A Novel Investigation Method for the S21 Detection Circuit

This research proposes a novel method to investigate the performance of the S21 detection circuit. Aiming at low frequencies or DC, the method serves as an efficient way of verification and enjoys the benefit of low testing costs. The novel investigation method is demonstrated at 50 MHz and verified by the scattering parameters at 11.05 GHz. Based on the investigation, a model of process variations is constructed. The length of the interface paths is estimated by the model to be 63µm, which is consistent with the corresponding length of 74.6µm in the layout. For the measured phase and magnitude, the model indicates that the process variations in the device under test cause errors of 18.91% and 1.27%, whereas those in the interface paths lead to errors of 1.83% and 1%. Based on the model, practical recommendations are also proposed to further improve the measurement precision in the future

Drug development progress in duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a severe, progressive, and incurable X-linked disorder caused by mutations in the dystrophin gene. Patients with DMD have an absence of functional dystrophin protein, which results in chronic damage of muscle fibers during contraction, thus leading to deterioration of muscle quality and loss of muscle mass over time. Although there is currently no cure for DMD, improvements in treatment care and management could delay disease progression and improve quality of life, thereby prolonging life expectancy for these patients. Furthermore, active research efforts are ongoing to develop therapeutic strategies that target dystrophin deficiency, such as gene replacement therapies, exon skipping, and readthrough therapy, as well as strategies that target secondary pathology of DMD, such as novel anti-inflammatory compounds, myostatin inhibitors, and cardioprotective compounds. Furthermore, longitudinal modeling approaches have been used to characterize the progression of MRI and functional endpoints for predictive purposes to inform Go/No Go decisions in drug development. This review showcases approved drugs or drug candidates along their development paths and also provides information on primary endpoints and enrollment size of Ph2/3 and Ph3 trials in the DMD space

Content-aware approach for improving biomedical image analysis: an interdisciplinary study series

Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity

Photon-Upconversion Nanoparticles as Background-Free Luminescent Labels for Immunoanalytical Applications

This thesis builds on photon-upconversion nanoparticles (UCNPs) as background-free luminescent labels in bioaffinity assays using antibodies as recognitions elements. UCNPs are nanocrystals that can absorb two or more near-infrared (NIR) photons and emit light with higher energy (anti-Stokes emission). The NIR excitation drastically reduces the measurement background by avoiding autofluorescence and minimizing light scattering. Together with a high photostability and constant emission (no blinking), UCNPs have become an excellent label for many bioanalytical applications. The aim of this work was to develop UCNP-based assays with the possibility to perform a single-molecule (digital) readout. The first part of the thesis describes the development of immunoassays from a historical perspective and explains the fundamental building blocks needed for affinity assays. Various assay formats are described. The structure, function, and preparation of antibodies is explained. Alternative recognition labels like aptamers and molecularly imprinted polymers (MIPs) are critically discussed, and important label types are examined in detail. Cornerstones in the immunoassay development are highlighted using selected examples from the literature. The definition, advantages, and challenges of digital (single-molecule) affinity assays are discussed with respect to different label types, such as enzymes, small molecular labels, and nanoparticles. The first research article describes the development of an immunoassay for counting individual molecules of the cancer biomarker prostate-specific antigen (PSA) with UCNPs coupled to an anti-PSA antibody. Individual UCNPs bound to a PSA molecule were visualized using a modified epifluorescence microscope that was equipped with a 980 nm-laser. The PSA concentration was determined in a digital way by counting the number of luminescent spots visible in a defined area of the microplate. Synthesis of the detection conjugate was optimized with respect to minimizing the aggregation of the nanoparticles, and the quality was controlled using agarose gel electrophoresis. The digital upconversion-linked immunosorbent assay (ULISA) reached a low limit of detection (LOD) of 1.2 pg/mL (42 fM) and covered three orders of magnitude for PSA spiked in 25% blood serum, which was approximately 10× more sensitive than commercial ELISA kits. It was demonstrated that the digital readout is superior to the conventional analog readout of the same microtiter plate using a plate reader equipped with a 980 nm-laser, which resulted in an LOD of 20.3 pg/mL (700 fM, 17× higher LOD). A combination of both readout methods increased the working range to four orders of magnitude from 1 pg/mL to 10,000 pg/mL. The compatibility with standard microplate assay procedures and the high sensitivity make the ULISA a powerful alternative to existing assays and will have a substantial impact in the future. The second research article focused on the surface modification of UCNPs to reduce non-specific binding, while simultaneously increasing the sensitivity of the PSA detection by exploiting the strong affinity of streptavidin towards biotin. A linker consisting of neridronate, a bisphosphonate that strongly coordinates to lanthanide ions, was chosen to anchor a long polyethylene glycol (PEG) spacer with an incorporated alkyne group at the other end. The alkyne group was used for the covalent immobilization of streptavidin azide onto the UCNPs, via a copper-catalyzed click reaction. Like the ULISA with antibody-UCNP conjugates, the digital ULISA with streptavidin-PEG-UCNPs improved the analog readout by a factor of 16. The strong affinity between biotin and streptavidin led to a 50× higher sensitivity compared to the former assay, which led to a subfemtomolar LOD of 800 aM (~50,000 PSA molecules in 100 µL sample) in 25% blood serum. The results obtained for real patient samples were in excellent agreement with results obtained from a standard method based on electrochemiluminescence (Elecsys, Roche). In Research article 3, the unique photophysical properties of UCNPs were exploited for the immunochemical labeling of a cancer marker on the surface of cells. We demonstrated that UCNP labeling is compatible with standard fluorescence labeling techniques but achieves unsurpassed signal to background ratios. We designed and characterized three different SA-UCNP conjugates and compared the results with a standard fluorescence-based readout using SA conjugated to 5(6)-carboxyfluorescein (SA-FAM). It was found that our previously established SA-PEG-neridronate-UCNPs showed the highest specific binding and, at the same time, the lowest non-specific signal among the three tested SA-UCNP conjugates. The signal-to-background ratio of SA-PEG-neridronate-UCNPs was 319, a 50-fold increase compared to the SA-FAM conjugate (signal to background of 6). Control experiments confirmed the specificity of the UCNP staining. The results demonstrated that UCNPs are a valuable addition to the existing repertoire of immunochemical labeling techniques. Research article 4 focuses on the analysis of enzyme kinetics at the single-molecule level. This research is closely related to the digital immunoassay established by the company Quanterix (Chapter IV.6.2). The conventional transition state theory (TST) is used to analyze and explain the reaction rates of enzymes. However, it does not account for static heterogeneity and dynamic effects in proteins, revealed by single-molecule measurements. We analyzed the reaction rates of individual β-D-galactosidase (GAL) and β-D-glucuronidase (GUS) molecules in large arrays of femtoliter-sized wells, revealing a static heterogeneity. The reaction rate distributions gave access to the intrinsic distributions of the free energy of activation (ΔG‡) of GAL and GUS. A broader distribution of ΔG‡ was found for GAL than for GUS, which is potentially caused by the multiple catalytic reaction pathways of GAL as a hydrolase and transglycosylase. Different catalytic reactions of GAL require more catalytically potent conformations for individual enzyme molecules in the enzyme population compared to GUS. Reaction rates of single enzyme molecules do not change over time (10 min). This indicates that each enzyme molecule has a broader set of conformations than it can access during catalysis. We adapted the TST for these findings by assuming transition state ensembles that can not only drive the enzymatic catalysis but also channel the reaction pathway. The aim of this thesis was to employ UCNPs as labels for highly sensitive immunoassays. With the first two research articles, the digital ULISA was successfully introduced and set the foundation for a new generation of digital immunoassays. It was further shown that UCNPs are exceptional labels for the immunochemical labeling of cells. Especially the low background of the UCNP label could have significant impact on tissue diagnostics in the (near) future

Plasmonics and its Applications

Plasmonics is a rapidly developing field that combines fundamental research and applications ranging from areas such as physics to engineering, chemistry, biology, medicine, food sciences, and the environmental sciences. Plasmonics appeared in the 1950s with the discovery of surface plasmon polaritons. Plasmonics then went through a novel propulsion in the mid-1970s, when surface-enhanced Raman scattering was discovered. Nevertheless, it is in this last decade that a very significant explosion of plasmonics and its applications has occurred. Thus, this book provides a snapshot of the current advances in these various areas of plasmonics and its applications, such as engineering, sensing, surface-enhanced fluorescence, catalysis, and photovoltaic devices

The zebrafish: a preclinical screening model for the optimization of nanomedicine formulations

Nanomedicines are a valuable option to achieve drug accumulation specifically in diseased cells or tissues and therefore reduce side effects. Since the introduction of the revolutionary concept called the magic bullet for such sophisticated treatments more than 100 years ago, a lot of hope and expectations were placed into the field of nanoparticulate drug delivery. Initial forms of nanoparticles such as liposomes were described and extensively characterized which finally resulted in the FDA approval of the first cancer nanomedicine, namely Doxil, in 1996. This early success fueled the already gold-rush like atmosphere and resulted in a huge amount of time and money invested in nanomedicine research and development. As it is often the case for such a much-noticed field of medicinal research, the number of approved and clinically applied nanomedicines was not able to keep up with the unrealistic expectations resulting from the exponential increase of nanomedicine related publications. This triggered a lot of criticism questioning basic principles such as the enhanced permeability and retention effect or even the general use of nanomedicines. Despite the fact that the raised points are legitimate to a certain degree, the field of nanomedicine is far away from suffering from a general crisis, underlined by the steadily (but slowly) increasing number of approved formulations. Nevertheless, it cannot be denied that nanomedicine development is a cumbersome process suffering from a lot of drop-outs during very early phases of clinical trials. Among other things, this is due to the fact that formulation design and optimization is mainly based on in vitro studies, which are not able to fully mimic complex biological conditions. Moreover, only a selected number of formulations can subsequently be assessed in rodent in vivo experiments, since such studies are expensive, time consuming and suffer from ethical concerns. Obviously, there is a huge gap between in vitro cell culture and rodent in vivo studies, which makes the selection of potentially successful nanomedicine formulations extremely difficult. In addition, this situation does not allow a thorough formulation design and optimization under complex biological conditions and hampers a detailed understanding of basic nanomedicine interactions with biological environments at a macromolecular level. Therefore, this PhD thesis aimed to introduce the zebrafish as a complementary and easy accessible in vivo model in order to bridge the gap between in vitro and rodent in vivo studies during nanomedicine development. In the first part (Chapters I-I to III-I), the current nanomedicine development process prior to rodent in vivo studies was reviewed and the zebrafish model was set-up, validated, and further characterized. Briefly, already described formulation effects on nanomedicine pharmacokinetics were reproduced and the predictive power of the zebrafish model system was verified. Thereby, a special focus was put on two main nanomedicine clearance mechanisms, namely phagocytosis by macrophages as a part of the mononuclear phagocytic system and scavenger receptors expressed on cells, which belong to the reticuloendothelial system. Based on the successful completion of the first part, the zebrafish model was used for the development of sophisticated nanoparticulate delivery systems (Chapter IV). For example, the optimal ligand density for an actively targeted nanoparticle was established in the zebrafish model and verified in a subsequent rodent biodistribution experiment. In addition, two different nanoparticle-enzyme systems were tested regarding their stability, biocompatibility, and functionality in this living biological system, i.e. zebrafish. During this thesis, general advantages of the zebrafish model such as large clutch size, optical transparency, availability of many transgenic lines, the possibility to screen a large number of formulations, and relatively low regulatory requirements became evident. All parameters were adapted to the purpose of nanomedicine formulation design and optimization. The promising findings will be further pursued in detailed follow-up studies regarding the development of an accurate and quantitative pharmacokinetic model, the elucidation of exact formulation dependent nanomedicine cell uptake and trafficking mechanisms under in vivo conditions, or to support the formulation design and optimization of nanomedicines for infectious diseases. Altogether, the presented zebrafish model showed to be a valuable and promising tool for several applications in the field of nanomedicine development and will hopefully foster the successful translation of further nanomedicines from bench to bedside