BCG directly induces cell cycle arrest in human transitional carcinoma cell lines as a consequence of integrin cross-linking

BACKGROUND: Current models of the mechanism by which intravesical BCG induces an anti-tumor effect in urothelial carcinoma propose a secondary cellular immune response as principally responsible. Our group has demonstrated that BCG mediated cross-linking of α5 [Image: see text] 1 integrin receptors present on the tumor surface elicits a complex biologic response involving AP1 and NF-κB signaling as well as the transactivation of immediate early genes. This study evaluated the direct biologic effect of cross-linking α5β1 integrin on cell cycle progression and apoptosis in two human urothelial carcinoma cell lines. METHODS: Two independent assays (MTT and Colony forming ability) were employed to measure the effect of α5β1 cross-linking (antibody mediated or BCG) on cellular proliferation. Flow cytometry was employed to measure effect of BCG and α5β1 antibody mediated cross-linking on cell cycle progression. Apoptosis was measured using assays for both DNA laddering and Caspase 3 activation. RESULTS: Results demonstrate that integrin cross-linking by BCG, or antibody mediated crosslinking of α5β1 resulted in a decrease in proliferating cell number. BCG treatment or α5β1 cross-linking increased the percentage of cells in G0/G1, in both 253J and T24 cell lines. Peptide mediated blockade of integrin binding site using RGDS reversed the effect BCG on both proliferation and cell cycle arrest. Apoptosis in response to BCG was not identified by either DNA laddering or Caspase 3 activation. CONCLUSION: These findings show that BCG exerts a direct cytostatic effect on human urothelial carcinoma cell lines. Cell cycle arrest at the G1/S interface is a mechanism by which BCG inhibits cellular proliferation. This effect is duplicated by antibody mediated cross-linking of α5β1 and likely occurs as a consequence of crosslink-initiated signal transduction to cell cycle regulatory genes

Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels

Atomic-Level Investigation of CHx and C2Hx Adsorption on β-SiC (111) Surface for CVD Diamond Growth from DFT Calculations

The focus of this paper is on the adsorption of unsaturated hydrocarbon molecules on β-SiC (111) surfaces during diamond film growth. The CHx and C2Hx molecules have been investigated to obtain a specific insight into absorbing diamond processes on the atomic scale. Structural and electronic properties of CHx and C2Hx adsorption on the Si- and C-terminated surfaces have been studied by first-principles calculations based on density functional theory (DFT). From the calculated energetics and geometries, we find that C2Hx adsorption on the Si-terminated surfaces has six possible surface reconstructions. For the C-terminated surface, there exist eight possible surface reconstructions. Five surface reconstructions, including CH2 adsorption on the Si- and C-terminated surface, CH–CH2 and CH=CH2 adsorption on the C-terminated surface, and C2H5 adsorption on the Si-terminated surface, have the largest hydrogen adsorption energies and more stability of surface reconstructions. Calculations demonstrate that the Si-terminated surface is energetically more favorable for fabricating CVD diamond coatings than the C-terminated surface

Hierarchical decentralized optimization architecture for economic dispatch : a new approach for large-scale power system

In this paper, a new hierarchical decentralized optimization architecture is proposed to solve the economic dispatch problem for a large-scale power system. Conventionally, such a problem is solved in a centralized way, which is usually inflexible and costly in computation. In contrast to centralized algorithms, in this paper we decompose the centralized problem into local problems. Each local generator only solves its own problem iteratively, based on its own cost function and generation constraint. An extra coordinator agent is employed to coordinate all the local generator agents. Besides, it also takes responsibility to handle the global demand supply constraint based on a newly proposed concept named virtual agent. In this way, different from existing distributed algorithms, the global demand supply constraint and local generation constraints are handled separately, which would greatly reduce the computational complexity. In addition, as only local individual estimate is exchanged between the local agent and the coordinator agent, the communication burden is reduced and the information privacy is also protected. It is theoretically shown that under proposed hierarchical decentralized optimization architecture, each local generator agent can obtain the optimal solution in a decentralized fashion. Several case studies implemented on the IEEE 30-bus and the IEEE 118-bus are discussed and tested to validate the proposed method.NRF (Natl Research Foundation, S’pore

A Novel Hybrid Model Based on an Improved Seagull Optimization Algorithm for Short-Term Wind Speed Forecasting

Wind energy is a clean energy source and is receiving widespread attention. Improving the operating efficiency and economic benefits of wind power generation systems depends on more accurate short-term wind speed predictions. In this study, a new hybrid model for short-term wind speed forecasting is proposed. The model combines variational modal decomposition (VMD), the proposed improved seagull optimization algorithm (ISOA) and the kernel extreme learning machine (KELM) network. The model adopts a hybrid modeling strategy: firstly, VMD decomposition is used to decompose the wind speed time series into several wind speed subseries. Secondly, KELM optimized by ISOA is used to predict each decomposed subseries. The ISOA technique is employed to accurately find the best parameters in each KELM network such that the predictability of a single KELM model can be enhanced. Finally, the prediction results of the wind speed sublayer are summarized to obtain the original wind speed. This hybrid model effectively characterizes the nonlinear and nonstationary characteristics of wind speed and greatly improves the forecasting performance. The experiment results demonstrate that: (1) the proposed VMD-ISOA-KELM model obtains the best performance for the application of three different prediction horizons compared with the other classic individual models, and (2) the proposed hybrid model combining the VMD technique and ISOA optimization algorithm performs better than models using other data preprocessing techniques

Pituitary Adenylate Cyclase-Activating Polypeptide Receptor Activation in the Hypothalamus Recruits Unique Signaling Pathways Involved in Energy Homeostasis

Pituitary adenylate cyclase activating polypeptide (PACAP) exerts pleiotropic effects on ventromedial nuclei (VMN) of the hypothalamus and its control of feeding and energy expenditure through the type I PAC1 receptor (PAC1R). However, the endogenous role of PAC1Rs in the VMN and the downstream signaling responsible for PACAP’s effects on energy balance are unknown. Numerous studies have revealed that PAC1Rs are coupled to both Gαs/adenylyl cyclase/protein kinase A (Gαs/AC/PKA) and Gαq/phospholipase C/protein kinase C (Gαq/PLC/PKC), while also undergoing trafficking following stimulation. To determine the endogenous role of PAC1Rs and downstream signaling that may explain PACAP’s pleiotropic effects, we used RNA interference to knockdown VMN PAC1Rs and pharmacologically inhibited PKA, PKC, and PAC1R trafficking. Knocking down PAC1Rs increased meal sizes, reduced total number of meals, and induced body weight gain. Inhibition of either PKA or PKC alone in awake male Sprague–Dawley rats, attenuated PACAP’s hypophagic and anorectic effects during the dark phase. However, PKA or PKC inhibition potentiated PACAP’s thermogenic effects during the light phase. Analysis of locomotor activity revealed that PKA inhibition augmented PACAP’s locomotor effects, whereas PKC inhibition had no effect. Finally, PACAP administration in the VMN induces surface PAC1R trafficking into the cytosol which was blocked by endocytosis inhibitors. Subsequently, inhibition of PAC1R trafficking into the cytosol attenuated PACAP-induced hypophagia. These results revealed that endogenous PAC1Rs uniquely engage PKA, PKC, and receptor trafficking to mediate PACAP’s pleiotropic effects in VMN control of feeding and metabolism