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Quantification discrimination

Agarwal et al. 1978), the quantification of these specific enzymes may indicate that exposure to endosulfan has occurred. Blood tests, such as decay curves for aminopyrine in plasma, which are semiquantitative indices of liver enzyme induction, have been used successfully in the past to demonstrate enzyme induction in pesticide-exposed workers. Because numerous chemicals found at hazardous waste sites also induce these hepatic enzymes, these measurements are not specific for endosulfan exposure. However, measurements of enzyme activity, together with the detection of the parent compound or its metabolites in tissue or excreta, can be useful indicators of exposure. All of these potential biomarkers require further verification in epidemiological studies. Further studies with focus on the development of methods to separate and measure the estrogenicity of endosulfan in in vitro assays would be valuable since these assays are more sensitive and discriminative than other conventional biomarkers. Preliminary results have been presented by Sonnenschein et al. (1995). [Pg.196]

The aim of the analysis of cannabinoids in plants is to discriminate between the phenotypes (drug-type/fiber-type). Quantification of cannabinoids in plant material is needed if it will be used in medicinal appHcations, e.g., in C. sativa extracts. The ratio between A9-THC and CBN can be used for the determination of the age of stored marijuana samples [84]. [Pg.25]

Hot split Column independent 50 ppm (FID) Ease of operation Independent of sample Rugged Qualitative analysis Flash vaporisation Thermal degradation Discrimination of higher boiling compounds possible Not suitable for trace analysis Poor, indirect quantification... [Pg.189]

Hot splitless WCOT 0.5 ppm (FID) without preconcentration Lower injection temperature than split Trace analysis Handles dirty samples Automation Flash vaporisation Optimisation required (splitless time, oven temperature, solvent) Limited number of solvents ( solvent effect ) Thermal degradation possible Discrimination possible Poor direct quantification Unsuitable for very polar substances... [Pg.189]

Cool on-column >250 pm column (i.d.) 1 ppm (FID) Reduced thermal degradation and discrimination Wide range of analyte concentrations High sample capacity (LVI) Autosamplers Direct quantification Excellent precision Control of operational conditions (initial oven temperature) Optimisation required Not applicable for polar solvents Column contamination by dirty matrices Poor long term stability... [Pg.189]

The advent of high-resolution capillary gas chromatography (HR-CGC) with on-column injection has resulted in improved GC analysis of polymer additives [92-94]. The solution of the additive mixture is injected directly into the cold end of the capillary column by means of a cold injector. Thus, sample discrimination, the instantaneous evaporation of the sample solvent, is avoided. The nonvaporising, on-column injection combined with very high resolution of the capillary columns allows accurate separation, identification and quantification of additives of complex mixtures. With the solvent venting technique, the sample is introduced into the column without splitting and sample concentrations... [Pg.190]

DNA and RNA quantification, SNP typing, hybridization, and structural alteration have been widely carried out by modified oligonucleotides possessing pyrene derivatives [104-113]. As is known, pyrene-1-carboxaldehyde fluorescence is considerably dependent on solvent polarity [114], being strong in methanol but insignificant in nonpolar solvents [115]. Owing to this property, Tanaka and collaborators developed a pyrenecarboxamide-tethered modified DNA base, PyU 46, and applied it to SNP discrimination in DNA [116-120],... [Pg.42]

The phenomenon of discrimination induced by matrix effects is quite disadvantageous in qualitative analysis, but in the quantification procedure its influence is devastating. Several techniques applying MS or MS-MS, however, can help to overcome this crucial influence. The most common way out of this dilemma is the application of column separation to minimise or even exclude matrix effects entailed with the disadvantage of long-lasting separations. In parallel, the difference between the time needed for the performance of LC examinations and the time needed for FIA becomes obvious and will be pointed out later on. [Pg.179]

Although confocal microscopic imaging of cells incubated with labeled targeted systems allow a rather clear decision about cytoinvasion, the quantification of cellular uptake is rather challenging, due to coincidence of cytoadhesion with cytoinvasion. The discrimination between both processes, however, is possible by taking into account some distinctive features of certain transport mechanisms. [Pg.648]

This procedure has been developed for quantification of the three types of macromolecules in tissue extracts, where other hiomolecules are also present. Small dissolved amounts of DNA, RNA, or protein, especially when no material should be consumed and no interfering substances are in the solution, maybe estimated by UV photometry, but a discrimination between DNA and RNA is impossible by reading absorbencies (cf. Protocol 1.2.5). [Pg.14]

Both the detection limit and the limit of quantification, as defined, are often not very stable characteristics of an analytical method, because the blank signal and the signal generated by the very low concentrations of the analyte are frequently dependent on certain analytical parameters, including the purity of reagents, sample matrices, environmental conditions, instrumentation, and the analysts themselves. Sensitivity is a measure of the ability of an analytical method to discriminate between small differences in analyte concentration. It is defined as the analyte signal per unit concentration of the analyte. Despite the apparent simplicity of the sensitivity concept, a degree of confusion surrounds its use. This confusion stems from the perception that the sensitivity of a method is the same as the limit of detection. [Pg.759]

When used in the time-invariant mode (i.e., in equilibrium), it is a first-order chemical sensor that can yield qualitative and quantitative information based on the LSER paradigm about composition of the vapor mixtures (Fig. 10.13). By acquiring the data in the transient regime, it becomes a second-order sensor and in addition to the composition, information about diffusion coefficients in different polymers is obtained. This is then the added value. It is possible only because the model describing the capacitance change included diffusion. In spite of the complexity of the response function, a good discrimination and quantification has been obtained. [Pg.331]

Hamid Muhammed, H. and Larsolle, A. (2003) Feature-vector based analysis of hyperspectral crop reflectance data for discrimination quantification of fungal disease severity in wheat. Biosyst. Eng. 86(2), 125-34. [Pg.298]

The utility of sulfur K-edge X-ray absorption spectroscopy for the determination and quantification of sulfur forms in nonvolatile hydrocarbons has been investigated. X-ray Absorption Near Edge Structure (XANES) spectra were obtained for a selected group of model compounds, for several petroleum asphaltene samples and for Rasa coal. For the model compounds the sulfur XANES was found to vary widely from compound to compound, and to provide a fingerprint for the form of sulfur involved. The use of third derivatives of the spectra enabled discrimination of mixtures of sulfide and thiophenic model compounds, and allowed approximate quantification of the amount of each component in the mixtures, in the asphaltene samples and the coal. These results represent the first demonstration that nonvolatile sulfide and thiophenic sulfur forms can be distinguished and approximately quantified by direct measurement. [Pg.223]

Endrizzi K, Fischer J, Klein K, Schwab M, Nussler A, Neuhaus P, Eichelbaum M, Zanger UM. Discriminative quantification of cytochrom P4502D6 and 2D7/8 psuedogene expression by TaqMan real-time reverse transcriptase polymerase chain reaction. Anal Biochem 2002 15 121-131. [Pg.326]


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