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Heparin is a natural polysaccharide, which plays essential role in many biological processes. Alterations in building blocks can modify biological roles of commercial heparin products, due to significant changes in the conformation of the polymer chain. The variability structure of heparin leads to difficulty in quality control using different analytical methods, including infrared (IR) spectroscopy. In this paper molecular modelling of heparin disaccharide subunits was performed using quantum chemistry. The structural and spectral parameters of these disaccharides have been calculated using RHF/6-311G. In addition, over-sulphated chondroitin sulphate disaccharide was studied as one of the most widespread contaminants of heparin. Calculated IR spectra were analyzed with respect to specific structure parameters. IR spectroscopic fingerprint was found to be sensitive to substitution pattern of disaccharide subunits. Vibrational assignments of calculated spectra were correlated with experimental IR spectral bands of native heparin. Chemometrics was used to perform multivariate analysis of simulated spectral data.
REM sleep without atonia (RSWA) is a key feature for the diagnosis of rapid eye movement (REM) sleep behaviour disorder (RBD). We introduce RBDtector, a novel open-source software to score RSWA according to established SINBAR visual scoring criteria. We assessed muscle activity of the mentalis, flexor digitorum superficialis (FDS), and anterior tibialis (AT) muscles. RSWA was scored manually as tonic, phasic, and any activity by human scorers as well as using RBDtector in 20 subjects. Subsequently, 174 subjects (72 without RBD and 102 with RBD) were analysed with RBDtector to show the algorithm’s applicability. We additionally compared RBDtector estimates to a previously published dataset. RBDtector showed robust conformity with human scorings. The highest congruency was achieved for phasic and any activity of the FDS. Combining mentalis any and FDS any, RBDtector identified RBD subjects with 100% specificity and 96% sensitivity applying a cut-off of 20.6%. Comparable performance was obtained without manual artefact removal. RBD subjects also showed muscle bouts of higher amplitude and longer duration. RBDtector provides estimates of tonic, phasic, and any activity comparable to human scorings. RBDtector, which is freely available, can help identify RBD subjects and provides reliable RSWA metrics.
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.
Schlafspindeln – Funktion, Detektion und Nutzung als Biomarker für die psychiatrische Diagnostik
(2022)
Hintergrund:
Die Schlafspindel ist ein Graphoelement des Elektroenzephalogramms
(EEG), das im Leicht- und Tiefschlaf beobachtet werden kann. Veränderungen der
Spindelaktivität wurden für verschiedene psychiatrische Erkrankungen beschrieben. Schlafspindeln zeigen aufgrund ihrer relativ konstanten Eigenschaften Potenzial als Biomarker in der psychiatrischen Diagnostik.
Methode:
Dieser Beitrag liefert einen Überblick über den Stand der Wissenschaft
zu Eigenschaften und Funktionen der Schlafspindeln sowie über beschriebene
Veränderungen der Spindelaktivität bei psychiatrischen Erkrankungen. Verschiedene methodische Ansätze und Ausblicke zur Spindeldetektion werden hinsichtlich deren Anwendungspotenzial in der psychiatrischen Diagnostik erläutert.
Ergebnisse und Schlussfolgerung:
Während Veränderungen der Spindelaktivität
bei psychiatrischen Erkrankungen beschrieben wurden, ist deren exaktes Potenzial für die psychiatrische Diagnostik noch nicht ausreichend erforscht. Diesbezüglicher Erkenntnisgewinn wird in der Forschung gegenwärtig durch ressourcenintensive und fehleranfällige Methoden zur manuellen oder automatisierten Spindeldetektion ausgebremst. Neuere Detektionsansätze, die auf Deep-Learning-Verfahren basieren, könnten die Schwierigkeiten bisheriger Detektionsmethoden überwinden und damit neue Möglichkeiten für die praktisch
Das Gesundheitswesen ist konfrontiert mit steigenden Kosten und einer immer schwieriger werdenden Personalsituation. Zeitgleich versprechen moderne Sprachsteuerungssysteme Prozesse in Arztpraxen und Krankenhäusern zu verschlanken und Vorgänge zu beschleunigen. Dennoch wird derzeit der Einsatz von Sprachsteuerungssystemen in Arztpraxen oder Krankenhäusern nur selten beobachtet, was auch an den besonders strengen Datenschutzauflagen der Datenschutzgrundverordnung (DSGVO) liegt. Darüber hinaus wirft die niedrige Nutzungsrate die Frage nach den konkreten Anforderungen und ihrer Umsetzbarkeit auf, was durch den vorliegenden Beitrag adressiert wird, indem die Ergebnisse von Interviews mit acht medizinischen Fachexperten ausgewertet werden. Ergänzend wird die technische Umsetzbarkeit einzelner Anforderungen mit unterschiedlichen Cloud-Anbietern erprobt.
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.
With proven impact of statistical fracture analysis on fracture classifications, it is desirable to minimize the manual work and to maximize repeatability of this approach. We address this with an algorithm that reduces the manual effort to segmentation, fragment identification and reduction. The fracture edge detection and heat map generation are performed automatically. With the same input, the algorithm always delivers the same output. The tool transforms one intact template consecutively onto each fractured specimen by linear least square optimization, detects the fragment edges in the template and then superimposes them to generate a fracture probability heat map.
We hypothesized that the algorithm runs faster than the manual evaluation and with low (< 5 mm) deviation. We tested the hypothesis in 10 fractured proximal humeri and found that it performs with good accuracy (2.5 mm ± 2.4 mm averaged Euclidean distance) and speed (23 times faster). When applied to a distal humerus, a tibia plateau, and a scaphoid fracture, the run times were low (1–2 min), and the detected edges correct by visual judgement. In the geometrically complex acetabulum, at a run time of 78 min some outliers were considered acceptable. An automatically generated fracture probability heat map based on 50 proximal humerus fractures matches the areas of high risk of fracture reported in medical literature.
Such automation of the fracture analysis method is advantageous and could be extended to reduce the manual effort even further.
This study addresses a proof-of-concept experiment with a biocompatible screen-printed carbon electrode deposited onto a biocompatible and biodegradable substrate, which is made of fibroin, a protein derived from silk of the Bombyx mori silkworm. To demonstrate the sensor performance, the carbon electrode is functionalized as a glucose biosensor with the enzyme glucose oxidase and encapsulated with a silicone rubber to ensure biocompatibility of the contact wires. The carbon electrode is fabricated by means of thick-film technology including a curing step to solidify the carbon paste. The influence of the curing temperature and curing time on the electrode morphology is analyzed via scanning electron microscopy. The electrochemical characterization of the glucose biosensor is performed by amperometric/voltammetric measurements of different glucose concentrations in phosphate buffer. Herein, systematic studies at applied potentials from 500 to 1200 mV to the carbon working electrode (vs the Ag/AgCl reference electrode) allow to determine the optimal working potential. Additionally, the influence of the curing parameters on the glucose sensitivity is examined over a time period of up to 361 days. The sensor shows a negligible cross-sensitivity toward ascorbic acid, noradrenaline, and adrenaline. The developed biocompatible biosensor is highly promising for future in vivo and epidermal applications.
Utilizing an appropriate enzyme immobilization strategy is crucial for designing enzyme-based biosensors. Plant virus-like particles represent ideal nanoscaffolds for an extremely dense and precise immobilization of enzymes, due to their regular shape, high surface-to-volume ratio and high density of surface binding sites. In the present work, tobacco mosaic virus (TMV) particles were applied for the co-immobilization of penicillinase and urease onto the gate surface of a field-effect electrolyte-insulator-semiconductor capacitor (EISCAP) with a p-Si-SiO₂-Ta₂O₅ layer structure for the sequential detection of penicillin and urea. The TMV-assisted bi-enzyme EISCAP biosensor exhibited a high urea and penicillin sensitivity of 54 and 85 mV/dec, respectively, in the concentration range of 0.1–3 mM. For comparison, the characteristics of single-enzyme EISCAP biosensors modified with TMV particles immobilized with either penicillinase or urease were also investigated. The surface morphology of the TMV-modified Ta₂O₅-gate was analyzed by scanning electron microscopy. Additionally, the bi-enzyme EISCAP was applied to mimic an XOR (Exclusive OR) enzyme logic gate.