Matrix effect defined

An important distinction was drawn (Matuszewski 2003) between an absolute matrix effect, defined as ME above, and a relative matrix effect that refers to the comparison of ME values determined using different sources (batches) of blank matrix (e.g., biofluids such as plasma or urine for bioanalysis, or environmental matrices such as soil or water). Experience has shown that the... 

The most accurate - and most popular - method of quantifying matrix effects is to analyze the unknown sample with a similar sample of known composition. The relationship between measured intensity and the content of each sample is, usually, defined by the relative sensitivity factor (RSF) ... 

In their broadest application, CRMs are used as controls to verify in a direct comparison the accuracy of the results of a particular measurement parallel with this verification, traceability may be demonstrated. Under conditions demonstrated to be equal for sample and CRM, agreement of results, e.g. as defined above, is proof. Since such possibilities for a direct comparison between samples and a CRM are rare, the user s claims for accuracy and traceability have to be made by inference. Naturally, the use of several CRMs of similar matrix but different analyte content will strengthen the user s inference. Even so, the user stiU has to assess and account for all uncertainties in this comparison of results. These imcertainty calculations must include beyond the common analytical uncertainty budget (i) a component that reflects material matrix effects, (2) a component that reflects differences in the amount of substance determined, (3) the uncertainty of the certified or reference value(s) used, and 4) the uncertainty of the comparison itself AU this information certainly supports the assertion of accuracy in relation to the CRM. However, the requirement of the imbroken chain of comparisons wiU not be formally fulfilled. 

The analytical response generated by an immunoassay is caused by the interaction of the analyte with the antibody. Although immunoassays have greater specificity than many other analytical procedures, they are also subject to significant interference problems. Interference is defined as any alteration in the assay signal different from the signal produced by the assay under standard conditions. Specific (cross-reactivity) and nonspecific (matrix) interferences may be major sources of immunoassay error and should be controlled to the greatest extent possible. Because of their different impacts on analyses, different approaches to minimize matrix effects and antibody cross-reactivity will be discussed separately. 

Quantitative XRF analysis has developed from specific to universal methods. At the time of poor computational facilities, methods were limited to the determination of few elements in well-defined concentration ranges by statistical treatment of experimental data from reference material (linear or second order curves), or by compensation methods (dilution, internal standards, etc.). Later, semi-empirical influence coefficient methods were introduced. Universality came about by the development of fundamental parameter approaches for the correction of total matrix effects... 

In certain circumstances the matrix, defined as everything except the analyte, contributes significantly to the absorbance of a sample and is also highly variable. One method that can be used to improve results is the method of standard additions. The basic idea is to add standard to the analyte so that the standard is subjected to the same matrix effects as the analyte. This method assumes that the system obeys the Beer-Lambert Law. 

During a single run, which may take all day if a large number of samples are to be analyzed, the instrument may drift from its optimum settings. To detect this drift in solution-based techniques, and also to compensate for some matrix effects, a known amount of an element may be added to each sample before analysis. This internal standard (also called a spike) is added to all the samples and blanks, with the exception of the instrument blank (which is defined as zero concentration for all elements see below). It is important that the element (or isotope) chosen as the spike is not an element which is to be determined in the samples, and preferably which does not occur naturally in the samples. It must not be an element which will cause, or suffer from, interference with the other elements to be determined. In solution ICP-MS,... 

Another calibration technique - standard addition - minimizes matrix effects because analytes with well defined increasing concentrations are added to a set of sample solutions to be analyzed. The measured calibration curve in the standard addition mode plots the measured ion intensities of analytes versus the concentration added to the sample solution. The concentration of analytes in the undoped sample is then determined by extrapolation of the calibration curve with the x-axis. Matrix matching is subsequently performed and the matrix effects (signal depression or interference problems) are considered. An example of the standard addition technique is described in Section 6.2.6 using solution based calibration in LA-ICP-MS. 

The overall characteristics of a design generated from an orthogonal matrix are defined by how factors and interactions are assigned to the different columns of the matrix. Certainly, different assignations lead to different experimental designs, but in any case a main effect should be confounded with other main effects. 

From the medical point of view, in contrast to the analytical which refers to the mechanism of sensor signal formation, a direct measurement is defined as a measurement carried out directly in undiluted sample (whole blood, plasma, serum, urine, etc.), whereas indirect measurement employ sample dilution. For an analytical chemist, a direct measurement is more challenging because of small sample volume, interferences and matrix effects, diffusion potential and carry-over effects, and the influence on the sensor lifetime due to high extracta-bility of active components by undiluted samples such as serum or urine. However, this measurement method has one important advantage it allows the measurement of the activity of analytes as-they-are . For... 

This paper discusses SIMS as a multi-dimensional technique for the analysis of inorganic and organic materials. The paper is divided into two parts inorganic and organic (or molecular) SIMS. The inorganic SIMS part focuses on the methods of quantitative analysis and depth profiling applications. In particular, SIMS matrix effects are defined and the physical models and empirical methods used to quantify SIMS results are reviewed. 

Let us begin by looking at the parameters that make SIMS measurements difficult to quantify. First, the secondary ion yield (defined as the ratio of the number of secondary ions sputtered from the surface of a solid sample to the number of primary ions incident upon the specimen) varies over four orders of magnitude from element to element. Second, the yield of each ion is affected by the composition of the matrix. This is the well known SIMS "matrix effect . Third, instrumental effects and ion collection/detection efficiencies can vary from instrument to instrument and specimen to specimen. 

The SIMS "matrix effect" is defined as any change in the secondary ion yields which are caused by changes in the chemical composition or structure of a particular specimen [28]. An example of the SIMS matrix effect is illustrated in Figure 2 for... 

Because the catabolic and metabolic pathways of biotech drugs are often poorly defined and sufficiently sensitive comparator assays are lacking, additional matrix effect tests by parallelism should be conducted with actual study samples. These are often performed on subject samples with aberrant PK profiles. A pool from several time points with sufficient analyte concentration of that subject is serially diluted. The observed concentration times the dilution factors should be within... 

Blocks of pure pyrite embedded in rock from a hydrothermal area were hand-picked under an optical microscope. The pyrite grains were crushed, sieved and preserved in the same way as the coal. We choose mineral pyrite rather than coal pyrite because it is easier to obtain. The behaviour differences between different pyrites are due to particle size effects or matrix effects, but not to pyrite itself, which is a well defined chemical and mineralogical species, ... 

Physical and chemical effects can be combined for identification as sample matrix effects. Matrix effects alter the slope of calibration curves, while spectral interferences cause parallel shifts in the calibration curve. The water-methanol data set contains matrix effects stemming from chemical interferences. As already noted in Section 5.2, using the univariate calibration defined in Equation 5.4 requires an interference-free wavelength. Going to multivariate models can correct for spectral interferences and some matrix effects. The standard addition method described in Section 5.7 can be used in some cases to correct for matrix effects. Severe matrix effects can cause nonlinear responses requiring a nonlinear modeling method. 

According to IUPAC, the LoD is defined as three times the standard deviation of the mean of the blank determinations added to the mean of the blank measures [12]. The LoD obtained for the PFA procedure (Table 1.3) is 8.2 pgkg-1 Pb. This value is low enough to quantify lead in the vast majority of foodstuffs. This method was successfully applied for various food samples, vegetable and animal tissues. No interferences from other elements have been observed. Matrix effects were seen with some samples, but were eliminated simply by diluting the samples. 

In practice an instrumental detection limit is of limited use because in analytical chemistry it is rare that no other procedural steps are involved. Normally a limit of detection for the whole analytical method is required. The terminology used in this area is confusing. In general, limit of detection and detection limit are synonymous. The detection limit will encompass factors such as (a) sample matrix effects (b) loss of the analyte during sample preparation etc. The detection limit for the analytical procedure is defined as The minimum single result which, with a stated prohahility, can be distinguished from a suitable blank value . ... 

As mentioned above, calculated absorbance values derived from peak height measurements are sensitive to matrix effects as well as changes in instrument properties. The integrated intensity defined as... 

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