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Characterisation of porous knitted titanium for replacement of intervertebral disc nucleus pulposus
(2017)
Effective restoration of human intervertebral disc degeneration is challenged by numerous limitations of the currently available spinal fusion and arthroplasty treatment strategies. Consequently, use of artificial biomaterial implant is gaining attention as a potential therapeutic strategy. Our study is aimed at investigating and characterizing a novel knitted titanium (Ti6Al4V) implant for the replacement of nucleus pulposus to treat early stages of chronic intervertebral disc degeneration. Specific knitted geometry of the scaffold with a porosity of 67.67 ± 0.824% was used to overcome tissue integration failures. Furthermore, to improve the wear resistance without impairing original mechanical strength, electro-polishing step was employed. Electro-polishing treatment changed a surface roughness from 15.22 ± 3.28 to 4.35 ± 0.87 μm without affecting its wettability which remained at 81.03 ± 8.5°. Subsequently, cellular responses of human mesenchymal stem cells (SCP1 cell line) and human primary chondrocytes were investigated which showed positive responses in terms of adherence and viability. Surface wettability was further enhanced to super hydrophilic nature by oxygen plasma treatment, which eventually caused substantial increase in the proliferation of SCP1 cells and primary chondrocytes. Our study implies that owing to scaffolds physicochemical and biocompatible properties, it could improve the clinical performance of nucleus pulposus replacement.
A wide variety of cell types exhibit substrate topography-based behavior, also known as contact guidance. However, the precise cellular mechanisms underlying this process are still unknown. In this study, we investigated contact guidance by studying the reaction of human endothelial cells (ECs) to well-defined microgroove topographies, both during and after initial cell spreading. As the cytoskeleton plays a major role in cellular adaptation to topographical features, two methods were used to perturb cytoskeletal structures. Inhibition of actomyosin contractility with the chemical inhibitor blebbistatatin demonstrated that initial contact guidance events are independent of traction force generation. However, cell alignment to the grooved substrate was altered at later time points, suggesting an initial ‘passive’ phase of contact guidance, followed by a contractility-dependent ‘active’ phase that relies on mechanosensitive feedback. The actin cytoskeleton was also perturbed in an indirect manner by culturing cells upside down, resulting in decreased levels of contact guidance and suggesting that a possible loss of contact between the actin cytoskeleton and the substrate could lead to cytoskeleton impairment. The process of contact guidance at the microscale was found to be primarily lamellipodia driven, as no bias in filopodia extension was observed on micron-scale grooves.
Intermediate filament reorganization dynamically influences cancer cell alignment and migration
(2017)
The interactions between a cancer cell and its extracellular matrix (ECM) have been the focus of an increasing amount of investigation. The role of the intermediate filament keratin in cancer has also been coming into focus of late, but more research is needed to understand how this piece fits in the puzzle of cytoskeleton-mediated invasion and metastasis. In Panc-1 invasive pancreatic cancer cells, keratin phosphorylation in conjunction with actin inhibition was found to be sufficient to reduce cell area below either treatment alone. We then analyzed intersecting keratin and actin fibers in the cytoskeleton of cyclically stretched cells and found no directional correlation. The role of keratin organization in Panc-1 cellular morphological adaptation and directed migration was then analyzed by culturing cells on cyclically stretched polydimethylsiloxane (PDMS) substrates, nanoscale grates, and rigid pillars. In general, the reorganization of the keratin cytoskeleton allows the cell to become more ‘mobile’- exhibiting faster and more directed migration and orientation in response to external stimuli. By combining keratin network perturbation with a variety of physical ECM signals, we demonstrate the interconnected nature of the architecture inside the cell and the scaffolding outside of it, and highlight the key elements facilitating cancer cell-ECM interactions.
Cell-cell and cell-extracellular matrix (ECM) adhesion regulates fundamental cellular functions and is crucial for cell-material contact. Adhesion is influenced by many factors like affinity and specificity of the receptor-ligand interaction or overall ligand concentration and density. To investigate molecular details of cell ECM and cadherins (cell-cell) interaction in vascular cells functional nanostructured surfaces were used Ligand-functionalized gold nanoparticles (AuNPs) with 6-8 nm diameter, are precisely immobilized on a surface and separated by non-adhesive regions so that individual integrins or cadherins can specifically interact with the ligands on the AuNPs. Using 40 nm and 90 nm distances between the AuNPs and functionalized either with peptide motifs of the extracellular matrix (RGD or REDV) or vascular endothelial cadherins (VEC), the influence of distance and ligand specificity on spreading and adhesion of endothelial cells (ECs) and smooth muscle cells (SMCs) was investigated. We demonstrate that RGD-dependent adhesion of vascular cells is similar to other cell types and that the distance dependence for integrin binding to ECM-peptides is also valid for the REDV motif. VEC-ligands decrease adhesion significantly on the tested ligand distances. These results may be helpful for future improvements in vascular tissue engineering and for development of implant surfaces.
Within the scope of the present cumulative doctoral thesis six scientific papers were published which illustrates that modern reaction model-free (=isoconversional) kinetic analysis (ICKA) methods represents a universal and effective tool for the controlled processing of thermosetting materials. In order to demonstrate the universal applicability of ICKA methods, the thermal cure of different thermosetting materials having a very broad range of chemical composition (melamine-formaldehyde resins, epoxy resins, polyester-epoxy resins, and acrylate/epoxy resins) were analyzed and mathematically modelled. Some of the materials were based on renewable resources (an epoxy resin was made from hempseed oil; linseed oil was modified into an acrylate/epoxy resin). With the aid of ICKA methods not only single-step but also complex multi-step reactions were modelled precisely. The analyzed thermosetting materials were combined with wood, wood-based products, paper, and plant fibers which are processed to various final products. Some of the thermosetting materials were applied as coating (in form of impregnated décor papers or powder and wet coatings respectively) on wood substrates and the epoxy resin from hempseed oil was mixed with plant fibers and processed into bio-based composites for lightweight applications. From the final products mechanical, thermal, and surface properties were determined. The activation energy as function of cure conversion derived from ICKA methods was utilized to predict accurately the thermal curing over the course of time for arbitrary cure conditions. Furthermore the cure models were used to establish correlations between the cross-linking during processing into products and the properties of the final products. Therewith it was possible to derive the process time and temperature that guarantee optimal cross-linking as well as optimal product properties
The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology.