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Long non-coding RNAs (lncRNAs) are crucial participants in cancer development. HOXA cluster antisense RNA 2 (HOXA-AS2) plays a tumor promoter role in bladder cancer. However, the functional role of HOXA-AS2 in cervical cancer remains unclear. Our study first found that HOXA-AS2 expression was up-regulated in cervical cancer cells. Then functional analysis including cell counting kit-8 (CCK-8), colony formation, transwell, and wound healing uncovered that reduction of HOXA-AS2 remarkably impeded cell proliferation and migration in cervical cancer. Additionally, luciferase reporter assays were performed to confirm that HOXA-AS2 activated Notch signaling pathway via the mediation of independent recombination signal binding protein for JK (RBP-JK) activity. As we know, Notch intracellular domain (NICD) is associated with RBP-JK in the nucleus to promote target genes in the Notch pathway. Through RNA immunoprecipitation (RIP), RNA pull down, and fluorescent in situ hybridization (FISH) assays, we observed that HOXA-AS2 combined with NICD. Moreover, the data from Co-IP assays indicated that HOXA-AS2 reduction weakened the interaction of NICD and RBP-JK. Collectively, HOXA-AS2 played a cancer-promoting role in cervical cancer development by modulating the Notch pathway, which might become a novel target for cervical cancer treatment.

Florfenicol is a chloramphenicol antibiotic that plays an essential role on bacteriostasis. Long-term use of florfenicol in livestock and poultry can cause immunetoxicity and reproductive toxicity and the consumption of animal-derived products with excessive residues of florfenicol will pose a certain threat to human health. To study residue depletion of oral florfenicol in chickens, 48 healthy 30 -day -old AA broilers received continuous administration of 150 mg/kg/d florfenicol for five days. Muscle, liver, kidney and sebum were collected at 0.16, 1, 3, 5, 7 and 9 days after discontinuation of the drug and detected by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Most previous studies have shown that acid hydrolysis is necessary for tissue sample extraction. However, the steps of acid hydrolysis are tedious and time-consuming. In this experiment, we tried to improve the solvent extraction method to simplify the pretreatment process and the effect of acid hydrolysis was further analyzed and compared. Using the WT1.4 software the withdrawal time in muscle, liver, kidney and sebum obtained by F-QuEChERS-AOAC 3202 method was 7.82, 0.06, 4.38, 13.71 days respectively while acid hydrolysis method were 8.89, 5.84, 5.39 and 9.65 days, respectively. To reduce the residues of florfenicol and ensure the safety of chicken products, it is recommended that chickens taking oral florfenicol should be subjected to a 14 -days withdrawal time.

Combined with ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), a method for simultaneous determination of 15 sulfonamides in livestock and poultry manure was established and further optimizes and improves the pre-treatment conditions. In this study, Fe3O4-multi-walled carbon nanotubes (MWCNTs) were used as the purification material, and achieved solid-liquid separation by an external magnet, which was faster than the traditional centrifugation process. The results showed that the recoveries of sulfonamides were from 89 to 119% and had relative standard deviations (RSDs) of less than 10%. The limit of detection (LOD) of the method was reached 0.5 to 1.0 μg/kg, and the limit of quantification (LOQ) was between 1.0 and 3.0 μg/kg. On the premise that a satisfactory recoveries can be obtained, Fe3O4-MWCNTs can be effectively used at least 3 times. We can conclude that this method has certain applicability and reliability in the analysis and detection of sulfonamides in livestock and poultry manure.

With the increasing demand of indoor location-based services, such as tracking targets in a smart building, device-free localization technique has attracted great attentions because it can locate the targets without employing any attached devices. Due to the limited space and complexity of the indoor environment, there still exist challenges in terms of high localization accuracy and high efficiency for indoor localization. In this paper, for addressing such issues, we first convert the received signal strength (RSS) signals into image pixels. The localization problem is then formulated as an image classification problem. To well handle the variant RSS images, a deep convolutional neural network is then structured for classification. Finally, for validating the proposed scheme, two real testbeds are built in the indoor environments, including a living room and a corridor of an apartment. Experimental results show that the proposed scheme achieves good localization performance. For example, the localization accuracy can reach up to 100% in the scenario of living room and 97.6% in the corridor. Moreover, the proposed approach outperforms the methods of the K-nearest-neighbor and the support vector machines in both the noiseless and noisy environments.

With the increasing interest in large-scale, high-resolution and real-time geographic information system (GIS) applications and spatial big data processing, traditional GIS is not efficient enough to handle the required loads due to limited computational capabilities.Various attempts have been made to adopt high performance computation techniques from different applications, such as designs of advanced architectures, strategies of data partition and direct parallelization method of spatial analysis algorithm, to address such challenges. This paper surveys the current state of parallel GIS with respect to parallel GIS architectures, parallel processing strategies, and relevant topics. We present the general evolution of the GIS architecture which includes main two parallel GIS architectures based on high performance computing cluster and Hadoop cluster. Then we summarize the current spatial data partition strategies, key methods to realize parallel GIS in the view of data decomposition and progress of the special parallel GIS algorithms. We use the parallel processing of GRASS as a case study. We also identify key problems and future potential research directions of parallel GIS. Refereed/Peer-reviewed