907 resultados para Single-Blind Method


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Developing a fast, inexpensive, and specific test that reflects the mutations present in Mycobacterium tuberculosis isolates according to geographic region is the main challenge for drug-resistant tuberculosis (TB) control. The objective of this study was to develop a molecular platform to make a rapid diagnosis of multidrug-resistant (MDR) and extensively drug-resistant TB based on single nucleotide polymorphism (SNP) mutations present in therpoB, katG, inhA,ahpC, and gyrA genes from Colombian M. tuberculosis isolates. The amplification and sequencing of each target gene was performed. Capture oligonucleotides, which were tested before being used with isolates to assess the performance, were designed for wild type and mutated codons, and the platform was standardised based on the reverse hybridisation principle. This method was tested on DNA samples extracted from clinical isolates from 160 Colombian patients who were previously phenotypically and genotypically characterised as having susceptible or MDR M. tuberculosis. For our method, the kappa index of the sequencing results was 0,966, 0,825, 0,766, 0,740, and 0,625 forrpoB, katG, inhA,ahpC, and gyrA, respectively. Sensitivity and specificity were ranked between 90-100% compared with those of phenotypic drug susceptibility testing. Our assay helps to pave the way for implementation locally and for specifically adapted methods that can simultaneously detect drug resistance mutations to first and second-line drugs within a few hours.

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We performed a comprehensive study to assess the fit for purpose of four chromatographic conditions for the determination of six groups of marine lipophilic toxins (okadaic acid and dinophysistoxins, pectenotoxins, azaspiracids, yessotoxins, gymnodimine and spirolides) by LC-MS/MS to select the most suitable conditions as stated by the European Union Reference Laboratory for Marine Biotoxins (EURLMB). For every case, the elution gradient has been optimized to achieve a total run-time cycle of 12 min. We performed a single-laboratory validation for the analysis of three relevant matrices for the seafood aquaculture industry (mussels, pacific oysters and clams), and for sea urchins for which no data about lipophilic toxins have been reported before. Moreover, we have compared the method performance under alkaline conditions using two quantification strategies: the external standard calibration (EXS) and the matrix-matched standard calibration (MMS). Alkaline conditions were the only scenario that allowed detection windows with polarity switching in a 3200 QTrap mass spectrometer, thus the analysis of all toxins can be accomplished in a single run, increasing sample throughput. The limits of quantification under alkaline conditions met the validation requirements established by the EURLMB for all toxins and matrices, while the remaining conditions failed in some cases. The accuracy of the method and the matrix effects where generally dependent on the mobile phases and the seafood species. The MMS had a moderate positive impact on method accuracy for crude extracts, but it showed poor trueness for seafood species other than mussels when analyzing hydrolyzed extracts. Alkaline conditions with EXS and recovery correction for OA were selected as the most proper conditions in the context of our laboratory. This comparative study can help other laboratories to choose the best conditions for the implementation of LC-MS/MS according to their own necessities.

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Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.

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Neuroimaging studies analyzing neurophysiological signals are typically based on comparing averages of peri-stimulus epochs across experimental conditions. This approach can however be problematic in the case of high-level cognitive tasks, where response variability across trials is expected to be high and in cases where subjects cannot be considered part of a group. The main goal of this thesis has been to address this issue by developing a novel approach for analyzing electroencephalography (EEG) responses at the single-trial level. This approach takes advantage of the spatial distribution of the electric field on the scalp (topography) and exploits repetitions across trials for quantifying the degree of discrimination between experimental conditions through a classification scheme. In the first part of this thesis, I developed and validated this new method (Tzovara et al., 2012a,b). Its general applicability was demonstrated with three separate datasets, two in the visual modality and one in the auditory. This development allowed then to target two new lines of research, one in basic and one in clinical neuroscience, which represent the second and third part of this thesis respectively. For the second part of this thesis (Tzovara et al., 2012c), I employed the developed method for assessing the timing of exploratory decision-making. Using single-trial topographic EEG activity during presentation of a choice's payoff, I could predict the subjects' subsequent decisions. This prediction was due to a topographic difference which appeared on average at ~516ms after the presentation of payoff and was subject-specific. These results exploit for the first time the temporal correlates of individual subjects' decisions and additionally show that the underlying neural generators start differentiating their responses already ~880ms before the button press. Finally, in the third part of this project, I focused on a clinical study with the goal of assessing the degree of intact neural functions in comatose patients. Auditory EEG responses were assessed through a classical mismatch negativity paradigm, during the very early phase of coma, which is currently under-investigated. By taking advantage of the decoding method developed in the first part of the thesis, I could quantify the degree of auditory discrimination at the single patient level (Tzovara et al., in press). Our results showed for the first time that even patients who do not survive the coma can discriminate sounds at the neural level, during the first hours after coma onset. Importantly, an improvement in auditory discrimination during the first 48hours of coma was predictive of awakening and survival, with 100% positive predictive value. - L'analyse des signaux électrophysiologiques en neuroimagerie se base typiquement sur la comparaison des réponses neurophysiologiques à différentes conditions expérimentales qui sont moyennées après plusieurs répétitions d'une tâche. Pourtant, cette approche peut être problématique dans le cas des fonctions cognitives de haut niveau, où la variabilité des réponses entre les essais peut être très élevéeou dans le cas où des sujets individuels ne peuvent pas être considérés comme partie d'un groupe. Le but principal de cette thèse est d'investiguer cette problématique en développant une nouvelle approche pour l'analyse des réponses d'électroencephalographie (EEG) au niveau de chaque essai. Cette approche se base sur la modélisation de la distribution du champ électrique sur le crâne (topographie) et profite des répétitions parmi les essais afin de quantifier, à l'aide d'un schéma de classification, le degré de discrimination entre des conditions expérimentales. Dans la première partie de cette thèse, j'ai développé et validé cette nouvelle méthode (Tzovara et al., 2012a,b). Son applicabilité générale a été démontrée avec trois ensembles de données, deux dans le domaine visuel et un dans l'auditif. Ce développement a permis de cibler deux nouvelles lignes de recherche, la première dans le domaine des neurosciences cognitives et l'autre dans le domaine des neurosciences cliniques, représentant respectivement la deuxième et troisième partie de ce projet. En particulier, pour la partie cognitive, j'ai appliqué cette méthode pour évaluer l'information temporelle de la prise des décisions (Tzovara et al., 2012c). En se basant sur l'activité topographique de l'EEG au niveau de chaque essai pendant la présentation de la récompense liée à un choix, on a pu prédire les décisions suivantes des sujets (en termes d'exploration/exploitation). Cette prédiction s'appuie sur une différence topographique qui apparaît en moyenne ~516ms après la présentation de la récompense. Ces résultats exploitent pour la première fois, les corrélés temporels des décisions au niveau de chaque sujet séparément et montrent que les générateurs neuronaux de ces décisions commencent à différentier leurs réponses déjà depuis ~880ms avant que les sujets appuient sur le bouton. Finalement, pour la dernière partie de ce projet, je me suis focalisée sur une étude Clinique afin d'évaluer le degré des fonctions neuronales intactes chez les patients comateux. Des réponses EEG auditives ont été examinées avec un paradigme classique de mismatch negativity, pendant la phase précoce du coma qui est actuellement sous-investiguée. En utilisant la méthode de décodage développée dans la première partie de la thèse, j'ai pu quantifier le degré de discrimination auditive au niveau de chaque patient (Tzovara et al., in press). Nos résultats montrent pour la première fois que même des patients comateux qui ne vont pas survivre peuvent discriminer des sons au niveau neuronal, lors de la phase aigue du coma. De plus, une amélioration dans la discrimination auditive pendant les premières 48heures du coma a été observée seulement chez des patients qui se sont réveillés par la suite (100% de valeur prédictive pour un réveil).

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A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants

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BACKGROUND: The diagnosis of hypertension in children is difficult because of the multiple sex-, age-, and height-specific thresholds to define elevated blood pressure (BP). Blood pressure-to-height ratio (BPHR) has been proposed to facilitate the identification of elevated BP in children. OBJECTIVE: We assessed the performance of BPHR at a single screening visit to identify children with hypertension that is sustained elevated BP. METHOD: In a school-based study conducted in Switzerland, BP was measured at up to three visits in 5207 children. Children had hypertension if BP was elevated at the three visits. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for the identification of hypertension were assessed for different thresholds of BPHR. The ability of BPHR at a single screening visit to discriminate children with and without hypertension was evaluated with receiver operating characteristic (ROC) curve analyses. RESULTS: The prevalence of systolic/diastolic hypertension was 2.2%. Systolic BPHR had a better performance to identify hypertension compared with diastolic BPHR (area under the ROC curve: 0.95 vs. 0.84). The highest performance was obtained with a systolic BPHR threshold set at 0.80 mmHg/cm (sensitivity: 98%; specificity: 85%; PPV: 12%; and NPV: 100%) and a diastolic BPHR threshold set at 0.45 mmHg/cm (sensitivity: 79%; specificity: 70%; PPV: 5%; and NPV: 99%). The PPV was higher among tall or overweight children. CONCLUSION: BPHR at a single screening visit had a high performance to identify hypertension in children, although the low prevalence of hypertension led to a low PPV.

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Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.

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The diagnosis of muscular dystrophies or the assessment of the functional benefit of gene or cell therapies can be difficult, especially for poorly accessible muscles, and it often lacks a singlefiber resolution. In the present study, we evaluated whether muscle diseases can be diagnosed from small biopsies using atomic force microscopy (AFM). AFM was shown to provide a sensitive and quantitative description of the resistance of normal and dystrophic myofibers within live muscle tissues explanted from Duchenne mdx mice. The rescue of dystrophin expression by gene therapy approaches led to the functional recovery of treated dystrophic muscle fibers, as probed using AFM and by in situ wholemuscle strength measurements. Comparison of muscles treated with viral or non-viral vectors indicated that the efficacy of the gene transfer approaches could be distinguished with a single myofiber resolution. This indicated full correction of the resistance to deformation in nearly all of the muscle fibers treated with an adeno-associated viral vector that mediates exon-skipping on the dystrophin mRNA. Having shown that AFM can provide a quantitative assessment of the expression of muscle proteins and of the muscular function in animal models, we assessed myofiber resistance in the context of human muscular dystrophies and myopathies. Thus, various forms of human Becker syndrome can also be detected using AFM in blind studies of small frozen biopsies from human patients. Interestingly, it also allowed the detection of anomalies in a fraction of the muscle fibers from patients showing a muscle weakness that could not be attributed to a known molecular or genetic defect. Overall, we conclude that AFM may provide a useful method to complement current diagnosis tools of known and unknown muscular diseases, in research and in a clinical context.

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In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

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Mathematical methods combined with measurements of single-cell dynamics provide a means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions, the pooling of measurements from several cells of a clonal population is mandatory. However, cell-to-cell variability originating from diverse sources poses computational challenges for such process reconstruction. We introduce a scalable Bayesian inference framework that properly accounts for population heterogeneity. The method allows inference of inaccessible molecular states and kinetic parameters; computation of Bayes factors for model selection; and dissection of intrinsic, extrinsic and technical noise. We show how additional single-cell readouts such as morphological features can be included in the analysis. We use the method to reconstruct the expression dynamics of a gene under an inducible promoter in yeast from time-lapse microscopy data.

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OBJECTIVE To evaluate the efficacy of Calendula officinalis in relation to Essential Fatty Acids for the prevention and treatment of radiodermatitis. METHOD This is a randomized double-blind controlled clinical trial with 51 patients with head and neck cancer in radiotherapy treatment divided into two groups: control (27) and experimental (24). RESULTS There is statistically significant evidence (p-value = 0.0120) that the proportion of radiodermatitis grade 2 in Essential Fatty Acids group is higher than Calendula group. Through the Kaplan-Meier survival curve we observed that Essential Fatty Acids group has always remained below the Calendula group survival curve, due to the lower risk of developing radiodermatitis grade 1, which makes the usage of Calendula more effective, with statistical significance (p-value = 0.00402). CONCLUSION Calendula showed better therapeutic response than the Essential Fatty Acids in the prevention and treatment of radiodermatitis. Brazilian Registry of Clinical Trials: RBR-237v4b.

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PURPOSE: To evaluate the utility of inversion recovery with on-resonant water suppression (IRON) in combination with injection of the long-circulating monocrystalline iron oxide nanoparticle (MION)-47 for contrast material-enhanced magnetic resonance (MR) angiography. MATERIALS AND METhods: Experiments were approved by the institutional animal care committee. Eleven rabbits were imaged at baseline before injection of a contrast agent and then serially 5-30 minutes, 2 hours, 1 day, and 3 days after a single intravenous bolus injection of 80 micromol of MION-47 per kilogram of body weight (n = 6) or 250 micromol/kg MION-47 (n = 5). Conventional T1-weighted MR angiography and IRON MR angiography were performed on a clinical 3.0-T imager. Signal-to-noise and contrast-to-noise ratios were measured in the aorta of rabbits in vivo. Venous blood was obtained from the rabbits before and after MION-47 injection for use in phantom studies. RESULTS: In vitro blood that contained MION-47 appeared signal attenuated on T1-weighted angiograms, while characteristic signal-enhanced dipolar fields were observed on IRON angiograms. In vivo, the vessel lumen was signal attenuated on T1-weighted MR angiograms after MION-47 injection, while IRON supported high intravascular contrast by simultaneously providing positive signal within the vessels and suppressing background tissue (mean contrast-to-noise ratio, 61.9 +/- 12.4 [standard deviation] after injection vs 1.1 +/- 0.4 at baseline, P < .001). Contrast-to-noise ratio was higher on IRON MR angiograms than on conventional T1-weighted MR angiograms (9.0 +/- 2.5, P < .001 vs IRON MR angiography) and persisted up to 24 hours after MION-47 injection (76.2 +/- 15.9, P < .001 vs baseline). CONCLUSION: IRON MR angiography in conjunction with superparamagnetic nanoparticle administration provides high intravascular contrast over a long time and without the need for image subtraction.

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Aims: A rapid and simple HPLC-MS method was developed for the simultaneousdetermination of antidementia drugs, including donepezil, galantamine, rivastigmineand its major metabolite NAP 226 - 90, and memantine, for TherapeuticDrug Monitoring (TDM). In the elderly population treated with antidementiadrugs, the presence of several comorbidities, drug interactions resulting frompolypharmacy, and variations in drug metabolism and elimination, are possiblefactors leading to the observed high interindividual variability in plasma levels.Although evidence for the benefit of TDM for antidementia drugs still remains tobe demonstrated, an individually adapted dosage through TDM might contributeto minimize the risk of adverse reactions and to increase the probability of efficienttherapeutic response. Methods: A solid-phase extraction procedure with amixed-mode cation exchange sorbent was used to isolate the drugs from 0.5 mL ofplasma. The compounds were analyzed on a reverse-phase column with a gradientelution consisting of an ammonium acetate buffer at pH 9.3 and acetonitrile anddetected by mass spectrometry in the single ion monitoring mode. Isotope-labeledinternal standards were used for quantification where possible. The validatedmethod was used to measure the plasma levels of antidementia drugs in 300patients treated with these drugs. Results: The method was validated accordingto international standards of validation, including the assessment of the trueness(-8 - 11 %), the imprecision (repeatability: 1-5%, intermediate imprecision:2 - 9 %), selectivity and matrix effects variability (less than 6 %). Furthermore,short and long-term stability of the analytes in plasma was ascertained. Themethod proved to be robust in the calibrated ranges of 1 - 300 ng/mL for rivastigmineand memantine and 2 - 300 mg/mL for donepezil, galantamine and NAP226 - 90. We recently published a full description of the method (1). We found ahigh interindividual variability in plasma levels of these drugs in a study populationof 300 patients. The plasma level measurements, with some preliminaryclinical and pharmacogenetic results, will be presented. Conclusion: A simpleLC-MS method was developed for plasma level determination of antidementiadrugs which was successfully used in a clinical study with 300 patients.

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There are various methods of providing pain relief for painful blind eyes. We wish to recommend this effective method of providing temporary analgesia in patients suffering from a severe painful blind eye before undergoing enucleation.

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We address the performance optimization problem in a single-stationmulticlass queueing network with changeover times by means of theachievable region approach. This approach seeks to obtainperformance bounds and scheduling policies from the solution of amathematical program over a relaxation of the system's performanceregion. Relaxed formulations (including linear, convex, nonconvexand positive semidefinite constraints) of this region are developedby formulating equilibrium relations satisfied by the system, withthe help of Palm calculus. Our contributions include: (1) newconstraints formulating equilibrium relations on server dynamics;(2) a flow conservation interpretation of the constraintspreviously derived by the potential function method; (3) newpositive semidefinite constraints; (4) new work decomposition lawsfor single-station multiclass queueing networks, which yield newconvex constraints; (5) a unified buffer occupancy method ofperformance analysis obtained from the constraints; (6) heuristicscheduling policies from the solution of the relaxations.