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Edge-based and face-based smoothed finite element methods (ES-FEM and FS-FEM, respectively) are modified versions of the finite element method allowing to achieve more accurate results and to reduce sensitivity to mesh distortion, at least for linear elements. These properties make the two methods very attractive. However, their implementation in a standard finite element code is nontrivial because it requires heavy and extensive modifications to the code architecture. In this article, we present an element-based formulation of ES-FEM and FS-FEM methods allowing to implement the two methods in a standard finite element code with no modifications to its architecture. Moreover, the element-based formulation permits to easily manage any type of element, especially in 3D models where, to the best of the authors' knowledge, only tetrahedral elements are used in FS-FEM applications found in the literature. Shape functions for non-simplex 3D elements are proposed in order to apply FS-FEM to any standard finite element.
Impaired cerebral autoregulation and neurovascular coupling (NVC) contribute to delayed cerebral ischemia after subarachnoid hemorrhage (SAH). Retinal vessel analysis (RVA) allows non-invasive assessment of vessel dimension and NVC hereby demonstrating a predictive value in the context of various neurovascular diseases. Using RVA as a translational approach, we aimed to assess the retinal vessels in patients with SAH. RVA was performed prospectively in 24 patients with acute SAH (group A: day 5–14), in 11 patients 3 months after ictus (group B: day 90 ± 35), and in 35 age-matched healthy controls (group C). Data was acquired using a Retinal Vessel Analyzer (Imedos Systems UG, Jena) for examination of retinal vessel dimension and NVC using flicker-light excitation. Diameter of retinal vessels—central retinal arteriolar and venular equivalent—was significantly reduced in the acute phase (p < 0.001) with gradual improvement in group B (p < 0.05). Arterial NVC of group A was significantly impaired with diminished dilatation (p < 0.001) and reduced area under the curve (p < 0.01) when compared to group C. Group B showed persistent prolonged latency of arterial dilation (p < 0.05). Venous NVC was significantly delayed after SAH compared to group C (A p < 0.001; B p < 0.05). To our knowledge, this is the first clinical study to document retinal vasoconstriction and impairment of NVC in patients with SAH. Using non-invasive RVA as a translational approach, characteristic patterns of compromise were detected for the arterial and venous compartment of the neurovascular unit in a time-dependent fashion. Recruitment will continue to facilitate a correlation analysis with clinical course and outcome.
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.
LAPS are field-effect-based potentiometric sensors which are able to monitor analyte concentrations in a spatially resolved manner. Hence, a LAPS sensor system is a powerful device to record chemical imaging of the concentration of chemical species in an aqueous solution, chemical reactions, or the growth of cell colonies on the sensor surface, to record chemical images. In this work, multi-chamber 3D-printed structures made out of polymer (PP-ABS) were combined with LAPS chips to analyse differentially and simultaneously the metabolic activity of Escherichia coli K12 and Chinese hamster ovary (CHO) cells, and the responds of those cells to the addition of glucose solution.
LAPS-based monitoring of metabolic responses of bacterial cultures in a paper fermentation broth
(2020)
As an alternative renewable energy source, methane production in biogas plants is gaining more and more attention. Biomass in a bioreactor contains different types of microorganisms, which should be considered in terms of process-stability control. Metabolically inactive microorganisms within the fermentation process can lead to undesirable, time-consuming and cost-intensive interventions. Hence, monitoring of the cellular metabolism of bacterial populations in a fermentation broth is crucial to improve the biogas production, operation efficiency, and sustainability. In this work, the extracellular acidification of bacteria in a paper-fermentation broth is monitored after glucose uptake, utilizing a differential light-addressable potentiometric sensor (LAPS) system. The LAPS system is loaded with three different model microorganisms (Escherichia coli, Corynebacterium glutamicum, and Lactobacillus brevis) and the effect of the fermentation broth at different process stages on the metabolism of these bacteria is studied. In this way, different signal patterns related to the metabolic response of microorganisms can be identified. By means of calibration curves after glucose uptake, the overall extracellular acidification of bacterial populations within the fermentation process can be evaluated.
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.
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.
On-line monitoring of the metabolic activity of microorganisms involved in intermediate stages of biogas production plays an important role to avoid undesirable “down times” during the biogas production. In order to control this process, an on-chip differential measuring system based on the light-addressable potentiometric sensor (LAPS) principle combined with a 3D-printed multi-chamber structure has been realized. As a test microorganism, Escherichia coli K12 (E. coli K12) were used for cell-based measurements. Multi-chamber structures were developed to determine the metabolic activity of E. coli K12 in suspension for a different number of cells, responding to the addition of a constant or variable amount of glucose concentrations, enabling differential and simultaneous measurements.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based potentiometric sensor with an electrolyte/insulator/semiconductor (EIS) structure, which is able to monitor analyte concentrations of (bio-)chemical species in aqueous solutions in a spatially resolved way. Therefore, it is also an appropriate tool to record 2D-chemical images of concentration variations on the sensor surface. In the present work, two differential, LAPS-based measurement principles are introduced to determine the metabolic activity of Escherichia coli (E. coli) K12 and Chinese hamster ovary (CHO) cells as test microorganisms. Hereby, we focus on i) the determination of the extracellular acidification rate (ΔpH/min) after adding glucose solutions to the cell suspensions; and ii) recording the amplitude increase of the photocurrent (Iph) related to the produced acids from E. coli K12 bacteria and CHO cells on the sensor surface by 2D-chemical imaging. For this purpose, 3D-printed multi-chamber structures were developed and mounted on the planar sensor-chip surface to define four independent compartments, enabling differential measurements with varying cell concentrations. The differential concept allows eliminating unwanted drift effects and, with the four-chamber structures, measurements on the different cell concentrations were performed simultaneously, thus reducing also the overall measuring time.