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.

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.

The state-of-the-art determination of urinary nucleosides using chromatographic techniques "hyphenated" with advanced bioinformatic methods.

Over the last decade metabolomics has gained increasing popularity and significance in life sciences. Together with genomics, transcriptomics and proteomics, metabolomics provides additional information on specific reactions occurring in humans, allowing us to understand some of the metabolic pathways in pathological processes. Abnormal levels of such metabolites as nucleosides in the urine of cancer patients (abnormal in relation to the levels observed in healthy volunteers) seem to be an original potential diagnostic marker of carcinogenesis. However, the expectations regarding the diagnostic value of nucleosides may only be justified once an appropriate analytical procedure has been applied for their determination. The achievement of good specificity, sensitivity and reproducibility of the analysis depends on the right choice of the phases (e.g. sample pretreatment procedure), the analytical technique and the bioinformatic approach. Improving the techniques and methods applied implies greater interest in exploration of reliable diagnostic markers. This review covers the last 11 years of determination of urinary nucleosides conducted with the use of high-performance liquid chromatography in conjunction with various types of detection, sample pretreatment methods as well as bioinformatic data processing procedures.

Metabolomic approach for determination of urinary nucleosides as potential tumor markers using electromigration techniques.

In the postgenome-sequencing era, several large projects have been running recently. Proteomics and other analysis or structural biology are the most active today. Since the late 1990 s, metabolomics has been gaining importance in systems biology, as it provides real-world end points that complement and help in the interpretation of genomic and proteomic data. Comprehensive information about the level changes of numerous metabolites present in the analyzed samples is essential in metabolomic studies. Therefore, the applied analytical techniques must be suitable for the simultaneous analysis of a diverse range of low-molecular-mass endogenous metabolites such as nucleosides at various concentrations and in different matrices, in particular, in urine and serum. In the view of metabolomic study, this domain is obviously significant to understand specific humans' reactions and it can be perceived as a diagnostic and predictive tool in pathological reactions. Since the term "metabolom" has occurred in common scientific use, there have been many publications about possible ways of analysis of nucleosides as metabolites of either oxidative DNA damage or RNA's turnover that are used as the potential tumor markers. Besides, the availability of fast, reproducible and easy to apply analytical techniques that would allow the identification of a large number of metabolites is highly desirable since they may provide detailed information about the progression of a pathological process. This paper, which describes the most relevant electromigration techniques, covers the period starting from the review of Karl H. Schram (Mass Spectrom. Rev. 1998, 17, 131-251) up to the beginning of 2009.

An Overview of the Application of Systems Biology in an Understanding of Chronic Rhinosinusitis (CRS) Development.

Chronic rhinosinusitis (CRS) is an inflammatory disease of the paranasal sinuses. It is defined as the presence of a minimum of two out of four main symptoms such as hyposmia, facial pain, nasal blockage, and discharge, which last for 8-12 weeks. CRS significantly impairs a patient's quality of life. It needs special treatment mainly focusing on preventing local infection/inflammation with corticosteroid sprays or improving sinus drainage using nasal saline irrigation. When other treatments fail, endoscopic sinus surgery is considered an effective option. According to the state-of-the-art knowledge of CRS, there is more evidence suggesting that it is more of an inflammatory disease than an infectious one. This condition is also treated as a multifactorial inflammatory disorder as it may be triggered by various factors, such as bacterial or fungal infections, airborne irritants, defects in innate immunity, or the presence of concomitant diseases. Due to the incomplete understanding of the pathological processes of CRS, there is a continuous search for new indicators that are directly related to the pathogenesis of this disease-e.g., in the field of systems biology. The studies adopting systems biology search for possible factors responsible for the disease at genetic, transcriptomic, proteomic, and metabolomic levels. The analyses of the changes in the genome, transcriptome, proteome, and metabolome may reveal the dysfunctional pathways of inflammatory regulation and provide a clear insight into the pathogenesis of this disease. Therefore, in the present paper, we have summarized the state-of-the-art knowledge of the application of systems biology in the pathology and development of CRS.

The application of gradient reversed-phase high-performance liquid chromatography to the pK(a) and log k(w) determination of polyprotic analytes.

The purpose of this work was to propose a theoretical model of the combined pH/organic modifier gradient in reversed-phase high-performance liquid chromatography (RP HPLC) with special emphasis on its applicability to polyprotic analytes. The model was developed and approximated to be useful for a data set comprising organic modifier gradients obtained at different pH changes and different gradient durations. It was evaluated regarding its ability to describe experimental data. The chromatographic pK(a) and lipophilicity parameter, log k(w), were obtained by fitting to the proposed model and comparing to the literature values.

Urinary Nucleosides and Deoxynucleosides.

Urinary nucleosides and deoxynucleosides are mainly known as metabolites of RNA turnover and oxidative damage of DNA. For several decades these metabolites have been examined for their potential use in disease states including cancer and oxidative stress. Subsequent improvements in analytical sensitivity and specificity have provided a reliable means to measure these unique molecules to better assess their relationship to physiologic and pathophysiologic conditions. In fact, some are currently used as antiviral and antitumor agents. In this review we provide insight into their molecular characteristics, highlight current separation techniques and detection methods, and explore potential clinical usefulness.

Multilevel pharmacokinetics-driven modeling of metabolomics data.

INTRODUCTION: Multilevel modeling is a quantitative statistical method to investigate variability and relationships between variables of interest, taking into account population structure and dependencies. It can be used for prediction, data reduction and causal inference from experiments and observational studies allowing for more efficient elucidation of knowledge. OBJECTIVES: In this study we introduced the concept of multilevel pharmacokinetics (PK)-driven modelling for large-sample, unbalanced and unadjusted metabolomics data comprising nucleoside and creatinine concentration measurements in urine of healthy and cancer patients. METHODS: A Bayesian multilevel model was proposed to describe the nucleoside and creatinine concentration ratio considering age, sex and health status as covariates. The predictive performance of the proposed model was summarized via area under the ROC, sensitivity and specificity using external validation. RESULTS: Cancer was associated with an increase in methylthioadenosine/creatinine excretion rate by a factor of 1.42 (1.09-2.03) which constituted the highest increase among all nucleosides. Age influenced nucleosides/creatinine excretion rates for all nucleosides in the same direction which was likely caused by a decrease in creatinine clearance with age. There was a small evidence of sex-related differences for methylthioadenosine. The individual a posteriori prediction of patient classification as area under the ROC with 5th and 95th percentile was 0.57(0.5-0.67) with sensitivity and specificity of 0.59(0.42-0.76) and 0.57(0.45-0.7), respectively suggesting limited usefulness of 13 nucleosides/creatinine urine concentration measurements in predicting disease in this population. CONCLUSION: Bayesian multilevel pharmacokinetics-driven modeling in metabolomics may be useful in understanding the data and may constitute a new tool for searching towards potential candidates of disease indicators.

New sorbent materials for selective extraction of cocaine and benzoylecgonine from human urine samples.

An increase in cocaine consumption has been observed in Europe during the last decade. Benzoylecgonine, as a main urinary metabolite of cocaine in human, is so far the most reliable marker of cocaine consumption. Determination of cocaine and its metabolite in complex biological samples as urine or blood, requires efficient and selective sample pretreatment. In this preliminary study, the newly synthesized sorbent materials were proposed for selective extraction of cocaine and benzoylecgonine from urine samples. Application of these sorbent media allowed to determine cocaine and benzoylecgonine in urine samples at the concentration level of 100ng/ml with good recovery values as 81.7%±6.6 and 73.8%±4.2, respectively. The newly synthesized materials provided efficient, inexpensive and selective extraction of both cocaine and benzoylecgonine from urine samples, which can consequently lead to an increase of the sensitivity of the current available screening diagnostic tests.

Statistical-based approach in potential diagnostic application of urinary nucleosides in urogenital tract cancer.

AIM: We aimed at evaluation the potential diagnostic role of urinary nucleosides in urogenital tract cancer. MATERIALS & METHODS: Concentrations of 12 nucleosides determined by LC-MS/MS were subjected to correlation, association and interaction analyses. RESULTS: We identified six pairs of nucleosides differently correlated in the group of patients and controls (p < 0.05). N-2-methylguanosine (odds ratio: 4.82; 95% CI: 1.78-12.93; p = 0.002) and N,N-dimethylguanosine (odds ratio: 5.45; 95% CI: 1.78-16.44; p = 0.003), were significantly associated with the disease risk (p-corrected = 0.004). Interaction between N-2-methylguanosine and adenosine (p-interaction = 0.019) suggested their multiplicative effect on the outcome. CONCLUSION: Urinary nucleosides, namely N,N-dimethylguanosine and N-2-methylguanosine may have the potential to serve as prognostic biomarkers. Gender-specific differences in urogenital tract cancer are likely to occur.

Comparison of RP-HPLC columns used for determination of nucleoside metabolic patterns in urine of cancer patients.

BACKGROUND: Metabolic profiling allows the measurement of a large set of both known and unknown metabolites (such as nucleosides and nucleobases) present in a biological sample (e.g., urine). RESULTS: Separation of the isolated urinary nucleosides was performed on two connected Gemini C18 columns - 3 µm pore size (50 cm total length) - at 55°C using mobile-phase gradient elution. The Mann-Whitney U test was used to distinguish differences in the concentration of compounds in urine from urogenital cancer patients and healthy controls. Comparison of mean concentration values from the healthy and cancer groups revealed statistically significant differences (p < 0.01) for most of the metabolites studied (excluding m7G, m3C and A). Observed elevated levels of nucleosides mean concentrated values in urine in the case of cancer patients are between 1.5 and 2.0. CONCLUSION: These results verify the usefulness of the RP-HPLC method to investigate the urinary pattern of normal and modified nucleosides.

New supervised alignment method as a preprocessing tool for chromatographic data in metabolomic studies.

The purpose of this work was to develop a new aligning algorithm called supervised alignment and to compare its performance with the correlation optimized warping. The supervised alignment is based on a "supervised" selection of a few common peaks presented on each chromatogram. The selected peaks are aligned based on a difference in the retention time of the selected analytes in the sample and the reference chromatogram. The retention times of the fragments between known peaks are subsequently linearly interpolated. The performance of the proposed algorithm has been tested on a series of simulated and experimental chromatograms. The simulated chromatograms comprised analytes with a systematic or random retention time shifts. The experimental chromatographic (RP-HPLC) data have been obtained during the analysis of nucleosides from 208 urine samples and consists of both the systematic and random displacements. All the data sets have been aligned using the correlation optimized warping and the supervised alignment. The time required to complete the alignment, the overall complexity of both algorithms, and its performance measured by the average correlation coefficients are compared to assess performance of tested methods. In the case of systematic shifts, both methods lead to the successful alignment. However, for random shifts, the correlation optimized warping in comparison to the supervised alignment requires more time (few hours versus few minutes) and the quality of the alignment described as correlation coefficient of the newly aligned matrix is worse 0.8593 versus 0.9629. For the experimental dataset supervised alignment successfully aligns 208 samples using 10 prior identified peaks. The knowledge about retention times of few analytes' in the data sets is necessary to perform the supervised alignment for both systematic and random shifts. The supervised alignment method is faster, more effective and simpler preprocessing method than the correlation optimized warping method and can be applied to the chromatographic and electrophoretic data sets.