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Internal standards minimal number

Another GC method, isotope dilution GC-MS, involves the addition of an isotopomer of the analyte of interest to the sampling manifold (e.g., see Bandy et al., 1993 and Blomquist et al., 1993). In the case of S02, where the ambient S02 consists mainly of K 0 and 32S, S02 containing the 34S isotope is used. This labeled S02 at mass 66 is used as internal standard and has a number of additional advantages such as minimizing the loss of the analyte in the sampling system (Bandy et al., 1993). The air with the added isotopomer is trapped cryogenically and then sampled into a GC-MS for analysis. [Pg.585]

Toraya s WPPD approach is quite similar to the Rietveld method it requires knowledge of the chemical composition of the individual phases (mass absorption coefficients of phases of the sample), and their unit cell parameters from indexing. The benefit of this method is that it does not require the structural model required by the Rietveld method. Furthermore, if the quality of the crystallographic structure is poor and contains disordered pharmaceutical or poorly refined solvent molecules, quantification by the WPPD approach will be unbiased by an inadequate structural model, in contrast to the Rietveld method. If an appropriate internal standard of known quantity is introduced to the sample, the method can be applied to determine the amorphous phase composition as well as the crystalline components.9 The Rietveld method uses structural-based parameters such as atomic coordinates and atomic site occupancies are required for the calculation of the structure factor, in addition to the parameters refined by the WPPD method of Toraya. The additional complexity of the Rietveld method affords a greater amount of information to be extracted from the data set, due to the increased number of refinable parameters. Furthermore, the method is commonly referred to as a standardless method, since the structural model serves the role of a standard crystalline phase. It is generally best to minimize the effect of preferred orientation through sample preparation. In certain instances models of its influence on the powder pattern can be used to improve the refinement.12... [Pg.297]

In quantitative mass spectrometry, the signal intensity depends not only on the amount of sample, but also on a number of other variables such as the ionization yield, focusing of the ion beam, and the amplification factor of the detector. As it is very difficult to keep these parameters constant over the whole period of analysis, nearly all quantitative applications of MS are based on a comparison of the ion current obtained from the component of interest, with the ion current obtained from a standard. In quantitative SIM this can be accomplished either by the continuous admission of a reference sample at a constant rate, concurrently with the sample under investigation, or by the use of an internal standard (IS) which is added to the sample prior to MS analysis (Halpern, 1981). The choice of this IS is of primary importance in the design of a new assay and was subject to some controversy in the late 1970s (Claeys et al., 1977 Lee and Millard, 1975 Millard, 1978b Self, 1979). Ideally, an IS should compensate for all possible losses during sample isolation, purification, derivatization, and separation steps and at the same time minimize variances due to the measurement process. In practice, the... [Pg.113]

A better way to minimize the effects of this ion suppression is to have the luxury of a stable-label internal standard. The stable-label internal standard has the same structure as the analyte molecule, but certain atoms in the molecule will be replaced by nonradioactive isotopes, thus giving the stable-label compound a different molecular mass, but virtually identical properties in every other way. This stable-label internal standard will extract, chromato-graphically elute, and ionize in the same ways as the analyte. It will be distinguishable by mlz in parent and, possibly, daughter ions depending on the position(s) of the isotopic label. Unfortunately, stable-label internal standards are not available for most early-phase drug discovery work because of the rapid time scale and the large number of compounds involved. [Pg.205]

Gratuze [49] recommended dividing the elements into several groups to reduce analysis time and minimize problems of fractionation that can occur as the laser ablates deeper into the sample. In this approach, major elements are measured in the first group of elements, and then one of these elements is selected to serve as the internal standard for subsequent groups. If line scans rather than spot ablations are used, then all elements can be collected simultaneously. Also, with time-of-flight (TOF) instruments (see below), analysis time does not increase with the number of elements. Therefore, the total time can be as short as a fraction of a second. [Pg.832]

LC-MS/MS instrnment parameters are shown in Table 3. Compound specific parameters are shown in Table 4. The acquisition file is divided into separate functions in which the number of SRM transitions monitored is minimized. This provides enhanced sensitivity since the mass spectrometer does not scan the SRM transitions for every compound during the entire run. One isotopically labeled compound is chosen as internal standard for every function. [Pg.35]

In Section 13.3.2, the importance of the mass levels of internal standards used for quantification is extensively discussed. In fact, the number of internal standards used for quantification of lipid species of a class is equally critical. In this section, a minimal number of internal standards that should be used for quantification of the species of a class by different approaches are discussed. In summary, the number of internal standards that should be used really depends on the number of the variables present in the employed approach. [Pg.347]

TABLE 15.1 Summary of Variables Present in the Methods and Their Required Minimal Number of Internal Standards for Quantification of Individual Species of a Polar Lipid Class... [Pg.348]

Platforms Variables Minimal Number of Internal Standards... [Pg.348]

Taken together, the minimal number of internal standards that should be used for accurate quantification is varied from method to method, largely depending on the existence of the variables in each method. Table 15.1 summarizes the easily recognizable variables present in each method and therefore the minimal number of internal standards necessary for the methods. As aforementioned, some alternative approaches could be used to reduce the minimal number of internal standards for quantification. It should be pointed out that any method employing a number of internal standards much less than the variables present in the method is unlikely able to provide accurate quantification, but it can still be used for relative comparison between the samples. If this is the case, it is advisable that the investigators should not overstate the results as quantitative. [Pg.348]

It should be noted that the costs of calibration standards, reference materials, chemicals, solutions, and acids are also something you have to plan for, but will not be used in this evaluation as they are not considered instrument-running costs. However, they are also required to carry out a complete assessment of each of the four techniques. For example, in ICP-MS, multielement standards are generally less expensive than purchasing the same number of single-element standards. In flame AA, it is fairly common to use iouization buffers to minimize the effects of easily ionizable elements. In ETA, matrix modifiers are widely used to change the volatility of analyte or matrix elements. Whereas in ICP-OES and ICP-MS, internal standards are used in the majority of analyses, especially if the sample matrices are different from the calibration standards. [Pg.296]

Figure 1 The course of energy minimization of a DNA duplex with different choices of coordinates. The rate of convergence is monitored by the decrease of the RMSD from the final local minimum structure, which was very similar in all three cases, with the number of gradient calls. The RMSD was normalized by its initial value. CC, IC, and SG stand for Cartesian coordinates, 3N internal coordinates, and standard geometry, respectively. Figure 1 The course of energy minimization of a DNA duplex with different choices of coordinates. The rate of convergence is monitored by the decrease of the RMSD from the final local minimum structure, which was very similar in all three cases, with the number of gradient calls. The RMSD was normalized by its initial value. CC, IC, and SG stand for Cartesian coordinates, 3N internal coordinates, and standard geometry, respectively.

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