Biology subjects

Gemeinhardt, A.

Publications and source records attributed to Gemeinhardt, A..

2 recordsLinked to original sources

bioRxiv2021

Precision size and refractive index analysis of weakly scattering nanoparticles in polydispersions.

Characterization of the size and material properties of particles in liquid suspensions is in very high demand, e.g., for the analysis of colloidal samples or of bodily fluids such as urine or blood plasma. However, the existing methods are limited in deciphering the constituents of realistic samples. Here, we introduce iNTA as a new method, which combines interferometric detection of scattering with nanoparticle tracking analysis, to reach an unprecedented sensitivity and precision in determining the size and refractive index distributions of nanoparticles in suspensions. After benchmarking iNTA with samples of colloidal gold, we present its remarkable ability to resolve the constituents of various multi-component and polydisperse samples of known origin. Furthermore, we showcase the method by elucidating the refractive index and size distributions of extracellular vesicles from Leishmania parasites and nanoparticles in human urine. The current performance of iNTA already enables advances in several important applications, but we also discuss possible improvements.

biophysics↗

bioRxiv2021

Optimized analysis for sensitive detection and analysis of single proteins via interferometric scattering microscopy

It has been shown that interferometric detection of Rayleigh scattering (iSCAT) can reach an exquisite sensitivity for label-free detection of nano-matter, down to single proteins. The sensitivity of iSCAT detection is intrinsically limited by shot noise, which can be indefinitely improved by employing higher illumination power or longer integration times. In practice, however, a large speckle-like background and technical issues in the experimental setup limit the attainable signal-to-noise ratio. Strategies and algorithms in data analysis are, thus, crucial for extracting quantitative results from weak signals, e.g. regarding the mass (size) of the detected nano-objects or their positions. In this article, we elaborate on some algorithms for processing iSCAT data and identify some key technical as well as conceptual issues that have to be considered when recording and interpreting the data. The discussed methods and analyses are made available in the extensive python-based platform, PiSCAT[§].

biophysics↗