Showing papers by "Jožef Stefan Institute published in 2021"

A comprehensive review on plasmonic-based biosensors used in viral diagnostics.

Abstract: The proliferation and transmission of viruses has become a threat to worldwide biosecurity, as exemplified by the current COVID-19 pandemic. Early diagnosis of viral infection and disease control have always been critical. Virus detection can be achieved based on various plasmonic phenomena, including propagating surface plasmon resonance (SPR), localized SPR, surface-enhanced Raman scattering, surface-enhanced fluorescence and surface-enhanced infrared absorption spectroscopy. The present review covers all available information on plasmonic-based virus detection, and collected data on these sensors based on several parameters. These data will assist the audience in advancing research and development of a new generation of versatile virus biosensors.

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease.

Abstract: The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput x-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (Mpro), which is essential for viral replication. In contrast to commonly applied x-ray fragment screening experiments with molecules of low complexity, our screen tested already-approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to Mpro In subsequent cell-based viral reduction assays, one peptidomimetic and six nonpeptidic compounds showed antiviral activity at nontoxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2.

Chemical Aspects of Human and Environmental Overload with Fluorine

Abstract: Over the last 100-120 years, due to the ever-increasing importance of fluorine-containing compounds in modern technology and daily life, the explosive development of the fluorochemical industry led to an enormous increase of emission of fluoride ions into the biosphere. This made it more and more important to understand the biological activities, metabolism, degradation, and possible environmental hazards of such substances. This comprehensive and critical review focuses on the effects of fluoride ions and organofluorine compounds (mainly pharmaceuticals and agrochemicals) on human health and the environment. To give a better overview, various connected topics are also discussed: reasons and trends of the advance of fluorine-containing pharmaceuticals and agrochemicals, metabolism of fluorinated drugs, withdrawn fluorinated drugs, natural sources of organic and inorganic fluorine compounds in the environment (including the biosphere), sources of fluoride intake, and finally biomarkers of fluoride exposure.

COCO: a platform for comparing continuous optimizers in a black-box setting

Abstract: COCO is a platform for Comparing Continuous Optimizers in a black-box setting. It aims at automatizing the tedious and repetitive task of benchmarking numerical optimization algorithms to the greatest possible extent. We present the rationals behind the development of the platform as a general proposition for a guideline towards better benchmarking. We detail underlying fundamental concepts of COCO such as its definition of a problem, the idea of instances, the relevance of target values, and runtime as central performance measure. Finally, we give a quick overview of the basic code structure and the available test suites.

Cutting edge development on graphene derivatives modified by liquid crystal and CdS/TiO2 hybrid matrix: optoelectronics and biotechnological aspects

Abstract: Two dimensional (2D) graphene and its derivatives modification with nanomaterials for formation of hybrid/nanocomposites undergo stimulus-induced optical and electrical changes which are important ...

Green Synthesis of Silver Nanoparticles with Antibacterial Activity Using Various Medicinal Plant Extracts: Morphology and Antibacterial Efficacy.

Abstract: A green synthetic route for the production of silver nanoparticles (AgNPs) using five different aqueous plant extracts, namely, Berberis vulgaris, Brassica nigra, Capsella bursa-pastoris, Lavandula angustifolia and Origanum vulgare, was investigated in this study. The present work demonstrates the influence of plant extract composition (antioxidant and total phenolic content) on the size and morphology of the produced AgNPs. The biosynthetic procedure was rapid and simple and was easily monitored via colour changes and ultraviolet and visible (UV-Vis) spectroscopy. Subsequently, measurement of zeta potential (ZP), photon cross-correlation spectroscopy (PCCS), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM) and selected area electron diffraction (SAED) analysis were employed to characterise the as-synthesised nanoparticles. The XRD investigation confirmed the presence of Ag0 in the nanoparticles, and interactions between the bioactive compounds of the plants and the produced AgNPs were evident in the FTIR spectra. TEM indicated that the nanoparticles exhibited a bimodal size distribution, with the smaller particles being spherical and the larger having a truncated octahedron shape. In addition, the antimicrobial activity of the AgNPs was tested against five bacterial strains. All synthesised nanoparticles exhibited enhanced antimicrobial activity at a precursor concentration of 5 mM compared to the control substance, gentamicin sulphate, with the best results observed for AgNPs prepared with B. nigra and L. angustifolia extracts.

Test of lepton flavor universality and search for lepton flavor violation in B → Kℓℓ decays

Abstract: We present measurements of the branching fractions for the decays B → Kμ+μ− and B → Ke+e−, and their ratio (RK), using a data sample of 711 fb−1 that contains 772 × 106 $$ B\overline{B} $$ events. The data were collected at the ϒ(4S) resonance with the Belle detector at the KEKB asymmetric-energy e+e− collider. The ratio RK is measured in five bins of dilepton invariant-mass-squared (q2): q2 ∈ (0.1, 4.0), (4.00, 8.12), (1.0, 6.0), (10.2, 12.8) and (> 14.18) GeV2/c4, along with the whole q2 region. The RK value for q2 ∈ (1.0, 6.0) GeV2/c4 is $$ {1.03}_{-0.24}^{+0.28} $$ ± 0.01. The first and second uncertainties listed are statistical and systematic, respectively. All results for RK are consistent with Standard Model predictions. We also measure CP-averaged isospin asymmetries in the same q2 bins. The results are consistent with a null asymmetry, with the largest difference of 2.6 standard deviations occurring for the q2 ∈ (1.0, 6.0) GeV2/c4 bin in the mode with muon final states. The measured differential branching fractions, $$ d\mathrm{\mathcal{B}} $$ /dq2, are consistent with theoretical predictions for charged B decays, while the corresponding values are below the expectations for neutral B decays. We have also searched for lepton-flavor-violating B → Kμ±e∓ decays and set 90% confidence-level upper limits on the branching fraction in the range of 10−8 for B+ → K+μ±e∓, and B0 → K0μ±e∓ modes.

Dry reforming of methane over Ni/Ce0.8Ti0.2O2-δ: The effect of Ni particle size on the carbon pathways studied by transient and isotopic techniques

Abstract: The effects of Ni particle size (dNi ∼ 22–45 nm) of Ni/Ce0.8Ti0.2O2-δ on the carbon paths in the dry reforming of methane at 750 °C have been investigated by various transient and isotopic experiments. The aim was to provide new insights for improving catalyst’s coke-resistance. Various correlations have been derived between dNi and (i) the initial kinetic rates (per Ni particle) of CH4 dissociation and CO disproportionation reactions along with their respective amounts of carbon accumulation, (ii) the integral rates of CH4 conversion and CO formation and the amount of carbon deposition in the DRM, and (iii) the rate of carbon removal by lattice oxygen of support compared to that by oxygen formed via the CO2 activation route during DRM. The former rate was found larger than the latter one independent of dNi (nm). CH4 dissociation is the exclusive route of inactive carbon formation during DRM independent of dNi.

Unravelling the multi-scale structure-property relationship of laser powder bed fusion processed and heat-treated AlSi10Mg.

Abstract: Tailoring heat treatments for Laser Powder Bed Fusion (LPBF) processed materials is critical to ensure superior and repeatable material properties for high-end applications. This tailoring requires in-depth understanding of the LPBF-processed material. Therefore, the current study aims at unravelling the threefold interrelationship between the process (LPBF and heat treatment), the microstructure at different scales (macro-, meso-, micro-, and nano-scale), and the macroscopic material properties of AlSi10Mg. A similar solidification trajectory applies at different length scales when comparing the solidification of AlSi10Mg, ranging from mould-casting to rapid solidification (LPBF). The similarity in solidification trajectories triggers the reason why the Brody-Flemings cellular microsegregation solidification model could predict the cellular morphology of the LPBF as-printed microstructure. Where rapid solidification occurs at a much finer scale, the LPBF microstructure exhibits a significant grain refinement and a high degree of silicon (Si) supersaturation. This study has identified the grain refinement and Si supersaturation as critical assets of the as-printed microstructure, playing a vital role in achieving superior mechanical and thermal properties during heat treatment. Next, an electrical conductivity model could accurately predict the Si solute concentration in LPBF-processed and heat-treated AlSi10Mg and allows understanding the microstructural evolution during heat treatment. The LPBF-processed and heat-treated AlSi10Mg conditions (as-built (AB), direct-aged (DA), stress-relieved (SR), preheated (PH)) show an interesting range of superior mechanical properties (tensile strength: 300-450 MPa, elongation: 4-13%) compared to the mould-cast T6 reference condition.

A critical review on multifunctional smart materials ‘nanographene’ emerging avenue: nano-imaging and biosensor applications

Abstract: Smart electronic materials ‘nanographene’ stated, its significant authentication has undergone massive improvements and has emerged as a ‘material of the century’ in materialize fields of ‘Chemical...

The essentials of marine biotechnology.

Abstract: Coastal countries have traditionally relied on the existing marine resources (e.g., fishing, food, transport, recreation, and tourism) as well as tried to support new economic endeavors (ocean energy, desalination for water supply, and seabed mining). Modern societies and lifestyle resulted in an increased demand for dietary diversity, better health and well-being, new biomedicines, natural cosmeceuticals, environmental conservation, and sustainable energy sources. These societal needs stimulated the interest of researchers on the diverse and underexplored marine environments as promising and sustainable sources of biomolecules and biomass, and they are addressed by the emerging field of marine (blue) biotechnology. Blue biotechnology provides opportunities for a wide range of initiatives of commercial interest for the pharmaceutical, biomedical, cosmetic, nutraceutical, food, feed, agricultural, and related industries. This article synthesizes the essence, opportunities, responsibilities, and challenges encountered in marine biotechnology and outlines the attainment and valorization of directly derived or bio-inspired products from marine organisms. First, the concept of bioeconomy is introduced. Then, the diversity of marine bioresources including an overview of the most prominent marine organisms and their potential for biotechnological uses are described. This is followed by introducing methodologies for exploration of these resources and the main use case scenarios in energy, food and feed, agronomy, bioremediation and climate change, cosmeceuticals, bio-inspired materials, healthcare, and well-being sectors. The key aspects in the fields of legislation and funding are provided, with the emphasis on the importance of communication and stakeholder engagement at all levels of biotechnology development. Finally, vital overarching concepts, such as the quadruple helix and Responsible Research and Innovation principle are highlighted as important to follow within the marine biotechnology field. The authors of this review are collaborating under the European Commission-funded Cooperation in Science and Technology (COST) Action Ocean4Biotech – European transdisciplinary networking platform for marine biotechnology and focus the study on the European state of affairs.

The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics.

Abstract: A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.

Magnetic Nanoparticles—A Multifunctional Potential Agent for Diagnosis and Therapy

Abstract: Magnetic nanoparticles gained considerable attention in last few years due to their remarkable properties. Superparamaganetism, non-toxicity, biocompatibility, chemical inertness, and environmental friendliness are some of the properties that make iron oxide nanoparticles (IONPs) an ideal choice for biomedical applications. Along with being easily tuneable and a tailored surface for conjugation of IONPs, their physio-chemical and biological properties can also be varied by modifying the basic parameters for synthesis that enhances the additional possibilities for designing novel magnetic nanomaterial for theranostic applications. This review highlights the synthesis, surface modification, and different applications of IONPs for diagnosis, imaging, and therapy. Furthermore, it also represents the recent report on the application of IONPs as enzyme mimetic compounds and a contrasting agent, and its significance in the field as an anticancer and antimicrobial agent.

Eigenstate thermalization hypothesis through the lens of autocorrelation functions

Abstract: Matrix elements of observables in eigenstates of generic Hamiltonians are described by the Srednicki ansatz within the eigenstate thermalization hypothesis (ETH). We study a quantum chaotic spin-fermion model in a one-dimensional lattice, which consists of a spin-1/2 XX chain coupled to a single itinerant fermion. In our study, we focus on translationally invariant observables including the charge and energy current, thereby also connecting the ETH with transport properties. Considering observables with a Hilbert-Schmidt norm of one, we first perform a comprehensive analysis of ETH in the model taking into account latest developments. A particular emphasis is on the analysis of the structure of the offdiagonal matrix elements $|\ensuremath{\langle}\ensuremath{\alpha}|\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{O}{|\ensuremath{\beta}\ensuremath{\rangle}|}^{2}$ in the limit of small eigenstate energy differences $\ensuremath{\omega}={E}_{\ensuremath{\beta}}\ensuremath{-}{E}_{\ensuremath{\alpha}}$. Removing the dominant exponential suppression of $|\ensuremath{\langle}\ensuremath{\alpha}|\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{O}{|\ensuremath{\beta}\ensuremath{\rangle}|}^{2}$, we find that (1) the current matrix elements exhibit a system-size dependence that is different from other observables under investigation and (2) matrix elements of several other observables exhibit a Drude-like structure with a Lorentzian frequency dependence. We then show how this information can be extracted from the autocorrelation functions as well. Finally, our study is complemented by a numerical analysis of the fluctuation-dissipation relation for eigenstates in the bulk of the spectrum. We identify the regime of $\ensuremath{\omega}$ in which the well-known fluctuation-dissipation relation is valid with high accuracy for finite systems.

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions.

Abstract: The human microbiome has emerged as a central research topic in human biology and biomedicine Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies

Immunotherapy of Glioblastoma: Current Strategies and Challenges in Tumor Model Development

Abstract: Glioblastoma is the most common brain malignant tumor in the adult population, and immunotherapy is playing an increasingly central role in the treatment of many cancers Nevertheless, the search for effective immunotherapeutic approaches for glioblastoma patients continues The goal of immunotherapy is to promote tumor eradication, boost the patient’s innate and adaptive immune responses, and overcome tumor immune resistance A range of new, promising immunotherapeutic strategies has been applied for glioblastoma, including vaccines, oncolytic viruses, immune checkpoint inhibitors, and adoptive cell transfer However, the main challenges of immunotherapy for glioblastoma are the intracranial location and heterogeneity of the tumor as well as the unique, immunosuppressive tumor microenvironment Owing to the lack of appropriate tumor models, there are discrepancies in the efficiency of various immunotherapeutic strategies between preclinical studies (with in vitro and animal models) on the one hand and clinical studies (on humans) on the other hand In this review, we summarize the glioblastoma characteristics that drive tolerance to immunotherapy, the currently used immunotherapeutic approaches against glioblastoma, and the most suitable tumor models to mimic conditions in glioblastoma patients These models are improving and can more precisely predict patients’ responses to immunotherapeutic treatments, either alone or in combination with standard treatment

Resolving the Dilemma of Fe-N-C Catalysts by the Selective Synthesis of Tetrapyrrolic Active Sites via an Imprinting Strategy.

Abstract: Combining the abundance and inexpensiveness of their constituent elements with their atomic dispersion, atomically dispersed Fe-N-C catalysts represent the most promising alternative to precious-metal-based materials in proton exchange membrane (PEM) fuel cells. Due to the high temperatures involved in their synthesis and the sensitivity of Fe ions toward carbothermal reduction, current synthetic methods are intrinsically limited in type and amount of the desired, catalytically active Fe-N4 sites, and high active site densities have been out of reach (dilemma of Fe-N-C catalysts). We herein identify a paradigm change in the synthesis of Fe-N-C catalysts arising from the developments of other M-N-C single-atom catalysts. Supported by DFT calculations we propose fundamental principles for the synthesis of M-N-C materials. We further exploit the proposed principles in a novel synthetic strategy to surpass the dilemma of Fe-N-C catalysts. The selective formation of tetrapyrrolic Zn-N4 sites in a tailor-made Zn-N-C material is utilized as an active-site imprint for the preparation of a corresponding Fe-N-C catalyst. By successive low- and high-temperature ion exchange reactions, we obtain a phase-pure Fe-N-C catalyst, with a high loading of atomically dispersed Fe (>3 wt %). Moreover, the catalyst is entirely composed of tetrapyrrolic Fe-N4 sites. The density of tetrapyrrolic Fe-N4 sites is more than six times as high as for previously reported tetrapyrrolic single-site Fe-N-C fuel cell catalysts.

Shining dark matter in XENON1T

Abstract: We point out that a nonrelativistic approximately 2 GeV dark matter (DM) which interacts with visible matter through higher-dimensional Rayleigh operators could explain the excess of ``electron recoil'' events recently observed by the XENON1T Collaboration A DM scattering event results in a few keV photon that on average carries most of the deposited energy, while the nuclear recoil energy is only a subleading correction Since the XENON1T detector does not discriminate between electrons and photons, such events would be interpreted as excess of the keV electrons Indirect constraints from dark matter annihilation are avoided for light mediators of $\mathcal{O}(10\text{ }\text{ }\mathrm{MeV})$ that have sizable couplings to neutrinos One-loop induced spin-independent scattering in dark matter may soon lead to a confirmation signal or already excludes regions of viable parameter space for the Rayleigh DM model, depending on what the exact values of the unknown nonperturbative nuclear matrix elements are

Atomic scale symmetry and polar nanoclusters in the paraelectric phase of ferroelectric materials.

Abstract: The nature of the “forbidden” local- and long-range polar order in nominally non-polar paraelectric phases of ferroelectric materials has been an open question since the discovery of ferroelectricity in oxide perovskites, ABO3. A currently considered model suggests locally correlated displacements of B-site atoms along a subset of cubic directions. Such off-site displacements have been confirmed experimentally; however, being essentially dynamic in nature they cannot account for the static nature of the symmetry-forbidden polarization implied by the macroscopic experiments. Here, in an atomically resolved study by aberration-corrected scanning transmission electron microscopy complemented by Raman spectroscopy, we reveal, directly visualize and quantitatively describe static, 2–4 nm large polar nanoclusters in the nominally non-polar cubic phases of (Ba,Sr)TiO3 and BaTiO3. These results have implications on understanding of the atomic-scale structure of disordered materials, the origin of precursor states in ferroelectrics, and may help answering ambiguities on the dynamic-versus-static nature of nano-sized clusters. The existence and atomic-level structure of the hypothetical polar nanoclusters above the Curie temperature is one of the oldest open questions in the physics of ferroelectrics. Here, the authors find the polar nanoclusters in the paraelectric phases of classical perovskite ferroelectrics.

On the molecular origins of the ferroelectric splay nematic phase.

Abstract: Nematic liquid crystals have been known for more than a century, but it was not until the 60s–70s that, with the development of room temperature nematics, they became widely used in applications. Polar nematic phases have been long-time predicted, but have only been experimentally realized recently. Synthesis of materials with nematic polar ordering at room temperature is certainly challenging and requires a deep understanding of its formation mechanisms, presently lacking. Here, we compare two materials of similar chemical structure and demonstrate that just a subtle change in the molecular structure enables denser packing of the molecules when they exhibit polar order, which shows that reduction of excluded volume is in the origin of the polar nematic phase. Additionally, we propose that molecular dynamics simulations are potent tools for molecular design in order to predict, identify and design materials showing the polar nematic phase and its precursor nematic phases. Nematic liquid crystals with polar order bear great potential for many applications but their rational design is difficult. Mandle et al. outline a set of design principles for this new phase of matter, guided by experiments and simulation, showing polar order to be driven by steric interactions.

Physics and applications of three-ion ICRF scenarios for fusion research

Abstract: This paper summarizes the physical principles behind the novel three-ion scenarios using radio frequency waves in the ion cyclotron range of frequencies (ICRF). We discuss how to transform mode conversion electron heating into a new flexible ICRF technique for ion cyclotron heating and fast-ion generation in multi-ion species plasmas. The theoretical section provides practical recipes for selecting the plasma composition to realize three-ion ICRF scenarios, including two equivalent possibilities for the choice of resonant absorbers that have been identified. The theoretical findings have been convincingly confirmed by the proof-of-principle experiments in mixed H–D plasmas on the Alcator C-Mod and JET tokamaks, using thermal 3He and fast D ions from neutral beam injection as resonant absorbers. Since 2018, significant progress has been made on the ASDEX Upgrade and JET tokamaks in H–4He and H–D plasmas, guided by the ITER needs. Furthermore, the scenario was also successfully applied in JET D–3He plasmas as a technique to generate fusion-born alpha particles and study effects of fast ions on plasma confinement under ITER-relevant plasma heating conditions. Tuned for the central deposition of ICRF power in a small region in the plasma core of large devices such as JET, three-ion ICRF scenarios are efficient in generating large populations of passing fast ions and modifying the q-profile. Recent experimental and modeling developments have expanded the use of three-ion scenarios from dedicated ICRF studies to a flexible tool with a broad range of different applications in fusion research.