,开发优质的生物电极已发展成为改善MFC性能的有效途径。共轭聚合物具有成本低、电导率高、化学稳定性及生物相容性好等优点,利用共轭聚合物修饰生物电极结构,可以实现大比表面积、缩短电荷转移路径,从而实现高效生物电化学性能。同时,纳米级共轭聚合物包覆细菌,可以使细菌产生的电子有效地传递到电极。文中综述了最近报道的共轭聚合物在MFC中的应用,重点介绍了共轭聚合物修饰的MFC阳极,系统分析了共轭聚合物的优点及局限性,以及这些高效复合生物电极如何解决MFC应用中存在的低输出功率、高欧姆内阻及长启动时间等问题。     

Simulation of sequential batch reactor (SBR) operation for simultaneous removal of nitrogen and phosphorus

Modeling of the operation of sequential batch reactor (SBR) was performed to find out optimum design parameters for simultaneous removal of nitrogen and phosphorus in a small-scale wastewater treatment plant. The models were set up with material balances on SBR operation and Monod kinetics. The model parameters were obtained to best fit the experimental results in a small scale SBR. The models were useful in optimizing hydraulic retention time (HRT) and successfully simulated operations of SBR in a larger scale. Especially the model predicted well the reactions occurring in the filling period as well as the effect of dilution, and evaluated the performance of SBR process under diverse operating conditions.     

Molecular characterization of avian-like H1N1 swine influenza a viruses isolated in Eastern China, 2011

Currently, three predominant subtypes of influenza virus are prevalent in pig populations worldwide: H1N1, H3N2, and H1N2. European avian-like H1N1 viruses, which were initially detected in European pig populations in 1979, have been circulating in pigs in eastern China since 2007. In this study, six influenza A viruses were isolated from 60 swine lung samples collected from January to April 2011 in eastern China. Based on whole genome sequencing, molecular characteristics of two isolates were determined. Phylogenetic analysis showed the eight genes of the two isolates were closely related to those of the avian-like H1N1 viruses circulating in pig populations, especially similar to those found in China. Four potential glycosylation sites were observed at positions 13, 26, 198, 277 in the HA1 proteins of the two isolates. Due to the presence of a stop codon at codon 12, the isolates contained truncated PB1-F2 proteins. In this study, the isolates contained 591Q, 627E and 701N in the polymerase subunit PB2, which had been shown to be determinants of virulence and host adaptation. The isolates also had a D rather than E at position 92 of the NS1, a marker of mammalian adaptation. Both isolates contained the GPKV motif at the PDZ ligand domain of the 3′ end of the NS1, a characteristic marker of the European avian-like swine viruses since about 1999, which is distinct from those of avian, human and classical swine viruses. The M2 proteins of the isolates have the mutation (S31N), a characteristic marker of the European avian-like swine viruses since about 1987, which may confer resistance to amantadine and rimantadine antivirals. Our findings further emphasize the importance of surveillance on the genetic diversity of influenza A viruses in pigs, and raise more concerns about the occurrence of cross-species transmission events.     

Disease-driven detection of differential inherited SNP modules from SNP network

Detection of the synergetic effects between variants, such as single-nucleotide polymorphisms (SNPs), is crucial for understanding the genetic characters of complex diseases. Here, we proposed a two-step approach to detect differentially inherited SNP modules (synergetic SNP units) from a SNP network. First, SNP-SNP interactions are identified based on prior biological knowledge, such as their adjacency on the chromosome or degree of relatedness between the functional relationships of their genes. These interactions form SNP networks. Second, disease-risk SNP modules (or sub-networks) are prioritised by their differentially inherited properties in IBD (Identity by Descent) profiles of affected and unaffected sibpairs. The search process is driven by the disease information and follows the structure of a SNP network. Simulation studies have indicated that this approach achieves high accuracy and a low false-positive rate in the identification of known disease-susceptible SNPs. Applying this method to an alcoholism dataset, we found that flexible patterns of susceptible SNP combinations do play a role in complex diseases, and some known genes were detected through these risk SNP modules. One example is GRM7, a known alcoholism gene successfully detected by a SNP module comprised of two SNPs, but neither of the two SNPs was significantly associated with the disease in single-locus analysis. These identified genes are also enriched in some pathways associated with alcoholism, including the calcium signalling pathway, axon guidance and neuroactive ligand-receptor interaction. The integration of network biology and genetic analysis provides putative functional bridges between genetic variants and candidate genes or pathways, thereby providing new insight into the aetiology of complex diseases.