Synthetic-echo time postprocessing technique for generating images with variable T2-weighted contrast: diagnosis of meniscal and cartilage abnormalities of the knee

To assess the feasibility and accuracy of a synthetic-echo time (TE) magnetic resonance (MR) postprocessing technique for the diagnostic evaluation of abnormalities of menisci and articular cartilage in the knee.

500 ml of blood loss does not decrease non-invasive tissue oxygen saturation (StO2) as measured by near infrared spectroscopy - A hypothesis generating pilot study in healthy adult women

Background The goal when resuscitating trauma patients is to achieve adequate tissue perfusion. One parameter of tissue perfusion is tissue oxygen saturation (StO2), as measured by near infrared spectroscopy. Using a commercially available device, we investigated whether clinically relevant blood loss of 500 ml in healthy volunteers can be detected by changes in StO2 after a standardized ischemic event. Methods We performed occlusion of the brachial artery for 3 minutes in 20 healthy female blood donors before and after blood donation. StO2 and total oxygenated tissue hemoglobin (O2Hb) were measured continuously at the thenar eminence. 10 healthy volunteers were assessed in the same way, to examine whether repeated vascular occlusion without blood donation exhibits time dependent effects. Results Blood donation caused a substantial decrease in systolic blood pressure, but did not affect resting StO2 and O2Hb values. No changes were measured in the blood donor group in the reaction to the vascular occlusion test, but in the control group there was an increase in the O2Hb rate of recovery during the reperfusion phase. Conclusion StO2 measured at the thenar eminence seems to be insensitive to blood loss of 500 ml in this setting. Probably blood loss greater than this might lead to detectable changes guiding the treating physician. The exact cut off for detectable changes and the time effect on repeated vascular occlusion tests should be explored further. Until now no such data exist.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

Dystrophic cardiomyopathy: amplification of cellular damage by Ca2+ signalling and reactive oxygen species-generating pathways

AIMS: Cardiac myopathies are the second leading cause of death in patients with Duchenne and Becker muscular dystrophy, the two most common and severe forms of a disabling striated muscle disease. Although the genetic defect has been identified as mutations of the dystrophin gene, very little is known about the molecular and cellular events leading to progressive cardiac muscle damage. Dystrophin is a protein linking the cytoskeleton to a complex of transmembrane proteins that interact with the extracellular matrix. The fragility of the cell membrane resulting from the lack of dystrophin is thought to cause an excessive susceptibility to mechanical stress. Here, we examined cellular mechanisms linking the initial membrane damage to the dysfunction of dystrophic heart. METHODS AND RESULTS: Cardiac ventricular myocytes were enzymatically isolated from 5- to 9-month-old dystrophic mdx and wild-type (WT) mice. Cells were exposed to mechanical stress, applied as osmotic shock. Stress-induced cytosolic and mitochondrial Ca(2+) signals, production of reactive oxygen species (ROS), and mitochondrial membrane potential were monitored with confocal microscopy and fluorescent indicators. Pharmacological tools were used to scavenge ROS and to identify their possible sources. Osmotic shock triggered excessive cytosolic Ca(2+) signals, often lasting for several minutes, in 82% of mdx cells. In contrast, only 47% of the WT cardiomyocytes responded with transient and moderate intracellular Ca(2+) signals. On average, the reaction was 6-fold larger in mdx cells. Removal of extracellular Ca(2+) abolished these responses, implicating Ca(2+) influx as a trigger for abnormal Ca(2+) signalling. Our further experiments revealed that osmotic stress in mdx cells produced an increase in ROS production and mitochondrial Ca(2+) overload. The latter was followed by collapse of the mitochondrial membrane potential, an early sign of cell death. CONCLUSION: Overall, our findings reveal that excessive intracellular Ca(2+) signals and ROS generation link the initial sarcolemmal injury to mitochondrial dysfunctions. The latter possibly contribute to the loss of functional cardiac myocytes and heart failure in dystrophy. Understanding the sequence of events of dystrophic cell damage and the deleterious amplification systems involved, including several positive feed-back loops, may allow for a rational development of novel therapeutic strategies.

PyGirl Generating Whole-System VMs from high-level models using PyPy

Virtual machines emulating hardware devices are generally implemented in low-level languages and using a low-level style for performance reasons. This trend results in largely difficult to understand, difficult to extend and unmaintainable systems. As new general techniques for virtual machines arise, it gets harder to incorporate or test these techniques because of early design and optimization decisions. In this paper we show how such decisions can be postponed to later phases by separating virtual machine implementation issues from the high-level machine-specific model. We construct compact models of whole-system VMs in a high-level language, which exclude all low-level implementation details. We use the pluggable translation toolchain PyPy to translate those models to executables. During the translation process, the toolchain reintroduces the VM implementation and optimization details for specific target platforms. As a case study we implement an executable model of a hardware gaming device. We show that our approach to VM building increases understandability, maintainability and extendability while preserving performance.

PyGirl: Generating Whole-System VMs from High-Level Prototypes Using PyPy

Virtual machines (VMs) emulating hardware devices are generally implemented in low-level languages for performance reasons. This results in unmaintainable systems that are difficult to understand. In this paper we report on our experience using the PyPy toolchain to improve the portability and reduce the complexity of whole-system VM implementations. As a case study we implement a VM prototype for a Nintendo Game Boy, called PyGirl, in which the high-level model is separated from low-level VM implementation issues. We shed light on the process of refactoring from a low-level VM implementation in Java to a high-level model in RPython. We show that our whole-system VM written with PyPy is significantly less complex than standard implementations, without substantial loss in performance.

Wnt activation of immortalized brain endothelial cells as a tool for generating a standardized model of the blood brain barrier in vitro

Reproducing the characteristics and the functional responses of the blood-brain barrier (BBB) in vitro represents an important task for the research community, and would be a critical biotechnological breakthrough. Pharmaceutical and biotechnology industries provide strong demand for inexpensive and easy-to-handle in vitro BBB models to screen novel drug candidates. Recently, it was shown that canonical Wnt signaling is responsible for the induction of the BBB properties in the neonatal brain microvasculature in vivo. In the present study, following on from earlier observations, we have developed a novel model of the BBB in vitro that may be suitable for large scale screening assays. This model is based on immortalized endothelial cell lines derived from murine and human brain, with no need for co-culture with astrocytes. To maintain the BBB endothelial cell properties, the cell lines are cultured in the presence of Wnt3a or drugs that stabilize β-catenin, or they are infected with a transcriptionally active form of β-catenin. Upon these treatments, the cell lines maintain expression of BBB-specific markers, which results in elevated transendothelial electrical resistance and reduced cell permeability. Importantly, these properties are retained for several passages in culture, and they can be reproduced and maintained in different laboratories over time. We conclude that the brain-derived endothelial cell lines that we have investigated gain their specialized characteristics upon activation of the canonical Wnt pathway. This model may be thus suitable to test the BBB permeability to chemicals or large molecular weight proteins, transmigration of inflammatory cells, treatments with cytokines, and genetic manipulation.

Bounds for the probability generating functional of a Gibbs point process

We derive explicit lower and upper bounds for the probability generating functional of a stationary locally stable Gibbs point process, which can be applied to summary statistics such as the F function. For pairwise interaction processes we obtain further estimates for the G and K functions, the intensity, and higher-order correlation functions. The proof of the main result is based on Stein's method for Poisson point process approximation.