Abstract: Many current anti-cancer therapies rely on increasing the intracellular reactive oxygen and nitrogen species (RONS) contents with the aim to induce irreparable damage, which subsequently results in tumor cell death. A novel tool in cancer therapy is the use of cold atmospheric plasma (CAP), which has been found to be very effective in the treatment of many different cancer cell types in vitro as well as in vivo, mainly through the vast generation of RONS. One of the key determinants of the cell's fate will be the interaction of RONS, generated by CAP, with important proteins, i.e. redox-regulatory proteins. One such protein is cytoglobin (CYGB), a recently discovered globin proposed to be involved in the protection of the cell against oxidative stress. In this study, the effect of plasma-produced RONS on CYGB was investigated through the treatment of CYGB with CAP for different treatment times. Spectroscopic analysis of CYGB showed that although chemical modifications occur, its secondary structure remains intact. Mass spectrometry experiments identified these modifications as oxidations of mainly sulfur-containing and aromatic amino acids. With longer treatment time, the treatment was also found to induce nitration of the heme. Furthermore, the two surface-exposed cysteine residues of CYGB were oxidized upon treatment, leading to the formation of intermolecular disulfide bridges, and potentially also intramolecular disulfide bridges. In addition, molecular dynamics and docking simulations confirmed, and further show, that the formation of an intramolecular disulfide bond, due to oxidative conditions, affects the CYGB 3D structure, thereby opening the access to the heme group, through gate functioning of His117. Altogether, the results obtained in this study (1) show that plasma-produced RONS can extensively oxidize proteins and (2) that the oxidation status of two redox-active cysteines lead to different conformations of CYGB.

Abstract: Non-thermal plasma (NTP) therapy has been emerging as a promising cancer treatment strategy, and recently, its ability to locally induce immunogenic cancer cell death is being unraveled. We hypothesized that the chemical species produced by NTP reduce immunosuppressive surface proteins and checkpoints that are overexpressed on cancerous cells. Here, 3D in vitro tumor models, an in vivo mouse model, and molecular dynamics simulations are used to investigate the effect of NTP on CD47, a key innate immune checkpoint. CD47 is immediately modulated after NTP treatment and simulations reveal the potential oxidized salt-bridges responsible for conformational changes. Umbrella sampling simulations of CD47 with its receptor, signal-regulatory protein alpha (SIRPα), demonstrate that the induced-conformational changes reduce its binding affinity. Taken together, this work provides new insight into fundamental, chemical NTP-cancer cell interaction mechanisms and a previously overlooked advantage of present NTP cancer therapy: reducing immunosuppressive signals on the surface of cancer cells.

Abstract: Background Excessive maternal pre-pregnancy and gestational weight gain are related to pregnancy- and birth outcomes. The interpregnancy time window offers a unique opportunity to intervene in order to acquire a healthy lifestyle before the start of a new pregnancy. Methods INTER-ACT is an e-health driven multicentre randomised controlled intervention trial targeting women at high risk of pregnancy- and birth related complications. Eligible women are recruited for the study at day 2 or 3 postpartum. At week 6 postpartum, participants are randomised into the intervention or control arm of the study. The intervention focuses on weight, diet, physical activity and mental well-being, and comprises face-to-face coaching, in which behavioural change techniques are central, and use of a mobile application, which is Bluetooth-connected to a weighing scale and activity tracker. The intervention is rolled out postpartum (4 coaching sessions between week 6 and month 6) and in a new pregnancy (3 coaching sessions, one in each trimester of pregnancy); the mobile app is used throughout the two intervention phases. Data collection includes data from the medical record of the participants (pregnancy outcomes and medical history), anthropometric data (height, weight, waist- and hip circumferences, skinfold thickness and body composition by bio-electrical impedance analysis), data from the mobile app (physical activity and weight; intervention group only) and questionnaires (socio-demographics, breastfeeding, food intake, physical activity, lifestyle, psychosocial factors and process evaluation). Medical record data are collected at inclusion and at delivery of the subsequent pregnancy. All other data are collected at week 6 and month 6 postpartum and every subsequent 6 months until a new pregnancy, and in every trimester in the new pregnancy. Primary outcome is the composite endpoint score of pregnancy-induced hypertension, gestational diabetes mellitus, caesarean section, and large-for-gestational-age infant in the subsequent pregnancy.

Abstract: Tumours are complex systems formed by cellular (malignant, immune, and endothelial cells, fibroblasts) and acellular components (extracellular matrix (ECM) constituents and secreted factors). A close interplay between these factors, collectively called the tumour microenvironment, is required to respond appropriately to external cues and to determine the treatment outcome. Cold plasma (here referred as ‘plasma’) is an emerging anticancer technology that generates a unique cocktail of reactive oxygen and nitrogen species to eliminate cancerous cells via multiple mechanisms of action. While plasma is currently regarded as a local therapy, it can also modulate the mechanisms of cell-to-cell and cell-to-ECM communication, which could facilitate the propagation of its effect in tissue and distant sites. However, it is still largely unknown how the physical interactions occurring between cells and/or the ECM in the tumour microenvironment affect the plasma therapy outcome. In this review, we discuss the effect of plasma on cell-to-cell and cell-to-ECM communication in the context of the tumour microenvironment and suggest new avenues of research to advance our knowledge in the field. Furthermore, we revise the relevant state-of-the-art in three-dimensional in vitro models that could be used to analyse cell-to-cell and cell-to-ECM communication and further strengthen our understanding of the effect of plasma in solid tumours.

Abstract: The treatment of a well plate by an atmospheric pressure plasma jet is common for<italic>in vitro</italic>plasma medicine research. Here, reactive species are largely produced through the mixing of the jet effluent with the surrounding atmosphere. This mixing can be influenced not only by the ambient conditions, but also by the geometry of the treated well. To limit this influence and control the atmosphere, a shielding gas is sometimes applied. However, the interplay between the gas shield and the well geometry has not been investigated. In this work, we developed a 2D-axisymmetric computational fluid dynamics model of the kINPen plasma jet, to study the mixing of the jet effluent with the surrounding atmosphere, with and without gas shield. Our computational and experimental results show that the choice of well type can have a significant influence on the effluent conditions, as well as on the effectiveness of the gas shield. Furthermore, the geometry of the shielding gas device can substantially influence the mixing as well. Our results provide a deeper understanding of how the choice of setup geometry can influence the plasma treatment, even when all other operating parameters are unchanged.

Abstract: Despite modern therapeutic advances, the survival prospects of pancreatic cancer patients remain poor, due to chemoresistance and dysregulated oncogenic kinase signaling networks. We applied a novel kinome activitymapping approach using biological peptide targets as phospho-sensors to identify vulnerable kinase de­pendencies for therapy sensitization by physical plasma. Ser/Thr-kinome specific activity changes were mapped upon induction of ferroptotic cell death in pancreatic tumor cells exposed to reactive oxygen and nitrogen species of plasma-treated water (PTW). This revealed a broad kinome activity response involving the CAMK, the AGC and CMGC family of kinases. This systems-level kinome network response supports stress adaptive switches between chemoresistant anti-oxidant responses of Kelch-like ECH-associated protein 1 (KEAP1)/Heme Oxy­genase 1 (HMOX1) and ferroptotic cell death sensitization upon suppression of Nuclear factor (erythroid derived 2)-like 2 (NRF2) and Glutathione peroxidase 4 (GPX4). This is further supported by ex vivo experiments in the chicken chorioallantoic membrane assay, showing decreased GPX4 and Glutathione (GSH) expression as well as increased lipid peroxidation, along with suppressed BxPC-3 tumor growth in response to PTW. Taken all together, we demonstrate that plasma treated water-derived oxidants sensitize pancreatic cancer cells to fer­roptotic cell death by targeting a NRF2-HMOX1-GPX4 specific kinase signaling network.

Abstract: Multiple cancer therapies nowadays rely on oxidative stress to damage cancer cells. Here we investigated the biological and molecular effect of oxidative stress on the interaction between CD44 and hyaluronan (HA), as interrupting their binding can hinder cancer progression. Our experiments demonstrated that the oxidation of HA decreased its recognition by CD44, which was further enhanced when both CD44 and HA were oxidized. The reduction of CD44–HA binding negatively affected the proliferative state of cancer cells. Our multi-level atomistic simulations revealed that the binding free energy of HA to CD44 decreased upon oxidation. The effect of HA and CD44 oxidation on CD44–HA binding was similar, but when both HA and CD44 were oxidized, the effect was much larger, in agreement with our experiments. Hence, our experiments and computations support our hypothesis on the role of oxidation in the disturbance of CD44–HA interaction, which can lead to the inhibition of proliferative signaling pathways inside the tumor cell to induce cell death.

Abstract: Gap junctions (GJs), essential structures for cell-cell communication, are made of two hemichannels (commonly called connexons), one on each adjacent cell. Found in almost all cells, GJs play a pivotal role in many physi­ological and cellular processes, and have even been linked to the progression of diseases, such as cancer. Modulation of GJs is under investigation as a therapeutic strategy to kill tumor cells. Furthermore, GJs have also been studied for their key role in activating anti-cancer immunity and propagating radiation- and oxidative stress-induced cell death to neighboring cells, a process known as the bystander effect. While, gap junction (GJ)based therapeutic strategies are being developed, one major challenge has been the paradoxical role of GJs in both tumor progression and suppression, based on GJ composition, cancer factors, and tumoral context. Therefore, understanding the mechanisms of action, regulation, and the dual characteristics of GJs in cancer is critical for developing effective therapeutics. In this review, we provide an overview of the current under­ standing of GJs structure, function, and paradoxical pro- and anti-tumoral role in cancer. We also discuss the treatment strategies to target these GJs properties for anti-cancer responses, via modulation of GJ function.

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: In this study we report on a 2D fluid model of a gliding arc discharge in argon. Despite the 3D nature of the discharge, 2D models are found to be capable of providing very useful information about the operation of the discharge. We employ two modelsan axisymmetric and a Cartesian one. We show that for the considered experiment and the conditions of a low current arc (around 30 mA) in argon, there is no significant heating of the cathode surface and the discharge is sustained by field electron emission from the cathode accompanied by the formation of a cathode spot. The obtained discharge power and voltage are relatively sensitive to the surface properties and particularly to the surface roughness, causing effectively an amplification of the normal electric field. The arc body and anode region are not influenced by this and depend mainly on the current value. The gliding of the arc is modelled by means of a 2D Cartesian model. The arcelectrode contact points are analysed and the gliding mechanism along the electrode surface is discussed. Following experimental observations, the cathode spot is simulated as jumping from one point to another. A complete arc cycle is modelled from initial ignition to arc decay. The results show that there is no interaction between the successive gliding arcs.

Abstract: In recent years there has been growing interest in the use of low-temperature atmospheric pressure plasmas for biomedical applications. Currently, however, there is very little fundamental knowledge regarding the relevant interaction mechanisms of plasma species with living cells. In this paper, we investigate the interaction of important plasma species, such as O3, O2 and O atoms, with bacterial peptidoglycan (or murein) by means of reactive molecular dynamics simulations. Specifically, we use the peptidoglycan structure to model the gram-positive bacterium Staphylococcus aureus murein. Peptidoglycan is the outer protective barrier in bacteria and can therefore interact directly with plasma species. Our results demonstrate that among the species mentioned above, O3 molecules and especially O atoms can break important bonds of the peptidoglycan structure (i.e. CO, CN and CC bonds), which subsequently leads to the destruction of the bacterial cell wall. This study is important for gaining a fundamental insight into the chemical damaging mechanisms of the bacterial peptidoglycan structure on the atomic scale.