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For performing point-of-care molecular diagnostics, magnetic immunoassays constitute a promising alternative to established enzyme-linked immunosorbent assays (ELISA) because they are fast, robust and sensitive. Simultaneous detection of multiple biomolecular targets from one body fluid sample is desired. The aim of this work is to show that multiplex magnetic immunodetection based on magnetic frequency mixing by means of modular immunofiltration columns prepared for different targets is feasible. By calculations of the magnetic response signal, the required spacing between the modules was determined. Immunofiltration columns were manufactured by 3D printing and antibody immobilization was performed in a batch approach. It was shown experimentally that two different target molecules in a sample solution could be individually detected in a single assaying step with magnetic measurements of the corresponding immobilization filters. The arrangement order of the filters and of a negative control did not influence the results. Thus, a simple and reliable approach to multi-target magnetic immunodetection was demonstrated.
In modern bioanalytical methods, it is often desired to detect several targets in one sample within one measurement. Immunological methods including those that use superparamagnetic beads are an important group of techniques for these applications. The goal of this work is to investigate the feasibility of simultaneously detecting different superparamagnetic beads acting as markers using the magnetic frequency mixing technique. The frequency of the magnetic excitation field is scanned while the lower driving frequency is kept constant. Due to the particles’ nonlinear magnetization, mixing frequencies are generated. To record their amplitude and phase information, a direct digitization of the pickup-coil’s signal with subsequent Fast Fourier Transformation is performed. By synchronizing both magnetic beads using frequency scanning in magnetic frequency mixing technique magnetic fields, a stable phase information is gained. In this research, it is shown that the amplitude of the dominant mixing component is proportional to the amount of superparamagnetic beads inside a sample. Additionally, it is shown that the phase does not show this behaviour. Excitation frequency scans of different bead types were performed, showing different phases, without correlation to their diverse amplitudes. Two commercially available beads were selected and a determination of their amount in a mixture is performed as a demonstration for multiplex measurements.
Sensitive and rapid detection of cholera toxin subunit B using magnetic frequency mixing detection
(2019)
Cholera is a life-threatening disease caused by the cholera toxin (CT) as produced by some Vibrio cholerae serogroups. In this research we present a method which directly detects the toxin’s B subunit (CTB) in drinking water. For this purpose we performed a magnetic sandwich immunoassay inside a 3D immunofiltration column. We used two different commercially available antibodies to capture CTB and for binding to superparamagnetic beads. ELISA experiments were performed to select the antibody combination. The beads act as labels for the magnetic frequency mixing detection technique. We show that the limit of detection depends on the type of magnetic beads. A nonlinear Hill curve was fitted to the calibration measurements by means of a custom-written python software. We achieved a sensitive and rapid detection of CTB within a broad concentration range from 0.2 ng/ml to more
than 700 ng/ml.
Suppose we have k samples X₁,₁,…,X₁,ₙ₁,…,Xₖ,₁,…,Xₖ,ₙₖ with different sample sizes ₙ₁,…,ₙₖ and unknown underlying distribution functions F₁,…,Fₖ as observations plus k families of distribution functions {G₁(⋅,ϑ);ϑ∈Θ},…,{Gₖ(⋅,ϑ);ϑ∈Θ}, each indexed by elements ϑ from the same parameter set Θ, we consider the new goodness-of-fit problem whether or not (F₁,…,Fₖ) belongs to the parametric family {(G₁(⋅,ϑ),…,Gₖ(⋅,ϑ));ϑ∈Θ}. New test statistics are presented and a parametric bootstrap procedure for the approximation of the unknown null distributions is discussed. Under regularity assumptions, it is proved that the approximation works asymptotically, and the limiting distributions of the test statistics in the null hypothesis case are determined. Simulation studies investigate the quality of the new approach for small and moderate sample sizes. Applications to real-data sets illustrate how the idea can be used for verifying model assumptions.
The paper deals with an asymptotic relative efficiency concept for confidence regions of multidimensional parameters that is based on the expected volumes of the confidence regions. Under standard conditions the asymptotic relative efficiencies of confidence regions are seen to be certain powers of the ratio of the limits of the expected volumes. These limits are explicitly derived for confidence regions associated with certain plugin estimators, likelihood ratio tests and Wald tests. Under regularity conditions, the asymptotic relative efficiency of each of these procedures with respect to each one of its competitors is equal to 1. The results are applied to multivariate normal distributions and multinomial distributions in a fairly general setting.
Im Rahmen der Digitalisierung ist die zunehmende Automatisierung von bisher manuellen Prozessschritten ein Aspekt, der massive Auswirkungen auf die zukünftige Arbeitswelt haben wird. In diesem Kontext werden an den Einsatz von Softwarerobotern zur Prozessautomatisierung hohe Erwartungen geknüpft. Bei den Implementierungsansätzen wird die Diskussion aktuell insbesondere durch Robotic Process Automation (RPA) und Chatbots geprägt. Beide Ansätze verfolgen das gemeinsame Ziel einer 1:1-Automatisierung von menschlichen Handlungen und dadurch ein direktes Ersetzen von Mitarbeitern durch Maschinen. Bei RPA werden Prozesse durch Softwareroboter erlernt und automatisiert ausgeführt. Dabei emulieren RPA-Roboter die Eingaben auf der bestehenden Präsentationsschicht, so dass keine Änderungen an vorhandenen Anwendungssystemen notwendig sind. Am Markt werden bereits unterschiedliche RPA-Lösungen als Softwareprodukte angeboten. Durch Chatbots werden Ein- und Ausgaben von Anwendungssystemen über natürliche Sprache realisiert. Dadurch ist die Automatisierung von unternehmensexterner Kommunikation (z. B. mit Kunden) aber auch von unternehmensinternen Assistenztätigkeiten möglich. Der Beitrag diskutiert die Auswirkungen von Softwarerobotern auf die Arbeitswelt anhand von Anwendungsbeispielen und erläutert die unternehmensindividuelle Entscheidung über den Einsatz von Softwarerobotern anhand von Effektivitäts- und Effizienzzielen.
Kein Urteil zum Datenschutzrecht sorgte im vergangenen Jahr für mehr panische Reaktionen als die Entscheidung des EuGH in der Rechtssache “Wirtschaftsakademie Schleswig-Holstein”(C-210/16). Das Urteil warf in datenschutzrechtlicher Literatur und Öffentlichkeit zahlreiche Fragen auf: Ist jetzt jeder “gemeinsam” Verantwortlicher? Was sind die Kriterien? Der EuGH hat kürzlich in einem – dem allgemeinen Vernehmen nach aufsehenerregenden, de facto aber kaum überraschenden – Urteil für Klarheit gesorgt. Dabei hat das Gericht jedoch einige Fragen offengelassen und neue Fragen aufgeworfen. Ein Blick auf alte und neue Herausforderungen in Kooperationsszenarien.