Publications by authors named "Michal Markuszewski"

Atrial fibrillation (AF) is the most frequent arrhythmia in the adult population associated with a high rate of severe consequences leading to significant morbidity and mortality worldwide. Therefore, its prompt recognition is of high clinical importance. AF detection often remains challenging due to unspecific symptoms and a lack of reliable biomarkers for its prediction.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Gestational diabetes mellitus (GDM) is a disorder which manifests itself for the first time during pregnancy and is mainly connected with glucose metabolism. It is also known that fatty acid profile changes in erythrocyte membranes and plasma could be associated with obesity and insulin resistance. These factors can lead to the development of diabetes.

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Article Synopsis
  • Breath analysis is a noninvasive method for monitoring biochemical processes and identifying health issues in the body.
  • While it has the potential to revolutionize diagnostics, it necessitates collaboration among multiple specialists due to its complexity.
  • The review aims to establish standardized experimental strategies to improve the reliability and reproducibility of breath analysis as a diagnostic tool.
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Article Synopsis
  • Renal cell carcinoma (RCC) lacks specific diagnostic methods and treatments, necessitating the evaluation of new diagnostic tools and treatment options.
  • This study utilized multiplatform untargeted metabolomics analysis of urine from RCC patients and healthy volunteers to identify unique metabolic patterns associated with RCC and its subtype, clear cell renal cell carcinoma (ccRCC).
  • Analyses revealed two panels of specific metabolites linked to RCC, highlighting disruptions in amino acid, lipid, and purine metabolism, with notable findings in modified nucleosides and significant changes in symmetric dimethylarginine (SDMA) levels in RCC patients.
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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.

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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.

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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.

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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.

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Recently, the diagnostic methods used by scientists in forensic examinations have enormously expanded. Metabolomics provides an important contribution to analytical method development. The main purpose of this review was to investigate and summarize the most recent applications of metabolomics in forensic science.

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Gastrointestinal stromal tumour has already been well explored at the genome level; however, little is known about metabolic processes occurring in the sarcoma. Sample preparation is a crucial step in untargeted metabolomics workflow, highly affecting the metabolome coverage and the quality of the results. In this study, four liquid-liquid extraction methods for the isolation of endogenous compounds from gastrointestinal stromal tumours were compared and evaluated.

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Renal dysplasia is a severe congenital abnormality of the kidney parenchyma, which is an important cause of end-stage renal failure in childhood and early adulthood. The diagnosis of renal dysplasia relies on prenatal or postnatal ultrasounds as children show no specific clinical symptoms before chronic kidney disease develops. Prompt diagnosis is important in terms of early introduction of nephroprotection therapy and improved long-term prognosis.

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