Title of Invention: METHODS OF QUANTIFYING N2-(1-CARBOXYETHYL)-2'-DEOXY-GUANOSINE (CEDG) AND SYNTHESIS OF OLIGONUCLEOTIDES CONTAINING CEDG Abstract: Methods of quantifying a N2-(1-carboxyethyl)-2′-deoxyguanosine (CEdG) levels in biological samples and comparing those levels to known normal levels can diagnose a number of metabolic disorders or complications associated therewith, including diabetes, its associated complications, and cancer. Methods can also determine whether therapies for disorders are effective by measuring CEdG levels before and after treatment. Measurement of CEdG levels is achieved by using liquid chromatography electrospray ionization tandem mass spectrometry. Detailed Description: PRIORITY CLAIM This application is a continuation of U.S. patent application Ser. No. 15/887,857, filed Feb. 2, 2018, issuing as U.S. Pat. No. 11,179,361, which is a continuation-in-part of U.S. patent application Ser. No. 15/859,188, filed Dec. 29, 2017, which is a continuation of U.S. patent application Ser. No. 14/536,299, filed Nov. 7, 2014, issued as U.S. Pat. No. 9,855,233, which is a continuation of U.S. patent application Ser. No. 13/308,433, filed Nov. 30, 2011, abandoned, which is a divisional of U.S. patent application Ser. No. 12/538,854, filed Aug. 10, 2009, abandoned, which claims priority to U.S. Provisional Application Ser. No. 61/087,393, filed Aug. 8, 2008, the contents of which are incorporated herein by reference in their entireties. GOVERNMENT INTEREST The present invention was made partially with government support under Grant Nos. P30 CA33572, and R01CA176611, awarded by National Institutes of Health. The government has certain rights in the present invention. SEQUENCE LISTING This application contains a Sequence Listing, which was submitted in ASCII format via EFS-Web, and is hereby incorporated by reference in its entirety. The ASCII copy, created on Nov. 11, 2021, is named SequenceListing.txt and is 1 KB in size. BACKGROUND Hyperglycemia increases circulating levels of glucose-derived α-oxoaldehydes such as methylglyoxal (MG) which react non-enzymatically with proteins, lipids, and nucleic acids to form AGEs, potentially modifying or inactivating their function. Unlike Amadori adducts such as HbA1c and fructosamine, which are formed reversibly in equilibrium with glucose, AGEs are typically irreversible and possess long lifetimes. Since CEdG is only known to be formed from the reaction of MG with dG, they may be considered stable surrogate biomarkers of MG exposure. MG has been shown to be significantly elevated in both type 1 and type 2 diabetes. Several endogenous sources of MG have been described including the non-enzymatic decomposition of glucose and its Amadori adducts, ketone body metabolism, and glycolysis. All of these processes are exacerbated by diabetes, and elevated circulating MG has not been clearly associated with any other diseases or environmental toxin exposure. Also, MG is a highly reactive electrophile and is present at micromolar levels in many foods and most living organisms. MG is a major environmental breakdown product of carbohydrates. MG is also generated biochemically during glycolysis via elimination of phosphate from the common enediol intermediate resulting from deprotonation of dihydroxyacetone phosphate and glyceraldehyde 3-phosphate. Additional endogenous sources of MG include the catabolism of threonine and the P450 mediated oxidation of ketone bodies and the oxidative breakdown of DNA and RNA under acidic conditions. MG is a probable mutagen in vivo. Methylglyoxal induces G>T and G>C transversions, as well as a large number (50%) of multibase deletions. Since 89% of the base substitution mutations are observed at guanosine, and N2-(1-carboxyethyl)-2′-deoxyguanosine (CEdG) is the predominant adduct formed from reaction of MG with DNA, this pattern of transversions arises from CEdG (as primer extension assays using oligonucleotide templates containing CEdG have evidenced). The presence of CEdG in DNA has also been shown to induce single-strand breaks, suggesting an alternative mechanism by which this adduct may contribute to genetic instability. Glycation results when a sugar, such as fructose or glucose, non-enzymatically links to a protein or lipid. Glycation typically impairs the function of the molecules to which it binds. Methylglyoxal reacts readily with nucleophilic moieties on proteins, lipids and DNA to produce covalent adducts known as advanced glycation end-products (AGEs). Protein AGEs are well characterized and have been proposed to play a role in the various pathologies associated with diabetes, cancer, aging, and Alzheimer's disease. The first clear correlation between abnormal levels of a protein-AGE and a human disease (diabetes) was described in 1969 for the hemoglobin A1c (HbA1c) adduct by Rahbar et al. Since then, HbA1c has become a commonly used biomarker for the diagnosis and treatment monitoring of diabetes.11-13 Accordingly, there is continued interest in the development of novel, more sensitive assays for the quantitative measurement of biomolecule-derived AGEs to complement and extend the clinical biomarker repertoire, as well as to assist in elucidating their role in pathology. Protein AGEs, formed from reactions of carbohydrate-derived α-oxoaldehydes such as methylglyoxal (MG) with amino acid nucleophiles, are elevated as a result of hyperglycemia and have been previously investigated as clinical biomarkers of glucose control and diabetic complications. Although there are numerous reports describing the correlation of various protein AGEs with hyperglycemia and diabetic complications, predictive power depends upon the exact combination of AGEs studied and the assay matrix (e.g. serum, collagen) examined. For example, protein AGEs in serum and collagen are also significantly elevated in obese/diabetic individuals and have been proposed as potential biomarkers of diabetic complications. In the Joslin Medalist study of patients with type 1 diabetes for 50 years, a specific combination of plasma protein AGEs was shown to be more accurate than HbA1c for the prediction of complications. However, it is difficult to compare data from various correlative studies on protein AGEs because different quantitative and semi-quantitative methods including gas chromatography (GC) and liquid chromatography mass spectrometry (LC-MS), high-performance liquid chromatography (HPLC), ELISA, and spectrofluorimetry have been used. Moreover, the biological matrix used for analysis appears to be critical as well, e.g., large variations in protein AGE levels have been reported in collagen calling into question the relevance of skin measurements for diabetic complications. No general consensus has emerged regarding which specific AGEs might be of optimal value for monitoring glucose control or predicting diabetic complications. Together with the lack of uniform methodology for measurement, this has made it difficult to standardize diagnostic endpoints. For these reasons, protein-AGE determination in the clinical setting has only seen limited use. Approximately a dozen protein-AGEs have been characterized and liquid chromatography tandem mass spectrometry (LC-MS/MS) methods have been described for their quantitative measurement. Choosing an appropriate protein-AGE biomarker for evaluating the glycation status of a particular target tissue or organ is complicated by unequal protein-AGE distributions across different tissues, varying adduct stabilities, and the limited availability of stable isotope standards for quantification. In spite of longstanding interest in the role of biopolymer glycation in human disease, no generally applicable method for the quantitative determination of CEdG has been described. A 32P post-labeling assay has been used to estimate endogenous levels of CEdG in human buccal epithelial cells of 2-3/107 nucleotides.28 However, although the post-labeling method offers potential advantages in sensitivity, a major drawback is that direct analyte verification is not possible. Moreover, post-labeling is prone to artifacts and false positives, and may lead to inaccurate estimation of adduct levels due to several factors including RNA contamination. An immunoaffinity-based method for the detection of CEdG using a polyclonal antibody coupled to a diode array HPLC platform has more recently been described by Schneider et al in 2006. This approach was used to provide the first demonstration of CEdG in human urine and cultured smooth muscle cells. In some cases, peak identity was confirmed by LC-MS/MS, but quantitation was not practical due to the imprecise nature of immunoaffinity chromatography. A monoclonal-based immunohistochemical detection method has also been reported and was used to demonstrate elevated levels of CEdG in aorta and kidney of diabetic patients relative to normal controls.31 However, antibody-based assays are primarily of value in qualitative and comparative determinations of adduct abundance. To date, there are no reliable quantitative methods for CEdG measurement, which is likely due to a lack of suitable isotopically enriched standards and other barriers to a reliable quantitative method. Such a method would be a substantial improvement in the art. SUMMARY In a first embodiment, AGEs, such as N2-(1-carboxyethyl)-2′-deoxyguanosine (CEdG) may be quantified in a biological sample using liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) for diagnosis, monitoring, and treatment of pathologies involving metabolic disorders, including abnormal glucose metabolism. Such pathologies include diabetes and diabetic complications including, but not limited to, microvascular and macrovascular complications—such as hypertension, stroke, cardiovascular diseases, neuropathy, nephropathy, and retinopathy; hyperosmolar hyperglycemic nonketotic syndrome (HHNS); ketoacidosis; foot and skin ulceration and damage, hearing impairment, Alzheimer's disease, as well as certain cancers, amongst other metabolic diseases or disorders. Quantification is achieved by a stable isotope dilution method using an internal standard. When the AGE is CEdG, the internal standard is 15N5-CEdG. The advantage of having two stereoisomers of CEdG that can be resolved and quantitated is that it allows for two independent measurements for the same condition, significantly enhancing the accuracy of the method. Detecting physiologically elevated or depressed AGE levels in a sample may indicate that the subject from which the sample was taken has a disease or disorder caused or indicated by such AGE levels. The quantification method allows for a precise determination of AGE amounts and thus, allows for sensitive determination of AGE levels compared to other samples from the same subject at the same time, other samples from the same subject at different time points, or other samples from other subjects, such as a person known not to be affected by a disease. For example, detecting elevated levels of CEdG in a person indicates predisposition to or the presence of hyperglycemia or diabetes. Reaction of double stranded DNA with MG or glucose in vitro produces primarily N2-(1-carboxyethyl)-2′-deoxyguanosine (CEdG) as a diastereomeric mixture (FIG. 1). The same type of sample may be used to compare between various AGE levels, such as a comparison between AGE levels in a first tissue sample and a second tissue sample. Alternatively, the AGE levels may be compared between various types of samples so long as the relative physiological normal level for each type of sample is known. In another embodiment, internal standards for other AGEs are created using the methods disclosed herein for synthesizing the internal standard of CEdG. Standards for MS are typically identical in structure to the intended analyte, but contain stable isotopes (15N, 13C, 18O)) in order to give a different mass to an otherwise chemically identical substance. The isotope behaves identically to the intended analyte, has the same retention on chromatography, undergoes the same chemistry, and is only distinguishable by mass. In a different embodiment, the quantification methods described herein may also be used to determine the effectiveness of a therapy, which may be a test compound or other protocol, intended to treat or ameliorate an AGE-related disease or disorder (a “therapeutically effective amount”). Before the therapy is administered, a first biological sample is taken. After the therapy has been administered, a second biological sample is taken. Additional biological samples may also be taken at other time points during and/or after the therapy. AGEs are quantified in the samples and the difference between AGE levels in the samples is measured. Other known statistical analysis, such as tests for statistical significance, may also be applied. If a successful therapy results in a reduction of the level of AGE and such reduction is noted after the administration of the therapy, it indicates that the therapy may be working for its intended purpose. If AGE levels in the sample are static or increased during the course of the therapy, it indicates that the therapy may not be working for its intended purpose of reducing AGE levels. If a successful therapy results in an increase of AGE levels with a treatment, the opposite analysis would apply: increases in AGE levels would indicate the therapy may be working, whereas static or decreased levels would indicate that the therapy may not be effective. Kits for quantifying AGE levels, such as CEdG levels, are also contemplated. Such kits facilitate the methods described herein may contain any of the following: standards such as 15N5-CEdG, tubes, labels, reagents such as buffer, and instructions for use. Another embodiment involves measuring urine samples in an animal model to monitor the dose dependency of LR-90 as it decreases CEdG levels in vivo. Yet another embodiment is measuring the effect of aromatase inhibitors on CEdG levels, and relatedly, on glycation status. CEdG levels are measured in a subject undergoing aromatase inhibitory therapy (AI) to determine the impact of AI on cognitive function and mental acuity. A method of measuring CEdG to predict chemosensitivity of tumors and to identify cancers that may be treated from targeting glyoxalase 1 (Glo1) and/or aldose reductase to restore chemosensitivity is also described. Tumors with elevated levels of CEdG are more sensitive to chemotherapy. Related methods of inducing production of CEdG or other AGE products in tumor cells or of administering CEdG to tumor cells to induce apoptosis and/or increased sensitivity to chemotherapy are also provided. The effectiveness of radiotherapy may also be tested by measuring CEdG in tumors. Also disclosed are methods of diagnosis, prognosis, or therapy of pathologies involving metabolic disorders such as diabetes and diabetic complications described above. The methods entail measuring the levels of one or more biomarkers such as CEdG in a biological sample from a patient, wherein an elevated level of the one or more biomarkers relative to the level of the biomarker in a control, healthy subject or to a preset threshold value indicating the status of the pathology or an elevated risk of the pathology. The methods of treating the pathology further include treating the patient who has an elevated level of the biomarker with one or more therapies. For example, the methods disclosed herein comprises administering a treatment for diabetes or diabetic complications to the subject who is determined to have the diabetic complication. The methods of prognosis further include treatment monitoring including comparing the levels of the biomarker before and after the treatment. In some embodiments, the pathology is diabetes, a diabetic complication, e.g., nephropathy, or cancer, and the biomarker is CEdG. In some embodiments, the methods disclosed herein comprise, after administering the treatment for diabetes or diabetic complications, determining whether the treatment is therapeutically effective by repeating the step(s) of measuring the levels of one or more biomarkers such as CEdG in a biological sample from a patient, wherein an elevated level of the one or more biomarkers relative to the level of the biomarker in a control, healthy subject or to a preset threshold value indicating the status of the pathology or an elevated risk of the pathology. In certain embodiments, the determination of whether the treatment is therapeutically effective can occur at any time after administration of treatment. Non-limiting examples include, taking a biological sample immediately after treatment, 1 hour after treatment, 2 hours after treatment, or after a regimen of a month, 6 months, or one year. A suitable treatment can be selected based on the particular diabetic complication. For example, various treatments for diabetic nephropathy are available, including for example, angiotensin-converting enzyme (ACE) inhibitors, such as captopril, enalapril, lisinopril, and ramipril, and angiotensin II receptor blockers (ARBs), such as cancesartan cilexetil, irbesartan, losartan potassium, and telmisartan. A novel synthesis of oligonucleotides containing site-specifically modified CEdG residues is shown in FIG. 16. Such synthesis facilitates experiments using CEdG, such as experiments that investigate the biological consequences of CEdG substitution in DNA and for serving as internal standards for assays measuring CEdG. These and other embodiments are further explained by reference to the detailed description. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1. The two CEdG diastereomers formed from reaction of MG with dG. FIG. 2. A representative HPLC chromatogram of the reaction of 15N5-dG with DL-glyceraldehyde. Peaks A and B correspond to the two diastereomers of 15N5-CEdG (R- and S-CEdG, respectively). FIG. 3. Full scan positive ion ESI-MS spectrum for 15N5-CEdG diastereomer peak A. FIG. 4. Time course product profiles of the reaction of dG and the A (R) and B (S) stereoisomers of CEdG with 1 M AcOH at 37° C. The inset shows the HPLC chromatogram of the reaction of CEdG-B at 450 min. FIG. 5. Quantitation of CEdG in normal (light grey) and diabetic (dark grey) Sprague-Dawley rats. Superscript a (“a”): Ordinate values represent ad libitum concentrations of the AGE inhibitor drug LR-90 (mg/L). *P<0.05 and **P<0.01 vs untreated diabetic animals (Bonferonni's test) (no asterisks). FIG. 6. LC-ESI-MS/MS measurements of CEdG diastereomers in calf thymus DNA subjected to various workup procedures. Hydrolyzed samples correspond to DNA treated with nuclease P1/alkaline phosphatase/phosphodiesterase. Calf thymus DNA samples were also reacted with proteinase K (Extracted) prior to hydrolysis. Levels of CEdG were measured in the presence or absence of carbonyl scavenger AG. FIG. 7. Reactions of carbonyl scavengers AG and D-P with MG yield isomeric aminotriazines (top) and 2-acylthiazolidine (bottom). FIGS. 8A-8C. UV spectra of stock solutions of unlabeled (FIG. 8A) and isotopically labeled CEdG diastereomers (FIGS. 8B-8C). FIG. 8A: UV spectra of CEdG(A(R))(solid line) and CEdG(B(S))(dotted line) with no isotopic labeling. Both samples were diluted 1:50; OD255(dG)=12,300 OD/M. For CEdG(A(R)), XX-49-A, 28.55 mL; diluted OD255=0.450; undiluted OD255=22.50; conc.=1.83 mM, 52.22 umol @ FW 338.30=17.67 mg. For CEdG(B(S)), XX-49-A, 40.61 mL; diluted OD255=0.327; undiluted OD255=16.35; conc.=1.33 mM, 53.98 umol @ FW 338.30=18.26 mg. FIG. 8B: 15N5-CEdG(A(R)); 2 μL stock diluted to 500; OD255=1.207. FIG. 8C: 15N5-CEdG(B(S)); 1 μL stock diluted to 500; OD255=0.883. FIG. 9. Proton (1H) NMR of CEdG(A(R)) isomer. The following parameters apply to the spectrum: transmitter freq: 399.806855 MHz; time domain size: 21340 points; width 5208.33 Hz=13.027115 ppm=0.244064 Hz/pt; number of scans: 512; freq. of 0 ppm: 399.804642 MHz; processed size: 65536 complex points; LB: 0.00; GB: 0.00. FIG. 10. Proton (1H)NMR of CEdG(B(S)) isomer. The following parameters apply to the spectrum: transmitter freq: 399.806855 MHz; time domain size: 21340 points; width 5208.33 Hz=13.027115 ppm=0.244064 Hz/pt; number of scans: 512; freq. of 0 ppm: 399.804643 MHz; processed size: 65536 complex points; LB: 0.500; GB: 0.00. FIG. 11. Carbon data: 13C NMR of CEdG(A(R)). The following parameters apply to the spectrum: transmitter freq: 100.541493 MHz; time domain size: 63750 points; width 24509.80 Hz=243.778000 ppm=0.384468 Hz/pt; number of scans: 12000; freq. of 0 ppm: 100.531015 MHz; processed size: 65536 complex points; LB: 0.00; GB: 0.00. FIG. 12. Carbon data:13C NMR of CEdG(B(S)). The following parameters apply to the spectrum: transmitter freq: 100.541493 MHz; time domain size: 63750 points; width 24509.80 Hz=243.778000 ppm=0.384468 Hz/pt; number of scans: 27000; freq. of 0 ppm: 100.531015 MHz; processed size: 65536 complex points; LB: 0.500; GB: 0.00. FIG. 13. MS2 and MS3 of sodiated CEdG(A(R)) parent ion obtained using the Thermo Finnigan LTQ-FT linear ion trap mass spectrometer, showing the expected molecular fragments for the isotopically enriched standards. FIGS. 14A and 14B. Product ion scans for CEdG(A(R)) (FIG. 14A) and 15N5-CEdG(A(R)) (FIG. 14B) at m/z 340 and 345, respectively, showing the daughter ions at m/z 224 and 229 monitored using a Micromass Quattro Ultima Triple Quadrupole Mass Spectrometer, showing the expected molecular fragments for the isotopically enriched standards. FIGS. 15A-15C. Observed isotopic distributions for 15N5-CEdG(A(R)) (FIG. 15A) and 15N5-CEdG(B(S)) and the calculated isotopic distribution for C13H1715N5NaO6 (FIG. 15B) The latter was calculated using the Molecular Weight Calculator, V. 6.38 (FIG. 15C). FIG. 16. Synthesis of oligonucleotides containing site-specifically modified CEdG. FIG. 17. Consistent elevation of CEdG in obese rats, nearly 10-fold in some examples, relative to lean controls. There is consistently more (S) isomer relative to (R) in biological samples from both rodents and humans. FIGS. 18A-18C. CEdG levels from tissue-extracted DNA in the liver (FIG. 18A), pancreas (FIG. 18B) and kidney (FIG. 18C) of Zucker rats, lean controls and Zucker rats treated with the glycation inhibitor LR-90. FIGS. 19A-19B. Measurement of urinary R-CEdG and S-CEdG isomers in post-menopausal women undergoing treatment with aromatase inhibitors. FIGS. 20A-20B. R-CEdG and S-CEdG distribution in human solid tumors and adjacent tissue in lung, breast and kidney cancers. FIGS. 21A-21B. Gender specific differences for CEdG and FPG. Each data point represents the average value of CEdG (FIG. 21A) or FPG (FIG. 21B) for individual mice. Neither CEdG nor FPG achieved a significant difference based on gender. FIGS. 22A-22B. LC-ESI-MS/MS chromatogram of (R,S)-CEdG. FIG. 22A. Representative ion chromatogram of (R,S)-CEdG in urine (top panel) and 15N5-(R,S)-CEdG isotopic standard (bottom panel). Mass transitions used for identification and quantification indicated in the inset. FIG. 22B. Structure of the DNA-AGE CEdG (m/z 340). Dashed arrow indicates the primary fragmentation giving rise to the mass transitions indicated in FIG. 22A. Asterisk (*) indicates the chiral center. FIGS. 23A-23C. CEdG is elevated as a result of hyperglycemia. CEdG was quantified as described above and time-averaged values (repeated measures analysis) were calculated for each individual animal. FIG. 23A. CEdG levels were compared between normoglycemic (n=22; FPG<200 mg/dL) and hyperglycemic (n=11; FPG 200 mg/dL) mice. Significance was determined using a non-parametric unpaired t-test. FIG. 23B. Mean CEdG levels were plotted for each animal and the median value was determined to be 17 pmol/24 h. FIG. 23C. Mean CEdG values grouped according to genotype, significance calculated as in FIG. 23A. FIG. 24. CEdG significantly increases over time in db/db mice. Individual CEdG measurements were plotted against the age of the mice at the time of collection. To determine differences over time between groups and individual animals, a linear mixed mode analysis was performed (see Table 5). This revealed a significant variation (p=0.0023) over time within the db/db animal population (red line), but not in the wt/db (green line) or wt (blue line) animals. Significant differences among animals within the db/db group were also observed. FIGS. 25A-25B. Correlation of CEdG with FPG and HbA1c. FIG. 25A. Average CEdG and FPG values for individual animals were determined using repeated measures analysis. Correlations were calculated with Spearman's coefficient (r=0.6621). FIG. 25B. Average CEdG and HbA1c calculated as in A, r=0.8016. FIG. 26. CEdG significantly correlates with HbA1c in humans. FIGS. 27A-27D. CEdG from tissue is elevated in hyperglycemic and Lepr mutant mice. DNA was isolated from pancreas, liver, colon, and kidney and analyzed for CEdG. CEdG values were averaged across tissues from individual mice and grouped according to glycemic status (FIG. 27A) or genotype (FIG. 27B). FIG. 27C. CEdG measurements from pancreas, liver, colon, and kidney from individual mice stratified by genotype. FIG. 27D. One-way ANOVA with Tukey's modification was used to analyze CEdG differences between genotypes (irrespective of tissue, last column) and between tissue (regardless of genotype, bottom row). †CEdG/106 dG. Significance values: *p≤0.05; **p≤0.01; ***p≤0.001; ****p≤0.0001. FIGS. 28A-28D. CEL and CML are elevated in urine of hyperglycemic mice and correlate with CEdG. FIG. 28A. Mean values of CEL and CML measured in urine from aged-matched hyperglycemic and normoglycemic wt (9), wt/db (9), and db/db (11) mice using LC-ESI-MS/MS. FPG was measured at the cessation of 24 h urine collection. Two-way ANOVA revealed a significant increase in CEL and CML in hyperglycemic mice (****p<0.0001). FIG. 28B. CML (n=32) and CEL (n=32) vs. FPG. No significant correlation was observed. CML, r=0.2458; CEL, r=0.2267. FIG. 28C. Plot of CML and CEL vs. CEdG for all mice; CML, r=0.7009 (****p<0.0001); CEL, r=0.4902 (**p=0.0044). FIG. 28D. CML (n=32) and CEL (n=32) vs. CEdG from hyperglycemic mice; CML, r=0.5589 (*p=0.0471); CEL, r=0.5805 (*p=0.0375). FIG. 29. CEdG significantly correlates with albumin alone. FIG. 30. CEdG significantly correlates with albumin when albumin was normalized to creatinine. FIGS. 31A-31B. Albumin alone (FIG. 31A) and albumin normalized to creatinine (FIG. 31B) were both elevated in Leprdb/db mice compared to Lepr+/db. DETAILED DESCRIPTION Quantitative measurement of AGEs is accomplished using mass spectrometry, such as LC-ESI-MS/MS and internal standards designed for each targeted AGE. Such measurements allow for precise determinations of AGE levels, including small or incremental changes in such levels. Various pathologies involving metabolic disorders such as diabetes and related complications and other diseases may be diagnosed by measuring N2-(1-carboxyethyl)-2′-deoxyguanosine (CEdG) levels alone or in conjunction with other AGEs in biological samples, including but not limited to urine, blood, plasma, serum, tissue (e.g. tumor tissue) samples. The CEdG levels from the biological sample are then compared to physiologically normal CEdG levels. Methods for further determining the efficacy of therapies or treatments applied to these pathologies comprise measuring the effect of the therapeutic has on the CEdG levels in a subject receiving it. Of the approximately 29 million people with diabetes in the United States, it is estimated that 30% are undiagnosed. Risk for developing diabetes associated complications increases with poor glycemic control. Therefore, identifying diabetic individuals earlier and more accurately remains an unmet clinical need. Delayed clinical intervention for diabetes increases the severity of microvascular complications (e.g., diabetic nephropathy, neuropathy, and retinopathy) and macrovascular complications (e.g., coronary artery disease, peripheral arterial disease, and stroke) as demonstrated by the Diabetes Control and Complications Trial (DCCT) and the subsequent long-term follow up study the Epidemiology of Diabetes Intervention and Complications (EDIC) trial.69,70 These studies demonstrated that frequent blood glucose measurements and intensive insulin therapy could significantly improve patient outcomes. However, such vigilant biomonitoring and therapeutic intervention is not a practical goal for the majority of patients with diabetes, and the development of improved diagnostic tools to identify patients most likely to benefit from intensive treatment is an ongoing challenge. Because of the inherent difficulties of accurate glucose monitoring, e.g., wide fluctuations in daily plasma levels, glucose instability, and variability in measurement methods and standards, validated long-term biomarkers of glycemic control have come into routine clinical practice. The primary example is hemoglobin A1c (HbA1c), the Amadori adduct of the N-terminal valine of the hemoglobin β-chain. Its measurement has since become the gold standard for the monitoring of glycemic control and more recently as a diagnostic index for diabetes. HbA1c measurement reflects the average glucose over ˜120 days, the mean lifetime of the erythrocyte. Although HbA1c levels 6.5% (48 mmol/mol) significantly correlate with diabetes, overreliance on HbA1c can lead to misdiagnosis in a significant percentage of the population. For example, the Finnish Diabetes Prevention Study showed that a diagnostic criteria of HbA1c 6.5% failed to identify ˜60% of patients with type 2 diabetes originally identified by two consecutive oral glucose tolerance tests. Although there is a linear relationship between mean blood glucose and HbA1c, ˜30% of patients with type 2 diabetes have HbA1c levels above or below values predicted from mean plasma glucose. Such individuals are classified as “high or low glycators” and consistently show these variations over time, suggesting an intrinsic biological origin of this phenomenon. The failure of HbA1c to invariably correlate with glycemic status has been attributed to a variety of factors that may influence HbA1c formation and persistence within erythrocytes. These include undiagnosed hemoglobinopathies, inter-individual variation in glucose transporter (GLUT) activity, erythrocyte turnover, and genetic differences attributed to ethnic background and other unidentified factors. Whatever the origin of the discrepancies between HbA1c measurement and standardized glucose tests, other potential biomarkers of glucose control should be developed to complement existing methods and refine our ability to more accurately diagnose and monitor diabetes. Novel biomarkers of metabolic diseases should complement existing clinical methodology by increasing diagnostic precision, particularly in patients difficult to identify as diabetic using common tests. The ability to accurately identify and monitor patients likely to become diabetic and to predict specific complications before patients become symptomatic remain significant challenges in diabetes care. For example, while HbA1c is an independent predictor of both mild and severe proliferative retinopathy, cardiovascular disease (CVD) is not clearly associated with HbA1c. Some groups have reported that deviations in measured HbA1c from values predicted from FPG can predict increased risk for retinopathy and nephropathy, while analogous models based on fructosamine measurement were reported to provide a more accurate algorithm for the prediction of nephropathy. In general, efforts to find improved diabetic biomarkers have often focused on glycation and protein AGEs rather than nucleic acid AGEs. Potential candidates for biomarkers of glycemia are DNA AGEs. The stability of DNA, its uniform cellular distribution, and its substantially longer lifetime relative to proteins suggests that DNA-AGE measurement could provide a more long-term assessment of glycemic control. In contrast to the multiplicity of amino acid AGEs described in humans, there are only two DNA-AGEs detectable in blood and urine; CEdG and a cyclic diol arising from direct addition of MG at N1, N2 of guanine (cMG-dG). In contrast to CEdG, whose stability in DNA and as a deoxynucleoside is comparable to 2′-deoxyguanosine, cMG-dG is significantly less stable and less suitable as a potential biomarker. Methods to detect DNA AGEs include 32P post-labeling, polyclonal antibody-based analysis, and LC-ESI-MS/MS. Of these methods, LC-ESI-MS/MS coupled with stable isotope dilution provides the most accurate quantification of CEdG. Using this approach, the first measurement of CEdG in a high-dose streptozotocin (STZ) rat model of type 1 diabetes demonstrated increased levels relative to normoglycemic controls. To further elucidate the physiological relevance of DNA-AGEs in type 2 models of diabetes, described herein are measurements of CEdG in Leprwt/wt (wt), Leprwt/db (wt/db), and Leprdb/db (db/db) mice, which provided a range of FPG from 70 to 978 mg/dL and HbA1c levels from 3-15% (9 to 140 mmol/mol). Mice with a Leprdb gene have an alternatively spliced variant of the leptin receptor, which is highly expressed in the hypothalamus and is resistant to the effects of the leptin hormone. This leads to the development of obesity, hyperglycemia, hyperlipidemia and other metabolic abnormalities within a few weeks of birth, which mimic the pathology found in type 2 diabetes. Heterozygous mice (wt/db) typically do not exhibit a gross diabetic phenotype; however, they exhibit several distinguishing metabolic traits relative to wt animals including a decreased rate of glucose oxidation and slower rates of catabolism. CEdG levels are measured using LC-ESI-MS/MS or other reliable means. CEdG levels from the sample are then compared to the levels in physiologically normal subjects. Methods for further determining the efficacy of therapies or treatments applied to various disorders comprise measuring the effect the therapeutic has on the CEdG levels in a subject receiving it. The subject having its AGE levels and/or the efficacy of treatment measured is preferably a mammal, such as a human. Thus, one method of quantifying one or more advanced glycation end products in a sample, comprises obtaining a biological sample from a subject; and performing LC-ESI-MS/MS assay on the sample using stable isotope dilution with an internal standard to determine AGE levels within a sample. When the AGE is CEdG, the internal standard is 15N5-CEdG. With CEdG quantities in hand, abnormal levels may indicate metabolic disorders or complications associated with these disorders such as diabetes and cancers. Upon detecting the levels, efficacies of various treatments may be determined using AGE levels as a marker for the success of the treatment. As shown in the working examples, CEdG excreted in the urine of wt, wt/db and db/db mice was measured over a period of 36 weeks and recorded contemporaneously with FPG and HbA1c. CEdG were significantly elevated in hyperglycemic compared to normoglycemic mice (FIG. 23A). Results revealed a positive correlation of urinary CEdG with FPG and HbA1c (FIG. 25). CEdG also positively correlated with the protein AGEs carboxymethyl and carboxyethyl lysine (CML and CEL, respectively) (FIG. 28). These data provide a rationale for applying CEdG measurement as a clinical tool for the diagnosis and management of metabolic diseases. DNA-AGEs likely enter circulation via DNA repair and/or degradation during cell turnover. CEdG remaining in genomic DNA poses significant hazards since it contributes to genomic instability, which may substantially increase the risk for certain cancers. This is particularly true of diabetic individuals as they have been reported to be compromised in DNA repair. The CEdG levels were examined in a subset of organs at risk for increased cancer incidence in metabolic disease, including pancreas, kidney, colon and liver; and the first measurement of DNA-AGEs in tissue from animal models of diabetes is described herein. This analysis revealed a significantly higher level of CEdG in organs isolated from hyperglycemic mice compared to normoglycemic controls (FIG. 27). As disclosed herein, since all nucleated cells contain DNA, and DNA has a longer lifetime than protein, measurement of the DNA-AGE CEdG may allow for more precise assessment of long term glycemic stress. The working examples demonstrate that a significant (17-fold) increase in the median value of urinary CEdG in animals with FPG≥200 mg/dL relative to normoglycemic controls. Moreover, consideration of CEdG values alone allowed for a prediction of hyperglycemia with >95% confidence. These observations are consistent with the data using a high dose STZ diabetic rat model, which demonstrated elevated CEdG levels in urine relative to non-diabetic animals. Significant increases in CEdG for both type 1 and 2 diabetic models suggest the direct influence of hyperglycemia on DNA-AGE formation, supported by the linear relationship of CEdG and FPG (FIG. 25A). In contrast to the narrow range of CEdG values observed for normoglycemic mice, values for the hyperglycemic animals were widely dispersed (FIG. 23A). This suggests that stratification of CEdG values may provide diagnostic information relevant to diabetes-related pathologies. For example, individuals in the highest quartile may be at the greatest risk for microvascular and macrovascular complications or cancers associated with metabolic disease. The highest quartile is predicted to be 60-80 nmol/24 hr. The second highest quartile 40 to 60 nmol/24 hr, the third highest quartile 20 to 40 nmol/24 hr and the lowest quartile 1 to 20 nmol/24 hr. This possibility will be more properly addressed in a clinical trial. The large increase in CEdG levels observed for the db/db group over time is striking. The age of the animal alone did not appear to make a substantial contribution, since increases in CEdG over time were insignificant in wt or wt/db mice (FIG. 24). This would suggest that increasing MG generation due to progressive diabetic pathology was the main contributing factor. Quantification of CEdG in tissue DNA revealed differences between wt and wt/db mice not apparent using the standard FPG or HbA1c markers. Organ data revealed a clear increase in CEdG between wt and wt/db mice when aggregate tissue CEdG measurements were considered (p<0.01, FIG. 27D), even though wt/db animals had FPG, HbA1c, and urinary CEdG values that were indistinguishable from wt (Table 4). The disparity between the CEdG in urine vs tissue may reflect differences between circulating levels of CEdG resulting from DNA repair and/or cell turnover vs local tissue accumulation. The wt/db mice may be considered to exhibit borderline metabolic disease, as they have been shown to have higher rates of glucose oxidation, slower rates of catabolism, and are significantly more prone to gestational diabetes relative to wt animals. The data suggest that MG-induced AGE accumulation can occur in tissue even with a relatively mild diabetic phenotype and contribute to DNA damage despite FPG and HbA1c levels within the normal range. Since it was not practical to assay tissue DNA from all organs, the subset sampled was chosen on the basis of data indicating increased diabetes-associated cancer susceptibility. This tissue sampling bias may have highlighted differences not apparent in the analysis of CEdG in urine. Genetic and epigenetic dysregulation due to the presence of long-lived CEdG modification of DNA may contribute to genomic instability and/or play a role in the phenomenon of metabolic memory in diabetes. As demonstrated in the working examples, the DNA-AGEs CEdG and the protein AGEs CML and CEL were linearly correlated in the animal model (FIG. 28C), but only CEdG bore a significant relationship to FPG (FIG. 25A vs. 28B). This suggests that measurement of protein and DNA-AGEs may bear different relationships to clinical endpoints of metabolic disease. In summary, the stable DNA-AGE CEdG was significantly elevated in mouse models of diabetes, was able to predict diabetes as a single parameter, correlated with FPG and HbA1c, and was substantially increased in organs of wt/db and db/db mice relative to wt. These observations have catalyzed longitudinal clinical trials to examine CEdG as a biomarker for metabolic disease. The term “diabetic complications,” “diabetic related pathologies” or the like refers to various conditions that can arise from or are linked to metabolic disorders or diseases associated with abnormal glucose regulation caused by diabetes. Metabolic disorders and diseases cover a wide range of disorders involving abnormal metabolic processing, including those related to carbohydrate metabolism, amino acid metabolism, organic acid metabolism, mitochondrial metabolism, porphyrin metabolism, fatty acid oxidation disorders, purine and pyrimidine metabolism, steroid metabolism, mitochondrial metabolism, peroxisomal and lysosomal storage disorders, and glycolytic metabolic disorders. Many types of clinical complications or pathologies can manifest themselves as a result of diabetes and diabetes-related metabolic disorders and diseases. These diabetic complications include microvascular and macrovascular complications—such as hypertension, stroke, cardiovascular diseases, neuropathy, nephropathy, and retinopathy; hyperosmolar hyperglycemic nonketotic syndrome (HHNS); ketoacidosis; foot and skin ulceration and damage, hearing impairment, Alzheimer's disease, as well as certain cancers. Cancers that are associated with diabetes and diabetes-related metabolic disorders and diseases are sometimes referred to as glycolytic cancers. A glycolytic cancer is a cancer that is caused or influenced by abnormal sugar processing, such as with glycation. Conditions which result in the impairment of glucose regulation such as diabetes and metabolic syndrome have been shown to significantly increase the risk for cancers of the breast, liver, kidney, lung, pancreas, colon, cervix and endometrium. In the case of hyperglycemia and/or diabetes, an elevated level of CEdG, as compared to normal physiological levels of CEdG, indicates that the subject has diabetes. A sensitive LC-ESI-MS/MS method for the measurement of CEdG in urine or double-stranded DNA is used. Quantification is achieved by the stable isotope dilution method using synthetic 15N5-CEdG as an internal standard. Urinary CEdG was measured in normal and streptozoticin-induced diabetic rats, and it was shown that adduct levels are significantly increased following the onset of hyperglycemia. LC-ESI-MS/MS was used to demonstrate a dose-dependent reduction in CEdG in response to administration of LR-90, an inhibitor of AGE formation. Measurement of CEdG from hydrolyzed and dephosphorylated double-stranded DNA was complicated by the fact that MG was present during the enzymatic workup. This was found to react with DNA during sample workup leading to artifactual overestimation of CEdG levels. In order to circumvent this problem, adventitious MG was sequestered by the addition of carbonyl scavengers such as aminoguanidine (AG) and D-penicillamine (D-P) prior to workup, resulting in stable and reproducible determinations. In the case of glycolytic cancers, such as breast cancer, a reduced level of CEdG, as compared to normal physiological levels of CEdG, indicates that the subject has cancer. The following examples are provided to better illustrate the claimed invention and are not to be interpreted as limiting the scope of the invention. To the extent that specific materials are mentioned, it is merely for purposes of illustration and is not intended to limit the invention. One skilled in the art may develop equivalent means or reactants without the exercise of inventive capacity and without departing from the scope of the invention. Example 1 Materials and instrumentation. 15N5-2′-deoxyguanosine was purchased from Silantes (Munich, Germany, lot #dG-N-0507-1/2); DL-glyceraldehyde (95%), calf thymus DNA was from Sigma (St. Louis, Mo.), and ammonium acetate (1M, pH 7 solution) from Fluka (Buchs, Switzerland). Phosphate salts were A.C.S. reagent grade from J. T. Baker (Phillipsburg, N.J.). HPLC grade CH3CN was purchased from Fisher Scientific (Fair Lawn, N.J.). All water was purified to a resistivity of 18.2 MS) using a Nanopure Diamond system by Barnstead International (Dubuque, Iowa). Solid phase extractions were performed using 1 ml strata-X-C cation mixed mode cartridges (Phenomenex, Torrance Calif.). Nuclease P1 was purchased from US Biologicals (Swampscott, Mass.). Phosphodiesterase II from bovine spleen and alkaline phosphatase from bovine intestinal mucosa was purchased from Sigma-Aldrich. HPLC separations were performed using a Hewlett-Packard Series 1100 Liquid Chromatography system equipped with a diode-array detector. Ultraviolet spectra were collected on an Ultrospec 3000 pro (Amersham Biosciences, Piscataway, N.J.). Mass analysis of synthetic 15N5-CEdG was performed using a Thermo Finnigan LTQ-FT linear ion trap mass spectrometer (San Jose, Calif.) in the Mass Spectrometry-Proteomics Core Facility of the City of Hope. LC-MS/MS analyses of CEdG in biological samples were carried out using a Micromass Quattro Ultima Triple Quadrupole Mass Spectrometer (Beverly, Mass.) interfaced to an Agilent 1100 Capillary HPLC system (Palo Alto, Calif.) equipped with a Synergi C18 analytical column (4μ, 150×2.0 mm; Phenomenex, Torrance, Calif.). 1H NMR spectra were recorded at 400 MHz on a VNMRS spectrometer (Varian, Inc., Palo Alto, Calif.) in the Synthesis and Biopolymer Core Facility of the City of Hope. 1D and 2D NMR data was processed using the Spinworks shareware program (version 2.5.5), copyright 1999-2006 by Kirk Marat and available from the University of Manitoba website. Synthesis and characterization of 15N5-CEdG. DL-Glyceraldehyde was used to generate methylgloxal (MG) in situ via guanine catalyzed dehydration.17 DL-Glyceraldehyde (9.5 mg) was added to 10 mg of 15N5-labeled dG, 12.3 mg potassium dihydrogen phosphate, and 24.0 mg disodium hydrogen phosphate in 87.7 μL H2O. The heterogeneous reaction mixture was vortexed and placed in a heat block at 40° C. Reactions were worked up following complete dissolution of solids (˜14-17 days) yielding a yellow-red viscous solution. Products were purified by HPLC in 10-15 μL aliquots on a 10×50 mm Waters XTerra MS C18 2.5μ column using a (Et)3NH4OAc (50 mM, pH 7)/CH3CN gradient. The CH3CN concentration was raised from 0 to 4.0% in the first 5 minutes, from 4.0 to 6.5% over 30 minutes; johnskelly@example.net% for 5 minutes, then raised to 90% to wash residual material off the column. Diastereomers CEdG-A and B eluted at 24 and 29 minutes, respectively (FIG. 2). Fractions were lyophilized to dryness prior to resuspension in 18.2 MS) H2O. Concentrations of stock solutions were calculated by UV using a molar extinction coefficient of 12,300 @ 255 nm. See, for example, FIGS. 8A-C. Mass analyses of 15N5-CEdG diastereomers were conducted using a Thermo-Finnigan LTQ FT ion trap mass spectrometer in the positive ion mode. A full scan MS for CEdG-A is shown in FIG. 3. The most intense ion was observed for the sodiated peak, C13H1715N5NaO6+: m/z 367.18 (obs), m/z 367.09 (calc). 1H NMR assignments for CEdG-A: 1H NMR (400 MHz, d6-DMSO, 18° C.) δ□10.60 (s, 1H, N1-H), δ 7.93 (s, 1H, C8-H), δ 6.76 (d, 1H, C2-NH), δ 6.12 (dd, 1H, C1′-H), δ 5.30 (d, 1H, C3′-OH), δ 4.89 (vbr, 1H, C5′-OH), δ 4.36 (m, 1H, C2-NH—CH), δ 4.32 (m, 1H, C4′-H), δ 3.81 (m, 1H, C3′-H), δ 3.50 (ddd, 2H, C5′-H2), δ 2.64 (ddd, 1H, C2′-H), δ 2.18 (ddd, 1H, C2′-H), δ 1.39 (d, 3H, C2-NH—CH—CH3). 13C NMR assignments for CEdG-A: (100.5 MHz, d6-DMSO, 18° C.) δ 174.1 (C2-NH—CH—COOH), δ 156.3 (C6), δ 151.5 (C2), δ 149.9 (C4), δ 136.1 (C8), δ 117.1 (C5), δ 87.6 (C3′), δ 82.9 (C1′), δ 70.8 (C4′), δ 61.7 (C5′), δ 49.0 (C2-NH—CH), δ ˜39.5 (C2′), δ 17.7 (C2-NH—CH—CH3). 1H and 13C NMR assignments for CEdG-B are nearly identical to the A isomer. Synthesis of oligonucleotides containing site-specifically modified CEdG residues. A synthetic scheme was devised for the quantitative preparation of oligonucleotides containing CEdG that can be readily accommodated on any standard DNA synthesizer using the conventional phosphoramidite technology. Oligos containing only pure D or L CEdG were prepared in a stereochemically pure manner using D- or L-alanine in a reaction that proceeds with retention of configuration. An NPE protected 2-fluoropurine phosphoramidite derivative was introduced into the polymer during standard oligonucleotide synthesis, and the reaction with D or L alanine was carried out prior to any deprotection step. Specifically, stereochemically pure R- or S-CEdG oligonucleotides were synthesized by nucleophilic substitution with either D- or L-alanine on 2-fluoro-2′-deoxyinosine (2-FdI) containing oligos followed by deprotection and purification. Oligonucleotides were prepared using an ABI394 DNA synthesizer loaded with either standard or 2-F-dl-CE phosphoramidites (0.2 μM scale). For the preparation of CEdG containing oligonucleotides, F-dl-containing fully-protected oligomers still bound to the CPG support were suspended in an aqueous solution of 1M D- or L-alanine in 250 mM potassium carbonate at 50° C. for 40 hours. Complete removal of all protecting groups was achieved by extended reaction at 50° C. in concentrated ammonia for 7 days. Separation of the desired oligonucleotide from failure sequences and other impurities was achieved by ion-pairing chromatography on a 10 mm×250 mm×Bridge Prep C18 5 μm column (Waters, Milford, Mass.), using a 40 minute 9.0% to 9.5% gradient of acetonitrile vs 100 mM triethylammonium acetate (TEAA, Fluka, Milwaukee, Wis.) at a constant 45° C. All oligonucleotides were characterized by chromatography under the indicated conditions and analyzed by ESI-FT/MS on an LTQ-FT (Thermo-Finnigan, San Jose, Calif.) in the Mass Spectrometry Core of the City of Hope Cancer Center. This new synthesis is superior to previously known syntheses for CEdG because it allows for the preparation of oligos containing stereochemically pure R- or S-CEdG in high yield. Oligos containing uniquely substituted CEdG residues are used to calibrate the biological measurement of CEdG by serving as internal standards. They are also used in biochemical assays for examining the biological consequences of site-specific CEdG substitution in DNA, including, but not limited to, aspects of their repair and mutagenic potential (FIG. 16). This synthetic scheme may also be used to make site specific substitutions for other AGEs. Stable Isotope Dilution. Internal standards for other AGEs usually contain stable isotopes (15N, 13C, 18O)) to create a different pass from the related analyte. Different concentrations of the stable isotope substituted compounds are prepared and analyzed by MS in order to determine the response height of the ion current as a function of different concentrations. A calibration plot is made of concentration vs ion current response. This is typically a linear plot of concentrations ranging from anticipated lowest detectable amounts to highest expected. The ion current response increases with concentration. To measure CEdG in a biological sample, a known amount of stable isotope standard is “spiked” into the sample. Since the CEdG in the sample and the CEdG standard have different molecular weights, they can be resolved by MS. The ion current response of CEdG in the sample is compared to the response of the spiked isotopically enriched CEdG. Since the concentration of isotopically enriched standard in the sample is known, comparison allows for calculation of the amount of CEdG in the biological sample by fitting to the calibration plot. Stability studies of CEdG in acidic solution. A 1.25 mM solution of CEdG-A, B or dG in 100 μL of 1M AcOH (pH 2.4) was stirred at 37° C. Aliquots (10 μl) were removed periodically and added to 404 of 2M TEAA (pH 7.0). HPLC product analyses were performed using an Alltech HS HyperPrep 100 BDS C18 8μ column. A gradient of 0 to 4% CH3CN over 5 min was followed by 6.5% CH3CN over 30 min. TEAA (pH 7) was kept constant at 50 mM. The ratio of free base (CEGuanine or Guanine) to intact nucleoside (CEdG or dG) was calculated by integration of the corresponding HPLC peaks (see inset in FIG. 4). The CEG free base was identified as Peak A by ESI-MS in negative ion mode. C8H8O3N5, observed: m/z 222.064; calculated: m/z 222.063. Animal Studies. All animal studies were carried out in compliance with the policies outlined in NIH Publication No. 85-23 “Guide for the Care and Use of Laboratory Animals.” Male Sprague-Dawley rats were rendered diabetic by injection of streptozoticin and maintained as previously described.18 AGE inhibitor LR-90 was administered ad libitum at concentrations ranging from 2.5-50 mg/L. Rats were housed in metabolic cages and urine was collected over a 24 hour period with several drops of toluene to inhibit microbial growth. Urine samples were stored at −80° C. prior to LC-MS/MS analysis for CEdG. The data in FIG. 5 represent 3 replicates from n different animals: non-diabetic controls, n=6; non-diabetic treated with 50 mg/L LR-90, n=5; diabetic control, n=3. For diabetic rats treated with varying doses of LR-90: 2.5 mg/L, n=4; 10 mg/L, n=5; 25 mg/L, n=6; 50 mg/L, n=8. Urine sample preparation. CEdG was concentrated from urine by solid phase extraction. A 1 ml strata-X-C cartridge was pre-conditioned by the sequential addition of 1 ml MeOH/CH3CN (1:1) followed by 2×1 ml 2% H3PO4. Then 15N5-CEdG was added as an internal standard (final concentration 5 μg/ml), the sample was acidified with 10 μl of 86% H3PO4, and finally 0.4 mL of urine was introduced via suction filtration. The cartridge was then washed with sequential additions of 1 ml 0.1% H3PO4 and 1 ml MeOH and then dried under vacuum for 1 minute. Finally, CEdG/15N5-CEdG containing fractions were eluted from the cartridge with 1 mL 3% NH4OH in MeOH:CH3CN (2:8 v/v). The eluent was evaporated to dryness in a centrifugal concentrator and reconstituted with 200 μl 0.1% formic acid prior to LC-MS/MS injection. Preparation of mononucleosides from DNA. Calf thymus or tissue-extracted DNA (100 μg) was dissolved in 80 μL of autoclaved 18.2 MS) H2O containing 20 μL of sodium acetate (100 mM, pH 5.5), 20 μL of 1×TBE, 1.5 μL of 50 mM ZnCl2, and 2.37 μL of a 100 mM AG or D-P stock solution. DNA was denatured at 95° C. for 5 min on a PCR heating block and then brought to 4° C. for 5 min. After equilibration to 45° C., 1.5 μL of 10 U/μL nuclease P1 was added. Alkaline phosphatase (4 μL of 8 U/μL), 1 U of bovine phosphodiesterase, and 14 μL of 100
{'application_number': '<application-reference appl-type="utility">\n<document-id>\n<country>US</country>\n<doc-number>17532928</doc-number>\n<date>20211122</date>\n</document-id>\n</application-reference>', 'publication_number': '<publication-reference>\n<document-id>\n<country>US</country>\n<doc-number>20220331273</doc-number>\n<kind>A1</kind>\n<date>20221020</date>\n</document-id>\n</publication-reference>', 'source_file': './application/2022/ipa221020.xml', 'source_data': 'USPTO-Application'}