Upregulation of AKAP12 by demethylation inhibits proliferation and increases chem osensitivity to adriamycin in leukemic cells

Purpose: To elucidate the role of AKAP12 in leukemia cells.Methods: Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blotting (WB) were employed to determine the expression of AKAP12 in leukocyte cell lines, while 5-azacytidine was used to treat the cells, followed by assessment of the expression of AKAP12. After constructing the overexpressing vector pc-AKAP12 and transfecting it into cells or treating the cells with 5-azacytidine, cell counting kit-8 assay (CCK-8) was used to determine cell proliferation. Cloning ability of the cells was evaluated by colony formation assay.  Furthermore, flow cytometry was employed to measure the degrees of cell cycle and cell apoptosis. The effect of AKAP12 on PI3K/AKT were determined by western blot.Results: The results showed that AKAP12 was lowly expressed in lymphocytic leukemia cell lines (p < 0.001), but was reversed by 5-azacytidine. Transfection of AKAP12 or 5-azacytidine treatment increased the expression of AKAP12 in the cells (p > 0.001), inhibited leukemia cell proliferation and clonality, and arrested cell cycle in G1 phase as well as induced apoptosis. In addition, PI3K/AKT signaling pathway was inhibited by AKAP12.Conclusion: AKAP12 is lowly expressed in leukemia cells, and may also play a role in inhibiting leukemia progression by suppressing the activity of PI3K/AKT pathway.Thus, targeting AKAP12 mght be a potential strategy in the management of lukemia

The gas temperature in flaring disks around pre-main sequence stars

A model is presented which calculates the gas temperature and chemistry in the surface layers of flaring circumstellar disks using a code developed for photon-dominated regions. Special attention is given to the influence of dust settling. It is found that the gas temperature exceeds the dust temperature by up to several hundreds of Kelvins in the part of the disk that is optically thin to ultraviolet radiation, indicating that the common assumption that Tgas=Tdust is not valid throughout the disk. In the optically thick part, gas and dust are strongly coupled and the gas temperature equals the dust temperature. Dust settling has little effect on the chemistry in the disk, but increases the amount of hot gas deeper in the disk. The effects of the higher gas temperature on several emission lines arising in the surface layer are examined. The higher gas temperatures increase the intensities of molecular and fine-structure lines by up to an order of magnitude, and can also have an important effect on the line shapes.Comment: 14 pages, 10 figures, accepted for publication in A&

Detection of a MicroRNA Signal in an In Vivo Expression Set of mRNAs

Background. microRNAs (miRNAs) are approximately 21 nucleotide non-coding transcripts capable of regulating gene expression. The most widely studied mechanism of regulation involves binding of a miRNA to the target mRNA. As a result, translation of the target mRNA is inhibited and the mRNA may be destabilized. The inhibitory effects of miRNAs have been linked to diverse cellular processes including malignant proliferation, apoptosis, development, differentiation, and metabolic processes. We asked whether endogenous fluctuations in a set of mRNA and miRNA profiles contain correlated changes that are statistically distinguishable from the many other fluctuations in the data set. Methodology/Principal Findings. RNA was extracted from 12 human primary brain tumor biopsies. These samples were used to determine genome-wide mRN

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Concurrent detection of cabozantinib as an anticancer agent and its major metabolites in human serum using fluorescence-coupled micellar liquid chromatography

A novel, highly sensitive, simple, and rapid strategy was designed and developed for simultaneous determination of cabozantinib (CBZ) as an anticancer agent and its main metabolites including monohydroxy sulfate (EXEL-1646), N-oxide (EXEL-5162(, amide cleavage product (EXEL-5366), and 6-desmethyl amide cleavage product sulfate) EXEL-1644). Measurements were done through a micellar liquid chromatography (MLC) method coupled with fluorescence detection. The high-performance liquid chromatography (HPLC) was performed using a Kinetex C18 100 Å column as well as acetonitrile, cetyltrimethylammonium bromide (CTAB; 0.2 mol.L−1), and tris buffer (pH 8.5) solutions as the mobile phase at a 40:50:10 (v/v) ratio. The method’s linearity (20 to 700 ng.mL−1), limit of detection (LOD; 2.11 to 3.69 ng.mL−1), limit of quantification (LOQ; 20 to 30 ng.mL−1), intra- and inter-day precisions (RSD < 4.00%), selectivity, recovery, and robustness were fully evaluated. According to the obtained results, the developed method can be used for simple and rapid (~35 min) quantification of CBZ as an anticancer drug and its major metabolites in human serum samples with high sensitivity and low cost

Group Decision Making-Based Fusion for Human Activity Recognition in Body Sensor Networks

Ensemble learning systems (ELS) have been widely utilized for human activity recognition (HAR) with multiple homogeneous or heterogeneous sensors. However, traditional ensemble approaches for HAR cannot always work well due to insufficient accuracy and diversity of base classifiers, the absence of ensemble pruning, as well as the inefficiency of the fusion strategy. To overcome these problems, this paper proposes a novel selective ensemble approach with group decision-making (GDM) for decision-level fusion in HAR. As a result, the fusion process in the ELS is transformed into an abstract process that includes individual experts (base classifiers) making decisions with the GDM fusion strategy. Firstly, a set of diverse local base classifiers are constructed through the corresponding mechanism of the base classifier and the sensor. Secondly, the pruning methods and the number of selected base classifiers for the fusion phase are determined by considering the diversity among base classifiers and the accuracy of candidate classifiers. Two ensemble pruning methods are utilized: mixed diversity measure and complementarity measure. Thirdly, component decision information from the selected base classifiers is combined by using the GDM fusion strategy and the recognition results of the HAR approach can be obtained. Experimental results on two public activity recognition datasets (The OPPORTUNITY dataset; Daily and Sports Activity Dataset (DSAD)) suggest that the proposed GDM-based approach outperforms the well-known fusion techniques and other state-of-the-art approaches in the literature

Detection of an Incipient Fault for Dual Three-Phase PMSMs Using a Modified Autoencoder

For the detection of incipient interturn short-circuit (IITSC) faults of machines without shutting them down, there are still shortcomings of insufficient incipient fault features and a high false alarm rate. This is especially the case for dual three-phase permanent magnet synchronous motors (PMSMs) with complex winding structures, and this kind of incipient fault detection is more complicated. To solve this detection difficulty, an IITSC detection method for dual three-phase PMSMs is proposed based on a modified deep autoencoder (MDAE). This autoencoder (AE) adopts an improved distribution metric combined with the maximum mean discrepancy (MMD) and the maximum covariance discrepancy (MCD) to extract the fault feature from the common features, which can improve the feature difference between the normal state and the incipient fault state. Then, the permutation entropy of the extracted features is calculated to detect the IITSC faults. The results illustrate that this method can not only detect IITSC faults online effectively and robustly, but also reduce the false alarm rate of the fault detection for dual three-phase PMSMs