Sampling-based approximate skyline query in sensor equipped IoT networks

The ever increasing requirements of data sensing applications result in the usage of IoT networks. These networks are often used for efficient data transfer. Wireless sensors are incorporated in the IoT networks to reduce the deployment and maintenance costs. Designing an energy efficient data aggregation method for sensor equipped IoT to process skyline query, is one of the most critical problems. In this paper, we propose two approximation algorithms to process the skyline query in wireless sensor networks. These two algorithms are uniform sampling based approximate skyline query and Bernoulli sampling-based approximate skyline query. Solid theoretical proofs are provided to confirm that the proposed algorithms can yield the required query results. Experiments conducted on actual datasets show that the two proposed algorithms have high performance in terms of energy consumption compared to the simple distributed algorithm

Long-term nickel contamination increases the occurrence of antibiotic resistance genes in agricultural soils

Heavy metal contamination is assumed to be a selection pressure on antibiotic resistance, but to our knowledge, evidence of the heavy metal-induced changes of antibiotic resistance is lacking on a long-term basis. Using quantitative PCR array and Illumina sequencing, we investigated the changes of a wide spectrum of soil antibiotic resistance genes (ARGs) following 4- 5 year nickel exposure (0-800 mg kg-1) in two long-term experimental sites. A total of 149 unique ARGs were detected, with multidrug and β-lactam resistance as the most prevailing ARG types. The frequencies and abundance of ARGs tended to increase along the gradient of increasing nickel concentrations, with the highest values recorded in the treatments amended with 400 mg nickel kg-1 soil. The abundance of mobile genetic elements (MGEs) was significantly associated with ARGs, suggesting that nickel exposure might enhance the potential for horizontal transfer of ARGs. Network analysis demonstrated significant associations between ARGs and MGEs, with the integrase intI1 gene having the most frequent interactions with other cooccurring ARGs. The changes of ARGs were mainly driven by nickel bioavailability and MGEs as revealed by structural equation models. Taken together, long-term nickel exposure significantly increased the diversity, abundance, and horizontal transfer potential of soil ARGs

Dissimilatory nitrate reduction to ammonium dominates soil nitrate retention capacity in subtropical forests

The abundance, community composition and activity of key nitrogen (N)-cycling functional guilds were monitored at a site where coniferous Cunninghamia lanceolate and broadleaved Mytilaria laosensis were planted in 1993. Leaf cellulose, litter C/N ratio, leaf dry matter content, soil inorganic N content were significantly higher under C. lanceolata, while specific leaf area, litter production, litter magnesium, soil C and soil C/NO3− ratio were higher under M. laosensis. The 15N tracing experiment together with quantitative PCR revealed that autotrophic nitrification rates, as well as the abundances of ammonia-oxidizing archaea and comammox Nitrospira were significantly higher under C. lanceolate than M. laosensis. However, M. laosensis exhibited substantially higher nitrate retention capacity via dissimilatory nitrate reduction to ammonium (DNRA), accompanied by a significantly higher abundance of nrfA gene than C. lanceolate. The Illumina sequencing indicated that tree species markedly affected soil bacterial community composition regardless of the soil layers. Redundancy analysis suggested that litter C/N ratio was the most influential factor explaining functional gene abundances and bacterial communities. Taken together, our findings showed that M. laosensis improved soil N retention capacity mainly through inhibiting autotrophic nitrification while enhancing DNRA activity. This study highlights the importance of tree species identity in influencing the microbially-mediated N cycling and bacterial community composition

Efficacy of recombinant adenovirus expressing a fusion gene from GM-CSF and Epstein-Barr virus LMP2A in a mouse tumor model

In this study, purified GM-CSF and LMP2A mRNAs were amplified by PCR. Then, the GM-CSF and LMP2A sequences were connected by the polypeptide linker (Gly4Ser)3 using gene splicing by overlap extension. The constructed fusion gene GC2A was inserted into the adenovirus vector. Then the recombinant vector was introduced into HEK 293T cells by calcium phosphate transfection to package the adenovirus. The levels of antibodies against the GM-CSF and LMP2Afusion proteins were measured by ELISA, and the CTL activity of the mouse splenic lymphocytes was determined by lactate dehydrogenase (LDH) release assay. Immunotherapy of mouse tumor (EBV-positive epithelial tumor cell line (GT39)) tissues was performed, and their morphologies were assessed. Finally, the data of each group were analyzed using SPSS 11.5 statistical software. The recombinant adenovirus could replicate in HEK 293Tcells and induce humoral and cellular immune responses in the mice. The maximum dose resulted in an antibody titer of 18500 (184.5 ± 8.7 pg/ml). At an effector: target ratio of 40:1, maximum specific lysis was observed which was approximately three times that detected in the control immunized mice. The tumor inhibition rate was approximately 76% compared with the control groups, indicating the presence of significant differences among the groups. Tumor-infiltrating lymphocytes were detected by hematoxylin-eosin (HE) staining. The recombinant adenovirus induced humoral and cellular immune responses and inhibited tumor growth in mice. It provided a theoretical basis and candidate vaccine for further preclinical trials

pyEIT: A python based framework for Electrical Impedance Tomography

We present a Python-based, open source Electrical Impedance Tomography (EIT) library called pyEIT. It is a multiplatform software released under the Apache License v2.0. pyEIT has a clean architecture and is well documented. It implements state-of-the-art EIT imaging algorithms and is also capable of simple 2D/3D meshing. pyEIT is written in Python. It accelerates the analysis of offline EIT data and can be incorporated into clinical EIT applications. In this paper, we focus on illustrating the fundamental design principles of pyEIT by using some intuitive examples about EIT forward computing and inverse solving. Keywords: Electrical Impedance Tomography, Inverse problems, Finite element method, Unstructrual mes

Phase III, randomized, double‐blind, placebo‐controlled study to evaluate the efficacy and safety of teneligliptin monotherapy in Chinese patients with type 2 diabetes mellitus inadequately controlled with diet and exercise

International audienceAims/introduction: Although the efficacy of teneligliptin, a highly selective dipeptidyl peptidase-4 inhibitor, has been amply studied for the treatment of type 2 diabetes, no clinical trials of teneligliptin have been carried out in China. We evaluated the efficacy and safety of teneligliptin monotherapy compared with a placebo in Chinese patients with type 2 diabetes mellitus inadequately controlled with diet and exercise.Materials and methods: This multicenter, randomized, double-blind, placebo-controlled, parallel-group study, carried out at 42 sites, enrolled type 2 diabetes patients with glycosylated hemoglobin 7.0 to <10.0% and fasting blood glucose <270 mg/dL. Patients were randomly assigned, in a 1:1 ratio, to treatment with 20 mg teneligliptin or a placebo (n = 127, each) administered orally once daily before breakfast for 24 weeks. Change in glycosylated hemoglobin from baseline to week 24 was the primary efficacy end-point. Safety was assessed by the incidence of adverse events and adverse drug reactions.Results: The least square mean (LSM) change in glycosylated hemoglobin from baseline to week 24 was -0.95% with teneligliptin versus -0.14% with a placebo, yielding an LSM difference (teneligliptin vs placebo) of -0.80% (P < 0.0001). For the secondary end-point, from baseline to week 24, the LSM change in fasting blood glucose was -21.9 mg/dL with teneligliptin versus -1.4 mg/dL with a placebo, yielding an LSM difference (teneligliptin vs placebo) of -20.5 mg/dL (P < 0.0001). The adverse event and adverse drug reaction incidence rates, including hypoglycemia, were similar in both groups.Conclusions: At 24 weeks, teneligliptin was generally well tolerated and effective in Chinese patients with type 2 diabetes mellitus inadequately controlled with diet and exercise

Arterial Sca1+ Vascular Stem Cells Generate De Novo Smooth Muscle for Artery Repair and Regeneration

Rapid regeneration of smooth muscle after vascular injury is essential for maintaining arterial function. The existence and putative roles of resident vascular stem cells (VSCs) in artery repair are controversial, and vessel regeneration is thought to be mediated by proliferative expansion of pre-existing smooth muscle cells (SMCs). Here, we performed cell fate mapping and single-cell RNA sequencing to identify Sca1+ VSCs in the adventitial layer of artery walls. After severe injury, Sca1+ VSCs migrate into the medial layer and generate de novo SMCs, which subsequently expand more efficiently compared with pre-existing smooth muscle. Genetic lineage tracing using dual recombinases distinguished a Sca1+PDGFRa+ VSC subpopulation that generates SMCs, and genetic ablation of Sca1+ VSCs or specific knockout of Yap1 in Sca1+ VSCs significantly impaired artery repair. These findings provide genetic evidence of a bona fide Sca1+ VSC population that produces SMCs and delineates their critical role in vessel repair.We thank Shanghai Model Organisms Center, Inc. (SMOC) for mouse generation, Dr. Camargo Fernando for Yap-flox mouse, and Baojin Wu, Guoyuan Chen, Zhonghui Weng, and Aimin Huang for animal husbandry. We also thank Wei Bian, Lin Qiu, and members of National Center for Protein Science Shanghai for technical help and assistance with microscopy. This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS; XDA16010507 and XDB19000000), the National Key Research and Development Program of China (2019YFA0110400, 2018YFA0107900, 2018YFA0108100, 2016YFC1300600, and 2017YFC1001303), the Shanghai Zhangjiang Stem Cell Project (ZJ2018-ZD-004), the National Science Foundation of China (31730112, 91639302, 31625019, 91849202, 81761138040, 81872241, 31701292, 31801215, and 31922032), the Youth Innovation Promotion Association of the CAS, the Key Project of Frontier Sciences of the CAS (QYZDB-SSW-SMC003), the Shanghai Science and Technology Commission (19JC1415700, 17ZR1449600, and 17ZR1449800), the Program for Guangdong Introduction Innovative and Entrepreneurial Teams (2017ZT07S347), the Major Program of the Development Fund for the Shanghai Zhangjiang National Innovation Demonstration Zone (Stem Cell Strategic Biobank and Stem Cell Clinical Technology Transformation Platform, ZJ2018-ZD-004), the Shanghai Yangfan Project, the China Postdoctoral Science Foundation, the China Postdoctoral Innovative Talent Support Program, the Young Elite Scientist Sponsorship Program by CAST (2018QNRC001, and 2017QNRC001), Boehringer Ingelheim, a Sanofi-SIBS fellowship, AstraZeneca, and a Royal Society Newton advanced fellowship.S