Physics of Life · Saarland University

The physics of the
red blood cell

Doctoral researcher in experimental soft-matter and biological physics at Saarland University. I study the mechanics, flow and aggregation of red blood cells, from single cells to dense suspensions, using in vivo microscopy, image analysis and physical modelling.

Reconstructed 3D red blood cell shapes: spherocyte, stomatocyte, discocyte, acanthocyte and echinocyte
Reconstructed red-cell shapes from confocal image stacks: spherocyte, stomatocyte, discocyte, acanthocyte and echinocyte.
01 · About
POSITIONDoctoral researcher
GROUPAG Wagner, Saarland University
BASEDSaarbrücken, DE
BORN1996, Neunkirchen

Background

Since 2022 I have been working towards a doctorate (Dr. rer. nat.) in the group of Prof. Christian Wagner at Saarland University. My Master's thesis dealt with the sedimentation of erythrocytes in colloidal-silica density gradients. My current work covers detection and tracking pipelines for microscopy data, 2D/3D image segmentation, shape analysis, and models of how red cells move, deform and aggregate.

The position is funded by a Young Investigator Grant awarded to Dr. Alexis Darras. In 2025 the work received the Best Poster Award at the Annual European Rheology Conference (AERC) in Lyon.

MATLABPythonC++ / CUDAImage analysisEmbedded systems
Collaborating institutions
Saarland University
Universitätsklinikum des Saarlandes
University of Bristol
KU Leuven
University of Zürich
Università di Pavia
Université Grenoble Alpes
University of Göttingen
University of Luxembourg
University of Bayreuth
Université Claude Bernard Lyon 1
Sorbonne Université, Station Biologique de Roscoff (CNRS)
Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan
Nanion Technologies (industry partner)
Saarland UniversityChristian Wagner, Lars Kaestner, Thomas John, Kirill Korneev, Yazdan Rashidi, Khadija Larhrissi, Min Qiao, Diana Örüm, Nikolas Lerch, Luca Hastenteufel
Clinical & Experimental Surgery, HomburgMatthias Laschke, Selina Wrublewsky
University of BristolAlexis Darras
KU LeuvenErin Koos, Pavlik Lettinga, Christoph Haessig
University of ZürichAnna Bogdanova, Asya Makhro
University of PaviaGiampaolo Minetti
Université Grenoble AlpesChaouqi Misbah
University of GöttingenCatalina Posada, Michael Rostas
Funding
Deutsche Forschungsgemeinschaft (DFG)
European Union, Horizon 2020 / Marie Skłodowska-Curie Actions
VolkswagenStiftung
Agence Nationale de la Recherche (ANR)

Young Investigator Grant of Saarland University (A. Darras) · DFG research unit FOR 2688 · Research Foundation – Flanders (FWO), project 1108426N.

02 · Research

Selected projects

Figures are taken from the respective studies and talks; references are given with each project. Click a figure to enlarge it.

Plasma channel (FITC-dextran) of an intravital recording
PlasmaFITC-dextran
Labelled healthy red blood cells (CellTracker Deep Red) flowing through a microvessel
Healthy red cellsCellTracker Deep Red
Labelled rigidified red blood cells (PKH26) flowing through a microvessel
Rigidified cellsPKH26
Merged fluorescence channels of the microvessel
Mergedall channels

Intravital fluorescence microscopy in a dorsal skinfold chamber: the three labels are recorded in separate channels and tracked frame by frame.

i.

Blood cells in vivo: tracking at vessel bifurcations

Detection and tracking pipelines for intravital microscopy. White blood cells are classified as rolling or flowing along the vessel wall and followed through bifurcations. In a second study, healthy and artificially rigidified red cells are compared at vessel junctions: rigid cells spend less time at the branch apex, which changes how blood is partitioned between the daughter vessels. This is relevant to diseases with stiffened red cells, such as malaria and sickle-cell disease. My contribution: video processing, tracking pipeline, data analysis, statistics and figures.

White blood cells: ongoing investigations with Khadija Larhrissi, AG Wagner.
Rigid versus healthy red cells: Rashidi*, Maurer*, Wrublewsky*, Larhrissi, John, Gidley, Toye, Kaestner, Wagner, Laschke, Darras. Biophysical Journal (2026). doi:10.1016/j.bpj.2026.03.023

Velocity distributions of healthy and rigid red cells along a vessel bifurcation, with lingering and partitioning statistics
Velocity distributions of healthy (H) and rigid (R) cells along a bifurcation (a) and the resulting statistics (b–d).
Red blood cells forming bands in a density gradient over 20 minutes, with measured and modelled concentration profiles
Band formation over 20 minutes: tube photographs (a) and measured concentration profile (b), compared with the space–time evolution (c) and final profile (d) of the continuity model.
ii.

Band patterns in density gradients

Centrifuged red cells settle into discrete bands, which were long interpreted as evidence of discontinuous cell ageing. Using a continuity equation that includes aggregation, we showed that the bands result from a competition between cell aggregation and net buoyancy. Related work explains the bands in classic Percoll gradients and the resulting limits of age separation.

Maurer, Romero, Lerch, John, Kaestner, Wagner, Darras. PNAS 122(51), e2515704122 (2025). doi:10.1073/pnas.2515704122

Pipeline from confocal image stacks to single-cell 3D surfaces, local curvature maps and curvature-flow transformation
From the confocal stack to the cell surface: segmentation and 3D reconstruction (top), surface extraction, local curvature and Willmore curvature flow (bottom).
iii.

3D phenotyping of red-cell shape

Cell surfaces from confocal and STED stacks are smoothed by Willmore curvature flow and decomposed into spherical harmonics, which places each cell on the stomatocyte–discocyte–echinocyte axis. A random-forest classifier reaches 92% accuracy on 730 cells and separates shape changes that are difficult to distinguish by eye. Developed together with Nikolas Lerch.

Building on the 3D red-cell phenotyping of Simionato, Quint et al. AG Wagner, Saarland University.

Red blood cell shape classes in the plane of the first two principal components
Shape classes in the plane of the first two principal components.
Further projects

Cytosol viscosity and density

Buoyant-density centrifugation gives the density distribution of red cells and, via the relation between cytosol viscosity and density, their intracellular viscosity. The results provide single-cell parameters for blood-flow models. My contribution: density-gradient preparation and measurements.

John, Kretsch, Maurer, Recktenwald, Kaestner, Wagner. Biophysical Journal 124(16) (2025). doi:10.1016/j.bpj.2025.07.002

Dose-response curves of Piezo1 currents for Yoda1 and Yoda2

Piezo1 activators: Yoda1 vs Yoda2

Automated patch clamp and calcium imaging are used to compare how the chemical activators Yoda1 and Yoda2 open the mechanosensitive Piezo1 channel in red cells.

Qiao, Penttinen, Coli, Murciano, Maurer, Wagner, Rotordam, Kaestner. Biomolecules 15(8), 1110 (2025). doi:10.3390/biom15081110

Experiment versus simulation of red blood cell shape dynamics in time-dependent capillary flow

Red-cell shapes in time-dependent capillary flow

In capillary flow, red cells adopt either a symmetric croissant or an off-centred slipper shape. Under time-dependent flow, the croissant-to-slipper transition is considerably faster than the reverse and depends on the flow ramp rate. Cells were tracked in a co-moving frame using a custom PID-controlled microscope stage.

Recktenwald*, Graessel*, Maurer, John, Gekle, Wagner. Biophysical Journal 121(1) (2022). doi:10.1016/j.bpj.2021.12.009

Fluo-4 calcium histogram: sickle red cells shift into the high-calcium range after THC

THC and sickle red cells

Δ⁹-THC activates cation channels in red cells, which raises intracellular calcium and leads to dehydration and shape change. After THC exposure, a large fraction of sickle cells shifts into the high-calcium range, suggesting that cannabis use may be harmful in sickle-cell disease.

Hatem*, Esperti*, Murciano*, Qiao*, … Maurer, … Egée. American Journal of Hematology 98(12) (2023). doi:10.1002/ajh.27109

Micrographs and growth data of the deposit of a drying red-cell droplet

Deposits of drying blood droplets

Drying droplets usually leave a ring-shaped deposit (coffee-ring effect). At low red-cell concentration, the deposit instead grows from a central edge. This growth is quantified via interface growth and roughness scaling, with potential use in blood-drop diagnostics.

Sardari, Mohammadian, Asfia, Maurer, Örüm, … Darras. J. Colloid Interface Sci. 679(A) (2025). doi:10.1016/j.jcis.2024.10.039

3D reconstruction of a percolating cluster of red blood cells

Red-cell aggregation and gel formation

Ongoing work: optical-tweezers measurements of the attraction between two cells are used to derive a pair-interaction potential, which enters a percolation model of aggregated blood as a gel.

Ongoing, with K. Korneev (AG Wagner) and C. Haessig (KU Leuven). 3D reconstruction and recording of the cells shown by C. Haessig.

03 · Publications

Peer-reviewed articles

* equal contribution
2026Impact of red blood cell rigidity on in vivo flow dynamics and lingering in bifurcationsRashidi*, Maurer*, Wrublewsky*, Larhrissi, John, Gidley, Toye, Kaestner, Wagner, Laschke, DarrasBiophysical Journal · doi:10.1016/j.bpj.2026.03.023DOI ↗ 2025Band pattern formation of erythrocytes in density gradients is due to competing aggregation and net buoyancyMaurer, Romero, Lerch, John, Kaestner, Wagner, DarrasPNAS 122(51), e2515704122 · doi:10.1073/pnas.2515704122DOI ↗ 2025Viscosity and density measurements on the cytosol of human red blood cellsJohn, Kretsch, Maurer, Recktenwald, Kaestner, WagnerBiophysical Journal 124(16), 2668-2676 · doi:10.1016/j.bpj.2025.07.002DOI ↗ 2025Piezo1 channel activators Yoda1 and Yoda2 in the context of red blood cellsQiao, Penttinen, Coli, Murciano, Maurer, Wagner, Rotordam, KaestnerBiomolecules 15(8), 1110 · doi:10.3390/biom15081110DOI ↗ 2025Deposit of red blood cells at low concentrations in evaporating droplets is dominated by a central edge growthSardari, Mohammadian, Asfia, Maurer, Örüm, Seemann, John, Kaestner, Wagner, Maleki, DarrasJ. Colloid Interface Sci. 679(A), 939-946 · doi:10.1016/j.jcis.2024.10.039DOI ↗ 2023Adverse effects of Δ⁹-tetrahydrocannabinol on sickle red blood cellsHatem*, Esperti*, Murciano*, Qiao*, Rotordam, Becker, Nader, Maurer, Pérès, Bouyer, Kaestner, Connes, EgéeAmerican Journal of Hematology 98(12), E383-E386 · doi:10.1002/ajh.27109DOI ↗ 2022Continuous Percoll gradient centrifugation of erythrocytes: explanation of cellular bands and compromised age separationMaurer, John, Makhro, Bogdanova, Minetti, Wagner, KaestnerCells 11(8), 1296 · doi:10.3390/cells11081296DOI ↗ 2022Red blood cell shape transitions and dynamics in time-dependent capillary flowsRecktenwald*, Graessel*, Maurer, John, Gekle, WagnerBiophysical Journal 121(1), 23-36 · doi:10.1016/j.bpj.2021.12.009DOI ↗

Additional manuscripts in preparation. Full list on ORCID. Ad hoc reviewer (2023), Scandinavian Journal of Clinical & Laboratory Investigation.

04 · Software & Teaching

Software

Research pipelines and teaching software, available on github.com/FelixMaurer.

Research tools
Teaching
05 · Curriculum Vitae

Education and employment

Education
since 2022
Dr. rer. nat., Physics

Experimental soft matter / biological physics, AG Wagner · Saarland University.

2019-21
M.Sc. Physics

Saarland University. Thesis: sedimentation of erythrocytes in a colloidal-silica density gradient.

2014-18
B.Sc. Physics

Saarland University. Thesis: statistical analysis of red-cell flow in microchannels.

Awards
2025
Best Poster Award · AERC, Lyon
2014
Abiturpreis · Deutsche Physikalische Gesellschaft
Employment
since 2022
Research associate (Wissenschaftlicher Mitarbeiter)

Saarland University · research & teaching. Funded by a Young Investigator Grant (A. Darras).

2019-23
Developer / Electronic Engineer

AspektEins GmbH · integrated systems, ARM firmware, PCB design (working student).

2015-20
Student research assistant

AG Wagner · microscope control, image analysis, portable optical tweezers.

Teaching & supervision
Mathematischer Vorkurs (lecturer, 2022-25) · Physik für Biologen (2025) · Kernphysik (2024-25) · Advanced lab FOPRA · γγ-angular correlation & positron lifetime (2023-26) · Optik & Thermodynamik (2023) · Grundpraktikum (2020-22).
Co-supervision: N. Lerch (B.Sc. + M.Sc.), L. Hastenteufel (B.Sc.). Mentoring: D. Örüm (MD), K. Larhrissi (PhD), M. Qiao (collaboration).
11 conference contributions incl. DPG Spring Meetings, AERC Lyon, Living Fluids (Marrakesh), BIFD (Edinburgh), DynaCaps (Compiègne).
06 · News & Press
07 · Contact

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