Ching-Hua Kuo

Northwestern University, Evanston, IL, United States

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Publications (36)106.41 Total impact

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    ABSTRACT: As fatty acids play an important role in biological regulation, the profiling of fatty acid expression has been used to discover various disease markers and to understand disease mechanisms. This study developed an effective and accurate comparative fatty acid analysis method using differential labeling to speed the metabolic profiling of fatty acids.
    Clinica Chimica Acta. 08/2014; 438.
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    ABSTRACT: Liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) has become one of the most widely used methods in pharmaceutical laboratories. Although LC-ESI-MS provides high sensitivity and high specificity for quantifying target analytes in complicated biofluids, the associated severe matrix effects (MEs) generally result in large quantification errors. Here, we propose a novel strategy for correcting MEs in various biofluids using a postcolumn infused-internal standard (PCI-IS) method in combination with matrix normalization factors (MNFs). We used the MNFs to normalize the encountered MEs in various biofluids to the MEs encountered in standard solutions. The use of a postcolumn infused-internal standard also corrects the MEs for individual samples. When using the PCI-IS method in combination with MNFs, the calibration curve generated from standard solutions can be applied to quantify the target analytes in various biofluids. We applied this new approach to quantify etoposide and etoposide catechol in plasma and CSF. The accuracy of the test results showed that over 93% of the data have quantification errors less than 20% and that 99% of the data have quantification errors less than 30%. The successful application of this method to evaluate real clinical samples revealed that our proposed MNFs in combination with the PCI-IS method largely simplifies the entire method development and validation processes, saves a great deal of time and cost without sacrificing quantification accuracy, and provides a simple means of quantifying target analytes in various biofluids. This method will be particularly useful in fields in which the same target analytes need to be quantified in various types of matrices, including bioanalysis, forensic toxicology, environmental studies, and food safety control.
    Journal of chromatography. A. 06/2014;
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    ABSTRACT: Plasma efavirenz concentrations in HIV-infected patients with tuberculosis (TB) may be affected by cytochrome P450 (CYP) 2B6 single-nucleotide polymorphisms and concurrent rifampicin use. We aimed to investigate the effects of CYP2B6 G516T polymorphisms and concomitant rifampicin use on the plasma efavirenz concentrations in HIV-infected Taiwanese. HIV-infected patients with or without TB who had received combination antiretroviral therapy containing efavirenz (600 mg daily) for two weeks or greater were enrolled for determinations of CYP2B6 G516T polymorphism and plasma efavirenz concentrations with the use of polymerase-chain-reaction restriction fragment-length polymorphism and high-performance liquid chromatography, respectively. From October 2009 to August 2012, 171 HIV-infected patients, including 18 with TB, were enrolled 113 (66.1%) with CYP2B6 G516G, 55 (32.2%) GT, and 3 (1.8%) TT genotype. Patients receiving rifampicin had a significantly lower median plasma efavirenz concentration than the control group (2.16 vs 2.92 mg/L, P = 0.003); however, all patients achieved target plasma concentration (>1 mg/L). Patients with GT or TT genotype had a significantly higher plasma concentration than those with GG genotype (2.50 vs 3.47 mg/L for GT genotype and 8.78 mg/L for TT genotype, P<0.001). Plasma efavirenz concentration >4 mg/L was noted in 38 (22.2%) patients, which was associated with a lower weight (per 10-kg increase, odds ratio, 0.52; 95% confidence interval, 0.33-0.83) and GT or TT genotype (odds ratio, 4.35; 95% confidence interval, 1.97-9.59) in multivariate analysis. Despite combination with rifampicin, sufficient plasma efavirenz concentrations can be achieved in HIV-infected Taiwanese with TB who receive efavirenz 600 mg daily. Carriage of CYP2B6 516 GT and TT genotypes and a lower weight are associated with higher plasma efavirenz concentrations.
    PLoS ONE 01/2014; 9(2):e88497. · 3.53 Impact Factor
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    ABSTRACT: Matrix effects (MEs) are a major problem affecting the quantitative accuracy of liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) when analyzing complicated samples. While analyzing urine specimens, the wide diversity of endogenous materials and different urine concentrations may result in inaccurate quantification. In this study, we propose a postcolumn-infused internal standard (PCI-IS) strategy for universal correction of MEs in urine specimens. MEs can be effectively corrected by dividing the target analyte signal intensity by the PCI-IS intensity. To evaluate the performance of PCI-IS, we used 6 benzodiazepine (BZD) drugs in 5 different concentrations of urine matrixes as a test model. The divergence of the BZD drug signal responses in 5 different urine matrixes was expressed using their respective coefficients of variation (CV) to evaluate the efficiency of using PCI-IS in correcting matrix effects. The CV of the BZD drug signal intensities in these 5 different concentrations of the urine matrixes were reduced from 10 to 30% to less than 10% when the PCI-IS correction method was employed. When the PCI-IS method was used to correct the 6 BZDs in 25 real human urine samples, over 90% of the test results exhibited quantification errors of less than 20%, and all of the test results had quantification errors of less than 30%. These results demonstrate that the PCI-IS method can resolve the problem of inaccurate quantification that arises from the diversity of urine specimens. The PCI-IS method is particularly useful for clinical analysis or forensic toxicology to improve the quantification accuracy in an economical way.
    Journal of Chromatography A 12/2013; · 4.61 Impact Factor
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    ABSTRACT: Antibiotic-resistant bacterial infection is one of the most serious clinical problems worldwide. Vancomycin, teicoplanin, daptomycin, and colistin are glycopeptide and lipopeptide antibiotics that are frequently used to treat multidrug-resistant bacterial infections. Therapeutic drug monitoring is recommended to ensure both safety and efficacy and to improve clinical outcomes. This study developed a fast, simple, and sensitive ultra-high-pressure liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for the simultaneous determination of the concentrations of these four drugs in human plasma. The sample preparation process includes a simple protein denaturation step using acetonitrile, followed by an 11-fold dilution with 0.1% formic acid. Eight target peaks for the four drugs can be analyzed within 3min using a Kinetex™ 2.6μm C18 column. The mass spectrometry parameters were optimized, and two transitions for each target peak were used for multiple reaction monitoring, which provided high sensitivity and specificity. The UHPLC-MS/MS method was validated over clinical concentration ranges. The intra-day and inter-day precisions for the ratio of the peak area of each analyte to the peak area of the internal standard were all below 12.7 and 14.7% relative standard deviations, respectively. The accuracy at low, medium, and high concentrations of the eight target peaks was between 89.3 and 110.7%. The standard curves for the analytes were linear and had coefficients of determination higher than 0.997. The limits of detection were all below 70ngmL(-1). The use of this method to analyze patient plasma samples confirmed that it is effective for the therapeutic drug monitoring of these four drugs and can be used to improve the therapeutic efficacy and safety of treatment with antibiotics.
    Talanta 11/2013; 116:593-603. · 3.50 Impact Factor
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    ABSTRACT: Micellar electrokinetic chromatography (MEKC) using a cationic surfactant, cetyltrimethylammonium bromide (CTAB), was applied to simultaneous separation of four types of hydrophobic steroid hormones including androgens, estrogens, progestins, and glucocorticoids. Various parameters, such as the concentration of CTAB, type and proportion of organic modifiers, and sample matrix have been demonstrated to be important with respect to the separation resolution, analysis time, and repeatability. Successful separation of cortisone, hydrocortisone, estriol, testosterone, estrone, progesterone, and estradiol was achieved at -25 kV using 100 mM Tris-boric acid buffer (pH 9.0) containing 40 mM CTAB and 20% 2-propanol using ultraviolet (UV) absorption detection. For estrogen compounds which possess intrinsic fluorescence, detection limits at the sub �Mlevel could be achieved with laser-induced fluorescence (LIF) detection. Two kinds of pharmaceutical preparations were analyzed using the developed method, and the results were in good agreement with the label claims.
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    ABSTRACT: Fatty liver is significantly associated with hepatic cirrhosis and liver cancer. Excessive alcohol consumption causes alcoholic fatty liver disease (AFLD). Ginger has been reported to exhibit antioxidant potential and hepatoprotective activity. In the present study, a mouse model for AFLD was developed by employing male C57BL/6 mice who were fed an alcohol-containing liquid diet (Lieber-DeCarli diet) ad libitum. In the treatment groups, ginger essential oil (GEO) and citral were orally administered every day for 4 weeks. Serum biochemical analysis, antioxidant enzyme activity analysis, and histopathological evaluation revealed that GEO and citral exhibited hepatoprotective activity against AFLD. Metabolites in serum samples were profiled by high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS). Metabolomic data indicated the amounts of metabolites such as D-glucurono-6,3-lactone, glycerol-3-phosphate, pyruvic acid, lithocholic acid, 2-pyrocatechuic acid, and prostaglandin E1 were increased after alcohol administration, but the levels were recovered in treatment groups. Our analysis indicated that ginger possesses hepatoprotective properties against AFLD. Further, these metabolites can serve as early non-invasive candidate biomarkers in the clinical application of AFLD for health management.
    Journal of Agricultural and Food Chemistry 10/2013; · 3.11 Impact Factor
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    ABSTRACT: An ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) method for the screening and confirmation of 62 drugs of abuse and their metabolites in urine was developed in this study. The most commonly abused drugs, including amphetamines, opioids, cocaine, benzodiazepines (BZDs) and barbiturates, and many other new and emerging abused drugs, were selected as the analytes for this study. Urine samples were diluted 5-fold with deionized water before analysis. Using a superficially porous micro-particulate column and an acetic acid-based mobile phase, 54 basic and 8 acidic analytes could be detected within 15 and 12 min in positive and negative ionization modes, respectively. The MS collision energies for the 62 analytes were optimized, and their respective fragmentation patterns were constructed in the in-house library for confirmatory analysis. The coefficients of variation of the intra- and inter-day precision of the analyte responses all were <17.39%. All analytes, except barbital, showed matrix effects of 77-121%. The limits of detection of the 62 analytes were between 2.8 and 187.5 ng/mL, which were lower than their respective cut-off concentrations (20-500 ng/mL). Ten urine samples from patients undergoing methadone treatment were analyzed by the developed UHPLC-QTOF-MS method, and the results were compared with the immunoassay method.
    Journal of analytical toxicology 09/2013; · 2.11 Impact Factor
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    ABSTRACT: BACKGROUND: Individuals with peripheral arterial disease (PAD) have a nearly two-fold increased risk of all-cause and cardiovascular disease mortality compared to those without PAD. This pilot study determined whether metabolomic profiling can accurately identify patients with PAD who are at increased risk of near-term mortality. METHOD: We completed a case-control study using (1)H NMR metabolomic profiling of plasma from 20 decedents with PAD, without critical limb ischemia, who had blood drawn within 8 months prior to death (index blood draw) and within 10 to 28 months prior to death (preindex blood draw). Twenty-one PAD participants who survived more than 30 months after their index blood draw served as a control population. RESULTS: Results showed distinct metabolomic patterns between preindex decedent, index decedent, and survivor samples. The major chemical signals contributing to the differential pattern (between survivors and decedents) arose from the fatty acyl chain protons of lipoproteins and the choline head group protons of phospholipids. Using the top 40 chemical signals for which the intensity was most distinct between survivor and preindex decedent samples, classification models predicted near-term all-cause death with overall accuracy of 78% (32/41), a sensitivity of 85% (17/20), and a specificity of 71% (15/21). When comparing survivor with index decedent samples, the overall classification accuracy was optimal at 83% (34/41) with a sensitivity of 80% (16/20) and a specificity of 86% (18/21), using as few as the top 10 to 20 chemical signals. CONCLUSION: Our results suggest that metabolomic profiling of plasma may be useful for identifying PAD patients at increased risk for near-term death. Larger studies using more sensitive metabolomic techniques are needed to identify specific metabolic pathways associated with increased risk of near-term all-cause mortality among PAD patients.
    Journal of vascular surgery: official publication, the Society for Vascular Surgery [and] International Society for Cardiovascular Surgery, North American Chapter 05/2013; · 3.52 Impact Factor
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    ABSTRACT: This study developed capillary electrophoresis (CE) and ultra-high-pressure liquid chromatography (UHPLC) methods coupled with UV detectors to characterize the metabolomic profiles of different rhubarb species. The optimal CE conditions used a back ground electrolyte (BGE) with 15 mM sodium tetraborate, 15 mM sodium dihydrogen phosphate monohydrate, 30 mM sodium deoxycholate, and 30% acetonitrile (ACN) (v/v) at pH 8.3. The optimal UHPLC conditions used a mobile phase composed of 0.05% phosphate buffer and ACN with gradient elution. The gradient profile increased linearly from 10% ACN to 21% ACN within the first 25 minutes, then increased to 33% ACN for the next 10 minutes. It took another 5 minutes to reach the 65% ACN, then for the next 5 minutes it stayed unchanged. Sixteen samples of Rheum officinale and Rheum tanguticum collected from various locations were analyzed by CE and UHPLC methods. The metabolite profiles of CE were aligned and baseline corrected before chemometric analysis. Metabolomic signatures of rhubarb species from CE and UHPLC were clustered using principle component analysis and distance-based redundancy analysis; the clusters were not only able to discriminate different species but also different cultivation regions. Similarity measurements were performed by calculating the correlation coefficient of each sample with the authentic samples. Hybrid rhizome was clearly identified through similarity measurement of UHPLC metabolite profile and later confirmed by gene sequencing. The present study demonstrated that CE and UHPLC are efficient and effective tools to identify and authenticate herbs even coupled with simple detectors.
    Electrophoresis 04/2013; · 3.26 Impact Factor
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    ABSTRACT: CYP2D6 (cytochrome P450 2D6) is one of the most important enzymes involved in drug metabolism, and CYP2D6 gene variants may cause toxic effects of therapeutic drugs or treatment failure. In this research, a rapid and simple method for genotyping the most common mutant alleles in the Asian population (CYP2D6*1/*1, CYP2D6*1/*10, CYP2D6*10/*10, CYP2D6*1/*5, CYP2D6*5/*10, and CYP2D6*5/*5) was developed by allele-specific polymerase chain reaction (AS-PCR) combined with capillary electrophoresis (CE). We designed a second mismatch nucleotide next to the single nucleotide polymorphism (SNP) site in allele-specific primers to increase the difference in PCR amplification. Besides, we established simulation equations to predict the CYP2D6 genotypes by analyzing the DNA patterns in the CE chromatograms. The multiplex PCR combined with CE method was applied to test 50 patients, and all of the test results were compared with the DNA sequencing method, long-PCR method and real-time PCR method. The correlation of the analytical results between the proposed method and other methods were higher than 90%, and the proposed method is superior to other methods for being able to simultaneous detection of SNPs and copy number variations (CNV). Furthermore, we compared the plasma concentration of aripiprazole (a CYP2D6 substrate) and its major metabolites with the genotype of 25 patients. The results demonstrate the proposed genotyping method is effective for estimating the activity of the CYP2D6 enzyme and shows potential for application in personalized medicine. Similar approach can be applied to simultaneous detection of SNPs and CNVs of other genes.
    Analytica chimica acta 02/2013; 763:67-75. · 4.31 Impact Factor
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    ABSTRACT: Liquid Chromatography - Time of Flight Mass Spectrometry has become an important technique for toxicological screening and metabolomics. We describe TIPick a novel algorithm that accurately and sensitively detects target compounds in biological samples. TIPick comprises two main steps: background subtraction and peak picking. By subtracting a blank chromatogram, TIPick eliminates chemical signals of blank injections and reduces false positive results. TIPick detects peaks by calculating the S(CC(INI) ) values of extracted ion chromatograms (EICs) without considering peak shapes, and it is able to detect tailing and fronting peaks. TIPick also uses duplicate injections to enhance the signals of the peaks and thus improve the peak detection power. Commonly seen split peaks caused by either saturation of the mass spectrometer detector or a mathematical background subtraction algorithm can be resolved by adjusting the mass error tolerance of the EICs and by comparing the EICs before and after background subtraction. The performance of TIPick was tested in a data set containing 297 standard mixtures; the recall, precision and F-score were 0.99, 0.97 and 0.98, respectively. TIPick was successfully used to construct and analyze the NTU MetaCore metabolomics chemical standards library, and it was applied for toxicological screening and metabolomics studies. Copyright © 2013 John Wiley & Sons, Ltd.
    Biological Mass Spectrometry 02/2013; 48(2):234-42. · 3.41 Impact Factor
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    ABSTRACT: Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.
    Cancers. 01/2013; 5(2):491-510.
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    ABSTRACT: Aristolochic acid nephropathy is caused by aristolochic acid (AA) and AA-containing herbs. In traditional Chinese medicine, a principle called "Jun-Chen-Zou-Shi" may be utilized to construct a remedial herbal formula that attempts to mitigate the toxicity of the main ingredient. This study used Bu-Fei-A-Jiao-Tang (BFAJT) to test if the compound remedy based on a principle of "Jun-Chen-Zou-Shi" can decrease the toxicity of AA-containing herbs. We compared the three toxicities of AA standard, Madouling (an Aristolochia herb), and a herbal formula BFAJT. AA standard was given for BALB/c mice at a dose of 5 mg/kg bw/day or 7.5 mg/kg bw/day for 10 days. Madouling and BFAJT were given at an equivalence of AA 0.5 mg/kg bw/day for 21 days. Nephrotoxicity was evaluated by metabolomics and histopathology. The urinary metabolomics profiles were characterized by (1)H NMR spectroscopy. The spectral data was analyzed with partial least squares discriminant analysis, and the significant differential metabolites between groups were identified. The result showed different degrees of acute renal tubular injuries, and metabolomics analysis found that the kidney injuries were focused in proximal renal tubules. Both metabolomics and pathological studies revealed that AA standard, Madouling, and BFAJT were all nephrotoxicants. The compositions of the compound remedy did not diminish the nephrotoxicity caused by AA.
    Evidence-based Complementary and Alternative Medicine 01/2013; 2013:263757. · 1.72 Impact Factor
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    ABSTRACT: Matrix effects (MEs) are a major problem affecting the quantitative accuracy of liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) when analyzing complicated samples. While analyzing urine specimens, the wide diversity of endogenous materials and different urine concentrations may result in inaccurate quantification. In this study, we propose a postcolumn-infused internal standard (PCI-IS) strategy for universal correction of MEs in urine specimens. MEs can be effectively corrected by dividing the target analyte signal intensity by the PCI-IS intensity. To evaluate the performance of PCI-IS, we used 6 benzodiazepine (BZD) drugs in 5 different concentrations of urine matrixes as a test model. The divergence of the BZD drug signal responses in 5 different urine matrixes were expressed using their respective coefficients of variation (CV) to evaluate the efficiency of using PCI-IS in correcting matrix effects. The CV of the BZD drug signal intensities in these 5 different concentrations of the urine matrixes were reduced from 10-30% to less than 10% when the PCI-IS correction method was employed. When the PCI-IS method was used to correct the 6 BZDs in 25 real human urine samples, over 90% of the test results exhibited quantification errors of less than 20%, and all of the test results had quantification errors of less than 30%. These results demonstrate that the PCI-IS method can resolve the problem of inaccurate quantification that arises from the diversity of urine specimens. The PCI-IS method is particularly useful for clinical analysis or forensic toxicology to improve the quantification accuracy in an economical way
    Journal of Chromatography A. 01/2013;
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    ABSTRACT: Baseline distortion in 1D 1H-NMR data complicates the quantification of individual components of biofluids in metabolomic experiments. Current 1D 1H-NMR baseline correction methods usually require manual parameter and filter tuning by experienced users to obtain desirable results from complex metabolomic spectra - thus becoming prone to correction variation and biased quantification. We present a novel alternative method, BaselineCorrector, for automatically estimating the baselines of 1D 1H-NMR metabolomic data. By collecting the standard deviations of spectral intensities, using a moving window to slide through a spectrum, BaselineCorrector can model the distribution of noise standard deviation as a derived chi-squared distribution in each window and then determine optimal parameters for least-error classification of signal and noise. Due to the universal property of noise distributions, BaselineCorrector can robustly recognize the baseline segments in various spectra. In addition to the commonly used 1D NOESY and CPMG pulse sequences, BaselineCorrector also provides an algorithm for correcting diffusion-edited NMR spectra. Using its classification model, BaselineCorrector is able to preserve low signal peaks and correctly handle wide, overlapping peaks in complex metabolomic spectra.
    Analytical Chemistry 12/2012; · 5.70 Impact Factor
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    ABSTRACT: Metabolomics is a powerful tool for understanding phenotypes and discovering biomarkers. Combinations of multiple batches or data sets in large cross-sectional epidemiology studies are frequently utilized in metabolomics, but various systematic biases can introduce both batch and injection order effects and often require proper calibrations prior to chemometric analyses. We present a novel algorithm, Batch Normalizer, to calibrate large scale metabolomic data. Batch Normalizer utilizes a regression model with consideration of the total abundance of each sample to improve its calibration performance, and it is able to remove both batch effect and injection order effects. This calibration method was tested using liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS) chromatograms of 228 plasma samples and 23 pooled quality control (QC) samples. We evaluated the performance of Batch Normalizer by examining the distribution of relative standard deviation (RSD) for all peaks detected in the pooled QC samples, the average Pearson correlation coefficients for all peaks between any two of QC samples, and the distribution of QC samples in the scores plot of a principal component analysis (PCA). After calibration by Batch Normalizer, the number of peaks in QC samples with RSD less than 15% increased from 11 to 914, all of the QC samples were closely clustered in PCA scores plot, and the average Pearson correlation coefficients for all peaks of QC samples increased from 0.938 to 0.976. This method was compared to 7 commonly used calibration methods. We discovered that using Batch Normalizer to calibrate LC/TOF-MS data produces the best calibration results.
    Analytical Chemistry 12/2012; · 5.70 Impact Factor
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    ABSTRACT: The number of cases of invasive fungal infections (IFIs) has risen significantly in recent years; therefore, this study developed a sensitive and effective sweeping-micellar electrokinetic chromatography (MEKC) method for the simultaneous determination of the three most frequently used triazole antifungal drugs for the treatment of IFIs, which included voriconazole, itraconazole, and posaconazole. Due to the diverse lipophilicity of the tested drugs, the analytical conditions that resulted in good resolution between itraconazole and posaconazole caused the peak for voriconazole to split. The splitting phenomenon was resolved by incorporating a high-salt stacking mechanism into the sweeping-MEKC method. The optimum background electrolyte was composed of 25 mM phosphoric acid solution (pH 2.2), 100 mM sodium dodecyl sulfate, 13 % acetonitrile, and 13 % tetrahydrofuran. The best peak shape of voriconazole was obtained when the conductivity ratio between the sample matrix and background electrolyte was 2.3. Compared to the conventional MEKC mode, the enhancement factor of the sweeping-MEKC method was 66 for itraconazole, 55 for posaconazole, and 43 for voriconazole. The sweeping-MEKC method was validated in terms of precision, accuracy, linearity, specificity, selectivity, and sensitivity. The linearity ranges of the method covered the commonly used therapeutic ranges of the three drugs. The developed sweeping-MEKC method was successfully applied to the analysis of clinical samples, thus demonstrating its applicability for clinical use.
    Analytical and Bioanalytical Chemistry 05/2012; 404(1):217-28. · 3.66 Impact Factor
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    ABSTRACT: The complex composition of welding fumes, multiplicity of molecular targets, diverse cellular effects, and lifestyles associated with laborers vastly complicate the assessment of welding fume exposure. The urinary metabolomic profiles of 35 male welders and 16 male office workers at a Taiwanese shipyard were characterized via (1)H NMR spectroscopy and pattern recognition methods. Blood samples for the same 51 individuals were also collected, and the expression levels of the cytokines and other inflammatory markers were examined. This study dichotomized the welding exposure variable into high (welders) versus low (office workers) exposures to examine the differences of continuous outcome markers-metabolites and inflammatory markers-between the two groups. Fume particle assessments showed that welders were exposed to different concentrations of chromium, nickel, and manganese particles. Multivariate statistical analysis of urinary metabolomic patterns showed higher levels of glycine, taurine, betaine/TMAO, serine, S-sulfocysteine, hippurate, gluconate, creatinine, and acetone and lower levels of creatine among welders, while only TNF-α was significantly associated with welding fume exposure among all cytokines and other inflammatory markers measured. Of the identified metabolites, the higher levels of glycine, taurine, and betaine among welders were suspected to play some roles in modulating inflammatory and oxidative tissue injury processes. In this metabolomics experiment, we also discovered that the association of the identified metabolites with welding exposure was confounded by smoking, but not with drinking, which is a finding consistent with known modified response of inflammatory markers among smokers. Our results correspond with prior studies that utilized nonmetabolomic analytical techniques and suggest that the metabolomic profiling is an efficient method to characterize the overall effect of welding fume exposure and other confounders.
    Chemical Research in Toxicology 02/2012; 25(3):676-86. · 3.67 Impact Factor