8 research outputs found

    Analisis Portofolio Optimal Dengan Single Index Model Untuk Meminimumkan Risiko Bagi Investor Di Bursa Efek Indonesia (Studi Pada Saham Indeks Kompas 100 Periode Februari 2010-juli 2014)

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    Investments can be made in the capital market, capital market instruments which are mostly attractive for investors is stock. Stock provides a return in the form of capital gains and dividends yield, not only noticing the return, investors need to pay attention to the investments risk. Unsystematis risk can be minimized by forming the optimal portfolio using one of the methods that is single index model. Study purpose is to knowing the stocks forming the optimal portfolio, the proportion of funds allocated to each stocks, the level of expectation return and risk.The method used in this research is descriptive research method with a quantitative approach. The samples used were 46 stocks in Kompas 100 Index, which meets the criteria for sampling. The results showed that 12 stocks of forming optimal portfolio, the stocks of which are UNVR, TRAM, MNCN, BHIT, JSMR, BMTR, GJTL, KLBF, AALI, CPIN, AKRA, and ASRI. Stock with highest proportion of funds is TRAM (23,52%), stock with lowest proportion of funds is AALI (0,62%). Portfolio which are formed will give return expectations by 3,05477% and carry the risk for about 0,1228%

    Quantitative Analysis of the Human AKR Family Members in Cancer Cell Lines Using the mTRAQ/MRM Approach

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    Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC–MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis

    Quantitative Analysis of the Human AKR Family Members in Cancer Cell Lines Using the mTRAQ/MRM Approach

    No full text
    Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC–MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis

    Quantitative Analysis of the Human AKR Family Members in Cancer Cell Lines Using the mTRAQ/MRM Approach

    No full text
    Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC–MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis

    Quantitative Analysis of the Human AKR Family Members in Cancer Cell Lines Using the mTRAQ/MRM Approach

    No full text
    Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC–MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis

    Quantitative Analysis of the Human AKR Family Members in Cancer Cell Lines Using the mTRAQ/MRM Approach

    No full text
    Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC–MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis

    Quantitative Analysis of the Human AKR Family Members in Cancer Cell Lines Using the mTRAQ/MRM Approach

    No full text
    Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC–MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis
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