DS-PACK: Tool assembly for the end-to-end support of controlled access human data sharing.

The EU General Data Protection Regulation (GDPR) requirements have prompted a shift from centralised controlled access genome-phenome archives to federated models for sharing sensitive human data. In a data-sharing federation, a central node facilitates data discovery; meanwhile, distributed nodes are responsible for handling data access requests, concluding agreements with data users and providing secure access to the data. Research institutions that want to become part of such federations often lack the resources to set up the required controlled access processes. The DS-PACK tool assembly is a reusable, open-source middleware solution that semi-automates controlled access processes end-to-end, from data submission to access. Data protection principles are engraved into all components of the DS-PACK assembly. DS-PACK centralises access control management and distributes access control enforcement with support for data access via cloud-based applications. DS-PACK is in production use at the ELIXIR Luxembourg data hosting platform, combined with an operational model including legal facilitation and data stewardship.

Bending and reverse bending during the fabrication of novel GaAs/(In,Ga)As/GaAs core-shell nanowires monitored byin situx-ray diffraction.

We report on the fabrication of a novel design of GaAs/(In,Ga)As/GaAs radial nanowire heterostructures on a Si 111 substrate, where, for the first time, the growth of inhomogeneous shells on a lattice mismatched core results in straight nanowires instead of bent. Nanowire bending caused by axial tensile strain induced by the (In,Ga)As shell on the GaAs core is reversed by axial compressive strain caused by the GaAs outer shell on the (In,Ga)As shell. Progressive nanowire bending and reverse bending in addition to the axial strain evolution during the two processes are accessed byin situby x-ray diffraction. The diameter of the core, thicknesses of the shells, as well as the indium concentration and distribution within the (In,Ga)As quantum well are revealed by 2D energy dispersive x-ray spectroscopy using a transmission electron microscope. Shell(s) growth on one side of the core without substrate rotation results in planar-like radial heterostructures in the form of free standing straight nanowires.

Dependence of the Structural and Magnetic Properties on the Growth Sequence in Heterostructures Designed by YbFeO3 and BaFe12O19.

The structure and the chemical composition of individual layers as well as of interfaces belonging to the two heterostructures M1 (BaFe12O19/YbFeO3/YSZ) and M2 (YbFeO3/BaFe12O19/YSZ) grown by pulsed laser deposition on yttria-stabilized zirconia (YSZ) substrates are deeply characterized by using a combination of methods such as high-resolution X-ray diffraction, transmission electron microscopy (TEM), and atomic-resolution scanning TEM with energy-dispersive X-ray spectroscopy. The temperature-dependent magnetic properties demonstrate two distinct heterostructures with different coercivity, anisotropy fields, and first anisotropy constants, which are related to the defect concentrations within the individual layers and to the degree of intermixing at the interface. The heterostructure with the stacking order BaFe12O19/YbFeO3, i.e., M1, exhibits a distinctive interface without any chemical intermixture, while an Fe-rich crystalline phase is observed in M2 both in atomic-resolution EDX maps and in mass density profiles. Additionally, M1 shows high c-axis orientation, which induces a higher anisotropy constant K1 as well as a larger coercivity due to a high number of phase boundaries. Despite the existence of a canted antiferromagnetic/ferromagnetic combination (T < 140 K), both heterostructures M1 and M2 do not reveal any detectable exchange bias at T = 50 K. Additionally, compressive residual strain on the BaM layer is found to be suppressing the ferromagnetism, thus reducing the Curie temperature (Tc) in the case of M1. These findings suggest that M1 (BaFe12O19/YbFeO3/YSZ) is suitable for magnetic storage applications.

Structural and Morphological Studies of Pt in the As-Grown and Encapsulated States and Dependency on Film Thickness.

The morphology and crystal structure of Pt films grown by pulsed laser deposition (PLD) on yttria-stabilized zirconia (YSZ)at high temperatures Tg = 900 °C was studied for four different film thicknesses varying between 10 and 70 nm. During the subsequent growth of the capping layer, the thermal stability of the Pt was strongly influenced by the Pt film's thickness. Furthermore, these later affected the film morphology, the crystal structure and hillocks size, and distribution during subsequent growth at Tg = 900 °C for a long duration. The modifications in the morphology as well as in the structure of the Pt film without a capping layer, named also as the as-grown and encapsulated layers in the bilayer system, were examined by a combination of microscopic and scattering methods. The increase in the thickness of the deposited Pt film brought three competitive phenomena into occurrence, such as 3D-2D morphological transition, dewetting, and hillock formation. The degree of coverage, film continuity, and the crystal quality of the Pt film were significantly improved by increasing the deposition time. An optimum Pt film thickness of 70 nm was found to be suitable for obtaining a hillock-free Pt bottom electrode which also withstood the dewetting phenomena revealed during the subsequent growth of capping layers. This achievement is crucial for the deposition of functional bottom electrodes in ferroelectric and multiferroic heterostructure systems.

BioKC: a collaborative platform for curation and annotation of molecular interactions.

Curation of biomedical knowledge into systems biology diagrammatic or computational models is essential for studying complex biological processes. However, systems-level curation is a laborious manual process, especially when facing ever-increasing growth of domain literature. New findings demonstrating elaborate relationships between multiple molecules, pathways and cells have to be represented in a format suitable for systems biology applications. Importantly, curation should capture the complexity of molecular interactions in such a format together with annotations of the involved elements and support stable identifiers and versioning. This challenge calls for novel collaborative tools and platforms allowing to improve the quality and the output of the curation process. In particular, community-based curation, an important source of curated knowledge, requires support in role management, reviewing features and versioning. Here, we present Biological Knowledge Curation (BioKC), a web-based collaborative platform for the curation and annotation of biomedical knowledge following the standard data model from Systems Biology Markup Language (SBML). BioKC offers a graphical user interface for curation of complex molecular interactions and their annotation with stable identifiers and supporting sentences. With the support of collaborative curation and review, it allows to construct building blocks for systems biology diagrams and computational models. These building blocks can be published under stable identifiers and versioned and used as annotations, supporting knowledge building for modelling activities.

The SYSCID map: a graphical and computational resource of molecular mechanisms across rheumatoid arthritis, systemic lupus erythematosus and inflammatory bowel disease.

Chronic inflammatory diseases (CIDs), including inflammatory bowel disease (IBD), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are thought to emerge from an impaired complex network of inter- and intracellular biochemical interactions among several proteins and small chemical compounds under strong influence of genetic and environmental factors. CIDs are characterised by shared and disease-specific processes, which is reflected by partially overlapping genetic risk maps and pathogenic cells (e.g., T cells). Their pathogenesis involves a plethora of intracellular pathways. The translation of the research findings on CIDs molecular mechanisms into effective treatments is challenging and may explain the low remission rates despite modern targeted therapies. Modelling CID-related causal interactions as networks allows us to tackle the complexity at a systems level and improve our understanding of the interplay of key pathways. Here we report the construction, description, and initial applications of the SYSCID map (https://syscid.elixir-luxembourg.org/), a mechanistic causal interaction network covering the molecular crosstalk between IBD, RA and SLE. We demonstrate that the map serves as an interactive, graphical review of IBD, RA and SLE molecular mechanisms, and helps to understand the complexity of omics data. Examples of such application are illustrated using transcriptome data from time-series gene expression profiles following anti-TNF treatment and data from genome-wide associations studies that enable us to suggest potential effects to altered pathways and propose possible mechanistic biomarkers of treatment response.

Effect of Underlayer Quality on Microstructure, Stoichiometry, and Magnetic Properties of Hexaferrite BaFe12O19 Grown on YSZ(111) by Pulsed Laser Deposition.

We have studied the effect of platinum underlayer for two deposited thicknesses on the microstructure, crystalline quality, morphology, chemical composition, and magnetic properties as well as magnetic domain formation of BaFe12O19 (BaM) grown on YSZ(111) by pulsed laser deposition (PLD). We found that PLD platinum deposited with a thickness of 25 nm cannot withstand the dewetting phenomenon occurring during the subsequent BaM layer growth. A smooth and continuous Pt underlayer that possesses a sharp interface and omits the intermixing between the BaM and substrate was successfully achieved for a deposited Pt film thickness of 75 nm. Independent of the thickness of the deposited Pt layer, the c-axis orientation as well as coercivity Hc and the anisotropy HA fields were significantly improved due to a remarkable improvement of lattice mismatch in comparison with the BaM layer grown without a Pt underlayer on YSZ(111). By applying high-resolution X-ray diffraction, scanning and transmission electron microscopy (SEM/TEM), and atomically resolved scanning TEM imaging combined with energy-dispersive X-ray spectroscopy, as well as atomic and magnetic force microscopy, a comprehensive investigation of both structure and chemical composition of the deposited BaM films and their interfacial regions was performed. This study aimed to correlate the enhancement of the overall magnetic properties and of the local spin magnetic domain orientation with the modification of BaM microstructure and chemical composition at the nanometer scale due to the Pt underlayer. Finally, we attempted to understand the mechanisms that control the magnetic properties of these BaM films in order to be able to tailor them.

Visualization of automatically combined disease maps and pathway diagrams for rare diseases.

Introduction: Investigation of molecular mechanisms of human disorders, especially rare diseases, require exploration of various knowledge repositories for building precise hypotheses and complex data interpretation. Recently, increasingly more resources offer diagrammatic representation of such mechanisms, including disease-dedicated schematics in pathway databases and disease maps. However, collection of knowledge across them is challenging, especially for research projects with limited manpower. Methods: In this article we present an automated workflow for construction of maps of molecular mechanisms for rare diseases. The workflow requires a standardized definition of a disease using Orphanet or HPO identifiers to collect relevant genes and variants, and to assemble a functional, visual repository of related mechanisms, including data overlays. The diagrams composing the final map are unified to a common systems biology format from CellDesigner SBML, GPML and SBML+layout+render. The constructed resource contains disease-relevant genes and variants as data overlays for immediate visual exploration, including embedded genetic variant browser and protein structure viewer. Results: We demonstrate the functionality of our workflow on two examples of rare diseases: Kawasaki disease and retinitis pigmentosa. Two maps are constructed based on their corresponding identifiers. Moreover, for the retinitis pigmentosa use-case, we include a list of differentially expressed genes to demonstrate how to tailor the workflow using omics datasets. Discussion: In summary, our work allows for an ad-hoc construction of molecular diagrams combined from different sources, preserving their layout and graphical style, but integrating them into a single resource. This allows to reduce time consuming tasks of prototyping of a molecular disease map, enabling visual exploration, hypothesis building, data visualization and further refinement. The code of the workflow is open and accessible at https://gitlab.lcsb.uni.lu/minerva/automap/.

A guide for developing comprehensive systems biology maps of disease mechanisms: planning, construction and maintenance.

As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.

Arena3Dweb: interactive 3D visualization of multilayered networks supporting multiple directional information channels, clustering analysis and application integration.

Arena3Dweb is an interactive web tool that visualizes multi-layered networks in 3D space. In this update, Arena3Dweb supports directed networks as well as up to nine different types of connections between pairs of nodes with the use of Bézier curves. It comes with different color schemes (light/gray/dark mode), custom channel coloring, four node clustering algorithms which one can run on-the-fly, visualization in VR mode and predefined layer layouts (zig-zag, star and cube). This update also includes enhanced navigation controls (mouse orbit controls, layer dragging and layer/node selection), while its newly developed API allows integration with external applications as well as saving and loading of sessions in JSON format. Finally, a dedicated Cytoscape app has been developed, through which users can automatically send their 2D networks from Cytoscape to Arena3Dweb for 3D multi-layer visualization. Arena3Dweb is accessible at http://arena3d.pavlopouloslab.info or http://arena3d.org.

Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses.

Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson's disease (PD), one of the most prevalent neurodegenerative disorders. Our approach is based on the PD-map, a comprehensive molecular interaction diagram that captures the key mechanisms involved in the initiation and progression of PD. Using Boolean modeling, we aim to gain a deeper understanding of the disease dynamics, identify potential drug targets, and simulate the response to treatments. Our analysis demonstrates the effectiveness of this approach in uncovering the intricacies of PD. Our results confirm existing knowledge about the disease and provide valuable insights into the underlying mechanisms, ultimately suggesting potential targets for therapeutic intervention. Moreover, our approach allows us to parametrize the models based on omics data for further disease stratification. Our study highlights the value of computational modeling in advancing our understanding of complex biological systems and diseases, emphasizing the importance of continued research in this field. Furthermore, our findings have potential implications for the development of novel therapies for PD, which is a pressing public health concern. Overall, this study represents a significant step forward in the application of computational modeling to the investigation of neurodegenerative diseases, and underscores the power of interdisciplinary approaches in tackling challenging biomedical problems.

Analysis: Flawed Datasets of Monkeypox Skin Images.

The self-proclaimed first publicly available dataset of Monkeypox skin images consists of medically irrelevant images extracted from Google and photography repositories through a process denominated web-scrapping. Yet, this did not stop other researchers from employing it to build Machine Learning (ML) solutions aimed at computer-aided diagnosis of Monkeypox and other viral infections presenting skin lesions. Neither did it stop the reviewers or editors from publishing these subsequent works in peer-reviewed journals. Several of these works claimed extraordinary performance in the classification of Monkeypox, Chickenpox and Measles, employing ML and the aforementioned dataset. In this work, we analyse the initiator work that has catalysed the development of several ML solutions, and whose popularity is continuing to grow. Further, we provide a rebuttal experiment that showcases the risks of such methodologies, proving that the ML solutions do not necessarily obtain their performance from the features relevant to the diseases at issue.

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net.

Protein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents. To address this challenge, we introduce the MINERVA Net web service, a repository of open-access disease maps allowing users to publicly share minimal information about their maps. The MINERVA Net repository provides REST API endpoints of particular disease maps, which then can be individually queried for content. In this article, we describe the concept of MINERVA Net and illustrate its use by comparing proteins and their interactions in three different disease maps.

Comparative Computational Screening of Natural-based Partial Agonists for PPARγ Receptor.

INTRODUCTION: The nuclear transcription factor PPARγ, which can modulate cell growth via proliferation and apoptosis-related mechanisms, is a promising target in cancer therapy. This study aims to focus on PPARγ as the target and use virtual screening to find hits. METHODS: A set of 5,677 flavonoid compounds were filtered by subjecting them to descriptor-based drug-likeness and ADMET strategies to discover drug-like compounds. The candidates' modes of binding to PPARγ were then evaluated using docking and MD simulation. PharmMapper was used to identify the potential targets of selected hits. The pharmacological network was constructed based on the GO and KEGG pathway analysis. RESULTS: In primary screening, 3,057 compounds met various drug-likeness criteria and docked well as partial agonists in the PPARγ-LBD. Five compounds (euchrenone b1, kaempferol-7-Orhamnoside, vincetoxicoside B, morusin, and karanjin) were selected with the use of ADMET profiles for further MD simulation investigation. Based on the PharmMapper findings, 52 proteins were then submitted to GO and KEGG enrichment analysis. As expected by GO and KEGG pathway enrichment studies, core targets were enriched in the PI3K-Akt signaling pathway (p < 0.01), indicating that certain chemicals may be involved in cancer processes. CONCLUSION: Our results suggested that the selected compounds might have sufficient drug-likeness, pharmacokinetics, and in silico bioactivity by acting as PPARγ partial agonists. Although much work remains to illuminate extensive cancer therapeutic/ chemopreventive efficacy of flavonoids in vivo, in silico methodology of our cheminformatics research may be able to provide additional data regarding the efficacy and safety of potential candidates for therapeutic targets.

Boolean modelling as a logic-based dynamic approach in systems medicine.

Molecular mechanisms of health and disease are often represented as systems biology diagrams, and the coverage of such representation constantly increases. These static diagrams can be transformed into dynamic models, allowing for in silico simulations and predictions. Boolean modelling is an approach based on an abstract representation of the system. It emphasises the qualitative modelling of biological systems in which each biomolecule can take two possible values: zero for absent or inactive, one for present or active. Because of this approximation, Boolean modelling is applicable to large diagrams, allowing to capture their dynamic properties. We review Boolean models of disease mechanisms and compare a range of methods and tools used for analysis processes. We explain the methodology of Boolean analysis focusing on its application in disease modelling. Finally, we discuss its practical application in analysing signal transduction and gene regulatory pathways in health and disease.

Smart Scheduling (SMASCH): multi-appointment scheduling system for longitudinal clinical research studies.

Objective: Facilitate the multi-appointment scheduling problems (MASPs) characteristic of longitudinal clinical research studies. Additional goals include: reducing management time, optimizing clinical resources, and securing personally identifiable information. Materials and methods: Following a model view controller architecture, we developed a web-based tool written in Python 3. Results: Smart Scheduling (SMASCH) system facilitates clinical research and integrated care programs in Luxembourg, providing features to better manage MASPs and speed up management tasks. It is available both as a Linux package and Docker image (https://smasch.pages.uni.lu). Discussion: The long-term requirements of longitudinal clinical research studies justify the employment of flexible and well-maintained frameworks and libraries through an iterative software life-cycle suited to respond to rapidly changing scenarios. Conclusions: SMASCH is a free and open-source scheduling system for clinical studies able to satisfy recent data regulations providing features for better data accountability. Better scheduling systems can help optimize several metrics that ultimately affect the success of clinical studies.

Effect of pulse laser frequency on PLD growth of LuFeO3 explained by kinetic simulations of in-situ diffracted intensities.

Atomistic processes during pulsed-laser deposition (PLD) growth influence the physical properties of the resulting films. We investigated the PLD of epitaxial layers of hexagonal LuFeO[Formula: see text] by measuring the X-ray diffraction intensity in the quasiforbidden reflection 0003 in situ during deposition. From measured X-ray diffraction intensities we determined coverages of each layer and studied their time evolution which is described by scaling exponent [Formula: see text] directly connected to the surface roughness. Subsequently we modelled the growth using kinetic Monte Carlo simulations. While the experimentally obtained scaling exponent [Formula: see text] decreases with the laser frequency, the simulations provided the opposite behaviour. We demonstrate that the increase of the surface temperature caused by impinging ablated particles satisfactorily explains the recorded decrease in the scaling exponent with the laser frequency. This phenomena is often overlooked during the PLD growth.

Standardized Colon Ascendens Stent Peritonitis in Rats - a Simple, Feasible Animal Model to Induce Septic Acute Kidney Injury.

AKI in septic patients is associated with increased mortality and poor outcome despite major efforts to refine the understanding of its pathophysiology. Here, an in vivo model is presented that combines a standardized septic focus to induce AKI and an intensive care (ICU) setup to provide an advanced hemodynamic monitoring and therapy comparable in human sepsis. Sepsis is induced by standardized colon ascendens stent peritonitis (sCASP). AKI is investigated functionally by measurement of blood and urine samples as well as histologically by evaluation of histopathological scores. Furthermore, the advanced hemodynamic monitoring and the possibility of repetitive blood gas sampling enable a differentiated analysis of severity of induced sepsis. The sCASP method is a standardized, reliable and reproducible method to induce septic AKI. The intensive care setup, continuous hemodynamic and gas exchange monitoring, low mortality rate as well as the opportunity of detailed analyses of kidney function and impairments are advantages of this setup. Therefore, the described method may serve as a new standard for experimental investigations of septic AKI.

COBREXA.jl: constraint-based reconstruction and exascale analysis.

SUMMARY: COBREXA.jl is a Julia package for scalable, high-performance constraint-based reconstruction and analysis of very large-scale biological models. Its primary purpose is to facilitate the integration of modern high performance computing environments with the processing and analysis of large-scale metabolic models of challenging complexity. We report the architecture of the package, and demonstrate how the design promotes analysis scalability on several use-cases with multi-organism community models. AVAILABILITY AND IMPLEMENTATION: https://doi.org/10.17881/ZKCR-BT30. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

OnTheFly2.0: a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis.

Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analyzing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly2.0, a web application for extracting biomedical entities from individual files such as plain texts, office documents, PDF files or images. OnTheFly2.0 can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform named entity recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and gene ontology terms. Multiple files can be analyzed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein-protein and protein-chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly2.0 currently supports 197 species and is available at http://bib.fleming.gr:3838/OnTheFly/ and http://onthefly.pavlopouloslab.info.