Nanosecond dynamics of a mimicked membrane-water interface observed by time-resolved stokes shift of LAURDAN

We studied the dipolar relaxation of the surfactant-water interface in reverse micelles of AOT-water in isooctane in the nanosecond and subnanosecond time ranges by incorporating the amphipathic solvatochromic fluorescent probes LAURDAN and TOE. A negative component was observed in the fluorescence decays in the red edge of the emission spectrum-the signature of an excited state reaction-with LAURDAN but not for TOE. The deconvolution of the transient reconstructed spectra of LAURDAN based on a model constructed by adding together three log-normal Gaussian equations made it possible to separate the specific dynamic solvent response from the intramolecular excited state reactions of the probe. The deconvoluted spectrum of lowest energy displayed the largest Stokes shift. This spectral shift was described by unimodal kinetics on the nanosecond timescale, whereas the relaxation kinetics of water-soluble probes have been reported to be biphasic (on the subnanosecond and nanosecond timescales) due to the heterogeneous distribution of these probes in the water pool. Most of this spectral shift probably resulted from water relaxation as it was highly sensitive to the water to surfactant molar ratio (w(0)) (60-65 nm at w(0) = 20-30). A small part of this spectral shift (9 nm at w(0) = 0) probably resulted from dipolar interaction with the AOT polar headgroup. The measured relaxation time values were in the range of the rotational motion of the AOT polar headgroup region as assessed by LAURDAN and TOE fluorescence anisotropy decays.     

Retrospective analysis of sequential dose-finding designs

The continual reassessment method (CRM) is a dose-finding design using a dynamic sequential updating scheme. In common with other dynamic schemes the method estimates a current dose level corresponding to some target percentile for experimentation. The estimate is based on all included subjects. This continual reevaluation is made possible by the use of a simple model. As it stands, neither the CRM, nor any of the other dynamic schemes, allow for the correct estimation of some target percentile, based on retrospective data apart from the exceptional situation in which the simplified model exactly generates the observations. In this article we focus on the very specific issue of retrospective analysis of data generated by some arbitrary mechanism and subsequently analyzed via the continual reassessment method. We show how this can be done consistently. The proposed methodology is not restricted to that particular design and is applicable to any sequential updating scheme in which dose levels are associated with percentiles via model inversion.     

A New Multivariate Approach to Studying Temporal Changes of Vegetation

We emphasize the necessity of a complex approach to evaluating vegetation change at various levels of abstraction. The analytical steps include comparisons at the data, derived variable, distance, ordination and classification levels. A variety of data randomization methods incorporated in testing the significance of changes in raw data are introduced and compared. It is shown that these are true alternatives to Procrustean comparisons, which offer an apparently unfortunate choice in the presence/absence case. We propose to evaluate nearest neighbor relationships among quadrats in a new method, called adjacency analysis, to detect temporal trends that may remain unrevealed, should our attention be paid to full distance structures only. As an illustration, compositional and structural changes in the rock grassland vegetation of the Sas-hegy Nature Reserve (Budapest, Hungary), intensively sampled by quadrats in 1977 and 2000, are evaluated. Permutation tests show that differences between the 2 years are much smaller than expected by chance alone. Such an overall stability in community structure, however, does not mean that minor aspects of vegetation pattern are invariant over the years. Changes in life form and seed mass spectra are explained by the fluctuation of hemicryptophytes and the slight but detectable expansion of annuals and woody species. Classification is slightly rearranged in time, with clearly detectable within-cluster changes, also depicted in ordination scattergrams.     

A set of epitope-tagging integration vectors for functional analysis in Saccharomyces cerevisiae

Functional analysis of genes from Saccharomyces cerevisiae has been the major goal after determination of genome sequences. Even though several tools for molecular-genetic analyses have been developed, only a limited number of reliable genetic tools are available to support functional assay at protein level. Epitope tagging is a powerful tool for detecting, purifying, and functional studying of proteins. But systematic tagging systems developed with integration vectors are not available. Here, we have constructed a set of integration vectors allowing a translational fusion of interested proteins to the four different epitope tags (HA, Myc, Flag, and GFP). To confirm function and expression of C-terminal-tagged proteins, we used Cdc11, a component of the septin filament that encircles the mother bud neck and consists of five major proteins: Cdc3, Cdc10, Cdc11, Cdc12, and Sep7. The tagged version of Cdc11 expressed under its endogenous promoter was found to be physiologically functional, as evidenced by localization at the neck and suppression of the growth defect associated with the temperature-sensitive mutation of cdc11-6. The expressed proteins were efficiently detected with antibodies against Cdc11 or the epitopes. When immunoprecipitated with anti-Myc antibody, each septin protein tagged with Myc was effectively copurified with other septin components, indicating formation of a stable septin complex. Because the modules of the tags were located under the same array of eighteen restriction sites on integration vectors containing four different markers (HIS3, TRP1, LEU2, or URA3), this tagging system provides efficient multiple tagging and stable expression of a gene of interest.     

Simple and rapid determination of metabolite content in plant cell culture medium using an FT-IR/ATR method

A simple, rapid and accurate mid-infrared (MIR) spectroscopic method for simultaneously determining the product (ethanol) content and the nutrient (sugar) content in plant-cell culture media was developed using a Fourier transform infrared (FT-IR) spectrometer equipped with an attenuated total reflectance (ATR) accessory. We assessed the potential of this method by comparing it to a high-performance liquid chromatography (HPLC) method, and using the developed method to measure the ethanol and sugar contents simultaneously in liquid culture media with rice and tabacum cell suspensions, respectively. The experimental results suggest that the sugar consumption and ethanol production behaviors of the plant cell suspensions can be non-destructively and simultaneously monitored using the developed method. Furthermore, the spectroscopic method provided in this study could be developed into a technique that could be used to analyze the overall kinetics of the metabolism of the plant cell suspensions.     

Determination of oxidized and reduced nicotinamide adenine dinucleotide in cell monolayers using a single extraction procedure and a spectrophotometric assay

While many investigations measuring oxidized nicotinamide adenine dinucleotide (NAD+) and reduced nicotinamide adenine dinucleotide (NADH) have been carried out on several mammalian tissues and blood cells, few reports have dealt with monolayers of cultured cells. Here we show a novel method to measure NAD+ and NADH in monolayers of a neuroblastoma cell line. The method was established by modifying a single extraction procedure originally developed for erythrocytes and an enzymatic cycling assay using a dye that absorbs in visible range. The following modifications were made. (i) Addition of 0.05% of a detergent, Triton X-100, to carbonate-bicarbonate extraction buffer enabled us to accurately measure cellular [NADH]/([NAD+]+[NADH]). (ii) Addition of N-ethyldibenzopyrazine ethyl sulfate salt (phenazine ethosulfate) immediately before the incubation suppressed the gradual decline of the sensitivity of the assay. The procedure presented here provides a simple and inexpensive measurement of NAD+ and NADH in cell monolayers.     

Extraction of leukemia specific glycan motifs in humans by computational glycomics

There have been almost no standard methods for conducting computational analyses on glycan structures in comparison to DNA and proteins. In this paper, we present a novel method for extracting functional motifs from glycan structures using the KEGG/GLYCAN database. First, we developed a new similarity measure for comparing glycan structures taking into account the characteristic mechanisms of glycan biosynthesis, and we tested its ability to classify glycans of different blood components in the framework of support vector machines (SVMs). The results show that our method can successfully classify glycans from four types of human blood components: leukemic cells, erythrocyte, serum, and plasma. Next, we extracted characteristic functional motifs of glycans considered to be specific to each blood component. We predicted the substructure alpha-D-Neup5Ac-(2-->3)-beta-D-Galp-(1-->4)-D-GlcpNAc as a leukemia specific glycan motif. Based on the fact that the Agrocybe cylindracea galectin (ACG) specifically binds to the same substructure, we conducted an experiment using cell agglutination assay and confirmed that this fungal lectin specifically recognized human leukemic cells.     

Prediction of methylated CpGs in DNA sequences using a support vector machine

DNA methylation plays a key role in the regulation of gene expression. The most common type of DNA modification consists of the methylation of cytosine in the CpG dinucleotide. At the present time, there is no method available for the prediction of DNA methylation sites. Therefore, in this study we have developed a support vector machine (SVM)-based method for the prediction of cytosine methylation in CpG dinucleotides. Initially a SVM module was developed from human data for the prediction of human-specific methylation sites. This module achieved a MCC and AUC of 0.501 and 0.814, respectively, when evaluated using a 5-fold cross-validation. The performance of this SVM-based module was better than the classifiers built using alternative machine learning and statistical algorithms including artificial neural networks, Bayesian statistics, and decision trees. Additional SVM modules were also developed based on mammalian- and vertebrate-specific methylation patterns. The SVM module based on human methylation patterns was used for genome-wide analysis of methylation sites. This analysis demonstrated that the percentage of methylated CpGs is higher in UTRs as compared to exonic and intronic regions of human genes. This method is available on line for public use under the name of Methylator at http://bio.dfci.harvard.edu/Methylator/.