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  Estimation of the mass density of biological matter from refractive index measurements

Möckel, C., Beck, T., Kaliman, S., Abuhattum Hofemeier, S., Kim, K., Kolb, J., et al. (2024). Estimation of the mass density of biological matter from refractive index measurements. Biophysical Reports, 4(2): 100156, pp. 100156. doi:10.1016/j.bpr.2024.100156.

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This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

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Möckel, Conrad1, 2, Autor           
Beck, Timon1, 2, Autor           
Kaliman, Sara1, 2, Autor           
Abuhattum Hofemeier, Shada1, 2, Autor           
Kim, Kyoohyun1, 2, Autor           
Kolb, Julia2, 3, Autor           
Wehner, Daniel2, 3, Autor           
Zaburdaev, Vasily2, 4, Autor           
Guck, Jochen1, 2, 4, Autor           
Affiliations:
1Guck Division, Max Planck Institute for the Science of Light, Max Planck Society, ou_3164416              
2Max-Planck-Zentrum für Physik und Medizin, Max Planck Institute for the Science of Light, Max Planck Society, ou_3164414              
3Wehner Research Group, Guck Division, Max Planck Institute for the Science of Light, Max Planck Society, ou_3358768              
4Friedrich-Alexander-Universität Erlangen-Nürnberg, External Organizations, DE, ou_3487833              

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 Zusammenfassung: The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms. One of the basic biophysical properties is the mass density (MD). It affects the dynamics in sub-cellular compartments and plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge, as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for assumptions about the biochemical composition of the sample and respective RI measurements. To this aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations and Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well-characterized complex mixtures given by bovine milk and intralipid emulsion and employ it to estimate the MD of living zebrafish (Danio rerio) larvae trunk tissue. Our results illustrate the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.

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Sprache(n): eng - English
 Datum: 2024-04-24
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1016/j.bpr.2024.100156
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Titel: Biophysical Reports
Genre der Quelle: Zeitschrift
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Seiten: - Band / Heft: 4 (2) Artikelnummer: 100156 Start- / Endseite: 100156 Identifikator: ISSN: 26670747