Method for performing cerebral perfusion-weighted MRI in neonates

Cerebral perfusion-weighted imaging (PWI) in neonates is known to be technically difficult and there are very few published studies on its use in preterm infants. In this paper, we describe one convenient method to perform PWI in neonates, a method only recently used in newborns. A device was used to manually inject gadolinium contrast material intravenously in an easy, quick and reproducible way. We studied 28 newborn infants, with various gestational ages and weights, including both normal infants and those suffering from different brain pathologies. A signal intensity-time curve was obtained for each infant, allowing us to build perfusion maps. This technique offered a fast and easy method to manually inject a bolus gadolinium contrast material, which is essential in performing PWI in neonates. Cerebral PWI is technically feasible and reproducible in neonates of various gestational age and with various pathologies.

A fast 3D approach for coronary MRA.

Two-dimensional (2D)-breath-hold coronary magnetic resonance angiography (MRA) has been shown to be a fast and reliable method to depict the proximal coronary arteries. Recent developments, however, allow for free-breathing navigator gated and navigator corrected three-dimensional (3D) coronary MRA. These 3D approaches have potential for improved signal-to-noise ratio (SNR) and allow for the acquisition of adjacent thin slices without the misregistration problems known from 2D approaches. Still, a major impediment of a 3D acquisition is the increased scan time. The purpose of this study was the implementation of a free-breathing navigator gated and corrected ultra-fast 3D coronary MRA technique, which allows for scan times of less than 5 minutes. Twelve healthy adult subjects were examined in the supine position using a navigator gated and corrected ECG triggered ultra-fast 3D interleaved gradient echo planar imaging sequence (TFE-EPI). A 3D slab, consisting of 20 slices with a reconstructed slice thickness of 1.5 mm, was acquired with free-breathing. The diastolic TFE-EPI acquisition block was preceded by a T2prep pre-pulse, a diaphragmatic navigator pulse, and a fat suppression pre-pulse. With a TR of 19 ms and an effective TE of 5.4 ms, the duration of the data acquisition window duration was 38 ms. The in-plane spatial resolution was 1.0-1.3 mm*1.5-1.9 mm. In all cases, the entire left main (LM) and extensive portions of the left anterior descending (LAD) and right coronary artery (RCA) could be visualized with an average scan time for the entire 3D-volume data set of 2:57 +/- 0:51 minutes. Average contiguous vessel length visualized was 53 +/- 11 mm (range: 42 to 75 mm) for the LAD and 84 +/- 14 mm (range: 62 to 112 mm) for the RCA. Contrast-to-noise between coronary blood and myocardium was 5.0 +/- 2.3 for the LM/LAD and 8.0 +/- 2.9 for the RCA, resulting in an excellent suppression of myocardium. We present a new approach for free-breathing 3D coronary MRA, which allows for scan times superior to corresponding 2D coronary MRA approaches, and which takes advantage of the enhanced SNR of 3D acquisitions and the post-processing benefits of thin adjacent slices. The robust image quality and the short average scanning time suggest that this approach may be useful for screening the major coronary arteries or identification of anomalous coronary arteries. J. Magn. Reson. Imaging 1999;10:821-825.

Quantitative antibiogram as a typing method for the prospective epidemiological surveillance and control of MRSA: comparison with molecular typing.

OBJECTIVE: Evaluation of the quantitative antibiogram as an epidemiological tool for the prospective typing of methicillin-resistant Staphylococcus aureus (MRSA), and comparison with ribotyping. METHODS: The method is based on the multivariate analysis of inhibition zone diameters of antibiotics in disk diffusion tests. Five antibiotics were used (erythromycin, clindamycin, cotrimoxazole, gentamicin, and ciprofloxacin). Ribotyping was performed using seven restriction enzymes (EcoRV, HindIII, KpnI, PstI, EcoRI, SfuI, and BamHI). SETTING: 1,000-bed tertiary university medical center. RESULTS: During a 1-year period, 31 patients were found to be infected or colonized with MRSA. Cluster analysis of antibiogram data showed nine distinct antibiotypes. Four antibiotypes were isolated from multiple patients (2, 4, 7, and 13, respectively). Five additional antibiotypes were isolated from the remaining five patients. When analyzed with respect to the epidemiological data, the method was found to be equivalent to ribotyping. Among 206 staff members who were screened, six were carriers of MRSA. Both typing methods identified concordant of MRSA types in staff members and in the patients under their care. CONCLUSIONS: The quantitative antibiogram was found to be equivalent to ribotyping as an epidemiological tool for typing of MRSA in our setting. Thus, this simple, rapid, and readily available method appears to be suitable for the prospective surveillance and control of MRSA for hospitals that do not have molecular typing facilities and in which MRSA isolates are not uniformly resistant or susceptible to the antibiotics tested.

Manipulating the sensitivity of signal-induced repression: quantification and consequences of altered brinker gradients.

Traditionally, the analysis of gene regulatory regions suffered from the caveat that it was restricted to artificial contexts (e.g. reporter constructs of limited size). With the advent of the BAC recombineering technique, genomic constructs can now be generated to test regulatory elements in their endogenous environment. The expression of the transcriptional repressor brinker (brk) is negatively regulated by Dpp signaling. Repression is mediated by small sequence motifs, the silencer elements (SEs), that are present in multiple copies in the regulatory region of brk. In this work, we manipulated the SEs in the brk locus. We precisely quantified the effects of the individual SEs on the Brk gradient in the wing disc by employing a 1D data extraction method, followed by the quantification of the data with reference to an internal control. We found that mutating the SEs results in an expansion of the brk expression domain. However, even after mutating all predicted SEs, repression could still be observed in regions of maximal Dpp levels. Thus, our data point to the presence of additional, low affinity binding sites in the brk locus.

Therapeutic drug monitoring of seven psychotropic drugs and four metabolites in human plasma by HPLC-MS.

A simple and sensitive LC-MS method was developed and validated for the simultaneous quantification of aripiprazole (ARI), atomoxetine (ATO), duloxetine (DUL), clozapine (CLO), olanzapine (OLA), sertindole (STN), venlafaxine (VEN) and their active metabolites dehydroaripiprazole (DARI), norclozapine (NCLO), dehydrosertindole (DSTN) and O-desmethylvenlafaxine (OVEN) in human plasma. The above mentioned compounds and the internal standard (remoxipride) were extracted from 0.5 mL plasma by solid-phase extraction (mix mode support). The analytical separation was carried out on a reverse phase liquid chromatography at basic pH (pH 8.1) in gradient mode. All analytes were monitored by MS detection in the single ion monitoring mode and the method was validated covering the corresponding therapeutic range: 2-200 ng/mL for DUL, OLA, and STN, 4-200 ng/mL for DSTN, 5-1000 ng/mL for ARI, DARI and finally 2-1000 ng/mL for ATO, CLO, NCLO, VEN, OVEN. For all investigated compounds, good performance in terms of recoveries, selectivity, stability, repeatability, intermediate precision, trueness and accuracy, was obtained. Real patient plasma samples were then successfully analysed.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.

The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

A novel method of dynamic culture surface expansion improves mesenchymal stem cell proliferation and phenotype.

Repeated passaging in conventional cell culture reduces pluripotency and proliferation capacity of human mesenchymal stem cells (MSC). We introduce an innovative cell culture method whereby the culture surface is dynamically enlarged during cell proliferation. This approach maintains constantly high cell density while preventing contact inhibition of growth. A highly elastic culture surface was enlarged in steps of 5% over the course of a 20-day culture period to 800% of the initial surface area. Nine weeks of dynamic expansion culture produced 10-fold more MSC compared with conventional culture, with one-third the number of trypsin passages. After 9 weeks, MSC continued to proliferate under dynamic expansion but ceased to grow in conventional culture. Dynamic expansion culture fully retained the multipotent character of MSC, which could be induced to differentiate into adipogenic, chondrogenic, osteogenic, and myogenic lineages. Development of an undesired fibrogenic myofibroblast phenotype was suppressed. Hence, our novel method can rapidly provide the high number of autologous, multipotent, and nonfibrogenic MSC needed for successful regenerative medicine.

A multilevel multiscale finite volume method

The Multiscale Finite Volume (MsFV) method has been developed to efficiently solve reservoir-scale problems while conserving fine-scale details. The method employs two grid levels: a fine grid and a coarse grid. The latter is used to calculate a coarse solution to the original problem, which is interpolated to the fine mesh. The coarse system is constructed from the fine-scale problem using restriction and prolongation operators that are obtained by introducing appropriate localization assumptions. Through a successive reconstruction step, the MsFV method is able to provide an approximate, but fully conservative fine-scale velocity field. For very large problems (e.g. one billion cell model), a two-level algorithm can remain computational expensive. Depending on the upscaling factor, the computational expense comes either from the costs associated with the solution of the coarse problem or from the construction of the local interpolators (basis functions). To ensure numerical efficiency in the former case, the MsFV concept can be reapplied to the coarse problem, leading to a new, coarser level of discretization. One challenge in the use of a multilevel MsFV technique is to find an efficient reconstruction step to obtain a conservative fine-scale velocity field. In this work, we introduce a three-level Multiscale Finite Volume method (MlMsFV) and give a detailed description of the reconstruction step. Complexity analyses of the original MsFV method and the new MlMsFV method are discussed, and their performances in terms of accuracy and efficiency are compared.