Longitudinal viscosity of blood plasma for rapid COVID-19 prognostics
Illibauer, J.; Clodi-Seitz, T.; Zoufaly, A.; Aberle, J. H.; Weninger, W. J.; Foedinger, M.; Elsayad, K.
Show abstract
Blood Plasma Viscosity (PV) is an established biomarker for numerous diseases. While PV colloquially refers to the shear viscosity, there is a second viscosity component--the bulk viscosity--that describes the irreversible fluid compressibility on short time scales. The bulk viscosity is acutely sensitive to solid-like suspensions, and obtainable via the longitudinal viscosity from acoustic attenuation measurements. Whether it has diagnostic value remains unexplored yet may be pertinent given the association of diverse pathologies with the formation of plasma suspensions, such as fibrin-microstructures in COVID-19 and long-COVID. Here we show that the longitudinal PV measured using Brillouin Light Scattering (BLS) can serve as a proxy for the shear PV of blood plasma, and exhibits a temperature dependence consistent with increased suspension concentrations in severe COVID-patient plasma. Our results open a new avenue for PV diagnostics based on the longitudinal PV, and show that BLS can provide a means for its clinical implementation.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Early-stage cancer results in a multiplicative increase in cell-free DNA originating from healthy tissue 90%
- Run-and-tumble dynamics of E. coli is governed by its mechanical properties 89%
- Active Sinking Particles: Sessile Suspension Feeders significantly alter the Flow and Transport to Sinking Aggregates 89%
Similar papers in this journal
- Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen 92%
- Measurement of hindered diffusion in complex geometries for high-speed single-molecule experiments 92%
- Verifying molecular clusters by 2-color localization microscopy and significance testing 91%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.