Abstract: MicroRNAs (miRNAs) are small oligonucleotides (18-25 bases) that play a key role in epigenetic regulation. Since the discovery of miRNAs in 1993, their role in biological processes has been extensively investigated. By now, it has been evidenced that monitoring and detection of miRNAs can improve (early) disease diagnosis. The existing diagnostic approaches have limitations such as the need for complex multistep protocols for sample preparation, analysis, data interpretation, high cost of equipment, the need for highly qualified personnel, and high laboratory standards. As opposed to this, point-of-care biosensors and chips aim to facilitate the procedure and avoid sending samples into centralized laboratories, which saves time, reduces the chance of sample degradation, and enables analysis of patient samples in remote areas, directly at home or primary and secondary care facilities (i.e. general practitioners and specialists). The latter is essential for therapy assessment and follow-up monitoring of patients with chronic diseases and cancer. Nevertheless, the development of such sensors is lagging compared to the projections of 10 – 20 years ago, mainly due to insufficient sensitivity, poor reproducibility, and the complexity of the sensors’ design reported in the research literature. This motivates the development of new detection strategies and technologies such as photoelectrochemical sensors that combine the best features of different sensing approaches. The primary concern when developing detection technologies for miRNA is the need for a highly sensitive and selective platform. This thesis explores a novel photoelectrochemical (PEC) method that is distinctive owing to its sensitive nature and simple and robust design. Firstly, we focused on the usage of recently emerging commercial gold-sputtered electrode systems for the detection of short nucleic acid with enzymatic amplification. Importantly, cleaning such electrodes is a challenge since the standard procedures known for regular disk electrodes such as polishing cannot be employed here, since it will damage the protective layer on the electrode. However, the electrodes can be washed and pretreated chemically and/or electrochemically. Thus, a procedure to effectively clean and modify the gold-sputtered electrode has been developed, resulting in high-performance gold-sputtered nucleic acid sensors. Next, the usage of molecular photosensitizers as an alternative to enzymatic amplification has been evaluated. We took advantage of the singlet oxygen production by photosensitizers upon photoexcitation, leading to a photocurrent response due to the singlet oxygen-induced (electro)chemical conversions. Following the demonstration of the detection strategy, the analytical performance of the sensing system was evaluated using magnetic beads-based nucleic acid assay on disposable electrode platforms, with a focus to enhance the sensitivity and robustness of the technique in detecting complementary nucleic acid targets. Following the fundamental evaluation of the singlet oxygen-based PEC detection of nucleic acids, we further optimized the assay and measurement parameters and employed the sensing strategy for a polymerase chain reaction-free (PCR-free) quantification of miRNAs related to prostate cancer. By successfully detecting and quantifying low-picomolar range concentrations (< 10 pM) in plasma samples from prostate cancer patients, we successfully showed the applicability of the novel sensing strategy. We have also compared and positioned the performance of our developed PEC strategy with an existing state-of-art technique, i.e. electrochemiluminescence (ECL). Our PEC strategy performed on par with ECL, both yielding low-picomolar detection limits in serum matrices, however quicker and cheaper than ECL. Owing to the versatility of this PEC technique, the final study explored its multiplexing capability. As a starting point in this branch of the research, we have investigated two possible ways for multiplexing. To perform multiple measurements at the same time, constructing calibration plots and quantifying unknown miRNA concentrations in patient samples at the same time, we have developed a high-throughput detection with 96X multi-channel electrode systems and in-house designed and constructed 96XLED illumination sources. Secondly, to detect more than one target miRNA in a single measurement, intra-vial multiplexing where the samples were analyzed for different targets in one vial was also explored. Altogether, this thesis presents the fundamentals, development and application of a novel PEC strategy for detecting short (< 25 bases) nucleic acid sequences, in particular, miRNA. With an aim to serve as a distinctive technique to function as a clinical testing platform without any need for PCR, this work adds value to the development of nucleic acid-based sensors for miRNAs and other short-stranded nucleic acid biomarkers, and benefits in the early detection of diseases like cancer.

Abstract: Novel emerging biorefinery technologies have gained interest and have the potential to tackle several sustainability challenges in our society. A lignin-first biorefinery process – reductive catalytic fractionation (RCF) – is currently under development with the aim to process wood into high-value end-products that replace highly polluting fossil oil-based products. However, such emerging technologies are not matured yet, holding a certain degree of technological, economic, and environmental uncertainty. Hence, an appropriate assessment method is required to assess techno-economic feasibility and environmental impacts of emerging uncertain technologies (e.g lignin-first RCF process). This dissertation aims to develop an integrated techno-environmental economic assessment framework to assess emerging technologies dynamically and prospectively from economic and environmental points of view. First, a techno-economic assessment (TEA) is performed to assess the economic feasibility and the most influential economic and technological parameters of the lignin-first RCF biorefinery taking the whole wood value chain into account. By making the relations across the wood value chain, the scale of the biorefinery, wood species, and output prices highly determine the economic feasibility. The economic feasibility can be reached by a sufficient capacity level which depends on wood species-specific conditions. Also, waste wood proves to be the most profitable feedstock in comparison to virgin wood. Second, an analytical real options analysis (ROA) is performed taking two correlated market uncertainties and the value of flexibility into account to identify the optimal investment decision in an RCF biorefinery. Two different investment options, separated and united investments in harvesting equipment and RCF biorefinery, are analyzed. In both scenarios, market uncertainty postpones the investment. When both investment decisions are united, the probability of investment increases in comparison to separated investments. The study reveals that RCF has the potential to stimulate investments within the wood value chain. Third, a consequential life cycle assessment (LCA) is performed to assess the carbon emissions and the environmental consequences of the lignin-first RCF process and its products. The study reveals that at the current stage RCF products have higher carbon emissions than their alternative counterparts. Several options to improve the environmental performance are discussed such as different RCF technology configurations, targeting different RCF products with the ability to replace higher polluting alternative counterparts on the markets. Other discussion points such as transportation type and the distance, (in-)direct land-use change, the use stage and disposal stages implications, and a more comprehensive environmental view of the RCF products, show the potential to improve the environmental performance of the RCF technology. Overall, the study shows that the RCF process can be environmentally desirable if the appropriate RCF configuration and products are chosen. Finally, the above-mentioned methods – techno-economic assessment, analytical real options analysis, and consequential life cycle assessment – are uniquely integrated within the newly developed integrated assessment framework. The framework has the aim to complement the shortcomings and combine the advantages of all three methods. The framework assesses emerging technologies to give predictive insights about the time-specific economic and environmental performance under the newly developed three threshold conditions: technological readiness, economic feasibility, and environmental desirability. The developed integrated assessment framework assesses dynamically and prospectively the RCF biorefinery implementation under Belgian conditions. It reveals that the economic feasibility increases and carbon emissions decrease over time. The RCF biorefinery fulfills all three threshold conditions – technological readiness, economic feasibility, and environmental desirability – consecutively. The newly developed integrated assessment framework offers decision support to several stakeholders of emerging technologies starting from low technology readiness level (TRL). Practitioners such as the technology developers, researchers, and policymakers can use the framework to evaluate emerging technologies that deal with high levels of technological, economic, and environmental uncertainties. The framework assesses emerging technologies on a detailed level to give decision-makers in-depth insights into the intertwined nature of the technological, economic, and environmental dimensions. It offers insights into the expected time-specific economic and environmental performances, potential, and challenges of the emerging technology to further improve the technology and direct R&Ds along the right path.