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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.
For pelvic floor disorders that cannot be treated with non-surgical procedures, minimally invasive surgery has become a more frequent and safer repair procedure. More than 20 million prosthetic meshes are implanted each year worldwide. The simple selection of a single synthetic mesh construction for any level and type of pelvic floor dysfunctions without adopting the design to specific requirements increase the risks for mesh related complications. Adverse events are closely related to chronic foreign body reaction, with enhanced formation of scar tissue around the surgical meshes, manifested as pain, mesh erosion in adjacent structures (with organ tissue cut), mesh shrinkage, mesh rejection and eventually recurrence. Such events, especially scar formation depend on effective porosity of the mesh, which decreases discontinuously at a critical stretch when pore areas decrease making the surgical reconstruction ineffective that further augments the re-operation costs. The extent of fibrotic reaction is increased with higher amount of foreign body material, larger surface, small pore size or with inadequate textile elasticity. Standardized studies of different meshes are essential to evaluate influencing factors for the failure and success of the reconstruction. Measurements of elasticity and tensile strength have to consider the mesh anisotropy as result of the textile structure. An appropriate mesh then should show some integration with limited scar reaction and preserved pores that are filled with local fat tissue. This chapter reviews various tissue reactions to different monofilament mesh implants that are used for incontinence and hernia repairs and study their mechanical behavior. This helps to predict the functional and biological outcomes after tissue reinforcement with meshes and permits further optimization of the meshes for the specific indications to improve the success of the surgical treatment.
An amperometric bi-enzyme biosensor based on substrate recycling principle for the amplification of the sensor signal has been developed for the detection of adrenaline in blood. Adrenaline can be used as biomarker verifying successful adrenal venous sampling procedure. The adrenaline biosensor has been realized via modification of a galvanic oxygen sensor with a bi-enzyme membrane combining a genetically modified laccase and a pyrroloquinoline quinone-dependent glucose dehydrogenase. The measurement conditions such as pH value and temperature were optimized to enhance the sensor performance. A high sensitivity and a low detection limit of about 0.5–1 nM adrenaline have been achieved in phosphate buffer at pH 7.4, relevant for measurements in blood samples. The sensitivity of the biosensor to other catecholamines such as noradrenaline, dopamine and dobutamine has been studied. Finally, the sensor has been successfully applied for the detection of adrenaline in human blood plasma.
Human-induced pluripotent stem cell-derived cardiomyocytes (hiPS-CM) today are widely used for the investigation of normal electromechanical cardiac function, of cardiac medication and of mutations. Computational models are thus established that simulate the behavior of this kind of cells. This section first motivates the modeling of hiPS-CM and then presents and discusses several modeling approaches of microscopic and macroscopic constituents of human-induced pluripotent stem cell-derived and mature human cardiac tissue. The focus is led on the mapping of the computational results one can achieve with these models onto mature human cardiomyocyte models, the latter being the real matter of interest. Model adaptivity is the key feature that is discussed because it opens the way for modeling various biological effects like biological variability, medication, mutation and phenotypical expression. We compare the computational with experimental results with respect to normal cardiac function and with respect to inotropic and chronotropic drug effects. The section closes with a discussion on the status quo of the specificity of computational models and on what challenges have to be solved to reach patient-specificity.
The light-addressable potentiometric sensor (LAPS) and scanning photo-induced impedance microscopy (SPIM) are two closely related methods to visualise the distributions of chemical species and impedance, respectively, at the interface between the sensing surface and the sample solution. They both have the same field-effect structure based on a semiconductor, which allows spatially resolved and label-free measurement of chemical species and impedance in the form of a photocurrent signal generated by a scanning light beam. In this article, the principles and various operation modes of LAPS and SPIM, functionalisation of the sensing surface for measuring various species, LAPS-based chemical imaging and high-resolution sensors based on silicon-on-sapphire substrates are described and discussed, focusing on their technical details and prospective applications.
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.
Reconstructive surgery and tissue replacements like ureters or bladders reconstruction have been recently studied, taking into account growth and remodelling of cells since living cells are capable of growing, adapting, remodelling or degrading and restoring in order to deform and respond to stimuli. Hence, shapes of ureters or bladders and their microstructure change during growth and these changes strongly depend on external stimuli such as training. We present the mechanical stimulation of smooth muscle cells in a tubular fibrin-PVDFA scaffold and the modelling of the growth of tissue by stimuli. To this end, mechanotransduction was performed with a kyphoplasty balloon catheter that was guided through the lumen of the tubular structure. The bursting pressure was examined to compare the stability of the incubated tissue constructs. The results showed the significant changes on tissues with training by increasing the burst pressure as a characteristic mechanical property and the smooth muscle cells were more oriented with uniformly higher density. Besides, the computational growth models also exhibited the accurate tendencies of growth of the cells under different external stimuli. Such models may lead to design standards for the better layered tissue structure in reconstructing of tubular organs characterized as composite materials such as intestines, ureters and arteries.
The presentation of enzymes on viral scaffolds has beneficial effects such as an increased enzyme loading and a prolonged reusability in comparison to conventional immobilization platforms. Here, we used modified tobacco mosaic virus (TMV) nanorods as enzyme carriers in penicillin G detection for the first time. Penicillinase enzymes were conjugated with streptavidin and coupled to TMV rods by use of a bifunctional biotin-linker. Penicillinase-decorated TMV particles were characterized extensively in halochromic dye-based biosensing. Acidometric analyte detection was performed with bromcresol purple as pH indicator and spectrophotometry. The TMV-assisted sensors exhibited increased enzyme loading and strongly improved reusability, and higher analysis rates compared to layouts without viral adapters. They extended the half-life of the sensors from 4 - 6 days to 5 weeks and thus allowed an at least 8-fold longer use of the sensors. Using a commercial budget-priced penicillinase preparation, a detection limit of 100 µM penicillin was obtained. Initial experiments also indicate that the system may be transferred to label-free detection layouts.
Nanotubular tobacco mosaic virus (TMV) particles and RNA-free lower-order coat protein (CP) aggregates have been employed as enzyme carriers in different diagnostic layouts and compared for their influence on biosensor performance. In the following, we describe a label-free electrochemical biosensor for improved glucose detection by use of TMV adapters and the enzyme glucose oxidase (GOD). A specific and efficient immobilization of streptavidin-conjugated GOD ([SA]-GOD) complexes on biotinylated TMV nanotubes or CP aggregates was achieved via bioaffinity binding. Glucose sensors with adsorptively immobilized [SA]-GOD, and with [SA]-GOD cross-linked with glutardialdehyde, respectively, were tested in parallel on the same sensor chip. Comparison of these sensors revealed that TMV adapters enhanced the amperometric glucose detection remarkably, conveying highest sensitivity, an extended linear detection range and fastest response times. These results underline a great potential of an integration of virus/biomolecule hybrids with electronic transducers for applications in biosensorics and biochips. Here, we describe the fabrication and use of amperometric sensor chips combining an array of circular Pt electrodes, their loading with GOD-modified TMV nanotubes (and other GOD immobilization methods), and the subsequent investigations of the sensor performance.
The inverse scattering problem for a conductive boundary condition and transmission eigenvalues
(2018)
In this paper, we consider the inverse scattering problem associated with an inhomogeneous media with a conductive boundary. In particular, we are interested in two problems that arise from this inverse problem: the inverse conductivity problem and the corresponding interior transmission eigenvalue problem. The inverse conductivity problem is to recover the conductive boundary parameter from the measured scattering data. We prove that the measured scatted data uniquely determine the conductivity parameter as well as describe a direct algorithm to recover the conductivity. The interior transmission eigenvalue problem is an eigenvalue problem associated with the inverse scattering of such materials. We investigate the convergence of the eigenvalues as the conductivity parameter tends to zero as well as prove existence and discreteness for the case of an absorbing media. Lastly, several numerical and analytical results support the theory and we show that the inside–outside duality method can be used to reconstruct the interior conductive eigenvalues.
The paper deals with the asymptotic behaviour of estimators, statistical tests and confidence intervals for L²-distances to uniformity based on the empirical distribution function, the integrated empirical distribution function and the integrated empirical survival function. Approximations of power functions, confidence intervals for the L²-distances and statistical neighbourhood-of-uniformity validation tests are obtained as main applications. The finite sample behaviour of the procedures is illustrated by a simulation study.
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.
A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals.
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.
Magnetic detection structure for Lab-on-Chip applications based on the frequency mixing technique
(2018)
A magnetic frequency mixing technique with a set of miniaturized planar coils was investigated for use with a completely integrated Lab-on-Chip (LoC) pathogen sensing system. The system allows the detection and quantification of superparamagnetic beads. Additionally, in terms of magnetic nanoparticle characterization ability, the system can be used for immunoassays using the beads as markers. Analytical calculations and simulations for both excitation and pick-up coils are presented; the goal was to investigate the miniaturization of simple and cost-effective planar spiral coils. Following these calculations, a Printed Circuit Board (PCB) prototype was designed, manufactured, and tested for limit of detection, linear response, and validation of theoretical concepts. Using the magnetic frequency mixing technique, a limit of detection of 15 µg/mL of 20 nm core-sized nanoparticles was achieved without any shielding.
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.
A field-effect biosensor employing tobacco mosaic virus (TMV) particles as scaffolds for enzyme immobilization is presented. Nanotubular TMV scaffolds allow a dense immobilization of precisely positioned enzymes with retained activity. To demonstrate feasibility of this new strategy, a penicillin sensor has been developed by coupling a penicillinase with virus particles as a model system. The developed field-effect penicillin biosensor consists of an Al-p-Si-SiO₂-Ta₂O₅-TMV structure and has been electrochemically characterized in buffer solutions containing different concentrations of penicillin G. In addition, the morphology of the biosensor surface with virus particles was characterized by scanning electron microscopy and atomic force microscopy methods. The sensors possessed a high penicillin sensitivity of ~ 92 mV/dec in a nearly-linear range from 0.1 mM to 10 mM, and a low detection limit of about 50 µM. The long-term stability of the penicillin biosensor was periodically tested over a time period of about one year without any significant loss of sensitivity. The biosensor has also been successfully applied for penicillin detection in bovine milk samples.
Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement
(2019)
Heating efficiency of magnetic nanoparticles decreases with gradual immobilization in hydrogels
(2019)
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.
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.
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.