The role of blood vessels in high-resolution volume conductor head modeling of EEG.

Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.

Variability in growth/no growth boundaries of 188 different Escherichia coli strains reveals that approximately 75% have a higher growth probability under low pH conditions than E. coli O157:H7 strain ATCC 43888.

This study investigated the variation in growth/no growth boundaries of 188 Escherichia coli strains. Experiments were conducted in Luria-Bertani media under 36 combinations of lactic acid (LA) (0 and 25 mM), pH (3.8, 3.9, 4.0, 4.1, 4.2 and 4.3 for 0 mM LA and 4.3, 4.4, 4.5, 4.6, 4.7 and 4.8 for 25 mM LA) and temperature (20, 25 and 30 °C). After 3 days of incubation, growth was monitored through optical density measurements. For each strain, a so-called purposeful selection approach was used to fit a logistic regression model that adequately predicted the likelihood for growth. Further, to assess the growth/no growth variability for all the strains at once, a generalized linear mixed model was fitted to the data. Strain was fitted as a fixed factor and replicate as a random blocking factor. E. coli O157:H7 strain ATCC 43888 was used as reference strain allowing a comparison with the other strains. Out of the 188 strains tested, 140 strains (∼75%) presented a significantly higher probability of growth under low pH conditions than the O157:H7 strain ATCC 43888, whereas 20 strains (∼11%) showed a significantly lower probability of growth under high pH conditions.

Lysozyme inhibitor conferring bacterial tolerance to invertebrate type lysozyme.

Invertebrate (I-) type lysozymes, like all other known lysozymes, are dedicated to the hydrolysis of peptidoglycan, the major bacterial cell wall polymer, thereby contributing to the innate immune system and/or digestive system of invertebrate organisms. Bacteria on the other hand have developed several protective strategies against lysozymes, including the production of periplasmic and/or membrane-bound lysozyme inhibitors. The latter have until now only been described for chicken (C-) type lysozymes. We here report the discovery, purification, identification and characterization of the first bacterial specific I-type lysozyme inhibitor from Aeromonas hydrophila, which we designate PliI (periplasmic lysozyme inhibitor of the I-type lysozyme). PliI has homologs in several proteobacterial genera and contributes to I-type lysozyme tolerance in A. hydrophila in the presence of an outer membrane permeabilizer. These and previous findings on C-type lysozyme inhibitors suggest that bacterial lysozyme inhibitors may have an important function, for example, in bacteria-host interactions.

Role of the alternative sigma factor sigma on Staphylococcus aureus resistance to stresses of relevance to food preservation.

AIMS: To examine the role of the alternative general stress sigma factor sigma(B) on the resistance of Staphylococcus aureus to stresses of relevance to food preservation, with special emphasis on emerging technologies such as pulsed electric fields (PEF) and high hydrostatic pressure (HHP). METHODS AND RESULTS: S. aureus strain Newman and its isogenic DeltasigB mutant were grown to exponential and stationary growth phases and its resistance to various stresses was tested. The absence of the sigma(B) factor caused a decrease in the resistance to heat, PEF, HHP, alkali, acid and hydrogen peroxide. In the case of heat, the influence of the sigma(B) factor was particularly important, and decreases in decimal reduction time values of ninefold were observed as a result of its deficiency. The increased thermotolerance of the parental strain as compared with the sigB mutant could be attributed to a better capacity to sustain and repair sublethal damages caused by heat. CONCLUSIONS: sigma(B) factor provides S. aureus cells with resistance to multiple stresses, increasing survival to heat, PEF and HHP treatments. SIGNIFICANCE AND IMPACT OF THE STUDY: Results obtained in this work help in understanding the physiological mechanisms behind cell survival and death in food-processing environments.

Inactivation of Salmonella Senftenberg strain W 775 during composting of biowastes and garden wastes.

AIMS: Determination of the minimum requirements (time-temperature relationship and moisture content) that are needed for a sufficient eradication of an indicator organism. METHODS AND RESULTS: To determine the hygienic safety of composting processes, the indicator organism Salmonella enterica ssp. enterica serotype Senftenberg strain W 775 (further abbreviated as W 775) was artificially inoculated on a meat carrier and monitored subsequently. Different types of composting processes, e.g. composting in enclosed facilities, in open-air and in-vessel composting, were investigated. The waste feedstocks used in this work were either biowastes (i.e. vegetable, fruit and garden wastes; also called source-separated household wastes) or pure garden wastes. Beside these large-scale trials, we also conducted some lab experiments in order to determine the impact of temperature, moisture content and the presence of an indigenous microflora on the eradication of W 775. We found the temperature to be the most important parameter to eradicate W 775 from compost. When the temperature of the compost heap is 60 degrees C and the moisture content varies between 60-65%, W 775 (10(8) CFU g(-1)) will be inactivated within 10 h of composting. The moisture content is, beside temperature, a second parameter that influences the survival of W 775. When the water content of the composting materials or meat carriers is reduced, a higher survival rate of W 775 was observed (survival rate increases 0.5 log(10) unit when there is a reduction of 5% in moisture content). In addition, other parameters (such as microbial antagonism, toxic compounds, etc.) have an influence on the survival of W 775 as well. CONCLUSIONS: Our study demonstrates that all types of composting processes tested in this work were sufficient to eradicate W 775 providing that they are well managed in terms of temperature and moisture content. SIGNIFICANCE AND IMPACT OF THE STUDY: To give a better view on the parameters of importance for the eradication of W 775 during composting.

Validation of predictive growth models describing superatmospheric oxygen effects on Pseudomonas fluorescens and Listeria innocua on fresh-cut lettuce.

Two microbial growth models predicting the growth of Pseudomonas fluorescens and Listeria innocua at superatmospheric oxygen and carbon dioxide concentrations at 7 degrees C were validated on fresh-cut butterhead lettuce. Cut lettuce was inoculated with the same strain of L. innocua as the in vitro experiments. The P. fluorescens strain was tagged with a gene encoding green fluorescent protein (GFP) in order to distinguish the inoculated strain from contaminating Pseudomonaceae. Also growth of aerobic mesophilic and lactic acid bacteria was monitored during the experiments. The suggested P. fluorescens model was appropriate to predict growth on cut lettuce. L. innocua on the other hand, grew considerably slower under in vivo circumstances than predicted. CO(2) had a growth promoting effect on L. innocua growing on cut lettuce, whereas in vitro an inhibiting effect was observed. Validation parameters are calculated and hypotheses to explain the discrepancy between predicted and observed growth of L. innocua are provided.

Advancing the boundaries of high-connectivity network simulation with distributed computing.

The availability of efficient and reliable simulation tools is one of the mission-critical technologies in the fast-moving field of computational neuroscience. Research indicates that higher brain functions emerge from large and complex cortical networks and their interactions. The large number of elements (neurons) combined with the high connectivity (synapses) of the biological network and the specific type of interactions impose severe constraints on the explorable system size that previously have been hard to overcome. Here we present a collection of new techniques combined to a coherent simulation tool removing the fundamental obstacle in the computational study of biological neural networks: the enormous number of synaptic contacts per neuron. Distributing an individual simulation over multiple computers enables the investigation of networks orders of magnitude larger than previously possible. The software scales excellently on a wide range of tested hardware, so it can be used in an interactive and iterative fashion for the development of ideas, and results can be produced quickly even for very large networks. In contrast to earlier approaches, a wide class of neuron models and synaptic dynamics can be represented.