Phenomenological observations document this “solution” by the visual system.”
“The TNF-related apoptosis-inducing ligand (TRAIL or Apo2L) preferentially cause apoptosis of malignant

cells in vitro and in vivo without severe toxicity. Therefore, TRAIL or agonist antibodies to the TRAIL DR4 and DR5 receptors are used in cancer therapy. However, many malignant cells are intrinsically-resistant or acquire resistance to TRAIL. It has been previously PI3K inhibitor proposed that the multidrug transporter P-glycoprotein (Pgp) might play a role in resistance of cells to intrinsic apoptotic pathways by interfering with components of ceramide metabolism or by modulating the electrochemical gradient across the plasma membrane. In this study we investigated whether Pgp also confers resistance toward extrinsic death ligands of the TNF family. To this end we focused our study on HeLa cells carrying a tetracycline-repressible plasmid system which shuts down Pgp expression in the presence of tetracycline. Our findings demonstrate that expression of Pgp is a significant factor conferring resistance to TRAIL administration, but not to other death ligands such as TNF-alpha. and Fas ligand. Moreover, blocking Pgp transport activity sensitizes the malignant cells toward TRAIL. Therefore, Pgp transport function is

required to confer resistance to TRAIL. Although the resistance to TRAIL-induced apoptosis is Pgp specific, TRAIL itself is not a direct substrate of Pgp. Pgp expression has no effect on the level of the TRAIL receptors DR4 and DR5. These findings might have clinical implications since the combination of TRAIL therapy with administration of Pgp modulators might Dibutyryl-cAMP mw sensitize TRAIL resistant tumors. (C) 2013 Elsevier Inc. All rights reserved.”
“Fetal ECG (FECG) telemonitoring

is an important branch in telemedicine. The design of a telemonitoring system via a wireless body area network with low energy consumption for ambulatory use is highly desirable. As an emerging technique, compressed sensing (CS) shows great promise in compressing/reconstructing data with low energy consumption. However, due to some specific characteristics of raw FECG recordings such as nonsparsity GSK1120212 cell line and strong noise contamination, current CS algorithms generally fail in this application. This paper proposes to use the block sparse Bayesian learning framework to compress/reconstruct nonsparse raw FECG recordings. Experimental results show that the framework can reconstruct the raw recordings with high quality. Especially, the reconstruction does not destroy the interdependence relation among the multichannel recordings. This ensures that the independent component analysis decomposition of the reconstructed recordings has high fidelity. Furthermore, the framework allows the use of a sparse binary sensing matrix with much fewer nonzero entries to compress recordings. Particularly, each column of the matrix can contain only two nonzero entries.