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Bladder cancer (BCa) is ninth amongst the most common types of cancer in the human population worldwide. The statistics of incidence and mortality of BCa are alarming and the currently applied diagnostic methods are still not sensitive enough. This leads to a large number of undiagnosed BCa cases, usually among patients in the early stages of the disease. Despite the fact that many risk factors of BCa have been recognized, the pathomechanism of development of bladder cancer has not been fully explained yet. Therefore, in the present study, multiplatform urinary metabolomics has been implemented in order to scrutinize potential diagnostic indicators of BCa that might help to explain its pathomechanism and be potentially useful in diagnosis and determination of stage of the disease. Urine samples collected from muscle-invasive high grade BCa patients (n = 24) and healthy volunteers (n = 24) were matched in terms of most common BCa risk factors i.e. gender, age, BMI and smoking status. They were analyzed by high performance liquid chromatography coupled with time of flight mass spectrometry detection (HPLC-TOF/MS) using RP and HILIC chromatography, gas chromatography hyphenated with triple quadruple mass spectrometry detection (GC-QqQ/MS) in scan mode, and proton nuclear magnetic resonance (1H NMR). The six datasets obtained were submitted to univariate and multivariate statistical analyses. 17 metabolites significantly discriminated urinary profiles of BCa patients from urinary profiles of healthy volunteers. These metabolites are mainly involved in amino acid metabolism, pyrimidine and purine metabolism, as well as energy metabolism and might play a crucial role in the pathogenesis of BCa.

Due to the structural diversity of natural compounds in plants kingdom and a wide range of beneficial properties for health, they are attractive to use for various applications. Natural bioactivity means pharmacological effects induced by compounds of interest, which can be a subject of change under different conditions and dependent on individual organism. Development of supercomputers, spectroscopy techniques, completion of human genome project led to development of computational techniques in drug design. Their application can significantly benefit drug discovery field by reducing experiments in vivo, thus preventing subjecting of ultimatively ineffective drug candidates to clinical trials and simultaneously making contribution to understanding initial disease complex mechanisms that can change, e.g. due to gene mutations. Therefore, bioactivity data for natural bioactive compounds as potential drug candidates needs to be constantly updated within sets of computerized collections. Current review focuses on modern computational techniques to study bioactivity of selected natural compounds.

Imidazol(in)e derivatives, having the chemical structure similar to clonidine, exert diverse pharmacological activities connected with their interactions with alpha2-adrenergic receptors, e.g. hypotension, bradycardia, sedation as well as antinociceptive, anxiolytic, antiarrhythmic, muscle relaxant and mydriatic effects. The mechanism of pupillary dilation observed after systemic administration of imidazol(in)es to rats, mice and cats depends on the stimulation of postsynaptic alpha2-adrenoceptors within the brain. It was proved that the central nervous system (CNS)-localized I1-imidazoline receptors are not engaged in those effects. It appeared interesting to analyze the CNS-mediated pharmacodynamics of imidazole(in)e agents in terms of their chromatographic and calculation chemistry-derived parameters. In the present study a systematic determination and comparative pharmacometric analysis of mydriatic effects in rats were performed on a series of 20 imidazol(in)e agents, composed of the well-known drugs and of the substances used in experimental pharmacology. The eye pupil dilatory activities of the compounds were assessed in anesthetized Wistar rats according to the established Koss method. Among twenty imidazol(in)e derivatives studied, 18 produced diverse dose-dependent mydriatic effects. In the quantitative structure-activity relationships (QSAR) analysis, the pharmacological data (half maximum mydriatic effect - ED50 in μmol/kg) were considered along with the structural parameters of the agents from molecular modeling. The theoretically calculated lipophilicity parameters, CLOGP, of imidazol(in)es, as well as their lipophilicity parameters from HPLC, logkw, were also considered. The attempts to derive statistically significant QSAR equations for a full series of the agents under study were unsuccessful. However, for a subgroup of eight apparently structurally related imidazol(in)es a significant relationship between log(1/ED50) and logkw values was obtained. The lack of "predictive" QSAR for the whole series of the structurally diverse agents is probably due to a complex mechanism of the ligand-alpha2-adrenergic receptor interactions, which are predominantly of a highly structurally specific polar nature. Such interactions are difficult to quantify with the established chemical structural descriptors, contrary to the less specific, molecular bulkiness-related interactions.

Design of a new drug entity is usually preceded by analysis of quantitative structure activity (properties) relationships, QSA(P)R. Six newly synthesized succinimide derivatives have been determined for (i) in silico physico-chemical descriptors, pharmacokinetic and toxicity predictors, (ii) in vitro biological activity on four different carcinoma cell lines and on normal fetal lung cells and (iii) lipophilicity on liquid chromatography. All compounds observed were predicted for good permeability and solubility, good oral absorption rate and moderate volume of distribution as well as for modest blood brain permeation, followed by acceptable observed toxicity. In silico determined lipophilicity, permeability through jejunum and aqueous solubility were correlated with experimentally obtained lipophilic constants (by use of high pressure liquid chromatography) and linear correlations were obtained. Absorption rate and volume of distribution were predicted by chromatographic lipophilicity measurements while permeation through blood bran barrier was predicted dominantly by molecular size defined with molecular weight. Five compounds have demonstrated antiproliferative activity toward cervix carcinoma HeLa cell lines; three were cytotoxic against breast carcinoma MCF-7 cells, while one inhibited proliferation of colon carcinoma HT 29 cell lines. Only one compound was cytotoxic toward normal cell lines, while other compounds were proven as safe. Antiproliferative potential against HeLa cells was described as exponential function of lipophilicity. Based on obtained results, lead compounds were selected.

Aim: The purpose of this work was to develop and validate a rapid and robust LC–MS/MS method for the determination of dexmedetomidine (DEX) in plasma, suitable for analysis of a large number of samples. Method: Systematic approach, Design of Experiments, was applied to optimize ESI source parameters and to evaluate method robustness, therefore, a rapid, stable and cost-effective assay was developed. The method was validated according to US FDA guidelines. LLOQ was determined at 5 pg/ml. The assay was linear over the examined concentration range (5–2500 pg/ml), Results: Experimental design approach was applied for optimization of ESI source parameters and evaluation of method robustness. The method was validated according to the US FDA guidelines. LLOQ was determined at 5 pg/ml. The assay was linear over the examined concentration range (R2 > 0.98). The accuracies, intra- and interday precisions were less than 15%. The stability data confirmed reliable behavior of DEX under tested conditions. Conclusion: Application of Design of Experiments approach allowed for fast and efficient analytical method development and validation as well as for reduced usage of chemicals necessary for regular method optimization. The proposed technique was applied to determination of DEX pharmacokinetics in pediatric patients undergoing long-term sedation in the intensive care unit.

Chemical compounds are obtained for their desired properties, which are chemical, physical or biological. To rationally guide search for compounds of the required properties, the quantitative structure–property relationships (QSPR) could be of utmost practical value. Alas, if chemists are much successful in predicting the courses of chemical reaction, and hence the structures of specific reaction products, it is not easy for them to get reliable predictions of compound properties. Actually, if we succeed in deriving reliable QSPR, we would achieve a kind of chemical ‘Theory of Everything’. A property which is well-measurable, reproducible and readily obtainable for quite large numbers of chemical structures is chromatographic retention parameter. Therefore, quantitative structure–retention relationship (QSRR), where R (chromatographic retention) stands for P (property), appears extraordinarily promising in exercising theory and practice of modelling of diverse properties of chemicals and to design appropriate structures. Studies on QSRR require knowledge and skill in separation sciences, combined with structural chemistry and proficiency in computer-assisted data processing based on chemometrics. In this chapter, the basic knowledge on QSRR has been presented and examples discussed critically from the point of view of importance for optimization of chromatographic separation of defined structurally analytes, for modelling interactions of xenobiotics with biomacromolecules and for rational design of drug candidates.

Arterial stiffening is a hallmark of early vascular aging (EVA) syndrome and an independent predictor of cardiovascular morbidity and mortality. In this case-control study we sought to identify plasma metabolites associated with EVA syndrome in the setting of hypertension. An untargeted metabolomic approach was used to identify plasma metabolites in an age-, BMI-, and sex-matched groups of EVA (n = 79) and non-EVA (n = 73) individuals with hypertension. After raw data processing and filtration, 497 putative compounds were characterized, out of which 4 were identified as lysophosphaditylcholines (LPCs) [LPC (18:2), LPC (16:0), LPC (18:0), and LPC (18:1)]. A main finding of this study shows that identified LPCs were independently associated with EVA status. Although LPCs have been shown previously to be positively associated with inflammation and atherosclerosis, we observed that hypertensive individuals characterized by 4 down-regulated LPCs had 3.8 times higher risk of EVA compared to those with higher LPC levels (OR = 3.8, 95% CI 1.7–8.5, P < 0.001). Our results provide new insights into a metabolomic phenotype of vascular aging and warrants further investigation of negative association of LPCs with EVA status. This study suggests that LPCs are potential candidates to be considered for further evaluation and validation as predictors of EVA in patients with hypertension.

For the first time, stepwise pH gradient thin-layer chromatograms of biologically active substances with controlled developing solvent velocity are presented and described in the paper. Change in buffer pH of the mobile phase solution influences retardation, selectivity, and shape of the separated substances' spots. The conducted research has confirmed that the mobile phase's pH gradient could be an essential factor to optimize the conditions of the separation of substances in reversed-phase high-performance thin-layer chromatography. The reproducibility of the gradient retardation factor values of separated substance zones is satisfactory.

The present paper reports a comparison study of two data processing procedures in GC–MS metabolome components investigation based on two modern softwares: Automated Mass Spectral Deconvolution and Identification System (AMDIS) and GC–MS Solution Postrun Analysis (GC–MS SPA). GC–MS SPA is intended for manual integration and identification, while AMDIS is proposed as a fast, and automatic data analysis tool. Both methods are based on the same free-access library. In the present study, 12 compounds previously detected in a metabolomic fingerprint of grasshopper abdominal secretion, were tested at three concentration levels: 2.5, 5 and 10 μg/mL. The processing procedures were evaluated by comparison of peak area ratio for each tested concentration. The obtained results proved that processing with the use of AMDIS was more sensitive and enabled the identification of all compounds at the lowest selected concentration. Additionally, the differentiation of structurally similar compounds was possible with the use of AMDIS software.

The purpose of this study was to assess the pharmacokinetics of dexmedetomidine in the ICU settings during the prolonged infusion and to compare it with the existing literature data using the Bayesian population modeling with literature-based informative priors. Thirty-eight patients were included in the analysis with concentration measurements obtained at two occasions: first from 0 to 24 h after infusion initiation and second from 0 to 8 h after infusion end. Data analysis was conducted using WinBUGS software. The prior information on dexmedetomidine pharmacokinetics was elicited from the literature study pooling results from a relatively large group of 95 children. A two compartment PK model, with allometrically scaled parameters, maturation of clearance and t-student residual distribution on a log-scale was used to describe the data. The incorporation of time-dependent (different between two occasions) PK parameters improved the model. It was observed that volume of distribution is 1.5-fold higher during the second occasion. There was also an evidence of increased (1.3-fold) clearance for the second occasion with posterior probability equal to 62 %. This work demonstrated the usefulness of Bayesian modeling with informative priors in analyzing pharmacokinetic data and comparing it with existing literature knowledge. Electronic supplementary material The online version of this article (doi:10.1007/s10928-016-9474-0) contains supplementary material, which is available to authorized users.

Reversed-phase high-performance liquid chromatography (RP-HPLC) is the most popular chromatographic mode, accounting for more than 90% of all separations. HPLC itself owes its immense popularity to it being relatively simple and inexpensive, with the equipment being reliable and easy to operate. Due to extensive automation, it can be run virtually unattended with multiple samples at various separation conditions, even by relatively low-skilled personnel. Currently, there are600 RP-HPLC columns available to end users for purchase, some of which exhibit very large differences in selectivity and production quality. Often, two similar RP-HPLC columns are not equally suitable for the requisite separation, and to date, there is no universal RP-HPLC column covering a variety of analytes. This forces analytical laboratories to keep a multitude of diverse columns. Therefore, column selection is a crucial segment of RP-HPLC method development, especially since sample complexity is constantly increasing. Rationally choosing an appropriate column is complicated. In addition to the differences in the primary intermolecular interactions with analytes of the dispersive (London) type, individual columns can also exhibit a unique character owing to specific polar, hydrogen bond, and electron pair donor-acceptor interactions. They can also vary depending on the type of packing, amount and type of residual silanols, "end-capping", bonding density of ligands, and pore size, among others. Consequently, the chromatographic performance of RP-HPLC systems is often considerably altered depending on the selected column. Although a wide spectrum of knowledge is available on this important subject, there is still a lack of a comprehensive review for an objective comparison and/or selection of chromatographic columns. We aim for this review to be a comprehensive, authoritative, critical, and easily readable monograph of the most relevant publications regarding column selection and characterization in RP-HPLC covering the past four decades. Future perspectives, which involve the integration of state-of-the-art molecular simulations (molecular dynamics or Monte Carlo) with minimal experiments, aimed at nearly "experiment-free" column selection methodology, are proposed.

The objective of this work was to develop a multilevel (hierarchical) model based on isocratic-reversed-phase-high-performance-chromatographic data collected in methanol and acetonitrile for 58 chemical compounds. Such a multilevel model is a regression model of the analyte-specific chromatographic measurements, in which all the regression parameters are given a probability model. It is a fundamentally different approach from the most common approach, where parameters are separately estimated for each analyte (without sharing information across analytes and different organic modifiers). The statistical analysis was done with Stan software implementing the Bayesian-statistics inference with Markov-chain Monte Carlo sampling. During the model-building process, a series of multilevel models of different complexity were obtained, such as (1) a model with no pooling (separate models were fitted for each analyte), (2) a model with partial pooling (a common distribution was used for analyte-specific parameters), and (3) a model with partial pooling as well as a regression model relating analyte-specific parameters and analyte-specific properties (QSRR equations). All the models were compared with each other using 10-fold cross-validation. The benefits of multilevel models in inference and predictions were shown. In particular the obtained models allowed us to (i) better understand the data and (ii) solve many routine analytical problems, such as obtaining well-calibrated predictions of retention factors for an analyte in acetonitrile-containing mobile phases given zero, one, or several measurements in methanol-containing mobile phases and vice versa.

Fast and reliable methods for the determination of hydrophobicity and acidity are desired in pre-clinical drug development phases to eliminate compounds with poor pharmacokinetic properties. Reversed-phase high-performance liquid chromatography (RP HPLC) coupled with time-of-flight mass spectrometry (RP HPLC-ESI-TOF-MS) is a convenient technique for that purpose. In this work we determined the chromatographic measure of hydrophobicity (logkw) and dissociation constant (pKa) simultaneously for a large and diverse group of 161 drugs. Retention times were determined by means of RP HPLC-ESI-TOF-MS for a series of pH and organic modifier gradients. We were able to measure retention times for 140 out of 161 (87%) compounds. For those analytes logkw and pKa parameters were calculated and compared with literature and ACD Labs-calculated data. The determined chromatographic measure of hydrophobicity and dissociation constant was closely related to literature and theoretically calculated values. Applied methodology achieved the medium-throughput screening rate of 100 compounds per day and proved to be a simple, fast and reliable approach of assessing important physicochemical properties of drugs. This technique has certain limitations as it is not applicable for very hydrophilic analytes (logP

Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice.

In this review, we will firstly discuss the types and the general properties of silica, focusing on the silica support used in chromatography and capillary electrophoresis. Additionally, the characterization of functional groups (silanols and siloxanes) will be considered in terms of activity of the stationary phases. We will then discuss physical chemistry of the stationary phases applied in liquid chromatography and capillary electrophoresis. The use of ionic liquids as a silanols’ suppressors will be presented in the next parts of the study, along with the examples of specific applications. The review is completed with conclusions and an outlook for the future developments in the area of analytical applications of ionic liquids.

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.

Trigonelline is a pyridine alkaloid found in fenugreek seeds and coffee beans. Most of the previous studies are concerned with the quantification of trigonelline along with other constituents in coffee herbs or beverages. Only a few have focused on its determination in animal or human tissues by applying different modes of HPLC with UV or MS detection. The aim of the study was to develop and validate a fast and simple method for trigonelline determination in serum by the use of hydrophilic interaction liquid chromatography (HILIC) with ESI-MS/MS detection. Separation of trigonelline was achieved on a Kinetex HILIC column operated at 35°C with acetonitrile-ammonium formate (10 mm, pH = 3) buffer mixture (55:45, v/v) as the mobile phase. The developed method was successfully applied to determine trigonelline concentration in mouse serum after intravenous administration of 10 mg/kg. The developed assay is sensitive (limit of detection = 1.5 ng/mL, limit of quantification = 5.0 ng/mL) and linear in a concentration range from 5.0 to 250.0 ng/mL. Sample preparation is limited to deproteinization, centrifugation and filtration. The application of the HILIC mode of chromatography with MS detection and selection of deuterated trigonelline as internal standard allowed a rapid and precise method of trigonelline quantification to be to developed.

This paper investigates correlations between the standard chromatographic parameter, log kw, obtained experimentally (classical thermodynamic) and obtained through the use of quantitative structure-retention relationships (QSRR) models (extrathermodynamic approach). QSRR models were created using descriptors from calculation chemistry, selected a priori on the basis of chemical intuition. Four modern analytical columns (packed with C18), often used in pharmaceutical analysis, were selected for the study. The simple extrathermodynamic model was demonstrated to be superior in terms of retention description with relation to rather complex models based on thermodynamic hermeneutics. However, all the QSRR equations derived are of limited predictive value as regards prediction of retention on the basis of the structure of the analyte. Nonetheless, they allow the differentiation of mechanism of separation operating on individual tested stationary phases. The descriptors, which are most significant in QSRR equati...

Aim. This study aimed to examine the influence of maturation and dosage on the sedative and haemodynamic response observed in rabbits after the administration of dexmedetomidine. Material and methods. The pharmacodynamics of dexmedetomidine was studied on 14 healthy New Zealand white rabbits at three periods of maturation; stage 1–1.5 months old, stage 2–2.5 months old and stage 3–6.5 months old ones. The administered dose of dexmedetomidine ranged from 25 µg/kg to 300 µg/kg of body weight. The pedal withdrawal reflex was used to measure the duration of anaesthesia. The heart rate and mean arterial pressure were measured at the third stage of the study to evaluate the haemodynamic response. A simple pharmacodynamic relationship between the dose and the duration of anesthesia was used to describe the data.Results. We observed that young rabbits were less sensitive to dexmedetomidine than adult animals, as was reflected by the pedal withdrawal reflex, and we found that the haemodynamic response to dexmedetomidine depended on dosage of the drug. Dexmedetomidine decreased the mean blood pressure in a dosage-dependent manner with the highest decrease observed for the lowest dose. As the dose increased, the hypotensive effect of the drug was less noticeable. After the administration of dexmedetomidine the heart rate decreased to the same value regardless of the dose applied.

A technique has recently been proposed for obtaining the reticulocyte (RET) age distribution from the flow cytometric reticulocyte count. It allows for a quantitative characterization of reticulocyte dynamics. In this work this technique was applied to characterize the blood, bone marrow and spleen reticulocytes in homeostatic and erythropoietically stimulated rats in order to determine the reticulocyte maturation times in the bone marrow and blood; and to confirm the presence of ineffective erythropoiesis (neocytolysis). The latter was done by comparing the reticulocyte removal rate from blood with bilirubin formation after erythropoiesis stimulation. A single subcutaneous dose (4050 IU/kg) of recombinant human erythropoietin (rHuEPO) was administered to rats, then their reticulocytes were stained with thiazole orange and the distribution of the fluorescent signal measured using flow cytometry. The obtained signal distribution of the reticulocytes was transformed to the age distribution and a set of basic parameters reflecting reticulocyte dynamics was determined. Bilirubin concentrations were measured to directly assess the presence of reticulocyte irreversible removal. The bilirubin formation was found to be considerably modulated by rHuEPO and corresponded well to the determined reticulocyte removal rate. The initial increase and subsequent decrease of the reticulocyte maturation time in blood was quantitated and directly linked with RET mobilization from the bone marrow. A substantial number (60%) of reticulocytes is sequestrated during homeostasis in rats. This number increases and then decreases after rHuEPO administration, as also reflected by bilirubin formation. Flow cytometry seems to be an excellent method for studying RET dynamics and the presence of young RBC neocytolysis. Copyright © 2014 John Wiley & Sons, Ltd.

Wound healing is still a serious medical problem due to process complexity and lack of effective medicaments. This is particularly true in the treatment of wounds arising in the course of such diseases as AIDS or diabetes. Therefore, scientific efforts are focused on the search for new compounds of natural origin, which could be used as medicines or evaluated for subsequent drug design. In folk medicine, grasshopper (Chorthippus spp.) abdominal secretion has been used to accelerate the wound healing process. In this context, the knowledge of the composition of grasshopper abdominal secretion is crucial. The aim of this study was to determine the main water-soluble components of grasshopper abdominal secretion with the use of GC/MS/MS. Liquid–liquid extraction was used as a pretreatment method to clean up, concentrate and fractionate compounds from the complex insect matrix. To obtain more stable and volatile compounds, necessary for GC/MS/MS analysis, a double-step derivatization process was carried out with the use of methoxyamine hydrochloride and a mixture of bis-N,O-trimethylsilyl trifluoroacetamide and chlorotrimethylsilane. As a result, 2,108 compounds were identified, mainly as amino acids, carbohydrates and organic acids. Some of the identified compounds are emphasized due to antimicrobial, antifungal or antioxidant activities reported in the literature. Moreover, a set of compounds characteristic for Chorthippus spp. samples has been selected. In the last part of the study, a statistical analysis was performed to demonstrate differences in composition of aqueous fractions of abdominal secretions from grasshoppers collected at two distant locations: Starogard Gdanski and Łubianka meadows.

In recent years biologically active compounds isolated from insects call special interest of drug researchers. According to some Polish etnopharmacological observations, secretion from the grasshopper's abdomen ( Orthoptera family) is believed to speed up the process of wound healing. In the present work we focused on determination of main components of the lipid fraction of material from grasshopper abdomen using GC–MS/MS. Samples were qualitatively analyzed using gas chromatography coupled with mass spectrometry. Both liquid–liquid extraction and solid-phase extraction pretreatment methods were used to concentrate and fractionate the compounds from the insect. In the derivatized fractions ca. 350 compounds were identified, including substances of known biological activity. The potential agents affecting wound healing have been indicated. A set of compounds characteristic for all the studied Chorthippus spp., have been identified. Data analysis revealed different lipidomic profiles of grasshoppers depending on the insects origin and collection area.

Background This study evaluates the time-of-day effect on midazolam and 1-OH midazolam pharmacokinetics, and on the sedative pharmacodynamic response in rabbits. Also, circadian fluctuations in rabbits’ vital signs, such as the blood pressure, heart rate and body temperature were examined. The water intake was measured in order to confirm the presence of the animals’ diurnal activity. The secondary aim involved the comparison of two methods of data analysis: a noncompartmental and a population modeling approach. Methods Twelve rabbits were sedated with intravenous midazolam 0.35 mg/kg at four local times: 09.00, 14.00, 18.00 and 22.00 h. Each rabbit served as its own control by being given a single infusion at the four different times of the day on four separate occasions. The values of the monitored physiological parameters were recorded during the experiment and arterial blood samples were collected for midazolam assay. The pedal withdrawal reflex was used as the measurement of the sedation response. Two and one compartmental models were successfully used to describe midazolam and 1-OH midazolam pharmacokinetics. The categorical pharmacodynamic data were described with a logistic model. Results and conclusions We did not find any time-of-day effects for the pharmacokinetic and pharmacodynamics parameters of midazolam. For 1-OH midazolam, statistically significant time-of-day differences in the apparent volume of distribution and clearance were noticed. They corresponded well with the rabbits’ water intake. The noncompartmental and model-based parameters were essentially similar. However, more information can be obtained from the population model and this method should be preferred in chronopharmacokinetic and chronopharmacodynamic studies.

In transcriptomics, micro RNAs (miRNAs) has gained much interest especially as potential disease indicators. However, apart from holding a great promise related to their clinical application, a lot of inconsistent results have been published. Our aim was to compare the miRNA expression levels in ovarian cancer and healthy subjects using the Bayesian multilevel model and to assess their potential usefulness in diagnosis. We have analyzed a case-control observational data on expression profiling of 49 preselected miRNA-based ovarian cancer indicators in 119 controls and 59 patients. A Bayesian multilevel model was used to characterize the effect of disease on miRNA levels controlling for differences in age and body weight. The difference between the miRNA level and health status of the patient on the scale of the data variability were discussed in the context of their potential usefulness in diagnosis. Additionally, the cross-validated area under the ROC curve (AUC) was used to assess the expected out-of-sample discrimination index of a different sets of miRNAs. The proposed model allowed us to describe the set of miRNA levels in patients and controls. Three highly correlated miRNAs: miR-101-3p, miR-142-5p, miR-148a-3p rank the highest with almost identical effect sizes that ranges from 0.45 to 1.0. For those miRNAs the credible interval for AUC ranged from 0.63 to 0.67 indicating their limited discrimination potential. A little benefit in adding information from other miRNAs was observed. There were several miRNAs in the dataset (miR-604, hsa-miR-221-5p) for which inferences were uncertain. For those miRNAs more experimental effort is needed to fully assess their effect in the context of new hits discovery and usefulness as disease indicators. The proposed multilevel Bayesian model can be used to characterize the panel of miRNA profile and to assess the difference in expression levels between healthy and cancer individuals.

This study describes application of liquid chromatography coupled with triple quadrupole mass spectrometry (LC-MS) for evaluation of vitamin C stability, the objective being prediction of the degradation products. Detection was performed with an UV detector (UV-Vis) in sequence with a triple-quad mass spectrometer in the multiple reaction mode. The negative ion mode of ESI and MS-MRM transitions of m/z 175→115 (quantifier) and 175→89 (qualifier) for ascorbic acid was used. All the validation parameters were within the range of acceptance proposed by the Food and Drug Administration. The method was fully validated in terms of linearity, LOD, LOQ, accuracy, and interday precision. Validation experiments revealed good linearity with R(2) = 0.999 within the established concentration range, and excellent repeatability (9.3%). The LOD of the method was 0.1524 ng/mL whereas the LOQ was 0.4679 ng/mL. LC-MS methodology proves to be an improved, simple, and fast approach to determining the content of vitamin C and its degradation products with high sensitivity, selectivity, and resolving power within 6 minutes of analysis.

In view of linear free-energy relationships (LFER) chromatographic systems are “free-energy transducers,” translating differences in the structure of analytes into quantitative differences in physicochemical properties, like retention parameters. Hence, quantitative structure property (retention) relationships (QSP(R)R) bear valuable information on analytes and the separation systems involved. We illustrate here what can be achieved from the statistically valid and physically meaningful quantitative structure-retention relationships, QSRR. In particular, one can predict retention data, confirm identification, and optimize conditions of separation of given structurally defined analytes. Also, QSPR can shed light on the molecular mechanism of separation operating on specific stationary phases. Additionally, one can assess such properties of drug analytes of pharmacokinetic importance, such as lipophilicity and acidity. Also, differences in interactions of xenobiotics with biomacromolecule components of chromatographic systems can conveniently be quantified. By means of QSRR, the chromatographic behavior of analytes in diverse separation systems can be related to their pharmacological properties. However, in context of recent warnings over misuse of P values in statistical data analyses, numerous reported and actually proposed QSP(R)R require critical reevaluation.

This study evaluates possible circadian rhythms during prolonged midazolam infusion in 27 pediatric intensive care unit (PICU) children under mechanical ventilation.Blood samples for midazolam and 1-OH-midazolam assay were collected throughout the infusion at different times of the day. The blood pressure, heart rate and body temperature were recorded every hour for the rhythms analysis. Population nonlinear mixed-effect modeling with NONMEM was used for data analysis.A two-compartment model for midazolam pharmacokinetics and a one-compartment model for midazolam metabolite adequately described the data. The 24 h profiles of all monitored physiological parameters were greatly disturbed/abolished in comparison with the well-known 24 h rhythmic patterns in healthy subjects. There was no significant circadian rhythm detected with respect to midazolam pharmacokinetics, its active metabolite pharmacokinetics and all monitored parameters.We concluded that the light-dark cycle did not influence midazolam pharmacokinetics in intensive care units children. Also, endogenous rhythms in critically ill and sedated children are severely disturbed and desynchronized. Our results confirmed that it is necessary to adjust the dose of midazolam to the patient's body weight. The low value of midazolam clearances observed in our study was probably caused by mechanical ventilation, which was shown to decrease the cardiac output.

Chamomile has been used as an herbal medication since ancient times and is still popular because it contains various bioactive phytochemicals that could provide therapeutic effects. In this study, a simple and reliable HPLC method was developed to evaluate the quality consistency of nineteen chamomile samples through establishing a chromatographic fingerprint, quantification of phenolic compounds and determination of antioxidant activity. For fingerprint analysis, 12 peaks were selected as the common peaks to evaluate the similarities of commercial samples of chamomile obtained from different manufacturers. A similarity analysis was performed to assess the similarity/dissimilarity of chamomile samples where values varied from 0.868 to 0.990 what indicating that samples from different manufacturers were consistent. Additionally, simultaneous quantification of five phenolic acids (gallic, caffeic, syringic, p-coumaric, ferulic) and four flavonoids (rutin, myricetin, quercetin and keampferol) was performed to interpret the quality consistency. In quantitative analysis, the nine individual phenolic compounds showed good regression (r > 0.9975). Inter- and intra-day precisions for all analysed compounds expressed as relative standard deviation (CV) ranged from 0.05% to 3.12%. Since flavonoids and other polyphenols are commonly recognised as natural antioxidants, the antioxidant activity of chamomile samples was evaluated using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity and ferric reducing/antioxidant power (FRAP) assay. Correlation analysis was used to assess the relationship between antioxidant activity and phenolic composition, and multivariate analysis (PCA and HCA) were applied to distinguish chamomile samples. Results shown in the study indicate high similarity of chamomile samples among them, widely spread in the market and commonly used by people as infusions or teas, as well as that there were no statistically significant differences among them, which in turn is a proof of high quality of commercially available samples of chamomile. The study indicated that the combination of chromatographic fingerprint and quantitative analysis can be readily utilised as a quality consistency method for chamomile and related medicinal preparations. Moreover, the applied strategy seems to be the most promising for the assessment of the investigated plant material.

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. Electronic supplementary material The online version of this article (doi:10.1007/s11306-017-1164-4) contains supplementary material, which is available to authorized users.

Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study). Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO) were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO) with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings. Such multivariate model represents high goodness-of-fit to the data, however the risk of overfitting increases relevantly. Therefore, the LASSO method was for the first time applied for statistical analysis of datasets obtained in untargeted metabolomics studies. The advantage behind LASSO lies in the ability to model different types of omics data, account for multicollinearity and p >> n problems.

Fluoroquinolones are the drugs of choice in the prevention of bacterial infections after transrectal ultrasound guided prostate biopsy. In order to improve assessment of antibacterial efficacy in the target tissue a simple, selective, rapid and robust HPLC-ESI-MS/MS method for the determination of levofloxacin and ciprofloxacin concentrations in human prostate bioptates was developed and validated. Preparation procedure for prostate samples (10mg) was carried out using homogenization and filtration steps. Analyses were performed within 3.5min using RP C18 column in the isocratic elution mode with mobile phase composed of a mixture of 0.1% formic acid aqueous solution and 0.1% formic acid methanol solution (v/v; 79:21). The method was linear between 0.3μg/g and 15μg/g for levofloxacin and ciprofloxacin with coefficient of correlation (r) ≥0.999. The limit of detection and the limit of quantification for levofloxacin were 0.06μg/g and 0.2μg/g and for ciprofloxacin were 0.04μg/g and 0.13μg/g, respectively. Average concentrations (±SD) of levofloxacin and ciprofloxacin obtained from patients tissue were 5.4±2.2μg/g and 3.9±1.5μg/g, respectively. Additionally, during validation procedure a novel, experimental design approach was applied for the robustness study. For evaluation of analytical method robustness, Plackett-Burman design was employed and for sample preparation method robustness Fractional Factorial design was used. The developed and validated method was successfully applied to examine prostate tissue samples obtained from patients enrolled into a clinical study. Up to now, there has been no other HPLC-ESI-MS/MS method reported for the simultaneous determination of levofloxacin and ciprofloxacin in human prostatic tissue.

Fluoroquinolones are considered as gold standard for the prevention of bacterial infections after transrectal ultrasound guided prostate biopsy. However, recent studies reported that fluoroquinolone- resistant bacterial strains are responsible for gradually increasing number of infections after transrectal prostate biopsy. In daily clinical practice, antibacterial efficacy is evaluated only in vitro, by measuring the reaction of bacteria with an antimicrobial agent in culture media (i.e. calculation of minimal inhibitory concentration). Such approach, however, has no relation to the treated tissue characteristics and might be highly misleading. Thus, the objective of this study was to develop, with the use of Design of Experiments approach, a reliable, specific and sensitive ultra-high performance liquid chromatography- diode array detection method for the quantitative analysis of levofloxacin in plasma and prostate tissue samples obtained from patients undergoing prostate biopsy. Moreover, correlation study between concentrations observed in plasma samples vs prostatic tissue samples was performed, resulting in better understanding, evaluation and optimization of the fluoroquinolone-based antimicrobial prophylaxis during transrectal ultrasound guided prostate biopsy. Box-Behnken design was employed to optimize chromatographic conditions of the isocratic elution program in order to obtain desirable retention time, peak symmetry and resolution of levofloxacine and ciprofloxacine (internal standard) peaks. Fractional Factorial design 2(4-1) with four center points was used for screening of significant factors affecting levofloxacin extraction from the prostatic tissue. Due to the limited number of tissue samples the prostatic sample preparation procedure was further optimized using Central Composite design. Design of Experiments approach was also utilized for evaluation of parameter robustness. The method was found linear over the range of 0.030-10μg/mL for human plasma and 0.300-30μg/g for human prostate tissue samples. The intra-day and inter-day variability for levofloxacine from both plasma and prostate samples were less than 10%, with accuracies between 93 and 108% of the nominal values. The limit of detection and the limit of quantification for human plasma were 0.01μg/mL and 0.03μg/mL, respectively. For the prostate tissue, the limit of detection and the limit of quantification were 0.1μg/g and 0.3μg/g, respectively. The average recoveries of levofloxacin were in the range from 99 to 106%. Also, the method fulfills requirements of robustness what was determined and proved by Design of Experiments. The developed method was successfully applied to examine prostate tissue and plasma samples from 140 hospitalized patients enrolled into the clinical study, 12h after oral administration of LVF at a dose of 500mg. The mean (±SD) LVF concentration in prostate was 6.22±3.52μg/g and in plasma 2.54±1.14μg/mL. Due to simplicity of the method and relative small amount of sample needed for the assay, the method can be applied in clinical practice for monitoring of LVF concentrations in plasma and prostate gland.

Convenient drug candidates testing methods for lipophilicity and acidity are highly requested in modern pharmaceutical research and development strategy. Reversed-phase high-performance liquid chromatography (RP HPLC) might be particularly useful for the determination of both pKa and the apparent (pH-dependent) octanol–water partition coefficient, applicable in high-throughput analysis of multi-component mixtures. In this report the pH/organic modifier gradient RP HPLC is presented as a means of simultaneous determination of acidity and lipophilicity of a series of 26 imidazoline-like drugs. The previously theoretically elaborated approach has been applied consisting in retention measurements in a series of methanol gradient runs differing in pH range and duration of the gradient. The simultaneously determined lipophilicity and dissociation constants have been demonstrated to correlate to the respective parameters form calculation chemistry. The proposed approach can be applied to compound mixtures, it requires only minute amounts of substances, and pKa values can be determined in the range 3–10 units and lipophilicity log P parameter in the range 0–7 units.

A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics.