A cyclization reaction in the electron-impact induced fragmentation of some N-propargylic oxoquinazolines and anilines

Evidence for an acetylenic rearrangement, involving the ring-closure of ions containing the N-propargylaniline substructure to the corresponding quinoline ions, has been obtained in a study of the electron-impact induced fragmentation of 1,4-dihydro-4-oxo-2-phenyl-1-propargylquinazoline (I) and 1,2,3,4-tetrahydro-2-oxo-3-phenyl-1-propargylquinazoline (II). The N-propargylaniline moiety is formed from compounds I and II through the RDA process. N-Methyl-N-propargylaniline (III), which was examined as a model compound, was also found to undergo this rearrangement but N-methyl-N-propargyl-2,6-xylidine (IV), on the other hand, exhibits a quite different fragmentation pattern due to its blocking methyl groups, which prevent the rearrangement. Exact mass measurement and specific deuterium labelling were used to establish the fragmentation routes.     

Untersuchungen über die Verwendung von125J-markiertem Testosteron bei Proteinbindungsmethoden

The newly synthesized¹²⁵I-testosterone-3-carboxy-methyloxime-tyramide was tested for its applicability in protein binding methods. The binding of the radioactive steroid derivative to sex hormone binding globulin (SHBG), albumins and testosterone antibodies was examined. Furthermore the adsorption to florisil, charcoal and amberlite was studied. The results show:

1. ¹²⁵I-testosterone is bound to antibodies obtained by immunization with testosterone-3-oxime-albumin conjugate similarly to³H-testosterone and unlabelled steroid.
2. ¹²⁵I-testosterone and³H-testosterone show identical binding to florisil, charcoal and amberlite.

Therefore the¹²⁵I-labelled hormone is suitable in competitive protein binding methods using testosterone antibodies and it can displace the tritium labelled hormone. Since¹²⁵I-steroids have higher specific activities the sensitivity of the method is increased. Furthermore the practicability is enhanced. Special problems arise through the relatively short half-life of the isotope and the changing specific activity. Another difficulty is its decreased chemical stability when compared with the tritiated steroid.     

Clean-up and analysis of carbazole and acridine type polycyclic aromatic nitrogen heterocyclics in complex sample matrices

A HPLC method for the analysis of polycyclic aromatic nitrogen heterocyclics (PANHs) in complex sample matrices is presented. It isolated and separated carbazole and acridine type PANHs with an absolute recovery of between 79–98%. Open column chromatography is used as an initial step to isolate a PANH fraction. By applying normal-phase liquid chromatography using a dimethylaminopropyl silica stationary phase and utilising back-flush technique it was possible to separate the PANH fraction into two fractions containing acridine type and carbazole type PANHs, respectively. The method applied on a sample of solvent refined coal heavy distillate (SRC II HD). A number of 3–5 ring acridines and carbazoles were identified with GC–electron impact MS and quantified with GC–nitrogen–phosphorous detection. Polycyclic aromatic hydrocarbons (PAHs) were determined in the SRC II HD sample by automated on-line clean-up and analysis of the obtained PAH fraction with coupled LC–GC–flame ionization detection. There was no overlap between the PANH and the PAH fractions with this method, and carbazoles and acridines were efficiently separated.     

Quinolines in clothing textiles—a source of human exposure and wastewater pollution?

A production process in which the use of various types of chemicals seems to be ubiquitous makes the textile industry a growing problem regarding both public health as well as the environment. Among several substances used at each stage, the present study focuses on the quinolines, a class of compounds involved in the manufacture of dyes, some of which are skin irritants and/or classified as probable human carcinogens. A method was developed for the determination of quinoline derivatives in textile materials comprising ultrasound-assisted solvent extraction, solid phase extraction cleanup, and final analysis by gas chromatography/mass spectrometry. Quinoline and ten quinoline derivatives were determined in 31 textile samples. The clothing samples, diverse in color, material, brand, country of manufacture, and price, and intended for a broad market, were purchased from different shops in Stockholm, Sweden. Quinoline, a possible human carcinogen, was found to be the most abundant compound present in almost all of the samples investigated, reaching a level of 1.9 mg in a single garment, and it was found that quinoline and its derivatives were mainly correlated to polyester material. This study points out the importance of screening textiles with nontarget analysis to investigate the presence of chemicals in an unbiased manner. Focus should be primarily on clothing worn close to the body.     

Formation of benzynes from 2,6-dihaloaryllithiums: mechanistic basis of the regioselectivity

The key elimination step for the formation of 3-chloro- and 3-fluorobenzyne from 2-chloro-6-fluorophenyllithium displays a pronounced solvent-dependent regioselectivity. 6Li and 13C NMR spectroscopic studies on 2-chloro-6-fluorophenyllithium reveal a single monomeric aryllithium, suggested by DFT computational studies to be a trisolvate. Rate studies indicate that the elimination of LiCl and LiF proceeds via trisolvated and disolvated monomers, respectively.     

Multivariate design

In multivariate data analysis such as principal components analysis (PCA) and projections to latent structures (PLS), it is essential that the training set systems (objects) are selected to provide data with substantial information for model parametrization, and to represent properly any future situations where the multilvariate model is used for predictions. In the framework of multivariate projections (PCA, SIMCA and PLS), elementary concepts of statistical design (fractional factorials and composite designs) can be used with the latent variables (PC or PLS scores) as design variables. The plan of action thus becomes: (1) problem formulation (specify aim and model, make a conceptual division of the investigated system into subsystems); (2) collection of multivariate data for each type of subsystems; (3) estimation of the practical dimensionality of the data for each type of subsystems by PC or PLS analysis; (4) use of the PC or PLS scores (t) as design variables in the combination of subsystems to systems in the training set; (5) measurement of responses (Y); (6) analysis of data by PCA or PLS; (7) interpretation of results with possible feedback to steps 1, 2 or 3. The procedures are illustrated by two problems: a structure/activity relationship for a family of peptides, and optimization of an organic synthesis with respect to system variables (solvent, substrate, co-reactant_) and process variables (temperature, reactant concentrations).     

Zur Analyse von Eisen -und Stahl

Ohne Zusammenfassung     

Simultaneous selective detection of organophosphate and phthalate esters using gas chromatography with positive ion chemical ionization tandem mass spectrometry and its application to indoor air and dust

A selective and sensitive method for the simultaneous determination of 14 organophosphate and six phthalate esters using gas chromatography (GC) and mass spectrometry (MS) is presented. Both of these compound classes are frequently found in the indoor environment due to their use as bulk additives in numerous polymers, consumer products and building materials. GC/MS utilizing positive ion chemical ionisation (PICI) in selected reaction monitoring (SRM) mode with isobutane as the reagent gas was found to be the best of the tested methods; it proved superior to electron ionisation (EI) in selected ion monitoring (SIM) mode and to PICI using methane as the reagent gas. The method was applied to indoor air samples collected by active air sampling using solid‐phase extraction (SPE) cartridges. Organophosphates and phthalates were simultaneously determined with method detection limits (MDLs) in the range of 0.1–47 ng m^?3. For most compounds the MDLs were ≤0.2 ng m^?3, but due to the presence of some of these ubiquitous indoor air pollutants in the blanks, significantly higher MDLs were observed for a few compounds. Finally, the method was also applied in the screening of a much more complex sample matrix, indoor dust. Copyright © 2010 John Wiley & Sons, Ltd.