Matrix effect definition

The deviations of Class I, here called absorption and enhancement effects, are known in the literature also as matrix effects, as self-absorption, and as interelement effects. The authors consider the most important objection to each of the last three names to be as. follows. To matrix effect the element sought (ncrt included in the matrix) contributes to the absorption effect for the sample in the same kind of way as any element (free or combined) in the matrix. To self-absorption the name makes no provision for enhancement effects. To interelement effects it fails to recognize that an absorption effect occurs even when only one element is present (Equation 7-4). The term matrix is useful but requires precise definition. What is the matrix when an internal standard is added, or when a powdered sample is dissolved ... 

A fully automated instrumental procedure has been developed for analyzing residual corrosion inhibitors in production waters in the field. The method uses ultraviolet (UV) and fluorescence spectrophotometric techniques to characterize different types of corrosion inhibitors. Laboratory evaluations showed that fluorescence is more suitable for field application because errors from high salinity, contamination, and matrix effect are minimized in fluorescence analysis. Comparison of the automated fluorescence technique with the classic extraction-dye transfer technique showed definite advantages of the former with respect to ease, speed, accuracy, and precision [1658],... 

It is important to note that the matrix effects, interferences, and variability in method efficiency are to be factored in when determining the MDL. If this was not done then only the background noise (see Figure 2, peak 13) would be considered in the definition of the MDL. In real-life samples there is a good possibility that matrix component peaks would either co-elute or elute at retention times close to... 

Although accepted by lUPAC and ACS, the k s /m" definition is hard to implement and does not take either variability in method efficiency or matrix effects into consideration. This would be rectifiable if the calibration curves were prepared from control matrix samples fortified at different concentrations (within one order of magnitude of an estimated LOD). 

Experiments with aldicarb sulfone in ground beef involved simple extraction with acetonitrile during tissue homogenization and resulted in a definite immunoassay response at the tolerance level of 10 qg kg A moderate, but rather consistent, matrix effect was observed. A more severe matrix effect was observed in bovine milk, blood, and urine. For the liquid matrices, sample dilution was not a satisfactory strategy, because the assay variability increased at lower concentrations, negating any benefit of reducing the matrix effect. This work clearly demonsttated that matrix effects are... 

If we desire to study the effects of two independent variables (factors) on one dependent factor, we will have to use a two-way analysis of variance. For this case the columns represent various values or levels of one independent factor and the rows represent levels or values of the other independent factor. Each entry in the matrix of data points then represents one of the possible combinations of the two independent factors and how it affects the dependent factor. Here, we will consider the case of only one observation per data point. We now have two hypotheses to test. First, we wish to determine whether variation in the column variable affects the column means. Secondly, we want to know whether variation in the row variable has an effect on the row means. To test the first hypothesis, we calculate a between columns sum of squares and to test the second hypothesis, we calculate a between rows sum of squares. The between-rows mean square is an estimate of the population variance, providing that the row means are equal. If they are not equal, then the expected value of the between-rows mean square is higher than the population variance. Therefore, if we compare the between-rows mean square with another unbiased estimate of the population variance, we can construct an F test to determine whether the row variable has an effect. Definitional and calculational formulas for these quantities are given in Table 1.19. 

Such chemical evidence as exists, plus a strong wavelength dependence of fluorescence yield from benzene and the low yield of triplet state formation at 2400 A. all point to a competing process whose importance at 2537 A. cannot for the moment be estimated. One must state, therefore, the evidence for the effect of colhsions on the rate of crossover of benzene from excited singlet to excited triplet states is conflicting. In solid matrix, vibrations definitely play an important role in intersystem crossover for benzene. ... 

The logic and consequences of such an approach are discussed, with background definitions and terminology as a starting point. Close attention is paid to the concept of measurement uncertainty as providing a single-number index of accuracy inherent in the procedure. The appropriateness of the uncertainty-based approach to analytical measurement is stressed in view of specific inaccuracy sources such as sampling and matrix effects. And methods for their evaluation are outlined. The question of a clear criterion for analytical procedure validation is also addressed from the standpoint of the quality requirement which measurement results need to meet as an end-product. 

The steric effect depends on the steric factor, /, which depends on the volume fraction of the fiber matrix. The definition of volume fraction is expanded to include the volume of the matrix that is inaccessible to the particle center due to the finite particle size ... 

Matrix effects, which result from the interference of LC co-eluting compounds on the ionization of analytes during the ESI process, induce either ion suppression or enhancement. The effects are matrix-dependent, and ultimately affect the LC-MS quantitative results. Several measures, which include sample extraction, clean-up, dilution, and chromatography, are mandatory and effective to reduce matrix effects. Sample extraction and/or clean-up as discussed in Chapter 4 remove the majority of endogenous compounds present in samples, but a small amount often remains in the final sample extracts. Dilution is the simplest clean-up approach and should be considered first as long as the required detection concentrations are achieved. LC or UHPLC separates analytes from some matrices, which definitely helps to reduce matrix effects. However, no matter what procedures are adopted, matrix effects may not be completely eliminated. Consequently, matrix effects need to be evaluated and compensation is made to achieve the... 

In this method, the components to be determined are added individually in definite amounts. The peak areas obtained are then plotted against the concentration. This method is also used for the preparation of a calibration curve. The disadvantages of the method are that production of the curves is time-consuming and matrix effects are ignored [1-3]. 

The recovery of an analyte in an assay is defined by the FDA in a strictly operational way as the detector response obtained Ifom an amount of the analyte added to and extracted from the biological matrix, compared to the detector response obtained for the true concentration of the pure authentic standard. Recovery pertains to the extraction efficiency of an analytical method within the limits of variability. Recovery of the analyte need not be 100 %, but the extent of recovery of an analyte and of the internal standard should be consistent, precise, and reproducible. Recovery experiments should be performed by comparing the analytical results for extracted samples at three concentrations (low, medium, and high) with unextracted standards that represent 100 % recovery (FDA 2001). In terms of the symbols used in Section 8.4, the recovery is thus defined as the ratio (R /R"), and is equivalent to determination of F provided diat no suppression or enhancement effects give rise to differences between R and R" and that the proportional systematic errors and 1 are negligible. The FDA definition of recovery also corresponds to that of the PE ( process efficiency ) parameter (Matuszewski 2003) discussed in Section 5.3.6a, since the former (FDA 2001) measures a combination of extraction efficiency and matrix effects (if any). 

Depth resolution is most commonly defined as the depth over which a signal from some abruptly appearing layer climbs from 16% of its maximum intensity to 84% when plotted on a hnear scale as this represents two standard deviations ( lGaussian function with a step function. This is illustrated in Figure 5.5. This definition is also applied to decaying signals from abruptly terminated layers. Caution must, however, be exercised when matrix effects and/or radiation-enhanced segregation are active, as these can modify the value derived relative to the absolute sputter-induced depth resolution. 

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