Metabolomics Meets Clinics: A Multivariate Analysis of Plasma and Urine Metabolic Signatures in Pulmonary Arterial Hypertension.

Pulmonary arterial hypertension (PAH) is a severe, multifactorial, and frequently misdiagnosed disorder. The aim of this observational study was to compare the plasma and urine metabolomic profiles of PAH patients and healthy control subjects. Plasma and urine metabolomic profiles were analyzed using the GC-MS technique. Correlations between metabolite levels and clinical parameters among PAH patients, as well as the between-group differences, were evaluated. The linear discriminant analysis model, which allows for subject classification in terms of PAH with the highest possible precision, was developed and proposed. Plasma pyruvic acid, cholesterol, threonine, urine 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid, butyric acid, 1,2-benzenediol, glucoheptonic acid, and 2-oxo-glutaric acid were found to build a relatively accurate classification model for PAH patients. The model reached an accuracy of 91% and significantly improved subject classification (OR = 119 [95% CI: 20.3-698.3], p < 0.0001). Five metabolites were detected in urine that provide easily available and noninvasive tests as compared to right heart catheterization. The selected panel of metabolites has potential for early recognition of patients with dyspnea and faster referral to a reference center.

A multiplatform metabolomics approach for comprehensive analysis of GIST xenografts with various KIT mutations.

Metabolites in biological matrices belong to diverse chemical groups, ranging from non-polar long-chain fatty acids to small polar molecules. The goal of untargeted metabolomic analysis is to measure the highest number of metabolites in the sample. Nevertheless, from an analytical point of view, no single technique can measure such a broad spectrum of analytes. Therefore, we selected a method based on GC-MS and LC-MS with two types of stationary phases for the untargeted profiling of gastrointestinal stromal tumours. The procedure was applied to GIST xenograft samples (n = 71) representing four different mutation models, half of which were treated with imatinib. We aimed to verify the method coverage and advantages of applying each technique. RP-LC-MS measured most metabolites due to a significant fraction of lipid components of the tumour tissue. What is unique and worth noting is that all applied techniques were able to distinguish between different mutation models. However, for detecting imatinib-induced alterations in the GIST metabolome, RP-LC-MS and GC-MS proved to be more relevant than HILIC-LC-MS, resulting in a higher number of significantly changed metabolites in four treated models. Undoubtedly, the inclusion of all mentioned techniques makes the method more comprehensive. Nonetheless, for green chemistry and time and labour saving, we assume that RP-LC-MS and GC-MS analyses are sufficient to cover the global GIST metabolome.

Targeted quantitative metabolomics with a linear mixed-effect model for analysis of urinary nucleosides and deoxynucleosides from bladder cancer patients before and after tumor resection.

In the present study, we developed and validated a fast, simple, and sensitive quantitative method for the simultaneous determination of eleven nucleosides and deoxynucleosides from urine samples. The analyses were performed with the use of liquid chromatography coupled with triple quadrupole mass spectrometry. The sample pretreatment procedure was limited to centrifugation, vortex mixing of urine samples with a methanol/water solution (1:1, v/v), evaporation and dissolution steps. The analysis lasted 20 min and was performed in dynamic multiple reaction monitoring mode (dMRM) in positive polarity. Process validation was conducted to determine the linearity, precision, accuracy, limit of quantification, stability, recovery and matrix effect. All validation procedures were carried out in accordance with current FDA and EMA regulations. The validated method was applied for the analysis of 133 urine samples derived from bladder cancer patients before tumor resection and 24 h, 2 weeks, and 3, 6, 9, and 12 months after the surgery. The obtained data sets were analyzed using a linear mixed-effect model. The analysis revealed that concentration level of 2-methylthioadenosine was decreased, while for inosine, it was increased 24 h after tumor resection in comparison to the preoperative state. The presented quantitative longitudinal study of urine nucleosides and deoxynucleosides before and up to 12 months after bladder tumor resection brings additional prospective insight into the metabolite excretion pattern in bladder cancer disease. Moreover, incurred sample reanalysis was performed proving the robustness and repeatability of the developed targeted method.

Toward the General Mechanistic Model of Liquid Chromatographic Retention.

Large datasets of chromatographic retention times are relatively easy to collect. This statement is particularly true when mixtures of compounds are analyzed under a series of gradient conditions using chromatographic techniques coupled with mass spectrometry detection. Such datasets carry much information about chromatographic retention that, if extracted, can provide useful predictive information. In this work, we proposed a mechanistic model that jointly explains the relationship between pH, organic modifier type, temperature, gradient duration, and analyte retention based on liquid chromatography retention data collected for 187 small molecules. The model was built utilizing a Bayesian multilevel framework. The model assumes (i) a deterministic Neue equation that describes the relationship between retention time and analyte-specific and instrument-specific parameters, (ii) the relationship between analyte-specific descriptors (log P, pKa, and functional groups) and analyte-specific chromatographic parameters, and (iii) stochastic components of between-analyte and residual variability. The model utilizes prior knowledge about model parameters to regularize predictions which is important as there is ample information about the retention behavior of analytes in various stationary phases in the literature. The usefulness of the proposed model in providing interpretable summaries of complex data and in decision making is discussed.

Metabolic Evaluation of Urine from Patients Diagnosed with High Grade (HG) Bladder Cancer by SPME-LC-MS Method.

Bladder cancer (BC) is a common malignancy of the urinary system and a leading cause of death worldwide. In this work, untargeted metabolomic profiling of biological fluids is presented as a non-invasive tool for bladder cancer biomarker discovery as a first step towards developing superior methods for detection, treatment, and prevention well as to further our current understanding of this disease. In this study, urine samples from 24 healthy volunteers and 24 BC patients were subjected to metabolomic profiling using high throughput solid-phase microextraction (SPME) in thin-film format and reversed-phase high-performance liquid chromatography coupled with a Q Exactive Focus Orbitrap mass spectrometer. The chemometric analysis enabled the selection of metabolites contributing to the observed separation of BC patients from the control group. Relevant differences were demonstrated for phenylalanine metabolism compounds, i.e., benzoic acid, hippuric acid, and 4-hydroxycinnamic acid. Furthermore, compounds involved in the metabolism of histidine, beta-alanine, and glycerophospholipids were also identified. Thin-film SPME can be efficiently used as an alternative approach to other traditional urine sample preparation methods, demonstrating the SPME technique as a simple and efficient tool for urinary metabolomics research. Moreover, this study's results may support a better understanding of bladder cancer development and progression mechanisms.

Metabolomic Insight into Polycystic Ovary Syndrome-An Overview.

Searching for the mechanisms of the polycystic ovary syndrome (PCOS) pathophysiology has become a crucial aspect of research performed in the last decades. However, the pathogenesis of this complex and heterogeneous endocrinopathy remains unknown. Thus, there is a need to investigate the metabolic pathways, which could be involved in the pathophysiology of PCOS and to find the metabolic markers of this disorder. The application of metabolomics gives a promising insight into the research on PCOS. It is a valuable and rapidly expanding tool, enabling the discovery of novel metabolites, which may be the potential biomarkers of several metabolic and endocrine disorders. The utilization of this approach could also improve the process of diagnosis and therefore, make treatment more effective. This review article aims to summarize actual and meaningful metabolomic studies in PCOS and point to the potential biomarkers detected in serum, urine, and follicular fluid of the affected women.

Determination of Urinary Pterins by Capillary Electrophoresis Coupled with LED-Induced Fluorescence Detector.

Urinary pterins have been found as potential biomarkers in many pathophysiological conditions including inflammation, viral infections, and cancer. However, pterins determination in biological samples is difficult due to their degradation under exposure to air, light, and heat. Besides, they occur at shallow concentration levels, and thus, standard UV detectors cannot be used without additional sample preconcentration. On the other hand, ultra-sensitive laser-induced fluorescence (LIF) detection can be used since pterins exhibit native fluorescence. The main factor that limits an everyday use of LIF detectors is its high price. Here, an alternative detector, i.e., light-emitted diode induced fluorescence (LEDIF) detector, was evaluated for the determination of pterins in urine samples after capillary electrophoresis (CE) separation. An optimized method was validated in terms of linearity range, limit of detection (LOD), limit of quantification (LOQ), intra- and interday precision and accuracy, sample stability in the autosampler, and sample stability during the freezing/thawing cycle. The obtained LOD (0.1 µM) and LOQ (0.3 µM) values were three-order of magnitude lower compared to UV detector, and two orders of magnitude higher compared to previously reported house-built LIF detector. The applicability of the validated method was demonstrated in the analysis of urine samples from healthy individuals and cancer patients.

Ionization of tocopherols and tocotrienols in atmospheric pressure chemical ionization.

RATIONALE: Tocopherols and tocotrienols are chemical compounds insusceptible to the ionization process under atmospheric pressure conditions. Therefore, the selection of the optimal ion source settings for their quantification requires special attention. The aim of this study was to analyse the influence of the APCI source parameters on the response of tocochromanols and two related compounds. METHODS: Standard solutions of target compounds were injected on the high-performance liquid chromatography/atmospheric pressure chemical ionization tandem mass spectrometry (HPLC/APCI-MS/MS) system separately and analysed with 30 randomly selected ion source settings. The obtained responses were modelled by multivariate linear regression with least absolute shrinkage and selection operator. The developed models were used to choose the best APCI conditions. RESULTS: Multivariate linear models were built for eight tocochromanols, trolox and BHT. The APCI settings derived from the models did not increase the peak areas obtained for T and T3 during the ionization process. Ionization conditions based on models for trolox and BHT improved analytical responses by 12-36% and 4-32%, respectively. The application of the ion source settings optimal for trolox and BHT to tocochromanols did not result in better analytical responses. CONCLUSIONS: The ionization pattern of tocochromanols in the APCI source is problematic and should be further investigated. Modelling methodology for response improvement presented in this study can be applied in similar studies.

Determination of tocopherols and tocotrienols in human breast adipose tissue with the use of high performance liquid chromatography-fluorescence detection.

Tocopherols and tocotrienols have been extensively studied owing to their anticancer potential, especially against breast cancer. Therefore, the aim of this study was to quantitatively determine tocochromanols in human breast adipose tissue with the use of HPLC-FLD. The sample preparation procedure included homogenization and solvent extraction with isopropanol-ethanol-0.1% formic acid mixture prior to solid-phase extraction. After implementation of central composite design, satisfactory separation of all eight target compounds was achieved within 10.5 min. Chromatographic runs were carried out with the use of a naphthylethyl chromatographic column with methanol-water mixture (89:11, v/v) as the mobile phase. Fluorescence detection of tocochromanols was performed with excitation and emission wavelengths 298 and 330 nm, respectively. The method was validated in terms of linearity, carryover, recovery, precision, accuracy and stability. Extraction yield was also determined for accurate evaluation of vitamin E content in human breast adipose tissue samples. Finally, concentrations of particular tocochromanols compounds were assessed in human breast adipose tissue samples obtained from 99 patients, including women with breast cancer, healthy volunteers and deceased women who had died as a result of accidents. The raw data was transformed according to the newly developed equation for accurate estimation of the concentrations of tocochromanols in breast adipose tissue samples. Results obtained in the study indicated that the proposed analytical assay could be useful in breast cancer research.

Sample Concentration of Charged Small Molecules and Peptides in Capillary Electrophoresis by Micelle to Cyclodextrin Stacking.

A stacking approach in capillary electrophoresis based on the reversal of the analytes' effective electrophoretic velocities at a dynamic stacking boundary formed between charged micelles (i.e., from long chain ionic surfactants) and neutral cyclodextrins (i.e., native α-, ß-, or γ-cyclodextrin) is presented. The approach was demonstrated by the long injection of samples in a micellar solution followed by injection of a cyclodextrin solution zone, and then separation by co-electro-osmotic flow capillary zone electrophoresis. The reversal is caused by the formation of stable cyclodextrin-surfactant complexes at the boundary that significantly decreased the retention factor of the analytes in the presence of a micellar pseudostationary phase. The dynamic boundary was formed at the cyclodextrin zone as the micelles penetrated this zone. Under optimum conditions, the boundary disappears, and the stacking ends when all the micelles have electrophoretically migrated to the boundary. Cationic and anionic small molecules were enriched using oppositely charged micelles from sodium dodecyl sulfate and cetyltrimethylammonium bromide, respectively. There were 1-2 orders of concentration magnitude improvement in analyte detection, which is expected in stacking with hydrodynamic injection. The improvements in the peak signals (height/corrected area) were up to 236/445 and 101/76 for the cationic and anionic analytes tested, respectively. Linearity (r2) and repeatability (%RSD of migration time, peak height, and corrected peak area) under the chosen stacking conditions (cations/anions) were ≥0.998/≥0.995 and ≤3.8%/≤5.7%, respectively. The stacking approach was also implemented in the direct analysis of peptides from trypsin digested bovine serum albumin.

Migration time shift of analytes in micellar electrokinetic chromatography induced by stacking.

A significant shift of migration time of nonretained compounds (ascorbic acid and cysteine) in micellar electrokinetic chromatography was observed under variation of sample matrix composition. The shift was affected by borate buffer concentration in sample matrix, sample injection time, and pH of BGE (80 mM SDS, Tris/HCl). Surprisingly, longer migration time of analyte was recorded at higher pH of separation buffer. These observations were linked to transient isotachophoresis process. Computer simulation with Simul5 software was conducted to support this hypothesis. The manuscript documents rarely reported in the literature phenomenon of isotachophoresis in micellar electrokinetic chromatography. The analytical potential of described observations was also discussed.

How to model temporal changes in nontargeted metabolomics study? A Bayesian multilevel perspective.

Analysis of time series data addresses the question on mechanisms underlying normal physiology and its alteration under pathological conditions. However, adding time variable to high-dimension, collinear, noisy data is a challenge in terms of mining and analysis. Here, we used Bayesian multilevel modeling for time series metabolomics in vivo study to model different levels of random effects occurring as a consequence of hierarchical data structure. A multilevel linear model assuming different treatment effects with double exponential prior, considering major sources of variability and robustness to outliers was proposed and tested in terms of performance. The treatment effect for each metabolite was close to zero suggesting small if any effect of cancer on metabolomics profile change. The average difference in 964 signals for all metabolites varied by a factor ranging from 0.8 to 1.25. The inter-rat variability (expressed as a coefficient of variation) ranged from 3-30% across all metabolites with median around 10%, whereas the inter-occasion variability ranged from 0-30% with a median around 5%. Approximately 36% of metabolites contained outlying data points. The complex correlation structure between metabolite signals was revealed. We conclude that kinetics of metabolites can be modeled using tools accepted in pharmacokinetics type of studies.

Evaluation of sample injection precision in respect to sensitivity in capillary electrophoresis using various injection modes.

A comparative study was conducted to assess the injection precision in capillary electrophoresis for cationic analytes (arecoline, codeine, papaverine). The precision was measured in respect to methods sensitivity in various injection modes in capillary electrophoresis: standard hydrodynamic injection (3.45 kPa for 6 s), large volume sample stacking (3.45 kPa for 40 s), and field-amplified sample injection (10 kV for 65 s). All measurements were conducted for aqueous solutions of standards to minimize the errors linked to the sample preparation step. The methods were submitted to precision assessment at three concentration levels: at the limit of quantification, three-fold and ten-fold of limit of quantification. The results were compared to those from high-performance liquid chromatography as a reference technique. The field-amplified sample injection method was shown to provide greatest sensitivity (quantification limits down to 4 ng/mL for all three tested compounds) but the lowest precision. High-performance liquid chromatography was established as the most reliable technique (coefficient of variation in all intraday experiments was below 1%). It was also shown that with a use of large volume sample injection technique, similar sensitivity as in high-performance liquid chromatography can be easily reached.

Sweeping of hydrophobic amines under inhomogeneous electric field and low surfactant concentration in micellar electrokinetic chromatography.

The influence of sample matrix on sample sweeping in MEKC was examined in the presented manuscript. Significant focusing effect was observed for relatively hydrophobic cationic compounds (emetine, strychnine and quinine) using high ionic strength sample matrix (900 mM H3 PO4 /720 mM Tris) which conductivity was about ninefold higher than utilized BGE. Moreover, the results were obtained using BGE composed of comparatively low surfactant concentration (10 mM SDS) and 40 mM H3 PO4 /32 mM Tris buffer solution. About 200 to 300-fold preconcentration of analytes was reached with the presented method. Basing on experimental results and computer simulation using Simul5 software, hypothetical mechanism of observed phenomenon was proposed.

Multidimensional capillary electrophoresis.

Multidimensional separation where two or more orthogonal displacement mechanisms are combined is a promising approach to increase peak capacity in CE. The combinations allow dramatic improvement of analytical performance since the total peak capacity is given by a product of the peak capacities of all methods. The initial reports were concentrated on the construction of effective connections between capillaries for 2D analysis. Today, 2D and 3D CE systems are now able to separate real complex biological or environmental mixtures with good repeatability, improved resolution with minimal loss of sample. This review will present the developments in the field of multidimensional CE during the last 15 years. The endeavors in this specific field were on the development of interfaces, interface-free techniques including integrated separations, microdevices, and on-line sample concentration techniques to improve detection sensitivity.

A comparative quantitative structure-retention relationships study for lipophilicity determination of compounds with a phenanthrene skeleton on cyano-, reversed phase-, and normal phase-thin layer chromatography stationary phases.

The phenanthrene skeleton is an important moiety in medical chemistry as it is present in steroidal drugs used as anti-inflammatory and anti-asthmatic agents as well as synthetic hormones or potassium sparing diuretics. Chromatographic properties of 14 derivatives containing the phenanthrene skeleton in their structure with known lipophilicity have been studied. NP, RP, and cyano-bonded silica stationary phases with three binary mobile phases (acetonitrile-water, acetone-water, and acetone-petroleum ether) were tested. Obtained chromatographic data were correlated with the lipophilicity expressed as values of log partition coefficient (P). The presented study was undertaken to find the best TLC system and chromatographic data processing method in order to predict log P values. Correlations between chromatographic data and measurements of lipophilicity of compounds were presented as results of established quantitative structure-retention relationships. Principal component analysis and cluster analysis were used to investigate the similarities among chromatographic systems.

Development and validation of UHPLC method for the determination of cyclosporine A in biological samples.

The aim of the study was to develop and validate a simple and rapid method for the determination of cyclosporine A (CsA) in ocular rabbit tissues using reversed-phase ultra-high-performance liquid chromatography (UHPLC) with UV detection. Previous publications on chromatographic methods of CsA determination in ocular tissues involved only reversed-phase HPLC separation, usually in combination with such detection techniques as radio-immunoassay and mass spectrometry. The application of the UHPLC technique allowed us to significantly decrease the analysis time. Cyclosporine D (CsD) was applied as the internal standard. Satisfactory separation was achieved on an XB-C18 Kinetex column at 60°C with the use of gradient elution mode. The retention times of CsA and CsD were found to be 4.5 and 5.1 min, respectively. The developed assay is specific, sensitive (limit of detection = 6 ng/mL and limit of quantitation = 18 ng/mL) and linear within the analyte concentration range of 0.018-5 µg/mL, with a correlation coefficient of 0.999. High sensitivity, low injection volume (10 µL), short time of analysis (6.5 min) and simplicity make this method useful for the fast analysis of CsA in rabbit ocular tissues and fluids: lacrimal fluid, aqueous humor, cornea, conjunctiva and eye globe.

C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning.

The rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation of various origins, oncological, cardiovascular, bacterial or viral events. In this study, we describe an interferometric sensor able to detect the CRP level for distinguishing between no-inflammation and inflammation states. The measurement head was made of a single mode optical fiber with a microsphere structure created at the tip. Its surface has been biofunctionalized for specific CRP bonding. Standardized CRP solutions were measured in the range of 1.9 µg/L to 333 mg/L and classified in the initial phase of the study. The real samples obtained from hospitalized patients with diagnosed Urinary Tract Infection or Urosepsis were then investigated. 27 machine learning classifiers were tested for labeling the phantom samples as normal or high CRP levels. With the use of the ExtraTreesClassifier we obtained an accuracy of 95% for the validation dataset. The results of real samples classification showed up to 100% accuracy for the validation dataset using XGB classifier.

Clinical image of sepsis-associated encephalopathy midst E. coli urosepsis: Emergency department database study.

Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, which, if untreated, leads to multi-organ failure. One of the severe possible complications is sepsis associated encephalopathy (SAE), a neurological dysfunction occurring secondary to a severe inflammatory response. It manifests as acute cognitive dysfunction and sudden-onset dysfunctions in mental state. Uropathogenic Escherichia coli is the most common pathogen causing bacteremia, responsible for 80% of uncomplicated outpatient urinary tract infections and 40% of nosocomial infections. The study aimed to assess the difference in the severity and the course of urosepsis caused by E. coli in patients with and without septic encephalopathy. Materials and methods: This study presents a retrospective analysis of the population of urosepsis patients admitted to the Emergency Department between September 2019 and June 2022. Inflammatory parameters, urinalysis and blood cultures were performed, along with a clinical evaluation of sepsis severity and encephalopathy. The patients were then stratified into SAE and non-SAE groups based on neurological manifestations and compared according to the collected data. Results: A total of 199 septic patients were included in the study. E. coli-induced urosepsis was diagnosed in 84 patients. In this group, SAE was diagnosed in 31 (36.9%) patients (33.3% in males, 40.5% females). Patients with SAE were found to be hypotensive (p < 0,005), with a higher respiratory rate (p < 0,017) resulting in a higher mortality rate (p = 0.002) compared to non-SAE septic patients. The APACHE II score was an independent risk factor associated with a higher mortality rate. Biochemical parameters between the groups did not show any statistical importance related to the severity of urosepsis. Conclusions: The severity of urosepsis and risk of SAE development increase according to the clinical condition and underlying comorbidities. Urosepsis patients with SAE are at a higher risk of death. Patients should undergo more careful screening for the presence of SAE on admission, and more intense monitoring and treatment should be provided for patients with SAE. This study indicates the need to develop projects aiming to further investigate neuroprotective interventions in sepsis.

Chasing Graphene-Based Anticancer Drugs: Where are We Now on the Biomedical Graphene Roadmap?

Graphene and graphene-based materials have attracted growing interest for potential applications in medicine because of their good biocompatibility, cargo capability and possible surface functionalizations. In parallel, prototypic graphene-based devices have been developed to diagnose, imaging and track tumor growth in cancer patients. There is a growing number of reports on the use of graphene and its functionalized derivatives in the design of innovative drugs delivery systems, photothermal and photodynamic cancer therapy, and as a platform to combine multiple therapies. The aim of this review is to introduce the latest scientific achievements in the field of innovative composite graphene materials as potentially applied in cancer therapy. The "Technology and Innovation Roadmap" published in the Graphene Flagship indicates, that the first anti-cancer drugs using graphene and graphene-derived materials will have appeared on the market by 2030. However, it is necessary to broaden understanding of graphene-based material interactions with cellular metabolism and signaling at the functional level, as well as toxicity. The main aspects of further research should elucidate how treatment methods (e.g., photothermal therapy, photodynamic therapy, combination therapy) and the physicochemical properties of graphene materials influence their ability to modulate autophagy and kill cancer cells. Interestingly, recent scientific reports also prove that graphene nanocomposites modulate cancer cell death by inducing precise autophagy dysfunctions caused by lysosome damage. It turns out as well that developing photothermal oncological treatments, it should be taken into account that near-infrared-II radiation (1000-1500 nm) is a better option than NIR-I (750-1000 nm) because it can penetrate deeper into tissues due to less scattering at longer wavelengths radiation.