Assessment of fluoroalkyltin compounds as fluorous Lewis acid catalysts

The synthesis of a variety of organotin compounds with 1H, 1H, 2H, 2H‐perfluorooctyl groups is reported, together with an improved method for the corresponding distannoxane. Unique properties of this compound are disclosed in terms of fluorophilicity and activity as a Lewis acid catalyst in comparison with other mono‐nuclear derivatives. A new criterion for obtaining high solubility in fluorocarbon solvents is presented. Copyright © 2003 John Wiley & Sons, Ltd.     

Developmental changes of poly(ADP-ribose) polymerase expression in Sarcophaga peregrina

To elucidate the physiological role of poly(ADP-ribose) polymerase (PARP), we studied the levels of PARP mRNA and protein during the developmental stages of Sarcophaga peregrina. PARP mRNA expression changed remarkably throughout the developmental stages. The level of PARP mRNA (the molecular ratio of PARP mRNA to the total RNA) was highest in unfertilized eggs and that of PARP protein (the molecular ratio of PARP protein to the total protein of the crude extract) was high in unfertilized and fertilized eggs and in 1st instar larvae. During the embryogenesis period, the levels of PARP mRNA and protein gradually decreased. The levels of PARP mRNA during larval and pupal periods became less than about 5% of that in unfertilized eggs. After the emergence of adult flies, the levels of PARP mRNA and protein increased both in female and male flies. PARP activity normalized with the total amount of protein in the crude extract changed in parallel to the level of PARP protein throughout the developmental stages. The biological significance of the drastic change of mRNA and protein levels of PARP still remains to be clarified.     

Baseline noise and measurement uncertainty in liquid chromatography.

The stochastic properties of baseline noise in HPLC systems with a UV photo-diode array, photo-multiplier and gamma-ray detector were examined by dividing the noise into auto-correlated random process (Markov process) and an independent process (white noise). The present work focused on the effect of the stochastic noise properties on a theoretical estimation of the standard deviation (SD) of area measurements in instrumental analyses. An estimation theory, called FUMI theory (Function of Mutual Information), was taken as an example. A computer simulation of noise was also used. It was shown that the reliability (confidence intervals) of theoretical SD estimates mainly depends on the following factors: the ratio of the white noise and Markov process occurring in the baselines; the number of data points used for the estimation; the width of a target peak for which the SD is estimated.     

A novel approach for LC-MS/MS-based chiral metabolomics fingerprinting and chiral metabolomics extraction using a pair of enantiomers of chiral derivatization reagents

Chiral metabolites are found in a wide variety of living organisms and some of them are understood to be physiologically active compounds and biomarkers. However, the overall analysis of chiral metabolomics is quite difficult due to the high number of metabolites, the significant diversity in their physicochemical properties, and concentration range from metabolite-to-metabolite. To solve this difficulty, we developed a novel approach for chiral metabolomics fingerprinting and chiral metabolomics extraction, which is based on the labeling of a pair of enantiomers of chiral derivatization reagents (i.e., DMT-(S,R)-Pro-OSu and DMT-3(S,R)-Apy) and precursor ion scan chromatography of the derivatives. The multivariate statistics is also required for this strategy. The proposed procedures were evaluated by the detection of a diagnostic marker (i.e., d-lactic acid) using the saliva of diabetic patients. This method was used for the determination of biomarker candidates of chiral amines and carboxyls in Alzheimer's disease (AD) brain homogenates. As the results, l-phenylalanine (L-Phe) and l-lactic acid (L-LA) were identified as the decreased and increased biomarker candidates in the AD brain, respectively. Therefore, the proposed approach seems to be helpful for the determination of non-target chiral metabolomics possessing amines and carboxyls.     

Influence of RNA Strand Rigidity on Polyion Complex Formation with Block Catiomers

Polyion complexes (b‐PICs) are prepared by mixing single‐ or double‐stranded oligo RNA (aniomer) with poly(ethylene glycol)‐b‐poly(l ‐lysine) (PEG‐PLL) (block catiomer) to clarify the effect of aniomer chain rigidity on association behaviors at varying concentrations. Here, a 21‐mer single‐stranded RNA (ssRNA) (persistence length: 1.0 nm) and a 21‐mer double‐stranded RNA (small interfering RNA, siRNA) (persistence length: 62 nm) are compared. Both oligo RNAs form a minimal charge‐neutralized ionomer pair with a single PEG‐PLL chain, termed unit b‐PIC (uPIC), at low concentrations (<≈0.01 mg mL⁻¹). Above the critical association concentration (≈0.01 mg mL⁻¹), ssRNA b‐PICs form secondary associates, PIC micelles, with sizes up to 30–70 nm, while no such multimolecular assembly is observed for siRNA b‐PICs. The entropy gain associated with the formation of a segregated PIC phase in the multimolecular PIC micelles may not be large enough for rigid siRNA strands to compensate with appreciably high steric repulsion derived from PEG chains. Chain rigidity appears to be a critical parameter in polyion complex association.

     

A non-negative matrix factorization model based on the zero-inflated Tweedie distribution

Non-negative matrix factorization (NMF) is a technique of multivariate analysis used to approximate a given matrix containing non-negative data using two non-negative factor matrices that has been applied to a number of fields. However, when a matrix containing non-negative data has many zeroes, NMF encounters an approximation difficulty. This zero-inflated situation occurs often when a data matrix is given as count data, and becomes more challenging with matrices of increasing size. To solve this problem, we propose a new NMF model for zero-inflated non-negative matrices. Our model is based on the zero-inflated Tweedie distribution. The Tweedie distribution is a generalization of the normal, the Poisson, and the gamma distributions, and differs from each of the other distributions in the degree of robustness of its estimated parameters. In this paper, we show through numerical examples that the proposed model is superior to the basic NMF model in terms of approximation of zero-inflated data. Furthermore, we show the differences between the estimated basis vectors found using the basic and the proposed NMF models for \(\beta \) divergence by applying it to real purchasing data.     

Protein structure predictions by parallel simulated annealing molecular dynamics using genetic crossover

We propose a conformational search method to find a global minimum energy structure for protein systems. The simulated annealing is a powerful method for local conformational search. On the other hand, the genetic crossover can search the global conformational space. Our method incorporates these attractive features of the simulated annealing and genetic crossover. In the previous works, we have been using the Monte Carlo algorithm for simulated annealing. In the present work, we use the molecular dynamics algorithm instead. To examine the effectiveness of our method, we compared our results with those of the normal simulated annealing molecular dynamics simulations by using an α-helical miniprotein. We used genetic two-point crossover here. The conformations, which have lower energy than those obtained from the conventional simulated annealing, were obtained.     

Selective photoinduced energy transfer from a thiophene rotaxane to acceptor

An energy transfer process was investigated using cyclodextrin-oligothiophene rotaxanes (2T-[2]rotaxane). The excited energy of 2T-[2]rotaxane is transferred to the sexithiophene derivative which is included in the cavity of β-CD stoppers of 2T-[2]rotaxane.