Synthesis of bicyclo-DNA nucleosides with additional functionalization in the carbocyclic ring

Two novel bicyclo nucleoside isomers carrying the base thymine in the furanose ring and an ester substituent in the carbocyclic ring were synthesized from a common bicyclic sugar precursor via a cyclopropanation/fragmentation pathway in nine steps. The relative configuration of the ester substituent in both isomers as well as the anomeric configuration in one nucleoside was determined by 1H-NMR difference NOE spectroscopy.

Evaluation of the accuracy of multilevel analysis parameter estimates for intra-cluster correlation in correlated binary data

Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^

Sparse computation for large-scale binary classification

Well-known data mining algorithms rely on inputs in the form of pairwise similarities between objects. For large datasets it is computationally impossible to perform all pairwise comparisons. We therefore propose a novel approach that uses approximate Principal Component Analysis to efficiently identify groups of similar objects. The effectiveness of the approach is demonstrated in the context of binary classification using the supervised normalized cut as a classifier. For large datasets from the UCI repository, the approach significantly improves run times with minimal loss in accuracy.

Functionalization of β-caryophyllene generates novel polypharmacology in the endocannabinoid system

The widespread dietary plant sesquiterpene hydrocarbon β-caryophyllene (1) is a CB2 cannabinoid receptor-specific agonist showing anti-inflammatory and analgesic effects in vivo. Structural insights into the pharmacophore of this hydrocarbon, which lacks functional groups other than double bonds, are missing. A structure-activity study provided evidence for the existence of a well-defined sesquiterpene hydrocarbon binding site in CB2 receptors, highlighting its exquisite sensitivity to modifications of the strained endocyclic double bond of 1. While most changes on this element were detrimental for activity, ring-opening cross metathesis of 1 with ethyl acrylate followed by amide functionalization generated a series of new monocyclic amides (11a, 11b, 11c) that not only retained the CB2 receptor functional agonism of 1 but also reversibly inhibited fatty acid amide hydrolase (FAAH), the major endocannabinoid degrading enzyme, without affecting monoacylglycerol lipase (MAGL) and α,β hydrolases 6 and 12. Intriguingly, further modification of this monocyclic scaffold generated the FAAH- and endocannabinoid substrate-specific cyclooxygenase-2 (COX-2) dual inhibitors 11e and 11f, which are probes with a novel pharmacological profile. Our study shows that by removing the conformational constraints induced by the medium-sized ring and by introducing functional groups in the sesquiterpene hydrocarbon 1, a new scaffold with pronounced polypharmacological features within the endocannabinoid system could be generated. The structural and functional repertoire of cannabimimetics and their yet poorly understood intrinsic promiscuity may be exploited to generate novel probes and ultimately more effective drugs.

Functionalization of PAMAM dendrimers with nitronyl nitroxide radicals as models for the outer-sphere relaxation in dentritic potential MRI contrast agents

PAMAM dendrimers functionalized with nitronyl nitroxide radicals were characterized. Quantitative determination of substitution with radicals was performed using EPR and electrochemical methods. The study of the 1H NMR relaxation of the surrounding water showed how the outer-sphere contribution to the relaxivity may be limited by the presence of the dendrimer core.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

Binary recombinase systems for high-resolution conditional mutagenesis.

Conditional mutagenesis using Cre recombinase expressed from tissue specific promoters facilitates analyses of gene function and cell lineage tracing. Here, we describe two novel dual-promoter-driven conditional mutagenesis systems designed for greater accuracy and optimal efficiency of recombination. Co-Driver employs a recombinase cascade of Dre and Dre-respondent Cre, which processes loxP-flanked alleles only when both recombinases are expressed in a predetermined temporal sequence. This unique property makes Co-Driver ideal for sequential lineage tracing studies aimed at unraveling the relationships between cellular precursors and mature cell types. Co-InCre was designed for highly efficient intersectional conditional transgenesis. It relies on highly active trans-splicing inteins and promoters with simultaneous transcriptional activity to reconstitute Cre recombinase from two inactive precursor fragments. By generating native Cre, Co-InCre attains recombination rates that exceed all other binary SSR systems evaluated in this study. Both Co-Driver and Co-InCre significantly extend the utility of existing Cre-responsive alleles.

Outcome-based adaptive randomization for binary data in clinical trials---Compare and contrast

Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^