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Genetic analysis suggests that the TGD2 protein of Arabidopsis is required for the biosynthesis of endoplasmic reticulum derived thylakoid lipids. TGD2 is proposed to be the substrate-binding protein of a presumed lipid transporter consisting of the TGD1 (permease) and TGD3 (ATPase) proteins. The TGD1, -2, and -3 proteins are localized in the inner chloroplast envelope membrane. TGD2 appears to be anchored with an N-terminal membrane-spanning domain into the inner envelope membrane, whereas the C-terminal domain faces the intermembrane space. It was previously shown that the C-terminal domain of TGD2 binds phosphatidic acid (PtdOH). To investigate the PtdOH binding site of TGD2 in detail, the C-terminal domain of the TGD2 sequence lacking the transit peptide and transmembrane sequences was fused to the C terminus of the Discosoma sp. red fluorescent protein (DR). This greatly improved the solubility of the resulting DR-TGD2C fusion protein following production in Escherichia coli. The DR-TGD2C protein bound PtdOH with high specificity, as demonstrated by membrane lipid-protein overlay and liposome association assays. Internal deletion and truncation mutagenesis identified a previously undescribed minimal 25-amino acid fragment in the C-terminal domain of TGD2 that is sufficient for PtdOH binding. Binding characteristics of this 25-mer were distinctly different from those of TGD2C, suggesting that additional sequences of TGD2 providing the proper context for this 25-mer are needed for wild type-like PtdOH binding.

Polar lipid trafficking is essential in eukaryotic cells as membranes of lipid assembly are often distinct from final destination membranes. A striking example is the biogenesis of the photosynthetic membranes (thylakoids) in plastids of plants. Lipid biosynthetic enzymes at the endoplasmic reticulum and the inner and outer plastid envelope membranes are involved. This compartmentalization requires extensive lipid trafficking. Mutants of Arabidopsis are available that are disrupted in the incorporation of endoplasmic reticulum-derived lipid precursors into thylakoid lipids. Two proteins affected in two of these mutants, trigalactosyldiacylglycerol 1 (TGD1) and TGD2, encode the permease and substrate binding component, respectively, of a proposed lipid translocator at the inner chloroplast envelope membrane. Here we describe a third protein of Arabidopsis, TGD3, a small ATPase proposed to be part of this translocator. As in the tgd1 and tgd2 mutants, triacylglycerols and trigalactolipids accumulate in a tgd3 mutant carrying a T-DNA insertion just 5' of the TGD3 coding region. The TGD3 protein shows basal ATPase activity and is localized inside the chloroplast beyond the inner chloroplast envelope membrane. Proteins orthologous to TGD1, -2, and -3 are predicted to be present in Gram- bacteria, and the respective genes are organized in operons suggesting a common biochemical role for the gene products. Based on the current analysis, it is hypothesized that TGD3 is the missing ATPase component of a lipid transporter involving TGD1 and TGD2 required for the biosynthesis of ER-derived thylakoid lipids in Arabidopsis.

The purpose of this study was to evaluate and compare the cytotoxicity and gene expression profiles in cell cultures exposed to whole smoke generated from a full flavor cigarette (Test 1), a low tar cigarette (Test 2), and an ultra-low tar cigarette (Test 3). In addition, a reference cigarette 2R4F was evaluated for cytotoxicity. Neutral red (NR) cytotoxicity assay was performed to determine relative cell death at each exposure concentration (n = 6). LC(50) was generated using wet total particular matter (WTPM), cigarette number, or nicotine concentrations. The overall order of cytotoxicity was Test 12R4F approximately Test 2Test 3. Cell culture samples were collected for RNA extraction at WTPM concentrations of each cigarette that gave similar nicotine concentrations. Affymetrix mouse whole genome 430 2.0 array was used to characterize the gene expression profiles for each cigarette. A total of 598 genes in Test 1, 176 genes in Test 2, and 234 genes in Test 3 samples were differentially expressed compared to the concurrent sham controls. The major biological processes associated with the changed genes in Test 1 samples were down-regulated DNA replication and cell proliferation; the same biological processes were much less affected in Test 2 and Test 3 samples. The common findings in all three cigarettes types were increased glutathione biosynthesis/consumption and inflammatory response, which are known biological effects caused by smoke exposure. The most significantly up-regulated genes were CYP1A1, GSTs, Hmox1, and Procr in smoke-exposed samples, which are either related to well-studied mechanisms of smoke exposure-related diseases or potential new biomarkers for assessing and monitoring biological effects of cigarette smoke exposure in vivo and in smokers. In summary, both the NR cytotoxicity assay and gene expression profiling were able to differentiate the three types of test cigarettes, and the results demonstrated reduced biological effects for the Test 2 and Test 3 cigarettes compared to the Test 1 cigarette in BALB/c-3T3 Cells.

Despite the widespread adoption of heterogeneous clusters in modern data centers, modeling heterogeneity is still a big challenge, especially for large-scale MapReduce applications. In a CPU/GPU hybrid heterogeneous cluster, allocating more computing resources to a MapReduce application does not always mean better performance, since simultaneously running CPU and GPU tasks will contend for shared resources. This paper proposes a heterogeneity model to predict the shared resource contention between the simultaneously running tasks of a MapReduce application when heterogeneous computing resources (e.g. CPUs and GPUs) are allocated. To support the approach, we present a heterogeneous MapReduce framework, Hadoop+, which enables CPUs and GPUs to process big data coordinately, and leverages the heterogeneity model to assist users in selecting the computing resources for different purposes. Our experimental results show three benefits. First, Hadoop+ exploits GPU capability, and achieves 1.4x to 16.1x speedups over Hadoop for 5 real applications when running individually. Second, the heterogeneity model can be used to allocate GPUs among multiple simultaneously running MapReduce applications, bringing up to 36.9% (17.6% in average) speedup when multiple applications are running simultaneously. Third, the model is verified to be able to select the optimal or most cost-effective resource consumption.

To develop a simple and rapid method for the simultaneous determination of nicotine and its nine metabolites in rat blood, an in vivo microdialysis sampling technique coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was established for quantitation and characterization of the pharmacokinetics of nicotine and its metabolites. Microdialysis probes were inserted into the jugular vein of Sprague Dawley rats, and dialysates were collected after nicotine (0.5 mg/kg, i.p.) administration. Target analytes and corresponding deuterated internal standards were separated on a hydrophilic interaction liquid chromatography column (HILIC BEH 2.1. × 150 mm, 1.7 μm) and detected by UPLC-MS/MS under multiple reaction monitoring mode. The limits of quantification for nicotine and its nine metabolites ranged from 0.039 to 0.46 ng/mL. Intra- and inter-day precision and accuracy were well within the predefined limits of acceptability (

The process of electroless copper plating, using sodium hypophosphite as the reductant and sodium citrate as the chelating agent, was studied using liner sweep voltammetry. The effects of temperature, pH, and concentration of nickel ion on the anodic oxidation of hypophosphite and the cathodic reduction of copper ion were tested. The results indicated that the higher bath temperature accelerated both the anodic and the cathodic processes. The increasing pH value promoted hypophosphite oxidation, whereas it blocked the reduction of the copper ion. The nickel ion not only intensively catalyzed the hypophosphite oxidation but also codeposited with the copper ion to form the Cu-Ni alloy. With regard to its catalytic activity, this alloy enabled the continuation of the electroless copper plating reaction.

Many factors, including exogenous carbon metabolites influence the expression of enzymes involved in nitrogen metabolism, but little is known about the effect of low temperature on the expression of those enzymes. To investigate that rice (Oryza sativa L.) seedlings grown at the optimal temperature (30 °C) were subjected to low temperature (20 °C) stress, and several key enzymes involved in ammonium assimilation and carbon metabolism, including glutamine synthetase (GS; EC 6.3.1.2), NADP-dependent isocitrate dehydrogenase (NADP-ICDH; EC 1.1.1.42), and NAD(H)-dependent glutamate dehydrogenase (GDH; EC 1.4.1.2) from rice roots were assessed. At low temperature, GS and ICDH activities were increased by 80 and 75%, respectively; thus, a positive parallel correlation was observed between the two enzymes. Native-PAGE analysis, together with activity staining and Western blot assays, showed that both GSrb activity and GSrb protein level were enhanced under low temperature. Meanwhile, NADH-GDH and NAD-GDH activity were both reduced, though to different extents. Biomass, NH4+, pH, and proline were measured as well. At low temperature, ammonium absorption was stimulated by the elevation of GS activity. Proline content was increased two-fold by low temperature, and this accumulation was in good agreement with the induction of GS activity. Similar observations were made in the rice roots fed with sucrose, indicating that at least partially low temperature has the similar effect as carbon compounds on the modulation of nitrogen metabolism. The possibility of the regulation of this metabolic pathway by 2-oxoglurate (2-OG) is discussed.

Spatial statistics is a growing discipline providing important analytical techniques in a wide range of disciplines in the natural and social sciences. In the R package GWmodel, we introduce techniques from a particular branch of spatial statistics, termed geographically weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localised calibration provides a better description. The approach uses a moving window weighting technique, where localised models are found at target locations. Outputs are mapped to provide a useful exploratory tool into the nature of the data spatial heterogeneity. GWmodel includes: GW summary statistics, GW principal components analysis, GW regression, GW regression with a local ridge compensation, and GW regression for prediction; some of which are provided in basic and robust forms., 43 pages, 14 figures

In this study, we present a collection of local models, termed geographically weighted (GW) models, that can be found within the GWmodel R package. A GW model suits situations when spatial data are poorly described by the global form, and for some regions the localised fit provides a better description. The approach uses a moving window weighting technique, where a collection of local models are estimated at target locations. Commonly, model parameters or outputs are mapped so that the nature of spatial heterogeneity can be explored and assessed. In particular, we present case studies using: (i) GW summary statistics and a GW principal components analysis; (ii) advanced GW regression fits and diagnostics; (iii) associated Monte Carlo significance tests for non-stationarity; (iv) a GW discriminant analysis; and (v) enhanced kernel bandwidth selection procedures. General Election data sets from the Republic of Ireland and US are used for demonstration. This study is designed to complement a companion GWmodel study, which focuses on basic and robust GW models.

Polo-like kinase 1 is a serine/threonine kinase which plays an essential role in mitosis and malignant transformation. The aim of this study was to investigate the prognostic significance of polo-like kinase 1 expression and determine its possibility as a therapeutic target in non-small cell lung cancer. Semi-quantitative RT-PCR assay was performed to detect polo-like kinase 1 mRNA expression in non-small cell lung cancer cells or tissues. Immunohistochemistry was performed to detect polo-like kinase 1 protein expression in 100 non-small cell lung cancer tissue samples, and the associations of polo-like kinase 1 expression with clinicopathological factors or prognosis of non-small cell lung cancer patients were evaluated. RNA interference was employed to inhibit endogenous polo-like kinase 1 expression and analyzed the effects of polo-like kinase 1 inhibition on the malignant phenotypes of non-small cell lung cancer cells including growth, apoptosis, radio- or chemoresistance. Also, the possible molecular mechanisms were also investigated. The levels of polo-like kinase 1 mRNA expression in non-small cell lung cancer cell lines or tissues were significantly higher than those in normal human bronchial epithelial cell line or corresponding non-tumor tissues. High polo-like kinase 1 expression was significantly correlated with advanced clinical stage, higher tumor classification and lymph node metastasis of non-small cell lung cancer patients (P=0.001, 0.004 and 0.001, respectively). Meanwhile, high polo-like kinase 1 protein expression was also an independent prognostic molecular marker for non-small cell lung cancer patients (hazard ratio: 2.113; 95% confidence interval: 1.326-3.557; P=0.017). Polo-like kinase 1 inhibition could significantly inhibit in vitro and in vivo proliferation, induce cell arrest of G(2)/M phase and apoptosis enhancement in non-small cell lung cancer cells, which might be activation of the p53 pathway and the Cdc25C/cdc2/cyclin B1 feedback loop. Further, inhibition of polo-like kinase 1 could enhance the sensitivity of non-small cell lung cancer cells to taxanes or irradiation. Thus, polo-like kinase 1 might be a prognostic marker and a chemo- or radiotherapeutic target for non-small cell lung cancer.

Tumor growth depends on angiogenesis and inducing angiogenesis is one of the most important hallmarks in the cancer development. Treatment with small molecules that inhibit angiogenesis has been an effective strategy for anti-cancer therapy. Some anti-angiogenic factors are derived from traditional Chinese herbs. Usnic acid (UA), an active compound mainly found in lichens, has shown some biological and physiological activities. However, the role and mechanism of UA in tumor angiogenesis are still unknown. The aim of this study was to assess the effects of UA on tumor angiogenesis. In this study, we demonstrated that UA strongly inhibited in vivo angiogenesis in a chick embryo chorioallantoic membrane assay and vascular endothelial growth factor-induced mouse corneal angiogenesis model. In a mouse xenograft tumor model, UA suppressed Bcap-37 breast tumor growth and angiogenesis without affecting mice body weight. In an in vitro assay, UA not only significantly inhibited endothelial cell proliferation, migration and tube formation, but also induced morphological changes and apoptosis in endothelial cells. In addition, UA inhibited Bcap-37 tumor cell proliferation. Moreover, western blot analysis of cell signaling molecules indicated that UA blocked vascular endothelial growth factor receptor (VEGFR) 2 mediated Extracellular signal-regulated protein kinases 1 and 2(ERK1/2) and AKT/P70S6K signaling pathways in endothelial cells. These results provided the first evidence of the biological function and molecular mechanism of UA in tumor angiogenesis.

Geographically Weighted Regression (GWR) is a local modelling technique to estimate regression models with spatially varying relationships. Generally, the Euclidean distance is the default metric for calibrating a GWR model in previous research and applications; however, it may not always be the most reasonable choice due to a partition by some natural or man-made features. Thus, we attempt to use a non-Euclidean distance metric in GWR. In this study, a GWR model is established to explore spatially varying relationships between house price and floor area with sampled house prices in London. To calibrate this GWR model, network distance is adopted. Compared with the other results from calibrations with Euclidean distance or adaptive kernels, the output using network distance with a fixed kernel makes a significant improvement, and the river Thames has a clear cut-off effect on the parameter estimations.

Cucurbitacin E (CuE, α-elaterin), a tetracyclic triterpenes compound from folk traditional Chinese medicine plants, has been shown to inhibit cancer cell growth, inflammatory response and bilirubin-albumin binding. However, the effects of CuE on tumor angiogenesis and its potential molecular mechanism are still unknown. Here, we demonstrated that CuE significantly inhibited human umbilical vascular endothelial cell (HUVEC) proliferation, migration and tubulogenesis in vitro and blocked angiogenesis in chick embryo chorioallantoic membrane assay and mouse corneal angiogenesis model in vivo. Furthermore, we found that CuE remarkably induced HUVEC apoptosis, inhibited tumor angiogenesis and suppressed human prostate tumor growth in xenograft tumor model. Finally, we showed that CuE blocked vascular endothelial growth factor receptor (VEGFR) 2-mediated Janus kinase (Jak) 2-signal transducer and activator of transcription (STAT) 3 signaling pathway in endothelial cells and suppressed the downstream protein kinases, such as extracellular signal-regulated kinase and p38 mitogen-activated protein kinases. Therefore, our studies provided the first evidence that CuE inhibited tumor angiogenesis by inhibiting VEGFR2-mediated Jak-STAT3 and mitogen-activated protein kinases signaling pathways and CuE is a potential candidate in angiogenesis-related disease therapy.

This paper presents layout optimization methods for complementary pass-transistor adiabatic logic (CPAL) circuits in order to make the circuits more energy-efficient. The layout optimisations for a low-power tree multiplier based on modified Booth algorithm is carried out. The multiplier has been realized with TSMC 0.18µm CMOS process technology with full-custom layouts, and full parasitic extraction is done. Compared with its layout of counterpart in conventional logic (static complementary CMOS logic), the adiabatic multiplier attains large energy savings.

In this paper, a successful research result from CAD-Grid (China-Austria-Cooperation-Grid-Frame), called as CA-RS-EP-PTBG (China-Austria-cooperation remote-sensing-embedded-parallel pre-treatment-service-base-of-Grid), is depicted. It helps scientists on various fields of information analysis and data mining for treating data conveniently with a high speed, sharing resource on-line, calling different independent services remotely and executing them flexibly.

The photosynthetic (thylakoid) membrane of plants is one of the most extensive biological cell membrane systems found in Nature. It harbours the photosynthetic apparatus, which is essential to life on Earth as carbon dioxide is fixed and atmospheric oxygen released by photosynthesis. Lipid biosynthetic enzymes of different subcellular compartments participate in the biogenesis of the thylakoid membrane system. This process requires the extensive exchange of lipid precursors between the chloroplast and the ER (endoplasmic reticulum). The underlying lipid trafficking phenomena are not yet understood at the mechanistic level, but genetic mutants of the model plant Arabidopsis thaliana with disruptions in lipid trafficking between the ER and the chloroplast have recently become available. Their study has led to the identification of components of the lipid transfer machinery at the inner chloroplast envelope.

Recent evidence indicates that long noncoding RNAs (lncRNAs) have a critical role in the regulation of cellular processes such as differentiation, proliferation, and metastasis. These lncRNAs are dysregulated in a variety of cancers and many function as tumor suppressors; however, the regulatory factors involved in silencing lncRNA transcription are poorly understood. In this study, we showed that epigenetic silencing of lncRNA SPRY4 intronic transcript 1 (SPRY4-IT1) occurs in non-small-cell lung cancer (NSCLC) cells through direct transcriptional repression mediated by the Polycomb group protein enhancer of zeste homolog 2 (EZH2). SPRY4-IT1 is derived from an intron within SPRY4, and is upregulated in melanoma cells; knockdown of its expression leads to cell growth arrest, invasion inhibition, and elevated rates of apoptosis. Upon depletion of EZH2 by RNA interference, SPRY4-IT1 expression was restored, and transfection of SPRY4-IT1 into NSCLC cells resulted in a significant antitumoral effect, both in culture and in xenografted nude mice. Moreover, overexpression of SPRY4-IT1 was found to have a key role in the epithelial–mesenchymal transition through the regulation of E-cadherin and vimentin expression. In EZH2-knockdown cells, which characteristically showed impaired cell proliferation and metastasis, the induction of SPRY4-IT1 depletion partially rescued the oncogenic phenotype, suggesting that SPRY4-IT1 repression has an important role in EZH2 oncogenesis. Of most relevance, translation of these findings into human NSCLC tissue samples demonstrated that patients with low levels of SPRY4-IT1 expression had a shorter overall survival time, suggesting that SPRY4-IT1 could be a biomarker for poor prognosis of NSCLC.

Background Aberrant expression of long noncoding RNAs (lncRNAs) has frequently been reported in cancer studies, including those of colorectal cancer (CRC). Increasing evidence suggests that lncRNAs are significantly correlated with the pathogenesis, development and metastasis of cancer. Loc554202 is a 2166-bp transcript on human chromosome 9p21.3, the expression of which is dysregulated in breast and lung cancer cells. However, its role in CRC remains under investigation. Methods Quantitative real-time polymerase chain reaction (qRT-PCR) was carried out to assess the relative expression of Loc554202 in CRC cell lines and tissues. Gain and/or loss of function approaches were used to investigate the potential functional roles in cell proliferation and apoptosis in vitro and in vivo. qRT-PCR, western-blotting and immunohistochemistry were used to evaluate the mRNA and protein expression of apoptosis-related factors. Results Loc554202 was significantly downregulated in cancerous tissues and CRC cell lines compared with adjacent normal tissue and a normal human intestinal epithelial cell line. Low Loc554202 expression was closely associated with advanced pathologic stage and a larger tumor size. The overexpression of Loc554202 decreased the cell proliferation and induced apoptosis in vitro and hindered tumorigenesis in vivo. Loc554202 regulated cell apoptosis partly through the activation of specific caspase cleavage cascades. Conclusion Our results suggest that Loc554202 may play an important role in the progression of CRC and could be a candidate prognostic biomarker or a target for new cancer therapies. Electronic supplementary material The online version of this article (doi:10.1186/s13046-015-0217-7) contains supplementary material, which is available to authorized users.

As an established spatial analytical tool, Geographically Weighted Regression (GWR) has been applied across a variety of disciplines. However, its usage can be challenging for large datasets, which are increasingly prevalent in today’s digital world. In this study, we propose two high-performance R solutions for GWR via Multi-core Parallel (MP) and Compute Unified Device Architecture (CUDA) techniques, respectively GWR-MP and GWR-CUDA. We compared GWR-MP and GWR-CUDA with three existing solutions available in Geographically Weighted Models (GWmodel), Multi-scale GWR (MGWR) and Fast GWR (FastGWR). Results showed that all five solutions perform differently across varying sample sizes, with no single solution a clear winner in terms of computational efficiency. Specifically, solutions given in GWmodel and MGWR provided acceptable computational costs for GWR studies with a relatively small sample size. For a large sample size, GWR-MP and FastGWR provided coherent solutions on a Personal Computer (PC) with a common multi-core configuration, GWR-MP provided more efficient computing capacity for each core or thread than FastGWR. For cases when the sample size was very large, and for these cases only, GWR-CUDA provided the most efficient solution, but should note its I/O cost with small samples. In summary, GWR-MP and GWR-CUDA provided complementary high-performance R solutions to existing ones, where for certain data-rich GWR studies, they should be preferred.

Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces.

In standard geographically weighted regression (GWR), the spatially-varying relationships between the dependent and each independent variable are explored under a constant and fixed scale, but for many processes their variation intensity may differ with respect to location and direction. To address this short-coming, a GWR model with parameter-specific distance metrics (PSDM GWR) can be used, which by default, also specifies parameter specific bandwidths. In doing so, PSDM GWR provides a scale-dependent extension of GWR. Commonly however, an ideal distance metric for a given independent variable parameter is not immediately obvious. Thus, in this article, PSDM GWR is investigated with respect to distance metric choice. Here, it is demonstrated that the optimum (distance metric specific) bandwidth corresponding to a given independent variable remains essentially constant, independent of the choices made for the other independent variables. This result allows for a considerable saving in computational overheads, permitting a much simpler searching procedure for multiple bandwidth optimization. Results are first demonstrated empirically, and then a simulation experiment is conducted to objectively verify the same findings. Computational savings are vital to the uptake of PSDM GWR, where ultimately, it should be considered the default choice in any GWR-based study of spatially-varying relationships, as standard GWR, mixed (or semi-parametric) GWR, flexible bandwidth (or multi-scale) GWR and the global regression are specific cases thereof.