159 research outputs found

    Solving an Optimal Control Problem of Cancer Treatment by Artificial Neural Networks

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    Cancer is an uncontrollable growth of abnormal cells in any tissue of the body. Many researchers have focused on machine learning and artificial intelligence (AI) based on approaches for cancer treatment. Dissimilar to traditional methods, these approaches are efficient and are able to find the optimal solutions of cancer chemotherapy problems. In this paper, a system of ordinary differential equations (ODEs) with the state variables of immune cells, tumor cells, healthy cells and drug concentration is proposed to anticipate the tumor growth and to show their interactions in the body. Then, an artificial neural network (ANN) is applied to solve the ODEs system through minimizing the error function and modifying the parameters consisting of weights and biases. The mean square errors (MSEs) between the analytical and ANN results corresponding to four state variables are 1.54e-06, 6.43e-07, 6.61e-06, and 3.99e-07, respectively. These results show the good performance and efficiency of the proposed method. Moreover, the optimal dose of chemotherapy drug and the amount of drug needed to continue the treatment process are achieved

    Expression analysis of carbohydrate antigens in ductal carcinoma in situ of the breast by lectin histochemistry

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    <p>Abstract</p> <p>Background</p> <p>The number of breast cancer patients diagnosed with ductal carcinoma <it>in situ </it>(DCIS) continues to grow. Laboratory and clinical data indicate that DCIS can progress to invasive disease. Carbohydrate-mediated cell-cell adhesion and tumor-stroma interaction play crucial roles in tumorigenesis and tumor aggressive behavior. Breast carcinogenesis may reflect quantitative as well as qualitative changes in oligosaccharide expression, which may provide a useful tool for early detection of breast cancer. Because tumor-associated carbohydrate antigens (TACA) are implicated in tumor invasion and metastasis, the purpose of this study was to assess the expression of selected TACA by lectin histochemistry on DCIS specimens from the archival breast cancer tissue array bank of the University of Arkansas for Medical Sciences.</p> <p>Methods</p> <p>For detection of TACA expression, specimens were stained with <it>Griffonia simplicifolia </it>lectin-I (GS-I) and <it>Vicia vilosa </it>agglutinin (VVA). We studied associations of lectin reactivity with established prognostic factors, such as tumor size, tumor nuclear grade, and expression of Her-2/neu, p53 mutant and estrogen and progesterone receptors.</p> <p>Results</p> <p>We observed that both lectins showed significant associations with nuclear grade of DCIS. DCIS specimens with nuclear grades II and III showed significantly more intense reactivity than DCIS cases with nuclear grade I to GS-1 (Mean-score chi-square = 17.60, DF = 2; <it>P </it>= 0.0002) and VVA (Mean-score chi-square = 15.72, DF = 2; <it>P </it>= 0.0004).</p> <p>Conclusion</p> <p>The results suggest that the expression of VVA- and GS-I-reactive carbohydrate antigens may contribute to forming higher grade DCIS and increase the recurrence risk.</p

    The geoaccumulation index and enrichment factor of mercury in mangrove sediment of Port Klang, Selangor, Malaysia.

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    Mangrove areas are important to the ecosystem. One of its crucial functions is as a sink of pollutants, especially metal ions. However, the accumulation of metals in mangrove sediment can generate negative impacts on plant growth, microbial activity, and soil fertility. Apart from that, the severity of the impact is highly influenced by the type of metal found in the sediment and the quality of sediment itself. One of the metals that have adverse effects on the environment is mercury. The objectives of this study are to determine the concentration and distribution of mercury and to assess the enrichment of mercury in Port Klang mangrove sediment by using geoaccumulation index and enrichment factor. Sediment samples were collected from 30 sampling points that cover Langat River and Klang River estuaries, Lumut Straits, Pulau Klang, and Pulau Indah. During sampling, water parameters such as pH, salinity, electrical conductivity, and total dissolved solids were measured in situ, whereas the total mercury in sediment samples was determined at the laboratory using inductively coupled plasma mass spectrometry. In this study, mercury was found to be concentrated along Lumut Strait especially in the mixing zone near the confluence of Langat River and at the jetty to Pulau Ketam. The geoaccumulation index and enrichment factor (calculated using logarithmized data of the reference element) found that three stations were enriched with mercury. In addition, geoaccumulation index was also observed to be more objective compared to enrichment factor whose results were influenced by the concentration of reference element used

    The Interaction of Canine Plasminogen with Streptococcus pyogenes Enolase: They Bind to One Another but What Is the Nature of the Structures Involved?

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    For years it has been clear that plasminogen from different sources and enolase from different sources interact strongly. What is less clear is the nature of the structures required for them to interact. This work examines the interaction between canine plasminogen (dPgn) and Streptococcus pyogenes enolase (Str enolase) using analytical ultracentrifugation (AUC), surface plasmon resonance (SPR), fluorescence polarization, dynamic light scattering (DLS), isothermal titration calorimetry (ITC), and simple pull-down reactions. Overall, our data indicate that a non-native structure of the octameric Str enolase (monomers or multimers) is an important determinant of its surface-mediated interaction with host plasminogen. Interestingly, a non-native structure of plasminogen is capable of interacting with native enolase. As far as we can tell, the native structures resist forming stable mixed complexes

    Integrated Assessment of Heavy Metal Contamination in Sediments from a Coastal Industrial Basin, NE China

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    The purpose of this study is to investigate the current status of metal pollution of the sediments from urban-stream, estuary and Jinzhou Bay of the coastal industrial city, NE China. Forty surface sediment samples from river, estuary and bay and one sediment core from Jinzhou bay were collected and analyzed for heavy metal concentrations of Cu, Zn, Pb, Cd, Ni and Mn. The data reveals that there was a remarkable change in the contents of heavy metals among the sampling sediments, and all the mean values of heavy metal concentration were higher than the national guideline values of marine sediment quality of China (GB 18668-2002). This is one of the most polluted of the world’s impacted coastal systems. Both the correlation analyses and geostatistical analyses showed that Cu, Zn, Pb and Cd have a very similar spatial pattern and come from the industrial activities, and the concentration of Mn mainly caused by natural factors. The estuary is the most polluted area with extremely high potential ecological risk; however the contamination decreased with distance seaward of the river estuary. This study clearly highlights the urgent need to make great efforts to control the industrial emission and the exceptionally severe heavy metal pollution in the coastal area, and the immediate measures should be carried out to minimize the rate of contamination, and extent of future pollution problems

    Linear and Branched Glyco-Lipopeptide Vaccines Follow Distinct Cross-Presentation Pathways and Generate Different Magnitudes of Antitumor Immunity

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    Glyco-lipopeptides, a form of lipid-tailed glyco-peptide, are currently under intense investigation as B- and T-cell based vaccine immunotherapy for many cancers. However, the cellular and molecular mechanisms of glyco-lipopeptides (GLPs) immunogenicity and the position of the lipid moiety on immunogenicity and protective efficacy of GLPs remain to be determined.We have constructed two structural analogues of HER-2 glyco-lipopeptide (HER-GLP) by synthesizing a chimeric peptide made of one universal CD4(+) epitope (PADRE) and one HER-2 CD8(+) T-cell epitope (HER(420-429)). The C-terminal end of the resulting CD4-CD8 chimeric peptide was coupled to a tumor carbohydrate B-cell epitope, based on a regioselectively addressable functionalized templates (RAFT), made of four alpha-GalNAc molecules. The resulting HER glyco-peptide (HER-GP) was then linked to a palmitic acid moiety, attached either at the N-terminal end (linear HER-GLP-1) or in the middle between the CD4+ and CD8+ T cell epitopes (branched HER-GLP-2). We have investigated the uptake, processing and cross-presentation pathways of the two HER-GLP vaccine constructs, and assessed whether the position of linkage of the lipid moiety would affect the B- and T-cell immunogenicity and protective efficacy. Immunization of mice revealed that the linear HER-GLP-1 induced a stronger and longer lasting HER(420-429)-specific IFN-gamma producing CD8(+) T cell response, while the branched HER-GLP-2 induced a stronger tumor-specific IgG response. The linear HER-GLP-1 was taken up easily by dendritic cells (DCs), induced stronger DCs maturation and produced a potent TLR- 2-dependent T-cell activation. The linear and branched HER-GLP molecules appeared to follow two different cross-presentation pathways. While regression of established tumors was induced by both linear HER-GLP-1 and branched HER-GLP-2, the inhibition of tumor growth was significantly higher in HER-GLP-1 immunized mice (p<0.005).These findings have important implications for the development of effective GLP based immunotherapeutic strategies against cancers
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