Plastic Fruit Stickers in Industrial Composting─Surface and Structural Alterations Revealed by Electron Microscopy and Computed Tomography

Often large quantities of plastics are found in compost, with price look-up stickers being a major but little-explored component in the contamination path. Stickers glued to fruit or vegetable peels usually remain attached to the organic material despite sorting processes in the composting plant. Here, we investigated the effects of industrial composting on the structural alterations of these stickers. Commercial polypropylene (PP) stickers on banana peels were added to a typical organic material mixture for processing in an industrial composting plant and successfully resampled after a prerotting (11 days) and main rotting step (25 days). Afterward, both composted and original stickers were analyzed for surface and structural changes via scanning electron microscopy, Fourier-transform infrared spectroscopy, and micro- and nano-X-ray computed tomography (CT) combined with deep learning approaches. The composting resulted in substantial surface changes and degradation in the form of microbial colonization, deformation, and occurrence of cracks in all stickers. Their pore volumes increased from 16.7% in the original sticker to 26.3% at the end of the compost process. In a similar way, the carbonyl index of the stickers increased. Micro-CT images additionally revealed structural changes in the form of large adhesions that penetrated the surface of the sticker. These changes were accompanied by delamination after 25 days of composting, thus overall hinting at the degradation of the stickers and the subsequent formation of smaller microplastic pieces.

Reversible Influence of Hemipiperazine Photochromism on the Early Development of Zebrafish Embryo

This study explores the potential of controlling organismal development with light by using reversible photomodulation of activity in bioactive compounds. Specifically, our research focuses on plinabulin 1, an inhibitor of tubulin dynamics that contains a photochromic motif called hemipiperazine. The two isomeric forms, Z-1 and E-1, can partially interconvert with light, yet show remarkable thermal stability in darkness. The Z-isomer exhibits higher cytotoxicity due to stronger binding to α-tubulin's colchicine site. The less toxic E-1 form, considered a "pro-drug", can be isolated in vitro and stored. Upon activation by blue or cyan light, it predominantly generates the more toxic Z-1 form. Here we demonstrate that 1 can effectively photomodulate epiboly, a critical microtubule-dependent cell movement during gastrulation in zebrafish embryos. This research highlights the potential of photomodulation for precise and reversible control of cellular activities and organismal development.

Förster resonance energy transfer within single chain nanoparticles

Single chain nanoparticles (SCNPs) are a highly versatile polymer architecture consisting of single polymer chains that are intramolecularly crosslinked. Currently, SCNPs are discussed as powerful macromolecular architectures for catalysis, delivery and sensors. Herein, we introduce a methodology based on Förster Resonance Energy Transfer (FRET) to evidence the folding of single polymer chains into SCNPs via fluorescence readout. We initially introduce a molecular FRET pair based on a bimane and nitrobenzoxadiazole (NBD) moiety and study its fluorescence properties in different solvents. We subsequently construct a low dispersity polymer chain carrying NBD units, while exploiting the bimane units for intramolecular chain collapse. Upon chain collapse and SCNP formation - thus bringing bimane and NBD units into close proximity - the SCNPs report their folded state by a strong and unambiguous FRET fluorescence signal. The herein introduced reporting of the folding state of SCNPs solely relies on an optical readout, opening avenues to monitoring SCNP folding without recourse to complex analytical methodologies.

Wetting Behavior of Inkjet-Printed Electronic Inks on Patterned Substrates

In inkjet printing technology, one important factor influencing the printing quality and reliability of printed films is the interaction of the jetted ink with the substrate surface. This short-range interaction determines the wettability and the adhesion of the ink to the solid surface and is hence responsible for the final shape of the deposited ink. Here, we investigate wetting morphologies of inkjet-printed inks on patterned substrates by carefully designed experimental test structures and simulations. The contact angles, the surface properties, and drop shapes, as well as their influence on the device variability, are experimentally and theoretically analyzed. For the simulations, we employ the phase-field method, which is based on the free energy minimization of the two-phase system with the given wetting boundary conditions. Through a systematic investigation of printed drops on patterned substrates consisting of hydrophilic and hydrophobic areas, we report that the printed morphology is related not only to the designed layout and the drop volume but also to the printing strategy and the wettability. Furthermore, we show how one can modify the intrinsic wettability of the patterned substrates to enhance the printing quality and reliability. Based on the present findings, we cast light on the improvement of the fabrication quality of thin film transistors.

A Multi-Scale Approach to Simulate the Nonlinear Optical Response of Molecular Nanomaterials

Nonlinear optics is essential for many recent photonic technologies. Here, a novel multi-scale approach is introduced to simulate the nonlinear optical response of molecular nanomaterials combining ab initio quantum-chemical and classical Maxwell-scattering computations. In this approach, the first hyperpolarizability tensor is computed with time-dependent density-functional theory and incorporated into a multi-scattering formalism that considers the optical interaction between neighboring molecules. Such incorporation is achieved by a novel object: the Hyper-Transition(T)-matrix. With this object at hand, the nonlinear optical response from single molecules and also from entire photonic devices can be computed, including the full tensorial and dispersive nature of the optical response of the molecules, as well as the optical interaction between different molecules as, for example, in the lattice of a molecular crystal. To demonstrate the applicability of the novel approach, the generation of a second-harmonic signal from a thin film of an Urea molecular crystal is computed and compared to more traditional simulations. Furthermore, an optical cavity is designed, which enhances the second-harmonic response of the molecular film up to more than two orders of magnitude. This approach is highly versatile and accurate and can be the working horse for the future exploration of nonlinear photonic molecular materials in structured photonic environments.

Photochemical Action Plots Reveal the Fundamental Mismatch Between Absorptivity and Photochemical Reactivity

Over the last years, the authors' laboratory has employed monochromatic tuneable laser systems to reveal a fundamental mismatch between the absorptivity of a chromophore and its photochemical reactivity for the vast majority of covalent bond forming reactions as well as specific bond cleavage reactions. In the general chemistry community, however, the long-held assumption pervades that effective photochemical reactions are obtained in situations where there is strong overlap between the absorption spectrum and the excitation wavelength. The current Perspective illustrates that the absorption spectrum of a molecule only provides information about electronic excitations and remains entirely silent on other energy redistribution mechanisms that follow, which critically influence photochemical reactivity. Future avenues of enquiry on how action plots can be understood are proposed and the importance of action plots for tailoring photochemical applications with never-before-seen precision is explored.

Metabolic labelling of DNA in cells by means of the "photoclick" reaction triggered by visible light

Two pyrene-tetrazole conjugates were synthesized as photoreactive chromophores that allow for the first time the combination of metabolic labelling of DNA in cells and subsequent bioorthogonal "photoclick" modification triggered by visible light. Two strained alkenes and three alkene-modified nucleosides were used as reactive counterparts and revealed no major differences in their "photoclick" reactivity. This is a significant advantage because it allows 5-vinyl-2'-deoxyuridine to be applied as the smallest possible alkene-modified nucleoside for metabolic labelling of DNA in cells. Both pyrene-tetrazole conjugates show fluorogenicity during the "photoclick" reactions, which is a second advantage for cellular imaging. Living HeLa cells were incubated with 5-vinyl-2'-deoxyuridine for 48 h to ensure one cell division. After fixation, the newly synthesized genomic DNA was successfully labelled by irradiation with visible light at 405 nm and 450 nm. This method is an attractive tool for the visualization of genomic DNA in cells with full spatiotemporal control by the use of visible light as a reaction trigger.

Explainable artificial intelligence for omics data: a systematic mapping study

Researchers increasingly turn to explainable artificial intelligence (XAI) to analyze omics data and gain insights into the underlying biological processes. Yet, given the interdisciplinary nature of the field, many findings have only been shared in their respective research community. An overview of XAI for omics data is needed to highlight promising approaches and help detect common issues. Toward this end, we conducted a systematic mapping study. To identify relevant literature, we queried Scopus, PubMed, Web of Science, BioRxiv, MedRxiv and arXiv. Based on keywording, we developed a coding scheme with 10 facets regarding the studies' AI methods, explainability methods and omics data. Our mapping study resulted in 405 included papers published between 2010 and 2023. The inspected papers analyze DNA-based (mostly genomic), transcriptomic, proteomic or metabolomic data by means of neural networks, tree-based methods, statistical methods and further AI methods. The preferred post-hoc explainability methods are feature relevance (n = 166) and visual explanation (n = 52), while papers using interpretable approaches often resort to the use of transparent models (n = 83) or architecture modifications (n = 72). With many research gaps still apparent for XAI for omics data, we deduced eight research directions and discuss their potential for the field. We also provide exemplary research questions for each direction. Many problems with the adoption of XAI for omics data in clinical practice are yet to be resolved. This systematic mapping study outlines extant research on the topic and provides research directions for researchers and practitioners.

The fungal metabolite 4-hydroxyphenylacetic acid from Neofusicoccum parvum modulates defence responses in grapevine

In a consequence of global warming, grapevine trunk diseases (GTDs) have become a pertinent problem to viticulture, because endophytic fungi can turn necrotrophic upon host stress killing the plant. In Neofusicoccum parvum Bt-67, plant-derived ferulic acid makes the fungus release Fusicoccin aglycone triggering plant cell death. Now, we show that the absence of ferulic acid lets the fungus secrete 4-hydroxyphenylacetic acid (4-HPA), mimicking the effect of auxins on grapevine defence and facilitating fungal spread. Using Vitis suspension cells, we dissected the mode of action of 4-HPA during defence triggered by the bacterial cell-death elicitor, harpin. Early responses (cytoskeletal remodelling and calcium influx) are inhibited, as well as the expression of Stilbene Synthase 27 and phytoalexin accumulation. In contrast to other auxins, 4-HPA quells transcripts for the auxin conjugating GRETCHEN HAGEN 3. We suggest that 4-HPA is a key component of the endophytic phase of N. parvum Bt-67 preventing host cell death. Therefore, our study paves the way to understand how GTDs regulate their latent phase for successful colonisation, before turning necrotrophic and killing the vines.

TURBOMOLE: Today and Tomorrow

TURBOMOLE is a highly optimized software suite for large-scale quantum-chemical and materials science simulations of molecules, clusters, extended systems, and periodic solids. TURBOMOLE uses Gaussian basis sets and has been designed with robust and fast quantum-chemical applications in mind, ranging from homogeneous and heterogeneous catalysis to inorganic and organic chemistry and various types of spectroscopy, light-matter interactions, and biochemistry. This Perspective briefly surveys TURBOMOLE's functionality and highlights recent developments that have taken place between 2020 and 2023, comprising new electronic structure methods for molecules and solids, previously unavailable molecular properties, embedding, and molecular dynamics approaches. Select features under development are reviewed to illustrate the continuous growth of the program suite, including nuclear electronic orbital methods, Hartree-Fock-based adiabatic connection models, simplified time-dependent density functional theory, relativistic effects and magnetic properties, and multiscale modeling of optical properties.

Amphiphiles Formed from Synthetic DNA-Nanomotifs Mimic the Stepwise Dispersal of Transcriptional Clusters in the Cell Nucleus

Stem cells exhibit prominent clusters controlling the transcription of genes into RNA. These clusters form by a phase-separation mechanism, and their size and shape are controlled via an amphiphilic effect of transcribed genes. Here, we construct amphiphile-nanomotifs purely from DNA, and we achieve similar size and shape control for phase-separated droplets formed from fully synthetic, self-interacting DNA-nanomotifs. Increasing amphiphile concentrations induce rounding of droplets, prevent droplet fusion, and, at high concentrations, cause full dispersal of droplets. Super-resolution microscopy data obtained from zebrafish embryo stem cells reveal a comparable transition for transcriptional clusters with increasing transcription levels. Brownian dynamics and lattice simulations further confirm that the addition of amphiphilic particles is sufficient to explain the observed changes in shape and size. Our work reproduces key aspects of transcriptional cluster formation in biological cells using relatively simple DNA sequence-programmable nanostructures, opening novel ways to control the mesoscopic organization of synthetic nanomaterials.

Knock-out of multidrug efflux pump MexXY-OprM results in increased susceptibility to antimicrobial peptides in Pseudomonas aeruginosa

Multidrug efflux systems of the resistance-nodulation-cell division family play a crucial role in resistance of Pseudomonas aeruginosa to a large variety of antibiotics. Here, we investigated the role of clinically relevant efflux pumps MexAB- OprM, MexCD- OprJ, and MexXY- OprM in resistance against different cationic antimicrobial peptides (AMPs). Our results indicate that a knock-out in efflux pump MexXY-OprM increased susceptibility to some AMPs by two- to eightfold. Our data suggest a contribution of MexXY-OprM in resistance to certain AMPs in P. aeruginosa, which should be considered in the future development of new and highly active antimicrobial peptides to fight multidrug resistant infections.

Advancing and critical appraisal of an integrative load monitoring approach in microcycles in professional soccer

Despite load monitoring being considered an integral part of targeted performance management, including injury and illness prevention, there is currently no consensus of an effective monitoring system in professional soccer. Thus, the aims were to apply an integrative load monitoring approach, previously established in rink-hockey, in professional soccer; extend this approach with further data (Short Recovery and Stress Scale); assess this (extended) approach, thereby further evaluating the relationship between the used external load (EL) measures (total distance, distance above 55% and 70% of individual maximal speed, number of accelerations and decelerations > 4 m/s2, total loading) and the internal load (IL) measure session rate of perceived exertion training load (sRPE-TL) as well as between the used EL measures and sRPE. This retrospective observational cohort study analyzed data from a Swiss team collected over a 14 week-period during the 2021/22 season. Based on our findings, the integrative approach tested proved to be an applicable load monitoring tool in professional soccer, placing players on a fitness-fatigue continuum throughout the different microcycle sessions without using tests, thus providing relevant information to individually tailor training programs. sRPE-TL (ρ [95% CI] = .55 [.51 to .59] to .87 [.85 to .88]; all p < .001) better reflected the EL experienced by players than sRPE (ρ [95% CI] = .45 [.40 to .50] to .71 [.69 to .75]; all p < .001) supporting the definition of sRPE-TL as a measure of IL. However, for even stronger relevance of the tested tool, further research is warranted, especially to ascertain its sensitivity and determine an optimal selection of EL and IL measures. In sum, the present data clearly demonstrate the importance of load management taking place at an individual level, even within team structures, thereby analyzing a set of both EL and IL measures.

Self-supervised pseudo-colorizing of masked cells

Self-supervised learning, which is strikingly referred to as the dark matter of intelligence, is gaining more attention in biomedical applications of deep learning. In this work, we introduce a novel self-supervision objective for the analysis of cells in biomedical microscopy images. We propose training deep learning models to pseudo-colorize masked cells. We use a physics-informed pseudo-spectral colormap that is well suited for colorizing cell topology. Our experiments reveal that approximating semantic segmentation by pseudo-colorization is beneficial for subsequent fine-tuning on cell detection. Inspired by the recent success of masked image modeling, we additionally mask out cell parts and train to reconstruct these parts to further enrich the learned representations. We compare our pre-training method with self-supervised frameworks including contrastive learning (SimCLR), masked autoencoders (MAEs), and edge-based self-supervision. We build upon our previous work and train hybrid models for cell detection, which contain both convolutional and vision transformer modules. Our pre-training method can outperform SimCLR, MAE-like masked image modeling, and edge-based self-supervision when pre-training on a diverse set of six fluorescence microscopy datasets. Code is available at: https://github.com/roydenwa/pseudo-colorize-masked-cells.

Removal of diclofenac by adsorption process studied in free-base porphyrin Zr-metal organic frameworks (Zr-MOFs)

As the world population continues to grow, there is also a rising concern regarding water pollution since this condition could negatively impact the supply of clean water. One of the most recent concerns is related to the pollution that comes from various pharmaceuticals, in particular non-steroidal anti-inflammatory drugs (NSAIDs) since they have been industrially produced at large scale and can be easily purchased as an over-the-counter medicine. Diclofenac is one of the most popular NSAIDs because of its high-effectiveness, which leads to its excessive consumption. Consequently, its presence in water bodies is also continuously increasing. An adsorption process could then be employed as a highly effective method to address this issue. In comparison to other conventional adsorbents such as activated carbon, the use of metal-organic frameworks (MOFs) as an alternative adsorbent is very attractive since it can offer various advantages such as tailorability and high adsorption capacity. In this study, the performance of three water-stable, free-base porphyrin MOFs assembled using zirconia-based nodes, namely MOF-525, MOF-545, and NU-902, for diclofenac adsorption was thoroughly investigated. Interestingly, although all three free-base porphyrin MOFs are assembled using the same building block and have a similar specific surface area (based on the experimental argon physisorption and calculation based on non-localized density functional theory), their diclofenac adsorption capacity is substantially different from one another. It is found that the highest diclofenac adsorption capacity is shown by MOF-525, which has maximum capacity around 792 mg g^-1. This is then followed by MOF-545 and NU-902 that have adsorption capacities around 591 and 486 mg g^-1, respectively. Some possible adsorption mechanisms are then thoroughly discussed that might contribute to this phenomenon. Lastly, their performance is also compared with other MOFs that are also studied for this purpose to show their performance superiority not only in terms of adsorption capacity but also their affinity towards the diclofenac molecule, which might be useful as an adsorption performance indicator in the real condition where the contaminant concentration is considerably low.

Efficient noble metal promoted bimetallic cobalt catalysts in the selective synthesis of acetaldehyde dimethyl acetal

Herein we report the one-pot cobalt catalysed synthesis of the dimethylacetal of acetaldehyde from synthesis gas and methanol. The product can be used as a fuel additive either as it is or after transacetalisation with long-chain alcohols. The product is obtained at moderate temperatures in good selectivities and high CO-conversions. A variation of the promotor metal (Au, Pt, Pd, and Ru) and of the support (γ-Al₂O₃ and CeO₂) in the catalyst was conducted, which showed a great impact of both the support and promotor on the activity and structure of the catalyst. Furthermore, a specific variation of temperatures and pressure for the most active catalyst and a model catalyst was conducted giving an interesting insight into ongoing processes.

Charge controlled interactions between DNA-modified silica nanoparticles and fluorosurfactants in microfluidic water-in-oil droplets

Microfluidic droplets are an important tool for studying and mimicking biological systems, e.g., to examine with high throughput the interaction of biomolecular components and the functionality of natural cells, or to develop basic principles for the engineering of artificial cells. Of particular importance is the approach to generate a biomimetic membrane by supramolecular self-assembly of nanoparticle components dissolved in the aqueous phase of the droplets at the inner water/oil interface, which can serve both to mechanically reinforce the droplets and as an interaction surface for cells and other components. While this interfacial assembly driven by electrostatic interaction of surfactants is quite well developed for water/mineral oil (W/MO) systems, no approaches have yet been described to exploit this principle for water/fluorocarbon oil (W/FO) emulsion droplets. Since W/FO systems exhibit not only better compartmentalization but also gas solubility properties, which is particularly crucial for live cell encapsulation and cultivation, we report here the investigation of charged fluorosurfactants for the self-assembly of DNA-modified silica nanoparticles (SiNP-DNA) at the interface of microfluidic W/FO emulsions. To this end, an efficient multicomponent Ugi reaction was used to synthesize the novel fluorosurfactant M4SURF to study the segregation and accumulation of negatively charged SiNP-DNA at the inner interface of microfluidic droplets. Comparative measurements were performed with the negatively charged fluorosurfactant KRYTOX, which can also induce SiNP-DNA segregation in the presence of cations. The segregation dynamics is characterized and preliminary results of cell encapsulation in the SiNP-DNA functionalized droplets are shown.

Reprocessed precise science orbits and gravity field recovery for the entire GOCE mission

ESA's Gravity field and steady-state Ocean Circulation Explorer (GOCE) orbited the Earth between 2009 and 2013 for the determination of the static part of Earth's gravity field. The GPS-derived precise science orbits (PSOs) were operationally generated by the Astronomical Institute of the University of Bern (AIUB). Due to a significantly improved understanding of remaining artifacts after the end of the GOCE mission (especially in the GOCE gradiometry data), ESA initiated a reprocessing of the entire GOCE Level 1b data in 2018. In this framework, AIUB was commissioned to recompute the GOCE reduced-dynamic and kinematic PSOs. In this paper, we report on the employed precise orbit determination methods, with a focus on measures undertaken to mitigate ionosphere-induced artifacts in the kinematic orbits and thereof derived gravity field models. With respect to the PSOs computed during the operational phase of GOCE, the reprocessed PSOs show in average a 8-9% better consistency with GPS data, 31% smaller 3-dimensional reduced-dynamic orbit overlaps, an 8% better 3-dimensional consistency between reduced-dynamic and kinematic orbits, and a 3-7% reduction of satellite laser ranging residuals. In the second part of the paper, we present results from GPS-based gravity field determinations that highlight the strong benefit of the GOCE reprocessed kinematic PSOs. Due to the applied data weighting strategy, a substantially improved quality of gravity field coefficients between degree 10 and 40 is achieved, corresponding to a remarkable reduction of ionosphere-induced artifacts along the geomagnetic equator. For a static gravity field solution covering the entire mission period, geoid height differences with respect to a superior inter-satellite ranging solution are markedly reduced (43% in terms of global RMS, compared to previous GOCE GPS-based gravity fields). Furthermore, we demonstrate that the reprocessed GOCE PSOs allow to recover long-wavelength time-variable gravity field signals (up to degree 10), comparable to information derived from GPS data of dedicated satellite missions. To this end, it is essential to take into account the GOCE common-mode accelerometer data in the gravity field recovery.

Disclosing the leaching behaviour of Pd@CMK3 catalysts in formic acid decomposition by electron tomography

Supported nanocatalysts exhibit different performances in batch and fixed bed reactors for a wide range of liquid phase catalytic reactions due to differences in metal leaching. To investigate this leaching process and its influence on the catalytic performance, a quantitative 3D characterization of the particle size and the particle distribution is important to follow the structural evolution of the active metal catalysts supported on porous materials during the reaction. In this work, electron tomography has been applied to uncover leaching and redeposition of a Pd@CMK3 catalyst during formic acid decomposition in batch and fixed bed reactors. The 3D distribution of Pd NPs on the mesoporous carbon CMK3 has been determined by a quantitative tomographic analysis and the determined structural changes are correlated with the observed differences in activity and stability of formic acid decomposition using batch and fixed bed reactors.

Elucidating the functional roles of prokaryotic proteins using big data and artificial intelligence

Annotating protein sequences according to their biological functions is one of the key steps in understanding microbial diversity, metabolic potentials, and evolutionary histories. However, even in the best-studied prokaryotic genomes, not all proteins can be characterized by classical in vivo, in vitro, and/or in silico methods-a challenge rapidly growing alongside the advent of next-generation sequencing technologies and their enormous extension of 'omics' data in public databases. These so-called hypothetical proteins (HPs) represent a huge knowledge gap and hidden potential for biotechnological applications. Opportunities for leveraging the available 'Big Data' have recently proliferated with the use of artificial intelligence (AI). Here, we review the aims and methods of protein annotation and explain the different principles behind machine and deep learning algorithms including recent research examples, in order to assist both biologists wishing to apply AI tools in developing comprehensive genome annotations and computer scientists who want to contribute to this leading edge of biological research.

Macroporous Silicone Chips for Decoding Microbial Dark Matter in Environmental Microbiomes

Natural evolution has produced an almost infinite variety of microorganisms that can colonize almost any conceivable habitat. Since the vast majority of these microbial consortia are still unknown, there is a great need to elucidate this "microbial dark matter" (MDM) to enable exploitation in biotechnology. We report the fabrication and application of a novel device that integrates a matrix of macroporous elastomeric silicone foam (MESIF) into an easily fabricated and scalable chip design that can be used for decoding MDM in environmental microbiomes. Technical validation, performed with the model organism Escherichia coli expressing a fluorescent protein, showed that this low-cost, bioinert, and widely modifiable chip is rapidly colonized by microorganisms. The biological potential of the chip was then illustrated through targeted sampling and enrichment of microbiomes in a variety of habitats ranging from wet, turbulent moving bed biofilters and wastewater treatment plants to dry air-based environments. Sequencing analyses consistently showed that MESIF chips are not only suitable for sampling with high robustness but also that the material can be used to detect a broad cross section of microorganisms present in the habitat in a short time span of a few days. For example, results from the biofilter habitat showed efficient enrichment of microorganisms belonging to the enigmatic Candidate Phyla Radiation, which comprise ∼70% of the MDM. From dry air, the MESIF chip was able to enrich a variety of members of Actinobacteriota, which is known to produce specific secondary metabolites. Targeted sampling from a wastewater treatment plant where the herbicide glyphosate was added to the chip's reservoir resulted in enrichment of Cyanobacteria and Desulfobacteria, previously associated with glyphosate degradation. These initial case studies suggest that this chip is very well suited for the systematic study of MDM and opens opportunities for the cultivation of previously unculturable microorganisms.

Pt nanoparticles under oxidizing conditions - implications of particle size, adsorption sites and oxygen coverage on stability

Platinum nanoparticles are efficient catalysts for different reactions, such as oxidation of carbon and nitrogen monoxides. Adsorption and interaction of oxygen with the nanoparticle surface, taking place under reaction conditions, determine not only the catalytic efficiency but also the stability of the nanoparticles against oxidation. In this study, platinum nanoparticles in oxygen environment are investigated by systematic screening of initial nanoparticle-oxygen configurations and employing density functional theory and a thermodynamics-based approach. The structures formed at low oxygen coverages are described by adsorption of atomic oxygen on the nanoparticles whereas at high coverages oxide-like species are formed. The relative stability of adsorption configurations at different oxygen coverages, including the phase of fully oxidized nanoparticles, is investigated by constructing p-T phase diagrams for the studied systems.

Copper Complexes of 1,4-Naphthoquinone Containing Thiosemicarbazide and Triphenylphosphine Oxide Moieties; Synthesis and Identification by NMR, IR, Mass, UV Spectra, and DFT Calculations

New 1,4-naphthoquinone derived by triphenylphosphaneylidene (Ph₃P) and N-substituted-hydrazine-1-carbothioamides were obtained during a one-pot reaction of 2,3-dichloro-1,4-naphthoquinone with thiosemicarbazides, Ph₃P and in the presence of triethyl amine (Et₃N) as a catalyst. The structure of the ligands was established by ESI, IR, and NMR spectra, in addition to elemental analyses and X-ray structure analysis. On subjecting the newly prepared ligands with CuCl₂ and Ph₃P, autoxidation occurs, and (E)-(2-(1,4-dioxo-3-(triphenyl phosphanylidene)-3,4-dihydronaphthalen-2(1H)-ylidene)carbamothioyl)hydrazinyl)-((triphenylphosphanyl)oxy)copper derivatives were formed in very good yields. The structure of the obtained complexes was proved by ESI, IR, NMR, and UV spectra, in addition to elemental analyses and theoretical calculations.

Quantification of Isomaltulose in Food Products by Using Heteronuclear Single Quantum Coherence NMR-Experiments

Isomaltulose is a commonly used sweetener in sports nutrition and in products intended for consumption by diabetics. Because previously established chromatographic methods for quantification of isomaltulose suffer from long analysis times (60–210 min), faster quantitative approaches are required. Here, an HSQC (heteronuclear single quantum coherence) experiment with reduced interscan delay was established in order to quantify isomaltulose next to potential additional sugars such as d-glucose, d-fructose, d-galactose, sucrose, lactose, and maltose in 53 min. By using HSQC coupled to non-uniform sampling (NUS) as well as ASAP-HSQC (acceleration by sharing adjacent polarization), analysis times were reduced to a few minutes. Application of NUS-HSQC with reduced interscan delay takes 27 min, resulting in accurate and precise data. In principle, application of ASAP-HSQC approaches (with analysis times as low as 6 min) can be used; however, precision data may not suffice all applications.

Overexpression of the Potato Monosaccharide Transporter StSWEET7a Promotes Root Colonization by Symbiotic and Pathogenic Fungi by Increasing Root Sink Strength

Root colonization by filamentous fungi modifies sugar partitioning in plants by increasing the sink strength. As a result, a transcriptional reprogramming of sugar transporters takes place. Here we have further advanced in the characterization of the potato SWEET sugar transporters and their regulation in response to the colonization by symbiotic and pathogenic fungi. We previously showed that root colonization by the AM fungus Rhizophagus irregularis induces a major transcriptional reprogramming of the 35 potato SWEETs, with 12 genes induced and 10 repressed. In contrast, here we show that during the early colonization phase, the necrotrophic fungus Fusarium solani only induces one SWEET transporter, StSWEET7a, while represses most of the others (25). StSWEET7a was also induced during root colonization by the hemi-biotrophic fungus Fusarium oxysporum f. sp. tuberosi. StSWEET7a which belongs to the clade II of SWEET transporters localized to the plasma membrane and transports glucose, fructose and mannose. Overexpression of StSWEET7a in potato roots increased the strength of this sink as evidenced by an increase in the expression of the cell wall-bound invertase. Concomitantly, plants expressing StSWEET7a were faster colonized by R. irregularis and by F. oxysporum f. sp. tuberosi. The increase in sink strength induced by ectopic expression of StSWEET7a in roots could be abolished by shoot excision which reverted also the increased colonization levels by the symbiotic fungus. Altogether, these results suggest that AM fungi and Fusarium spp. might induce StSWEET7a to increase the sink strength and thus this gene might represent a common susceptibility target for root colonizing fungi.

Basophil Activation to Gluten and Non-Gluten Proteins in Wheat-Dependent Exercise-Induced Anaphylaxis

Wheat-dependent exercise-induced anaphylaxis (WDEIA) is a cofactor-induced wheat allergy. Gluten proteins, especially ω5-gliadins, are known as major allergens, but partially hydrolyzed wheat proteins (HWPs) also play a role. Our study investigated the link between the molecular composition of gluten or HWP and allergenicity. Saline extracts of gluten (G), gluten with reduced content of ω5-gliadins (G-ω5), slightly treated HWPs (sHWPs), and extensively treated HWPs (eHWPs) were prepared as allergen test solutions and their allergenicity assessed using the skin prick test and basophil activation test (BAT) on twelve patients with WDEIA and ten controls. Complementary sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE), high-performance liquid chromatography (HPLC), and mass spectrometry (MS) analyses revealed that non-gluten proteins, mainly α-amylase/trypsin inhibitors (ATIs), were predominant in the allergen test solutions of G, G-ω5, and sHWPs. Only eHWPs contained gliadins and glutenins as major fraction. All allergen test solutions induced significantly higher %CD63⁺ basophils/anti-FcεRI ratios in patients compared with controls. BAT using sHWPs yielded 100% sensitivity and 83% specificity at optimal cut-off and may be useful as another tool in WDEIA diagnosis. Our findings indicate that non-gluten proteins carrying yet unidentified allergenic epitopes appear to be relevant in WDEIA. Further research is needed to clarify the role of nutritional ATIs in WDEIA and identify specific mechanisms of immune activation.

Local Electrical Impedance Mapping of the Atria: Conclusions on Substrate Properties and Confounding Factors

The treatment of atrial fibrillation and other cardiac arrhythmias as a major cause of cardiovascular hospitalization has remained a challenge predominantly for patients with severely remodeled substrate. Individualized ablation strategies are extremely important both for pulmonary vein isolation and subsequent ablations. Current approaches to identifying arrhythmogenic regions rely on electrogram-based features such as activation time and voltage. Novel technologies now enable clinical assessment of the local impedance as tissue property. Previous studies demonstrated its use for ablation monitoring and indicated its potential to differentiate healthy substrate, scar, and pathological tissue. This study investigates the potential of local electrical impedance-based substrate mapping of the atria for human in-vivo data. The presented pipeline for impedance mapping particularly contains options for dealing with undesirable effects originating from cardiac motion, catheter motion, or proximity to other intracardiac devices. Bloodpool impedance was automatically determined as a patient-specific reference. Full-chamber, left atrial impedance maps were drawn up from interpolating the measured impedances to the atrial endocardium. Finally, the origin and magnitude of oscillations of the raw impedance recording were probed into. The most dominant reason for exclusion of impedance samples was the loss of endocardial contact. With median elevations above the bloodpool impedance between 29 and 46 Ω, the impedance within the pulmonary veins significantly exceeded the remaining atrial walls presenting median elevations above the bloodpool impedance between 16 and 20 Ω. Previous ablation lesions were distinguished from their surroundings by a significant drop in local impedance while the corresponding regions did not differ for the control group. The raw impedance was found to oscillate with median amplitudes between 6 and 17 Ω depending on the patient. Oscillations were traced back to an interplay of atrial, ventricular, and respiratory motion. In summary, local impedance measurements demonstrated their capability to distinguish pathological atrial tissue from physiological substrate. Methods to limit the influence of confounding factors that still hinder impedance mapping were presented. Measurements at different frequencies or the combination of multiple electrodes could lead to further improvement. The presented examples indicate that electrogram- and impedance-based substrate mapping have the potential to complement each other toward better patient outcomes in future.

Sequence-independent activation of photocycloadditions using two colours of light

We exploit two reactive chromophores to establish sequence-independent photochemical activation, employing ortho-methyl benzaldehyde (oMBA) and N,N-(dimethylamino)pyrene aryl tetrazole (APAT) with N-(2-hydroxy)ethyl maleimide (NHEM), without any additives. Critically, the order of the irradiation sequence is irrelevant, as the shorter wavelength does not activate the higher wavelength activated species. Therefore, full sequence-independent λ-orthogonality is achieved through differences in both the reaction quantum yields (Φ r,oMBA and Φ r,APAT) and wavelength-dependent reactivity profiles of the employed chromophores.

A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction

Automatic cell segmentation and tracking enables to gain quantitative insights into the processes driving cell migration. To investigate new data with minimal manual effort, cell tracking algorithms should be easy to apply and reduce manual curation time by providing automatic correction of segmentation errors. Current cell tracking algorithms, however, are either easy to apply to new data sets but lack automatic segmentation error correction, or have a vast set of parameters that needs either manual tuning or annotated data for parameter tuning. In this work, we propose a tracking algorithm with only few manually tunable parameters and automatic segmentation error correction. Moreover, no training data is needed. We compare the performance of our approach to three well-performing tracking algorithms from the Cell Tracking Challenge on data sets with simulated, degraded segmentation—including false negatives, over- and under-segmentation errors. Our tracking algorithm can correct false negatives, over- and under-segmentation errors as well as a mixture of the aforementioned segmentation errors. On data sets with under-segmentation errors or a mixture of segmentation errors our approach performs best. Moreover, without requiring additional manual tuning, our approach ranks several times in the top 3 on the 6^th edition of the Cell Tracking Challenge.

Nature of Fast Relaxation Processes and Spectroscopy of a Membrane-Active Peptide Modified with Fluorescent Amino Acid Exhibiting Excited State Intramolecular Proton Transfer and Efficient Stimulated Emission

A fluorescently labeled peptide that exhibited fast excited state intramolecular proton transfer (ESIPT) was synthesized, and the nature of its electronic properties was comprehensively investigated, including linear photophysical and photochemical characterization, specific relaxation processes in the excited state, and its stimulated emission ability. The steady-state absorption, fluorescence, and excitation anisotropy spectra, along with fluorescence lifetimes and emission quantum yields, were obtained in liquid media and analyzed based on density functional theory quantum-chemical calculations. The nature of ESIPT processes of the peptide's chromophore moiety was explored using a femtosecond transient absorption pump-probe technique, revealing relatively fast ESIPT velocity (∼10 ps) in protic MeOH at room temperature. Efficient superluminescence properties of the peptide were realized upon femtosecond excitation in the main long-wavelength absorption band with a corresponding threshold of the pump pulse energy of ∼1.5 μJ. Quantum-chemical analysis of the electronic structure of the peptide was performed using the density functional theory/time-dependent density functional theory level of theory, affording good agreement with experimental data.