Metabolites In Biological Samples Research Articles

Electrochemical Sensors, Biosensors, and Optical Sensors for the Detection of Opioids and Their Analogs: Pharmaceutical, Clinical, and Forensic Applications

Pharmaceutical opioids are intravenously or orally administered analgesics. While they are effective in relieving chronic and acute pain, their narrow window of therapeutic use contributes to the high occurrence of abuse. The associated abuse of this family of drugs can be correlated to the increase in dependency, overdose, and death of users. The negative effects of opioids extend beyond the physical and psychological effects experienced by the user to their unregulated synthesis and sale, which contribute to socioeconomic challenges and are a biproduct of this global public health epidemic. From clinical to point-of-care applications, the detection and real-time monitoring of this family of drug is critical in the fight to decrease abuse and improve use in clinical settings. Chromatographic separations and chromatography–mass spectrometry are traditional methods of opioid analyses, but the high cost, long analysis time, and absence of portability highlight the need for the development of fast, in situ, point-of-care analysis, or of community drug monitoring services. This review highlights recent electrochemical and optical (FTIR, Raman, colorimetric, and fluorescent) advances and biosensors for pharmaceutical and illicit opioid analysis. Specifically, an emphasis is placed on the detection of opioids and their metabolites in biological samples and in vitro cellular assays for clinical diagnosis and forensic applications. The challenges and prospects of the role of electrochemical sensors, biosensors, and optical sensors for opioid analysis in promoting clinical diagnosis, forensic study, point-of-care, and community drug monitoring services to reduce harm are also provided.

Application of Metabolomics Across the Spectrum of Pulmonary and Critical Care Medicine.

In recent years, metabolomics, the systematic study of small molecule metabolites in biological samples, has yielded fresh insights into the molecular determinants of pulmonary diseases and critical illness. The purpose of this article is to orient the reader to this emerging field by discussing the fundamental tenets underlying metabolomics research, the tools and techniques that serve as foundational methodologies, and the various statistical approaches to analysis of metabolomics datasets. We present several examples of metabolomics applied to pulmonary and critical care medicine in order to illustrate the potential of this avenue of research to deepen our understanding of pathophysiology. We conclude by reviewing recent advances in the field and future research directions that stand to further the goal of personalizing medicine in order to improve patient care.

Analysis of vitamin D and its metabolites in biological samples – Part I: Optimization and comparison of UHPSFC-MS/MS and UHPLC-MS/MS methods

Fat-soluble vitamin D is an essential bioactive compound important for human health. Insufficient vitamin D levels can result not only in bone disease but also in other disorders, such as cancer, metabolic disorders, and diseases related to poor immune function. The current methods commonly used for vitamin D analysis are often applied to determine the levels of the most abundant metabolite in plasma, i.e., 25-OH-D2/D3. These methods do not consider the presence of other hydroxylated and esterified metabolites, including isomers and epimers, which are typically found in low concentrations.In this study, we developed a fast and selective ultra-high performance supercritical fluid chromatography (UHPSFC) method using a 150 mm long 1-amino anthracene (1-AA) column and a mobile phase consisting of carbon dioxide and methanol/isopropanol (1/1, v/v) mixed with 8 % water. After thorough optimization of column temperature and back pressure, the separation of four vitamin D3 esters, vitamin D3 and D2, and eight mono- and di-hydroxylated metabolites, including three groups of isomers, was achieved in 10 min. Two ion sources, atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization optimized within this study, were compared in tandem mass spectrometry (MS/MS) detection. No significant sensitivity differences were observed. Subsequently, the same 1-AA column chemistry was examined in ultra-high performance liquid chromatography (UHPLC) as the stationary phase that could hypothetically bring different selectivity in the separation of vitamin D and its metabolites. However, this hypothesis was rejected, and C18 was used as a stationary phase in the final optimized UHPLC-MS/MS method. Despite detailed optimization, the final 15 min UHPLC method was not able to separate di-hydroxylated isomers of vitamin D3, while it enabled better resolution of esterified forms compared to UHPSFC.Optimized methods provided similar repeatability of retention times and peak areas, with RSD < 2 % and 10 %, respectively. The lowest limits of quantification were in the range of 1.2 – 4.9 ng/mL for UHPSFC-APCI-MS/MS, while for UHPLC-APCI-MS/MS, they were typically in the range of 2.6 – 9.6 ng/mL. Based on the obtained results, the UHPSFC-APCI-MS/MS method was the most promising approach for fast, selective, and sensitive analysis that could be applied in the analysis of biological samples with emphasis on the separation of both hydroxylated and esterified metabolites, including isomeric forms.

Analysis of vitamin D and its metabolites in biological samples – Part II: Optimization of a sample preparation method for liver tissue

Extraction of vitamin D, including its hydroxylated and esterified metabolites, from soft tissues such as the liver is challenging due to the lipophilic character of matrix and analytes that are expected in very low concentration levels.In this study, we aimed at the optimization of two-step extraction using solid–liquid extraction as the first step, followed by solid-phase extraction. Various solvents, including ethanol, acetonitrile, methanol, acetone, heptane, and heptane with isopropanol, were investigated to isolate vitamin D compounds from liver tissue in the first step. Acetone was finally selected as the most suitable solvent for the solid–liquid extraction, with the highest recovery in the range of 67 – 98% for polar hydroxylated forms and 3 – 28% for lipophilic vitamin D and esters. Two solid phase extraction (SPE) based on the (i) “bind and elute strategy” and (ii) “removal strategy” using hydrophilic-lipophilic balanced SPE sorbent were optimized as a proceeding step for acetone extracts to increase the method selectivity. Finally, two optimized methods, combining solid–liquid extraction and individual SPE strategy, were examined in terms of sensitivity, recovery, matrix effect, accuracy, and precision.The limits of quantification were in the range of 1 – 10 ng/mL and 3 – 20 ng/mL analyzed by ultra-high performance supercritical fluid chromatography and ultra-high performance liquid chromatography hyphenated a with tandem mass spectrometer, respectively. The absolute recovery determined for the “bind and elute strategy” protocol was in the range of 3 – 24 %. Nevertheless, this method was free of matrix effects, which were determined to be in the 73 – 120 % range. On the contrary, the “removal strategy” approach provided higher recovery values for all compounds (47 – 123 %), but the results for nonpolar vitamin D and esters were strongly affected by signal suppression (matrix effects 3 – 51 %). Both methods fulfilled the criteria for accuracy and precision requested by the European Medicine Agency Guideline on Bioanalysis.“Removal strategy” SPE with decreased manual intervention and lower solvent consumption was finally applied to mouse liver tissue to determine vitamin D and its hydroxylated and esterified metabolites for the first time. The results, i.e., vitamin D esters detected in liver tissue, supported the notion that esters of vitamin D can be stored in lipophilic tissues to release vitamin D.

Novel LC-MS/MS Method for Simultaneous Determination of Monoamine Neurotransmitters and Metabolites in Human Samples.

For the simultaneous determination of monoamine neurotransmitters (NTs) like dopamine, serotonin, noradrenaline, and epinephrine, and their metabolites (metanephrine, normetanephrine, 3-methoxytyramine, vanillylmandelic acid, 3,4-dihydroxyphenylacetic acid, homovanillic acid, and 5-hydroxyindoleacetic acid), a robust liquid chromatography method coupled with tandem mass spectrometry (LC-MS/MS) was introduced as the analytical method. This analytical method proved to be accurate for the simultaneous measurement of the amounts of 11 NTs and their metabolites in biological samples. The method proved to be more efficient and better than the previously reported method in terms of precision, recovery, sample requirement, and extraction procedure. The reported method requires only 100 μL of blood and 200 μL of urine, and the extraction procedure requires acetonitrile precipitation, filtration, drying, and reconstitution in water. The separation of all analytes was performed on an C18 column (4.6 mm × 150 mm and 1.8 μm). A 10 min gradient elution program with a mobile phase consisting of phase A (0.2% formic acid in water) and phase B (methanol) was used. The positive ionization mode was used for the detection of all analytes in multiple reaction monitoring (MRM). The proposed method was validated with an internal standard and yielded lower limits of detection and quantification ranges of 0.0182-0.0797 ng/mL and 0.0553-0.2415 ng/mL, respectively, with a good linearity (R2) between 0.9959 and 0.9994. The recoveries ranged from 73.37% to 116.63% in blood and from 80.9% to 115.33% in urine. For the NTs and metabolites, the intra- and interday % CV were 0.24-9.36 and 0.85-9.67, respectively. The developed LC-MS/MS method was successfully used for the determination of trace amounts of endogenous compounds in human blood and urine samples.

Metabolomics: a review of liquid chromatography mass spectrometry-based methods and clinical applications

Abstract Introduction Metabolomics is a rapidly growing field that aims to understand the complex metabolic pathways involved in health and disease. Liquid chromatography mass spectrometry (LC-MS) based untargeted metabolomics has emerged as a powerful tool for investigating the metabolic changes associated with various diseases, and for identifying potential biomarkers for early disease detection and treatment monitoring. This review provides a comprehensive overview of LC-MS based untargeted metabolomics and its clinical applications. Content The advantages and challenges of untargeted metabolomics are discussed, encompassing sample preparation, data processing, sample storage, acquisition mode selection, column strategy, and annotation. The latest advancements in LC-MS technology and data analysis techniques are reviewed, which have facilitated the more accurate and sensitive detection of metabolites in biological samples. The clinical applications of untargeted metabolomics are emphasized, including its utilization in disease diagnosis, treatment monitoring, and personalized medicine. Examples are provided of how biomarkers for various diseases, such as cancer, coronary heart disease, and infectious disease, have been identified through the application of untargeted metabolomics. Summary and outlook Overall, LC-MS based untargeted metabolomics is a powerful tool for investigating the complex metabolic changes associated with various diseases, and has the potential to transform clinical diagnosis, treatment, and personalized medicine.

Analytical methods for detecting butane, propane, and their metabolites in biological samples: Implications for inhalant abuse detection

Worldwide, various inhalants are widely abused for recreational purposes, with butane and propane emerging as among the most commonly misused volatile substances, posing a significant risk of sudden death. The rapid elimination and oxidation of these highly volatile compounds upon inhalation necessitate the identification of butane and propane along with their metabolites in biological samples. Hence, the primary objective of this study is twofold: firstly, to establish a method for analyzing butane, propane, and metabolites, and secondly, to demonstrate the detection window and exposure indicators associated with the inhalation of butane and propane. In pursuit of this objective, we developed analytical methods for the determination of isobutane, n-butane, propane, and their nine metabolites in both blood and urine. Headspace-gas chromatography–mass spectrometry (GC–MS) and solid-phase microextraction-GC–MS were employed for the analyses, demonstrating acceptable precision and accuracy. An animal study revealed that isobutane and n-butane were only detectable below the limit of quantification (LOQ) in rat blood 5 min after exposure. Meanwhile, the three major metabolites—2-methyl-2-propanol, 2-butanol, and 2-butanone—were observed 5 min after exposure but persisted in rat urine even 5 h post-exposure. Additionally, human urine samples identified other metabolites, including acetone, acetoin, and 2,3-butanediol isomers. The presence of specific metabolites corresponding to each inhalant confirmed the abuse of butane and propane. This comprehensive approach provides valuable insights into the detection and assessment of inhalation to these volatile substances.

Recent findings and advancements in the detection of designer benzodiazepines: a brief review.

This review article takes a closer look at a new class of psychoactive substances called designer benzodiazepines (DBZs) and the challenges of their detection. These are adinazolam, clonazolam, deschloroetizolam, diclazepam, etizolam, flualprazolam, flubromazepam, flubromazolam, phenazepam, and pyrazolam. They are central nervous system depressants and sedatives that can cause psychomotor impairment and increase the overdose risk when combined with other sedatives. DBZs undergo phase I and II metabolism similar to traditional benzodiazepines, but their specific metabolic pathways and the influence of genetic polymorphisms are yet to be clarified. Advances in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enhanced the method's sensitivity for DBZs and their metabolites in biological samples and coupled with improved blood sampling methods require less blood for drug monitoring. Further research should focus on elucidating their pharmacokinetic properties and metabolism in humans, especially in view of genetic polymorphisms and drug interactions that could inform clinical treatment choices. Even though we have witnessed important advances in DBZ detection and measurement, further refinements are needed to expand the scope of detectable DBZs and their metabolites. All this should help toxicological research to better identify and characterise the risks of chronic and polydrug abuse and facilitate clinical, forensic, and regulatory responses to this growing issue.

Profiling Analysis of Tryptophan Metabolites in the Urine of Patients with Parkinson's Disease Using LC-MS/MS.

Although Parkinson's disease (PD) is a representative neurodegenerative disorder and shows characteristic motor impediments, the pathophysiological mechanisms and treatment targets for PD have not yet been clearly identified. Since several tryptophan metabolites produced by gut microbiota could pass the blood-brain barrier and, furthermore, might influence the central nervous system, tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways might be the most potent targets for PD development. Furthermore, most metabolites are circulated via the blood, play roles in and/or are metabolized via the host organs, and finally are excreted into the urine. Therefore, profiling the overall tryptophan metabolic pathways in urine samples of patients with PD is important to understanding the pathological mechanisms, finding biomarkers, and discovering therapeutic targets for PD. However, the development of profiling analysis based on tryptophan metabolism pathways in human urine samples is still challenging due to the wide physiological ranges, the varied signal response, and the structural diversity of tryptophan metabolites in complicated urine matrices. In this study, an LC-MS/MS method was developed to profile 21 tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways in human urine samples using ion-pairing chromatography and multiple reaction monitoring determination. The developed method was successfully applied to urine samples of PD patients (n = 41) and controls (n = 20). Further, we investigated aberrant metabolites to find biomarkers for PD development and therapeutic targets based on the quantitative results. Unfortunately, most tryptophan metabolites in the urine samples did not present significant differences between control and PD patients, except for indole-3-acetic acid. Nonetheless, indole-3-acetic acid was reported for the first time for its aberrant urinary levels in PD patients and tentatively selected as a potential biomarker for PD. This study provides accurate quantitative results for 21 tryptophan metabolites in biological samples and will be helpful in revealing the pathological mechanisms of PD development, discovering biomarkers for PD, and further providing therapeutic targets for various PD symptoms. In the near future, to further investigate the relationship between gut microbial metabolites and PD, we will employ studies on microbial metabolites using plasma and stool samples from control and PD patients.

SPA-STOCSY: an automated tool for identifying annotated and non-annotated metabolites in high-throughput NMR spectra.

Nuclear magnetic resonance spectroscopy (NMR) is widely used to analyze metabolites in biological samples, but the analysis requires specific expertise, it is time-consuming, and can be inaccurate. Here, we present a powerful automate tool, SPatial clustering Algorithm-Statistical TOtal Correlation SpectroscopY (SPA-STOCSY), which overcomes challenges faced when analyzing NMR data and identifies metabolites in a sample with high accuracy. As a data-driven method, SPA-STOCSY estimates all parameters from the input dataset. It first investigates the covariance pattern among datapoints and then calculates the optimal threshold with which to cluster datapoints belonging to the same structural unit, i.e. the metabolite. Generated clusters are then automatically linked to a metabolite library to identify candidates. To assess SPA-STOCSY's efficiency and accuracy, we applied it to synthesized spectra and spectra acquired on Drosophila melanogaster tissue and human embryonic stem cells. In the synthesized spectra, SPA outperformed Statistical Recoupling of Variables (SRV), an existing method for clustering spectral peaks, by capturing a higher percentage of the signal regions and the close-to-zero noise regions. In the biological data, SPA-STOCSY performed comparably to the operator-based Chenomx analysis while avoiding operator bias, and it required <7min of total computation time. Overall, SPA-STOCSY is a fast, accurate, and unbiased tool for untargeted analysis of metabolites in the NMR spectra. It may thus accelerate the use of NMR for scientific discoveries, medical diagnostics, and patient-specific decision making. The codes of SPA-STOCSY are available at https://github.com/LiuzLab/SPA-STOCSY.

Immobilized Enzymes on Magnetic Beads for Separate Mass Spectrometric Investigation of Human Phase II Metabolite Classes.

The human body has evolved to remove xenobiotics through a multistep clearance process. Non-endogenous metabolites are converted through a series of phase I and different phase II enzymes into compounds with higher hydrophilicity. These compounds are important for diverse research fields such as toxicology, nutrition, biomarker discovery, doping control, and microbiome metabolism. One of the challenges in these research fields has been the investigation of the two major phase II modifications, sulfation and glucuronidation, and the corresponding unconjugated aglycon independently. We have now developed a new methodology utilizing an immobilized arylsulfatase and an immobilized β-glucuronidase to magnetic beads for treatment of human urine samples. The enzyme activities remained the same compared to the enzyme in solution. The separate mass spectrometric investigation of each metabolite class in a single sample was successfully applied to obtain the dietary glucuronidation and sulfation profile of 116 compounds. Our new chemical biology strategy provides a new tool for the investigation of metabolites in biological samples with the potential for broad-scale application in metabolomics, nutrition, and microbiome studies.

Quantitative Metabolomic Dataset of Avian Eye Lenses

Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics may help to reveal the molecular basis of a disease, make a diagnosis, and monitor treatment responses, while in agriculture, it can improve crop yields and plant breeding. However, animal metabolomics faces several challenges due to the complexity and diversity of animal metabolomes, the lack of standardized protocols, and the difficulty in interpreting metabolomic data. The current dataset includes quantitative metabolomic profiles of eye lenses from 26 bird species (111 specimens) that can aid researchers in developing new experiments, mathematical models, and integrating with other “-omics” data. The dataset includes raw 1H NMR spectra, protocols for sample preparation, and data preprocessing, with the final table containing information on the abundance of 89 reliably identified and quantified metabolites. The dataset is quantitative, making it relevant for supplementing with new specimens or comparison groups, followed by data mining and expected new interpretations. The data were obtained using the bird specimens collected in compliance with ethical standards and revealed potential differences in metabolic pathways due to phylogenetic differences or environmental exposure.

Profiling of Amino Metabolites in Biological Samples without Protein Precipitation Using a Solid-Phase-Supported Phenyl Isothiocyanate-Based Chemoselective Probe.

Amino metabolites are essential for life activities and can be used clinically as biomarkers for disease diagnosis and treatment. Solid-phase-supported chemoselective probes can simplify sample handling and enhance detection sensitivity. However, the low efficiency and complicated preparation of traditional probes limit their further application. In this work, a novel solid-phase-supported probe Fe3O4-SiO2-polymers-phenyl isothiocyanate (FSP-PITC) was developed by immobilizing phenyl isothiocyanate on magnetic beads with disulfide as an orthogonal cleavage site, which can couple amino metabolites directly regardless of whether proteins and other matrixes were removed. After purification, the targeted metabolites were released by dithiothreitol and detected by high-resolution mass spectrometry. The simplified processing steps shorten the analysis time, and the introduction of polymers results in a 100-1000-fold increase in probe capacity. With high stability and specificity, FSP-PITC pretreatment allows accurate qualitative and quantitative (R2 > 0.99) analysis, facilitating the detection of metabolites in subfemtomole quantities. Using this strategy, 4158 metabolite signals were detected in negative ion mode. Among them, 352 amino metabolites including human cells (226), serum (227), and mouse samples (274) were searched from the Human Metabolome Database. These metabolites participate in metabolic pathways of amino acids, biogenic amine, and the urea cycle. All these results indicate that FSP-PITC is a promising probe for novel metabolite discovery and high-throughput screening.

Quantitative plasma profiling by 1H NMR-based metabolomics: impact of sample treatment.

Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.

Comparison of serum metabolomics in women with breast Cancer Prior to Chemotherapy and at 1 year: cardiometabolic implications

ObjectiveEarly-stage breast cancer (BC) is the second most common malignancy in women, worldwide. Early-detection and treatment advances have led to 5-year survival rates of 90% for early-stage breast cancer. However, the long-term morbidity of breast cancer remains high, with a majority of survivors facing increased risk of cardiometabolic conditions as well as secondary cancers. In particular, African American women with breast cancer experience higher morbidity and mortality than other women. Metabolomics is the comprehensive study of metabolites in biological samples to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways. Although some studies have found differential metabolites in women with breast cancer compared to normal controls, there has been little study of women with breast cancer across time and the active treatment trajectory. This study examines and compares the serum metabolomic profile of women with BC, prior to initial chemotherapy and at 1 year after inception of chemotherapy.MethodsThis study examined serum metabolites through a secondary analysis of a longitudinal parent study (EPIGEN) of women diagnosed with early-stage BC. Participants were evaluated across 5 time points: prior to their receipt of chemotherapy (T1), at the time of their 4th chemotherapy treatment (T2), 6 months after the initiation of chemotherapy (T3), one year after the initiation of chemotherapy (T4) and two years after the initiation of chemotherapy (T5). This analysis focused on the metabolomic data from 70 participants from T1 to T4. Using ultra high-pressure liquid chromatography high resolution mass spectrometry (UHPLC-HRMS), we performed Friedman Rank Sum Test followed by Nemenyi post-hoc pairwise tests to identify which metabolite levels differed between time points, focusing on metabolites with a Benjamini-Hochberg false discovery rate (FDR) from the overall Friedman test < 0.05 and then specifically examined the p-values from the T1 vs. T4 pairwise comparison.ResultsThe untargeted serum metabolomics yielded a total of 2,395 metabolites identified on the basis of the accurate mass and MS/MS fragmentation, 1,264 of which were significant after Friedman’s test (FDR < 0.05). The analysis then focused on the levels of 124 metabolites from the T1 vs. T4 post-hoc comparison that had a combined FDR < 0.05 and fold change (FC) > 2.0. Metabolite set enrichment analysis (MSEA) as part of Metaboanalyst 3.0 was performed to identify pathways that were significantly altered. The known metabolites identified from the functional analysis were used to evaluate the up and down regulated pathways. The 40metabolites from the Functional Analysis were mainly attributed to amino acids (specifically lysine regulation), fatty acids (particularly unsaturated) and steroid hormone synthesis (lysophosphatidic acid).ConclusionThere were multiple significant changes in the serum metabolomic profile of women with breast cancer at one-year post inception of chemotherapy compared to pre-chemotherapy, most notably associated with lysine degradation, branched-chain amino acid synthesis, linoleic acid metabolism, tyrosine metabolism and biosynthesis of unsaturated fatty acids as the top 5 metabolic pathways. Some of these changes could be associated with metabolic perturbations that are consistent with heightened risk of cardiometabolic morbidity. Our results provide new insights into the mechanisms underlying potential heightened cardiovascular health risks in this population.

Optimization of chromatographic systems for detection and determination of carbamazepine in pharmaceutical formulations, serum, and saliva by HPLC-DAD

Carbamazepine (CBZ) is an anticonvulsant drug, widely used also in various disorders like neuropathic pain, bipolar affective disorder, resistant schizophrenia, and trigeminal neuralgia. Appropriate analytical procedures are necessary to monitor, detect and quantify CBZ in pharmaceutical formulations and biological samples. The search for new methods for drug determination is one of the most important challenges of modern scientific research. It is important to study the chromatographic conditions of CBZ analysis, which is necessary for the further development of efficient drug determination methods. In this work, retention, peak symmetry, and system efficiency of CBZ on Polar RP and Phenyl-Hexyl stationary phases were investigated. Various mobile phases containing methanol (MeOH) and/or acetonitrile (ACN) as organic modifiers, acetate buffer, and the addition of diethylamine (DEA) were applied. Different chromatographic systems were compared to obtain satisfying retention, peak shape, and system efficiency. The most optimal chromatographic system with Polar RP column was applied for the determination of CBZ in pharmaceutical formulations, human serum, and saliva by the high-performance liquid chromatography with diode array detection (HPLC-DAD) method. Solid-phase extraction (SPE) method was applied for sample preparation prior to chromatographic analysis. The proposed method was validated for linearity, selectivity, precision, and accuracy. Confirmation of the presence of CBZ and its main metabolites in biological samples obtained from patients was performed using the ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method.

Electrochemical study for simultaneous detection of procaine hydrochloride and its metabolite in biological samples using a nanostructured strong sensor

Electrochemical study for simultaneous detection of procaine hydrochloride and its metabolite in biological samples using a nanostructured strong sensor

Facile synthesis of amino-functionalized magnetic materials for efficient enrichment of anionic metabolites from biological samples

The analysis of biological samples is often affected by the background matrix. Proper sample preparation is a critical step in the analytical procedure for complex samples. In this study, a simple and efficient enrichment strategy based on Amino-functionalized Polymer-Magnetic MicroParticles (NH2-PMMPs) with coral-like porous structures was developed to enable the detection of 320 anionic metabolites, providing detailed coverage of phosphorylation metabolism. Among them, 102 polar phosphate metabolites including nucleotides, cyclic nucleotides, sugar nucleotides, phosphate sugars, and phosphates, were enriched and identified from serum, tissues, and cells. Furthermore, the detection of 34 previously unknown polar phosphate metabolites in serum samples demonstrates the advantages of this efficient enrichment method for mass spectrometric analysis. The limit of detections (LODs) were between 0.02 and 4 nmol/L for most anionic metabolites and its high sensitivity enabled the detection of 36 polar anion metabolites from 10 cell equivalent samples. This study has provided a promising tool for the efficient enrichment and analysis of anionic metabolites in biological samples with high sensitivity and broad coverage, facilitating the knowledge of the phosphorylation processes of life.

Urinary and Serum Concentration of Deoxynivalenol (DON) and DON Metabolites as an Indicator of DON Contamination in Swine Diets.

Pig health is impaired and growth performance is reduced when exposed to deoxynivalenol (DON). The measurement of DON in individual feedstuffs and complete swine diets is variable because of the inconsistent distribution of mycotoxins in feed and the difficulties in obtaining representative samples. We investigated whether measuring DON and its metabolites in biological samples could be used as a predictor of DON ingestion by pigs. Blood samples were collected between 3 and 4 h after the morning meal and urine samples were quantitatively collected over a 24 h period on d 40 and 82 of the study to evaluate serum and urinary content of DON and DON metabolites (iso-deoxynivalenol, DON-3-glucuronide, DON-15-glcurunide, deepoxy-deoxynivalenol, iso-deepoxy-deoxynivalenol, deepoxy-deoxynivalenol-3-glucuronide, and deepoxy-deoxynivalenol-15-glucuronide). The intake of DON was positively correlated with urinary DON output. Similarly, there was an increase in serum DON level with increasing DON intake. Overall, it was found that DON intake correlated with DON concentration in urine and blood serum when samples were collected under controlled conditions. Analyzing DON levels in urine and blood serum could be used to predict a pig's DON intake.

The Quantification of Paclitaxel and Its Two Major Metabolites in Biological Samples by HPLC-MS/MS and Its Application in a Pharmacokinetic and Tumor Distribution Study in Xenograft Nude Mouse.

A rapid and sensitive high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method was developed for the quantification of Paclitaxel (PTX), 6α-hydroxypaclitaxel (6α-OHP), and p-3'-hydroxypaclitaxel (3'-OHP) in mouse plasma and tumor tissue. The analytes were separated using a C18 column (50 × 2.1 mm, 1.8 μm), and a triple-quadrupole mass spectrometry device equipped with an electrospray ionization (ESI) source was applied for their detection. PTX, 6α-OHP, and 3'-OHP were extracted from the biological samples with the solid-phase extraction cartridge. The method was fully validated according to the FDA's guidance. The method was linear over the concentration ranges of 0.5~1000.0 ng/mL for PTX and 0.25~500.0 ng/mL for 6α-OHP and 3'-OHP. The precision, accuracy, extraction recovery, and matrix effects were within acceptable limits. The present method was successfully applied to the study of the pharmacokinetics and distribution of PTX, 6α-OHP, and 3'-OHP in the tumors of post xenograft nude mice intravenously injected with PTX solution.