Abstract: In this work, we take a crucial step towards the industrial readiness of plasma-based CO2 conversion. We present a stepwise method to study plasma reactors in series as a first approach to a recycle flow. By means of this procedure, the CO2 conversion is enhanced by a factor of 3, demonstrating that a single-pass plasma treatment performs far below the optimal capacity of the reactor. Furthermore, we explore the effect of O2 in the mixture with our flexible procedure. Addition of O2 in the mixture has a clear detrimental effect on the conversion, in agreement with other experiments in atmospheric pressure plasmas. O2 removal is however highly beneficial, demonstrating a conversion per pass that is 1.6 times higher than the standard procedure. Indeed, extracting one of the products prevents recombination reactions. Based on these insights, we discuss opportunities for further improvements, especially in the field of specialised separation techniques.

Abstract: Cold atmospheric plasma and nanomedicine originally emerged as individual domains, but are increasingly applied in combination with each other. Most research is performed in the context of cancer treatment, with only little focus yet on the possible synergies. Many questions remain on the potential of this promising hybrid technology, particularly regarding regenerative medicine and tissue engineering. In this perspective article, we therefore start from the fundamental mechanisms in the individual technologies, in order to envision possible synergies for wound healing and tissue recovery, as well as research strategies to discover and optimize them. Among these strategies, we demonstrate how cold plasmas and nanomaterials can enhance each other’s strengths and overcome each other’s limitations. The parallels with cancer research, biotechnology and plasma surface modification further serve as inspiration for the envisioned synergies in tissue regeneration. The discovery and optimization of synergies may also be realized based on a profound understanding of the underlying redox- and field-related biological processes. Finally, we emphasize the toxicity concerns in plasma and nanomedicine, which may be partly remediated by their combination, but also partly amplified. A widespread use of standardized protocols and materials is therefore strongly recommended, to ensure both a fast and safe clinical implementation.

Abstract: Natural deep eutectic solvents (NADES) represent a green alternative to common organic solvents in the biochemical industry due to their benign behavior and tailorable properties, in particular as media for enzymatic reactions. However, to fully exploit their potential in enzymatic reactions, there is a need for a more fundamental understanding of how these neoteric solvents influence the course of these reac-tions. Thus, the aim of this study is to investigate the influence of NADES with various molar composi-tions on the stability and structure of enzymes, applying molecular dynamics simulations. This can help to better understand the effect of individual compounds of NADES, in addition to eutectic mixtures. More specifically, we simulate the behavior of Candida antarctica lipase B (CALB) enzyme in NADES com-posed of choline chloride with either urea, ethylene glycol or glycerol. Hereto, we monitor the NADES microstructure, the general stability of the enzyme and changes in the structure of its active sites and sur-face residues. Our simulations show that none of the studied NADES systems significantly disrupt the microstructure of the solvent or the stability of the CALB enzyme within the time scales of the simula-tions. The enzyme preserves its initial structure, size and intra-chain hydrogen bonds in all investigated compositions and, for the first time reported, also in NADES with increased hydrogen bond donating com-pound ratios. As the main novelty, our results indicate that, in addition to the composition, the molar ratio can be an additional variable to fine-tune the physicochemical properties of NADES without altering the enzyme characteristics. These findings could facilitate the development and application of task -tailored NADES media for biocatalytic processes. (c) 2022 Elsevier B.V. All rights reserved.

Abstract: We studied the use of low current (hundreds of milliamperes) gliding arc/glow discharges for CO2 dissociation, at atmospheric pressure, in three different configurations. All of these are based on the gliding arc design with flat diverging electrodes. The discharge is mainly in the normal glow regime with contracted positive column. The CO2 gas is injected from a nozzle, at the closest separation between the electrodes. A pair of quartz glasses is placed on both sides of the electrodes, so that the gas flow is restricted to the active plasma area, between the electrodes. For two of the tested configurations, an external magnetic field was applied, to create a magnetic force, both in the direction of the gas flow, and opposite to the gas flow. In the first case, the arc is accelerated, shortening the period between ignition and extinction, while in the second case, it is stabilized (magneticallystabilized). We studied two quantities, namely the CO2 conversion and the energy efficiency of the conversion. Generally, the CO2 conversion decreases with increasing flow rate and increases with power. The energy effi­ciency increases with the flow rate, for all configurations. The magnetically-stabilized configuration is more stable and efficient at low gas flow rates, but has poor performance at high flow rates, while the non-stabilized configurations exhibit good conversion for a larger range of flow rates, but they are generally more unstable and less efficient.

Abstract: Low temperature plasmas (LTPs) enable to create a highly reactive environment at near ambient temperatures due to the energetic electrons with typical kinetic energies in the range of 1 to 10 eV (1 eV = 11600K), which are being used in applications ranging from plasma etching of electronic chips and additive manufacturing to plasma-assisted combustion. LTPs are at the core of many advanced technologies. Without LTPs, many of the conveniences of modern society would simply not exist. New applications of LTPs are continuously being proposed. Researchers are facing many grand challenges before these new applications can be translated to practice. In this paper, we will discuss the challenges being faced in the field of LTPs, in particular for atmospheric pressure plasmas, with a focus on health, energy and sustainability.

Abstract: With climate change still a pressing issue, there is a great need for carbon capture, utilisation and storage (CCUS)
methods. We propose a novel concept where CO2 conversion is accomplished by O2 splitting followed by the
addition of O atoms to CO2. The latter is studied here by means of kinetic modelling. In the first instance, we
study various CO2/O ratios, and we observe an optimal CO2 conversion of around 30–40% for 50% O addition.
Gas temperature also has a large influence, with a minimum temperature of around 1000 K to a maximum of
2000 K for optimal conversion. In the second instance, we study various CO2/O/O2 ratios, due to O2 being a
starting gas. Also here we define optimal regions for CO2 conversion, which reach maximum conversion for a
CO2 fraction of 50% and an O/O2 ratio bigger than 1. Those can be expanded by heating on one hand, for low
atomic oxygen availability, and by quenching after reaction on the other hand, for cases where the temperatures
are too high. Our model predictions can serve as a guideline for experimental research in this domain.

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: This study hypothesizes that the application of low-dose nonthermal biocompatible dielectric barrier discharge plasma (DBD-NBP) to human gingival fibroblasts (HGFs) will inhibit colony formation but not cell death and induce matrix metalloproteinase (MMP) expression, extracellular matrix (ECM) degradation, and subsequent cell migration, which can result in enhanced wound healing. HGFs treated with plasma for 3 min migrate to each other across the gap faster than those in the control and 5-min treatment groups on days 1 and 3. The plasma-treated HGFs show significantly high expression levels of the cell cycle arrest-related p21 gene and enhanced MMP activity. Focal adhesion kinase (FAK) mediated attenuation of wound healing or actin cytoskeleton rearrangement, and plasma-mediated reversal of this attenuation support the migratory effect of DBD-NBP. Further, this work performs computer simulations to investigate the effect of oxidation on the stability and conformation of the catalytic kinase domain (KD) of FAK. It is found that the oxidation of highly reactive amino acids (AAs) Cys427, Met442, Cys559, Met571, Met617, and Met643 changes the conformation and increases the structural flexibility of the FAK protein and thus modulates its function and activity. Low-dose DBD-NBP-induces host cell cycle arrest, ECM breakdown, and subsequent migration, thus contributing to the enhanced wound healing process.

Abstract: The Quantemol database (QDB) provides cross sections and rates of processes important for plasma models; heavy particle collisions (chemical reactions) and electron collision processes are considered. The current version of QDB has data on 28 917 processes between 2485 distinct species plus data for surface processes. These data are available via a web interface or can be delivered directly to plasma models using an application program interface; data are available in formats suitable for direct input into a variety of popular plasma modeling codes including HPEM, COMSOL, ChemKIN, CFD-ACE+, and VisGlow. QDB provides ready assembled plasma chemistries plus the ability to build bespoke chemistries. The database also provides a Boltzmann solver for electron dynamics and a zero-dimensional model. Thesedevelopments, use cases involving O₂, Ar/NF₃, Ar/NF₃/O₂, and He/H₂O/O₂chemistries, and plans for the future are presented.

Abstract: To gain insights into the underlying mechanisms of NTP therapy sensitivity and resistance, using the firstever
NTP-resistant cell line derived from sensitive melanoma cells (A375).
Methods: Melanoma cells were exposed to NTP and re-cultured for 12 consecutive weeks before evaluation
against the parental control cells. Whole transcriptome sequencing analysis was performed to identify differentially
expressed genes and enriched molecular pathways. Glucose uptake, extracellular lactate, media acidification,
and mitochondrial respiration was analyzed to determine metabolic changes. Cell death inhibitors were
used to assess the NTP-induced cell death mechanisms, and apoptosis and ferroptosis was further validated via
Annexin V, Caspase 3/7, and lipid peroxidation analysis.
Results: Cells continuously exposed to NTP became 10 times more resistant to NTP compared to the parental cell
line of the same passage, based on their half-maximal inhibitory concentration (IC50). Sequencing and metabolic
analysis indicated that NTP-resistant cells had a preference towards aerobic glycolysis, while cell death analysis
revealed that NTP-resistant cells exhibited less apoptosis but were more vulnerable to lipid peroxidation and
ferroptosis.
Conclusions: A preference towards aerobic glycolysis and ferroptotic cell death are key physiological changes in
NTP-resistance cells, which opens new avenues for further, in-depth research into other cancer types.

Abstract: Since its discovery 20 years ago, many studies have been performed to gain insight into the functional role of cytoglobin (Cygb). However, Cygb has been proven to be a promiscuous protein. Yet, there is a consensus that Cygb is a cytoprotective protein involved in redox homeostasis. CYGB is a ubiquitously expressed hexacoordinated globin that is highly expressed in melanocytes and is often found to be downregulated during melanocyte-to-melanoma transition. In Chapter III, we investigated the molecular mechanism through which CYGB could be involved in redox regulation. Here, we showed that CYGB contains two redox-sensitive cysteine residues and that the formation of an intramolecular disulfide bridge resulted in the heme group becoming more accessible to external ligands. This supports the hypothesis that Cys38 and Cys83 serve as sensitive redox sensors. In Chapter IV we showed that CYGB mRNA and protein levels were elevated upon exposure to hypoxia. Interestingly, this upregulation was most likely HIF-2α-dependent. We propose that in melanoma, HIF-2α, rather than HIF-1α, positively regulates CYGB under hypoxic conditions in a cell type specific way. In Chapter V, the cytotoxic effect of indirect NTP treatment in two melanoma cell lines with divergent endogenous CYGB expression levels was investigated. We confirmed that NTP endows cytotoxicity that induces cell death through apoptosis and that this was mediated through the production of ROS. Moreover, we showed that CYGB protects melanoma cells from ROS-induced apoptosis by the scavenging of ROS. Interestingly, CYGB expression influenced the expression of NRF2 and HO-1. We identified the lncRNA MEG3 as a possible mechanism through which NRF2 expression and its downstream target HO-1 can be regulated by CYGB. In chapter VI, increased basal ROS levels and higher degree of lipid peroxidation upon RSL3 treatment contributed to the increased sensitivity of CYGB knockdown G361 cells to ferroptosis. Furthermore, transcriptome analysis demonstrates the enrichment of multiple cancer malignancy pathways upon CYGB knockdown, supporting a tumor-suppressive role for CYGB. Remarkably, CYGB expression regulation was identified as a critical determinant of the ferroptosis–pyroptosis therapy response. This suggests that CYGB is involved in the regulation of multiple modes of programmed cell death. FInally, we sought to delineate the RONS that are responsible for plasma-induced ICD. Our results highlight the importance of the short-lived species. Furthermore, we are first to demonstrate that NTP-created vaccine is safely prepared and offers complete protection. Moreover, we provide conclusive evidence that direct application of NTP induces ICD in melanoma.

Abstract: Plasma-based nitrogen fixation for fertilizer production is an attractive alternative to the fossil fuel-based industrial processes. However, many factors hinder its applicability, e.g., the commonly observed inverse correlation between energy consumption and production rates or the necessity to enhance the selectivity toward NO2, the desired product for a more facile formation of nitrate-based fertilizers. In this work, we investigated the use of a rotating gliding arc plasma for nitrogen fixation at elevated pressures (up to 3 barg), at different feed gas flow rates and composition. Our results demonstrate a dramatic increase in the amount of NOx produced as a function of increasing pressure, with a record-low EC of 1.8 MJ/(mol N) while yielding a high production rate of 69 g/h and a high selectivity (94%) of NO2. We ascribe this improvement to the enhanced thermal Zeldovich mechanism and an increased rate of NO oxidation compared to the back reaction of NO with atomic oxygen, due to the elevated pressure.

Abstract: 200 years ago, humanity started the industrial revolution by discovering fossil fuels, which lead to unprecedented technological advancements. However it has become alarmingly clear that the major environmental concerns associated with fossil fuels require a short-term transition from a carbon-based energy economy to a sustainable one based on green electricity. A key step concerning this transition exists in developing electricity-driven alternatives for chemical processes that rely on fossil fuels as a raw material. A technology that is gaining increasing interest to achieve this, is plasma technology. Using plasmas to induce chemical reactions by selectively heating electrons in a gas has already delivered promising results for gas conversion applications like CO2 conversion and N2 fixation, but plasma reactors still require optimization to be considered industrially competitive to existing fossil fuel-based processes and emerging other electricity-based technologies. In this thesis I develop computational models to describe plasma reactors and identify key mechanisms in three different plasma reactors for three different gas conversion applications, i.e. N2 fixation, combined CO2-CH4 conversion and CO2 splitting. I first developed models to describe a new rotating gliding arc (GA) reactor operating in two arc modes, which, as revealed by my model, are characterized by distinct plasma chemistry pathways. Subsequently, my colleague and I study the quenching effect of an effusion nozzle to this rotating GA reactor, reaching the best results to date for N2 fixation into NOx at atmospheric pressure, i.e., NOx concentrations up to 5.9%, at an energy cost down to 2.1 MJ/mol. Afterwards, I investigate the possible improvement of N2 admixtures in plasma-based CO2 and CH4 conversion, as significant amounts of N2 are often found in industrial CO2 waste streams, and gas separations are financially costly. Through combining my models with the experiment from a fellow PhD student, we reveal that moderate amounts of N2 (i.e. around 20%) increase both the electron density and the gas temperature to yield an overall energy cost reduction of 21%. Finally, I model quenching nozzles for plasma-based CO2 conversion in a microwave reactor, to explain the enhancements in CO2 conversion that were demonstrated in experiments. Through computational modelling I reveal that the nozzle introduces fast gas quenching resulting in the suppression of recombination reactions, which have more impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: Natural deep eutectic solvents (NADES) show great promise as media for enzymatic reactions in areas where (bio)compatibility with natural or medicinal products is a must. While in theory they can be tailored to the intended reaction to ensure optimized yields, the knowledge to date is predominantly empirical, with some mechanistic reports providing a fragmented view at best. Therefore, it is not easy to explain experimental observations, let alone make predictions. The aim of this study was to develop a structured, holistic understanding of the effects of NADES media on enzymatic reactions, distinguishing between effects on solubility, solvation, viscosity, inhibition and denaturation. Experimental and computational chemistry methods were combined to separately study the interactions between enzyme, substrate, and NADES as reaction media. The initial enzyme activity and the final conversion of vinyl laurate transesterification by immobilized Candida antarctica lipase were studied experimentally. The direct effect of NADES on the same enzyme was modeled by molecular dynamics simulation. The effect of solubility was studied by both experimental and computational methods. To predict the solubility and viscosity of NADES, data-driven models were developed by combining group contribution and machine learning methods, based on the accumulated experimental knowledge on NADES found in the literature. Finally, the composed relationships and prediction models were applied to the practical example of deacetylation of mannosylerythritol lipids (MELs). The experimental findings show that the chosen NADES system has a significant effect on both the apparent initial activity and the final conversion. However, in the simulations, the enzyme retains its original structure; moreover, NADES has an additional stabilizing effect on the enzyme. In addition, changes in the molar ratio of the compounds in NADES do not show a significant effect on the stability of the enzyme. These results indicate that the main effect of NADES on the reaction is mainly related to the substrate-solvent interactions (solvation energy) and the viscosity of the system. On the other hand, the experimental results only confirmed the significance of solvation, viscosity did not show a clear correlation with the studied reaction parameters. The machine learning models built for solubility and viscosity gave quantitative predictions of these properties. The accumulated knowledge was used to optimize the yield in the deacetylation reaction of MELs. The combination of these methods provides fundamental knowledge about the effect of NADES on biocatalysis, but the results are also applicable to other uses of NADES.