Systematic review of cholinergic drugs for neuroleptic-induced tardive dyskinesia: a meta-analysis of randomized controlled trials

The authors evaluated the efficacy of cholinergic drugs in the treatment of neuroleptic-induced tardive dyskinesia (TD) by a systematic review of the literature on the following agents: choline, lecithin, physostigmine, tacrine, 7-methoxyacridine, ipidacrine, galantamine, donepezil, rivastigmine, eptastigmine, metrifonate, arecoline, RS 86, xanomeline, cevimeline, deanol, and meclofenoxate. All relevant randomized controlled trials, without any language or year limitations, were obtained from the Cochrane Schizophrenia Group's Register of Trials. Trials were classified according to their methodological quality. For binary and continuous data, relative risks (RR) and weighted or standardized mean differences (SMD) were calculated, respectively. Eleven trials with a total of 261 randomized patients were included in the meta-analysis. Cholinergic drugs showed a minor trend for improvement of tardive dyskinesia symptoms, but results were not statistically significant (RR 0.84, 95% confidence interval (CI) 0.68 to 1.04, p=0.11). Despite an extensive search of the literature, eligible data for the meta-analysis were few and no results reached statistical significance. In conclusion, we found no evidence to support administration of the old cholinergic agents lecithin, deanol, and meclofenoxate to patients with tardive dyskinesia. In addition, two trials were found on novel cholinergic Alzheimer drugs in tardive dyskinesia, one of which was ongoing. Further investigation of the clinical effects of novel cholinergic agents in tardive dyskinesia is warranted. (C) 2004 Elsevier Inc. All rights reserved.

Improvement of the Derjaguin-Broekhoff-de Boer theory for capillary condensation/evaporation of nitrogen in mesoporous systems and its implications for pore size analysis of MCM-41 silicas and related materials

In this work, we propose an improvement of the classical Derjaguin-Broekhoff-de Boer (DBdB) theory for capillary condensation/evaporation in mesoporous systems. The primary idea of this improvement is to employ the Gibbs-Tolman-Koenig-Buff equation to predict the surface tension changes in mesopores. In addition, the statistical film thickness (so-called t-curve) evaluated accurately on the basis of the adsorption isotherms measured for the MCM-41 materials is used instead of the originally proposed t-curve (to take into account the excess of the chemical potential due to the surface forces). It is shown that the aforementioned modifications of the original DBdB theory have significant implications for the pore size analysis of mesoporous solids. To verify our improvement of the DBdB pore size analysis method (IDBdB), a series of the calcined MCM-41 samples, which are well-defined materials with hexagonally ordered cylindrical mesopores, were used for the evaluation of the pore size distributions. The correlation of the IDBdB method with the empirically calibrated Kruk-Jaroniec-Sayari (KJS) relationship is very good in the range of small mesopores. So, a major advantage of the IDBdB method is its applicability for small mesopores as well as for the mesopore range beyond that established by the KJS calibration, i.e., for mesopore radii greater than similar to4.5 nm. The comparison of the IDBdB results with experimental data reported by Kruk and Jaroniec for capillary condensation/evaporation as well as with the results from nonlocal density functional theory developed by Neimark et al. clearly justifies our approach. Note that the proposed improvement of the classical DBdB method preserves its original simplicity and simultaneously ensures a significant improvement of the pore size analysis, which is confirmed by the independent estimation of the mean pore size by the powder X-ray diffraction method.

Playing in continuous spaces: Some analysis and extension of population-based incremental learning

As an alternative to traditional evolutionary algorithms (EAs), population-based incremental learning (PBIL) maintains a probabilistic model of the best individual(s). Originally, PBIL was applied in binary search spaces. Recently, some work has been done to extend it to continuous spaces. In this paper, we review two such extensions of PBIL. An improved version of the PBIL based on Gaussian model is proposed that combines two main features: a new updating rule that takes into account all the individuals and their fitness values and a self-adaptive learning rate parameter. Furthermore, a new continuous PBIL employing a histogram probabilistic model is proposed. Some experiments results are presented that highlight the features of the new algorithms.