Refine
Year of publication
Institute
- Fachbereich Medizintechnik und Technomathematik (9)
- Fachbereich Elektrotechnik und Informationstechnik (7)
- Fachbereich Energietechnik (7)
- IfB - Institut für Bioengineering (7)
- Fachbereich Luft- und Raumfahrttechnik (6)
- Fachbereich Maschinenbau und Mechatronik (5)
- Fachbereich Chemie und Biotechnologie (4)
- INB - Institut für Nano- und Biotechnologien (4)
- Solar-Institut Jülich (1)
Document Type
- Article (24)
- Conference Proceeding (8)
- Part of a Book (6)
- Book (1)
- Conference: Meeting Abstract (1)
Keywords
- MINLP (3)
- Experimental validation (2)
- Process engineering (2)
- Atmospheres (1)
- Biosensor (1)
- Cooling system (1)
- Engineering optimisation (1)
- Engineering optimization (1)
- Exoplanet (1)
- Gas sensor (1)
Persistent infection with the high-risk Human Papillomavirus type 16 (HPV 16) is the causative event for the development of cervical cancer and other malignant tumors of the anogenital tract and of the head and neck. Despite many attempts to develop therapeutic vaccines no candidate has entered late clinical trials. An interesting approach is a DNA based vaccine encompassing the nucleotide sequence of the E6 and E7 viral oncoproteins. Because both proteins are consistently expressed in HPV infected cells they represent excellent targets for immune therapy. Here we report the development of 8 DNA vaccine candidates consisting of differently rearranged HPV-16 E6 and E7 sequences within one molecule providing all naturally occurring epitopes but supposedly lacking transforming activity. The HPV sequences were fused to the J-domain and the SV40 enhancer in order to increase immune responses. We demonstrate that one out of the 8 vaccine candidates induces very strong cellular E6- and E7- specific cellular immune responses in mice and, as shown in regression experiments, efficiently controls growth of HPV 16 positive syngeneic tumors. This data demonstrates the potential of this vaccine candidate to control persistent HPV 16 infection that may lead to malignant disease. It also suggests that different sequence rearrangements influence the immunogenecity by an as yet unknown mechanism.
Persistent infection with high-risk human papillomaviruses (hrHPV) can result in the formation of anogenital cancers. As hrHPV proteins E6 and E7 are required for cancer initiation and maintenance, they are ideal targets for immunotherapeutic interventions. Previously, we have described the development of DNA vaccines for the induction of HPV16 E6 and E7 specific T cell immunity. These vaccines consist of ‘gene-shuffled’ (SH) versions of HPV16 E6 and E7 that were fused to Tetanus Toxin Fragment C domain 1 (TTFC) and were named TTFC-E6SH and TTFC-E7SH. Gene-shuffling was performed to avoid the risk of inducing malignant transformation at the vaccination site. Here, we describe the preclinical safety evaluation of these candidate vaccines by analysis of their transforming capacity in vitro using established murine fibroblasts (NIH 3T3 cells) and primary human foreskin keratinocytes (HFKs). We demonstrate that neither ectopic expression of TTFC-E6SH and TTFC-E7SH alone or in combination enabled NIH 3T3 cells to form colonies in soft agar. In contrast, expression of HPV16 E6WT and E7WT alone or in combination resulted in effective transformation. Similarly, retroviral transduction of HFKs from three independent donors with both TTFC-E6SH and TTFC-E7SH alone or in combination did not show any signs of immortalization. In contrast, the combined expression of E6WT and E7WT induced immortalization in HFKs from all donors. Based on these results we consider it justified to proceed to clinical evaluation of DNA vaccines encoding TTFC-E6SH and TTFC-E7SH in patients with HPV16 associated (pre)malignancies.
Many efforts are made worldwide to establish magnetic fluid hyperthermia (MFH) as a treatment for organ-confined tumors. However, translation to clinical application hardly succeeds as it still lacks of understanding the mechanisms determining MFH cytotoxic effects. Here, we investigate the intracellular MFH efficacy with respect to different parameters and assess the intracellular cytotoxic effects in detail. For this, MiaPaCa-2 human pancreatic tumor cells and L929 murine fibroblasts were loaded with iron-oxide magnetic nanoparticles (MNP) and exposed to MFH for either 30 min or 90 min. The resulting cytotoxic effects were assessed via clonogenic assay. Our results demonstrate that cell damage depends not only on the obvious parameters bulk temperature and duration of treatment, but most importantly on cell type and thermal energy deposited per cell during MFH treatment. Tumor cell death of 95% was achieved by depositing an intracellular total thermal energy with about 50% margin to damage of healthy cells. This is attributed to combined intracellular nanoheating and extracellular bulk heating. Tumor cell damage of up to 86% was observed for MFH treatment without perceptible bulk temperature rise. Effective heating decreased by up to 65% after MNP were internalized inside cells.
Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems.
The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.
Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.
Past earthquakes demonstrated the high vulnerability of industrial facilities equipped with complex process technologies leading to serious damage of the process equipment and multiple and simultaneous release of hazardous substances in industrial facilities. Nevertheless, the design of industrial plants is inadequately described in recent codes and guidelines, as they do not consider the dynamic interaction between the structure and the installations and thus the effect of seismic response of the installations on the response of the structure and vice versa. The current code-based approach for the seismic design of industrial facilities is considered not enough for ensure proper safety conditions against exceptional event entailing loss of content and related consequences. Accordingly, SPIF project (Seismic Performance of Multi- Component Systems in Special Risk Industrial Facilities) was proposed within the framework of the European H2020 - SERA funding scheme (Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe). The objective of the SPIF project is the investigation of the seismic behavior of a representative industrial structure equipped with complex process technology by means of shaking table tests. The test structure is a three-story moment resisting steel frame with vertical and horizontal vessels and cabinets, arranged on the three levels and connected by pipes. The dynamic behavior of the test structure and installations is investigated with and without base isolation. Furthermore, both firmly anchored and isolated components are taken into account to compare their dynamic behavior and interactions with each other. Artificial and synthetic ground motions are applied to study the seismic response at different PGA levels. After each test, dynamic identification measurements are carried out to characterize the system condition. The contribution presents the numerical simulations to calibrate the tests on the prototype, the experimental setup of the investigated structure and installations, selected measurement data and finally describes preliminary experimental results.
The Atmospheric Remote-Sensing Infrared Exoplanet Large-survey, ARIEL, has been selected to be the next (M4) medium class space mission in the ESA Cosmic Vision programme. From launch in 2028, and during the following 4 years of operation, ARIEL will perform precise spectroscopy of the atmospheres of ~1000 known transiting exoplanets using its metre-class telescope. A three-band photometer and three spectrometers cover the 0.5 µm to 7.8 µm region of the electromagnetic spectrum. This paper gives an overview of the mission payload, including the telescope assembly, the FGS (Fine Guidance System) - which provides both pointing information to the spacecraft and scientific photometry and low-resolution spectrometer data, the ARIEL InfraRed Spectrometer (AIRS), and other payload infrastructure such as the warm electronics, structures and cryogenic cooling systems.