Classification and recognition of compounds in low-resolution open-path FT-IR spectrometry by Kohonen self-organizing maps

The possibility of using one- and two-dimensional Kohonen self-organizing maps (SOMs) to recognize similarities in low-resolution vapor-phase infrared spectra without any additional information, i.e., in an unsupervised mode, has been investigated. Full-range vapor-phase FT-IR reference spectra were first used to train the networks and the trained networks were then used to classify the reference spectra into several groups. The feasibility of reducing the spectral range to be consistent with the atmospheric windows used in open-path FT-IR spectrometry was also studied. Kohonen networks are shown to be relatively immune to the presence of noise. An example of using a trained Kohonen map to recognize the presence of selected compounds in field-measured open-path FT-IR spectra is given.     

Application of self-organizing maps in compounds pattern recognition and combinatorial library design

In the computer-aided drug design, in order to find some new leads from a large library of compounds, the pattern recognition study of the diversity and similarity assessment of the chemical compounds is required; meanwhile in the combinatorial library design, more attention is given to design target focusing library along with diversity and drug-likeness criteria. This review presents the current state-of-art applications of Kohonen self-organizing maps (SOM) for studying the compounds pattern recognition, comparing the property of molecular surfaces, distinguishing drug-like and nondrug-like molecules, splitting a dataset into the proper training and test sets before constructing a QSAR (Quantitative Structural-Activity Relationship) model, and also for the combinatorial libraries comparison and the combinatorial library design. The Kohonen self-organizing map will continue to play an important role in drug discovery and library design.     

Raman spectrometry and neural networks for the classification of wood types. 2. Kohonen self-organizing maps

One- and two-dimensional Kohonen self-organizing maps (SOMs) were successfully used for the unsupervised differentiation of the Fourier transform Raman spectra of hardwoods from softwoods. The SOMs were also applied to differentiate temperate woods from tropical woods, and results showed that the two types of woods could only be partly differentiated. A semi-quantitative method that is based on the Euclidean distances of the weight matrix has been developed to assist the automatic clustering of the neurons in a two-dimensional SOM.     

Classification of perovskites with supervised self-organizing maps

In this work supervised self-organizing maps were used for structural classification of perovskites. For this purpose, structural data for total number of 286 perovskites, belonging to ABO3 and/or A2BB'O6 types, were collected from literature: 130 of these are cubic, 85 orthorhombic and 71 monoclinic. For classification purposes, the effective ionic radii of the cations, electronegativities of the cations in B-position, as well as, the oxidation states of these cations, were used as input variables. The parameters of the developed models, as well as, the most suitable variables for classification purposes were selected using genetic algorithms. Two-third of all the compounds were used in the training phase. During the optimization process the performances of the models were checked using cross-validation leave-1/10-out. The performances of obtained solutions were checked using the test set composed of the remaining one-third of the compounds. The obtained models for classification of these three classes of perovskite compounds show very good results. Namely, the classification of the compounds in the test set resulted in small number of discrepancies (4.2-6.4%) between the actual crystallographic class and the one predicted by the models. All these results are strong arguments for the validity of supervised self-organizing maps for performing such types of classification. Therefore, the proposed procedure could be successfully used for crystallographic classification of perovskites in one of these three classes.     

Relative characterization of rosemary samples according to their geographical origins using microwave-accelerated distillation, solid-phase microextraction and Kohonen self-organizing maps

For centuries, rosemary (Rosmarinus officinalis L.) has been used to prepare essential oils which, even now, are highly valued due to their various biological activities. Nevertheless, it has been noted that these activities often depend on the origin of the rosemary plant and the method of extraction. Since both of these quality parameters can greatly influence the chemical composition of rosemary oil, an original analytical method was developed where "dry distillation" was coupled to headspace solid-phase microextraction (HS-SPME) and then a data mining technique using the Kohonen self-organizing map algorithm was applied to the data obtained. This original approach uses the newly described microwave-accelerated distillation technique (MAD) and HS-SPME; neither of these techniques require external solvent and so this approach provides a novel "green" chemistry sampling method in the field of biological matrix analysis. The large data set obtained was then treated with a rarely used chemometric technique based on nonclassical statistics. Applied to 32 rosemary samples collected at the same time from 12 different sites in the north of Algeria, this method highlighted a strong correlation between the volatile chemical compositions of the samples and their origins, and it therefore allowed the samples to be grouped according to geographical distribution. Moreover, the method allowed us to identify the constituents that exerted the most influence during classification.     

Conformational analysis of lipid molecules by self-organizing maps

The authors have studied the use of the self-organizing map (SOM) in the analysis of lipid conformations produced by atomic-scale molecular dynamics simulations. First, focusing on the methodological aspects, they have systematically studied how the SOM can be employed in the analysis of lipid conformations in a controlled and reliable fashion. For this purpose, they have used a previously reported 50 ns atomistic molecular dynamics simulation of a 1-palmitoyl-2-linoeayl-sn-glycero-3-phosphatidylcholine (PLPC) lipid bilayer and analyzed separately the conformations of the headgroup and the glycerol regions, as well as the diunsaturated fatty acid chain. They have elucidated the effect of training parameters on the quality of the results, as well as the effect of the size of the SOM. It turns out that the main conformational states of each region in the molecule are easily distinguished together with a variety of other typical structural features. As a second topic, the authors applied the SOM to the PLPC data to demonstrate how it can be used in the analysis that goes beyond the standard methods commonly used to study the structure and dynamics of lipid membranes. Overall, the results suggest that the SOM method provides a relatively simple and robust tool for quickly gaining a qualitative understanding of the most important features of the conformations of the system, without a priori knowledge. It seems plausible that the insight given by the SOM could be applied to a variety of biomolecular systems and the design of coarse-grained models for these systems.     

Classification of bacteria by pyrolysis-capillary column gas chromatography-mass spectrometry and pattern recognition

Pyrolysis followed by capillary column gas chromatography-mass spectrometry has been applied to the classification of five bacterial species of the genus Flacobacterium. Data were subjected to computerized pattern recognition using the ARTHUR software package. The results indicate that classification potential is greatly improved by the use of mass fragmentography. Other factors such as growth media, harvesting and storage conditions were found to be relatively unimportant.     

Classification of Antarctic algae by applying Kohonen neural network with 14 elements determined by inductively coupled plasma optical emission spectrometry

Optical emission spectrometers can generate results, which sometimes are not easy to interpret, mainly when the analyses involve classifications. To make simultaneous data interpretation possible, the Kohonen neural network is used to classify different Antarctic algae according to their taxonomic groups from the determination of 14 analytes. The Kohonen neural network architecture used was 5×5 neurons, thus reducing 14-dimension input data to two-dimensional space. The input data were 14 analytes (As, Co, Cu, Fe, Mn, Sr, Zn, Cd, Cr, Mo, Ni, Pb, Se, V) with their concentrations, determined by inductively coupled plasma optical emission spectrometry in 11 different species of algae. Three taxonomic groups (Rhodophyta, Phaeophyta and Cholorophyta) can be differentiated and classified through only their Cu content.     

Clustering analysis of keishibukuryogan formulas by use of self-organizing maps

Kampo medicines, traditional herbal medicines in Japan, are comprised of multiple botanical raw materials that contain a number of pharmacologically active substances. Conventionally, the quality control of kampo medicines has been performed by analyzing the contents of two or three representative components. However, it is not sufficient to check quality only with a limited number of specific components. We performed HPLC of 287 lots of keishibukuryogan formulas, calculated the areas of 11 components on chromatograms as feature values and made a cluster analysis using self-organizing maps (SOMs). We verified the precision (repeatability and intermediate precision) of clustering results when using the same samples and successfully established an clustering method using SOMs that is capable of precisely clustering differences in HPLC-fingerprints among pharmaceutical manufacturers, differences in HPLC-fingerprints due to the combination ratios of botanical raw materials, and differences in HPLC-fingerprints due to changes in component contents caused by time-course deterioration. Consequently, we could confirm that this method is useful for controlling the quality of multiple component drugs and analyzing quality differences.     

三光气的含量的光谱快速测定

光气是一种重要的化工原料,在农药、医药、高分子材料的研究和生产中应用很广.但光气剧毒,使用不当容易发生危险.碳酸双三氯甲酯,俗称三光气或固体光气,简称BTC,是一种固体化合物,挥发性小,使用方便,可以作为光气的代用品.近年来,三光气作为光气的替代产品已经被人们广泛接受.     

Application of self-organizing maps in conformational analysis of lipids.

The characteristics of lipid assemblies are important for the functions of biological membranes. This has led to an increasing utilization of molecular dynamics simulations for the elucidation of the structural features of biomembranes. We have applied the self-organizing map (SOM) to the analysis of the complex conformational data from a 1-ns molecular dynamics simulation of PLPC phospholipids in a membrane assembly. Mapping of 1.44 million molecular conformations to a two-dimensional array of neurons revealed, without human intervention, the main conformational features in hours. Both the whole molecule and the characteristics of the unsaturated fatty acid chains were analyzed. All major structural features were easily distinguished, such as the orientational variability of the headgroup, the mainly trans state dihedral angles of the sn-1 chain, and both straight and bent conformations of the unsaturated sn-2 chain. Furthermore, presentation of the trajectory of an individual lipid molecule on the map provides information on conformational dynamics. The present results suggest that the SOM method provides a powerful tool for routinely gaining rapid insight to the main molecular conformations as well as to the conformational dynamics of any simulated molecular assembly without the requirement of a priori knowledge.     

Remote,real-time,on-line monitoring of high-temperature samples by noninvasive open-path laser plasma spectrometry

A remote detection system based on optical emission spectrometry of laser-induced plasmas has been developed to record spectra in the visible region from samples placed at remote distances from the excitation source. Unlike from fiber-optic-based systems, light collection is performed remotely as well. Laboratory-scale experiments have shown the possibility of performing real-time analysis of samples placed remotely. The application in the noninvasive analysis of hot samples (at 1,200 degrees C) has been demonstrated as well, allowing the dynamic monitoring of selective elemental migration.     

Detection of chemical agents in the atmosphere by open-path FT-IR spectroscopy under conditions of background interference: II. Fog and rain

Open-path FT-IR spectra of low-concentration releases of diethyl ether were measured both when a glycol fog was passed into the infrared beam and when large water droplets from a lawn sprinkler were sprayed into the beam. It was shown that the glycol fog, for which the droplet size was much less than the wavelength of the infrared radiation, gave rise to a significant interference such that partial least squares (PLS) regression would only yield reasonable values for the ether concentration if background spectra in which the glycol fog was present were included in the calibration set. On the other hand, target factor analysis (TFA) allowed the presence of the ether to be recognized without precalibration. When large water droplets were present in the beam, any infrared radiation entering the droplet was completely absorbed, so that both PLS and TFA would yield accurate results.     

Detection of chemical agents in the atmosphere by open-path FT-IR spectroscopy under conditions of background interference: I. High-frequency flashes

Open-path FT-IR spectra were measured while fireworks were emitting smoke and incandescent particles into the infrared beam. These conditions were designed to simulate the appearance of smoke and explosions in a battlefield. Diethyl ether was used to simulate the vapor-phase spectra of G agents such as sarin. The measured interferograms were corrected by a high-pass filter and were rejected when interfering features were of such high frequency that they could not be removed by application of this filter. The concentration of diethyl ether was calculated correctly by partial least squares regression in the absence of fireworks but significant errors were encountered when the spectra of the oxide particles were not included in the calibration set. Target factor analysis allowed the presence of the analyte to be detected even when the incandescent particles were present in the beam.     

Comparison of substructural epitopes in enzyme active sites using self-organizing maps

Summary This paper presents a new algorithm to compare substructural epitopes in protein binding cavities. Through the comparison of binding cavities accommodating well characterized ligands with cavities whose actual guests are yet unknown, it is possible to draw some conclusions on the required shape of a putative ligand likely to bind to the latter cavities. To detect functional relationships among proteins, their binding-site exposed physicochemical characteristics are described by assigning generic pseudocenters to the functional groups of the amino acids flanking the particular active site. The cavities are divided into small local regions of four pseudocenters having the shape of a pyramid with triangular basis. To find similar local regions, an emergent self-organizing map is used for clustering. Two local regions within the same cluster are similar and form the basis for the superpositioning of the corresponding cavities to score this match. First results show that the similarities between enzymes with the same EC number can be found correctly. Enzymes with different EC numbers are detected to have no common substructures. These results indicate the benefit of this method and motivate further studies.     

Determination of enantiomeric excess for organic primary amine compounds by chiral recognition fast-atom bombardment mass spectrometry

Enantiomeric excess (ee) of organic primary amine compounds such as phenylglycine methyl ester hydrochloride (2) has been determined by fast-atom bombardment (FAB) mass spectrometry (NBA matrix). Chiral recognition in host–guest complexation systems between crown ethers [H] and amino acid ester ammonium ions [G] has been extended to the ee determination. The method characteristically uses a 1/1 mixture of a pair of enantiomeric hosts whose enantiomer is isotopically labeled [(RRRR)-1 and (SSSS)-1-d₆]. Chiral recognition of a given guest is simply measured with the given host–pair reagent from the relative peak intensities of the two corresponding diastereomeric host–guest complex ions in I[(H_RRRR · G)⁺]/I[(H_SSSS-d6 · G)⁺ = I_R/I_S-d6, so called IRIS value. The IRIS value varies in a linear fashion with the ee quantitiy of 2 and produces a symmetric linear V-shaped plot, indicating that in the case of a primary amine guest (such as 2) with unknown ee, one can determine the ee by this type of chiral recognition FAB mass spectometry. Further, based on the observed concentration effects on the IRIS values, it is suggested that the present IRIS value reflects the concentration ratio of the diastereomeric complex ions formed in the matrix.     

Diffuse reflection and polarization modulation FT-IR spectrometry of surface species

Summary Two techniques for measuring the infrared spectra of adsorbed species on surfaces of different types are described. Diffuse reflectance spectra of species adsorbed on powdered substrates with a high surface area can be measured with an exceptionally high signal-to-noise ratio. The technique is illustrated by the adsorption of carbon monoxide on rhodium supported on alumina at metal loadings between 0.1 and 10%. Some doubt is cast on previous band assignments for adsorbed CO molecules. Grazing incidence reflection-absorption spectrometry can be used to measure the spectra of molecules on flat metallic substrates of very low surface area. Attempts to develop a technique for observing the intermolecular vibration between the adsorbate and the substrate using a unique triple modulation approach are discussed.

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FT-IR-Spektrometrie mit diffuser Reflexions- und Polari-sations-Modulation von Adsorbaten an Oberflächen

Zusammenfassung Zwei Techniken zur Messung von Infrarot-Spektren von Adsorbaten verschiedener Art werden beschrieben. Diffuse Reflexionsspektren von Adsorbaten an pulverförmigen Substraten mit einer großen Oberfläche können mit einem außerordentlich großen Signal-zu-RauschVerhältnis gemessen werden. Als Beispiel dient die Adsorption von Kohlenstoffmonoxid an Rhodium auf Aluminiumoxid bei Metallgehalten von 0,1 bis 10%. Einige Zweifel an früheren Bandzuweisungen für adsorbierte CO-Moleküle werden geäußert. Reflexions-Absorptions-Spektrometrie mit streifendem Einfall kann zur Messung der Spektren von Molekülen an flachen metallischen Substraten mit sehr geringer Oberfläche benutzt werden. Versuche zur Entwicklung einer Technik für die Beobachtung der intermolekularen Schwingungen zwischen dem Adsorbaten und dem Substrat mittels einer einzigartigen Dreifach-Modulationstechnik werden diskutiert.

     

Identification of compounds in wine by HPLC-tandem mass spectrometry

In this work several compounds were detected in wines by HPLC-tandem mass spectrometry. In particular cinnamic and benzoic acids, tyrosol, apigenin-7-glucoside and luteolin-7-glucoside were identified and quantified in Italian wines. Red wines show bigger amount of cinnamic and benzoic acids than white wines. tyrosol is in bigger amount with respect to two flavones: luteolin-7-glucoside and apigenin-7-glucoside. These last two flavones are only in some wine, but it can be important to detect the presence of different substances in small amount to be able to characterize a wine.