27 resultados para method applied to liquid samples

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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After the discovery of synthetic cannabimimetic substances in 'Spice'-like herbal mixtures marketed as 'incense' or 'plant fertilizer' the active compounds have been declared as controlled substances in several European countries. As expected, a monitoring of new herbal mixtures which continue to appear on the market revealed that shortly after control measures have been taken by legal authorities, other compounds were added to existing mixtures and to new products. Several compounds of the aminoalkylindole type have been detected so far in herbal mixtures but still their consumption cannot be detected by commonly used drug-screening procedures, encouraging drug users to substitute cannabis with those products. There is a increasing demand on the part of police authorities, hospitals and psychiatrists for detection and quantification of synthetic cannabinoids in biological samples originating from psychiatric inpatients, emergency units or assessment of fitness to drive. Therefore, a liquid chromatography-tandem mass spectrometry method after liquid-liquid extraction for the quantitation of JWH-015, JWH-018, JWH-073, JWH-081, JWH 200, JWH-250, WIN 55,212-2 and methanandamide and the detection of JWH-019 and JWH-020 in human serum has been developed and fully validated according to guidelines for forensic toxicological analyses. The method was successfully applied to 101 serum samples from 80 subjects provided by hospitals, detoxification and therapy centers, forensic psychiatric centers and police authorities. Fifty-seven samples or 56.4% were found positive for at least one aminoalkylindole. JWH-019, JWH-020, JWH-200, WIN 55,212-2 and methanandamide were not detected in any of the analyzed samples.

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The chemotherapeutic drug 5-fluorouracil (5-FU) is widely used for treating solid tumors. Response to 5-FU treatment is variable with 10-30% of patients experiencing serious toxicity partly explained by reduced activity of dihydropyrimidine dehydrogenase (DPD). DPD converts endogenous uracil (U) into 5,6-dihydrouracil (UH(2) ), and analogously, 5-FU into 5-fluoro-5,6-dihydrouracil (5-FUH(2) ). Combined quantification of U and UH(2) with 5-FU and 5-FUH(2) may provide a pre-therapeutic assessment of DPD activity and further guide drug dosing during therapy. Here, we report the development of a liquid chromatography-tandem mass spectrometry assay for simultaneous quantification of U, UH(2) , 5-FU and 5-FUH(2) in human plasma. Samples were prepared by liquid-liquid extraction with 10:1 ethyl acetate-2-propanol (v/v). The evaporated samples were reconstituted in 0.1% formic acid and 10 μL aliquots were injected into the HPLC system. Analyte separation was achieved on an Atlantis dC(18) column with a mobile phase consisting of 1.0 mm ammonium acetate, 0.5 mm formic acid and 3.3% methanol. Positively ionized analytes were detected by multiple reaction monitoring. The analytical response was linear in the range 0.01-10 μm for U, 0.1-10 μm for UH(2) , 0.1-75 μm for 5-FU and 0.75-75 μm for 5-FUH(2) , covering the expected concentration ranges in plasma. The method was validated following the FDA guidelines and applied to clinical samples obtained from ten 5-FU-treated colorectal cancer patients. The present method merges the analysis of 5-FU pharmacokinetics and DPD activity into a single assay representing a valuable tool to improve the efficacy and safety of 5-FU-based chemotherapy.

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Ketamine and norketamine are being transported across the blood brain barrier and are also entering from blood into cerebrospinal fluid (CSF). Enantioselective distributions of these compounds in brain and CSF have never been determined. The enantioselective CE based assay previously developed for equine plasma was adapted to the analysis of these compounds in equine brain via use of an acidic pre-extraction of interferences prior to liquid/liquid extraction at alkaline pH. CSF can be treated as plasma. With 100 mg of brain tissue and 0.5 mL of CSF or plasma, assay conditions for up to 30 nmol/g and 6 μM, respectively, of each enantiomer with LOQs of 0.5 nmol/g and 0.1 μM, respectively, were established and the assays were applied to equine samples. CSF and plasma samples analyzed stemmed from anesthetized patient horses and brain, CSF and plasma were obtained from anesthetized horses that were euthanized with an overdose of pentobarbital. Data obtained indicate that ketamine and norketamine enantiomers are penetrating into brain and CSF with those of ketamine being more favorably transported than norketamine, whereas metabolites of norketamine are hindered. More work is required to properly investigate possible stereoselectivities of the ketamine metabolism and transport of metabolites from blood into brain tissue and CSF.

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A global metabolic profiling methodology based on gas chromatography coupled to time-of-flight mass spectrometry (GC-TOFMS) for human plasma was applied to a human exercise study focused on the effects of beverages containing glucose, galactose, or fructose taken after exercise and throughout a recovery period of 6 h and 45 min. One group of 10 well trained male cyclists performed 3 experimental sessions on separate days (randomized, single center). After performing a standardized depletion protocol on a bicycle, subjects consumed one of three different beverages: maltodextrin (MD)+glucose (2:1 ratio), MD+galactose (2:1), and MD+fructose (2:1), consumed at an average of 1.25 g of carbohydrate (CHO) ingested per minute. Blood was taken straight after exercise and every 45 min within the recovery phase. With the resulting blood plasma, insulin, free fatty acid (FFA) profile, glucose, and GC-TOFMS global metabolic profiling measurements were performed. The resulting profiling data was able to match the results obtained from the other clinical measurements with the addition of being able to follow many different metabolites throughout the recovery period. The data quality was assessed, with all the labelled internal standards yielding values of <15% CV for all samples (n=335), apart from the labelled sucrose which gave a value of 15.19%. Differences between recovery treatments including the appearance of galactonic acid from the galactose based beverage were also highlighted.

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When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

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Background The World Health Organization estimates that in sub-Saharan Africa about 4 million HIV-infected patients had started antiretroviral therapy (ART) by the end of 2008. Loss of patients to follow-up and care is an important problem for treatment programmes in this region. As mortality is high in these patients compared to patients remaining in care, ART programmes with high rates of loss to follow-up may substantially underestimate mortality of all patients starting ART. Methods and Findings We developed a nomogram to correct mortality estimates for loss to follow-up, based on the fact that mortality of all patients starting ART in a treatment programme is a weighted average of mortality among patients lost to follow-up and patients remaining in care. The nomogram gives a correction factor based on the percentage of patients lost to follow-up at a given point in time, and the estimated ratio of mortality between patients lost and not lost to follow-up. The mortality observed among patients retained in care is then multiplied by the correction factor to obtain an estimate of programme-level mortality that takes all deaths into account. A web calculator directly calculates the corrected, programme-level mortality with 95% confidence intervals (CIs). We applied the method to 11 ART programmes in sub-Saharan Africa. Patients retained in care had a mortality at 1 year of 1.4% to 12.0%; loss to follow-up ranged from 2.8% to 28.7%; and the correction factor from 1.2 to 8.0. The absolute difference between uncorrected and corrected mortality at 1 year ranged from 1.6% to 9.8%, and was above 5% in four programmes. The largest difference in mortality was in a programme with 28.7% of patients lost to follow-up at 1 year. Conclusions The amount of bias in mortality estimates can be large in ART programmes with substantial loss to follow-up. Programmes should routinely report mortality among patients retained in care and the proportion of patients lost. A simple nomogram can then be used to estimate mortality among all patients who started ART, for a range of plausible mortality rates among patients lost to follow-up.

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Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).