Abstract: A portable and highly sensitive sensor was designed for the specific detection of 3,4-methyl-enedioxy-methamphetamine (MDMA), in a range of field-testing situations. The sensor can detect MDMA in street samples, even when other controlled substances drugs, or adulterants are present. In this work, we report for the first time a sensor using electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA and then produced using solid phase synthesis. A composite comprising chitosan, reduced graphene oxide, and molecularly imprinted polymer nanoparticles synthesized for MDMA for the first time was immobilized on screen-printed carbon electrodes. The sensors displayed a satisfactory sensitivity (106.8 nA x mu M-1), limit of detection (1.6 nM; 0.31 ng/mL), and recoveries (92-99%). The accuracy of the results was confirmed through validation using Ultra-High Performance Liquid Chromatography coupled with tandem Mass Spectrometry (UPLC-MS/MS). This technology could be used in forensic analysis and make it possible to selectively detect MDMA in street samples. A highly sensitive and portable sensor has been developed to detect MDMA in street samples. It uses electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA, which were immobilized on screen-printed carbon electrodes with chitosan and graphene. The sensor showed good sensitivity and satisfactory recoveries (92-99%), confirmed with UPLC-MS/MS validation. This technology has the potential to be used in forensic analysis.image

Abstract: Intercellular communication plays a crucial role in cancer, as well as other diseases, such as inflammation, tissue degeneration, and neurological disorders. One of the proteins responsible for this, are connexins (Cxs), which come together to form a hemichannel. When two hemichannels of opposite cells interact with each other, they form a gap junction (GJ) channel, connecting the intracellular space of these cells. They allow the passage of ions, reactive oxygen and nitrogen species (RONS), and signaling molecules from the interior of one cell to another cell, thus playing an essential role in cell growth, differentiation, and homeostasis. The importance of GJs for disease induction and therapy development is becoming more appreciated, especially in the context of oncology. Studies have shown that one of the mechanisms to control the formation and disruption of GJs is mediated by lipid oxidation pathways, but the underlying mechanisms are not well understood. In this study, we performed atomistic molecular dynamics simulations to evaluate how lipid oxidation influences the channel properties of Cx26 hemichannels, such as channel gating and permeability. Our results demonstrate that the Cx26 hemichannel is more compact in the presence of oxidized lipids, decreasing its pore diameter at the extracellular side and increasing it at the amino terminus domains, respectively. The permeability of the Cx26 hemichannel for water and RONS molecules is higher in the presence of oxidized lipids. The latter may facilitate the intracellular accumulation of RONS, possibly increasing oxidative stress in cells. A better understanding of this process will help to enhance the efficacy of oxidative stress-based cancer treatments.

Abstract: This study examines five benzyl alcohol derivatives and three chemically similar compounds and compares them against benzyl alcohol in gelled emulsions for the removal of overpaint during cleaning of oil paintings. Comparative cleaning tests using xanthan gels, Pemulen® TR-2 gels, and neat solvent were made on overpaint on fragments of a seventeenth-century test painting. This approach demonstrated that molecular changes to a benzyl alcohol core resulted in enhanced control during the cleaning process. In some cases a benzyl alcohol derivative enabled selective removal of non-original material, when benzyl alcohol appeared to affect the original paint. Select derivatives were also tested in an area of overpaint on a sixteenth-century oil on panel painting by Jan van Scorel in the Rijksmuseum Collection through modifying the chemical activity of benzyl alcohol. Finally, two GC-MS-based methods were used to monitor benzyl alcohol retention and possible oxidation in paint layers post-treatment.

Abstract: Lignin removal plays a crucial role in the efficient bioconversion of lignocellulose to fermentable sugars. As a delignification process, fungal pretreatment has gained great interest due to its environmental friendliness and low energy consumption. In our previous study, a positive linear correlation between acid-insoluble lignin degradation and the achievable enzymatic saccharification yield has been found, hereby highlighting the importance of the close follow-up of lignin degradation during the solid-state fungal pretreatment process. However, the standard quantification of lignin, which relies on the two-step acid hydrolysis of the biomass, is highly laborious and time-consuming. Vibrational spectroscopy has been proven as a fast and easy alternative; however, it has not been extensively researched on lignocellulose subjected to solid-state fungal pretreatment. Therefore, the present study examined the suitability of near-infrared spectroscopy (NIR) for the rapid and easy assessment of lignin content in poplar wood pretreated with Phanerochaete chrysosporium. Furthermore, the predictive power of the obtained calibration model and the recently published ATR-FTIR spectroscopy-based model were compared for the first time using the same fungus-treated wood data set. PLSR was used to correlate the NIR spectra to the acid-insoluble lignin contents (19.9%-27.1%) of pretreated wood. After normalization and second derivation, a PLSR model with a good coefficient of determination (RCV2 = 0.89) and a low root mean square error (RMSECV = 0.55%) were obtained despite the heterogeneous nature of the fungal solid-state fermentation. The performance of this PLSR model was comparably good to the one obtained by ATR-FTIR (RCV2 = 0.87) while it required more extensive spectral pre-processing. In conclusion, both methods will be highly useful for the high-throughput and user-friendly monitoring of lignin degradation in a solid-state fungal pretreatment-based biorefinery concept.

Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: Green infrastructure (GI) is already known to be a suitable way to enhance air quality in urban environments. Living wall systems (LWS) can be implemented in locations where other forms of GI, such as trees or hedges, are not suitable. However, much debate remains about the variables that influence their particulate matter (PM) accumulation efficiency. This study attempts to clarify which plant species are relatively the most efficient in capturing PM and which traits are decisive when it comes to the implementation of a LWS. We investigated 11 plant species commonly used on living walls, located close to train tracks and roads. PM accumulation on leaves was quantified by magnetic analysis (Saturation Isothermal Remanent Magnetization (SIRM)). Several leaf morphological variables that could potentially influence PM capture were assessed, as well as the Wall Leaf Area Index. A wide range in SIRM values (2.74–417 μA) was found between all species. Differences in SIRM could be attributed to one of the morphological parameters, namely SLA (specific leaf area). This suggest that by just assessing SLA, one can estimate the PM capture efficiency of a plant species, which is extremely interesting for urban greeners. Regarding temporal variation, some species accumulated PM over the growing season, while others actually decreased in PM levels. This decrease can be attributed to rapid leaf expansion and variations in meteorology. Correct assessment of leaf age is important here; we suggest individual labeling of leaves for further studies. Highest SIRM values were found close to ground level. This suggests that, when traffic is the main pollution source, it is most effective when LWS are applied at ground level. We conclude that LWS can act as local sinks for PM, provided that species are selected correctly and systems are applied according to the state of the art.

Abstract: This paper brings the comparison of performances of CO2 conversion by plasma and plasma-assisted catalysis based on the data collected from literature in this field, organised in an open access online data-base. This tool is open to all users to carry out their own analyses, but also to contributors who wish to add their data to the database in order to improve the relevance of the comparisons made, and ultimately to improve the efficiency of CO2 conversion by plasma-catalysis. The creation of this database and data-base user interface is motivated by the fact that plasma-catalysis is a fast-growing field for all CO2 con-version processes, be it methanation, dry reforming of methane, methanolisation, or others. As a result of this rapid increase, there is a need for a set of standard procedures to rigorously compare performances of different systems. However, this is currently not possible because the fundamental mechanisms of plasma-catalysis are still too poorly understood to define these standard procedures. Fortunately how-ever, the accumulated data within the CO2 plasma-catalysis community has become large enough to war-rant so-called “big data” studies more familiar in the fields of medicine and the social sciences. To enable comparisons between multiple data sets and make future research more effective, this work proposes the first database on CO2 conversion performances by plasma-catalysis open to the whole community. This database has been initiated in the framework of a H2020 European project and is called the “PIONEER DataBase”. The database gathers a large amount of CO2 conversion performance data such as conversion rate, energy efficiency, and selectivity for numerous plasma sources coupled with or without a catalyst. Each data set is associated with metadata describing the gas mixture, the plasma source, the nature of the catalyst, and the form of coupling with the plasma. Beyond the database itself, a data extraction tool with direct visualisation features or advanced filtering functionalities has been developed and is available online to the public. The simple and fast visualisation of the state of the art puts new results into context, identifies literal gaps in data, and consequently points towards promising research routes. More advanced data extraction illustrates the impact that the database can have in the understanding of plasma-catalyst coupling. Lessons learned from the review of a large amount of literature during the setup of the database lead to best practice advice to increase comparability between future CO2 plasma-catalytic studies. Finally, the community is strongly encouraged to contribute to the database not only to increase the visibility of their data but also the relevance of the comparisons allowed by this tool. (c) 2023 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. This is an open access article under the CC BY license (http://creati- vecommons.org/licenses/by/4.0/).

Abstract: In present work, we have performed the Grand Canonical Monte Carlo (GCMC) simulations to quantify CO2 capture inside porous silica at high operating temperatures of 673.15 K and 873.15 K; and over a operating pressure range of 500 kPa – 4000 kPa that are methane steam reforming process parameters. Related chemical potential values at these thermodynamic conditions are obtained from the bulk phase simulations in the Canonical ensemble in conjunction with Widom’s insertion technique, where the CO2 has been accurately represented by TraPPE force field. Present structure of the porous silica is a single slit pore geometry of various heights (H = 20 Å, 31.6 Å, 63.2 Å and 126.5 Å), dimensions in which possible vapour-liquid equilibria for generic square well fluids has been reported in literature. Estimation of the pore-fluid interactions show a higher interaction between silica pore and adsorbed CO2 compared to the reported pore-fluid interactions between homogeneous carbon slit pore and adsorbed CO2; thus resulting in an enhancement of adsorption inside silica pores of H = 20 Å and H = 126.5 Å, which are respectively 3.5 times and 1.5 times higher than that in homogeneous carbon slit pores of same dimensions and at 673.15 K and 500 kPa. Estimated local density plots indicate the presence of structured layers due to more molecular packing, which confirms possible liquid-like and vapour-like phase coexistence of the supercritical bulk phase CO2 under confinement.

Abstract: Generalized Möbius-Listing surfaces and bodies generalize Möbius bands, and this research was motivated originally by solutions of boundary value problems. Analogous to cutting of the original Möbius band, for this class of surfaces and bodies, results have been obtained when cutting such bodies or surfaces. In general, cutting leads to interlinked and intertwined different surfaces or bodies, resulting in very complex systems. However, under certain conditions, the result of cutting can be a single surface or body, which reduces complexity considerably. These conditions are based on congruence and rotational symmetry of the resulting cross sections after cutting, and on the knife cutting the origin

Abstract: Mitigating the adverse effects of air pollution, especially on human health, is one of the greater contemporary challenges for cities. Street canyons have herein been identified as bottleneck areas in urbanized environments. Focusing on the necessity of fast-response interventions, strategies to control source-receptor pathways (e.g. implementing low boundary walls (LBWs)) are gaining interest. A potential strategy which is greatly overlooked is the adjustment (reduction or displacement) of traffic lanes in order to increase the distance between source (traffic) and recipient (pedestrians). Within our study, computation fluid dynamics (CFD) is used to simulate the impact of alternations to traffic lanes (whether or not combined with LBWs) on the pedestrian exposure to NO2 for a specific case-study (Belgie center dot lei, Antwerp) under two prevailing wind directions. The average differences in NO2 concentrations for the entire pedestrian area ranged between +1.0 % to-3.6 %. On specific locations, reduction up to-8.0 % were reached. In case of perpendicular winds, a lateral displacement of all traffic lanes towards the windward facade including LBWs was found most beneficial to reduce pedestrian exposure. LBWs also showed to be efficient in reducing potential adverse effects of lane displacement under less frequent wind directions.

Abstract: Delve into the diverse aspects of plant morphology, their responses to global climate change, and the spatiotemporal dynamics of forest productivity. Join us on a journey through the intricate web of plant characteristics and their impact on the environment.

Abstract: Electrons, X-rays and neutrons that pass through a thin crystalline sample will be diffracted. Diffraction patterns of crystalline materials contain Bragg reflections (sharp discrete intensity maxima) and diffuse scattering (a weak continuous background). The Bragg reflections contain information about the average crystal structure (the type of atoms and the average atomic positions), whereas the diffuse scattering contains information about the short-range order (deviations from the average crystal structure that are ordered on a local scale). Because the properties of many materials depend on the short-range order, refining short-range order parameters is essential for understanding and optimizing material properties. The refinement of short-range order parameters has previously been applied to the diffuse scattering in single-crystal X-ray and single-crystal neutron diffraction data but not yet to the diffuse scattering in single-crystal electron diffraction data. In this work, we will verify the possibility to refine short-range order parameters from the diffuse scattering in single-crystal electron diffraction data. Electron diffraction allows to acquire data on submicron-sized crystals, which are too small to be investigated with single-crystal X-ray and single-crystal neutron diffraction. In the first part of this work, we will refine short-range order parameters from the one-dimensional diffuse scattering in electron diffraction data acquired on the lithium-ion battery cathode material Li1.2Ni0.13Mn0.54Co0.13O2. The number of stacking faults and the twin percentages will be refined from the diffuse scattering using a Monte Carlo refinement. We will also describe a method to determine the spinel/layered phase ratio from the intensities of the Bragg reflections in electron diffraction data. In the second part of this work, we will refine short-range order parameters from the three-dimensional diffuse scattering in both single-crystal electron and single-crystal X-ray diffraction data acquired on Nb0.84CoSb. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms will be refined from the diffuse scattering using a Monte Carlo refinement and a three-dimensional difference pair distribution function refinement. The effect of different experimental parameters on the spatial resolution of the observed diffuse scattering will also be investigated. Finally, the model of the short-range Nb-vacancy order in Nb0.84CoSb will also be applied to LiNi0.5Sn0.3Co0.2O2.

Abstract: Dry deposition is an important process determining pollutant concentrations, especially when studying the influence of urban green infrastructure on particulate matter (PM) levels in cities. Computational fluid dynamics (CFD) models of PM capture by vegetation are useful tools to increase their applicability. The meso-scale models of Zhang et al. (Atmos Environ 35:549-560, 2001) and Petroff and Zhang (Geosci Model Dev 3(2):753-769, 2010) have often been adopted in CFD models, however a comparison of these models with measurements including all PM particle sizes detrimental to health has been rarely reported and certainly not for green wall species. This study presents dry deposition experiments on real grown Hedera helix in a wind tunnel setup with wind speeds from 1 to 4 m s(-1) and PM consisting of a mixture of soot (0.02 – 0.2 mu mu m) and dust particles (0.3 – 10 mu mu m). Significant factors determining the collection efficiency (%) were particle diameter and wind speed, but relative air humidity and the type of PM (soot or dust) did not have a significant influence. Zhang's model outperformed Petroff's model for particles < 0.3 mu mu m, however the inclusion of turbulent impaction in Petroff's model resulted in better agreement with the measurements for particles > 2 – 3 mu mu m. The optimised model had an overall root-mean-square-error of similar to 4% for collection efficiency (CE) and 0.4 cm s-1 for deposition velocity (nu d), which was shown to be highly competitive against previously described models. It can thus be used to model PM deposition on other plant species, provided the correct parameterisation of the drag by this species. A detailed description of the spatial distribution of the vegetation could solve the underestimation for particle sizes of 0.3 – 2 mu mu m.

Abstract: Single nucleotide point mutations in the KRAS oncogene occur frequently in human cancers, rendering them intriguing targets for diagnosis, early detection and personalized treatment. Current detection methods are based on polymerase chain reaction, sometimes combined with next-generation sequencing, which can be expensive, complex and have limited availability. Here, we propose a novel singlet oxygen (1O2)-based photoelectrochemical detection methodology for single-point mutations, using KRAS mutations as a case study. This detection method combines the use of a sandwich assay, magnetic beads and robust chemical photosensitizers, that need only air and light to produce 1O2, to ensure high specificity and sensitivity. We demonstrate that hybridization of the sandwich hybrid at high temperatures enables discrimination between mutated and wild-type sequences with a detection rate of up to 93.9%. Additionally, the presence of background DNA sequences derived from human cell-line DNA, not containing the mutation of interest, did not result in a signal, highlighting the specificity of the methodology. A limit of detection as low as 112 pM (1.25 ng/mL) was achieved without employing any amplification techniques. The developed 1O2-based photoelectrochemical methodology exhibits unique features, including rapidity, ease of use, and affordability, highlighting its immense potential in the field of nucleic acid-based diagnostics.