69 research outputs found

    Small RNA interference-mediated gene silencing of heparanase abolishes the invasion, metastasis and angiogenesis of gastric cancer cells

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    <p>Abstract</p> <p>Background</p> <p>Heparanase facilitates the invasion and metastasis of cancer cells, and is over-expressed in many kinds of malignancies. Our studies indicated that heparanase was frequently expressed in advanced gastric cancers. The aim of this study is to determine whether silencing of heparanase expression can abolish the malignant characteristics of gastric cancer cells.</p> <p>Methods</p> <p>Three heparanase-specific small interfering RNA (siRNAs) were designed, synthesized, and transfected into cultured gastric cancer cell line SGC-7901. Heparanase expression was measured by RT-PCR, real-time quantitative PCR and Western blot. Cell proliferation was detected by MTT colorimetry and colony formation assay. The <it>in vitro </it>invasion and metastasis of cancer cells were measured by cell adhesion assay, scratch assay and matrigel invasion assay. The angiogenesis capabilities of cancer cells were measured by tube formation of endothelial cells.</p> <p>Results</p> <p>Transfection of siRNA against 1496-1514 bp of encoding regions resulted in reduced expression of heparanase, which started at 24 hrs and lasted for 120 hrs post-transfection. The siRNA-mediated silencing of heparanase suppressed the cellular proliferation of SGC-7901 cells. In addition, the <it>in vitro </it>invasion and metastasis of cancer cells were attenuated after knock-down of heparanase. Moreover, transfection of heparanase-specific siRNA attenuated the <it>in vitro </it>angiogenesis of cancer cells in a dose-dependent manner.</p> <p>Conclusions</p> <p>These results demonstrated that gene silencing of heparanase can efficiently abolish the proliferation, invasion, metastasis and angiogenesis of human gastric cancer cells <it>in vitro</it>, suggesting that heparanase-specific siRNA is of potential values as a novel therapeutic agent for human gastric cancer.</p

    A Subset of Latency-Reversing Agents Expose HIV-Infected Resting CD4⁺ T-Cells to Recognition by Cytotoxic T-Lymphocytes

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    Resting CD4⁺ T-cells harboring inducible HIV proviruses are a critical reservoir in antiretroviral therapy (ART)-treated subjects. These cells express little to no viral protein, and thus neither die by viral cytopathic effects, nor are efficiently cleared by immune effectors. Elimination of this reservoir is theoretically possible by combining latency-reversing agents (LRAs) with immune effectors, such as CD8⁺ T-cells. However, the relative efficacy of different LRAs in sensitizing latently-infected cells for recognition by HIV-specific CD8⁺ T-cells has not been determined. To address this, we developed an assay that utilizes HIV-specific CD8⁺ T-cell clones as biosensors for HIV antigen expression. By testing multiple CD8⁺ T-cell clones against a primary cell model of HIV latency, we identified several single agents that primed latently-infected cells for CD8⁺ T-cell recognition, including IL-2, IL-15, two IL-15 superagonists (IL-15SA and ALT-803), prostratin, and the TLR-2 ligand Pam₃CSK₄. In contrast, we did not observe CD8⁺ T-cell recognition of target cells following treatment with histone deacetylase inhibitors or with hexamethylene bisacetamide (HMBA). In further experiments we demonstrate that a clinically achievable concentration of the IL-15 superagonist ‘ALT-803’, an agent presently in clinical trials for solid and hematological tumors, primes the natural ex vivo reservoir for CD8⁺ T-cell recognition. Thus, our results establish a novel experimental approach for comparative evaluation of LRAs, and highlight ALT-803 as an LRA with the potential to synergize with CD8⁺ T-cells in HIV eradication strategies.United States. National Institutes of Health (AI111860

    Large Scale Metric Learning for Distance-Based Image Classification on Open Ended Data Sets

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    International audienceMany real-life large-scale datasets are open-ended and dynamic: new images are continuously added to existing classes, new classes appear over time, and the semantics of existing classes might evolve too. Therefore, we study large-scale image classification methods that can incorporate new classes and training images continuously over time at negligible cost. To this end we consider two distance-based classifiers, the k-nearest neighbor (k-NN) and nearest class mean (NCM) classifiers. Since the performance of distance-based classifiers heavily depends on the used distance function, we cast the problem into one of learning a low-rank metric, which is shared across all classes. For the NCM classifier we introduce a new metric learning approach, and we also introduce an extension to allow for richer class representations. Experiments on the ImageNet 2010 challenge dataset, which contains over one million training images of thousand classes, show that, surprisingly, the NCM classifier compares favorably to the more flexible k-NN classifier. Moreover, the NCM performance is comparable to that of linear SVMs which obtain current state-of-the-art performance. Experimentally we study the generalization performance to classes that were not used to learn the metrics. Using a metric learned on 1,000 classes, we show results for the ImageNet-10K dataset which contains 10,000 classes, and obtain performance that is competitive with the current state-of-the-art, while being orders of magnitude faster

    Prevalence and trend of hepatitis C virus infection among blood donors in Chinese mainland: a systematic review and meta-analysis

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    <p>Abstract</p> <p>Background</p> <p>Blood transfusion is one of the most common transmission pathways of hepatitis C virus (HCV). This paper aims to provide a comprehensive and reliable tabulation of available data on the epidemiological characteristics and risk factors for HCV infection among blood donors in Chinese mainland, so as to help make prevention strategies and guide further research.</p> <p>Methods</p> <p>A systematic review was constructed based on the computerized literature database. Infection rates and 95% confidence intervals (95% CI) were calculated using the approximate normal distribution model. Odds ratios and 95% CI were calculated by fixed or random effects models. Data manipulation and statistical analyses were performed using STATA 10.0 and ArcGIS 9.3 was used for map construction.</p> <p>Results</p> <p>Two hundred and sixty-five studies met our inclusion criteria. The pooled prevalence of HCV infection among blood donors in Chinese mainland was 8.68% (95% CI: 8.01%-9.39%), and the epidemic was severer in North and Central China, especially in Henan and Hebei. While a significant lower rate was found in Yunnan. Notably, before 1998 the pooled prevalence of HCV infection was 12.87% (95%CI: 11.25%-14.56%) among blood donors, but decreased to 1.71% (95%CI: 1.43%-1.99%) after 1998. No significant difference was found in HCV infection rates between male and female blood donors, or among different blood type donors. The prevalence of HCV infection was found to increase with age. During 1994-1995, the prevalence rate reached the highest with a percentage of 15.78% (95%CI: 12.21%-19.75%), and showed a decreasing trend in the following years. A significant difference was found among groups with different blood donation types, Plasma donors had a relatively higher prevalence than whole blood donors of HCV infection (33.95% <it>vs </it>7.9%).</p> <p>Conclusions</p> <p>The prevalence of HCV infection has rapidly decreased since 1998 and kept a low level in recent years, but some provinces showed relatively higher prevalence than the general population. It is urgent to make efficient measures to prevent HCV secondary transmission and control chronic progress, and the key to reduce the HCV incidence among blood donors is to encourage true voluntary blood donors, strictly implement blood donation law, and avoid cross-infection.</p
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