Ingenieurwissenschaften und zugeordnete Tätigkeiten
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- 2022 (3) (entfernen)
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- Antibody (2)
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Analytical methods based on the selectivity of antibodies, often called immunoassays, are a back-bone of clinical laboratory diagnostics. To bring them to the field, i.e., to make immunoanalytical methods portable, hopefully even faster, more sensitive, and robust, advanced materials are re-quired. Materials can be novel labels, e.g., chemical or particle labels, such as fluorophores or na-noparticles. Carrier particles, such as magnetic or polymer beads, make it possible to adopt the as-says to meso- or microfluidic set-ups and encoding them opens the path to multiplex analysis. Spe-cialty electrodes can enable for higher sensitivity in electrochemical detection. Without research into better materials, efforts to bring analysis to the point-of-need will not bear fruit.
Immunoanalytical Techniques, i.e., antibody-based analytical methods, have been used for decades in clinical diagnostics. What makes them attractive for other fields of application is their short time-to-result and high sensitivity. Microplate-based assays such as ELISA have been adopted early in environmental and food analysis. Yet, to make immunoassays even faster, more sensitive, robust, and, most desirable, portable, advanced materials, sometimes developed for other purposes, can be profitably used to achieve these goals. Materials can be novel labels, e.g., chemical or particle labels, such as fluorophores or nanoparticles. Carrier particles, such as magnetic or polymer beads, make it possible to adopt the assays to meso- or microfluidic set-ups and encoding them opens the path to multiplex analysis. Specialty electrodes can enable for higher sensitivity in electrochemical detection. All this broadens the scope of application and lowers effort and cost for analysis at the point-of-need.
The roughness as a property of core–shell (CS) microparticles plays a key role in their functionality. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task with approaches using electron microscopy images being scarce and showing pronounced differences in terms of methodology and results. This work presents a generalized method for the reliable roughness determination of nonplanar specimens such as CS particles from electron microscopic images, the method being robust and reproducible with a high accuracy. It involves a self-written software package (Python) that analyzes the recorded images, extracts corresponding data, and calculates the roughness based on the deviation of the identified contour. Images of single particles are taken by a dual mode scanning electron microscopy (SEM) setup which permits imaging of the same field-of-view of the sample with high resolution and surface sensitive in SE InLens mode as well as in transmission mode (TSEM). Herein, a new type of polystyrene core–iron oxide shell–silica shell particles is developed to serve as a set of lower micrometer-sized study objects with different surface roughness; the analysis of their images by the semiautomatic workflow is demonstrating that the particles’ profile roughness can be quantitatively obtained.