Daniel P. Cardinali, MD, PhD

• Department of Physiology, Faculty of Medicine,
• University of Buenos Aires, Buenos Aires, Argentina

In the case of Verapamil (Scheme 1) arthritis in the knee at young age buy medrol 4 mg with mastercard, the molecular weight of the compound is 420 Da arthritis pain doterra medrol 16mg free shipping, indicating an even number of nitrogen atoms in the molecule rheumatoid arthritis early onset quality 4mg medrol. The exchange of hydrogen for deuterium in organic molecules has been used in mass spectrometry for structural studies in both solution phase and gas phase baking soda arthritis relief cheap medrol 4mg. This method measures the difference in molecular weight of a compound before and after the deuterium exchange to determine the exchangeable hydrogens in a molecule for structural elucidations arthritis medicine buy medrol american express. For example arthritis neck fusion 4mg medrol free shipping, one can determine the number of labile hydrogen atoms from the mass shift X of [M + H+] in H2O to [M + D+] in D2O as X - 1. This method can enable some degree of H/D exchange without change of chromatographic separation. However, back-exchange can occur and contribute to incomplete exchange due to the presence of H2O in solvents or inadequate amounts of D2O. The change of chromatographic retention time due to the use of deuterated mobile phases should not be an issue because of the use of mass identifications. This approach provides accurate measurements of exchangeable hydrogens in a molecule to assist structural elucidation (examples will be presented in later section on identification of drug metabolites). Traditional accurate mass measurements are carried out in a magnetic sector mass spectrometer, requiring relatively large quantities of materials. Internal calibration is based on mixing one or several internal standards or calibrants of known molecular weight with the analyte and then using the known masses to calibrate the mass measurements of unknowns that coexist in the sample mixture. A mass measurement accuracy of 102 ppm is required to distinguish these elemental compositions. Thus, an unequivocal elemental composition of a compound can be obtained with sufficient high mass measurement accuracy. The calculation is based on the valences of elements involved, as shown in equation (7-1). The prominent abundant fragment ions are the most stable fragments that tend to be formed. The fragmentation processes also depend on the stability of the transition states by which the ions are produced. Many of the fragment ions observed in the product-ion spectra are formed by collision-induced heterolytic cleavage. In this case, the driving force for the fragmentation of an ion is dependent on the stabilities of the resulting ion and the radical species relative to the energy of the initial ionic species. For instance, the formation of stable product ions, including acylium ion, benzylic ion, and allylic carbonium ion, are able to promote homolytic cleavage. It is possible to derive structural information from the fragmentation pattern in a spectrum. The appearance of prominent peaks at certain mass numbers is empirically correlated with certain structural features. For example, the mass spectrum of an aromatic compound is usually dominated by a peak at m/z 91, corresponding to the tropylium ion. Structural information can also be obtained from the differences between the masses of two peaks in a spectrum. In addition, the knowledge of the principles governing the mode of fragmentation of ions makes it possible to confirm the structure assigned to a compound. This information is often used to determine the juxtaposition of structural fragments and thus to distinguish between isomeric substances. Reasonable guesses can be made as to which fragment ions to be expected in a mass spectrum if the isomeric substances are known. The fragmentation pattern of Florfenicol is characterized by an unusual feature of a most abundant peak occurring at odd mass, that is, m/z 241. To assess the quality of a combinatorial chemistry library, it is essential to determine the purity and quantity of the expected products. Commercial software, developed by instrument manufacturers, has made possible the unattended and rapid analysis of tens of thousands of individual components of a specific library. They used one of the nine channels to introduce reference standard as the lock mass to calibrate the instrument. The mass accuracies were found to be better than 5 and 10 ppm for 50% and 80% of the samples, respectively, from a single batch analysis of 960 samples [79]. A well-established method for drug discovery is the utilization of a biological assay to screen a large library of small organic molecules for their ability to bind target biopolymers. This step serves to denature the target, thereby dissociating the previously bound small molecules from the complex. The unbound small molecules are directly introduced into a high-resolution mass spectrometer for analysis. Often, impurities are synthetic by-products, starting materials, or degradation products. Drug regulatory agencies require the purity of a pharmaceutical to be fully defined. This is important to ensure that the pharmacological and toxicological effects are truly those of the drug substances and not due to the impurities. The impurities in pharmaceuticals are mainly formed during the synthetic process from starting materials, intermediates, and by-products. These impurities, however, are likely to contain components that affect the purity of the final manufactured pharmaceutical. Byproducts are often generated during synthesis and are one of the major sources of pharmaceutical impurities. The identification of the by-products often allows the Development Operations to refine the manufacturing process to minimize impurities and, thus, to maximize yield. The main limitation associated with this approach is that relatively large sample quantities are needed for analysis, and the process can be very labor-intense. In certain cases, if the impurities are found at very low levels in the drug substance, extraction procedures are used to concentrate them to detectable levels. The protonated molecular ions ([M + H+]) of the impurities A, D, E, F, G were found to be at m/z 392, 339, 324, 482, and 558, respectively. The base peak at m/z 305 might arise from the neutral loss of a 2-vinylamino-ethanol. Both have a base peak at m/z 88 which was produced when an N-(2-hydroxyethyl) aminoethyl group was cleaved from the molecule. Further studies suggested that impurities D and E are photo-decomposition products of DuP 941[87]. The degradation profiles are critical to the safety and potency assessment of the drug candidate for clinical trials. The degradation products usually arise from the ingredients used in dosage formulation and/or in the process of formulation where temperature, humidity, and light may all play a role. The degradants can be generated from hydrolysis, oxidation, adduct formation, dimerization, rearrangement, and often the combination of these processes. These methods exposed drug candidates to forced degradation conditions such as acid, base, heat, oxidation, and exposure to light. A successful identification of the degradation products can help formulation scientists to understand the degradation mechanism of drug candidate and improve the clinical formulation development. The same group demonstrated that the similar procedure could be applied to obtain the structural information of the degradation products of paclitaxel (Taxol) [89]. This approach drastically reduced the time required for isolation and purification of substantial quantities of material and expedited the identification process. There has been substantial increase in both the variety and the number of newly synthesized drug candidates in the discovery stage. Therefore, significant resources were invested in developing high-throughput analytical methods to support in vivo studies. The radioactivity method is also limited by the requirement of expensive radiolabeled compounds, though it generally provides sufficient sensitivity for the determinations. The reference compound was a structural analog of ketotifen and was used to increase the precision of the assay. The calibration plasma samples, fortified with the reference compound, were prepared at seven concentrations, ranging from 0. Statistical Analysis of Back-Calculated Normalized Ketotifen Concentrations of the Calibration Standards in Human Plasma Concentration (ng/mL) 0. However, in order to accelerate the drug discovery cycle, it is critical to develop rapid and efficient analytical method to support the needs for high-throughput screening. The product ion at m/z 495 (C27H31N2O7) was formed in the collision cell after cleavage of the sulfur bond and ester binding at C-11 [103]. Deviations from the mean calculated concentrations over three runs were between -5. With this on-line automated quantitation method, the calibration curves were found to be linear with a correlation coefficient better than 0. One common matrix effect is ion suppression due to co-eluting components that can affect the ionization efficiency of the analyte of interest. Many researchers have investigated a variety of methods for the control of the matrix effects. They found that the switching from an analogous to the isotopically labeled internal standard significantly improved the accuracy and precision of the assay by reducing the matrix effect [115]. This was probably due to the assumption that the isotopically labeled internal standard generally co-elutes with the analyte of interest, and it would experience the same extent of matrix effect as the analyte. Korfmacher and co-workers [108, 116] illustrated that exogenous (outside) material could be the cause of matrix suppression. Generally, the nonpolar exogenous material leaching out from the plastic tubes used to store the plasma samples eluted late in the chromatographic run. If the analytes and internal standards co-eluted with this suppression agent, their responses would be significantly reduced. Thus, it needs to be evaluated during a validation or prior to the analysis of human plasma samples. The identification of metabolites may reveal the metabolically labile portions of a molecule in a particular drug series. This information can be used by the synthetic chemists to synthesize compounds that are less susceptible to metabolism and, consequently, have a lower elimination rate and a longer half-life. In general, drugs are metabolized to more polar, hydrophilic entities, thereby facilitating their elimination from the body. The analysis involved the use of the product-ion spectra of compound A and 14C-labeled compound A as the structural templates for the identification of metabolite structures. A comparison of the product-ion spectrum of compound A with that of the 14Clabeled compound A suggested that the fragments at m/z 231, 215, 203, 191, and 175 were associated with the trifluoromethoxy phenyl moiety, whereas the fragments at m/z 184, 172, 159, 131, 91, and 56 were associated with the phenyl piperidine moiety. The signal at m/z 91 was outside the calibrated mass range resulting in a larger error. Source: Reprinted from reference 131, with permission of the American Society for Pharmacology and Experimental Therapeutics. Other metabolites, which might be the intermediates for formation of the keto acid, were also observed in the radiochromatogram of rat plasma (spectrum not shown) [131]. It is generally accepted that toxicities can stem from drug bioactivation in vivo, thus identifying the potential toxic metabolites is crucial in the lead optimization process [108, 121, 127, 132]. For example, the formation of acyl glucuronide conjugate forced the withdrawal of four marketed drugs due to hepatotoxicity [134]. Since this thermal deoxygenation is unique to N-oxide metabolites, it can also be used to differentiate N-oxides from other hydroxylated metabolites. The determination of the number of exchangeable hydrogen atoms in a structure can provide additional information for structural characterization, such as the differentiation between N- or S-oxide formation and hydroxylation in drug metabolism studies. This suggested that M1 and M2 might be oxidation metabolites of promethazine-that is, addition of oxygen or a hydroxyl group to the phenothiazine. This revealed that M1 had no exchangeable hydrogen atom in its structure, which ruled out the possibility of the hydroxyl structure. On the other hand, M2 had one exchangeable hydrogen atom, and thus it was assumed to be a hydroxylated metabolite. Bycroft, Fast atom bombardment mass spectrometry of bleomycin A2 and B2 and their metal complexes, Biochemi. Rudenauer, Secondary Ion Mass Spectrometry: Basic Concepts, Instrumental Aspects, Applications and Trends, John Wiley & Sons, New York, 1986. Hillenkamp, Matrix-assisted ultraviolet laser desorption of non-volatile compounds, Int. Skurat, Capillary system for introducing liquid mixtures into an analytical mass spectrometer, Z. McLafferty, Liquid chromatography/mass spectrometry system providing continuous monitoring with nanogram sensitivity, J. Cottrell, A continuous-flow sample probe for fast atom bombardment mass spectrometry, Anal. Goto, Direct coupling of micro highperformance liquid chromatography with fast atom bombardment mass spectrometry, J.

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Although these ions cause the complicating of the mass spectra arthritis medication celebrex buy cheap medrol 4 mg, they were also found to be useful for the confirmation of the molecular ion of an analyte of interest arthritis pain relief products buy discount medrol 16mg online. The isotopic pattern of a molecular ion peak provides valuable chemical information and can be used to determine the formula of the molecule arthritis in the fingers exercises purchase medrol cheap. Most of the common elements encountered in organic molecules have more than one isotope arthritis pain weather medrol 16mg discount, except fluorine science diet arthritis dog food order medrol 4mg without a prescription, iodine arthritis in dogs injections cheap medrol online visa, and phosphorus (Table 7-4). One example is for chlorine, which has two isotopes of 35 Da and 37 Da with a characteristic isotopic ratio of 3: 1. The isotopic pattern may complicate the molecular weight assignment; on the other hand, it will also provide valuable reference for recognizing the type and number of element in a molecule. The characteristic patterns resulting from multiple isotopic contributions of the chlorine, bromine, and sulfur isotopes are shown in Table 7-5. Isotopic Abundances for Ions Containing Different Numbers of Sulfur, Chlorine, and Bromine Atoms Number of Cl Atoms 100 97. The isotopic intensity pattern is in good agreement with that of two chlorine atoms (Table 7-5), due to the ions C27H31O635Cl2, C27H31O635Cl37Cl, and C27H31O637Cl2. The characteristic isotopic patterns resulting from combinations of the isotope peaks can be used to ascertain elemental composition of the corresponding ion. If the nominal molecular weight of an analyte appears to be an even mass number, the compound contains an even number of nitrogen atoms (or no nitrogen atoms). On the other hand, if the nominal molecular weight of an analyte appears to be an odd mass number, the compound contains an odd number of nitrogen atoms. This so-called "Nitrogen Rule" is very useful for determining the nitrogen content of an unknown compound. Iribarne, Field-induced ion evaporation from liquid surfaces at atmospheric pressure, J. Shkurov, Ion extraction from solutions at atmospheric pressure-a method for mass-spectrometric analysis of bioorganic substances, Dokl. Kebarle, A brief overview of the present status of the mechanisms involved in electrospray mass spectrometry, J. Stillwell, New picogram detection system based on a mass spectrometer with an external ionization source at atmospheric pressure, Anal. Browner, Monodisperse aerosol generation interface for combining liquid chromatography with mass spectroscopy, Anal. Livingston, the production of high speed light ions without the use of high voltages, Phys. Leuthold, Triple quadrupole linear ion trap mass spectrometer for the analysis of small molecules and macromolecules, J. Cook, Protonation in electrospray mass spectrometry: Wrongway-round or right-way-round Kebarle, Electrospray-ion spray: A comparison of mechanisms and performance, Anal. Zenobi, Quantitative determination of noncovalent binding interactions using soft ionization mass spectrometry, Int. Kebarle, Effect of the conductivity of the electrosprayed solution on the electrospray current. Kebarle, Investigations of the electrospray interface for liquid chromatography/mass spectrometry, Anal. Van Dorsselaer, Correlation between solvation energies and electrospray mass spectrometric response factors. Study by electrospray mass spectrometry of supramolecular complexes in thermodynamic equilibrium in solution, J. Lambert, Exact mass measurement of product ions for the structural confirmation and identification of unknown compounds using a quadrupole time-of-flight spectrometer: A simplified approach using combined tandem mass spectrometric functions, Rapid Commun. Bateman, Accurate mass liquid chromatography/mass spectrometry on quadrupole orthogonal acceleration timeof-flight mass analyzers using switching between separate sample and reference sprays. Luijten, Identification of an N-(hydroxysulfonyl)oxy metabolite using in vitro microorganism screening, high-resolution and tandem electrospray ionization mass spectrometry, Rapid Commun. Gross, Charge-remote fragmentation: An account of research on mechanisms and applications, Int. Adams, Charge-remote fragmentations: analytical applications and fundamental studies, Mass Spectrom. Hartwig, Handbook of Combinatorial Chemistry, Volume 1: Drugs, Catalysts, Materials, John Wiley & Sons, New York, 2002. Hogan, High-throughput characterization of combinatorial libraries generated by parallel synthesis, Anal. Yan, Parallel highthroughput accurate mass measurement using a nine-channel multiplexed electrospray liquid chromatography ultraviolet time-of-flight mass spectrometry system, Rapid Commun. Eyler, Exact mass measurements using a 7 tesla fourier transform ion cyclotron resonance mass spectrometer in a good laboratory practices-regulated environment, J. Senko, Analysis of combinatorial libraries using electrospray Fourier transform ion cyclotron resonance mass spectrometry, Rapid Commun. Armstrong, A review of high-throughput screening approaches for drug discovery, Am. Oldenburg, Current and future trends in high throughput screening for drug discovery, Annu. Lee, Predictive strategy for the rapid structure elucidation of drug degradants, J. Gross, Accurate mass measurements by Fourier transfor mass spectrometry, Mass Spectrom. Floriano, Quantitative determination of Eteinascidin 743 in human plasma by miniaturized highperformance liquid chromatography coupled with electrospray ionization tandem mass spectrometry, J. Bourgogne, Quantitative high-throughput analysis of drugs in biological matrices by mass spectrometry, Mass Spectrom. Korfmacher, Rapid determination of pharmacokinetic properties of new chemical entities: In vivo approaches, Comb. Beschke, Fully-automated assay by liquid chromatography for routine drug monitoring in body fluids-method development with biological samples, J. A new chromatograph for pharmacokinetic drug monitoring by direct injection of body fluids, J. Wang, Investigation of matrix effects in bioanalytical high-performance liquid chromatography/tandem mass spectrometric assays: Application to drug discovery, Rapid Commun. Hop, Applications of quadrupole-time-of-flight mass spectrometry to facilitate metabolite identification, Am. Korfmacher, Lead optimization strategies as part of a drug metabolism environment, Curr. Auriola, Liquid chromatography/atmospheric pressure ionization-mass spectrometry in drug metabolism studies, J. Baillie, Drug-protein adducts: An industry perspective on minimizing the potential for drug bioactivation in drug discovery and development, Chem. Raab, Identification of metabolites of a substance P (neurokinin 1 receptor) antagonist in rat hepatocytes and rat plasma, Drug Metab. Baillie, Minimizing the potential for metabolic activation as an integral part of drug design, Curr. Bor, Timing of new black box warnings and withdrawals for prescription medications, J. An enzyme catalyzing the conversion of 4-nitroquinoline1-oxide to 4-hydroxyaminoquinoline-1-oxide in rat liver and hepatomas, Cancer Res. Kiese, the biochemical production of ferrihemoglobin-forming derivatives from aromatic amines, and mechanisms of ferrihemoglobin formation, Pharmacol. Chowdhury, Liquid chromatography/mass spectrometry methods for distinguishing N-oxides from hydroxylated compounds, Anal. Chiu, Use of online hydrogen/deuterium exchange to facilitate metabolite identification, Rapid Commun. Biemann, Mass Spectrometry: Organic Chemical Applications, McGraw-Hill, New York, 1962. It is very important to understand the aim of analysis and the requirements for a particular method to be developed. General method development considerations that apply to all reversedphase methods are discussed in Section 8. These include properties of the analyte, detector, mobile phase, stationary phase, and gradient considerations. Building upon this knowledge, strategies for method development for target analytes in which the structure is known and not known are given as general guidelines. This material is reinforced with several method development case studies emphasizing the approaches used and the shortcomings that were encountered during the method development continuum. Also, a method development flow chart for gradient separations is provided in Section 8. The chromatographer needs to understand the aim of analysis in order to make judicious choices prior to the commencement of method development and the implications it may have on the final method that is developed. The following should be considered: method development time, the maximum run time for analysis, the number of samples expected per week, the complexity of the mixture, the structure of the main analyte (physicochemical properties), possible degradation pathways. For example, a fast method is needed to monitor reaction conversion of two components. However, a more complex method would be needed for stability-indicating purposes where multiple degradation products, synthetic by-products, and excipient peaks need to be resolved from the active pharmaceutical ingredient. The latter are raw materials in which some part of the raw material structure is incorporated into the final structure of the drug substance. For the raw materials, usually an identification test and concentration of the reagent suffices although the purity of these materials is sometimes also deemed as a necessity. To ensure the quality of the key raw materials, the level and type of impurities present in these materials need to be determined and appropriate specifications need to be set. Note that the impurities may carry forward in the downstream chemistry and/or may react to form new synthetic by-products. Different lots from the same manufacturer and/or lots of key raw materials from different manufacturers are usually tested. In the following example, the importance of determining the quality of the key raw material is highlighted. The starting material that is used is 3,4,5-trimethoxy benzaldehyde (a key raw material). Depending on the quality of this key raw material, the impurities from this starting material may further react in the subsequent synthetic steps (downstream chemistry) at the benzaldehyde functionality to produce undesired synthetic by-products. Both these synthetic by-products were presumed to come from the starting key raw material 3,4,5trimethoxybenzaldehyde. This would include determining the purity of the key raw material with a defined method and relating the purity of the key raw material from different lots/manufacturers to the quality of the final drug substance. Methods that monitor reaction conversion should ensure the resolution of all solvents and in-process impurities from the reactants and the desired intermediate. The goal here is to monitor product A going to product B-in essence, measuring the disappearance of A or completion of the reaction if reagent A is used in excess. Also, the concentration of product B may be needed as well as the purity of product B to control any undesired by-products. It must be determined how long the reaction should proceed in order to form the desired intermediate in good yield and for how long the intermediate is stable in solution prior to going to the next step (hold point stability). These reaction monitoring analyses should be fast because the reaction time scales may be in the order of minutes to hours. In-line flow injection analysis or spectroscopic methods are sometimes used to monitor reactions (reaction conversion) that are on the minute time scale and for reactions that involve hazardous materials because by the time the samples are analyzed by an off-line chromatographic method, the reaction has gone to completion and/or undesired by-products may have been formed. It is advantageous to have short methods to analyze these reaction conversion samples.

Dynamic transfer of the analyte molecules between mobile phase and adsorbent surface in the presence of secondary equilibria effects is also only part of the processes responsible for the analyte retention on the column rheumatoid arthritis joint changes purchase medrol with mastercard. These processes just outline a complex picture that chromatographic theory should be able to describe can arthritis in dogs cause fever purchase medrol 4 mg on-line. Kinetic aspect of chromatographic zone migration is responsible for the band broadening arthritis fingers popping order medrol 16mg with visa, and the thermodynamic aspect is responsible for the analyte retention in the column arthritis pain in hands order medrol 4mg free shipping. From the analytical point of view arthritis in fingers home remedies buy medrol 16 mg, kinetic factors determine the width of chromatographic peak whereas the thermodynamic factors determine peak position on the chromatogram rheumatoid arthritis diet coke cheap medrol online master card. Both aspects are equally important, and successful separation could be achieved either by optimization of band broadening (efficiency) or by variation of the peak positions on the chromatogram (selectivity). On the other hand, analyte retention or selectivity is mainly dependent on the competitive intermolecular interactions and are influenced by eluent type, composition, temperature, and other variables which allow functional variation. Retention factor is convenient because it is independent on the column dimensions and mobilephase flow rate. Note that all other chromatographic conditions significantly affect retention factor. Efficiency is the measure of the degree of peak dispersion in a particular column; as such, it is essentially the characteristic of the column. Efficiency is expressed in the number of theoretical plates (N) calculated as t N = 16 R w 2 (2-2) where tR is the analyte retention time and w is the peak width at the baseline. Selectivity is the ability of chromatographic system to discriminate two different analytes. This parameter has essentially the sense of the height equivalent to the theoretical plate and could be denoted as H, so we get H= 2 L (2-8) Several different processes lead to the band-spreading phenomena in the column which include: multipath effect; molecular diffusion; displacement in the porous beds; secondary equilibria; and others. Each of these processes introduces its own degree of variance toward the overall band-spreading process. Usually these processes are assumed to be independent; and based on the fundamental statistical law, overall band-spreading (variance) is equal to the sum of the variances for each independent process: 2 = i2 tot (2-9) In the further discussion we assume the total variance in all cases. In the form of equation (2-8) the definition of H is exactly identical to the plate height as it evolved from the distillation theory and was brought to chromatography by Martin and Synge [2]. Since we considered symmetrical bandbroadening of a Gaussian shape, we can use Gaussian function to relate its standard deviation to more easily measurable quantities. This distance is equal to four standard deviations, and the final equation for efficiency will be t N = 16 r wb 2 (2-14) Another convenient determination for N is by using the peak width at the halfheight. On the other hand, geometry of the packing material and uniformity and density of the column packing are the main factors defining the efficiency of particular column. There is no clear fundamental relationship between the particle diameter and the expected column efficiency, but phenomenologically an increase of the efficiency can be expected with the decrease of the particle diameter, since the difference between the average size of the pores in the particles of the packing material and the effective size of interparticle pores decreases, which leads to the more uniform flow inside and around the particles. The experimental dependence of the theoretical plate height on the flow velocity for columns packed with same type of particles of different average diameter. Three terms of the above equation essentially represent three different processes that contribute to the overall chromatographic band-broadening. A-represents multipath effect or eddy diffusion B-represents molecular diffusion C-represents mass transfer the multipath effect is a flow-independent term, which defines the ability of different molecules to travel through the porous media with paths of different length. The molecular diffusion term is inversely proportional to the flow rate, which means that the slower the flow rate, the longer component stays in the column and the molecular diffusion process has more time to broaden the peak. The mass-transfer term is proportional to the flow rate, which means that the faster the flow, the greater the band-broadening. In theory there is an optimum flow rate that allows obtaining the highest efficiency (the lower theoretical plate height). For columns packed with smaller particles, efficiency is not as adversely affected at faster flow rates, because the mass-transfer term is lower for these columns. Essentially, this means that retention equilibrium is achieved much faster in these columns. However, the overall efficiency of the columns packed with smaller particles (<2 m) is not much higher compared to conventional columns with 3- to 5- particles. This small increase of the efficiency may only slightly improve the separation; however, the comparison of the run times at the same volumetric flow rates on both columns shows that the separation on the second column can be achieved five times faster. Therefore, the fastest possible separation requires that the maximum pressure allowed by the instrument be used, assuming that the resolution requirement can still be met. As a result, one wants to make the most of the pressure available by reducing the pressure drop across the column as much as possible. Shorter columns have lower pressure requirements, allowing to gain an advantage in speed. It must be kept in mind, however, that N will decrease as u increases (for particles 3 m), meaning that at faster velocities longer columns are necessary to give the required theoretical plates, thus generating greater operating pressures. From the practical point of view, in case of the lack of resolution for some specific separation there are generally two ways to improve it: Increase the efficiency, or increase the selectivity. At the same time, the increase of the column length leads to the increase of the flow resistance and backpressure, which limits the ability to further increase the column length. If we assume that the peak widths of two adjacent peaks are approximately equal, we can rewrite expression (2-18) in the form R= X 2 - X1 4 (2-21) For symmetrical chromatographic bands, this is the ratio of the distance between peaks maxima to the peak width. The distance between peak maxima is proportional to the distance of the chromatographic zone migration, and the peak width is proportional to the square root of this distance. At low selectivity to achieve the same resolution, one has to use a longer column to increase efficiency and consequently operate under higher-pressure conditions. Expression (2-17) predicts a linear increase of the backpressure with the increase of the flow rate, column length, and mobile phase viscosity. The decrease of the particle diameter, on the other hand, leads to the quadratic increase of the column backpressure. Unfortunately, the direct algebraic transformation of expression (2-19) into some form of functional dependence of R on k, and N is impossible. Knox and Thijssen were the first to independently propose the transformation based on the assumption of equal peak width (w2 = w1) and consideration of the retention of the first peak of the pair (k1). Purnell [7] suggested to center attention on the second peak of the pair, thus using the peak width of the second component as a base width (meaning that the width of the first peak is equal to the width of the second peak). This assumption leads to the following equation: k a - 1 N R = 2 k2 + 1 a 4 (2-23) Both equations do not give a real resolution value; also, the greater the distance between peaks, the higher the error. Said [6] suggests the use of average values instead of selection of the first or second primary peaks, which leads to the following expression for resolution: a - 1 k N R= a + 1 1 + k 2 (2-24) All these expressions give approximate values of resolution; also, the smaller the distance between target peaks in the chromatogram, the closer the values to the true resolution. Retention factor and selectivity are the parameters related to the analyte interaction with the stationary phase and reflect the thermodynamic properties of chromatographic system. Retention factor is calculated using expression (2-1) from the analyte retention time or retention volume and the total volume of the liquid in the column. Even if the analyte molecules do not interact with the column packing material, the analyte needs some time to pass through the column. The corresponding volume is either the void volume, the volume of the liquid phase in the column, or the dead volume. Analyte retention volume that exceeds the column void volume is essentially the volume of the mobile phase which had passed through the column while analyte molecules were retained by the packing material. To derive the relationship of the analyte retention with the thermodynamic properties of chromatographic system, the mechanism of the analyte behavior in the column should be determined. The first one is analyte partitioning between mobile and stationary phases, the second one is the adsorption of the analyte on the surface of nonpolar adsorbent, and the third one has been suggested by Knox and Pryde [11], where they assume the preferential adsorption of the organic mobile-phase modifier on the adsorbent surface followed by the analyte partitioning into this adsorbed layer. Partitioning is the first and probably the simplest model of the retention mechanism. It assumes the existence of two different phases (mobile and stationary) and instant equilibrium of the analyte partitioning between these phases. Simple phenomenological interpretation of the dynamic partitioning process was also introduced at about the same time. Probably, the most consistent and understandable description of this theory is given by C. It is then assumed that Rf could be considered as the fraction of time which a component spends in the mobile phase and by multiplying mobile-phase velocity on Rf the average component velocity in the column is obtained. Equation (2-30) describes the retention of the analyte, which undergoes only one process of ideal partitioning between well-defined mobile and stationary phases. In gas chromatography the analyte partitioning between mobile gas phase and stationary liquid phase is a real retention mechanism; also, phase parameters, such as volume, thickness, internal diameter, and so on, are well known and easily determined. The assumption that the retardation factor, Rf, which is a quantitative ratio, could be considered as the fraction of time that components spend in the mobile phase is not obvious either. The phenomenological description of the retention mechanism discussed above is only applicable for the system with single partitioning process and well-defined stationary and mobile phases. A more general method for the derivation of retention function is based on the solution of column mass balance [17]. The analyte in the column slice dx is considered to be in instantaneous thermodynamic equilibrium. To simplify the discussion and allow for the analytical solution of mass balance equation, the absence of the axial analyte dispersion is assumed. The following assumptions on the behavior of the chromatographic systems are made: 1. Molar volumes of the analyte and mobile-phase components are constant, and compressibility of the liquid phase is negligible. Adsorbent is rigid material impermeable for the analyte and mobilephase components. Adsorbent is characterized by its specific surface area and pore volume, which are evenly distributed axially and radially in the column. The column void volume, V0, is defined as the total volume of the liquid phase in the column and could be measured independently [18]. Total adsorbent surface area in the column, S, is determined as the product of the adsorbent mass and specific surface area. Mobilephase flow F in mL/min; analyte concentration c in mol/L; n is the analyte accumulation in the slice dx in mol; v is the mobile-phase volume in the slice dx expressed as V0/L, where L is the column length; s is the adsorbent surface area in the slice dx, expressed as S/L, where S is the total adsorbent area in the column. During the same time dt the amount of analyte leaving the zone dx could be expressed as F(c + dc)dt. The difference in the analyte amount entering zone dx and exiting it at the same time dt will be Fdcdt. The analyte accumulation in the zone dx could be expressed in the form of the gradient of the concentration along the column axis (x) c Fdcdc = - F dxdt x t (2-31) Equation (2-31) represents the analyte amount accumulated in the zone dx during the time dt. The analyte distribution function in the selected zone is the second half of the mass balance equation; the amount of analyte accumulated in zone dx should be equal to the amount distributed inside this zone. This distribution function is the key for the solution of equation (2-32), and the definition of this function essentially determines how chromatographic retention will be described. Further development of the mathematical description of the chromatographic process requires the definition of the analyte distribution function y(c), or essentially the introduction of the retention model (or mechanism). In this mechanism the analyte is distributed between the mobile and stationary phases, and phenomenological description of this process is given in Section 2. The Vm and Vs are the volume of the mobile and the volume of the stationary phases in the column, respectively. Instant equilibrium of the analyte distribution between mobile and stationary phases is assumed. For low analyte concentration the distribution function is assumed to be linear and its slope (derivative) is equal to the analyte distribution constant K. To be able to use this equation, we need to define (or independently determine) the volumes of these phases. Adsorption is a process of the analyte concentrational variation (positive or negative) at the interface as a result of the influence of the surface forces. Physical interface between contacting phases (solid adsorbent and liquid mobile phase) is not the same as its mathematical interpretation. The physical interface has certain thickness because the variation of the chemical potential can have very sharp change, but it could not have a break in its derivative at the transition point through the interface. In the adsorption model the column packing material is composed of solid porous particles with high surface area and is impermeable for the analyte and the eluent molecules. Adsorbent nonpermeability is an important condition, since it essentially states that all processes occurs in the liquid phase. Since adsorption is related to the adsorbent surface, it is possible to consider the analyte distribution between the whole liquid phase and the surface. Using surface concentrations and the Gibbs concept of excess adsorption [20], it is possible to describe the adsorption from binary mixtures without the definition of adsorbed phase volume. Determination of the total amount of the analyte adsorbed on the surface requires the definition of the volume where this accumulation is observed, usually called the adsorbed layer volume (Va). In chromatographic systems, adsorbents have large surface area, and even very small variation in the adsorbed layer thickness lead to a significant variation on the adsorbed layer volume. There is no uniform approach to the definition of this volume or adsorbed layer thickness in the literature [14, 21, 22]. Another approach to the expression of the analyte adsorbed on the surface is based on the consideration of the surface specific quantity which has been accumulated on the surface in excess to the equilibrium concentration of the same analyte in bulk solution. In a liquid binary solution, this accumulation is accompanied by the corresponding displacement of another component (solvent) from the surface region into the bulk solution. Excess adsorption G of a component in binary mixture is defined from a comparison of two static systems with the same liquid volume V0 and adsorbent surface area S. In the first system the adsorbent surface considered to be inert (does not exert any surface forces in the solution) and the total amount of analyte (component 2) will be n0 = V0c0. In the second system the adsorbent surface is active and component 2 is preferentially adsorbed; thus its amount in the bulk solution is decreased.

The clumping of the chromatin in these nuclei results in a distinctive dark arthritis anatomy definition purchase genuine medrol online, ropy pattern (solid black arrows) that leaves some areas white (dashed black arrows) arthritis equipment purchase 4mg medrol with amex. In the case of erythroblasts preparing to make hemoglobin rheumatoid arthritis essential oils discount 4mg medrol with mastercard, this is in the form of free ribosomes arthritis in the knee cure purchase cheapest medrol and medrol. The two cells indicated by the red arrow demonstrate good examples of clumps (black arrows) and white areas (dashed black arrows) arthritis in dogs today tonight buy medrol with a visa. Extreme chromatin condensation arthritis knots in fingers 4mg medrol sale, called pyknosis, is seen in late-stage erythroblasts (green arrow). However, this cell has begun to synthesize granules, which initially accumulate in the region of the Golgi, resulting in a prominent patch of pink (black arrow) in the formerly exclusively blue cytoplasm. Gradually, the cytoplasm changes from blue to pink (cells B through D) as the cell matures. The erythrocyte precursor cytoplasm is pure blue (red arrow) at early stages; as the cells mature (green arrow), eosinophilic hemoglobin is added, resulting in a dull purple or gray color. This process, termed hematopoiesis or hemopoiesis, is driven by a self-replicating hematopoietic stem cell that is a common precursor for all blood cells. This cell, and its early progeny, have the histologic appearance of lymphocytes, so they are not identified routinely. Later stages take on specific characteristics that place these cells in identifiable stages. These characteristics include cytoplasmic granules (azurophilic, eosinophilic, basophilic, neutrophilic), the presence or absence of nucleoli, nuclear shape, chromatin pattern (fine or clumped), and cytoplasmic staining (basophilic or eosinophilic). Recognition of these cellular features makes it possible to identify specific developmental stages in blood cell maturation, which will be discussed in upcoming chapters. The products of granulocyte maturation are mature cells that have granules and other products that are used in the immune response. Therefore, as these cells mature, they transition from cells that are actively synthesizing these products to cells that have accumulated these products but are synthetically less active. The nucleus takes on the appearance of a less active cell; it loses its nucleoli, the chromatin becomes clumped, and the nucleus becomes smaller and segmented. Helpful Hint Understanding this principle will help mentally organize the stages of granulocyte production, which will aid in learning. However, during the later stages of hematopoiesis, these cells transition through histologically identifiable stages. This is especially true for the granulocytes, which will be the main focus of this chapter. Monocytes, lymphocytes, and dendritic cells also go through developmental stages as they mature. These stages do not have clear histologically identifiable features, so they will be mentioned only briefly in the chapters discussing lymphatic tissues and organs. Helpful Hint A full understanding of the cells discussed in the next two chapters requires the ability to recognize the cellular features discussed in the previous chapter: cytoplasmic granules, nucleoli, nuclear shape, chromatin pattern, and cytoplasmic basophilia. If some uncertainty exists in recognizing these features, it is best to review them before proceeding. They can be distinguished from each other because the promyelocyte has nonspecific (azurophilic, primary) granules, while the myeloblast does not. At these early stages, it cannot be determined in routine smears whether the myeloblast or promyelocyte is committed to the neutrophilic, eosinophilic, or basophilic cell lineage. Boxed cells are progenitors of granulocytes and platelets, cell types covered in this chapter. Therefore, many cells have features consistent with two stages, and some cells do not appear to belong to any stage at all. This is not unusual, particularly in slides prepared of peripheral blood from patients with leukemia. Note that the presence of increased white blood cells in the bone marrow may compromise production of red blood cells and platelets, so patients with leukemia often have associated anemia or bleeding disorders. One type, called acute promyelocytic leukemia, results in an increase in the number of promyelocytes. These cells have abnormal azurophilic granules, often in the form of elongated structures called Auer rods, which enable fairly rapid diagnosis. Helpful Hint As mentioned, the myeloblast and promyelocyte cannot be placed into a specific granulocyte lineage with routine hematologic stains. Myelocytes (and later stages), on the other hand, contain specific granules, so proper identification includes the type of granulocyte. However, the nucleus is smaller with clumpy chromatin and no nucleoli, so it is definitely a myelocyte. The most recognizable feature that differentiates these stages, however, is nuclear shape. The eosinophil and basophil series of cells also undergo similar maturation of their nuclei. These cells are not as common, however, and their large granules usually obstruct the nucleus. In addition, the cell expands its basophilic cytoplasm, which will be "shed" to produce platelets. The resulting megakaryocytes are large cells, with extensive eosinophilic cytoplasm, often foamy, with granules and a multilobed nucleus. The cytoplasm shows some remaining basophilia, but eosinophilic regions are visible as well. Their size will undoubtedly be the single most important way to differentiate them from cells in the white blood cell series. If you look closely, however, you will see cytoplasmic eosinophilia, particularly near the bottom of the cell. This is due to the production of neutrophilic specific granules, which is a feature of the myelocyte stage and not the promyelocyte. This occurrence is referred to as "nuclear-cytoplasmic mismatch"-a feature often seen in leukemias. Clinical Correlate As discussed in the chapter on blood, a complete blood count and differential blood cell count ("differential") are used routinely in clinical practice. However, these immature cells may be released from the bone marrow in larger numbers before they are fully mature to assist in fighting infections. A left shift is commonly seen in cells of the neutrophil series and typically signifies a bacterial infection. The numerous nuclei observed throughout the slide represent different stages of blood cell development, but staging is not routinely accomplished in such material because the magnification is insufficient and because the features of each cell are obscured by both the superimposition of cells in the thickness of a routine section and the proximity of cells to one another. Despite this, in this figure three megakaryocytes are easily identified (outlined): really large cells with multilobed nuclei and eosinophilic cytoplasm. Once the megakaryocyte is formed, it resides in the marrow next to the sinuses (capillaries in the marrow), where it "sheds" portions of its cytoplasm and plasma membrane into the bloodstream. Later stages of granulocyte maturation include cells with characteristics that can be visualized by routine hematologic staining (Wright stain). The first identifiable stage, the myeloblast, is a large cell with multiple nucleoli, fine chromatin, and basophilic cytoplasm that lacks granules. This cell enlarges and begins to generate azurophilic (nonspecific) granules, becoming a promyelocyte. From here, the cell begins to produce specific granules (neutrophilic, eosinophilic, basophilic). The production of specific granules occurs at the same time that nucleoli cease to be visible and the chromatin appears clumpy. The loss of nucleoli and appearance of specific granules mark the progression of the cell into the myelocyte stage. Continued maturation of these cells largely features changes in nuclear shape, from round (myelocyte) to indented (metamyelocyte) to horseshoe (band or stab) and, finally, to segmented (mature cell). Megakaryocytes generate platelets and are recognized in bone marrow as very large cells with a large, multilobed nucleus and abundant cytoplasm. The difference is very subtle; the typical proerythroblast has more intense cytoplasmic basophilia than a myeloblast does. However, in many cases it is difficult to distinguish the two with certainty on routine staining. However, the main concept that early precursors are "producers" that develop into a final product that contains functional proteins is consistent with granulocytes. The final cell, the erythrocyte, is filled with hemoglobin, a soluble cytosolic protein. As the cells mature, hemoglobin is produced, with a concomitant reduction in the number of ribosomes; therefore, maturing red blood cells will gradually become less basophilic and more eosinophilic. The resulting cell, which contains hemoglobin and a few ribosomes, is the reticulocyte that is released into the bloodstream. Nucleoli Proerythroblast Basophilic erythroblast Polychromatophilic erythroblast 20. This signifies that the cell has shut down ribosome production (which happens in the nucleoli) but still has plenty of ribosomes in the cytoplasm to maintain cytoplasmic basophilia. The mixture of hemoglobin (eosinophilia) and ribosomes (basophilia) in the cytoplasm produces a purple/gray color, which gives way to increasing eosinophilia as hemoglobin concentration increases and ribosomes are degraded. The reticulocyte still has a small number of ribosomes, so although it is fairly eosinophilic, it is tinged with a little basophilia. Recall that a lymphocyte has a small condensed nucleus, with a thin rim of blue cytoplasm. These cells can be distinguished because the basophilic erythroblast is larger, with a larger nucleus and a chromatin pattern that is clumpy but has clear areas within the nucleus. As the cell matures, nucleoli disappear and the nuclear chromatin gradually condenses. Synthesis of hemoglobin introduces eosinophilia to the cytoplasm; this and the loss of ribosomes cause the cytoplasm to transition from a basophilic to eosinophilic color as the cell matures. Although this tissue, by volume, is approximately half hematopoietic cells and half adipose, it is still considered red marrow due to its hematopoietic activity. Red blood cells function within the bloodstream, while white blood cells are largely active after they leave the blood and enter peripheral tissues and organs. However, specific lymphocytes called T lymphocytes (T cells) complete their maturation in the thymus before they are released as active cells. Bone marrow and thymus are the producers of blood cells and are the focus of this chapter. Subsequent chapters will examine tissues and organs of the lymphatic system and locations where white blood cells are active in fighting infections. Because these elements have a limited lifespan, bone marrow is a very mitotically active tissue. The bright pink tissue is bone (osseous tissue), including compact (black arrows) and spongy bone (blue arrows). Bone marrow (green arrows) occupies the marrow cavity of the shaft of long bones as well as the spaces between the spicules of spongy bone. Therefore, this is red marrow, which is highly cellular; most of these cells are developing red and white blood cells. What appear to be spaces (X) are specialized capillaries of the bone marrow, called sinusoids (sinuses). Bone marrow (green arrows), compact bone (black arrows), and spicules of spongy bone (blue arrows) are indicated. Xs indicated capillaries (sinusoids) of the bone marrow; yellow arrows indicate megakaryocytes. Yellow marrow is essentially adipose tissue and is identified as yellow marrow only by its location in a marrow compartment. As a person reaches adulthood, the marrow in the shafts of long bones loses hematopoietic activity and becomes yellow marrow. Blood cell production is maintained by the remaining red marrow in the epiphyseal regions of long bones and in flat bones. Under certain conditions, regions containing yellow marrow may become active red marrow again by growth of existing red marrow or seeding from circulating stem cells. Thymus Axillary lymph nodes Thoracic duct Spleen Cisterna chyli Intestinal lymph nodes Lymphatic pathways Lymph nodules in the ileum (Peyer patches) Inguinal lymph nodes Afferent peripheral lymphatics Vermiform appendix Bone marrow Video 21. This is a complicated and not well understood selection process, part of which includes removal of T cells that would bind to self-antigen if released into the general circulation. These pouches are spaces of oral cavity lined by epithelial cells that separate the oral cavity from the underlying connective tissue. The thymus develops from the right and left third pharyngeal pouches (light blue). Tissue from these pouches separate from the oral cavity, migrate into the neck, and come to lie anterior to the trachea, where they fuse into a single organ.

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