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: 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: Plasma degradation is one of the most effective methods for the abatement of greenhouse gas sulfur hexafluoride
(SF6). To evaluate the potential of MgO as a catalyst in plasma degradation, we investigate the catalytic properties
of MgO on SF6 adsorption and activation by density functional theory (DFT) where the O-defective and
hydroxylated surfaces are considered as two typical plasma-generated surfaces. Our results show that perfect
MgO (001) and (111) surfaces cannot interact with SF6 and only physical adsorption happens. In case of Odefective
MgO surfaces, the O vacancy is the most stable adsorption site. SF6 undergoes a decomposition to SF5
and F over the O-defective MgO (001) surface and undergoes an elongation of the bottom S-F bond over the Odefective
(111) surface. Besides, SF6 shows a physically adsorption at the stepsite of the MgO (001) surface,
accompanied by small changes in its bond angle and length. Furthermore, SF6 is found to be physically and
chemically adsorbed over 0.5 and 1.0 ML (monolayer) H-covered O-terminated MgO (111) surfaces, respectively.
The SF6 molecule undergoes a self-decomposition on the 1.0 ML hydroxylated surface via a surface bonding
process. This study shows that defective and hydroxylated MgO surfaces have the surface capacities for SF6
activation, which shows that MgO has potential as packing material in SF6 waste treatment in packed-bed
plasmas.

Abstract: We present a zero-dimensional kinetic model to characterise specifically the gas-phase dynamics of methane
conversion in a nanosecond pulsed discharge (NPD) plasma reactor. The model includes a systematic approach to
capture the nanoscale power discharges and the rapid ensuing changes in electric field, gas and electron temperature,
as well as species densities. The effects of gas temperature and reactor pressure on gas conversion and
product selectivity are extensively investigated and validated against experimental work. We discuss the
important reaction pathways and provide an analysis of the dynamics of the heating and cooling mechanisms. H
radicals are found to be the most populous plasma species and they participate in hydrogenation and dehydrogenation
reactions, which are the dominant recombination reactions leading to C2H4 and C2H2 as main
products (depending on the pressure).

Abstract: By combining dielectric barrier discharge plasma and external heating, we exploit a two-stage hybrid plasmathermal
system (HPTS), i.e., a plasma stage followed by a thermal stage, for direct non-oxidative coupling of
CH4 to C2H4 and H2, yielding a CH4 conversion of ca. 17 %. In the two-stage HPTS, the plasma first converts CH4
into C2H6 and C3H8, which in the thermal stage leads to a high C2H4 selectivity of ca. 63 % by pyrolysis, with H2
selectivity of ca. 64 %.

Abstract: Plasma catalysis is emerging for plasma-assisted gas conversion
processes. However, the underlying mechanisms of plasma catalysis are poorly
understood. In this work, we present a 1D heterogeneous catalysis model with axial
dispersion (i.e., accounting for back-mixing and molecular diffusion of fluid elements in
the process stream in the axial direction), for plasma-catalytic NO production from
N2/O2 mixtures. We investigate the concentration and reaction rates of each species
formed as a function of time and position across the catalyst, in order to determine the
underlying mechanisms. To obtain insights into how the performance of the process
can be further improved, we also study how changes in the postplasma gas flow
composition entering the catalyst bed and in the operation conditions of the catalytic
stage affect the performance of NO production.

Abstract: Given the ecological problems associated to the CO2 emissions of fossil fuels, plasma technology has gained
interest for conversion of CO2 into value-added products. Microwave plasmas operating at atmospheric pressure
have proven to be especially interesting, due to the high gas temperatures inside the reactor (i.e. up to 6000 K)
allowing for efficient thermal dissociation of CO2 into CO and O2. However, the performance of these high
temperature plasmas is limited by recombination of CO back into CO2 once the gas cools down in the afterglow.
In this work, we computationally investigated several quenching nozzles, developed and experimentally tested
by Hecimovic et al., [1] for their ability to quickly cool the gas after the plasma, thereby quenching the CO
recombination reactions. Using a 3D computational fluid dynamics model and a quasi-1D chemical kinetics
model, we reveal that a reactor without nozzle lacks gas mixing between hot gas in the center and cold gas near
the reactor walls. Especially at low flow rates, where there is an inherent lack of convective cooling due to the
low gas flow velocity, the temperature in the afterglow remains high (between 2000 and 3000 K) for a relatively
long time (in the 0.1 s range). As shown by our quasi-1D chemical kinetics model, this results in a important loss
of CO due to recombination reactions. Attaching a nozzle in the effluent of the reactor induces fast gas quenching
right after the plasma. Indeed, it introduces (i) more convective cooling by forcing cool gas near the walls to mix
with hot gas in the center of the reactor, as well as (ii) more conductive cooling through the water-cooled walls of
the nozzle. Our model shows that gas quenching and the suppression of recombination reactions have more
impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach-based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction-allows us to probe a fairly wide range of rates in several superheated and cavitation regimes in a consistent manner. Rate predictions from this approach bridge disparate independent literature studies on the same model system. As such, we find that rate predictions based on classical nucleation theory, direct brute force molecular dynamics simulations, and seeding are consistent with our approach and one another. Published rates derived from forward flux sampling simulations are, however, found to be outliers. This study serves two purposes: First, we validate the reliability of common modeling techniques and extrapolation approaches on a paradigmatic problem in materials science and chemical physics. Second, we further test our highly generic recipe for rate calculations, and establish its applicability to nucleation processes.

Abstract: Although the heterogeneity of pyrolyzed Fe???N???C materials is known and has been reported previously, the atomic structure of the active sites and their detailed reaction mechanisms are still unknown. Here, we identified two pyridinic Fe???N4-like centers with different local C coordinates, i.e., FeN4C8 and FeN4C10, and studied their electrocatalytic activity for the nitrogen reduction reaction (NRR) based on density functional theory (DFT) calculations. We also discovered the influence of the adsorption of NH2 as a functional ligand on catalyst performance on the NRR. We confirmed that the NRR selectivity of the studied catalysts is essentially governed either by the local C coordination or by the dynamic structure associated with the FeII/FeIII. Our investigations indicate that the proposed traditional pyridinic FeN4C10 has higher catalytic activity and selectivity for the NRR than the robust FeN4C8 catalyst, while it may have outstanding activity for promoting other (electro)catalytic reactions. <comment>Superscript/Subscript Available</comment

Abstract: Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification. ,

Abstract: Accurate barriers for rate controlling elementary reactions on metal surfaces are key to understanding, controlling, and predicting the rate of heterogeneously catalyzed processes. While barrier heights for gas phase reactions have been extensively benchmarked, dissociative chemisorption barriers for the reactions of molecules on metal surfaces have received much less attention. The first database called SBH10 and containing 10 entries was recently constructed based on the specific reaction parameter approach to density functional theory (SRP-DFT) and experimental results. We have now constructed a new and improved database (SBH17) containing 17 entries based on SRP-DFT and experiments. For this new SBH17 benchmark study, we have tested three algorithms (high, medium, and light) for calculating barrier heights for dissociative chemisorption on metals, which we have named for the amount of computational effort involved in their use. We test the performance of 14 density functionals at the GGA, GGA+vdW-DF, and meta-GGA rungs. Our results show that, in contrast with the previous SBH10 study where the BEEF-vdW-DF2 functional seemed to be most accurate, the workhorse functional PBE and the MS2 density functional are the most accurate of the GGA and meta-GGA functionals tested. Of the GGA+vdW functionals tested, the SRP32-vdW-DF1 functional is the most accurate. Additionally, we found that the medium algorithm is accurate enough for assessing the performance of the density functionals tested, while it avoids geometry optimizations of minimum barrier geometries for each density functional tested. The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. While these are avoided in the light algorithm, this algorithm is found not to give a reliable description of functional performance. The combination of relative ease of use and demonstrated reliability of the medium algorithm will likely pave the way for incorporation of the SBH17 database in larger databases used for testing new density functionals and electronic structure methods.

Abstract: Catalysis science and technology increased efforts recently to progress beyond conventional “thermal” catalysis and face the challenges of net-zero emissions and electrification of production. Nevertheless, a better gaps and opportunities analysis is necessary. This review analyses four emerging areas of unconventional or less- conventional catalysis which share the common aspect of using directly renewable energy sources: (i) plasma catalysis, (ii) catalysis for flow chemistry and process intensification, (iii) application of electromagnetic (EM) fields to modulate catalytic activity and (iv) nanoscale generation at the catalyst interface of a strong local EM by plasmonic effect. Plasma catalysis has demonstrated synergistic effects, where the outcome is higher than the sum of both processes alone. Still, the underlying mechanisms are complex, and synergy is not always obtained. There is a crucial need for a better understanding to (i) design catalysts tailored to the plasma environment, (ii) design plasma reactors with optimal transport of plasma species to the catalyst surface, and (iii) tune the plasma conditions so they work in optimal synergy with the catalyst. Microfluidic reactors (flow chemistry) is another emerging sector leading to the intensification of catalytic syntheses, particularly in organic chemistry. New unconventional catalysts must be designed to exploit in full the novel possibilities. With a focus on (a) continuous-flow photocatalysis, (b) electrochemical flow catalysis, (c) microwave flow catalysis and (d) ultra­ sound flow activation, a series of examples are discussed, with also indications on scale-up and process indus­ trialisation. The third area discussed regards the effect on catalytic performances of applying oriented EM fields spanning several orders of magnitude. Under well-defined conditions, gas breakdown and, in some cases, plasma formation generates activated gas phase species. The EM field-driven chemical conversion processes depend further on structured electric/magnetic catalysts, which shape the EM field in strength and direction. Different effects influencing chemical conversion have been reported, including reduced activation energy, surface charging, hot spot generation, and selective local heating. The last topic discussed is complementary to the third, focusing on the possibility of tuning the photo- and electro-catalytic properties by creating a strong localised electrical field with a plasmonic effect. The novel possibilities of hot carriers generated by the plasmonic effect are also discussed. This review thus aims to stimulate the reader to make new, creative catalysis to address the challenges of reaching a carbon-neutral world.

Abstract: Theoretical studies on molecule-metal surface reactions have so far been limited to small surface unit cells due to computational costs. Here, for the first time molecular dynamics simulations on very large surface unit cells at the level of density functional theory are performed, allowing a direct comparison to experiments performed on a curved crystal. Specifically, the reaction of D-2 on a curved Pt crystal is investigated with a neural network potential (NNP). The developed NNP is also accurate for surface unit cells considerably larger than those that have been included in the training data, allowing dynamical simulations on very large surface unit cells that otherwise would have been intractable. Important and complex aspects of the reaction mechanism are discovered such as diffusion and a shadow effect of the step. Furthermore, conclusions from simulations on smaller surface unit cells cannot always be transfered to larger surface unit cells, limiting the applicability of theoretical studies of smaller surface unit cells to heterogeneous catalysts with small defect densities.

Abstract: Immobilization of single metal atoms on a solid host opens numerous possibilities for catalyst designs. If that host is a two-dimensional sheet, sheet curvature becomes a design parameter potentially complementary to host and metal composition. Here, we use a combination of density functional theory calculations and microkinetic modeling to compare the mechanisms and kinetics of formic acid decomposition and formation, chosen for their relevance as a potential hydrogen storage medium, over single Ru atoms anchored to pyridinic nitrogen in a planar graphene flake (RuN4-G) and curved carbon nanotube (RuN4-CNT). Activation barriers are lowered and the predicted turnover frequencies are increased over RuN4-CNT relative to RuN4-CNT. The results highlight the potential of curvature control as a means to achieve high performance and robust catalysts.

Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.