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.

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.

Determination of urinary androgens in women with polycystic ovary syndrome using LC-QqQ/MS and the application of thin film solid-phase microextraction (TF-SPME).

Hyperandrogenism is one of the most pronounced symptoms of Polycystic Ovary Syndrome (PCOS) and seems to play a key role in the pathogenesis of this complex disorder. Nevertheless, there is still a lack of consistent results regarding common steroid predictors of PCOS. Therefore, a liquid chromatography tandem mass spectrometry (HPLC-QqQ/MS) method was developed and validated to determine the concentrations of four classic androgens: androstenedione (An-dione), testosterone (T), 5α-dihydrotestosterone (DHT) and androsterone (An) in urine samples obtained from women with PCOS and healthy controls. The limits of detection were between 0.04 and 0.09 ng/mL, while the limits of quantification ranged from 0.1 to 0.3 ng/mL respectively. As a pre-treatment procedure prior to analysis, hydrolysis using ß-glucuronidase and thin film solid-phase microextraction (TF-SPME) was applied. The methodology was employed to perform targeted metabolomics of urinary steroids in women with PCOS and healthy controls. All measured androgens: An-dione (p < 0.0001), T (p = 0.0001), DHT (p < 0.0001) and An (p = 0.0002) showed significantly higher concentrations in the urine of women with PCOS. The largest difference in the mean concentration was found for DHT, which was 2.8 times higher in the PCOS group (13.9 ± 14.1 ng/mg creatinine) in comparison to healthy controls (4.9 ± 3.4 ng/mg creatinine). The results of receiver operating characteristic curve indicated that determination of the panel of three urinary androgens: T+DHT+An-dione with, under the study assumptions, was the best predictor of PCOS diagnosis (AUC of ROC curve = 0.91 (95 % CI: 0.8212-0.9905). The application of an LC-MS/MS-based analysis, together with highly sensitive extraction techniques like TF-SPME, is a suitable approach to perform fast assays and obtain reliable results - crucial in the search for valuable and significant steroids predictors of PCOS.

Microscopic and Biopharmaceutical Evaluation of Emulsion and Self-Emulsifying Oil with Cyclosporine.

Among the currently available commercial eye drops with cyclosporine A (Cs) there is a lack of long-acting dosage forms and products with a concentration of the drug substance higher than 0.1%, although Cs is widely used in ophthalmology. The aim of the research was to conduct the microscopic and biopharmaceutical evaluation of two formulations, an emulsion (EM) and a self-emulsifying oil (SEO), both with 0.5% of Cs, proposed for use in eye drops, and the comparison of both. SEO eye drops with Cs or any other drug substance are currently not available as marketed products, and the highest concentration of Cs in the ocular emulsion is only 0.1%. The microscopic evaluation of the emulsion and the SEO after emulsification with water was carried out using a high-resolution digital microscopy. The properties of both preparations were compared using the high dynamic range function or optical shadow effect mode. Images in the 3D composition mode were also recorded. The in vivo study of the Cs formulations was performed on male albino rabbits. The eye tolerance of the preparations was assessed using the ocular irritation test, which is a modified Draize test. Placebo carriers (without the drug substance) were also subjected to irritation testing. The concentration of Cs in the tissues (cornea and conjunctiva) and fluids (tear fluid and aqueous humor) of the rabbit eye was determined after multiple instillations of Cs-EM or Cs-SEO. The tested preparations were compared using the digital microscopy technique, which highlights the features of the formulations and eliminates the risk of unnoticeable properties that are difficult to observe in classical optical microscopy. Both tested Cs-loaded formulations are classified as practically non-irritating. There were also no significant differences when testing the placebo carriers. After a topical administration, Cs was widely distributed in all tissues (e.g., in cornea 1.3 ng/mg and 1.0 ng/mg) and fluids of the eye (e.g., in tear fluid 11.6 µg/mL and 4.3 µg/mL), after the administration of Cs-SEO and Cs-EM, respectively. The obtained results allow us to recognize both tested formulations, the emulsion and the self-emulsifying oil with 0.5% Cs content, as carriers safe for ophthalmic use and effective in delivering the drug substance to the structures of the eye.

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.

Plasma untargeted metabolomics with proteinase K discloses phospholipid signature associated with pulmonary arterial hypertension.

Pulmonary arterial hypertension is a rare but life-threatening and clinically heterogeneous disease. The diagnostic schedule of this disorder is complex, and no specific indicator of the arterial etiology has been explored. In this study, untargeted plasma metabolomics was applied to evaluate the metabolic fingerprints of pulmonary arterial hypertension patients. Plasma samples were prepared using a new approach, which applies proteinase K during the sample preparation procedure to increase the metabolite coverage. The metabolic fingerprints were determined via LC-MS and subsequently analyzed with the use of both uni- and multivariate statistics. A total of 21 metabolites were discovered to be significantly altered in pulmonary arterial hypertensive patients. The metabolites were mainly related to the phospholipid metabolic pathways. In this study, decreases were found in the phosphatidylcholines (PCs) [PC(32:0), PC(40:7), PC(42:7)], phosphatidylethanolamine PE(18:0/18:2), lysophosphatidylethanolamines (LPEs) [LPE(22:6), LPE(18:2), LPE(18:0), LPE(20:4), LPE(20:1), LPE(20:0)], lysophosphatidylcholine LPC(20:4) and lysophosphatidylserine LPS(19:0), as well as increase of sphingomyelin SM(36:2), in the plasma samples of pulmonary arterial hypertensive patients in comparison to the control group. Besides their function as components of the biological membranes, these metabolites are also involved in the intracellular signaling pathways that are related to cell proliferation and apoptosis. The results obtained during this study confirm the potential of (untargeted) metabolomics to identify the molecular characteristics of the pathophysiology of pulmonary arterial hypertension. The clinical relevance of this study constitutes the selection of a metabolic panel that can potentially detect and properly diagnose the disease.

Searching for the primary metabolic alterations of polycystic ovary syndrome by application of the untargeted metabolomics approach.

Despite a large number of studies, the pathogenesis of polycystic ovary syndrome (PCOS) still remains unexplained. In light of ambiguous observations reported in metabolomics, there is a need to carry out studies focusing on confirming the discriminating power of the proposed metabolomics biomarkers. Our research aimed to perform a validation study of metabolites detected in our previous study from serum samples, on the new set of samples obtained from PCOS women and healthy controls to confirm previously selected compounds. Additionally, the second biological matrix - urine - was used to get a more comprehensive insight into metabolic alterations. We applied two analytical techniques - gas chromatography and liquid chromatography coupled with mass spectrometry to analyze both serum and urine samples obtained from 35 PCOS patients and 35 healthy women. Thank to our approach, we identified and described a comprehensive set of metabolites altered in PCOS patients. Results of our study indicate increased steroid hormone synthesis, alteration in sphingo- and phospholipids metabolism, and disturbed fatty acids metabolism. Moreover, the citric acid cycle, γ-glutamyl cycle, vitamin B metabolism, and a few primary amino acids like tryptophan, phenylalanine, histidine, and alanine are altered.

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.

Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment.

The study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain up to 97% accuracy of the measurement method with the use of use of machine learning. The method was validated on urine samples from 241 patients. The advantages of the proposed solution are the simplicity of the sensor, mobility, versatility, and low cost of the test.

Development of the thin film solid phase microextraction (TF-SPME) method for metabolomics profiling of steroidal hormones from urine samples using LC-QTOF/MS.

In the present study, the development and optimization of a thin film solid phase microextraction method (TF-SPME) was conducted for metabolomics profiling of eight steroid compounds (androsterone, dihydrotestosterone, dihydroepiandrosterone, estradiol, hydroxyprogesterone, pregnenolone, progesterone and testosterone) from urine samples. For optimization of extraction method, two extraction sorbents (PAN-C18 and PS-DVB) were used as they are known to be effective for isolation of low-polarity analytes. The stages of sample extraction and analyte desorption were considered as the most crucial steps in the process. Regarding the selection of the most suitable desorption solution, six different mixtures were analyzed. As a result, the mixture of ACN: MeOH (1:1, v/v) was chosen in terms of the highest analytes' abundances that were achieved using the chosen solvent. Besides other factors were examined such as the volume of desorption solvent and the time of both extraction and desorption processes. The analytical determination was carried out using the ultra-high performance liquid chromatography coupled with high resolution tandem mass spectrometry detection in electrospray ionization and positive polarity in a scan mode (UHPLC-ESI-QTOF/MS). The developed and optimized TF-SPME method was validated in terms of such parameters as extraction efficiency, recovery as well as matrix effect. As a result, the extraction efficiency and recovery were in a range from 79.3% to 99.2% and from 88.8% to 111.8%, respectively. Matrix effect, calculated as coefficient of variation was less than 15% and was in a range from 1.4% to 11.1%. The values of both validation parameters (recovery and matrix effect) were acceptable in terms of EMA criteria. The proposed TF-SPME method was used successfully for isolation of steroids hormones from pooled urine samples before and after enzymatic hydrolysis of analytes.

Metabolomic and transcriptomic response to imatinib treatment of gastrointestinal stromal tumour in xenograft-bearing mice.

BACKGROUND: Although imatinib is a well-established first-line drug for treating a vast majority of gastrointestinal stromal tumours (GIST), GISTs acquire secondary resistance during therapy. Multi-omics approaches provide an integrated perspective to empower the development of personalised therapies through a better understanding of functional biology underlying the disease and molecular-driven selection of the best-targeted individualised therapy. In this study, we applied integrative metabolomic and transcriptomic analyses to elucidate tumour biochemical processes affected by imatinib treatment. MATERIALS AND METHODS: A GIST xenograft mouse model was used in the study, including 10 mice treated with imatinib and 10 non-treated controls. Metabolites in tumour extracts were analysed using gas chromatography coupled with mass spectrometry (GC-MS). RNA sequencing was also performed on the samples subset (n=6). RESULTS: Metabolomic analysis revealed 21 differentiating metabolites, whereas next-generation RNA sequencing data analysis resulted in 531 differentially expressed genes. Imatinib significantly changed the profile of metabolites associated mainly with purine and pyrimidine metabolism, butanoate metabolism, as well as alanine, aspartate, and glutamate metabolism. The related changes in transcriptomic profiles included genes involved in kinase activity and immune responses, as well as supported its impact on the purine biosynthesis pathway. CONCLUSIONS: Our multi-omics study confirmed previously known pathways involved in imatinib anticancer activity as well as correlated imatinib-relevant downregulation of expression of purine biosynthesis pathway genes with the reduction of respectful metabolites. Furthermore, considering the importance of the purine biosynthesis pathway for cancer proliferation, we identified a potentially novel mechanism for the anti-tumour activity of imatinib. Based on the results, we hypothesise metabolic modulations aiming at the reduction in purine and pyrimidine pool may ensure higher imatinib efficacy or re-sensitise imatinib-resistant tumours.

Molecular signature of renal cell carcinoma by means of a multiplatform metabolomics analysis.

Renal cell carcinoma (RCC) is a disease with no specific diagnostic method or treatment. Thus, the evaluation of novel diagnostic tools or treatment possibilities is essential. In this study, a multiplatform untargeted metabolomics analysis of urine was applied to search for a metabolic pattern specific for RCC, which could enable comprehensive assessment of its biochemical background. Thirty patients with diagnosed RCC and 29 healthy volunteers were involved in the first stage of the study. Initially, the utility of the application of the selected approach was checked for RCC with no differentiation for cancer subtypes. In the second stage, this approach was used to study clear cell renal cell carcinoma (ccRCC) in 38 ccRCC patients and 38 healthy volunteers. Three complementary analytical platforms were used: reversed-phase liquid chromatography coupled with time-of-flight mass spectrometry (RP-HPLC-TOF/MS), capillary electrophoresis coupled with time-of-flight mass spectrometry (CE-TOF/MS), and gas chromatography triple quadrupole mass spectrometry (GC-QqQ/MS). As a result of urine sample analyses, two panels of metabolites specific for RCC and ccRCC were selected. Disruptions in amino acid, lipid, purine, and pyrimidine metabolism, the TCA cycle and energetic processes were observed. The most interesting differences were observed for modified nucleosides. This is the first time that the levels of these compounds were found to be changed in RCC and ccRCC patients, providing a framework for further studies. Moreover, the application of the CE-MS technique enabled the determination of statistically significant changes in symmetric dimethylarginine (SDMA) in RCC.

Metabolically Doping of 3D Diatomaceous Biosilica with Titanium.

Diatoms represent, in terms of species number, one of the largest groups of microalgae that have the ability to synthesize phenomenal mineral composites characterized by complex hierarchical structures. Their shells, called frustules, create intricately ornamented structures, reminiscent of the most sophisticated, natural mosaics. Ordinated pore systems perforate siliceous walls of the frustules with diameters ranging from nano to micro-scale, forming openwork three-dimensional silica structures. The use of these features is one of the main challenges in developing new technological solutions. In this study we assess the ability of selected diatom species (Pseudostaurosira trainorii) for metabolic insertion of soluble titanium from the culture medium into the structure of amorphous silica cell walls by its cultivation in laboratory conditions. The study is aimed at obtaining new and strengthening the already existing optical properties of diatomaceous biosilica. The physicochemical properties of the obtained materials have been studied using a series of instrumental methods.

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.

Binding indocyanine green to human serum albumin potentially enhances the detection of sentinel lymph nodes. An initial step for facilitating the detection of first-station nodes in penile and other urological cancers.

Introduction: Surgical oncology strives to remove the primary cancer tumor together with its local lymphatic tissue. One of the techniques improving the staging of lymph nodes is sentinel node biopsy. The most common agent used in SNB is indocyanine green (ICG). Indocyanine green is characterized by its high affinity for human serum albumin (HSA). In practice, the visualization of the sentinel node is enhanced by attaching a relatively large carrier to the ICG molecule. The aim of this study was to investigate whether the covalent linking of ICG to a nanocolloid would extend the time of detection of the dye as it binds to HSA, assessed by fluorescence measurements in vitro. Material and methods: The influence of the molar concentration of ICG on its ability to form a complex with HSA was investigated. The dye luminescence was measured, with an increasing amount of dye in the presence of a constant concentration of HSA. The stability of the ICG:HSA complex was also investigated. Results: The binding of ICG and human protein in a solution ratio of 3 : 1 made it possible to detect the ICG luminescence with better and prolonged visibility. In the case of the two lowest ratios, complex formation was not observed. The use of ICG bound to a nanocolloid based on human serum albumin increases the luminescence of the HSA : ICG complex up to 98%. Conclusions: Properly selected proportions of human albumin protein and ICH allowed higher and longer luminescence to be achieved. Nevertheless, further studies are necessary to establish the optimal concentration ratio.

Untargeted Metabolomics Study of Three Matrices: Seminal Fluid, Urine, and Serum to Search the Potential Indicators of Prostate Cancer.

The simultaneous determination of metabolites from biological fluids may provide more accurate information about the current body condition. So far, the metabolomics approach has been successfully applied to study the mechanism of several disorders and to search for novel biomarkers. Urine and plasma are widely accepted matrices for the evaluation of several pathologies, while prostate cancer (CaP) development is still unknown. For this reason, an alternative matrix, the seminal fluid, was proposed to expand the knowledge about the CaP pathomechanism. The main aim of this study was to develop and optimize the sample preparation protocol to ensure the highest coverage of the metabolome of ejaculate samples. Parameters like the type and composition of the solvent mixture, time of extraction, and applied volume of the solvent were tested. The optimized method was applied for the untargeted metabolomics profiling of seminal fluid samples obtained from CaP patients. Moreover, urine and serum samples were also prepared for untargeted metabolomics analysis. Analyses were carried out with the use of two complementary analytical techniques: GC-EI-QqQ/MS and LC-ESI-TOF/MS. Finally, the metabolic signature of seminal fluid (n = 7), urine (n = 7), and plasma (n = 7) samples was compared. Furthermore, the hypothesis of the increased level of metabolites in ejaculate samples related to the CaP development was evaluated. The results indicated that the developed and optimized sample preparation protocol for seminal fluid may be successfully applied for metabolomics study. Untargeted analysis of ejaculate enabled to determine the following classes of compounds: fatty acids, sphingolipids, phospholipids, sugars, and their derivatives, as well as amino acids. Finally, a comparison of the three tested matrices was carried out. To our best knowledge, it is the first time when the metabolic profile of the three matrices, namely, urine, plasma, and seminal fluid, was compared. Based on the results, it can be pointed out that ejaculate comprises the metabolic signature of both matrices (polar compounds characteristic for urine, and non-polar ones present in plasma samples). Compared to plasma, semen samples revealed to have a similar profile; however, determined levels of metabolites were lower in case of ejaculate. In case of urine samples, compared to semen metabolic profiles, the levels of detected metabolites were decreased in the latter ones.

Pre- and Post-Resection Urine Metabolic Profiles of Bladder Cancer Patients: Results of Preliminary Studies on Time Series Metabolomics Analysis.

The incidence of bladder cancer (BCa) has remained high for many years. Nevertheless, its pathomechanism has not yet been fully understood and is still being studied. Therefore, multiplatform untargeted urinary metabolomics analysis has been performed in order to study differences in the metabolic profiles of urine samples collected at three time points: before transurethral resection of bladder tumor (TURBT), the day after the procedure and two weeks after TURBT. Collected samples were analyzed with the use of high-performance liquid chromatography hyphenated with time-of-flight mass spectrometry detection (HPLC-TOF/MS) and gas chromatography coupled with triple quadrupole mass spectrometry detection (GC-QqQ/MS, in a scan mode). Levels of metabolites selected in our previous study were assessed in order to confirm their potential to differentiate the healthy and diseased samples, regardless of the risk factors and individual characteristics. Hippuric acid, pentanedioic acid and uridine confirmed their potential for sample differentiation. Based on the results of statistical analysis for the paired samples (comparison of metabolic profiles of samples collected before TURBT and two weeks after), a set of metabolites belonging to nucleotide metabolism and methylation processes was also selected. Longitudinal studies proved to be useful for the evaluation of metabolic changes in bladder cancer.

Common Strategies and Factors Affecting Off-Line Breath Sampling and Volatile Organic Compounds Analysis Using Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS).

An analysis of exhaled breath enables specialists to noninvasively monitor biochemical processes and to determine any pathological state in the human body. Breath analysis holds the greatest potential to remold and personalize diagnostics; however, it requires a multidisciplinary approach and collaboration of many specialists. Despite the fact that breath is considered to be a less complex matrix than blood, it is not commonly used as a diagnostic and prognostic tool for early detection of disordered conditions due to its problematic sampling, analysis, and storage. This review is intended to determine, standardize, and marshal experimental strategies for successful, reliable, and especially, reproducible breath analysis.