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It was generally believed that coal sources are not favorable as live-in habitats for microorganisms due to their recalcitrant chemical nature and negligible decomposition. However, accumulating evidence has revealed the presence of diverse microbial groups in coal environments and their significant metabolic role in coal biogeochemical dynamics and ecosystem functioning. The high oxygen content, organic fractions, and lignin-like structures of lower-rank coals may provide effective means for microbial attack, still representing a greatly unexplored frontier in microbiology. Coal degradation/conversion technology by native bacterial and fungal species has great potential in agricultural development, chemical industry production, and environmental rehabilitation. Furthermore, native microalgal species can offer a sustainable energy source and an excellent bioremediation strategy applicable to coal spill/seam waters. Additionally, the measures of the fate of the microbial community would serve as an indicator of restoration progress on post-coal-mining sites. This review puts forward a comprehensive vision of coal biodegradation and bioprocessing by microorganisms native to coal environments for determining their biotechnological potential and possible applications.
Objective
Hemodialysis patients show an approximately threefold higher prevalence of cognitive impairment compared to the age-matched general population. Impaired microcirculatory function is one of the assumed causes. Dynamic retinal vessel analysis is a quantitative method for measuring neurovascular coupling and microvascular endothelial function. We hypothesize that cognitive impairment is associated with altered microcirculation of retinal vessels.
Methods
152 chronic hemodialysis patients underwent cognitive testing using the Montreal Cognitive Assessment. Retinal microcirculation was assessed by Dynamic Retinal Vessel Analysis, which carries out an examination recording retinal vessels' reaction to a flicker light stimulus under standardized conditions.
Results
In unadjusted as well as in adjusted linear regression analyses a significant association between the visuospatial executive function domain score of the Montreal Cognitive Assessment and the maximum arteriolar dilation as response of retinal arterioles to the flicker light stimulation was obtained.
Conclusion
This is the first study determining retinal microvascular function as surrogate for cerebral microvascular function and cognition in hemodialysis patients. The relationship between impairment in executive function and reduced arteriolar reaction to flicker light stimulation supports the involvement of cerebral small vessel disease as contributing factor for the development of cognitive impairment in this patient population and might be a target for noninvasive disease monitoring and therapeutic intervention.
On the basis of bivariate data, assumed to be observations of independent copies of a random vector (S,N), we consider testing the hypothesis that the distribution of (S,N) belongs to the parametric class of distributions that arise with the compound Poisson exponential model. Typically, this model is used in stochastic hydrology, with N as the number of raindays, and S as total rainfall amount during a certain time period, or in actuarial science, with N as the number of losses, and S as total loss expenditure during a certain time period. The compound Poisson exponential model is characterized in the way that a specific transform associated with the distribution of (S,N) satisfies a certain differential equation. Mimicking the function part of this equation by substituting the empirical counterparts of the transform we obtain an expression the weighted integral of the square of which is used as test statistic. We deal with two variants of the latter, one of which being invariant under scale transformations of the S-part by fixed positive constants. Critical values are obtained by using a parametric bootstrap procedure. The asymptotic behavior of the tests is discussed. A simulation study demonstrates the performance of the tests in the finite sample case. The procedure is applied to rainfall data and to an actuarial dataset. A multivariate extension is also discussed.
Virgin passive colon biomechanics and a literature review of active contraction constitutive models
(2022)
The objective of this paper is to present our findings on the biomechanical aspects of the virgin passive anisotropic hyperelasticity of the porcine colon based on equibiaxial tensile experiments. Firstly, the characterization of the intestine tissues is discussed for a nearly incompressible hyperelastic fiber-reinforced Holzapfel–Gasser–Ogden constitutive model in virgin passive loading conditions. The stability of the evaluated material parameters is checked for the polyconvexity of the adopted strain energy function using positive eigenvalue constraints of the Hessian matrix with MATLAB. The constitutive material description of the intestine with two collagen fibers in the submucosal and muscular layer each has been implemented in the FORTRAN platform of the commercial finite element software LS-DYNA, and two equibiaxial tensile simulations are presented to validate the results with the optical strain images obtained from the experiments. Furthermore, this paper also reviews the existing models of the active smooth muscle cells, but these models have not been computationally studied here. The review part shows that the constitutive models originally developed for the active contraction of skeletal muscle based on Hill’s three-element model, Murphy’s four-state cross-bridge chemical kinetic model and Huxley’s sliding-filament hypothesis, which are mainly used for arteries, are appropriate for numerical contraction numerical analysis of the large intestine.
The mechanical behavior of the large intestine beyond the ultimate stress has never been investigated. Stretching beyond the ultimate stress may drastically impair the tissue microstructure, which consequently weakens its healthy state functions of absorption, temporary storage, and transportation for defecation. Due to closely similar microstructure and function with humans, biaxial tensile experiments on the porcine large intestine have been performed in this study. In this paper, we report hyperelastic characterization of the large intestine based on experiments in 102 specimens. We also report the theoretical analysis of the experimental results, including an exponential damage evolution function. The fracture energies and the threshold stresses are set as damage material parameters for the longitudinal muscular, the circumferential muscular and the submucosal collagenous layers. A biaxial tensile simulation of a linear brick element has been performed to validate the applicability of the estimated material parameters. The model successfully simulates the biomechanical response of the large intestine under physiological and non-physiological loads.
Orthodontic treatments are concomitant with mechanical forces and thereby cause teeth movements. The applied forces are transmitted to the tooth root and the periodontal ligaments which is compressed on one side and tensed up on the other side. Indeed, strong forces can lead to tooth root resorption and the crown-to-tooth ratio is reduced with the potential for significant clinical impact. The cementum, which covers the tooth root, is a thin mineralized tissue of the periodontium that connects the periodontal ligament with the tooth and is build up by cementoblasts. The impact of tension and compression on these cells is investigated in several in vivo and in vitro studies demonstrating differences in protein expression and signaling pathways. In summary, osteogenic marker changes indicate that cyclic tensile forces support whereas static tension inhibits cementogenesis. Furthermore, cementogenesis experiences the same protein expression changes in static conditions as static tension, but cyclic compression leads to the exact opposite of cyclic tension. Consistent with marker expression changes, the singaling pathways of Wnt/ß-catenin and RANKL/OPG show that tissue compression leads to cementum degradation and tension forces to cementogenesis. However, the cementum, and in particular its cementoblasts, remain a research area which should be explored in more detail to understand the underlying mechanism of bone resorption and remodeling after orthodontic treatments.
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.
This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cramér–von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices.
Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles’ magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.
On the basis of independent and identically distributed bivariate random vectors, where the components are categorial and continuous variables, respectively, the related concomitants, also called induced order statistic, are considered. The main theoretical result is a functional central limit theorem for the empirical process of the concomitants in a triangular array setting. A natural application is hypothesis testing. An independence test and a two-sample test are investigated in detail. The fairly general setting enables limit results under local alternatives and bootstrap samples. For the comparison with existing tests from the literature simulation studies are conducted. The empirical results obtained confirm the theoretical findings.
Analysis and computation of the transmission eigenvalues with a conductive boundary condition
(2022)
We provide a new analytical and computational study of the transmission eigenvalues with a conductive boundary condition. These eigenvalues are derived from the scalar inverse scattering problem for an inhomogeneous material with a conductive boundary condition. The goal is to study how these eigenvalues depend on the material parameters in order to estimate the refractive index. The analytical questions we study are: deriving Faber–Krahn type lower bounds, the discreteness and limiting behavior of the transmission eigenvalues as the conductivity tends to infinity for a sign changing contrast. We also provide a numerical study of a new boundary integral equation for computing the eigenvalues. Lastly, using the limiting behavior we will numerically estimate the refractive index from the eigenvalues provided the conductivity is sufficiently large but unknown.
Exposure to prolonged periods in microgravity is associated with deconditioning of the musculoskeletal system due to chronic changes in mechanical stimulation. Given astronauts will operate on the Lunar surface for extended periods of time, it is critical to quantify both external (e.g., ground reaction forces) and internal (e.g., joint reaction forces) loads of relevant movements performed during Lunar missions. Such knowledge is key to predict musculoskeletal deconditioning and determine appropriate exercise countermeasures associated with extended exposure to hypogravity.
An alternative method is presented to numerically compute interior elastic transmission eigenvalues for various domains in two dimensions. This is achieved by discretizing the resulting system of boundary integral equations in combination with a nonlinear eigenvalue solver. Numerical results are given to show that this new approach can provide better results than the finite element method when dealing with general domains.
Retinal vessels are similar to cerebral vessels in their structure and function. Moderately low oscillation frequencies of around 0.1 Hz have been reported as the driving force for paravascular drainage in gray matter in mice and are known as the frequencies of lymphatic vessels in humans. We aimed to elucidate whether retinal vessel oscillations are altered in Alzheimer's disease (AD) at the stage of dementia or mild cognitive impairment (MCI). Seventeen patients with mild-to-moderate dementia due to AD (ADD); 23 patients with MCI due to AD, and 18 cognitively healthy controls (HC) were examined using Dynamic Retinal Vessel Analyzer. Oscillatory temporal changes of retinal vessel diameters were evaluated using mathematical signal analysis. Especially at moderately low frequencies around 0.1 Hz, arterial oscillations in ADD and MCI significantly prevailed over HC oscillations and correlated with disease severity. The pronounced retinal arterial vasomotion at moderately low frequencies in the ADD and MCI groups would be compatible with the view of a compensatory upregulation of paravascular drainage in AD and strengthen the amyloid clearance hypothesis.
Introduction
In regard of surgical training, the reproducible simulation of life-like proximal humerus fractures in human cadaveric specimens is desirable. The aim of the present study was to develop a technique that allows simulation of realistic proximal humerus fractures and to analyse the influence of rotator cuff preload on the generated lesions in regards of fracture configuration.
Materials and methods
Ten cadaveric specimens (6 left, 4 right) were fractured using a custom-made drop-test bench, in two groups. Five specimens were fractured without rotator cuff preload, while the other five were fractured with the tendons of the rotator cuff preloaded with 2 kg each. The humeral shaft and the shortened scapula were potted. The humerus was positioned at 90° of abduction and 10° of internal rotation to simulate a fall on the elevated arm. In two specimens of each group, the emergence of the fractures was documented with high-speed video imaging. Pre-fracture radiographs were taken to evaluate the deltoid-tuberosity index as a measure of bone density. Post-fracture X-rays and CT scans were performed to define the exact fracture configurations. Neer’s classification was used to analyse the fractures.
Results
In all ten cadaveric specimens life-like proximal humerus fractures were achieved. Two III-part and three IV-part fractures resulted in each group. The preloading of the rotator cuff muscles had no further influence on the fracture configuration. High-speed videos of the fracture simulation revealed identical fracture mechanisms for both groups. We observed a two-step fracture mechanism, with initial impaction of the head segment against the glenoid followed by fracturing of the head and the tuberosities and then with further impaction of the shaft against the acromion, which lead to separation of the tuberosities.
Conclusion
A high energetic axial impulse can reliably induce realistic proximal humerus fractures in cadaveric specimens. The preload of the rotator cuff muscles had no influence on initial fracture configuration. Therefore, fracture simulation in the proximal humerus is less elaborate. Using the presented technique, pre-fractured specimens are available for real-life surgical education.
Introduction: In peripheral percutaneous (VA) extracorporeal membrane oxygenation (ECMO) procedures the femoral arteries perfusion route has inherent disadvantages regarding poor upper body perfusion due to watershed. With the advent of new long flexible cannulas an advancement of the tip up to the ascending aorta has become feasible. To investigate the impact of such long endoluminal cannulas on upper body perfusion, a Computational Fluid Dynamics (CFD) study was performed considering different support levels and three cannula positions.
Methods: An idealized literature-based- and a real patient proximal aortic geometry including an endoluminal cannula were constructed. The blood flow was considered continuous. Oxygen saturation was set to 80% for the blood coming from the heart and to 100% for the blood leaving the cannula. 50% and 90% venoarterial support levels from the total blood flow rate of 6 l/min were investigated for three different positions of the cannula in the aortic arch.
Results: For both geometries, the placement of the cannula in the ascending aorta led to a superior oxygenation of all aortic blood vessels except for the left coronary artery. Cannula placements at the aortic arch and descending aorta could support supra-aortic arteries, but not the coronary arteries. All positions were able to support all branches with saturated blood at 90% flow volume.
Conclusions: In accordance with clinical observations CFD analysis reveals, that retrograde advancement of a long endoluminal cannula can considerably improve the oxygenation of the upper body and lead to oxygen saturation distributions similar to those of a central cannulation.
Wearable EEG has gained popularity in recent years driven by promising uses outside of clinics and research. The ubiquitous application of continuous EEG requires unobtrusive form-factors that are easily acceptable by the end-users. In this progression, wearable EEG systems have been moving from full scalp to forehead and recently to the ear. The aim of this study is to demonstrate that emerging ear-EEG provides similar impedance and signal properties as established forehead EEG. EEG data using eyes-open and closed alpha paradigm were acquired from ten healthy subjects using generic earpieces fitted with three custom-made electrodes and a forehead electrode (at Fpx) after impedance analysis. Inter-subject variability in in-ear electrode impedance ranged from 20 kΩ to 25 kΩ at 10 Hz. Signal quality was comparable with an SNR of 6 for in-ear and 8 for forehead electrodes. Alpha attenuation was significant during the eyes-open condition in all in-ear electrodes, and it followed the structure of power spectral density plots of forehead electrodes, with the Pearson correlation coefficient of 0.92 between in-ear locations ELE (Left Ear Superior) and ERE (Right Ear Superior) and forehead locations, Fp1 and Fp2, respectively. The results indicate that in-ear EEG is an unobtrusive alternative in terms of impedance, signal properties and information content to established forehead EEG.
Image reconstruction analysis for positron emission tomography with heterostructured scintillators
(2022)
The concept of structure engineering has been proposed for exploring the next generation of radiation detectors with improved performance. A TOF-PET geometry with heterostructured scintillators with a pixel size of 3.0×3.1×15 mm3 was simulated using Monte Carlo. The heterostructures consisted of alternating layers of BGO as a dense material with high stopping power and plastic (EJ232) as a fast light emitter. The detector time resolution was calculated as a function of the deposited and shared energy in both materials on an event-by-event basis. While sensitivity was reduced to 32% for 100 μm thick plastic layers and 52% for 50 μm, the CTR distribution improved to 204±49 ps and 220±41 ps respectively, compared to 276 ps that we considered for bulk BGO. The complex distribution of timing resolutions was accounted for in the reconstruction. We divided the events into three groups based on their CTR and modeled them with different Gaussian TOF kernels. On a NEMA IQ phantom, the heterostructures had better contrast recovery in early iterations. On the other hand, BGO achieved a better contrast to noise ratio (CNR) after the 15th iteration due to the higher sensitivity. The developed simulation and reconstruction methods constitute new tools for evaluating different detector designs with complex time responses.
Frequency mixing magnetic detection (FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for the characterization and distinction (also known as “colourization”) of different types of magnetic nanoparticles (MNPs) based on their core sizes. In a previous work, it was shown that the large particles contribute most of the FMMD signal. This leads to ambiguities in core size determination from fitting since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome by modelling the signal intensity using the Langevin model in thermodynamic equilibrium including a lognormal core size distribution fL(dc,d0,σ) fitted to experimentally measured FMMD data of immobilized MNPs. For each given median diameter d0, an ambiguous amount of best-fitting pairs of parameters distribution width σ and number of particles Np with R2 > 0.99 are extracted. By determining the samples’ total iron mass, mFe, with inductively coupled plasma optical emission spectrometry (ICP-OES), we are then able to identify the one specific best-fitting pair (σ, Np) one uniquely. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, σ, Np) directly from FMMD measurements, allowing precise MNPs sample characterization.