Suivi de l'adhésion thérapeutique des patients hypertendus ou dyslipi- démiques par les cercles de qualité médecins-pharmaciens [Monitoring drug adherence for hypertensive and dyslipidemic patients in networks of community-based pharmacists and physicians].

Patient adherence is often poor for hypertension and dyslipidaemia. A monitoring of drug adherence might improve these risk factors control, but little is known in ambulatory care. We conducted a randomised controlled study in networks of community-based pharmacists and physicians in the canton of Fribourg to examine whether monitoring drug adherence with an electronic monitor (MEMS) would improve risk factor control among treated, but uncontrolled hypertensive and dyslipidemic patients. The results indicate that MEMS achieve a better blood pressure control and lipid profile, although its implementation requires considerable resources. The study also shows the value of collaboration between physicians and pharmacists in the field of patient adherence to improve ambulatory care of patients with cardiovascular risk factors.

Correlation between plasma and urine phenylalanine concentrations.

In this pilot study, we show that plasma phenylalanine concentration can be predicted from urine concentration if the age of the patient is taken into consideration. This observation could open the way to a new monitoring of phenylketonuric patients in which painful frequent blood sampling, mandatory to adapt the low phenylalanine diet, could be mostly replaced by urinalysis. Compliance to treatment would be improved and hence also the ultimate mental development. Since this study was based on a small number of patients, validation of the model in a large multicentric survey is needed before it can be recommended.

White matter maturation reshapes structural connectivity in the late developing human brain.

From toddler to late teenager, the macroscopic pattern of axonal projections in the human brain remains largely unchanged while undergoing dramatic functional modifications that lead to network refinement. These functional modifications are mediated by increasing myelination and changes in axonal diameter and synaptic density, as well as changes in neurochemical mediators. Here we explore the contribution of white matter maturation to the development of connectivity between ages 2 and 18 y using high b-value diffusion MRI tractography and connectivity analysis. We measured changes in connection efficacy as the inverse of the average diffusivity along a fiber tract. We observed significant refinement in specific metrics of network topology, including a significant increase in node strength and efficiency along with a decrease in clustering. Major structural modules and hubs were in place by 2 y of age, and they continued to strengthen their profile during subsequent development. Recording resting-state functional MRI from a subset of subjects, we confirmed a positive correlation between structural and functional connectivity, and in addition observed that this relationship strengthened with age. Continuously increasing integration and decreasing segregation of structural connectivity with age suggests that network refinement mediated by white matter maturation promotes increased global efficiency. In addition, the strengthening of the correlation between structural and functional connectivity with age suggests that white matter connectivity in combination with other factors, such as differential modulation of axonal diameter and myelin thickness, that are partially captured by inverse average diffusivity, play an increasingly important role in creating brain-wide coherence and synchrony.

Sleep EEG changes after middle cerebral artery infarcts in mice: different effects of striatal and cortical lesions.

STUDY OBJECTIVES: Hemispheric stroke in humans is associated with sleep-wake disturbances and sleep electroencephalogram (EEG) changes. The correlation between these changes and stroke extent remains unclear. In the absence of experimental data, we assessed sleep EEG changes after focal cerebral ischemia of different extensions in mice. DESIGN: Following electrode implantation and baseline sleep-wake EEG recordings, mice were submitted to sham surgery (control group), 30 minutes of intraluminal middle cerebral artery (MCA) occlusion (striatal stroke), or distal MCA electrocoagulation (cortical stroke). One and 12 days after stroke, sleep-wake EEG recordings were repeated. The EEG recorded from the healthy hemisphere was analyzed visually and automatically (fast Fourier analysis) according to established criteria. MEASUREMENTS AND RESULTS: Striatal stroke induced an increase in non-rapid eye movement (NREM) sleep and a reduction of rapid eye movement sleep. These changes were detectable both during the light and the dark phase at day 1 and persisted until day 12 after stroke. Cortical stroke induced a less-marked increase in NREM sleep, which was present only at day 1 and during the dark phase. In cortical stroke, the increase in NREM sleep was associated in the wake EEG power spectra, with an increase in the theta and a reduction in the beta activity. CONCLUSION: Cortical and striatal stroke lead to different sleep-wake EEG changes in mice, which probably reflect variable effects on sleep-promoting and wakefulness-maintaining neuronal networks.

The correlation between inbreeding and fitness: does allele size matter?

The availability of highly polymorphic genetic markers, in particular microsatellites, has made it possible to test the effect of inbreeding on fitness in the field and in the absence of pedigree information. It has been suggested that the squared difference in allele size at a locus (d(2)) might be a better indicator of the level of inbreeding than is heterozygosity. Using an elegant new analytical model, Tsitrone et al. now put this idea to the test, and to rest.

Unconditioned responses and functional fear networks in human classical conditioning.

Human imaging studies examining fear conditioning have mainly focused on the neural responses to conditioned cues. In contrast, the neural basis of the unconditioned response and the mechanisms by which fear modulates inter-regional functional coupling have received limited attention. We examined the neural responses to an unconditioned stimulus using a partial-reinforcement fear conditioning paradigm and functional MRI. The analysis focused on: (1) the effects of an unconditioned stimulus (an electric shock) that was either expected and actually delivered, or expected but not delivered, and (2) on how related brain activity changed across conditioning trials, and (3) how shock expectation influenced inter-regional coupling within the fear network. We found that: (1) the delivery of the shock engaged the red nucleus, amygdale, dorsal striatum, insula, somatosensory and cingulate cortices, (2) when the shock was expected but not delivered, only the red nucleus, the anterior insular and dorsal anterior cingulate cortices showed activity increases that were sustained across trials, and (3) psycho-physiological interaction analysis demonstrated that fear led to increased red nucleus coupling to insula but decreased hippocampus coupling to the red nucleus, thalamus and cerebellum. The hippocampus and the anterior insula may serve as hubs facilitating the switch between engagement of a defensive immediate fear network and a resting network.

. Phenotype/genotype correlation associated with a novel nonsense Glu20stop mutation in the Rp2 gene in a three-generation family with x-linked retinitis pigmentosa

Purpose: To assess the phenotype of patients in a large 3 generation Swiss family with X-linked retinitis pigmentosa (XLRP) due to a novel nonsense mutation Glu20stop in RP2 gene and to correlate with the genotype. Methods: 6 affected patients (1 male, 5 females, age range: 23 - 73 years) were assessed with a complete ophthalmologic examination. All had fundus autofluorescence images, standardised electroretinography, Goldmann visual fields and Optical Coherence Tomography. In addition, medical records of 2 affected male patients were reviewed. Blood sample was taken for molecular analysis. Results: The male patients were severely affected at a young age with early macular involvement. The youngest 23 y old male had also high myopia and vision of less than 0.05 according to Snellen EDTRS chart bilaterally. All 5 female carriers had some degree of rod-cone dystrophy, but no macular involvement. The visual acuity was 1.0 in the younger carriers, while the 73 years old had VA of 0.5. Two females had mild myopia (range -0.75 to -2) and one had anisometropia of 3.5D, with the more severely affected eye being myopic. Three out of 5 female carriers had optic nerve drusen. Conclusions: We report a novel Glu20stop mutation in RP2 gene, which is a rare cause of XLRP. Our description of severe phenotype in male patients with high myopia and early macular atrophy confirms previous reports. Unlike previous reports, all our female carriers had RP, but not macular involvement or high myopia. The identifiable phenotype for RP2-XLRP aids in clinical diagnosis and targeted genetic screening.

Solitary fibrous tumor of the lateral ventricle: CT appearances and pathologic correlation with follow-up.

Intracranial solitary fibrous tumors are rare, and intraventricular fibrous tumors are even more unusual. We report a case of solitary fibrous tumor in the region of trigone and body of the left lateral ventricle and discuss the clinical presentation, CT characteristics, and histopathologic features with 1-year follow-up. We speculate that the tumor arose from the perivascular connective tissue of the choroid plexus.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Multiplex real-time PCR for the diagnosis of malaria: correlation with microscopy.

Malaria is generally diagnosed by microscopy and rapid antigen testing. Molecular methods become more widely used. In the present study, the contribution of a quantitative multiplex malaria PCR was investigated. We assessed: (i) the agreement between PCR-based identification and microscopy and (ii) the correlation between the parasite load as determined by quantitative PCR and by microscopy. For 83 patients positive by microscopy for Plasmodium spp., the first EDTA-blood sample was tested by multiplex PCR to confirm smear-based species identification. Parasite load was assessed daily using both microscopy and PCR. Among the 83 patients tested, one was positive by microscopy only and 82 were positive by microscopy and PCR. Agreement between microscopy and PCR for the identification at the species level was 89% (73/82). Six of the nine discordant results corresponded to co-infections by two or three species and were attributed to inaccurate morphological identification of mixed cases. The parasite load generally decreased rapidly after treatment had been started, with similar decay curves being obtained using both microscopy and PCR. Our PCR proved especially useful for identifying mixed infections. The quantification obtained by PCR closely correlated with microscopy-based quantification and could be useful for monitoring treatment efficacy, at least in clinical trials.