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Chitin deacetylases (CDAs) catalyze N-deacetylation of chitin, a crucial process for chitin modification. In the present paper, LdCDA1 was identified in Leptinotarsa decemlineata. It was copiously expressed in larval foregut, hindgut and epidermis. Just before the molt in the first, second and third larval instars, the mRNA levels of LdCDA1 were high. In the fourth (final)-instar larvae, a peak occurred 4 days after ecdysis. In vivo results revealed that LdCDA1 transcriptionally responded, positively and negatively respectively, to 20-hydroxyecdysone and juvenile hormone titers. Moreover, knockdown of LdCDA1 significantly reduced foliage consumption, lengthened developing period and prevented growth in the final instar larvae. Three distinct lethal phenotypes were noted in the LdCDA1 RNAi larvae. About 30% of the RNAi larvae became moribund and finally died; approximately 50% of deformed pupae died as pharate adults; and around 20% of LdCDA1 depleted pupae finally emerged as abnormal adults and eventually died within 1 week after emergence. Furthermore, chitin content was low and the mRNA levels of five chitin biosynthesis transcripts (LdUAP1, LdUAP2, LdChSAa, LdChSAb and LdChSB) were significantly declined in the LdCDA1 RNAi larvae. In addition, glucose, trehalose and glycogen contents were increased in the LdCDA1 depleted hypomorphs, along with highly expressed genes coding for trehalose and glycogen synthesis enzymes. The findings provide a compelling piece of evidence that CDA1 is critical for chitin deposition in L. decemlineata. Moreover, LdCDA1 may be a potential target for control of the larvae.
Sun,,Jian-Da,Chen,,Chuang-Zhen,Chen,,Jian-Zhou,Li,,Dong-Sheng,Chen,,Zhi-Jian,Zhou,,Ming-Zhen,Li,,De-Rui Asian Pacific Organization for Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.5
Treatment responses of $N_0$ stage nasopharyngeal carcinoma were firstly analyzed comprehensively to evaluate long term outcomes of patients and identify prognostic factors. A total of 610 patients with $N_0$ NPC, undergoing definitive radiotherapy to their primary lesion and prophylactic radiation to upper neck, were reviewed retrospectively. Concomitant chemotherapy was administrated to 65 out of the 610. Survival rates of the patients were calculated using the Kaplan-Meier method and compared by log-rank test. Prognostic factors were identified by the Cox regression model. The study revealed the 5-year and 10-year overall, disease-free, disease-specific, local failure-free, regional failure-free, locoregional failure-free and distant metastasis-free survival rates to be 78.7% and 66.8%, 68.8% and 55.8%, 79.9% and 70.4%, 81.2% and 72.5%, 95.8% and 91.8%, 78.3% and 68.5%, 88.5% and 85.5%, respectively. There were 192 patients experiencing failure (31.5%) after radiotherapy or chemoradiotherapy. Of these, local recurrence, regional relapse and distant metastases as the first event of failure occurred in 100 (100/610, 16.4%), 15(15/610, 2.5%) and 52 (52/610, 8.5%), respectively. Multivariate analysis showed that T stage was the only independent prognostic factor for patients with $N_0$ NPC (P=0.000). Late T stage (P=0.000), male (P=0.039) and anemia (P=0.007) were independently unfavorable factors predicting disease-free survival. After treatment, satisfactory outcome wasgenerally achieved in patients with $N_0$ NPC. Local recurrence represented the predominant mode of treatment failure, while T stage was the only independent prognostic factor for overall survival. Late T stage, male gender, and anemia independently predicted lower possibility of the disease-free survival.
Hong,Zhao,Zhi-Zhou,Shi,Rui,Jiang,Dong-Bing,Zhao,Hai-Tao,Zhou,Jian-Wei,Liang,Xin-Yu,Bi,Jian-Jun,Zhao,Zhi-Yu,Li,Jian-Guo,Zhou,Zhen,Huang,Ye-Fan,Zhang,Jian,Wang,Xin,Xu,Yan,Cai,Ming-Rong,Wang,Yu,Zhang 한국유전학회 2016 Genes & Genomics Vol.38 No.11
Genomic aberrations of rectal carcinoma, especially DNA copy number changes associated with metastasis were largely unclear. We aim to identify the metastasis associated biomarkers in stage II rectal cancer. Formalin-fixed, paraffin-embedded primary tumor tissues of stage II rectal carcinoma were analyzed by array-based comparative genomic hybridization, and genomic aberrations were identified by Genomic Workbench and SAM software. Copy number changes and mRNA expressions were validated by Real-time PCR in an independent rectal cancer samples. The results showed that the most frequent gains in stage II rectal cancer were at 1q21.2-q23.1, 3p21.31, 11q12.2-q23.3, 12q24.11-q24.31, 12q13.11-q14.1 and losses in 18q11.2-q23, 17q21.33-q22, 13q31.1-q31.3, 21q21.1-q21.3, 8p23.3-p23.1 and 4q22.1-q23. Twenty-two amplifications and five homozygous deletions were also identified. We further found that S100A1 (1q21.3-q23.1), MCM7 (7q22.1) and JUND (19p13.11) were amplified and overexpressed in stage II rectal cancer. Interestingly, the genomic aberrations affected 14 signaling pathways including VEGF signaling pathway and fatty acid metabolism. Most importantly, loss of 13q31.1-q34 and gain of 1q44 were associated with distant metastasis. Our results indicated that these metastasis associated genomic changes may be useful to reveal the pathogenesis of rectal cancer metastasis and identify candidate biomarkers.
The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data trans-mission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Di-minishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy effi-ciency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collabo-rations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs.
This study investigated the geographic and pairwise distances of nine Chinese local Cashmere goat populations through the analysis of 20 microsatellite DNA markers. Fluorescence PCR was used to identify the markers, which were selected based on their significance as identified by the Food and Agriculture Organization of the United Nations (FAO) and the International Society for Animal Genetics (ISAG). In total, 206 alleles were detected; the average allele number was 10.30; the polymorphism information content of loci ranged from 0.5213 to 0.7582; the number of effective alleles ranged from 4.0484 to 4.6178; the observed heterozygosity was from 0.5023 to 0.5602 for the practical sample; the expected heterozygosity ranged from 0.5783 to 0.6464; and Allelic richness ranged from 4.7551 to 8.0693. These results indicated that Chinese Cashmere goat populations exhibited rich genetic diversity. Further, the Wright's F-statistics of subpopulation within total (FST) was 0.1184; the genetic differentiation coefficient (GST) was 0.0940; and the average gene flow (Nm) was 2.0415. All pairwise FST values among the populations were highly significant (p<0.01 or p<0.001), suggesting that the populations studied should all be considered to be separate breeds. Finally, the clustering analysis divided the Chinese Cashmere goat populations into at least four clusters, with the Hexi and Yashan goat populations alone in one cluster. These results have provided useful, practical, and important information for the future of Chinese Cashmere goat breeding.
Causticizing calcium carbonate (CCC) is produced as a by-product in the causticization step of the kraft pulping process. It is often calcined in a rotary lime kiln after being dewatered and reused in the causticizing process. But for the China mill, the conventional recycled way is difficult because the CCC is mainly obtained from non-wood pulping materials, which higher silicon content led to serious silicon obstacle. So it is often discarded as solid waste or used in landfill after dewatering and secondary pollution is brought. In order to prevent its secondary pollution, recent years, the CCC is used as a filler in China papermaking industry. In mill trials, the CCC can be used to replace an amount of precipitated calcium carbonate (PCC). Unfortunately, the application scope and dosage of CCC have been limited due to its lower sizing efficiency than PCC. In this study, the reason for the lower sizing efficiency of alkyl ketene dimer (AKD) when CCC was used as a filler was investigated. The results showed that the materials in green liquid, such as insoluble matter in green liquid, silicon and metal ions, were a little influence on the sizing efficiency of AKD. The higher BET and BJH pore volume of the CCC were the main reason for lower sizing efficiency of AKD when it was used as filler.
Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.
Bayesian model updating technique has been widely investigated and utilized in the field of finite element model (FEM) updating for its advantages in system uncertainty quantification. Most existing studies focus on numerical and experimental models. More studies on large-scale civil infrastructures based on field monitoring are still required. A case study on Bayesian FEM updating of the Runyang Suspension Bridge (RSB), a long-span suspension bridge with a main span of 1,490 m, is carried out in this paper. The Bayesian updating method is utilized to update the initial FEM of RSB, aiming to make the numerical modal properties match the field monitoring results. Two stochastic sampling algorithms, i.e., the Metropolis-Hastings (MH) algorithm and the Hybrid Monte Carlo (HMC) algorithm, are respectively investigated to show their advantages and limitations in Bayesian updating. Subsequently, based on the experimentalsamples generated by the Latin hypercube sampling algorithm, a Kriging predictor is established as a surrogate model to reduce the computational burden of model updating. Results show that the HMC algorithm could guarantee much higher acceptance rate of the sampled chain than the MH algorithm especially when the updating step size is large. In addition, combined with the Kriging predictor, Bayesian model updating method could serve as an effective and efficient tool to calibrate the FEM of large-scale civil infrastructures.