What is the most common way of doing a chemical analysis of urine in a physicians office lab?

2.2.4 Stimulant analysis in urine

Urine analysis for illegal drugs is increasingly performed in forensic laboratories (especially in Japan). Gas chromatography–mass spectrometry (GC–MS) is extensively used because of its versatility and reliability. By way of sample preparation for GC analysis, conventional liquid–liquid extraction has a widespread use, but it is not only laborious but also environmentally unfriendly due to the consumption of considerable amounts of organic solvents. Therefore, microintegration of the sample preparation procedure is required.

Conventional procedures and corresponding MUOs are illustrated in Figure 8 (Miyaguchi et al., 2006). Urine samples are mixed with organic solvent (1-Chlorobutane) and stimulants in urine are extracted. After phase separation, the organic solution is mixed with derivatization reagent (trifluoroacetic anhydride). Unreacted derivatization reagents were washed by extracting with water. The washed organic solution was collected in a vial, and the concentration was determined by GC–MS. These conventional processes are easily dissolved to unit operations and converted to corresponding MUOs. The MUOs can be integrated to microchips by CFCP as shown in Figure 9. The conventional procedures can be simplified by the multiphase microflow network. The sample preparation time was decreased from several hours to 5 min, and total analysis time including GC–MS is below 20 min. In addition, just 100 µl of sample and reagent are required. These features will open on-site and precise urine analysis in near future.

Analysis of Urine

As with blood, urine analysis is used in clinical studies, and the relative concentrations of various ionic species are of great importance in both disease diagnostic and drug metabolism studies. For example, IC is used to determine urine oxalate concentrations. Urinary oxalate levels are an important parameter in urolithiasis research (kidney stones). Other anions that can be determined in urine using IC include phosphate, sulfate, bromide, citrate, nitrate, nitrite, and thiosulfate. As with blood and serum samples, both ultrafiltration and centrifugation are often used as sample cleanup steps.

Interesting applications include the use of IC coupled with ICP-MS detection for the determination of anionic arsenic species in urine resulting from occupational and dietary exposure. Species include urinary arsenate, arsenite, dimethylarsinic acid, and methylarsonic acid, and are separated using a hydrophilic anion exchange resin with a weak acid eluent. Studies have also been carried out using IC and ion interaction liquid chromatography to determine human urinary thiocyanate concentrations and relate concentrations found to levels of smoking. Thiocyanate is the main metabolic product of cyanide inhaled with cigarette smoke. Fig. 6 shows overlaid ion chromatograms of a smoker’s urine sample and the same sample spiked with thiocyanate. The chromatograms shown were obtained using ion interaction chromatography, utilizing a short reversed-phase column and a tetrabutylammonium chloride and methanol eluent. Detection was carried out using direct UV absorbance at 230 nm.

Glucose

The first rapid tests in urine analysis were carried out in the 1940s by adding tablets to urine samples. The test for sugar was refined in the Clinitest reagent tablets (Ames Co., Elkhart, IN). They are an ingenious adaptation of the alkaline copper reduction test in self-heating tablet form. Each tablet contains copper sulfate, sodium carbonate, and citric acid. Sodium carbonate and citric acid form an effervescent couple, which facilitates the rapid dissolution of the tablet and generates a little heat. Much more heat is liberated by the dissolution of sodium hydroxide and its partial neutralization by citric acid. In the alkaline medium, the sugar reduces the blue copper(II) sulfate solution to reddish insoluble copper(I) oxide. The carbon dioxide displaces the air above the reaction and prevents reoxidation of the copper(I) oxide during the test. The color of the mixture indicates the proportion of sugar in urine.

The Clinistix (Ames Co.) is an enzymatic glucose test based on the activity of the enzyme glucose oxidase that uses dry-reagent chemical technology. A firm plastic strip, to which a stiff absorbent cellulose area is affixed, is impregnated with a buffered mixture of glucose oxidase, peroxidase, and o-tolidine. In the first stage of the reaction, glucose is oxidized by atmospheric oxygen in the presence of glucose oxidase to gluconic acid and hydrogen peroxide, while in the second stage hydrogen peroxide/peroxidase oxidizes o-tolidine to a blue quinoidal product.

In another dry-reagent configuration in Diasti (Ames Co.) the o-tolidine in the second stage of the reaction is replaced by potassium iodide, which is oxidized in the presence of peroxidase to form free iodine. Newer test strips contain hexokinase in place of glucose oxidase. A very sensitive spot test for Benedict-positive compounds uses 2,2′-bicinchoninate as a chromogen. This test is ∼ 10,000 times more sensitive than the classical Benedict test.

Several companies are now offering plastic strips with eight or nine separate reagent areas affixed that fulfill in only 1 min the function of a routine urine analysis laboratory. These include N-Multistix and Hema-Combistix (Ames Co.), the Combur-9-Test, BMD Chemstrips, and BM 33071 glucose pad (Boehringer Mannheim), and the Rapignost (Hoechst AG).

To eliminate interpersonnel variations in interpretation of the dipstick colors, simple reflectance scanning instruments may be used. The Ames Clinitek Auto 200, Glucometer II, and Seralyzer, the Urotron L R System, Reflotron, Rapignost Total Screen L, Reflolux II and Accu-Check II (Boebringer Mannheim), the Glucoscan 3000 (Lifescan, Inc., Mountain View, CA), the Super Action Analyzer SA 4220 (Kyoto Daiichi, Kogaku), the Cobas Bio Analyzer (BCL, Lewes, UK), the Y Si 23 A analyzer (Clandon Scientific, Aldershot, UK), and the Cheme-Trics Analyzer (Technicon, Tarrytown, NY) are all reflectance measuring instruments that irradiate the dipstick with polychromatic light and measure the reflected radiation.

1.2 The need for multidimensional GC

Whether a sample is a solid (e.g., soil collected from an environmental petroleum spill), a liquid (e.g., urine analysis for doping control), or a gas (e.g., exhaled air for medical diagnosis), there are at least two layers of complexity that need to be taken into consideration when performing any chromatographic analysis. The first level of complexity involves the extraction of the analytes of interest from the sample matrix. A blood sample, for instance, would never be directly injected into a GC or an LC instrument because the extraneous matter in the sample matrix would seriously compromise the analysis of the target analytes in addition to creating some cleanup problems for the instrument itself. However, even when proper sample preparation has been performed, there are several factors that contribute to the second layer of complexity in any given analytical sample. These factors include (1) the number of target analytes to separate, (2) the relative properties of these analytes (chemical functionalities), (3) the relative concentrations of the target analytes in the sample, and (4) the presence of interferents in the sample (such as background from the stationary phase bleeding, impurities in the extraction solvent, or additional compounds that were extracted during the sample preparation). As a consequence of these factors, separations are prone to contain a number of coelutions due to the fact that there are either too many compounds to separate for the selected column (the peak capacity problem), too much of a difference in concentrations between trace analytes and high concentration compounds in the sample (the dynamic range problem), or too much of a range in the properties of the target analytes in a sample (the general elution problem). Giddings has reported on the mismatch that exists between the dimensionality of the separation system and the dimensionality of the sample and the effects that this mismatch creates on the crowding of peaks in a chromatogram [14].

An illustration of the utility of multidimensional separations is given in Fig. 1.1 through the concept of the GC chemical space. Similarly to the periodic table of elements, the chemical space is an organizing principle for the representation of the structural diversity that exists in the organic chemistry universe. In the chemical space, each molecule is placed at coordinates that correspond to measurable properties such as size, molecular weight, density, lipophilicity, charge, flexibility, rigidity, hydrogen bond capacity, etc. [15]. Visualization of the chemical space is typically limited to three-dimensional plots even though there a many more dimensions of information available for each molecule. The proper selection of the visualization axes can reveal useful trends between similar molecules, and such plots are currently being investigated in the world of pharmaceutical drug design as a predictor of toxicity prior to the synthetic work to be achieved in the laboratory [16,17].

In Fig. 1.1A, we define the GC chemical space in terms of the following three “principal components”: volatility, polarity, and molecular weight. Volatility is the primary separation mechanism for GC. This separation mechanism is based on the volatility differences that exist between the components of a sample, which can be captured by parameters such as boiling point or Kovats/Van den dool retention index values [18–20]. In Fig. 1.1A, the volatility axis is represented in terms of retention index values on a nonpolar stationary phase. The range between C1 alkane (value: 100) and C70 alkane (value: 7000) is likely to contain the vast majority of all volatilizable compounds.

Polarity separation is the second most frequently adopted mechanism in GC next to volatility. Polarity separations are resulted from several interactions that include hydrogen bonding, electrostatic dipole, and ionic or covalent bond formation. Metrics of polarity include parameters such as the octanol/water coefficient or the specific retention index (ΔI) values which have been used to determine the relative polarity character of stationary phases in GC [21–23]. ΔI is obtained by subtracting the retention index of a compound on a nonpolar stationary phase from the retention index of the same compound on a polar stationary phase. Relatively nonpolar compounds (like 1-decene) have retention index values of 985 and 1047 on nonpolar and polar stationary phases, respectively, which results in a ΔI value of 62. Compounds on the other end of the polarity spectrum (like diethylene glycol) have ΔI values over 1000. The range provided in Fig. 1.1A captures the vast majority of compounds amenable to GC analysis.

Molecular weight is selected as a third parameter because it defines the range of molecules that belong to the GC separation domain and also provides a connection to mass spectrometry (MS) detection which is viewed as the most important detector for separation science technologies (most GC/MS instruments provide a mass range between 0 and 1000 atomic mass units). The NIST database contains approximately 100,000 distinct organic chemicals [24] with information that can be cataloged in the GC chemical space, so it is clear that this information cube is well populated.

No chemical sample contains all of these compounds at any given time, and the goal of GC analytical separations is typically performed on a much smaller subset, which is represented in Fig. 1.1B by a randomly chosen mixture containing 60 compounds. Conventional 1D GC analysis is analogous to sending a linear probe through the GC chemical space and projecting the properties of the compounds onto the line, as shown in Fig. 1.1C. The analysis shows that, even though occupying distinct coordinates in the GC cube, a number of these compounds end up projecting in the same spot on the line, which leads to coelutions as can be seen in the “projected chromatogram” shown in Fig. 1.1C. This projected chromatogram displays 29 peaks, of which only 16 peaks are single compounds. The 13 peaks that are the result of projected coelutions account for 44 of the 60 compounds in the sample. Even though other projection lines can be found in this sample that may result in fewer coelutions, it is evident that the likelihood of resolving a significantly higher percentage of compounds in this sample using a linear probe is low due to the relative positions of these compounds in the chemical space.

Comprehensive two-dimensional GC analyses are analogous to sending a plane in the GC chemical space, as shown in Fig. 1.1D. The additional amount of space afforded by the plane allows for a significantly higher number of resolved peaks in the analytical run, and in this particular sample 57 of the 60 sample compounds (95%) are fully resolved, with only 3 partial coelutions (which are highlighted in the bidimensional projection plot in Fig. 1.1D). It is important to point out that while this bidimensional approach does not guarantee this drastic effect of a resolution enhancement for any given sample, it does adequately demonstrate the substantial improvement in resolution power from the single probe approach. It is also worth noting that, for the sake of simplicity, we have limited our illustration to the case of sample components with identical (or very similar) concentrations. It is clear that concentration differences in a sample (which impacts the size of the dots in the GC chemical space) also play a role in the number of coelutions that can result from the projections, but the overall conclusions with regard to the resolution gains that are made with multidimensional GC are still valid.

Exposure and Exposure Monitoring

Exposure monitoring is difficult to perform, but will usually manifest as symptomology associated with sodium fluoroacetate toxicity. The primary route of exposure is via the oral route and will appear in 0.5–3 h following ingestion. Confirmation of sodium fluoroacetate is accomplished by urine analysis to detect exposure. This would be particularly advantageous in individuals who have been exposed at subtoxic doses. The first symptoms will be abdominal discomfort, nausea, vomiting, and possibility of abdominal bloating. As the toxic effect proceeds, the affected individual will begin to sweat and show signs of central nervous system (CNS) effects such as confusion and agitation. Dermal exposure can be toxic, but usually manifests as signs of surface irritation. Due to the nature of sodium fluoroacetate, any organ system that has high-energy demands could be susceptible to the actions of sodium fluoroacetate. Of primary concern are workers in plants which manufacture and/or process sodium fluoroacetate.

3.06.10 Conclusion

The fact that urine can indicate some diseases has been known for thousands of years. The process of urine excretion is very well understood now. Today researchers are not content with the visualized results provided by simple urine test strips. Laboratory medicine scientists try to extend the usefulness of this easily accessible specimen and to unveil the ‘hidden’ biomarkers in urine samples for clinical diagnosis, drug control, and environment exposure assessment.

Sophisticated analytical methods such as HPLC-MS/MS, GC/MS, real-time PCR, etc. are frequently used for urine analysis. These modern analytical techniques generally provide good sensitivity, specificity, and accuracy. The sampling and sample treatment procedures are major contributors to the overall analytical data quality. To improve the analytical reproducibility and reliability, careful urine sampling and sample pretreatment are required.

Appropriate protocols for the collection, handling, and treatment vary with the target analytes and the purpose of urine analysis. Therefore, this chapter does not attempt to offer a single ‘standard protocol’ for urine sampling; instead, it provides information on the types of urine samples, urine collection, sample preservation, and sample treatment methods for different analytical purposes. Although established protocols have been commonly used in clinical laboratories for routine urine analysis, there is continued need to develop procedures for urine sample collection, handling, and treatment that are meaningful and reliable for more sophisticated analyses and exploratory studies, such as genomic, proteomic, and metabolomic analyses.

Urine

The abundance and noninvasive sampling of urine make it another suitable biofluid for clinical analysis. However, the elevated salt concentration in urine complicates an MS analysis. On the other hand, protein or lipid interferences are almost always absent. Urine is chemically complex and therefore contains valuable clinical information. It consists of metabolic waste products that are formed from the substances present in food, environmental contaminants, microbial byproducts in addition to other substances such as drugs and metabolites.47,48 The MS platforms used in urine analysis (urinalysis) include LC-MS/MS, GC-MS, and ICP-MS.47 The LC systems include HPLC as well as ultra-high-performance liquid chromatography.47,49 Polar analytes are readily separated using hydrophilic interaction chromatography (HILIC) columns.10 Direct infusion ESI-MS analysis of urine specimens can be achieved following dilution or SPE steps since these steps reduce the ion suppression caused by the high salt content in unprocessed urine. Additionally, calibration techniques such as stable isotope dilution (SID) and standard addition can be used to minimize the negative effects of ion suppression on the analytical results.50 Urine filtration and kidney excretion rate in addition to the total urine volume determine the concentration of chemical substances present within the urine sample.51 This makes interpretation of urine analysis results challenging. However, the composition variability can be offset by measuring the ratios of one constituent to another (such as the urinary testosterone-to-epitestosterone ratio).52

4 Future perspectives

Integrated paper-based sensing platforms, which include all steps in an analytical process chain, have the potential to serve as powerful tools for diagnostic applications. We analysed tailor-made solutions for different the samples, sampling methods as well as the investigated biomarkers. The paper-based technologies for the analysis of samples collected in an invasive manner are already matured and a many commercial products are nowadays available. With the exception of urine analysis, systems for the testing of samples taken in a non-invasive way are rather new developments and show great potential for further research and subsequent translation into industry. In the academic field, we see paper-based solutions coming up, which prepare the steps towards the integration of a detection methodology, novel (non-)invasive samples or extend theses platforms for the analysis of biomarkers, which require complex sample preparation such as nucleic acid testing. While paper-based technologies compete with other more matured technologies in some fields of application like the analysis cellular components, we identified great potential for the development of integrated paper-based platforms in other fields, where almost no commercial products are available. Despite their great potential for diagnostic applications and beyond, the applicability of integrated paper-based sensors should be carefully considered depending on the specific application scenario. In our opinion, hybrid approaches combining paper-based elements with other materials and novel technologies is the solution for creating the next generation of powerful integrated paper-based sensing devices.

3.09.8.4 Interpretation, False-Positive and False-Negative Results

Some screening programs introduced MS/MS as a pilot program to determine incidence of the screened disorders, appropriate analyte decision criteria, usually about 4 SD above the mean, and determine false-positive and false-negative rates. Decision criteria may differ depending on derivatized and nonderivatized methodologies. Because of variation in the volume of blood applied to the filter paper during collection, the volume of blood assayed by MS/MS may vary. The use of analyte ratios may improve sensitivity and reduce false-positive results.42 Because analyte concentrations may change during the first ten days of life, age-specific decision limits may be required to avoid false-negative and minimize false-positive results.43 Diagnostic confirmation for abnormal screen results may involve repeat acylcarnitine analysis, urine organic acid analysis, enzyme assay, and mutation analysis.

North Carolina established the first pilot program in 1997 and during this time almost 200 000 newborns were screened with an overall incidence of 1:4300 for disorders detected by MS/MS. The incidence of disorders proved to be higher than expected, indicating that disorders may not always cause a severe phenotype or present later in life with a different clinical phenotype. Identification of six false-negative results led to improved algorithms for defining normal and abnormal results and its implementation would have detected three of the six newborns.43

One of the continuing challenges of MS/MS analysis is the determination of appropriate decision criteria to define normal and abnormal results. The sensitivity and specificity of MS/MS is >99%, but the positive predictive value (PPV), defined as the likelihood that a newborn with an analyte value above the defined limit has the disorder, is as low as 10% for some analytes. This means that 1 out every 10 cases identified as positive on the newborn screen will be true positive while 9 will be a false positive. Factors contributing to the low PPV include low-birth-weight infants, total parenteral nutrition, nutritional supplementation with medium chain triglyceride (MCT) formula, and use of medications, including carnitine therapy and antibiotics containing pivalic acid derivatives. Maternal factors may also cause false-positive results. These include maternal vitamin B12 deficiency and maternal metabolic disorders.39

5.4 Excretion

PAH metabolites and their conjugates are predominantly excreted via the feces and to a lesser extent in the urine. Conjugates excreted in the bile can be hydrolyzed by enzymes in the gut flora and reabsorbed. It can be inferred from available data on total body burdens in humans that PAH do not persist for long periods of time in the body and that turnover is rapid. This excludes those PAH moieties that become covalently bound to tissue constituents, in particular to nucleic acids, and are not removed by repair. The excretion of urinary metabolites is a method used to access internal human exposure of PAH [120,121]. A number of researchers have reported the detection of PAH metabolites in human urine after exposure by inhalation [122,123]. Usually the metabolite used in urine analysis for the determination of concentration of excretion is 1-hydroxypyrene [76], 1- and 3-hydroxychrysene have also been used [124]. In several studies conducted with human subjects, some interesting conclusions were drawn. First, smokers had higher level of urinary 1-hydroxypyrene concentration than nonsmokers. Second, the level of urinary 1-hydroxypyrene in the electrode plant workers correlated inversely with age [76].

For studies performed on laboratory animals, it was discovered that the excretion of benzo(a)pyrene metabolites following low level of inhalation exposure is more rapid in rats [82–85] than in dogs and monkeys [125]. In humans, elimination of 1-hydroxypyrene has been reported after some volunteers ingested food with high PAH content [89]. Similar results have also been reported for laboratory animals [124].

There are sufficient data to show that PAH are equally excreted following dermal exposure. A study on some patients with psoriasis that were treated with coal tar covering on their skin for 3 weeks show that 1-hydroxypyrene tremendously increased during the period but declined afterward perhaps as the skin healed and became less permeable [126]. However, in the study on automobile repair workers who used mineral oils and were exposed to high concentration of PAH showed that exposure to PAH through dermal contact with those who used engine oil is low since no significant difference was recorded in the 1-hydroxypyrene urinary level of the workers and those of control mineral oil [127]. For studies involving laboratory animals, elimination of PAH following dermal exposure was rather high in concentration [128,129].