Stimuli-responsive Novel Amphiphilic Polymers for Chemical and Biomedical Applications

Amphiphilic polymers are a class of polymers that self-assemble into different types of microstructure, depending on the solvent environment and external stimuli. Self assembly structures can exist in many different forms, such as spherical micelles, rod-like micelles, bi-layers, vesicles, bi-continuous structure etc. Most biological systems are basically comprised of many of these organised structures arranged in an intelligent manner, which impart functions and life to the system. We have adopted the atom transfer radical polymerization (ATRP) technique to synthesize various types of block copolymer systems that self-assemble into different microstructure when subject to an external stimuli, such as pH or temperature. The systems that we have studied are: (1) pH responsive fullerene (C60) containing poly(methacrylic acid) (PMAA-b-C60); (2) pH and temperature responsive fullerene containing poly[2-(dimethylamino)ethyl methacrylate] (C₆₀-b-PDMAEMA); (3) other responsive water-soluble fullerene systems. By varying temperature, pH and salt concentration, different types microstructure can be produced. In the presence of inorganic salts, fractal patterns at nano- to microscopic dimension were observed for negatively charged PMAA-b-C60, while such structure was not observed for positively charged PDMAEMA-b-C60. We demonstrated that negatively charged fullerene containing polymeric systems can serve as excellent nano-templates for the controlled growth of inorganic crystals at the nano- to micrometer length scale and the possible mechanism was proposed. The physical properties and the characteristics of their self-assembly properties will be discussed, and their implications to chemical and biomedical applications will be highlighted.

Discrete and continuous compositions

This paper examines a dataset which is modeled well by the Poisson-Log Normal process and by this process mixed with Log Normal data, which are both turned into compositions. This generates compositional data that has zeros without any need for conditional models or assuming that there is missing or censored data that needs adjustment. It also enables us to model dependence on covariates and within the composition

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observed for each individual. A particular case of FDA is when the observed functions are density functions, that are also an example of infinite dimensional compositional data. In this work we compare several methods for dimensionality reduction for this particular type of data: functional principal components analysis (PCA) with or without a previous data transformation and multidimensional scaling (MDS) for diferent inter-densities distances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (households income distributions)

Attention, memory and verbal learning and their relation to schizotypal traits in unaffected parents of schizophrenic patients

The main objective of this ex post facto study is to compare the differences in cognitive functions and their relation to schizotypal personality traits between a group of unaffected parents of schizophrenic patients and a control group. A total of 52 unaffected biological parents of schizophrenic patients and 52 unaffected parents of unaffected subjects were assessed in measures of attention (Continuous Performance Test- Identical Pairs Version, CPT-IP), memory and verbal learning (California Verbal Learning Test, CVLT) as well as schizotypal personality traits (Oxford-Liverpool Inventory of Feelings and Experiences, O-LIFE). The parents of the patients with schizophrenia differ from the parents of the control group in omission errors on the Continuous Performance Test- Identical Pairs, on a measure of recall and on two contrast measures of the California Verbal Learning Test. The associations between neuropsychological variables and schizotpyal traits are of a low magnitude. There is no defined pattern of the relationship between cognitive measures and schizotypal traits

Special Functions

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