Rapid LC-MS/MS quantification of the major benzodiazepines and their metabolites on dried blood spots using a simple and cost-effective sample pretreatment.

BACKGROUND: Dried blood spots (DBS) sampling has gained popularity in the bioanalytical community as an alternative to conventional plasma sampling, as it provides numerous benefits in terms of sample collection and logistics. The aim of this work was to show that these advantages can be coupled with a simple and cost-effective sample pretreatment, with subsequent rapid LC-MS/MS analysis for quantitation of 15 benzodiazepines, six metabolites and three Z-drugs. For this purpose, a simplified offline procedure was developed that consisted of letting a 5-µl DBS infuse directly into 100 µl of MeOH, in a conventional LC vial. RESULTS: The parameters related to the DBS pretreatment, such as extraction time or internal standard addition, were investigated and optimized, demonstrating that passive infusion in a regular LC vial was sufficient to quantitatively extract the analytes of interest. The method was validated according to international criteria in the therapeutic concentration ranges of the selected compounds. CONCLUSION: The presented strategy proved to be efficient for the rapid analysis of the selected drugs. Indeed, the offline sample preparation was reduced to a minimum, using a small amount of organic solvent and consumables, without affecting the accuracy of the method. Thus, this approach enables simple and rapid DBS analysis, even when using a non-DBS-dedicated autosampler, while lowering the costs and environmental impact.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study.

To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

Buprenorphine and norbuprenorphine quantification in human plasma by simple protein precipitation and ultra-high performance liquid chromatography tandem mass spectrometry.

A highly sensitive ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method was developed for the quantification of buprenorphine and its major metabolite norbuprenorphine in human plasma. In order to speed up the process and decrease costs, sample preparation was performed by simple protein precipitation with acetonitrile. To the best of our knowledge, this is the first application of this extraction technique for the quantification of buprenorphine in plasma. Matrix effects were strongly reduced and selectivity increased by using an efficient chromatographic separation on a sub-2μm column (Acquity UPLC BEH C18 1.7μm, 2.1×50mm) in 5min with a gradient of ammonium formate 20mM pH 3.05 and acetonitrile as mobile phase at a flow rate of 0.4ml/min. Detection was made using a tandem quadrupole mass spectrometer operating in positive electrospray ionization mode, using multiple reaction monitoring. The procedure was fully validated according to the latest Food and Drug Administration guidelines and the Société Française des Sciences et Techniques Pharmaceutiques. Very good results were obtained by using a stable isotope-labeled internal standard for each analyte, to compensate for the variability due to the extraction and ionization steps. The method was very sensitive with lower limits of quantification of 0.1ng/ml for buprenorphine and 0.25ng/ml for norbuprenorphine. The upper limit of quantification was 250ng/ml for both drugs. Trueness (98.4-113.7%), repeatability (1.9-7.7%), intermediate precision (2.6-7.9%) and internal standard-normalized matrix effects (94-101%) were in accordance with international recommendations. The procedure was successfully used to quantify plasma samples from patients included in a clinical pharmacogenetic study and can be transferred for routine therapeutic drug monitoring in clinical laboratories without further development.

Outcomes of minimally invasive simple prostatectomy for benign prostatic hyperplasia: a systematic review and meta-analysis.

PURPOSE: (1) To assess the outcomes of minimally invasive simple prostatectomy (MISP) for the treatment of symptomatic benign prostatic hyperplasia in men with large prostates and (2) to compare them with open simple prostatectomy (OSP). METHODS: A systematic review of outcomes of MISP for benign prostatic hyperplasia with meta-analysis was conducted. The article selection process was conducted according to the PRISMA guidelines. RESULTS: Twenty-seven observational studies with 764 patients were analyzed. The mean prostate volume was 113.5 ml (95 % CI 106-121). The mean increase in Qmax was 14.3 ml/s (95 % CI 13.1-15.6), and the mean improvement in IPSS was 17.2 (95 % CI 15.2-19.2). Mean duration of operation was 141 min (95 % CI 124-159), and the mean intraoperative blood loss was 284 ml (95 % CI 243-325). One hundred and four patients (13.6 %) developed a surgical complication. In comparative studies, length of hospital stay (WMD -1.6 days, p = 0.02), length of catheter use (WMD -1.3 days, p = 0.04) and estimated blood loss (WMD -187 ml, p = 0.015) were significantly lower in the MISP group, while the duration of operation was longer than in OSP (WMD 37.8 min, p < 0.0001). There were no differences in improvements in Qmax, IPSS and perioperative complications between both procedures. The small study sizes, publication bias, lack of systematic complication reporting and short follow-up are limitations. CONCLUSIONS: MISP seems an effective and safe treatment option. It provides similar improvements in Qmax and IPSS as OSP. Despite taking longer, it results in less blood loss and shorter hospital stay. Prospective randomized studies comparing OSP, MISP and laser enucleation are needed to define the standard surgical treatment for large prostates.

Copeptin is associated with kidney length, renal function, and prevalence of simple cysts in a population-based study.

Arginine vasopressin (AVP) has a key role in osmoregulation by facilitating water transport in the collecting duct. Recent evidence suggests that AVP may have additional effects on renal function and favor cyst growth in polycystic kidney disease. Whether AVP also affects kidney structure in the general population is unknown. We analyzed the association of copeptin, an established surrogate for AVP, with parameters of renal function and morphology in a multicentric population-based cohort. Participants from families of European ancestry were randomly selected in three Swiss cities. We used linear multilevel regression analysis to explore the association of copeptin with renal function parameters as well as kidney length and the presence of simple renal cysts assessed by ultrasound examination. Copeptin levels were log-transformed. The 529 women and 481 men had median copeptin levels of 3.0 and 5.2 pmol/L, respectively (P<0.001). In multivariable analyses, the copeptin level was associated inversely with eGFR (β=-2.1; 95% confidence interval [95% CI], -3.3 to -0.8; P=0.002) and kidney length (β=-1.2; 95% CI, -1.9 to -0.4; P=0.003) but positively with 24-hour urinary albumin excretion (β=0.11; 95% CI, 0.01 to 0.20; P=0.03) and urine osmolality (β=0.08; 95% CI, 0.05 to 0.10; P<0.001). A positive association was found between the copeptin level and the presence of renal cysts (odds ratio, 1.6; 95% CI, 1.1 to 2.4; P=0.02). These results suggest that AVP has a pleiotropic role in renal function and may favor the development of simple renal cysts.