{"type": "FeatureCollection", "features": [{"id": "10.1016/j.chemosphere.2024.143146", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:16:10Z", "type": "Journal Article", "created": "2024-08-23", "title": "Predicting bioconcentration factors (BCFs) for per- and polyfluoroalkyl substances (PFAS)", "description": "The file contains a publication entitled \u2018Predicting bioconcentration factors (BCFs) for per- and polyfluoroalkyl substances (PFAS)\u2019 by Dominika Kowalska, Anita Sosnowska, Szymon Zdybel, Maciej St\u0119pnik, Tomasz Puzyn with Supplementary Materials.", "keywords": ["Fluorocarbons", "QSPR model", "bioconcentration", "in silico", "PFAS", "Fishes", "BCF", "Animals", "Quantitative Structure-Activity Relationship", "Perfluoroalkyl compounds", "MLR", "Water Pollutants", " Chemical", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1016/j.chemosphere.2024.143146"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Chemosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.chemosphere.2024.143146", "name": "item", "description": "10.1016/j.chemosphere.2024.143146", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.chemosphere.2024.143146"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-09-01T00:00:00Z"}}, {"id": "10.1038/s41598-023-49194-y", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:18:27Z", "type": "Journal Article", "created": "2023-12-13", "title": "Unraveling the genome of Bacillus velezensis MEP218, a strain producing fengycin homologs with broad antibacterial activity: comprehensive comparative genome analysis", "description": "Abstract<p>Bacillus sp. MEP218, a soil bacterium with high potential as a source of bioactive molecules, produces mostly C16\uffe2\uff80\uff93C17 fengycin and other cyclic lipopeptides (CLP) when growing under previously optimized culture conditions. This work addressed the elucidation of the genome sequence of MEP218 and its taxonomic classification. The genome comprises 3,944,892\uffc2\uffa0bp, with a total of 3474 coding sequences and a G\uffe2\uff80\uff89+\uffe2\uff80\uff89C content of 46.59%. Our phylogenetic analysis to determine the taxonomic position demonstrated that the assignment of the MEP218 strain to Bacillus velezensis species provides insights into its evolutionary context and potential functional attributes. The in silico genome analysis revealed eleven gene clusters involved in the synthesis of secondary metabolites, including non-ribosomal CLP (fengycins and surfactin), polyketides, terpenes, and bacteriocins. Furthermore, genes encoding phytase, involved in the release of phytic phosphate for plant and animal nutrition, or other enzymes such as cellulase, xylanase, and alpha 1\uffe2\uff80\uff934 glucanase were detected. In vitro antagonistic assays against Salmonella typhimurium, Acinetobacter baumanii, Escherichia coli, among others, demonstrated a broad spectrum of C16\uffe2\uff80\uff93C17 fengycin produced by MEP218. MEP218 genome sequence analysis expanded our understanding of the diversity and genetic relationships within the Bacillus genus and updated the Bacillus databases with its unique trait to produce antibacterial fengycins and its potential as a resource of biotechnologically useful enzymes.</p", "keywords": ["0301 basic medicine", "Bacillus", "Gene", "Agricultural and Biological Sciences", "https://purl.org/becyt/ford/1.6", "Phylogeny", "GC-content", "2. Zero hunger", "0303 health sciences", "Genome", "Acinetobacter", "soil bacteria", "Q", "Probiotics and Prebiotics", "R", "Life Sciences", "Anti-Bacterial Agents", "3. Good health", "Ribosomal RNA", "Medicine", "Microbial genetics", "metagenomics assembly", "Biotechnology", "Bacteriocin", "Science", ".", "Synteny", "Microbiology", "Article", "Applied microbiology", "Lipopeptides", "03 medical and health sciences", "Biochemistry", " Genetics and Molecular Biology", "Genetics", "Escherichia coli", "RNA Sequencing Data Analysis", "https://purl.org/becyt/ford/1", "Molecular Biology", "Biology", "genetic engineering", "Bacteria", "Secondary metabolites", "In silico", "bacterial genomes", "Whole genome sequencing", "FOS: Biological sciences", "Microbial Enzymes and Biotechnological Applications", "Antibacterial activity", "Genome", " Bacterial", "Food Science", "Phylogenetic tree"]}, "links": [{"href": "https://www.nature.com/articles/s41598-023-49194-y.pdf"}, {"href": "https://doi.org/10.1038/s41598-023-49194-y"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41598-023-49194-y", "name": "item", "description": "10.1038/s41598-023-49194-y", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41598-023-49194-y"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-13T00:00:00Z"}}, {"id": "10.2139/ssrn.4173912", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:21:13Z", "type": "Journal Article", "created": "2022-07-28", "title": "How the Structure of Per- and Polyfluoroalkyl Substances (Pfas) Influences Their Binding Potency to the Peroxisome Proliferator-Activated and Thyroid Hormone Receptors \u2013 an in Silico Screening Study", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In this study, we investigated PFAS (per- and polyfluoroalkyl substances) binding potencies to nuclear hormone receptors (NHRs): peroxisome proliferator-activated receptors (PPARs) \u03b1, \u03b2, and \u03b3 and thyroid hormone receptors (TRs) \u03b1 and \u03b2. We have simulated the docking scores of 43 perfluoroalkyl compounds and based on these data developed QSAR (Quantitative Structure-Activity Relationship) models for predicting the binding probability to five receptors. In the next step, we implemented the developed QSAR models for the screening approach of a large group of compounds (4464) from the NORMAN Database. The in silico analyses indicated that the probability of PFAS binding to the receptors depends on the chain length, the number of fluorine atoms, and the number of branches in the molecule. According to the findings, the considered PFAS group bind to the PPAR\u03b1, \u03b2, and \u03b3 only with low or moderate probability, while in the case of TR \u03b1 and \u03b2 it is similar except that those chemicals with longer chains show a moderately high probability of binding.</p></article>", "keywords": ["0301 basic medicine", "Fluorocarbons", "0303 health sciences", "Receptors", " Thyroid Hormone", "binding probability", "peroxisome proliferator-activated receptor", "QSAR", "PFAS", "H2020", "thyroid receptor", "Organic chemistry", "Quantitative Structure-Activity Relationship", "molecular docking", "virtual screening", "PROMISCES", "MLR", "Article", "03 medical and health sciences", "perfluoroalkyl compounds", "QD241-441", "in silico", "Peroxisome Proliferators", "perfluoroalkyl compounds; PFAS; peroxisome proliferator-activated receptor; thyroid receptor; QSAR; MLR; in silico; binding probability; molecular docking; virtual screening"]}, "links": [{"href": "http://www.mdpi.com/1420-3049/28/2/479/pdf"}, {"href": "https://www.mdpi.com/1420-3049/28/2/479/pdf"}, {"href": "https://doi.org/10.2139/ssrn.4173912"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/SSRN%20Electronic%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2139/ssrn.4173912", "name": "item", "description": "10.2139/ssrn.4173912", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2139/ssrn.4173912"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.3390/ijms25105216", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:21:51Z", "type": "Journal Article", "created": "2024-05-14", "title": "Development of a Robust Read-Across Model for the Prediction of Biological Potency of Novel Peroxisome Proliferator-Activated Receptor Delta Agonists", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>A robust predictive model was developed using 136 novel peroxisome proliferator-activated receptor delta (PPAR\u03b4) agonists, a distinct subtype of lipid-activated transcription factors of the nuclear receptor superfamily that regulate target genes by binding to characteristic sequences of DNA bases. The model employs various structural descriptors and docking calculations and provides predictions of the biological activity of PPAR\u03b4 agonists, following the criteria of the Organization for Economic Co-operation and Development (OECD) for the development and validation of quantitative structure\u2013activity relationship (QSAR) models. Specifically focused on small molecules, the model facilitates the identification of highly potent and selective PPAR\u03b4 agonists and offers a read-across concept by providing the chemical neighbours of the compound under study. The model development process was conducted on Isalos Analytics Software (v. 0.1.17) which provides an intuitive environment for machine-learning applications. The final model was released as a user-friendly web tool and can be accessed through the Enalos Cloud platform\u2019s graphical user interface (GUI).</p></article>", "keywords": ["0301 basic medicine", "570", "610", "Quantitative Structure-Activity Relationship", "molecular docking", "01 natural sciences", "Isalos Analytics Platform", "in silico modelling", "Article", "0104 chemical sciences", "Molecular Docking Simulation", "Machine Learning", "03 medical and health sciences", "machine learning", "PPAR\u03b4 agonist", "Humans", "PPAR delta", "Software"]}, "links": [{"href": "https://www.mdpi.com/1422-0067/25/10/5216/pdf"}, {"href": "https://doi.org/10.3390/ijms25105216"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Molecular%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/ijms25105216", "name": "item", "description": "10.3390/ijms25105216", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/ijms25105216"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-05-10T00:00:00Z"}}, {"id": "10.5281/zenodo.14945573", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:23:47Z", "type": "Report", "title": "Deliverable D1.5 \u2013 Set of novel QSAR models/grouping/read-across and in vitro bioassay approaches predicting relevant toxicological endpoints for PFAS/PM(T) chemicals", "description": "The deliverable is a profiling of activities for pre-selected single and complex industrial mixtures of PFAS/PM(T)s with in vitro bioassay testing and QSAR modeling for a selection of most relevant toxicological endpoints. \u00a0A set of novel in silico and in vitro methods have been developed and applied for the large group of PFAS/PM(T)s.  The in vitro toxicity profiling followed a stepwise approach, by first testing the potential reference compounds PFOA and PFOS as well as industrial mixtures (e.g., GenX and ADONA) with a wide range of in silico and in vitro methods (see for an overview in Annex, Table A1). Based on these initial results, the most suitable in vitro toxicity endpoints (see table 7 and table 10) have been chosen for toxicity profiling the wider set of the selected PFAS compounds as well as for toxicity testing selected complex mixture (e.g., water, soil).   In the case of PMTs, at first, the potential bioactivity of several key PMTs (e.g., bisphenol A, triclosan, methyl-paraben, 5-chlorobenzotriazole, benzothiazole) have been evaluated using a range of in vitro toxicity profiling methods (see for an overview in Annex, Table A1). In a second step, the most suitable in vitro toxicity endpoints (see table 8 and 11) have been used for toxicity profiling an extended group of PMT compounds as well as for testing complex mixtures (e.g., water, soil).\u00a0   Regarding the group of PFAS, in silico modelling has been performed for a few thousands of chemicals (see Kowalski et al.,\u00a0 2023), while in case of in vitro testing the focus was on a selection of 40/2 PFAS/industrial mixtures compounds proposed by the chemical-analytical laboratories involved in PROMISCES and commercially available within a limited budget.  In this study, the in silico modeling part investigated PFAS binding potencies to nuclear hormone receptors (NHRs) such as peroxisome proliferator-activated receptors (PPARs) \u03b1, \u03b2, and \u03b3 and thyroid hormone receptors (TRs) \u03b1 and \u03b2. In the first in silico step, the developed QSAR models were implemented for the screening approach of a large group of compounds (4464) from the NORMAN Database related to these 5 above mentioned NHRs. The in silico analyses indicated that the probability of PFAS binding to the receptors depends on the chain length, the number of fluorine atoms, and the number of branches in the molecule. According to the findings, the considered PFAS group bind to the PPAR\u03b1, \u03b2, and \u03b3 only with low or moderate probability, while in the case of TR \u03b1 and \u03b2 it is similar except that those chemicals with longer chains show a moderately high probability of binding.  The in silico analysis shows from the here tested 15 endpoints that most PFAS reflect a high binding probability to sex hormone receptors (anti-AR and ER). however, receptors from the peroxisome proliferator-activated (PPAR \u03b1, \u03b2, \u03b3) glucocorticoid (GR and anti-GR), liver X (LXR \u03b1, \u03b2) and retinoid X (RXR \u03b1) groups are unaffected or slightly affected by PFAS (low and moderate binding probability).   Regarding the parallel in vitro bioassay toxicity analysis, an established standardised in vitro test battery (consisting of e.g., genotoxicity, neurotoxicity, cytotoxicity, obesity and early warning testing) was applied to meet specific criteria of PFAS/iPM(T) (endpoints, sensitivity and specificity).   Based on existing and improved CALUX bioassays, different toxicological endpoints involving metabolic syndrome (obesity related PPAR), endocrine EATS testing, genotoxicity (p53 related) and general toxicity pathways (e.g. early warning PXR) to characterise PM(T) properties of chemicals were assessed.   The in vitro bioassay groups addressed 40 PFAS compounds (e.g. all regulated 20 PFAS) and industrial standards (e.g., ADONA, GenX) with a combination of a wide range of CALUX bioassay endpoints (e.g., table 7 with 6 endpoints) and additional general toxicity in vitro bioassays (e.g., table 9 with 8 in vitro endpoints).   Potency factors for selected PFAS/ iPM(T) have been established for several of the here used in vitro bioassays by two bioassay laboratories (UBA, BDS). Comparing both data sets, 80% of the relative potency factors for PFAS tested on e.g., the TTR-TRb CALUX, were found to be within an order of magnitude.  Potency factors for selected PFAS have been established for each of the here used in vitro human cell-based CALUX bioassays. For example, in case of the TTR-TRb CALUX bioassay, the RPF values are rang from non-detected (e.g., several FTOH compounds) to the P37DMOA compound (RPF = up to 2.3; see tables 7 and 10).  Additional up to 22 PM(T) chemicals (e.g., see table 8 and 10) have been tested with a combination of a wide range of CALUX bioassays (e.g., table 8 with 6 endpoints) and additional general toxicity in vitro bioassays (e.g., table 10 with 4 in vitro endpoints). This included i) selecting a wide range of reporter gene assays to screen the toxic profiles of a set of PM(T) chemicals, ii) selecting the most suitable bioassay panel, and iii) validating bioassay panels and cross-validating the responses obtained from the selected panel of human cell-line based bioassays  Potency factors for selected iPM(T) have been established for each of the here used in vitro human cell-based CALUX bioassays. For all CALUX bioassays applied, RPF-values ranged from not-detected (e.g., several in vitro endpoints at benzotriazole) up to RPF values above 0.5 for several PMTs (e.g., galaxolide and triclosan, see table 8, or methyl-paraben in table 10 at the male hormone inhibition).  In a second step, the 3 most active PFAS compounds on the in vitro TTR-TRb CALUX (PFOA with RPF = 1; P37DMOA with RPF = 2.3; 6:2 FTAB with RPF = 0.00015; see table 7) have been used to find in in silico modelling new PFAS structure-analogue compounds. In case of PFOA 12 structure-in vitro toxicity analogues were found, while in case of P37DMOA only 3 analogues and in case of 6:2 FTAB only 7 analogues were found.  Our study shows that such an combined approach of in silico and in\u00a0 vitro toxicity evaluations of single PFAS congeners (from the large group of PFAS) is a promising and suitable strategy to cover a large variety of different key events in toxicology in a time- and cost-efficient way. Such early key events can lead to protein production or molecular signalling that occur in individual cells. Later events can include altered tissue or organ function. Such key events are important because after the molecular initiating event, they can characterize the progression of the toxicity.  Relative potency factors (RPFs) have been determined here by a combination of in silico and vitro toxicity tools and can further help to give first toxicity indications for the handful regulated and the not yet regularly tested/regulated PFAS to be included in the testing strategy for single compounds and complex mixtures of these compounds.", "keywords": ["Deliverable", "thyroid hormone transport competition", "TTR TR CALUX", "PFAS", "in vitro assay (CALUX)", "non-animal methods (NAM)", "in silico modeling"], "contacts": [{"organization": "Behnisch, Peter, Sosnowska, Anita, Mombelli, Enrico, Kuckelkorn, Jochen,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14945573"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14945573", "name": "item", "description": "10.5281/zenodo.14945573", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14945573"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-28T00:00:00Z"}}, {"id": "11336/226991", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:26:12Z", "type": "Journal Article", "created": "2023-12-13", "title": "Unraveling the genome of Bacillus velezensis MEP218, a strain producing fengycin homologs with broad antibacterial activity: comprehensive comparative genome analysis", "description": "Abstract<p>Bacillus sp. MEP218, a soil bacterium with high potential as a source of bioactive molecules, produces mostly C16\uffe2\uff80\uff93C17 fengycin and other cyclic lipopeptides (CLP) when growing under previously optimized culture conditions. This work addressed the elucidation of the genome sequence of MEP218 and its taxonomic classification. The genome comprises 3,944,892\uffc2\uffa0bp, with a total of 3474 coding sequences and a G\uffe2\uff80\uff89+\uffe2\uff80\uff89C content of 46.59%. Our phylogenetic analysis to determine the taxonomic position demonstrated that the assignment of the MEP218 strain to Bacillus velezensis species provides insights into its evolutionary context and potential functional attributes. The in silico genome analysis revealed eleven gene clusters involved in the synthesis of secondary metabolites, including non-ribosomal CLP (fengycins and surfactin), polyketides, terpenes, and bacteriocins. Furthermore, genes encoding phytase, involved in the release of phytic phosphate for plant and animal nutrition, or other enzymes such as cellulase, xylanase, and alpha 1\uffe2\uff80\uff934 glucanase were detected. In vitro antagonistic assays against Salmonella typhimurium, Acinetobacter baumanii, Escherichia coli, among others, demonstrated a broad spectrum of C16\uffe2\uff80\uff93C17 fengycin produced by MEP218. MEP218 genome sequence analysis expanded our understanding of the diversity and genetic relationships within the Bacillus genus and updated the Bacillus databases with its unique trait to produce antibacterial fengycins and its potential as a resource of biotechnologically useful enzymes.</p", "keywords": ["0301 basic medicine", "Bacteriocin", "Science", "Bacillus", ".", "Gene", "Synteny", "Microbiology", "Article", "Agricultural and Biological Sciences", "Lipopeptides", "03 medical and health sciences", "https://purl.org/becyt/ford/1.6", "Biochemistry", " Genetics and Molecular Biology", "Genetics", "Escherichia coli", "RNA Sequencing Data Analysis", "https://purl.org/becyt/ford/1", "Molecular Biology", "Biology", "Phylogeny", "GC-content", "2. Zero hunger", "0303 health sciences", "Genome", "Acinetobacter", "Bacteria", "Secondary metabolites", "Q", "Probiotics and Prebiotics", "In silico", "R", "Life Sciences", "Anti-Bacterial Agents", "3. Good health", "Ribosomal RNA", "Whole genome sequencing", "FOS: Biological sciences", "Medicine", "Microbial Enzymes and Biotechnological Applications", "Antibacterial activity", "Genome", " Bacterial", "metagenomics assembly", "Biotechnology", "Food Science", "Phylogenetic tree"]}, "links": [{"href": "https://www.nature.com/articles/s41598-023-49194-y.pdf"}, {"href": "https://doi.org/11336/226991"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11336/226991", "name": "item", "description": "11336/226991", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11336/226991"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-13T00:00:00Z"}}, {"id": "20.500.11820/03f81a44-477a-4a8c-b34d-85892c85bd6f", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:26:42Z", "type": "Journal Article", "created": "2017-10-13", "title": "An Explicit Structural Model of Root Hair and Soil Interactions Parameterised by Synchrotron X-ray Computed Tomography", "description": "The rhizosphere is a zone of fundamental importance for understanding the dynamics of nutrient acquisition by plant roots. The canonical difficulty of experimentally investigating the rhizosphere led long ago to the adoption of mathematical models, the most sophisticated of which now incorporate explicit representations of root hairs and rhizosphere soil. Mathematical upscaling regimes, such as homogenisation, offer the possibility of incorporating into larger-scale models the important mechanistic processes occurring at the rhizosphere scale. However, we lack concrete descriptions of all the features required to fully parameterise models at the rhizosphere scale. By combining synchrotron X-ray computed tomography (SRXCT) and a novel root growth assay, we derive a three-dimensional description of rhizosphere soil structure suitable for use in multi-scale modelling frameworks. We describe an approach to mitigate sub-optimal root hair detection via structural root hair growth modelling. The growth model is explicitly parameterised with SRXCT data and simulates three-dimensional root hair ideotypes in silico, which are suitable for both ideotypic analysis and parameterisation of 3D geometry in mathematical models. The study considers different hypothetical conditions governing root hair interactions with soil matrices, with their respective effects on hair morphology being compared between idealised and image-derived soil/root geometries. The studies in idealised geometries suggest that packing arrangement of soil affects hair tortuosity more than the particle diameter. Results in field-derived soil suggest that hair access to poorly mobile nutrients is particularly sensitive to the physical interaction between the growing hairs and the phase of the soil in which soil water is present (i.e. the hydrated textural phase). The general trends in fluid-coincident hair length with distance from the root, and their dependence on hair/soil interaction mechanisms, are conserved across Cartesian and cylindrical geometries.", "keywords": ["Plant biology", "2. Zero hunger", "0301 basic medicine", "0303 health sciences", "X-ray CT", "Biomedical imaging and signal processing", "Mathematical Concepts", "15. Life on land", "Models", " Biological", "Plant Roots", "root hairs", "Soil", "03 medical and health sciences", "Imaging", " Three-Dimensional", "in silico", "structural modelling", "synchrotron", "Rhizosphere", "Original Article", "Computer Simulation", "rhizosphere", "Tomography", " X-Ray Computed", "Synchrotrons"]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s11538-017-0350-x.pdf"}, {"href": "https://doi.org/20.500.11820/03f81a44-477a-4a8c-b34d-85892c85bd6f"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Bulletin%20of%20Mathematical%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11820/03f81a44-477a-4a8c-b34d-85892c85bd6f", "name": "item", "description": "20.500.11820/03f81a44-477a-4a8c-b34d-85892c85bd6f", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11820/03f81a44-477a-4a8c-b34d-85892c85bd6f"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-10-13T00:00:00Z"}}, {"id": "11579/182202", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:26:17Z", "type": "Journal Article", "created": "2024-05-14", "title": "Development of a Robust Read-Across Model for the Prediction of Biological Potency of Novel Peroxisome Proliferator-Activated Receptor Delta Agonists", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>A robust predictive model was developed using 136 novel peroxisome proliferator-activated receptor delta (PPAR\u03b4) agonists, a distinct subtype of lipid-activated transcription factors of the nuclear receptor superfamily that regulate target genes by binding to characteristic sequences of DNA bases. The model employs various structural descriptors and docking calculations and provides predictions of the biological activity of PPAR\u03b4 agonists, following the criteria of the Organization for Economic Co-operation and Development (OECD) for the development and validation of quantitative structure\u2013activity relationship (QSAR) models. Specifically focused on small molecules, the model facilitates the identification of highly potent and selective PPAR\u03b4 agonists and offers a read-across concept by providing the chemical neighbours of the compound under study. The model development process was conducted on Isalos Analytics Software (v. 0.1.17) which provides an intuitive environment for machine-learning applications. The final model was released as a user-friendly web tool and can be accessed through the Enalos Cloud platform\u2019s graphical user interface (GUI).</p></article>", "keywords": ["0301 basic medicine", "570", "610", "Quantitative Structure-Activity Relationship", "molecular docking", "01 natural sciences", "Isalos Analytics Platform", "in silico modelling", "Article", "0104 chemical sciences", "Molecular Docking Simulation", "Machine Learning", "03 medical and health sciences", "machine learning", "PPAR\u03b4 agonist", "Humans", "PPAR delta", "Software"]}, "links": [{"href": "https://www.mdpi.com/1422-0067/25/10/5216/pdf"}, {"href": "https://doi.org/11579/182202"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Molecular%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11579/182202", "name": "item", "description": "11579/182202", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11579/182202"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-05-10T00:00:00Z"}}, {"id": "39181470", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:28:00Z", "type": "Journal Article", "created": "2024-08-23", "title": "Predicting bioconcentration factors (BCFs) for per- and polyfluoroalkyl substances (PFAS)", "description": "The file contains a publication entitled \u2018Predicting bioconcentration factors (BCFs) for per- and polyfluoroalkyl substances (PFAS)\u2019 by Dominika Kowalska, Anita Sosnowska, Szymon Zdybel, Maciej St\u0119pnik, Tomasz Puzyn with Supplementary Materials.", "keywords": ["Fluorocarbons", "QSPR model", "bioconcentration", "in silico", "PFAS", "Fishes", "BCF", "Animals", "Quantitative Structure-Activity Relationship", "Perfluoroalkyl compounds", "MLR", "Water Pollutants", " Chemical", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/39181470"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Chemosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "39181470", "name": "item", "description": "39181470", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/39181470"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-09-01T00:00:00Z"}}, {"id": "50|userclaim___::85c2e6974a364f4a96fdee6d82a5dd41", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:28:25Z", "type": "Other", "title": "Unraveling the genome of Bacillus velezensis MEP218, a strain producing fengycin homologs with broad antibacterial activity: comprehensive comparative genome analysis", "keywords": ["Bacteriocin", "Gene", "Synteny", "Microbiology", "Agricultural and Biological Sciences", "Biochemistry", " Genetics and Molecular Biology", "Genetics", "Escherichia coli", "RNA Sequencing Data Analysis", "Molecular Biology", "Biology", "GC-content", "Genome", "Acinetobacter", "Bacteria", "Probiotics and Prebiotics", "In silico", "Life Sciences", "Ribosomal RNA", "Whole genome sequencing", "FOS: Biological sciences", "Microbial Enzymes and Biotechnological Applications", "metagenomics assembly", "Biotechnology", "Food Science", "Phylogenetic tree"], "contacts": [{"organization": "Mariano Pistorio, Mar\u00eda Julia Estrella, Edgardo Jofr\u00e9, Gonzalo Torres Tejerizo, Bruno Contreras-Moreira, Daniela Medeot, Anal\u00eda Sannazzaro, Medeot, Daniela, Daniela B. Medeot, Sannazzaro, Anal\u00eda, Anal\u00eda In\u00e9s Sannazzaro, Estrella, Maria Julia, Mar\u00eda Julia Estrella, Torres Tejerizo, Gonzalo, Gonzalo Torres Tejerizo, Contreras\u2011Moreira, Bruno, Bruno Contreras\u2010Moreira, Pistorio, Mariano, Mariano Pistorio, Jofr\u00e9, Edgardo, Edgardo Jofr\u00e9,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|userclaim___::85c2e6974a364f4a96fdee6d82a5dd41"}, {"rel": "self", "type": "application/geo+json", "title": "50|userclaim___::85c2e6974a364f4a96fdee6d82a5dd41", "name": "item", "description": "50|userclaim___::85c2e6974a364f4a96fdee6d82a5dd41", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|userclaim___::85c2e6974a364f4a96fdee6d82a5dd41"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-13T00:00:00Z"}}, {"id": "85c2e6974a364f4a96fdee6d82a5dd41", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:29:24Z", "type": "Other", "title": "Unraveling the genome of Bacillus velezensis MEP218, a strain producing fengycin homologs with broad antibacterial activity: comprehensive comparative genome analysis", "keywords": ["Bacteriocin", "Gene", "Synteny", "Microbiology", "Agricultural and Biological Sciences", "Biochemistry", " Genetics and Molecular Biology", "Genetics", "Escherichia coli", "RNA Sequencing Data Analysis", "Molecular Biology", "Biology", "GC-content", "Genome", "Acinetobacter", "Bacteria", "Probiotics and Prebiotics", "In silico", "Life Sciences", "Ribosomal RNA", "Whole genome sequencing", "FOS: Biological sciences", "Microbial Enzymes and Biotechnological Applications", "metagenomics assembly", "Biotechnology", "Food Science", "Phylogenetic tree"], "contacts": [{"organization": "Mariano Pistorio, Mar\u00eda Julia Estrella, Edgardo Jofr\u00e9, Gonzalo Torres Tejerizo, Bruno Contreras-Moreira, Daniela Medeot, Anal\u00eda Sannazzaro, Medeot, Daniela, Daniela B. Medeot, Sannazzaro, Anal\u00eda, Anal\u00eda In\u00e9s Sannazzaro, Estrella, Maria Julia, Mar\u00eda Julia Estrella, Torres Tejerizo, Gonzalo, Gonzalo Torres Tejerizo, Contreras\u2011Moreira, Bruno, Bruno Contreras\u2010Moreira, Pistorio, Mariano, Mariano Pistorio, Jofr\u00e9, Edgardo, Edgardo Jofr\u00e9,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/85c2e6974a364f4a96fdee6d82a5dd41"}, {"rel": "self", "type": "application/geo+json", "title": "85c2e6974a364f4a96fdee6d82a5dd41", "name": "item", "description": "85c2e6974a364f4a96fdee6d82a5dd41", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/85c2e6974a364f4a96fdee6d82a5dd41"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-13T00:00:00Z"}}, {"id": "PMC9866891", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:30:34Z", "type": "Journal Article", "created": "2022-07-28", "title": "How the Structure of Per- and Polyfluoroalkyl Substances (Pfas) Influences Their Binding Potency to the Peroxisome Proliferator-Activated and Thyroid Hormone Receptors \u2013 an in Silico Screening Study", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In this study, we investigated PFAS (per- and polyfluoroalkyl substances) binding potencies to nuclear hormone receptors (NHRs): peroxisome proliferator-activated receptors (PPARs) \u03b1, \u03b2, and \u03b3 and thyroid hormone receptors (TRs) \u03b1 and \u03b2. We have simulated the docking scores of 43 perfluoroalkyl compounds and based on these data developed QSAR (Quantitative Structure-Activity Relationship) models for predicting the binding probability to five receptors. In the next step, we implemented the developed QSAR models for the screening approach of a large group of compounds (4464) from the NORMAN Database. The in silico analyses indicated that the probability of PFAS binding to the receptors depends on the chain length, the number of fluorine atoms, and the number of branches in the molecule. According to the findings, the considered PFAS group bind to the PPAR\u03b1, \u03b2, and \u03b3 only with low or moderate probability, while in the case of TR \u03b1 and \u03b2 it is similar except that those chemicals with longer chains show a moderately high probability of binding.</p></article>", "keywords": ["0301 basic medicine", "Fluorocarbons", "0303 health sciences", "Receptors", " Thyroid Hormone", "binding probability", "peroxisome proliferator-activated receptor", "QSAR", "PFAS", "thyroid receptor", "Organic chemistry", "Quantitative Structure-Activity Relationship", "molecular docking", "virtual screening", "MLR", "Article", "03 medical and health sciences", "perfluoroalkyl compounds", "QD241-441", "in silico", "Peroxisome Proliferators", "perfluoroalkyl compounds; PFAS; peroxisome proliferator-activated receptor; thyroid receptor; QSAR; MLR; in silico; binding probability; molecular docking; virtual screening"]}, "links": [{"href": "http://www.mdpi.com/1420-3049/28/2/479/pdf"}, {"href": "https://www.mdpi.com/1420-3049/28/2/479/pdf"}, {"href": "https://doi.org/PMC9866891"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/SSRN%20Electronic%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC9866891", "name": "item", "description": "PMC9866891", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC9866891"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=In+silico&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=In+silico&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=In+silico&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=In+silico&offset=12", "hreflang": "en-US"}], "numberMatched": 12, "numberReturned": 12, "distributedFeatures": [], "timeStamp": "2026-07-28T07:05:50.524222Z"}