Tissue Engineering and Regenerative Medicine International Society (TERMIS) European Chapter Conference 2022

Session

S22 Bringing together state-of-the-art quantitative biology and machine learning-based modeling for controlling and predicting cell and cell population phenotype in the context of regenerative medicine

S22

Jun 28, 2022, 3:30 PM

ICE Krakow

Conveners

S22 Bringing together state-of-the-art quantitative biology and machine learning-based modeling for controlling and predicting cell and cell population phenotype in the context of regenerative medicine

• Bernd Rolauffs (G.E.R.N. Center for Tissue Replacement, Regeneration & Neogenesis, Department of Orthopedics and Trauma Surgery, Faculty of Medicine, Medical Center-Albert-Ludwigs-University of Freiburg )
• Jesús Chato-Astrain (Department of Histology (Tissue Engineering Group), University of Granada, Spain. Instituto de investigación Biosanitaria ibs. GRANADA, Spain)
• Yuto Takemoto (Graduate School of Pharmaceutical Sciences, Nagoya University )

941. Image-based label-free analysis for quantitative and real-time understanding of cellular status

Kato, Ryuji (Nagoya University)

6/28/22, 3:30 PM

invited lecture

"Image-based analysis of cells is a powerful modality to measure and record the high content information which reflects the cellular status during their culture. Although morphology has been known for a long to contain significant information to monitor the transitions of cellular status, their analysis has been limited to experience-based interpretations. However, by the recent rapid...

915. Basics of Cellular and Subcellular Mechanobiology

Schlunck, Günther (Eye Center - Freiburg University Medical Center)

6/28/22, 3:50 PM

invited lecture

We will discuss the influence of cell shape and mechanical load on cell adhesions, cytoskeletal structure, cell signaling and transcription as determinants of cell fate and function.

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221. CHONDROCYTE PROLIFERATION IS INFLUENCED MORE BY F-ACTIN DENSITY AND THE MACROSCOPIC TISSUE DISEASE STATE THAN BY CELL SHAPE OR MICROPATTERN GEOMETRY

Rolauffs, Bernd (G.E.R.N. Center for Tissue Replacement, Regeneration & Neogenesis, Department of Orthopedics and Trauma Surgery, Faculty of Medicine, Medical Center-Albert-Ludwigs-University of Freiburg )

6/28/22, 4:10 PM

podium presentation

Introduction: Chondrocytes beneath the joint surface display a distinct superficial chondrocyte spatial organization (SCSO), which is a marker of tissue ultrastructure and function that undergoes a proliferative remodeling in early osteoarthritis [1,2]. Cellular filamentous actin (F-actin) and cell volume, two proliferation cofactors, change with osteoarthritis and might contribute to...

228. Morphology-based detection of senescence in expanded mesenchymal stem cells

Takemoto, Yuto (Graduate School of Pharmaceutical Sciences, Nagoya University )

6/28/22, 4:20 PM

podium presentation

The expansion culture of cells is an essential process for manufacturing cells for therapeutic use. However, it is also an activity with a huge dilemma. This is because for clinical cell therapy treatment, and also for preparing cells for establishing cell bank, it is strongly required to expand cell number by passage culture to prepare a sufficient number of cells for applications, however at...

230. Using a machine learning-supported approach for assessing and predicting the susceptibility of articular cartilage to mechanical trauma-induced changes in cellularity

Selig, Mischa (G.E.R.N. Research Center for Tissue Replacement, Regeneration & Neogenesis, Dept. of Orthopedics and Trauma Surgery )

6/28/22, 4:30 PM

podium presentation

Using a machine learning-supported approach for assessing and predicting the susceptibility of articular cartilage to mechanical trauma-induced changes in cellularity

M. Selig1,2, Laura Saager, Klaus Böhme, Bodo Kurz2, and B. Rolauffs1
Presenting Author: Mischa Selig, mischa.selig@uniklinik-freiburg.de
1G.E.R.N. Research Center for Tissue Replacement, Regeneration & Neogenesis,...

231. PREDICTION OF M1, M2A AND M2C MACROPHAGE PHENOTYPES AND THEIR IL-10 PRODUCTION POTENTIAL BASED ON SINGLE CELL MORPHOLOGY AND PROTEIN INTENSITY USING A NOVEL MACHINE-LEARNING BASED APPROACH

Poehlman, Logan (TU Dresden )

6/28/22, 4:40 PM

podium presentation

Introduction: Macrophages are a heterogeneous population of cells. In response to microenvironmental cues macrophages shift their polarization state, alter their phenotype and adopt pro- or anti-inflammatory functions, promoting tissue inflammation or contributing to its resolution. Using a novel high throughput image-based single cell morphology and protein intensity machine learning...

16. PREDICTION OF MEDICAL DEVICE COATING PROPERTIES VIA MACHINE LEARNING

Gribova, Varvara (University of Strasbourg)

6/28/22, 4:50 PM

podium presentation

"Introduction
Layer-by-layer (LbL) coating is a method for surface modification based on the electrostatic interactions between two polyelectrolytes. LbL coatings are used for multiple biomedical applications, because natural polyelectrolytes presenting good biocompatibility can be used for LbL film build-up. It is possible to develop antibacterial surfaces, smart healing materials, and...