Performance of (consensus) kNN QSAR for predicting estrogenic activity in a large diverse set of organic compounds

A novel method (in the context of quantitative structure-activity relationship (QSAR)) based on the k nearest neighbour (kNN) principle, has recently been introduced for the derivation of predictive structure-activity relationships. Its performance has been tested for estimating the estrogen binding affinity of a diverse set of 142 organic molecules. Highly predictive models have been obtained. Moreover, it has been demonstrated that consensus-type kNN QSAR models, derived from the arithmetic mean of individual QSAR models were statistically robust and provided more accurate predictions than the great majority of the individual QSAR models. Finally, the consensus QSAR method was tested with 3D QSAR and log P data from a widely used steroid benchmark data set.     

Island growth in submonolayer deposition with aggregation and fragmentation

Island growth is studied in the case of island aggregation and break-up during submonolayer deposition. It is demonstrated that the island size distributions are of the scaling form and the mean island size has a power-law behaviour corresponding to hyperthermal deposition conditions. The corresponding scaling exponents are analytically derived and compared with the simulations by the revised particle coalescence method developed here. The scaling exponents are found to depend only on the homogeneity exponents of aggregation and fragmentation kernels.Received: 4 September 2003, Published online: 30 January 2004PACS: 68.55.-a Thin film structure and morphology - 68.35.Fx Diffusion; interface formation - 36.40.Sx Diffusion and dynamics of clustersPresent addressM. Rusanen: Institut Français du Pétrole, Groupe de Modélisation Moléculaire, BP 311, 92852 Rueil-Malmaison, France;Present address J. Asikainen: HRS F27, ETH Zentrum, 8092 Zürich, Switzerland     

Intrinsic equations for a generalized relaxed elastic line on an oriented surface in the galilean space

In this article, we derive the intrinsic equations for a generalized relaxed elastic line on an oriented surface in the Galilean 3-dimensional space G₃. These equations will give direct and more geometric approach to questions concerning about generalized relaxed elastic lines on an oriented surface in G₃.     

Lentivirus-mediated transgene delivery to the hippocampus reveals sub-field specific differences in expression

Background  

In the adult hippocampus, the granule cell layer of the dentate gyrus is a heterogeneous structure formed by neurons of different ages, morphologies and electrophysiological properties. Retroviral vectors have been extensively used to transduce cells of the granule cell layer and study their inherent properties in an intact brain environment. In addition, lentivirus-based vectors have been used to deliver transgenes to replicative and non-replicative cells as well, such as post mitotic neurons of the CNS. However, only few studies have been dedicated to address the applicability of these widespread used vectors to hippocampal cells in vivo. Therefore, the aim of this study was to extensively characterize the cell types that are effectively transduced in vivo by VSVg-pseudotyped lentivirus-based vectors in the hippocampus dentate gyrus.     

Allenyl ester precursors for 1H-inden-1-ol carboxylates: comparisons with their propargylic equivalents having terminal alkyne functions

The reactivity of allenyl carboxylates, Ar(R¹)CCCH(O₂CR²) and their isomeric equivalents the terminal propargylic carboxylates, ArC(R¹)(O₂CR²)CCH, in gold-catalyzed carbocyclization to indenes provides information on 1,3 and 1,2-carboxylate shifts associated with their interconversion. Allenyl carboxylates transform specifically to 1H-inden-1-yl carboxylates in high yields, under Au^I-catalysis. Their equivalent propargylic carboxylates give complex mixtures of indene isomers and elimination products. Mechanistic tests indicate that interconversion of the terminal propargylic carbonate to its allene is at best slow in this case.