Shear modulus determination in model hydrogels by means of elongated magnetic nanoprobes

The mechanical characterization of complex soft matter by quasi-static magnetometry using nanoscopic magnetic probes is demonstrated for model hydrogels doped with two types of elongated magnetic nanoparticles. Chemically crosslinked poly(acrylamide) (PAAm) hydrogels serve as the matrix in which nickel nanorods or weakly magnetized hematite (α-Fe₂O₃) ellipsoids are embedded as local probes. We investigated the swelling behavior of the ferrogels in order to verify that their equilibrium swelling degree in water is not influenced by the probes, shows a good correlation with the Frenkel–Flory–Rehner model. The proposed magnetomechanical method relies on a correlation between the shear modulus of the PAAm hydrogel matrix and the coercive fields of the corresponding isotropic ferrogels. By extending the Stoner–Wohlfarth model for single-domain blocked magnetic particles by a term for particle rotation in an elastic matrix, information on the shear modulus of the matrix can be obtained. Comparison of the results with the expected relation from rubber elasticity theory illustrates both the general potential as well as the limits of the approach. © 2012 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2012     

Characterizing bitterness: identification of key structural features and development of a classification model

This work describes the first approach in the development of a comprehensive classification method for bitterness of small molecules. The data set comprises 649 bitter and 13 530 randomly selected molecules from the MDL Drug Data Repository (MDDR) which are analyzed by circular fingerprints (MOLPRINT 2D) and information-gain feature selection. The feature selection proposes substructural features which are statistically correlated to bitterness. Classification is performed on the selected features via a na?ve Bayes classifier. The substructural features upon which the classification is based are able to discriminate between bitter and random compounds, and thus we propose they are also functionally responsible for causing the bitter taste. Such substructures include various sugar moieties as well as highly branched carbon scaffolds. Cynaropicrine contains a number of the substructural features found to be statistically associated with bitterness and thus was correctly predicted to be bitter by our model. Alternatively, both promethazine and saccharin contain fewer of these substructural features, and thus the bitterness in these compounds was not identified. Two different classes of bitter compounds were identified, namely those which are larger and contain mainly oxygen and carbon and often sugar moieties, and those which are rather smaller and contain additional nitrogen and/or sulfur fragments. The classifier is able to predict 72.1% of the bitter compounds. Feature selection reduces the number of false-positives while also increasing the number of false negatives to 69.5% of bitter compounds correctly predicted. Overall, the method presented here presents both one of the largest databases of bitter compounds presently available as well as a relatively reliable classification method.     

Harvesting chemical information from the Internet using a distributed approach: ChemXtreme

The Internet is a comprehensive resource of chemical information which is at the same time largely unstructured. It provides a wealth of scientific information such as experimental data and requires a suitable automated data mining and analysis tool for its meaningful exploration. The Java based software presented here, ChemXtreme, is developed for harvesting chemical information from the Internet employing the Google API in combination with a distributed client/server text analysis architecture based on JavaRMI. It represents the first and until now the only toolkit for automated structured data retrieval from the Internet which is itself open source. ChemXtreme employs the "search the search engine" strategy, where the URLs returned from the search engine are analyzed further via textual pattern analysis. This process resembles the manual analysis of the hit list, where relevant data are captured and, by means of human intervention, are mined into a format suitable for further analysis. ChemXtreme on the other hand transforms chemical information automatically into a structured format suitable for storage in databases and further analysis and also provides links to the original information source. The query data retrieved from the search engine by the server is encoded, encrypted, and compressed and then sent to all the participating active clients in the network for parsing. Relevant information identified by the clients on the retrieved Web sites is sent back to the server, verified, and added to the database for data mining and further analysis. The distributed further analysis of URLs in a client/server architecture scales very favorably, thus producing only minimal overhead.     

Synthesis and some transformations of new 9-furylnaphtho[2,3-b]furan derivatives

The synthesis of a number of naphtho[2,3-b]furan derivatives, containing a furyl substituent in position 9 by intramolecular cyclization of 2-carboxy and 2-formylbis(5-alkylfur-2-yl)methanes is described. The reactivity of the title compounds in formylation, acetylation, nitration, and oxidation reactions has been investigated. It was shown that nitration of 2-methyl-9-(5-methyl-2-furyl)naphtho[2,3-b]furan-4-yl acetate leads to oxidative furan ring opening rather than to electrophilic substitution.     

Simple route to 3-(2-indolyl)-1-propanones via a furan recyclization reaction

A simple route to 1-R-3-(2-indolyl)-1-propanones has been elaborated based on recyclization of 2-(2-aminobenzyl)furan derivatives. Being a modification of the Reissert indole synthesis, our approach employs the furan ring as a source of carbonyl function. This approach is general and allows varying of substituents in aromatic ring as well as in 3-position of indole nucleus.