Rose-like ZnO nanostructures were synthesized by the precipitation method using a biosurfactant (surfactin) as a templating-agent stabilizer. The concentration of surfactin in the precursor solution significantly influenced the thickness and density of the petals in the rose-like structures, and all samples were of a wurtzite phase. The thickness of the petal was found to decrease with increasing surfactin concentration. The average thickness of the petals was found to be between 10 and 13 nm. Photocatalytic degradation of methylene blue using rose-like ZnO nanostuctures was investigated, and the morphology, density and thickness of the ZnO petals were found to influence the photodegradation activity. The samples with loosely-spread petals, or plate-like ZnO structures, brought about the strongest photodegradation in comparison with the dense rose-like structures. The greater activity of the loose-petal structures was correlated with their higher absorption in the UV region in comparison with the other samples. The ZnO samples prepared using low surfactin concentrations had higher rate constant values, i.e., 9.1 x 10(-3) min(-1), which revealed that the photodegradation of methylene blue under UV irradiation progressed by a pseudo first-order kinetic reaction.
Entropy is a great development in science. We proposed that entropy decrease due to internal interactions in the isolated system is possible. We define the entangled scale, which mainly involves the number n and entangled degree. Since coherence, entanglement and correlation are all internal interactions in information systems, we discuss quantitatively entropy decrease along coherence, and entropy increase only for incoherence. From beginning quantum heat engine, we must systematically study quantum thermodynamics. Based on some astrophysical simulation models, they shown that the universe evolves from disorder to structures, which correspond to entropy decrease. This is consistence with theoretical result. The simulation must be an isolated system only using internal gravitational interactions.
Intrinsic and acquired resistance to antineoplastic agents continues to be a major clinical impediment to successful treatment of cancer in general, and breast cancer in particular. For example, about 40% of ER-positive metastatic breast tumors fail to respond to tamoxifen therapy, and of those that initially respond many will eventually develop resistance. Similarly, taxanes used as a first-line chemotherapy agent will have a response rate of 50%, which comes down to 20–30% in second- or third-line chemotherapy; nearly half of the treated subjects do not respond to it and suffer side effects. These facts underscore the importance of understanding the mechanism of resistance, which is crucial for the optimal systemic therapy of breast cancer. Unfortunately, in spite of extensive inquiry in this field, little is known about the key molecules/signaling pathways that regulate this phenomenon. Recently, we have discovered that small non-coding RNAs, i.e. microRNA (miRNAs), may play a critical role in mediating drug resistance in breast cancers. We have identified miRNAs that are differentially expressed between drug-resistant and sensitive breast cancer cells. Specifically, we have combined a high-throughput screening platform with a library of chemically synthesized inhibitors for all known human miRNAs and identified specific miRNA that selectively sensitize/de-sensitize drug-resistant breast cancer cells to either tamoxifen or trastuzumab (herceptin), drugs that are commonly used as a first line treatment for ER-positive and Her2-positive breast cancers, respectively. We identified 10 and 12 miRNA inhibitors that sensitized resistant cells to tamoxifen and trastuzumab, respectively. Interestingly, expression of cognate miRNA/s that sensitize resistant tumors to drug-induced cell death in our screen was found to be lower in relapsed (drug-resistant) metastatic breast cancer patients compared to normal matched control. In addition to tumor tissues, the levels of sensitizer miRNA/s in the blood sera of relapsed metastatic breast cancer patients was found to be dramatically lower than that of normal healthy individual. These findings are significant as it suggests that miRNAs can be efficiently detected in blood serum and therefore, can be used as a potential biomarker for predicting treatment outcomes. In addition, miRNAs may provide novel therapeutic tools for the treatment of drug-resistant breast cancers. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-07-10.
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