Binding characteristics of novel nonsteroidal antiestrogens to the rat uterine estrogen receptors

Tamoxifen (TAM), the only antiestrogen currently available for the endocrine therapy of breast cancer behaves as a mixed agonist/antagonist of estrogen action, thus limiting its therapeutic potential. We report the binding characteristics of a novel series of nonsteroidal antiestrogens to the rat uterine estrogen receptor. As measured by competition studies, the affinity of EM-652, the active metabolite of the prodrug EM-800, for the estrogen receptor is 7-11 times higher than that of 17beta-estradiol (E2), ICI 182780, and hydroxy-tamoxifen (OH-TAM), the active metabolite of Tamoxifen. EM-652 is 20x more potent than ICI 164384 and Droloxifene while it is 400 times more potent than Toremifene in displacing [3H]E2 from the rat uterine estrogen receptor. On the other hand, the prodrug EM-800 and Tamoxifen have respectively 150-fold and 410-fold less affinity for the estrogen receptor than the pure antiestrogen EM-652. No significant binding of EM-652, EM-800, TAM or OH-TAM was observed to the rat uterine progesterone receptor at concentrations up to 10,000 nM except for TAM that caused a 50% displacement of labeled R5020 at 4000 nM. No significant binding of EM-652 or EM-800 was observed on the rat ventral prostate androgen receptor or the rat uterine progesterone receptor. The present data demonstrate the high affinity and specificity of the new antiestrogen, EM-652, for the rat uterine estrogen receptor. The antiestrogen EM-652 thus becomes the compound having the highest known affinity for the estrogen receptor. Due to its unique potency and its pure antiestrogenic activity already demonstrated in many systems, this antiestrogen could well offer an important advance for the endocrine therapy of breast cancer, uterine cancer, and other estrogen-sensitive diseases in women.     

Predictors of GBV-C infection among patients referred for renal transplantation

The etiology of liver disease remains unknown in about 4 to 23% of dialysis patients and 10 to 16% of renal transplant recipients. A search for other causative agents of liver disease led to the discovery of the GB group of viruses. We studied the association between the presence of GB virus C (GBV-C) infection, known risk factors for parenterally-transmitted infections and history or laboratory evidence of liver disease among end-stage renal disease (ESRD) patients referred for renal transplantation to the New England Organ Bank, MA. Stored sera from patients on the renal transplantation waiting list between November 1986 and June 1990 were tested for antibody to hepatitis C virus (HCV). Sera were available in 1544 of 3243 (48%) patients, and anti-HCV was detected by ELISA3 in 287 (19%). All 287 anti-HCV positive patients formed the anti-HCV positive cohort and 286 randomly selected anti-HCV negative patients formed the anti-HCV negative cohort (573 patients overall). Additional sera were available for GBV-C RNA testing in 465 of 573 (81%) patients, and GBV-C RNA was detected by RT-PCR in 146. The overall extrapolated prevalence of serum GBV-C RNA was 29%. The prevalence of serum GBV-C RNa among anti-HCV positive patients (35%) was not significantly different from that among anti-HCV negative patients (29%; P = 0.22). In a univariate analysis, compared to patients without GBV-C RNA, patients with serum GBV-C RNA were younger [odds ratio (OR) 0.98 per year of age, P = 0.01], had a lower proportion of males (OR 0.64, P = 0.03), lower proportion of patients with diabetes mellitus (OR 0.44, P = 0.01), higher proportion of patients with a previous transplantation (OR 1.53, P = 0.04), longer duration of dialysis at the time of enrollment (OR 1.004 per month on dialysis, P = 0.03), and a higher proportion of patients with history of transfusions (OR 4.58, P = 0.01). Serum GBV-C RNA was not associated with a significantly increased OR for history of liver disease or non-A, non-B hepatitis, or elevated serum alanine aminotransferase levels. In a step-wise multivariate regression analysis, a younger age (OR 0.98 per year of age, P = 0.03), and history of blood transfusions (OR 3.89, P = 0.03) were associated with an increased OR for serum GBV-C RNA, while diabetes mellitus was associated with a decreased OR for GBV-C RNA (OR 0.47, P = 0.01). Anti-HCV was not a predictor of serum GBV-C RNA (OR 1.07, P = 0.77). The results of this study support the fact that GBV-C is a parenterally transmitted virus and shed light on the modes of transmission of GBV-C among ESRD patients. However, the association with liver disease remains to be established.     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

Delayed self-heterodyne linewidth measurement of VCSELs

We report on high-resolution linewidth measurements of proton-implanted InGaAs-GaAs VCSELs employing the delayed self-heterodyne method. Devices with 16-/spl mu/m active diameter exhibit record low linewidths of 20 MHz and 4-MHz residual linewidth. The linewidth enhancement factor is accurately determined from the ratio of induced phase to amplitude modulation indexes.     

Adaptive control of permanent magnet synchronous machines with disturbance estimation

In this paper,an adaptive control scheme is introduced for permanent magnet synchronous machines (PMSMs)as an alternative to classical control techniques.The adaptive control strategy capitalizes on the machine’s inverse dynamics to achieve accurate tracking by using an observer to approximate disturbance in the form of friction and load torque.The controller’s output is then fed to a space vector pulse width modulation(SVPWM)algorithm to produce duty cycles for the inverter.The control scheme is validated through a set of simulations on an experimentally validated PMSM model.Results for different situations highlight its high speed tracking accuracy and high performance in compensating for friction and load disturbances of various magnitudes.     

Action recognition via bio-inspired features: The richness of center–surround interaction

Motion is a key feature for a wide class of computer vision approaches to recognize actions. In this article, we show how to define bio-inspired features for action recognition. To do so, we start from a well-established bio-inspired motion model of cortical areas V1 and MT. The primary visual cortex, designated as V1, is the first cortical area encountered in the visual stream processing and early responses of V1 cells consist in tiled sets of selective spatiotemporal filters. The second cortical area of interest in this article is area MT where MT cells pool incoming information from V1 according to the shape and characteristic of their receptive field. To go beyond the classical models and following the observations from Xiao et al. [61], we propose here to model different surround geometries for MT cells receptive fields. Then, we define the so-called bio-inspired features associated to an input video, based on the average activity of MT cells. Finally, we show how these features can be used in a standard classification method to perform action recognition. Results are given for the Weizmann and KTH databases. Interestingly, we show that the diversity of motion representation at the MT level (different surround geometries), is a major advantage for action recognition. On the Weizmann database, the inclusion of different MT surround geometries improved the recognition rate from 63.01 ± 2.07% up to 99.26 ± 1.66% in the best case. Similarly, on the KTH database, the recognition rate was significantly improved with the inclusion of MT different surround geometries (from 47.82 ± 2.71% up to 92.44 ± 0.01% in the best case). We also discussed the limitations of the current approach which are closely related to the input video duration. These promising results encourage us to further develop bio-inspired models incorporating other brain mechanisms and cortical areas in order to deal with more complex videos.     

EASEA: specification and execution of evolutionary algorithms on GPGPU

EASEA is a framework designed to help non-expert programmers to optimize their problems by evolutionary computation. It allows to generate code targeted for standard CPU architectures, GPGPU-equipped machines as well as distributed memory clusters. In this paper, EASEA is presented by its underlying algorithms and by some example problems. Achievable speedups are also shown onto different NVIDIA GPGPUs cards for different optimization algorithm families.     

Broken symmetries and thermodynamic limit in quantum antiferromagnets

We study how the Néel order breaks the symmetries of the hamiltonian in quantum antiferromagnet. The construction of a quantum wave packet that mimics the classical groundstate implies the existence of an extensive number of states: 1) with an energy scale much smaller than the spin-waves excitations (magnons); 2) with well defined symmetries.For the case of the triangular lattice, we find that all necessary properties to obtain a Néel state are well verified, already on periodic samples as small as 21 spins. For this system, this is a new and strong evidence of Néel order in the thermodynamic limit.