Combination of dasatinib and curcumin eliminates chemo-resistant colon cancer cells

Metastatic colorectal cancer remains a serious health concern with poor patient survival. Although 5-Fluorouracil (5-FU) or 5-FU plus oxaliplatin (FOLFOX) is the standard therapy for colorectal cancer, it has met with limited success. Recurrence of the tumor after chemotherapy could partly be explained by the enrichment of the chemo-resistant sub-population of cancer stem cells (CSCs) that possess the ability for self-renewal and differentiation into different lineages in the tumor. Therefore development of therapeutic strategies that target CSCs for successful treatment of this malignancy is warranted. The current investigation was undertaken to examine the effectiveness of the combination therapy of dasatinib (a Src inhibitor) and curcumin (a dietary agent with pleiotropic effect) in inhibiting the growth and other properties of carcinogenesis of chemo-resistant colon cancer cells that are enriched in CSCs sub-population. Remnants of spontaneous adenomas from APCMin +/- mice treated with dasatinib and/or curcumin were analyzed for several cancer stem cell markers (ALDH, CD44, CD133 and CD166). Human colon cancer cells HCT-116 (p53 wild type; K-ras mutant) and HT-29 (p53 mutant; K-ras wild type) were used to generate FOLFOX resistant (referred to as CR) cells. The effectiveness of the combination therapy in inhibiting growth, invasive potential and stemness was examined in colon cancer CR cells. The residual tumors from APCMin +/- mice treated with dasatinib and/or curcumin showed 80-90% decrease in the expression of the CSC markers ALDH, CD44, CD133, CD166. The colon cancer CR cells showed a higher expression of CSCs markers, cell invasion potential and ability to form colonospheres, compared to the corresponding parental cells. The combination therapy of dasatinib and curcumin demonstrated synergistic interactions in CR HCT-116 and CR HT-29 cells, as determined by Calcusyn analysis. The combinatorial therapy inhibited cellular growth, invasion and colonosphere formation and also reduced CSC population as evidenced by the decreased expression of CSC specific markers: CD133, CD44, CD166 and ALDH. Our data suggest that the combination therapy of dasatinib and curcumin may be a therapeutic strategy for re-emergence of chemo-resistant colon cancer by targeting CSC sub-population

The Wnt/β-catenin pathway regulates growth and maintenance of colonospheres

<p>Abstract</p> <p>Background</p> <p>Recent evidence suggests that epithelial cancers, including colorectal cancer are driven by a small sub-population of self-renewing, multi-potent cells termed cancer stem cells (CSCs) which are thought to be responsible for recurrence of cancer. One of the characteristics of CSCs is their ability to form floating spheroids under anchorage-independent conditions in a serum-free defined media. The current investigation was undertaken to examine the role of Wnt/β-catenin pathway in regulating the growth and maintenance of colonospheres. Human colon cancer cells HCT-116 (p53 wild type; <it>K-ras </it>mutant), HCT-116 (p53 null; <it>K-ras </it>mutant) and HT-29 (p53 mutant) were used.</p> <p>Results</p> <p>Colonospheres formed <it>in vitro </it>exhibited higher expression of colon CSCs markers LGR5, CD44, CD166 and Musashi-1 along with putative CSC marker EpCAM, compared to the corresponding parental cancer cells and also exhibit the ability to form spheroids under extreme limiting dilution, indicating the predominance of CSCs in colonospheres. Colonospheres formed by HCT-116 cells show over 80% of the cells to be CD44 positive, compared to ≤ 1% in the corresponding parental cells. Additionally, colonospheres showed reduced membrane bound β-catenin but had increased levels of total β-catenin, cyclin-D1 and c-myc and down regulation of axin-1 and phosphorylated β-catenin. Increased expression of β-catenin was associated with a marked transcriptional activation of TCF/LEF. The latter was greatly decreased following down regulation of β-catenin by the corresponding siRNA, leading to a marked reduction in CD44 positive cells as well as colonospheres formation. In contrast, upregulation of c-myc, a down-stream effector of TCF/LEF greatly augmented the formation of colonospheres.</p> <p>Conclusion</p> <p>Our data suggest that colonospheres formed by colon cancer cell lines are highly enriched in CSCs and that Wnt/β-catenin pathway plays a critical role in growth and maintenance of colonospheres.</p

A Family of Maximum Margin Criterion for Adaptive Learning

In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D^2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are compenent to be adopted in complicated application scenarios.Comment: 14 page

Changing atmospheric CO2 concentration was the primary driver of early Cenozoic climate

The Early Eocene Climate Optimum (EECO, which occurred about 51 to 53 million years ago)1, was the warmest interval of the past 65 million years, with mean annual surface air temperature over ten degrees Celsius warmer than during the pre-industrial period2–4. Subsequent global cooling in the middle and late Eocene epoch, especially at high latitudes, eventually led to continental ice sheet development in Antarctica in the early Oligocene epoch (about 33.6 million years ago). However, existing estimates place atmospheric carbon dioxide (CO2) levels during the Eocene at 500–3,000 parts per million5–7, and in the absence of tighter constraints carbon–climate interactions over this interval remain uncertain. Here we use recent analytical and methodological developments8–11 to generate a new high-fidelity record of CO2 concentrations using the boron isotope (δ11Β) composition of well preserved planktonic foraminifera from the Tanzania Drilling Project, revising previous estimates6. Although species-level uncertainties make absolute values difficult to constrain, CO2 concentrations during the EECO were around 1,400 parts per million. The relative decline in CO2 concentration through the Eocene is more robustly constrained at about fifty per cent, with a further decline into the Oligocene12. Provided the latitudinal dependency of sea surface temperature change for a given climate forcing in the Eocene was similar to that of the late Quaternary period13, this CO2 decline was sufficient to drive the well documented high- and low-latitude cooling that occurred through the Eocene14. Once the change in global temperature between the pre-industrial period and the Eocene caused by the action of all known slow feedbacks (apart from those associated with the carbon cycle) is removed2–4, both the EECO and the late Eocene exhibit an equilibrium climate sensitivity relative to the pre-industrial period of 2.1 to 4.6 degrees Celsius per CO2 doubling (66 per cent confidence), which is similar to the canonical range (1.5 to 4.5 degrees Celsius15), indicating that a large fraction of the warmth of the early Eocene greenhouse was driven by increased CO2 concentrations, and that climate sensitivity was relatively constant throughout this period

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating

Exact score distribution computation for ontological similarity searches

<p>Abstract</p> <p>Background</p> <p>Semantic similarity searches in ontologies are an important component of many bioinformatic algorithms, e.g., finding functionally related proteins with the Gene Ontology or phenotypically similar diseases with the Human Phenotype Ontology (HPO). We have recently shown that the performance of semantic similarity searches can be improved by ranking results according to the probability of obtaining a given score at random rather than by the scores themselves. However, to date, there are no algorithms for computing the exact distribution of semantic similarity scores, which is necessary for computing the exact <it>P</it>-value of a given score.</p> <p>Results</p> <p>In this paper we consider the exact computation of score distributions for similarity searches in ontologies, and introduce a simple null hypothesis which can be used to compute a <it>P</it>-value for the statistical significance of similarity scores. We concentrate on measures based on Resnik's definition of ontological similarity. A new algorithm is proposed that collapses subgraphs of the ontology graph and thereby allows fast score distribution computation. The new algorithm is several orders of magnitude faster than the naive approach, as we demonstrate by computing score distributions for similarity searches in the HPO. It is shown that exact <it>P</it>-value calculation improves clinical diagnosis using the HPO compared to approaches based on sampling.</p> <p>Conclusions</p> <p>The new algorithm enables for the first time exact <it>P</it>-value calculation via exact score distribution computation for ontology similarity searches. The approach is applicable to any ontology for which the annotation-propagation rule holds and can improve any bioinformatic method that makes only use of the raw similarity scores. The algorithm was implemented in Java, supports any ontology in OBO format, and is available for non-commercial and academic usage under: <url>https://compbio.charite.de/svn/hpo/trunk/src/tools/significance/</url></p

Knowledge, attitudes and practices (KAP) relating to avian influenza in urban and rural areas of China

<p>Abstract</p> <p>Background</p> <p>Studies have revealed that visiting poultry markets and direct contact with sick or dead poultry are significant risk factors for H5N1 infection, the practices of which could possibly be influenced by people's knowledge, attitudes and practices (KAPs) associated with avian influenza (AI). To determine the KAPs associated with AI among the Chinese general population, a cross-sectional survey was conducted in China.</p> <p>Methods</p> <p>We used standardized, structured questionnaires distributed in both an urban area (Shenzhen, Guangdong Province; n = 1,826) and a rural area (Xiuning, Anhui Province; n = 2,572) using the probability proportional to size (PPS) sampling technique.</p> <p>Results</p> <p>Approximately three-quarters of participants in both groups requested more information about AI. The preferred source of information for both groups was television. Almost three-quarters of all participants were aware of AI as an infectious disease; the urban group was more aware that it could be transmitted through poultry, that it could be prevented, and was more familiar with the relationship between AI and human infection. The villagers in Xiuning were more concerned than Shenzhen residents about human AI viral infection. Regarding preventative measures, a higher percentage of the urban group used soap for hand washing whereas the rural group preferred water only. Almost half of the participants in both groups had continued to eat poultry after being informed about the disease.</p> <p>Conclusions</p> <p>Our study shows a high degree of awareness of human AI in both urban and rural populations, and could provide scientific support to assist the Chinese government in developing strategies and health-education campaigns to prevent AI infection among the general population.</p

Accreting Neutron Stars in Low-Mass X-Ray Binary Systems

Using the Rossi X-ray Timing Explorer (RossiXTE), astronomers have discovered that disk-accreting neutron stars with weak magnetic fields produce three distinct types of high-frequency X-ray oscillations. These oscillations are powered by release of the binding energy of matter falling into the strong gravitational field of the star or by the sudden nuclear burning of matter that has accumulated in the outermost layers of the star. The frequencies of the oscillations reflect the orbital frequencies of gas deep in the gravitational field of the star and/or the spin frequency of the star. These oscillations can therefore be used to explore fundamental physics, such as strong-field gravity and the properties of matter under extreme conditions, and important astrophysical questions, such as the formation and evolution of millisecond pulsars. Observations using RossiXTE have shown that some two dozen neutron stars in low-mass X-ray binary systems have the spin rates and magnetic fields required to become millisecond radio-emitting pulsars when accretion ceases, but that few have spin rates above about 600 Hz. The properties of these stars show that the paucity of spin rates greater than 600 Hz is due in part to the magnetic braking component of the accretion torque and to the limited amount of angular momentum that can be accreted in such systems. Further study will show whether braking by gravitational radiation is also a factor. Analysis of the kilohertz oscillations has provided the first evidence for the existence of the innermost stable circular orbit around dense relativistic stars that is predicted by strong-field general relativity. It has also greatly narrowed the possible descriptions of ultradense matter.Comment: 22 pages, 7 figures, updated list of sources and references, to appear in "Short-period Binary Stars: Observation, Analyses, and Results", eds. E.F. Milone, D.A. Leahy, and D. Hobill (Dordrecht: Springer, http://www.springerlink.com

Anti-tumor effect of adenovirus-mediated gene transfer of pigment epithelium-derived factor on mouse B16-F10 melanoma

<p>Abstract</p> <p>Background</p> <p>Angiogenesis plays an important role in tumor growth, invasion, and eventually metastasis. Antiangiogenic strategies have been proven to be a promising approach for clinical therapy for a variety of tumors. As a potent inhibitor of tumor angiogenesis, pigment epithelium-derived factor (PEDF) has recently been studied and used as an anticancer agent in several tumor models.</p> <p>Methods</p> <p>A recombined adenovirus carrying PEDF gene (Ad-PEDF) was prepared, and its expression by infected cells and in treated animals was confirmed with Western blotting and ELISA, respectively. Its activity for inhibiting human umbilical vein endothelial cell (HUVEC) proliferation was tested using the MTT assay. C57BL/6 mice bearing B16-F10 melanoma were treated with i.v. administration of 5 × 10⁸IU/mouse Ad-PEDF, or 5 × 10⁸IU/mouse Ad-Null, or normal saline (NS), every 3 days for a total of 4 times. Tumor volume and survival time were recorded. TUNEL, CD31 and H&E stainings of tumor tissue were conducted to examine apoptosis, microvessel density and histological morphology changes. Antiangiogenesis was determined by the alginate-encapsulated tumor cell assay.</p> <p>Results</p> <p>The recombinant PEDF adenovirus is able to transfer the PEDF gene to infected cells and successfully produce secretory PEDF protein, which exhibits potent inhibitory effects on HUVEC proliferation. Through inhibiting angiogenesis, reducing MVD and increasing apoptosis, Ad-PEDF treatment reduced tumor volume and prolonged survival times of mouse bearing B16-F10 melanoma.</p> <p>Conclusion</p> <p>Our data indicate that Ad-PEDF may provide an effective approach to inhibit mouse B16-F10 melanoma growth.</p