Rationale: Cisplatin (CDDP) is a broad-spectrum anticancer drug but chemoresistance to CDDP impedes its wide use for cancer therapy. Autophagy is an event occurring in the cytoplasm and cytoplasmic LC3 puncta formation is a hallmark of autophagy. Graphene oxide (GO) is a nanomaterial that provokes autophagy in CT26 colon cancer cells and confers antitumor effects. Here we aimed to evaluate whether combined use of GO with CDDP (GO/CDDP) overcomes chemoresistance in different cancer cells and uncover the underlying mechanism.Methods: We treated different cancer cells with GO/CDDP and evaluated the cytotoxicity, death mechanism, autophagy induction and nuclear entry of CDDP. We further knocked down genes essential for autophagic flux and deciphered which step is critical to nuclear import and cell death. Finally, we performed immunoprecipitation, mass spectrometry and immunofluorescence labeling to evaluate the association of LC3 and CDDP.Results: We uncovered that combination of GO and CDDP (GO/CDDP) promoted the killing of not only CT26 cells, but also ovarian, cervical and prostate cancer cells. In the highly chemosensitized Skov-3 cells, GO/CDDP significantly enhanced concurrent nuclear import of CDDP and autophagy marker LC3 and elevated cell necrosis, which required autophagy initiation and progression but did not necessitate late autophagy events (e.g., autophagosome completion and autolysosome formation). The GO/CDDP-elicited nuclear trafficking and cell death also required importin α/β, and LC3 also co-migrated with CDDP and histone H1/H4 into the nucleus. In particular, GO/CDDP triggered histone H4 acetylation in the nucleus, which could decondense the chromosome and enable CDDP to more effectively access chromosomal DNA to trigger cell death.Conclusion: These findings shed light on the mechanisms of GO/CDDP-induced chemosensitization and implicate the potential applications of GO/CDDP to treat multiple cancers.
This paper proposes the development of a two-axis sun tracking solar energy system using fuzzy logic as intelligent quality policy. To achieve maximum efficiency for solar panels, it is necessary to follow the sun's path in the sky. Therefore, the architecture for the two-axis sun tracking solar energy system uses software to control the hardware. The hardware comprises (i) solar cells; (ii) lead-acid batteries; (iii) a gear box; (iv) a stepping motor; and (v) a light detection circuit, while the software comprises (i) a detection system; (ii) a fuzzy tracking controller; and (iii) a database system. A fuzzy logic controller is designed as the software architecture of the system to decide the timing for tracking the sun. The nearest position that results in receiving direct sunlight is obtained from the database. Our system is fully automatic in a changing environment and takes into account meteorological changes and the effects of the external environment arising from a malfunction. This approach reduces the number of starting motors and results in smaller energy loss in cloudy, cloud mask, or unstable weather conditions.
Other comprehensive income items (OCI) increase and decrease book value and therefore indicate more or less firm value. It follows that OCI items, albeit transitory, may contribute to a wealth effect that influences expenditure decisions. In support, our regression results indicate an association between current year OCI and future discretionary financing, investing, and operating expenditures. However, we also find that OCI-influenced expenditures are not associated with future profitability, suggesting such expenditures are not value creating. In further tests, we find that future discretionary expenditures are associated with both positive OCI and negative OCI for higher leveraged firms but only associated with positive OCI for lower leveraged firms. These results suggest that, for highly leveraged firms, positive OCI loosens debt constraints on future expenditures while negative OCI tightens debt constraints on future expenditures. For firms without debt constraints the results are suggestive of possible wealth transfers from debtholders to shareholders. K E Y W O R D S debt constraints, discretionary investing, financing and operating expenditures, other comprehensive income, wealth effect, wealth transfers
INTRODUCTIONThe information value of other comprehensive income relative to earnings is not well understood. Other comprehensive income (OCI) and earnings appear to have similar components. OCI and earnings both contain gains that increase owners' equity and indicate more firm value. Similarly, OCI and earnings both contain losses that decrease owners' equity and indicate less firm value. The wealth effect of gains and losses on firm value suggests, all things being equal, that managers with firm value increases will tend to spend more and managers with firm value decreases will tend to spend less. However, OCI items and earnings items differ fundamentally. Unrealized gains and losses are likely to be presented, at least temporarily, in owners' equity as OCI items while realized gains and losses appear on the income statement as components of earnings. In part because OCI gains and losses are unrealized, they are largely considered transitory thereby potentially limiting their usefulness for predicting future cash flows (Jones & Smith, 2011), income 72
This paper proposes a novel feedrate interpolation strategy depending on the error feedback information. The proposed strategy incorporates the real-time non-uniform rational B-spline (NURBS) algorithm and is applied in a biaxial contouring stage system. The objective of the strategy is to improve the contouring accuracy to cope with the highprecision standard nowadays. The proposed method does achieve the control purpose that if the detected contouring performance is beyond a given specified value, then the feedrate controller will vary the actual feedrate to provide better contouring accuracy. By real-time adjusting the feedrate depending on the error feedback, contouring error will not accumulate such that the precision can be improved. Many experiments are conducted and the results do show the effectiveness of the proposed method.
In the paper, a cloud-dust based intelligent maximum power analysis system for photovoltaic is proposed. In order to resolve NP problem for photovoltaic, factors of photovoltaic are integrated to cloud-dust based intelligent maximum power analysis system for computing. This study is the development of the maximum power analysis system for photovoltaic, to improve the solar panels effects of the different region and enable them to get maximum efficiency of the power generation. The design methodology of this study includes: (1) The monitoring and control Module (2) The prediction and evaluation module (3) The performance diagnosis module (4) The maintenance prescription module. At last, we can find the advantages of the cloud-dust based intelligent maximum power analysis system for photovoltaic. It increases overall competitive performance of products, reduces cost of products and consummation rates of human resources.
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