27 research outputs found
Caffeic Acid Phenethyl Ester Causes p21Cip1 Induction, Akt Signaling Reduction, and Growth Inhibition in PC-3 Human Prostate Cancer Cells
Caffeic acid phenethyl ester (CAPE) treatment suppressed proliferation, colony formation, and cell cycle progression in PC-3 human prostate cancer cells. CAPE decreased protein expression of cyclin D1, cyclin E, SKP2, c-Myc, Akt1, Akt2, Akt3, total Akt, mTOR, Bcl-2, Rb, as well as phosphorylation of Rb, ERK1/2, Akt, mTOR, GSK3α, GSK3β, PDK1; but increased protein expression of KLF6 and p21Cip1. Microarray analysis indicated that pathways involved in cellular movement, cell death, proliferation, and cell cycle were affected by CAPE. Co-treatment of CAPE with chemotherapeutic drugs vinblastine, paclitaxol, and estramustine indicated synergistic suppression effect. CAPE administration may serve as a potential adjuvant therapy for prostate cancer
Gene expression profiling of response to mTOR inhibitor everolimus in pre-operatively treated post-menopausal women with oestrogen receptor-positive breast cancer
Lattice Order Group Decision Making with Interval Probability Based on Prospect Theory
Androgen Suppresses the Proliferation of Androgen Receptor-Positive Castration-Resistant Prostate Cancer Cells via Inhibition of Cdk2, CyclinA, and Skp2
Cholestane-3β, 5α, 6β-triol Suppresses Proliferation, Migration, and Invasion of Human Prostate Cancer Cells
Expert System Development Using Fuzzy If–Then Rules for Ergonomic Compatibility of AMT for Lean Environments
Difference in Protein Expression Profile and Chemotherapy Drugs Response of Different Progression Stages of LNCaP Sublines and Other Human Prostate Cancer Cells
Material Criticality Assessment for Business Purposes Using Fuzzy Linguistic Method
A secure supply of raw materials plays a vital role in the rapid growth of emerging technologies. The criticality assessment has been introduced to evaluate the supply risk of materials from economic, social and environmental aspects. From business perspective, multiple critical metrics should be involved, so that the decision makers can focus on the different metrics and put efforts to minimize the corresponding risks. However, due to the complexity of assessment and uncertainties in data sources, some metrics cannot be evaluated quantitatively, but qualitatively. This paper introduces a fuzzy linguistic approach to evaluate multiple risk metrics for material criticality assessment. The risk levels and the importance weight of metrics, expressed in linguistic terms, are modeled by triangular or trapezoid membership functions. We apply this method to evaluate the criticality of three materials: Cobalt, Tungsten, and Yttrium. We use matrix operation to aggregate the MFs of the multiple metrics in order to represent the overall criticality. As a result, the three materials are ranked according to their critical levels. The proposed fuzzy linguistic approach shows the advantage to evaluate the criticality with multi-criteria when only qualitative data is available. The membership function is an appropriate way to represent linguistic terms with imprecision, which are commonly used to interpret risk terms. The definition of multiple metrics provides flexibility for the users to choose risk categories they are interested in, and the aggregation of the metrics supports them to compare the criticality of materials. Further study may focus on how to justify importance weight judgments to make tradeoff decision, or integrate temporal factor to predict the future critical risk for business purpose