OBJECTIVE: Methylphenidate is commonly used in the treatment of Attention Deficit Hyperactivity Disorder and narcolepsy. Methylphenidate is administered as a racemic mixture of the d- and l-threo enantiomers; however, the d-enantiomer is primarily responsible for the pharmacologic activity. Previous studies of the behavioral effects of methylphenidate have highlighted sex differences in the responsiveness to the drug, namely an increased sensitivity of females to its stimulatory effects. These differences may be due to differences in the uptake, distribution, and elimination of methylphenidate from male and female brains. Therefore, we compared the pharmacokinetics of d- and l-threo methylphenidate in the brains of male and female rats. MATERIALS AND METHODS: Adult male and female Sprague-Dawley rats were injected with 5 mg/kg d, l-threo methylphenidate, and whole brains were collected at various time points following injection. We measured methylphenidate concentrations utilizing chiral high pressure liquid chromatography followed by mass spectrometry. RESULTS: Females exhibited consistently higher brain concentrations of both d- and lmethylphenidate and a slower clearance of methylphenidate from brain as compared to males, particularly with the active d-enantiomer. CONCLUSIONS: The increased sensitivity of females to methylphenidate may be partially explained by an increase in total brain exposure to the drug

Objective: The aim of this study was to investigate inherent in vitro permeability, metabolism, and cytotoxicity of idebenone - an active used to protect skin as an anti-aging agent -and compare it to idebenone linoleate. Methods: Idebenone and idebenone linoleate were investigated in pig ear skin and melanoma (B16: F10 mouse) cells. Diffusion experiments were conducted at 37 °C (bath temperature) using Franz diffusion cells. Authentic metabolite samples were synthetically prepared. Samples were analyzed using liquid chromatography-mass spectrometry/mass spectrometry. Cell viability was determined via the 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide (MTT) assay. Results: Idebenone was shown to permeate across viable porcine ear tissue; there was no evidence that idebenone linoleate permeated across porcine ear tissue after 4 h. Idebenone was metabolized to idebenone acid in both pig ear and mouse melanocytes; only minor idebenone linoleate metabolism was observed. Idebenone displayed delayed in vitro toxicity (via MTT assay) in melanocytes, while idebenone linoleate displayed no such in vitro toxicity. Conclusions: The in vitro metabolism and cytotoxicity results suggest that metabolic activation of idebenone is the likely culprit that activates the skin irritation mechanism via idebenone in vivo usage. An idebenone ester (e.g. idebenone linoleate) appears to provide a superior in vitro safety profile over idebenone.

Raloxifene is a highly insoluble, highly metabolized serum estrogen receptor modulator approved for use in the treatment of osteoporosis. Hydroxybutenyl-beta-cyclodextrin (HBenBCD) is a novel solubility enhancer previously demonstrated to increase the oral bioavailability of tamoxifen, letrozole, and itraconazole. The current study evaluated the pharmacokinetics of raloxifene in oral and intravenous formulations with HBenBCD in male Wistar-Hannover rats. Analytical methodology to measure raloxifene and its metabolites was developed by measuring raloxifene metabolism in vitro. Formulation with HBenBCD significantly increased raloxifene oral bioavailability. Mean ± S.D. oral bioavailabilities were 2.6 ± 0.4% for raloxifene formulated with microcrystalline cellulose, 7.7 ± 2.1% for a solid capsule formulation of raloxifene:HBenBCD complex, and 5.7 ± 1.3% for a liquid-filled capsule formulation containing raloxifene:HBenBCD/PEG400/H2O. Relative to raloxifene/microcrystalline filled capsules, the presence of HBenBCD in the solid capsule formulation afforded: (i) a decrease in raloxifene Tmax (2.5 ± 0.5 h versus 4.0 ± 0.5 h); (ii) a two-fold increase in raloxifene Cmax and a three-fold increase in raloxifene AUC; and (iii) a 12-fold increase in raloxifene glucuronide Cmax and a 6.5-fold increase in raloxifene glucuronide AUC. Hence, these studies demonstrate that raloxifene formulations containing HBenBCD significantly increased the oral bioavailability in rats relative to formulations that did not contain HBenBCD.

Synthetic cannabinoids (SCs), present a multitude of problems in terms of maintaining up-to-date, reliable, specific, and sensitive methods of detection. Synthetic cannabinoids are novel psychoactive substances originally synthesized for medical use and research purposes. Abuse of these compounds, however, has demonstrated a variety of effects ranging from euphoria to aggressive behavior and loss of consciousness. The most dangerous reported result of synthetic cannabinoids use has been death. The number of synthetic cannabinoid compounds detected drastically increased from two to over 80 compounds within six years. The marketing of these compounds, similar naming, and described pharmacological interactions, create the dangerous and very false perception that SCs are similar to, or the same as, tetrahydrocannabinol in cannabis products. This research focused on the development of a method to detect and quantify seven synthetic cannabinoids in urine, plasma, and gummy bears. The seven synthetic cannabinoids studied include XLR-11, AB-PINACA 5-pentanoic acid metabolite, UR-144 5-pentanoic acid metabolite, 5F-PB-22, AM-2201 4-hydroxypentyl metabolite, JWH-018, and JWH-018 5-hydroxypentyl metabolite. Sample preparation methods and a two dimensional liquid chromatography tandem mass spectrometry method were optimized and developed for analysis of the seven SCs in each matrix. The method was successfully applied to 17 authentic urine case samples previously screened positive for synthetic cannabinoids and a calibration curve for each matrix was generated from spiked samples at varying concentrations. Utilizing two-dimensional (2D) chromatography for the analysis of synthetic cannabinoids allowed for a novel approach to be employed. With this method, 100% organic samples were analyzed with improved resolution and increased sensitivity. The sample preparation method for the urine and plasma samples included a protein precipitation technique with acid followed by solid phase extraction (SPE) on a mixed-mode reversed phase strong anion exchange sorbent. The spiked gummy bear samples were prepared in 50% methanol in water, dissolved by heating, and extracted with SPE on the same sorbent used for the urine and plasma samples. A 200µL injection of the 100% MeOH extracts was injected into 2D-LC-MS/MS for analysis with a loading and diluting solvent consisting of water and 2% ammonium hydroxide and elution solvents containing water or methanol with 0.5% formic acid. These conditions were optimized with an automated method development protocol assessing various conditions such as mobile phase solvents, pH additives, and trap column chemistries. The final chromatography method utilized an ACQUITY ultra performance liquid chromatography (UPLC) ethylene bridged hybrid (BEH) C8 2.1 x 30mm, 10µm trap column and an ACQUITY UPLC high strength silica with tri-functional C18 bonding (HSS T3) analytical column 2.1 x 150mm, 1.7µm. The urine calibration curve produced had a linear dynamic range (LDR) of 0.05-2.5ng/mL for UR-144 5-COOH and AB-PINACA 5-COOH and 0.05-5ng/mL for the other five synthetic cannabinoids. R2 values included 0.992 and 0.993 for UR-144 5-COOH and AB-PINACA 5-COOH, respectively and 0.995 or above for the other five compounds. Synthetic cannabinoids were detected at varying concentrations in all 17 urine case samples. Analysis of plasma and gummy bear samples was also successfully carried out. Plasma calibration curves had a LDR 0.05-10ng/mL with all R2 values above 0.995. Gummy bear calibration curves produced a LDR of 0.05-10ng/mL or 0.05-2.5ng/mL with R2 values over 0.995. All extraction recovery values were greater than 80% with the exception of 63% recovery for AB-PINACA 5-COOH in the gummy bear matrix. Suppression effects of 8%, 19%, and 6.6% were observed for urine, plasma, and gummy bears, respectively. Relatively low recovery values, reduced linear dynamic ranges, and suppression matrix effects for the carboxylic acid analytes assessed in this research suggested an alternative approach may be more successful for the analysis of these particular compound types in all three matrices. Overall, a sensitive, specific, and reliable method was developed with low limits of detection and quantification for efficient and rapid analysis of compounds at trace levels utilizing 2D-LC-MS/MS.

No description available.

Apolipoprotein E (apoE) occurs on the majority of plasma lipoproteins and plays a major role in the lipid metabolism in the periphery and in the central nervous system. ApoE is a polymorphic protein with three common isoforms, apoE2, apoE3 and apoE4, derived from respective alleles '2, '3 and '4. The aim of this study was to develop a sample pretreatment protocol combined with rapid mass spectrometry (MS)-based assay for simultaneous apolipoprotein profiling and apoE phenotype identification. This assay was validated in 481 samples from patients with stable atherosclerotic cardiovascular disease (ASCVD) and applied to study association with mild cognitive impairment (MCI) in the LIFE Adult study, including overall 690 study subjects. Simultaneous quantification of 8–12 major apolipoproteins including apoA-I, apoB-100 and apoE could be performed within 6.5 min. Phenotyping determined with the developed MS assay had good agreement with the genotyping by real-time fluorescence PCR (97.5%). ApoE2 isoform was associated with the highest total apoE concentration compared to apoE3 and apoE4 (p < 0.001). In the subgroup of diabetic atherosclerotic cardiovascular disease (ASCVD) patients, apoE2 isoform was related to higher apoC-I levels (apoE2 vs. apoE3, p < 0.05), while in the subgroup of ASCVD patients under statin therapy apoE2 was related to lower apoB-100 levels (apoE2 vs. apoE3/apoE4, p < 0.05). A significant difference in apoE concentration observed between mild cognitive impairment (MCI) subjects and controls was confirmed for each apoE phenotype. In conclusion, this study provides evidence for the successful implementation of an MS-based apoE phenotyping assay, which can be used to assess phenotype effects on plasma lipid and apolipoprotein levels.

No description available.

No description available.

Liquid chromatography coupled with mass spectrometry (LC-MS) has been widely used in various omic studies for biomarker discovery. Appropriate LC-MS data preprocessing steps are needed to detect true differences between biological groups. Retention time alignment is one of the most important yet challenging preprocessing steps, in order to ensure that ion intensity measurements among multiple LC-MS runs are comparable. In this dissertation, we propose a Bayesian alignment model (BAM) for analysis of LC-MS data. BAM uses Markov chain Monte Carlo (MCMC) methods to draw inference on the model parameters and provides estimates of the retention time variability along with uncertainty measures, enabling a natural framework to integrate information of various sources. From methodology development to practical application, we investigate the alignment problem through three research topics: 1) development of single-profile Bayesian alignment model, 2) development of multi-profile Bayesian alignment model, and 3) application to biomarker discovery research. Chapter 2 introduces the profile-based Bayesian alignment using a single chromatogram, e.g., base peak chromatogram from each LC-MS run. The single-profile alignment model improves on existing MCMC-based alignment methods through 1) the implementation of an efficient MCMC sampler using a block Metropolis-Hastings algorithm, and 2) an adaptive mechanism for knot specification using stochastic search variable selection (SSVS). Chapter 3 extends the model to integrate complementary information that better captures the variability in chromatographic separation. We use Gaussian process regression on the internal standards to derive a prior distribution for the mapping functions. In addition, a clustering approach is proposed to identify multiple representative chromatograms for each LC-MS run. With the Gaussian process prior, these chromatograms are simultaneously considered in the profile-based alignment, which greatly improves the model estimation and facilitates the subsequent peak matching process. Chapter 4 demonstrates the applicability of the proposed Bayesian alignment model to biomarker discovery research. We integrate the proposed Bayesian alignment model into a rigorous preprocessing pipeline for LC-MS data analysis. Through the developed analysis pipeline, candidate biomarkers for hepatocellular carcinoma (HCC) are identified and confirmed on a complementary platform. / Ph. D.

Metabolomics aims at the detection and quantitation of metabolites within a biological system. As the most direct representation of phenotypic changes, metabolomics is an important component in system biology research. Recent development on high-resolution, high-accuracy mass spectrometers enables the simultaneous study of hundreds or even thousands of metabolites in one experiment. Liquid chromatography-mass spectrometry (LC-MS) is a commonly used instrument for metabolomic studies due to its high sensitivity and broad coverage of metabolome. However, the identification of metabolites remains a bottle-neck for current metabolomic studies. This thesis focuses on utilizing computational approaches to improve the accuracy and efficiency for metabolite identification in LC-MS/MS-based metabolomic studies. First, an outlier screening approach is developed to identify those LC-MS runs with low analytical quality, so they will not adversely affect the identification of metabolites. The approach is computationally simple but effective, and does not depend on any preprocessing approach. Second, an integrated computational framework is proposed and implemented to improve the accuracy of metabolite identification and prioritize the multiple putative identifications of one peak in LC-MS data. Through the framework, peaks are likely to have the m/z values that can give appropriate putative identifications. And important guidance for the metabolite verification is provided by prioritizing the putative identifications. Third, an MS/MS spectral matching algorithm is proposed based on support vector machine classification. The approach provides an improved retrieval performance in spectral matching, especially in the presence of data heterogeneity due to different instruments or experimental settings used during the MS/MS spectra acquisition. / Master of Science