The use of 'electronic nose' sensor responses to predict the inhibition activity of alcohols on the cytochrome P-450 catalyzed p-hydroxylation of aniline.

A quantitative structure activity relationship (QSAR) has been formulated to describe the inhibitory action of a series of alcohols on the cytochrome P-450 catalyzed p-hydroxylation of aniline. The descriptors used in the QSAR are the responses of individual sensors in a polymer-based electronic nose, and are all easily generated experimental values. If the various electronic nose sensor response patterns for the family of test alcohols reflect differences in the chemical properties that are involved in the cytochrome P-450 inhibition process, it ought to be possible to correlate the differences in the electronic nose signals of these analytes with the differences in the cytochrome P-450 inhibition by these species. To evaluate this possibility, multiple linear regression was performed on data obtained from exposure of a series of test alcohols to 19 sensors of a conducting polymer composite electronic nose array. A genetic algorithm was then used to select the optimal set of sensors that best described the inhibitory activity of these alcohols within a linear regression model. The regression equation fit the inhibition data of 20 of the alcohols with an R of 0.995. This fit compares favorably with previously published QSARs on this system that have used log P (P triple bond octanol-water partition coefficient) along with steric parameters of the alcohols, and also compares favorably to QSARs formulated using theoretically calculated parameters.

Comparison of the performance of different discriminant algorithms in analyte discrimination tasks using an array of carbon black--polymer composite vapor detectors.

An array of 20 compositionally different carbon black--polymer composite chemiresistor vapor detectors was challenged under laboratory conditions to discriminate between a pair of extremely similar pure analytes (H2O and D2O), compositionally similar mixtures of pairs of compounds, and low concentrations of vapors of similar chemicals. Several discriminant algorithms were utilized, including k nearest neighbors (kNN, with k = 1), linear discriminant analysis (LDA, or Fisher's linear discriminant), quadratic discriminant analysis (QDA), regularized discriminant analysis (RDA, a hybrid of LDA and QDA), partial least squares, and soft independent modeling of class analogy (SIMCA). H2O and D2O were perfectly classified by most of the discriminants when a separate training and test set was used. As expected, discrimination performance decreased as the analyte concentration decreased, and performance decreased as the composition of the analyte mixtures became more similar. RDA was the overall best-performing discriminant, and LDA was the best-performing discriminant that did not require several cross-validations for optimization.

Covalent metal-organic networks: pyridines induce 2-dimensional oligomerization of (mu-OC6H4O)2Mpy2 (M = Ti, V, Zr).

Treatment of M(OiPr)4 (M = Ti, V) and [Zr(OEt)4]4 with excess 1,4-HOC6H4OH in THF afforded [M(OC6H4O)a(OC6H4OH)3.34-1.83a(OiPr)0.66-0.17a(THF)0.2]n (M = Ti, 1-Ti; V, 1-V, 0.91 < or = a < or = 1.82) and [Zr(1,4-OC6H4O)2-x(OEt)2x]n (1-Zr, x = 0.9). The combination of of 1-M (M = Ti, V, Zr) or M(OiPr)4 (M = Ti, V), excess 1,4- or 1,3-HOC6H4OH, and pyridine or 4-phenylpyridine at 100 degrees C for 1 d to 2 weeks afforded various 2-dimensional covalent metal-organic networks: [cis-M(mu 1,4-OC6H4O)2py2] infinity (2-M, M = Ti, Zr), [trans-M(mu 1,4-OC6H4O)2py2.py] infinity (3-M, M = Ti, V), solid solutions [trans-TixV1-x(mu 1,4-OC6H4O)2py2.py] infinity (3-TixV1-x, x approximately 0.4, 0.6, 0.9), [trans-M(mu 1,4-OC6H4O)2(4-Ph-py)2] infinity (4-M, M = Ti, V), [trans-Ti(mu 1,3-OC6H4O)2py2] infinity (5-Ti), and [trans-Ti(mu 1,3-OC6H4O)2(4-Ph-py)2] infinity (6-Ti). Single-crystal X-ray diffraction experiments confirmed the pleated sheet structure of 2-Ti, the flat sheet structure of 3-Ti, and the rippled sheet structures of 4-Ti, 5-Ti, and 6-Ti. Through protolytic quenching studies and by correspondence of powder XRD patterns with known titanium species, the remaining complexes were structurally assigned. With py or 4-Ph-py present, aggregation of titanium centers is disrupted, relegating the building block to the cis- or trans-(ArO)4Tipy2 core. The sheet structure types are determined by the size of the metal and the interpenetration of the layers, which occurs primarily through the pyridine residues and inhibits intercalation chemistry.

Quantitative study of the resolving power of arrays of carbon black-polymer composites in various vapor-sensing tasks.

A statistical metric, based on the magnitude and standard deviations along linear projections of clustered array response data, was utilized to facilitate an evaluation of the performance of detector arrays in various vapor classification tasks. This approach allowed quantification of the ability of a 14-element array of carbon black-insulating polymer composite chemiresistors to distinguish between members of a set of 19 solvent vapors, some of which vary widely in chemical properties (e.g., methanol and benzene) and others of which are very similar (e.g., n-pentane and n-heptane). The data also facilitated evaluation of questions such as the optimal number of detectors required for a specific task, whether improved performance is obtained by increasing the number of detectors in a detector array, and how to assess statistically the diversity of a collection of detectors in order to understand more fully which properties are underrepresented in a particular set of array elements. In addition, the resolving power of arrays of carbon black-polymer composites was compared to the resolving power of specific collections of bulk conducting organic polymer or tin oxide detector arrays in a common set of vapor classification tasks.