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- Einspielen <Werkstoff> (7)
- FEM (4)
- Finite-Elemente-Methode (4)
- LAPS (4)
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Recently, we introduced and mathematically analysed a new method for grid deformation (Grajewski et al., 2009) [15] we call basic deformation method (BDM) here. It generalises the method proposed by Liao et al. (Bochev et al., 1996; Cai et al., 2004; Liao and Anderson, 1992) [4], [6], [20]. In this article, we employ the BDM as core of a new multilevel deformation method (MDM) which leads to vast improvements regarding robustness, accuracy and speed. We achieve this by splitting up the deformation process in a sequence of easier subproblems and by exploiting grid hierarchy. Being of optimal asymptotic complexity, we experience speed-ups up to a factor of 15 in our test cases compared to the BDM. This gives our MDM the potential for tackling large grids and time-dependent problems, where possibly the grid must be dynamically deformed once per time step according to the user's needs. Moreover, we elaborate on implementational aspects, in particular efficient grid searching, which is a key ingredient of the BDM.
Superparamagnetic iron oxide nanoparticles (SPION) are extensively used for magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), as well as for magnetic fluid hyperthermia (MFH). We here describe a sequential centrifugation protocol to obtain SPION with well-defined sizes from a polydisperse SPION starting formulation, synthesized using the routinely employed co-precipitation technique. Transmission electron microscopy, dynamic light scattering and nanoparticle tracking analyses show that the SPION fractions obtained upon size-isolation are well-defined and almost monodisperse. MRI, MPI and MFH analyses demonstrate improved imaging and hyperthermia performance for size-isolated SPION as compared to the polydisperse starting mixture, as well as to commercial and clinically used iron oxide nanoparticle formulations, such as Resovist® and Sinerem®. The size-isolation protocol presented here may help to identify SPION with optimal properties for diagnostic, therapeutic and theranostic applications.
Three-dimensional (3D) full-field measurements provide a comprehensive and accurate validation of finite element (FE) models. For the validation, the result of the model and measurements are compared based on two respective point-sets and this requires the point-sets to be registered in one coordinate system. Point-set registration is a non-convex optimization problem that has widely been solved by the ordinary iterative closest point algorithm. However, this approach necessitates a good initialization without which it easily returns a local optimum, i.e. an erroneous registration. The globally optimal iterative closest point (Go-ICP) algorithm has overcome this drawback and forms the basis for the presented open-source tool that can be used for the validation of FE models using 3D full-field measurements. The capability of the tool is demonstrated using an application example from the field of biomechanics. Methodological problems that arise in real-world data and the respective implemented solution approaches are discussed.
Magnetic nanoparticles (MNPs) are used as therapeutic and diagnostic agents for local delivery of heat and image contrast enhancement in diseased tissue. Besides magnetization, the most important parameter that determines their performance for these applications is their magnetic relaxation, which can be affected when MNPs immobilize and agglomerate inside tissues. In this letter, we investigate different MNP agglomeration states for their magnetic relaxation properties under excitation in alternating fields and relate this to their heating efficiency and imaging properties. With focus on magnetic fluid hyperthermia, two different trends in MNP heating efficiency are measured: an increase by up to 23% for agglomerated MNP in suspension and a decrease by up to 28% for mixed states of agglomerated and immobilized MNP, which indicates that immobilization is the dominant effect. The same comparatively moderate effects are obtained for the signal amplitude in magnetic particle spectroscopy.
Many efforts are made worldwide to establish magnetic fluid hyperthermia (MFH) as a treatment for organ-confined tumors. However, translation to clinical application hardly succeeds as it still lacks of understanding the mechanisms determining MFH cytotoxic effects. Here, we investigate the intracellular MFH efficacy with respect to different parameters and assess the intracellular cytotoxic effects in detail. For this, MiaPaCa-2 human pancreatic tumor cells and L929 murine fibroblasts were loaded with iron-oxide magnetic nanoparticles (MNP) and exposed to MFH for either 30 min or 90 min. The resulting cytotoxic effects were assessed via clonogenic assay. Our results demonstrate that cell damage depends not only on the obvious parameters bulk temperature and duration of treatment, but most importantly on cell type and thermal energy deposited per cell during MFH treatment. Tumor cell death of 95% was achieved by depositing an intracellular total thermal energy with about 50% margin to damage of healthy cells. This is attributed to combined intracellular nanoheating and extracellular bulk heating. Tumor cell damage of up to 86% was observed for MFH treatment without perceptible bulk temperature rise. Effective heating decreased by up to 65% after MNP were internalized inside cells.
Heating efficiency of magnetic nanoparticles decreases with gradual immobilization in hydrogels
(2019)
Enzyme-catalyzed reactions have been designed to mimic various Boolean logic gates in the general framework of unconventional biomolecular computing. While some of the logic gates, particularly OR, AND, are easy to realize with biocatalytic reactions and have been reported in numerous publications, some other, like NXOR, are very challenging and have not been realized yet with enzyme reactions. The paper reports on a novel approach to mimicking the NXOR logic gate using the bell-shaped enzyme activity dependent on pH values. Shifting pH from the optimum value to the acidic or basic values by using acid or base inputs (meaning 1,0 and 0,1 inputs) inhibits the enzyme reaction, while keeping the optimum pH (assuming 0,0 and 1,1 input combinations) preserves a high enzyme activity. The challenging part of the present approach is the selection of an enzyme with a well-demonstrated bell-shape activity dependence on the pH value. While many enzymes can satisfy this condition, we selected pyrroloquinoline quinone (PQQ)-dependent glucose dehydrogenase as this enzyme has the optimum pH center-located on the pH scale allowing the enzyme activity change by the acidic and basic pH shift from the optimum value corresponding to the highest activity. The present NXOR gate is added to the biomolecular “toolbox” as a new example of Boolean logic gates based on enzyme reactions.
Monitoring the cellular metabolism of bacteria in (bio)fermentation processes is crucial to control and steer them, and to prevent undesired disturbances linked to metabolically inactive microorganisms. In this context, cell-based biosensors can play an important role to improve the quality and increase the yield of such processes. This work describes the simultaneous analysis of the metabolic behavior of three different types of bacteria by means of a differential light-addressable potentiometric sensor (LAPS) set-up. The study includes Lactobacillus brevis, Corynebacterium glutamicum, and Escherichia coli, which are often applied in fermentation processes in bioreactors. Differential measurements were carried out to compensate undesirable influences such as sensor signal drift, and pH value variation during the measurements. Furthermore, calibration curves of the cellular metabolism were established as a function of the glucose concentration or cell number variation with all three model microorganisms. In this context, simultaneous (bio)sensing with the multi-organism LAPS-based set-up can open new possibilities for a cost-effective, rapid detection of the extracellular acidification of bacteria on a single sensor chip. It can be applied to evaluate the metabolic response of bacteria populations in a (bio)fermentation process, for instance, in the biogas fermentation process.
L.setulosus is offered for creation of biopreparation «Setulin», possesing he- mostatic action, the basic reactant of biopreparation is diterpen – lagochirzin. Results under the maintenance and dynamics of diterpen lagochirzin accumula- tion in various parts of L.setulosus are presented: in roots, stalks, leaves, flowers and calyx lobes during the growing season, and also results on conditions of cultivation L.setulosus in the conditions of a typical sierozem are resulted. From the obtained data is visible, that the given species of a plant is endemic. It is established, that dynamics of accumulation of lagochirzin in phytomass accrues from the beginning to the middle of the growing season. The chemical analysis of L.setulosus on a localization of lagochirzin in various organs of a plant, has shown, that the greatest quantity of lagochirzin collects in calyx lobes of the plants. Also it is established, that L.setulosus can be cultivated in the conditions of the typical sierozem, a mineral food is necessary for the given species of plants of Lagochilus genus, except nitric fertilizers. Comparative studying of wild-growing and cultural forms of L.setulosus has shown, that in the cultivated phytomass of plants the maintenance of lagochirzin on 17-20 % higher than in the wild-growing species.
The scope of this study is the measurement of endotoxin adsorption rate for carbonized rice husk. It showed good adsorption properties for LPS. During the batch experiments, several techniques were used and optimized for improving the material’s adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics.
On the model of musculocutaneous wound in rats, the effect of applicative sorption by carbonized rise shell (CRS) on the healing of festering wound was studied. It has been shown, that cytological changes end with rapid scar formation. The use of CRS at the period of severe purulent wound contributes to its favorable course, prevents the development of complications of the animals from sepsis.
At the present time, one of the most serious environmental problems of Central Asia and South Kazakhstan is the ongoing large-scale deterioration of principal urban tree populations. Several major centers of massive spread of invasive plant pests have been found in urban dendroflora of this region. The degree of damage of seven most wide-spread aboriginal tree species was found to range from 21.4±1.1 to 85.4±1.8%. In particular, the integrity of the native communities of sycamore (Platanus spp.), willow (Salix spp.), poplar (Populus spp.) and elm (Ulmus spp.) is highly endangered. Our taxonomic analysis of the most dangerous tree pests of the region has revealed them as neobiontic xylophilous insects such as Cossus cossus L. (Order: Lepidoptera L.) Monochamus urussovi Fisch., Monochamus sutor L., Acanthocinus aedelis L. and Ñetonia aureate L. (Order: Coleoptera L.). We relate the origin of this threatening trend with the import of industrial wood in the mid 90s of the last century that was associated with high degree of the constructional work in the region. Because of the absence of efficient natural predators of the pest species, the application of microbiological methods of the pest control and limitation is suggested.
Suspension depletion approach for exemption of infected Solanum jasminoides cells from pospiviroids
(2018)
Despite numerous studies, viroid elimination from infected plants remains a very challenging task. This study introduces for the first time a novel ‘suspension depletion’ approach for exemption of Solanum jasminoides plants from viroids. The proposed method implies initial establishment of suspension cultures of the infected plant cells. The suspended cells were then physically treated (mild thermotherapy, 33 °C), which presumably delayed the replication of the viroid. The viroid concentration in the treated biomass was monitored weekly using pospiviroid-specific PCR. After 10–12 weeks of continuous treatment, a sufficient decrease in viroid concentration was observed such that the infection became undetectable by PCR. The treated single cells then gave rise to microcolonies on a solid culture medium and the obtained viroid-negative clones were further promoted to regenerate into viroid-free plants. Three years of accumulated experimental data suggests feasibility, broad applicability, and good efficacy of the proposed approach.
A new in vitro tool to investigate cardiac contractility under physiological mechanical conditions
(2019)
Hydrogen peroxide (H2O2) is a typical surface sterilization agent for packaging materials used in the pharmaceutical, food and beverage industries. We use the finite-elements method to analyze the conceptual design of an in-line thermal evaporation unit to produce a heated gas mixture of air and evaporated H2O2 solution. For the numerical model, the required phase-transition variables of pure H2O2 solution and of the aerosol mixture are acquired from vapor-liquid equilibrium (VLE) diagrams derived from vapor-pressure formulations. This work combines homogeneous single-phase turbulent flow with heat-transfer physics to describe the operation of the evaporation unit. We introduce the apparent heat-capacity concept to approximate the non-isothermal phase-transition process of the H2O2-containing aerosol. Empirical and analytical functions are defined to represent the temperature- and pressure-dependent material properties of the aqueous H2O2 solution, the aerosol and the gas mixture. To validate the numerical model, the simulation results are compared to experimental data on the heating power required to produce the gas mixture. This shows good agreement with the deviations below 10%. Experimental observations on the formation of deposits due to the evaporation of stabilized H2O2 solution fits the prediction made from simulation results.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based (bio-) chemical sensor, in which a desired sensing area on the sensor surface can be defined by illumination. Light addressability can be used to visualize the concentration and spatial distribution of the target molecules, e.g., H+ ions. This unique feature has great potential for the label-free imaging of the metabolic activity of living organisms. The cultivation of those organisms needs specially tailored surface properties of the sensor. O2 plasma treatment is an attractive and promising tool for rapid surface engineering. However, the potential impacts of the technique are carefully investigated for the sensors that suffer from plasma-induced damage. Herein, a LAPS with a Ta2O5 pH-sensitive surface is successfully patterned by plasma treatment, and its effects are investigated by contact angle and scanning LAPS measurements. The plasma duration of 30 s (30 W) is found to be the threshold value, where excessive wettability begins. Furthermore, this treatment approach causes moderate plasma-induced damage, which can be reduced by thermal annealing (10 min at 300 °C). These findings provide a useful guideline to support future studies, where the LAPS surface is desired to be more hydrophilic by O2 plasma treatment.
Experience has shown that a priori created static resource allocation plans are vulnerable to runtime deviations and hence often become uneconomic or highly exceed a predefined soft deadline. The assumption of constant task execution times during allocation planning is even more unlikely in a cloud environment where virtualized resources vary in performance. Revising the initially created resource allocation plan at runtime allows the scheduler to react on deviations between planning and execution. Such an adaptive rescheduling of a many-task application workflow is only feasible, when the planning time can be handled efficiently at runtime. In this paper, we present the static low-complexity resource allocation planning algorithm (LCP) applicable to efficiently schedule many-task scientific application workflows on cloud resources of different capabilities. The benefits of the presented algorithm are benchmarked against alternative approaches. The benchmark results show that LCP is not only able to compete against higher complexity algorithms in terms of planned costs and planned makespan but also outperforms them significantly by magnitudes of 2 to 160 in terms of required planning time. Hence, LCP is superior in terms of practical usability where low planning time is essential such as in our targeted online rescheduling scenario.
Production and Characterization of Porous Fibroin Scaffolds for Regenerative Medical Application
(2019)
Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement
(2019)
We propose the so-called chance constrained programming model of stochastic programming theory to analyze limit and shakedown loads of structures under random strength with a lognormal distribution. A dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit and the shakedown limit. The edge-based smoothed finite element method (ES-FEM) is used with three-node linear triangular elements.
Socio-technical scenarios for energy-intensive industries: the future of steel production in Germany
(2019)
BACKGROUND: Muscle stretch reflexes are widely considered to beneficially influence joint stability and power generation in the lower limbs. While in the upper limbs and especially in the muscles surrounding the shoulder joint such evidence is lacking. OBJECTIVE: To quantify the electromyographical response in the muscles crossing the shoulder of specifically trained overhead athletes to an anterior perturbation force. METHODS: Twenty healthy male participants performed six sets of different external shoulder rotation stretches on an isokinetic dynamometer over a range of amplitudes and muscle pre-activation moment levels. All stretches were applied with a dynamometer acceleration of 10,000∘/s2 and a velocity of 150∘/s. Electromyographical response was measured via sEMG. RESULTS: Consistent reflexes were not observed in all experimental conditions. The reflex latencies revealed a significant muscle main effect (F (2,228) = 99.31, p< 0.001; η2= 0.466; f= 0.934) and a pre-activation main effect (F (1,228) = 142.21, p< 0.001; η2= 0.384; f= 1.418). The stretch reflex amplitude yielded a significant pre-activation main effect (F (1,222) = 470.373, p< 0.001; η2= 0.679; f= 1.454). CONCLUSION: Short latency muscle reflexes showed a tendency to an anterior to posterior muscle recruitment whereby the main internal rotator muscles of the shoulder revealed the most consistent results.
After a liver tumor intervention the medical doctor has to compare both pre and postoperative CT acquisitions to ensure that all carcinogenic cells are destroyed. A correct assessment of the intervention is of vital importance, since it will reduce the probability of tumor recurrence. Some methods have been proposed to support the medical doctors during the assessment process, however, all of them focus on secondary tumors. In this paper a tool is presented that enables the outcome validation for both primary and secondary tumors. Therefore, a multiphase registration (preoperative arterial and portal phases) followed by a registration between the pre and postoperative CT images is carried out. The first registration is in charge of the primary tumors that are only visible in the arterial phase. The secondary tumors will be incorporated in the second registration step. Finally, the part of the tumor that was not covered by the necrosis is quantified and visualized. The method has been tested in 9 patients, with an average registration error of 1.41 mm.
BACKGROUND
Immunosuppression is often considered as an indication for antibiotic prophylaxis to prevent surgical site infections (SSI) while performing skin surgery. However, the data on the risk of developing SSI after dermatologic surgery in immunosuppressed patients are limited.
PATIENTS AND METHODS
All patients of the Department of Dermatology and Allergology at the University Hospital of RWTH Aachen in Aachen, Germany, who underwent hospitalization for a dermatologic surgery between June 2016 and January 2017 (6 months), were followed up after surgery until completion of the wound healing process. The follow-up addressed the occurrence of SSI and the need for systemic antibiotics after the operative procedure. Immunocompromised patients were compared with immunocompetent patients. The investigation was conducted as a retrospective analysis of patient records.
RESULTS
The authors performed 284 dermatologic surgeries in 177 patients. Nineteen percent (54/284) of the skin surgery was performed on immunocompromised patients. The most common indications for surgical treatment were nonmelanoma skin cancer and malignant melanomas. Surgical site infections occurred in 6.7% (19/284) of the cases. In 95% (18/19), systemic antibiotic treatment was needed. Twenty-one percent of all SSI (4/19) were seen in immunosuppressed patients.
CONCLUSION
According to the authors' data, immunosuppression does not represent a significant risk factor for SSI after dermatologic surgery. However, larger prospective studies are needed to make specific recommendations on the use of antibiotic prophylaxis while performing skin surgery in these patients.
The available data on complications after dermatologic surgery have improved over the past years. Particularly, additional risk factors have been identified for surgical site infections (SSI). Purulent surgical sites, older age, involvement of head, neck, and acral regions, and also the involvement of less experienced surgeons have been reported to increase the risk of the SSI after dermatologic surgeries.1 In general, the incidence of SSI after skin surgery is considered to be low.1,2 However, antibiotics in dermatologic surgeries, especially in the perioperative setting, seem to be overused,3,4 particularly regarding developing antibiotic resistances and side effects.
Immunosuppression has been recommended to be taken into consideration as an additional indication for antibiotic prophylaxis to prevent SSI after skin surgery in special cases.5,6 However, these recommendations do not specify the exact dermatologic surgeries, and were not specifically developed for dermatologic surgery patients and treatments, but adopted from other surgical fields.6 According to the survey conducted on American College of Mohs Surgery members in 2012, 13% to 29% of the surgeons administered antibiotic prophylaxis to immunocompromised patients to prevent SSI while performing dermatologic surgery on noninfected skin,3 although this was not recommended by Journal of the American Academy of Dermatology Advisory Statement. Indeed, the data on the risk of developing SSI after dermatologic surgery in immunosuppressed patients are limited. However, it is possible that due to the insufficient evidence on the risk of SSI occurrence in this patient group, dermatologic surgeons tend to overuse perioperative antibiotic prophylaxis.
To make specific recommendations on the use of antibiotic prophylaxis in immunosuppressed patients in the field of skin surgery, more information about the incidence of SSI after dermatologic surgery in these patients is needed. The aim of this study was to fill this data gap by investigating whether there is an increased risk of SSI after skin surgery in immunocompromised patients compared with immunocompetent patients.
Postural and metabolic benefits of using a forearm support walker in older adults with impairments
(2019)
Background
Impairment of neurovascular coupling (NVC) was recently reported in the context of subarachnoid hemorrhage and may correlate with disease severity and outcome. However, previous techniques to evaluate NVC required invasive procedures. Retinal vessels may represent an alternative option for non-invasive assessment of NVC.
Methods
A prototype of an adapted retinal vessel analyzer was used to assess retinal vessel diameter in mice. Dynamic vessel analysis (DVA) included an application of monochromatic flicker light impulses in predefined frequencies for evaluating NVC. All retinae were harvested after DVA and electroretinograms were performed.
Results
A total of 104 retinal scans were conducted in 21 male mice (90 scans). Quantitative arterial recordings were feasible only in a minority of animals, showing an emphasized reaction to flicker light impulses (8 mice; 14 scans). A characteristic venous response to flicker light, however, could observed in the majority of animals. Repeated measurements resulted in a significant decrease of baseline venous diameter (7 mice; 7 scans, p < 0.05). Ex-vivo electroretinograms, performed after in-vivo DVA, demonstrated a significant reduction of transretinal signaling in animals with repeated DVA (n = 6, p < 0.001).
Conclusions
To the best of our knowledge, this is the first non-invasive study assessing murine retinal vessel response to flicker light with characteristic changes in NVC. The imaging system can be used for basic research and enables the investigation of retinal vessel dimension and function in control mice and genetically modified animals.
Algal polysaccharides (extracellular polysaccharides) and carbon nanotubes (CNTs) were adsorbed on dioctadecyldimethylammonium bromide Langmuir monolayers to serve as a matrix for the incorporation of urease. The physicochemical properties of the supramolecular system as a monolayer at the air–water interface were investigated by surface pressure–area isotherms, surface potential–area isotherms, interfacial shear rheology, vibrational spectroscopy, and Brewster angle microscopy. The floating monolayers were transferred to hydrophilic solid supports, quartz, mica, or capacitive electrolyte–insulator–semiconductor (EIS) devices, through the Langmuir–Blodgett (LB) technique, forming mixed films, which were investigated by quartz crystal microbalance, fluorescence spectroscopy, and field emission gun scanning electron microscopy. The enzyme activity was studied with UV–vis spectroscopy, and the feasibility of the thin film as a urea sensor was essayed in an EIS sensor device. The presence of CNT in the enzyme–lipid LB film not only tuned the catalytic activity of urease but also helped to conserve its enzyme activity. Viability as a urease sensor was demonstrated with capacitance–voltage and constant capacitance measurements, exhibiting regular and distinctive output signals over all concentrations used in this work. These results are related to the synergism between the compounds on the active layer, leading to a surface morphology that allowed fast analyte diffusion owing to an adequate molecular accommodation, which also preserved the urease activity. This work demonstrates the feasibility of employing LB films composed of lipids, CNT, algal polysaccharides, and enzymes as EIS devices for biosensing applications.
Monitoring of organic acids (OA) and volatile fatty acids (VFA) is crucial for the control of anaerobic digestion. In case of unstable process conditions, an accumulation of these intermediates occurs. In the present work, two different enzyme-based biosensor arrays are combined and presented for facile electrochemical determination of several process-relevant analytes. Each biosensor utilizes a platinum sensor chip (14 × 14 mm²) with five individual working electrodes. The OA biosensor enables simultaneous measurement of ethanol, formate, d- and l-lactate, based on a bi-enzymatic detection principle. The second VFA biosensor provides an amperometric platform for quantification of acetate and propionate, mediated by oxidation of hydrogen peroxide. The cross-sensitivity of both biosensors toward potential interferents, typically present in fermentation samples, was investigated. The potential for practical application in complex media was successfully demonstrated in spiked sludge samples collected from three different biogas plants. Thereby, the results obtained by both of the biosensors were in good agreement to the applied reference measurements by photometry and gas chromatography, respectively. The proposed hybrid biosensor system was also used for long-term monitoring of a lab-scale biogas reactor (0.01 m³) for a period of 2 months. In combination with typically monitored parameters, such as gas quality, pH and FOS/TAC (volatile organic acids/total anorganic carbonate), the amperometric measurements of OA and VFA concentration could enhance the understanding of ongoing fermentation processes.
False spectra formation in the differential two-channel scheme of the laser Doppler flowmeter
(2018)
Noise in the differential two-channel scheme of a classic laser Doppler flowmetry (LDF) instrument was studied. Formation of false spectral components in the output signal due to beating of electrical signals in the differential amplifier was found out. The improved block-diagram of the flowmeter was developed allowing to reduce the noise.
The chemical imaging sensor is a semiconductor-based chemical sensor capable of visualizing pH and ion distributions. The spatial resolution depends on the lateral diffusion of photocarriers generated by illumination of the semiconductor substrate. In this study, two types of optical setups, one based on a bundle of optical fibers and the other based on a binocular tube head, were developed to project a hybrid illumination of a modulated light beam and a ring-shaped constant illumination onto the sensor plate. An improved spatial resolution was realized by the ring-shaped constant illumination, which suppressed lateral diffusion of photocarriers by enhanced recombination due to the increased carrier concentration.
Detecting synchronization clusters in multivariate time series via coarse-graining of Markov chains
(2007)
Rationale: Previous studies [Topolnik et al., Cereb Cortex 2003; 13: 883; Schindler et al., Brain 2007; 130: 65] indicate that the termination of focal onset seizures may be causally related to an increase of global neuronal correlation during the second half of the seizures. This increase was observed to occur earlier in complex partial seizures than in secondarily generalized seizures. We here address the question whether such an increase of neuronal correlation prior to seizure end is indeed a global phenomenon, involving both hemispheres or whether there are side-specific differences. Methods: We analyzed 20 focal onset seizures (10 complex partial, 10 secondarily generalized seizures) recorded in 13 patients who underwent presurgical evaluation of focal epilepsies of different origin. EEG was recorded intracranially from bilaterally implanted subdural strip and intrahippocampal depth electrodes. Utilizing a moving window approach, we investigated the evolution of the maximum cross correlation for all channel combinations during seizures. For each moving window the mean value of the maximum cross correlation (MCC) between all electrode contacts was computed separately for each hemisphere. After normalization of seizure durations, MCC values of the ipsi- and contralateral hemisphere for all seizures were determined. Results: We observed that the MCC of the contralateral hemisphere in complex partial seizures increased during the first half of the seizure, whereas, for the same time interval, the MCC of the ipsilateral hemisphere even declined below the level of the pre-seizure period. In contrast, no significant differences between both hemispheres could be observed for secondarily generalized seizures where both hemispheres showed a simultaneous increase of MCC during the second half of the seizures. The level of MCC for the contralateral hemisphere was higher for complex partial seizures than for secondarily generalized seizures during the first half of the seizure. Conclusions: Our findings indicate that there are indeed lateralized differences in the evolution of global neuronal correlation during complex partial and secondarily generalized seizures. The observed contralateral increase of neuronal correlation during complex partial seizures might indicate an emerging self-organizing mechanism for preventing the spread of seizure activity.
Objective
To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval.
Methods
We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics.
Results
Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings.
Conclusions
Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks.
Significance
An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks.
We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.
We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.
Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.
Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.
Data-driven prediction and prevention of extreme events in a spatially extended excitable system
(2015)
The stimulation and dominance of potentially harmful phytoplankton taxa at a given locale and time are determined by local environmental conditions as well as by transport to or from neighboring regions. The present study investigated the occurrence of common harmful algal bloom (HAB) taxa within the Southern California Bight, using cross-correlation functions to determine potential dependencies between HAB taxa and environmental factors, and potential links to algal transport via local hydrography and currents. A simulation study, in which Lagrangian particles were released, was used to assess travel times due to advection by prevailing ocean currents in the bight. Our results indicate that transport of some taxa may be an important mechanism for the expansion of their distributions into other regions, which was supported by mean travel times derived from our simulation study and other literature on ocean currents in the Southern California Bight. In other cases, however, phytoplankton dynamics were rather linked to local environmental conditions, including coastal upwelling events. Overall, our study shows that complex current patterns in the Southern California Bight may contribute significantly to the formation and expansion of HABs in addition to local environmental factors determining the spatiotemporal dynamics of phytoplankton blooms.
We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.
Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle.
Prosthetic textile implants of different shapes, sizes and polymers are used to correct the apical prolapse after hysterectomy (removal of the uterus). The selection of the implant before or during minimally invasive surgery depends on the patient’s anatomical defect, intended function after reconstruction and most importantly the surgeon’s preference. Weakness or damage of the supporting tissues during childbirth, menopause or previous pelvic surgeries may put females in higher risk of prolapse. Numerical simulations of reconstructed pelvic floor with weakened tissues and organ supported by textile product models: DynaMesh®-PRS soft, DynaMesh®-PRP soft and DynaMesh®-CESA from FEG Textiletechnik mbH, Germany are compared.
The porosity of surgical meshes makes them flexible for large elastic deformation and establishes the healing conditions of good tissue in growth. The biomechanic modeling of orthotropic and compressible materials requires new materials models and simulstaneoaus fit of deformation in the load direction as well as trannsversely to to load. This nonlinear modeling can be achieved by an optical deformation measurement. At the same time the full field deformation measurement allows the dermination of the change of porosity with deformation. Also the socalled effective porosity, which has been defined to asses the tisssue interatcion with the mesh implants, can be determined from the global deformation of the surgical meshes.
In this work, a cell-based biosensor to evaluate the sterilization efficacy of hydrogen peroxide vapor sterilization processes is characterized. The transducer of the biosensor is based on interdigitated gold electrodes fabricated on an inert glass substrate. Impedance spectroscopy is applied to evaluate the sensor behavior and the alteration of test microorganisms due to the sterilization process. These alterations are related to changes in relative permittivity and electrical conductivity of the bacterial spores. Sensor measurements are conducted with and without bacterial spores (Bacillus atrophaeus), as well as after an industrial sterilization protocol. Equivalent two-dimensional numerical models based on finite element method of the periodic finger structures of the interdigitated gold electrodes are designed and validated using COMSOL® Multiphysics software by the application of known dielectric properties. The validated models are used to compute the electrical properties at different sensor states (blank, loaded with spores, and after sterilization). As a final result, we will derive and tabulate the frequency-dependent electrical parameters of the spore layer using a novel model that combines experimental data with numerical optimization techniques.
Field-effect-based electrolyte-insulator-semiconductor (EIS) sensors were modified with a bilayer of positively charged weak polyelectrolyte (poly(allylamine hydrochloride) (PAH)) and probe single-stranded DNA (ssDNA) and are used for the detection of complementary single-stranded target DNA (cDNA) in different test solutions. The sensing mechanism is based on the detection of the intrinsic molecular charge of target cDNA molecules after the hybridization event between cDNA and immobilized probe ssDNA. The test solutions contain synthetic cDNA oligonucleotides (with a sequence of tuberculosis mycobacteria genome) or PCR-amplified DNA (which origins from a template DNA strand that has been extracted from Mycobacterium avium paratuberculosis-spiked human sputum samples), respectively. Sensor responses up to 41 mV have been measured for the test solutions with DNA, while only small signals of ∼5 mV were detected for solutions without DNA. The lower detection limit of the EIS sensors was ∼0.3 nM, and the sensitivity was ∼7.2 mV/decade. Fluorescence experiments using SybrGreen I fluorescence dye support the electrochemical results.
In lab-on-chip systems, electrodes are important for the manipulation (e.g., cell stimulation, electrolysis) within such systems. An alternative to commonly used electrode structures can be a light-addressable electrode. Here, due to the photoelectric effect, the conducting area can be adjusted by modification of the illumination area which enables a flexible control of the electrode. In this work, titanium dioxide based light-addressable electrodes are fabricated by a sol–gel technique and a spin-coating process, to deposit a thin film on a fluorine-doped tin oxide glass. To characterize the fabricated electrodes, the thickness, and morphological structure are measured by a profilometer and a scanning electron microscope. For the electrochemical behavior, the dark current and the photocurrent are determined for various film thicknesses. For the spatial resolution behavior, the dependency of the photocurrent while changing the area of the illuminated area is studied. Furthermore, the addressing of single fluid compartments in a three-chamber system, which is added to the electrode, is demonstrated.
A chip-based amperometric biosensor referring on using the bioelectrocatalytical amplification principle for the detection of low adrenaline concentrations is presented. The adrenaline biosensor has been prepared by modification of a platinum thin-film electrode with an enzyme membrane containing the pyrroloquinoline quinone-dependent glucose dehydrogenase and glutaraldehyde. Measuring conditions such as temperature, pH value, and glucose concentration have been optimized to achieve a high sensitivity and a low detection limit of about 1 nM adrenaline measured in phosphate buffer at neutral pH value. The response of the biosensor to different catecholamines has also been proven. Long-term stability of the adrenaline biosensor has been studied over 10 days. In addition, the biosensor has been successfully applied for adrenaline detection in human blood plasma for future biomedical applications. Furthermore, preliminary experiments have been carried to detect the adrenaline-concentration difference measured in peripheral blood and adrenal venous blood, representing the adrenal vein sampling procedure of a physician.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based potentiometric device, which detects concentration changes of an analyte solution on the sensor surface in a spatially resolved way. It uses a light source to generate electron–hole pairs inside the semiconductor, which are separated in the depletion region due to an applied bias voltage across the sensor structure and hence, a surface-potential-dependent photocurrent can be read out. However, depending on the beam angle of the light source, scattering effects can occur, which influence the recorded signal in LAPS-based differential measurements. To solve this problem, a novel illumination unit based on a field programmable gate array (FPGA) consisting of 16 small-sized tunable infrared laser-diode modules (LDMs) is developed. Due to the improved focus of the LDMs with a beam angle of only 2 mrad, undesirable scattering effects are minimized. Escherichia coli (E. coli) K12 bacteria are used as a test microorganism to study the extracellular acidification on the sensor surface. Furthermore, a salt bridge chamber is built up and integrated with the LAPS system enabling multi-chamber differential measurements with a single Ag/AgCl reference electrode.