Refine
Year of publication
- 2024 (8)
- 2023 (8)
- 2022 (28)
- 2021 (30)
- 2020 (32)
- 2019 (43)
- 2018 (38)
- 2017 (34)
- 2016 (31)
- 2015 (33)
- 2014 (19)
- 2013 (27)
- 2012 (25)
- 2011 (25)
- 2010 (34)
- 2009 (35)
- 2008 (30)
- 2007 (28)
- 2006 (20)
- 2005 (22)
- 2004 (26)
- 2003 (17)
- 2002 (12)
- 2001 (4)
- 2000 (14)
- 1999 (9)
- 1998 (10)
- 1997 (5)
- 1996 (6)
- 1995 (3)
- 1994 (3)
- 1993 (5)
- 1992 (2)
- 1991 (5)
- 1990 (6)
- 1989 (3)
- 1988 (7)
- 1987 (10)
- 1986 (1)
- 1985 (2)
- 1984 (3)
- 1983 (2)
- 1982 (1)
- 1981 (1)
- 1980 (2)
Institute
- IfB - Institut für Bioengineering (601)
- Fachbereich Medizintechnik und Technomathematik (554)
- Fachbereich Luft- und Raumfahrttechnik (141)
- Fachbereich Chemie und Biotechnologie (13)
- Kommission für Forschung und Entwicklung (6)
- Senat (2)
- Arbeitsstelle fuer Hochschuldidaktik und Studienberatung (1)
- Fachbereich Gestaltung (1)
- Fachbereich Maschinenbau und Mechatronik (1)
Has Fulltext
- no (709) (remove)
Language
- English (601)
- German (93)
- Russian (13)
- Multiple languages (2)
Document Type
- Article (509)
- Conference Proceeding (112)
- Part of a Book (36)
- Book (14)
- Report (12)
- Patent (9)
- Doctoral Thesis (8)
- Other (4)
- Habilitation (3)
- Review (1)
Keywords
- solar sail (5)
- CellDrum (3)
- GOSSAMER-1 (3)
- MASCOT (3)
- Biocomposites (2)
- Iterative learning control (2)
- Limit analysis (2)
- Mars (2)
- Natural fibres (2)
- Polymer-matrix composites (2)
Background
True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).
Results
Fluorescence microscopy images of leaflet cross sections have been taken from a set of five date palm tree cultivars (Hewlat al Jouf, Khlas, Nabot Soltan, Shishi, Um Raheem). After features extraction from images, the obtained data have been fed in a multilayer perceptron ANN with backpropagation learning algorithm.
Conclusions
Overall, an accurate result in prediction and differentiation of date palm tree cultivars was achieved with average prediction in tenfold cross-validation is 89.1% and reached 100% in one of the best ANN.
The CellDrum technology (The term 'CellDrum technology' includes a couple of slightly different technological setups for measuring lateral mechanical tension in various types of cell monolayers or 3D-tissue constructs) was designed to quantify the contraction rate and mechanical tension of self-exciting cardiac myocytes. Cells were grown either within flexible, circular collagen gels or as monolayer on top of respective 1-mum thin silicone membranes. Membrane and cells were bulged outwards by air pressure. This biaxial strain distribution is rather similar the beating, blood-filled heart. The setup allowed presetting the mechanical residual stress level externally by adjusting the centre deflection, thus, mimicking hypertension in vitro. Tension was measured as oscillating differential pressure change between chamber and environment. A 0.5-mm thick collagen-cardiac myocyte tissue construct induced after 2 days of culturing (initial cell density 2 x 10(4) cells/ml), a mechanical tension of 1.62 +/- 0.17 microN/mm(2). Mechanical load is an important growth regulator in the developing heart, and the orientation and alignment of cardiomyocytes is stress sensitive. Therefore, it was necessary to develop the CellDrum technology with its biaxial stress-strain distribution and defined mechanical boundary conditions. Cells were exposed to strain in two directions, radially and circumferentially, which is similar to biaxial loading in real heart tissues. Thus, from a biomechanical point of view, the system is preferable to previous setups based on uniaxial stretching.
All cells generate contractile tension. This strain is crucial for mechanically controlling the cell shape, function and survival. In this study, the CellDrum technology quantifying cell's (the cellular) mechanical tension on a pico-scale was used to investigate the effect of lipopolysaccharide (LPS) on human aortic endothelial cell (HAoEC) tension. The LPS effect during gram-negative sepsis on endothelial cells is cell contraction causing endothelium permeability increase. The aim was to finding out whether recombinant activated protein C (rhAPC) would reverse the endothelial cell response in an in-vitro sepsis model. In this study, the established in-vitro sepsis model was confirmed by interleukin 6 (IL-6) levels at the proteomic and genomic levels by ELISA, real time-PCR and reactive oxygen species (ROS) activation by florescence staining. The thrombin cellular contraction effect on endothelial cells was used as a positive control when the CellDrum technology was applied. Additionally, the Ras homolog gene family, member A (RhoA) mRNA expression level was checked by real time-PCR to support contractile tension results. According to contractile tension results, the mechanical predominance of actin stress fibers was a reason of the increased endothelial contractile tension leading to enhanced endothelium contractility and thus permeability enhancement. The originality of this data supports firstly the basic measurement principles of the CellDrum technology and secondly that rhAPC has a beneficial effect on sepsis influenced cellular tension. The technology presented here is promising for future high-throughput cellular tension analysis that will help identify pathological contractile tension responses of cells and prove further cell in-vitro models.