Insulin and insulin-like growth factor-I signal transduction requires p21ras

We have investigated the role of cellular p21ras protein in insulin and insulin-like growth factor-I (IGF-I) signaling pathways. Insulin stimulation increased Ras-GTP formation in Rat-1 fibroblasts overexpressing normal human insulin receptors (HIRc-B), far greater than in parental Rat-1 fibroblasts, indicating that competent insulin receptors mediate this response. Cellular microinjection of a dominant-negative mutant p21ras protein (N17 ras) or anti-p21ras monoclonal antibody (Y13-259) into HIRc-B cells reduced insulin- and IGF-I-stimulated DNA synthesis by 75-90%. Insulin-induced c-fos protein expression was also inhibited by 74%. Microinjection of oncogenic p21ras (T-24 ras) into HIRc-B cells activated the mitogenic pathway, and coinjection of N17 ras and T-24 ras showed that oncogenic p21ras rescued the cells from the N17 ras blockade. This later finding indicates that T-24 ras acts downstream of N17 ras. In conclusion, 1) microinjection of a dominant interferring ras mutant into quiescent cells abrogated subsequent insulin and IGF-I mitogenic signaling; 2) oncogenic ras protein rescued cells from the N17 ras blockade, indicating that T24 ras action is downstream of the site of N17 inhibition; and 3) p21ras is an intermediate signaling molecule in the insulin/IGF-I signal transduction pathway and is required for gene expression and DNA synthesis.     

Simultaneous estimation and factor selection in quantile regression via adaptive sup-norm regularization

Some regularization methods, including the group lasso and the adaptive group lasso, have been developed for the automatic selection of grouped variables (factors) in conditional mean regression. In many practical situations, such a problem arises naturally when a set of dummy variables is used to represent a categorical factor and/or when a set of basis functions of a continuous variable is included in the predictor set. Complementary to these earlier works, the simultaneous and automatic factor selection is examined in quantile regression. To incorporate the factor information into regularized model fitting, the adaptive sup-norm regularized quantile regression is proposed, which penalizes the empirical check loss function by the sum of factor-wise adaptive sup-norm penalties. It is shown that the proposed method possesses the oracle property. A simulation study demonstrates that the proposed method is a more appropriate tool for factor selection than the adaptive lasso regularized quantile regression.     

Multi-target visual tracking and occlusion detection by combining Bhattacharyya Coefficient and Kalman filter innovation

This paper introduces an approach for visual tracking of multi-target with occlusion occurrence. Based on the author’s previous work in which the Overlap Coefficient (OC) is used to detect the occlusion, in this paper a method of combining Bhattacharyya Coefficient (BC) and Kalman filter innovation term is proposed as the criteria for jointly detecting the occlusion occurrence. Fragmentation of target is introduced in order to closely monitor the occlusion development. In the course of occlusion, the Kalman predictor is applied to determine the location of the occluded target, and the criterion for checking the re-appearance of the occluded target is also presented. The proposed approach is put to test on a standard video sequence, suggesting the satisfactory performance in multi-target tracking.     

Synthesis of polymers for hole and electron transport materials inorganic electroluminescent devices

Styrene-type polymers having tetraphenylbenzidine (TPD) or tetraphenylphenyldiaminobenzene unit (PDA) and a oxadiazole unit (PBD) on the side chain were prepared as hole and electron transport materials, respectively, of an electroluminescent (EL) device. The device structures employed were [indium-tin-oxide (ITO)/hole transport layer (HTL)/Al] (type I), or [ITO/hole transport layer (HTL)/electron transport layer (ETL)/Al] (type II). Type I devices provided current density higher than 100 mA/cm² but no luminescence was observed. Type II devices emitted luminescence of about 10 cd/m² at the current density of about 170 mA/cm². The emission maximums of these devices were 460 and 530 nm for the device using TPD and PDA, respectively     

An optimal choice of window width for LOWESS normalization of microarray data

The purpose of normalization in microarray data analysis is to minimize systematic variations in the measured gene expression levels of two co-hybridized mRNA samples so that biological differences can be more easily distinguished. The most commonly and widely used normalization procedure for spotted arrays is probably the intensity dependent and print-tip LOWESS normalization. It is well known that the choices of different parameter values greatly affect the quality of the normalization results, and thus poor quality of the normalization results could be due to the arbitrary choice of the smoothing parameters for LOWESS normalization. In many normalization studies, however, LOWESS has been simply used without rigorous consideration of the parameters. In this article, we propose a bootstrap method to find the optimal window width in print-tip normalization by applying the cross validation technique. We also compare through simulation studies the normalization results by using the proposed method with those by fixing the window width.     

Role of Dendritic Cell in Diabetic Nephropathy

Diabetic nephropathy (DN) is one of the most significant microvascular complications in diabetic patients. DN is the leading cause of end-stage renal disease, accounting for approximately 50% of incident cases. The current treatment options, such as optimal control of hyperglycemia and elevated blood pressure, are insufficient to prevent its progression. DN has been considered as a nonimmune, metabolic, or hemodynamic glomerular disease initiated by hyperglycemia. However, recent studies suggest that DN is an inflammatory disease, and immune cells related with innate and adaptive immunity, such as macrophage and T cells, might be involved in its development and progression. Although it has been revealed that kidney dendritic cells (DCs) accumulation in the renal tissue of human and animal models of DN require activated T cells in the kidney disease, little is known about the function of DCs in DN. In this review, we describe kidney DCs and their subsets, and the role in the pathogenesis of DN. We also suggest how to improve the kidney outcomes by modulating kidney DCs optimally in the patients with DN.     

Lipid‐enveloped PLGA as a hybrid carrier for sustained delivering camptothecin in ovarian cancer

Camptothecin (CPT) is plant alkaloid exhibiting in a wide range of solid tumours. However, CPT was instability at physiological pH conditions, the lactone moieties easily hydrolysed makes systemic toxicity risky. Moreover, the water insolubility of CPT was obstructed in clinical development. The aim of the study was to utilise nontoxic and biodegradable poly(D,L‐lactic‐co‐glycolic acid) (PLGA) incorporated lipid as a hybrid nanoparticle (lipid‐PLGA NPs) for delivery of CPT. Lipid‐PLGA NPs were produced by a nano‐precipitation technique. The optimal formulation was presented that particles of which were 43 nm in diameter, with a polydispersity index of 0.3 which indicated a smaller and well‐distributed pattern. Moreover, a high capacity of ∼95% entrapment efficiency was achieved. An in vitro release study showed that non‐formulated CPT with a lag time of ∼0 h, demonstrated an obvious burst effect; in contrast, sustained released and a lag time delay were clearly observed in lipid‐PLGA NPs. The cytotoxicity study confirmed that human ovarian cancer cells (ES‐2) were inhibited by lipid‐PLGA NPs. CPT was successful entrapped in lipid‐PLGA NPs which achieved smaller size and well distribution. Lipid‐PLGA NPs resolve the water insolubility and produced a sustained, slow‐release pattern of CPT and controlled the cytotoxicity toward ES‐2.Inspec keywords: polymers, lipid bilayers, drug delivery systems, cancer, tumours, pH, solubility, nanoparticles, nanomedicineOther keywords: lipid‐enveloped PLGA, hybrid carrier, camptothecin, ovarian cancer, plant alkaloid, solid tumours, pH, lactone moieties, systemic toxicity, water insolubility, poly(D,L‐lactic‐co‐glycolic acid), hybrid nanoparticle, nano‐precipitation, entrapment efficiency, burst effect     

Correlation of the vector diffraction effect on the optical lithographic image of a binary mask with magnification of the projection system

We show quantitatively through a computer simulation the effect ofvector diffraction on the image in optical lithography. Thesimulation was made with a new program, and the variation ofdiffraction as the magnification was varied was calculated for variousnumerical apertures and degrees of defocus. The diffraction at themask improves the images of lines across the polarizing direction, andthe diffraction at the lens improves the images of the lines along thepolarizing direction. We investigated the difference between imagesof lines along and across the polarizing direction as the magnificationincreased. Our result shows that the effect of the lens is sodominant that the images of lines along the polarizing direction arealways better.     

Bootstrapping least distance estimator in the multivariate regression model

The most popular estimation methods in multivariate linear regression are the multivariate least squares estimation and the multivariate least absolute estimation. Each method repeats its univariate estimation method p, the number of response variables, times. Although they are relatively easy to apply, they do not employ the relationship between response variables. This study considers the multivariate least distance estimator of Bai et al. (1990) that accounts for this relationship. We confirm its relative efficiency with respect to the multivariate least absolute estimator under the multivariate normal distribution and contaminated distribution. However, the asymptotic inference of the multivariate least distance estimator is shown to perform poorly in certain circumstances. We suggest the bootstrap method to infer the regression parameters and confirm its viability using Monte Carlo studies.