Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis

Without non-linear basis functions many problems can not be solved by linear algorithms. This article proposes a method to automatically construct such basis functions with slow feature analysis (SFA). Non-linear optimization of this unsupervised learning method generates an orthogonal basis on the unknown latent space for a given time series. In contrast to methods like PCA, SFA is thus well suited for techniques that make direct use of the latent space. Real-world time series can be complex, and current SFA algorithms are either not powerful enough or tend to over-fit. We make use of the kernel trick in combination with sparsification to develop a kernelized SFA algorithm which provides a powerful function class for large data sets. Sparsity is achieved by a novel matching pursuit approach that can be applied to other tasks as well. For small data sets, however, the kernel SFA approach leads to over-fitting and numerical instabilities. To enforce a stable solution, we introduce regularization to the SFA objective. We hypothesize that our algorithm generates a feature space that resembles a Fourier basis in the unknown space of latent variables underlying a given real-world time series. We evaluate this hypothesis at the example of a vowel classification task in comparison to sparse kernel PCA. Our results show excellent classification accuracy and demonstrate the superiority of kernel SFA over kernel PCA in encoding latent variables

Controlled-Release from High-Loaded Reservoir-Type Systems—A Case Study of Ethylene-Vinyl Acetate and Progesterone

Reservoir systems (drug-loaded core surrounded by drug-free membrane) provide long-term controlled drug release. This is especially beneficial for drug delivery to specific body regions including the vagina. In this study, we investigated the potential of reservoir systems to provide high drug release rates over several weeks. The considered model system was an intra-vaginal ring (IVR) delivering progesterone (P4) in the mg/day range using ethylene-vinyl acetate (EVA) as release rate-controlling polymers. To circumvent the high material needs associated with IVR manufacturing, we implemented a small-scale screening procedure that predicts the drug release from IVRs. Formulations were designed based on the solubility and diffusivity of P4 in EVAs with varying vinyl acetate content. High in-vitro P4 release was achieved by (i) high P4 solubility in the core polymer; (ii) high P4 partition coefficient between the membrane and the core; and/or (iii) low membrane thicknesses. It was challenging for systems designed to release comparatively high fractions of P4 at early times to retain a constant drug release over a long time. P4 crystal dissolution in the core could not counterbalance drug diffusion through the membrane and drug crystal dissolution was found to be the rate-limiting step. Overall, high P4 release rates can be achieved from EVA-based reservoir system

Effect of EC313 on gene expression of proliferation, apoptotic markers and PR regulated genes.

<p>A-B), Gene expression in mammary glands of overiectomized C57BL/6 mice treated with E2, EC313 0.1 and 1.0 mg/kg. Columns are average of relative amount (ΔΔCt) of tested mRNA ± SD (n = 6) (**P<0.01 vs E2-control, *P<0.001 vs E2-control).</p

Glucocorticoid receptor (GR) antagonistic activity, Progesterone receptor (PR)—agonistic and antagonistic activity is evaluated and IC50 values as well as agonistic/antagonistic ratios were noted.

<p>ND- Not determined.</p

Antiestrogenic effect of EC312/313 on cell viability and proliferation in vitro.

<p>A-B) Antiestrogenic effect of EC312 and EC313 on cell growth in the presence and absence of endogenous estrogens. T47D cells were plated at 30,000 cells per well in 5% FBS-RPMI and grown for 2 days before treatment. The cells were then incubated with EC312 and EC313 at indicated concentrations for 5 days and counted for cell number. *P<0.01 vs control. <b>C)</b> The compounds were treated as per the conditions above with and without E2 (0.1nM). Tested compounds were found to inhibit E2 induced cell proliferation as comparable to that of BZD (10nM). EC317 was used as a pure PR antagonist (*P<0.01 vs control).</p