Understanding animal movement is at the core of ecology, evolution and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g. body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the level of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g. metabolic rates) and biomechanical traits (e.g. limb length, locomotion form) influence migration distances? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world.
- Klíčová slova
- Biologging, Integration, Macroecology, Repository, Tracking data, Trait data,
- MeSH
- big data MeSH
- databáze faktografické MeSH
- ekologie * metody MeSH
- migrace zvířat MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
Access to information about chemicals in products and articles is critical for supporting enforcement of chemical regulations, assessing risks from chemicals, allowing informed consumer choices, and enabling product circularity. In this work, we identified and evaluated available databases (DBs) on chemicals in products and articles from the literature using a defined protocol and from European national market surveillance authorities, nongovernmental agencies, and industrial sector groups using questionnaires. This is the first comprehensive review of DBs that provide information about chemicals in products and articles. A majority of these DBs are heterogeneous in terms of scope, ontologies, and data structures. Among the 57 identified DBs, 49 identified specific substances and only 30 reported their concentration in their products. In addition, 35 DBs included hazard information and 27 DBs provided safety information about products or chemicals. The analysis highlights the lack of comprehensive or accessible data on chemicals in products and articles for most categories of products/articles and jurisdictions. The limitations of existing DBs were attributed to scattered regulatory information requirements, a lack of data for unregulated substances, the complexity of supply chain communication, and confidentiality issues. In response to these challenges, we identified opportunities for improving existing information transfer structures and exploring alternative data sources to promote product and article safety and circularity.
- Klíčová slova
- REACH, compliance, consumer products, enforcement, regulations,
- MeSH
- databáze faktografické * MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
Genetic diagnosis of rare diseases requires accurate identification and interpretation of genomic variants. Clinical and molecular scientists from 37 expert centers across Europe created the Solve-Rare Diseases Consortium (Solve-RD) resource, encompassing clinical, pedigree and genomic rare-disease data (94.5% exomes, 5.5% genomes), and performed systematic reanalysis for 6,447 individuals (3,592 male, 2,855 female) with previously undiagnosed rare diseases from 6,004 families. We established a collaborative, two-level expert review infrastructure that allowed a genetic diagnosis in 506 (8.4%) families. Of 552 disease-causing variants identified, 464 (84.1%) were single-nucleotide variants or short insertions/deletions. These variants were either located in recently published novel disease genes (n = 67), recently reclassified in ClinVar (n = 187) or reclassified by consensus expert decision within Solve-RD (n = 210). Bespoke bioinformatics analyses identified the remaining 15.9% of causative variants (n = 88). Ad hoc expert review, parallel to the systematic reanalysis, diagnosed 249 (4.1%) additional families for an overall diagnostic yield of 12.6%. The infrastructure and collaborative networks set up by Solve-RD can serve as a blueprint for future further scalable international efforts. The resource is open to the global rare-disease community, allowing phenotype, variant and gene queries, as well as genome-wide discoveries.
- MeSH
- databáze genetické MeSH
- exom genetika MeSH
- genom lidský genetika MeSH
- genomika * metody MeSH
- lidé MeSH
- rodokmen MeSH
- výpočetní biologie metody MeSH
- vzácné nemoci * genetika diagnóza MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
Today, MALDI-ToF MS is an established technique to characterize and identify pathogenic bacteria. The technique is increasingly applied by clinical microbiological laboratories that use commercially available complete solutions, including spectra databases covering clinically relevant bacteria. Such databases are validated for clinical, or research applications, but are often less comprehensive concerning highly pathogenic bacteria (HPB). To improve MALDI-ToF MS diagnostics of HPB we initiated a program to develop protocols for reliable and MALDI-compatible microbial inactivation and to acquire mass spectra thereof many years ago. As a result of this project, databases covering HPB, closely related bacteria, and bacteria of clinical relevance have been made publicly available on platforms such as ZENODO. This publication in detail describes the most recent version of this database. The dataset contains a total of 11,055 spectra from altogether 1,601 microbial strains and 264 species and is primarily intended to improve the diagnosis of HPB. We hope that our MALDI-ToF MS data may also be a valuable resource for developing machine learning-based bacterial identification and classification methods.
The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.
- Klíčová slova
- global alliance for genomics and health, human phenotype ontology, phenopacket schema,
- MeSH
- algoritmy MeSH
- databáze genetické MeSH
- fenotyp * MeSH
- genomika * metody MeSH
- lidé MeSH
- software * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.
The European Chemical Biology Database (ECBD, https://ecbd.eu) serves as the central repository for data generated by the EU-OPENSCREEN research infrastructure consortium. It is developed according to FAIR principles, which emphasize findability, accessibility, interoperability and reusability of data. This data is made available to the scientific community following open access principles. The ECBD stores both positive and negative results from the entire chemical biology project pipeline, including data from primary or counter-screening assays. The assays utilize a defined and diverse library of over 107 000 compounds, the annotations of which are continuously enriched by external user supported screening projects and by internal EU-OPENSCREEN bioprofiling efforts. These compounds were screened in 89 currently deposited datasets (assays), with 48 already being publicly accessible, while the remaining will be published after a publication embargo period of up to 3 years. Together these datasets encompass ∼4.3 million experimental data points. All public data within ECBD can be accessed through its user interface, API or by database dump under the CC-BY 4.0 license.
BACKGROUND: Cross-sectional anatomy is a challenging yet a vital foundation to clinical practice. The traditional teachings of gross anatomy cadaveric dissections do not cover adequate training of recognizing anatomical structures on CT, MRI and sonographic cross-sections. New modern technologies are emerging as teaching tools in anatomy aiming to deliver visual interactive experience. The Visible Human Project provides a library of cross-sectional images compiled from cryosectioned body donors that was utilized by modern technologies such as the virtual dissection table (Anatomage) in constructing 3D software applications visualizing the internal composition of the human body virtually. Hereby, this article explores an integrative approach utilizing the Visible Human Project based applications and basic radiological modalities. PURPOSE: The purpose of our newly implemented teaching approach was to test and assure technology fitness to the medical curriculum and its potential influence on students' performance in learning gross as well as cross-sectional anatomy in much depth. BASIC PROCEDURES: A three years (2021-2024) observational study was conducted by implanting a practical cross-sectional anatomy optional course by selectively utilizing Anatmage interactively beside CT, MRI and ultrasound practice. The performance of 50 participants was evaluated in the form of a written test comprised of labeling of ten cross-sectional images and drawing of two cross-section schemes. Their optional course test scores were compared to their obligatory anatomy subject test scores; and to a non-participants control group of 50 retrospective obligatory anatomy subject test scores. In addition, the participants' attitude toward the training lessons was assessed through a survey focused on satisfaction level, competence and ability to recognize structures on radiological images. MAIN FINDINGS: The participants reported a high level of practical engagement. The test scores in the anatomy obligatory subject were positively influenced by this implemented practical course. Students showed improved test scores in the standardized labeling keyword questions, while the scheme questions showed discrepancy. PRINCIPAL CONCLUSIONS: Integrating Visible Human Project based applications with radiological modalities showed positive efficacy on the students' engagement and learning performance. Inevitably, cadaveric dissection and prosection remain the cornerstone of gross anatomy education. Integrating both modalities of teaching would excel students' practical skills in applied clinical anatomy.
- Klíčová slova
- Anatomage, Anatomy education, Cross-sectional anatomy, Radiological anatomy, Ultrasound education, Virtual anatomy, Visible Human Project,
- MeSH
- anatomie průřezová * výchova MeSH
- anatomie výchova MeSH
- disekce výchova MeSH
- dospělí MeSH
- kurikulum * MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mladý dospělý MeSH
- mrtvola MeSH
- projekty vizualizace člověka * MeSH
- průřezové studie MeSH
- školy lékařské MeSH
- studenti lékařství MeSH
- studium lékařství pregraduální metody MeSH
- zobrazování trojrozměrné MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- pozorovací studie MeSH
MOTIVATION: Structure-based methods for detecting protein-ligand binding sites play a crucial role in various domains, from fundamental research to biomedical applications. However, current prediction methodologies often rely on holo (ligand-bound) protein conformations for training and evaluation, overlooking the significance of the apo (ligand-free) states. This oversight is particularly problematic in the case of cryptic binding sites (CBSs) where holo-based assessment yields unrealistic performance expectations. RESULTS: To advance the development in this domain, we introduce CryptoBench, a benchmark dataset tailored for training and evaluating novel CBS prediction methodologies. CryptoBench is constructed upon a large collection of apo-holo protein pairs, grouped by UniProtID, clustered by sequence identity, and filtered to contain only structures with substantial structural change in the binding site. CryptoBench comprises 1107 structures with predefined cross-validation splits, making it the most extensive CBS dataset to date. To establish a performance baseline, we measured the predictive power of sequence- and structure-based CBS residue prediction methods using the benchmark. We selected PocketMiner as the state-of-the-art representative of the structure-based methods for CBS detection, and P2Rank, a widely-used structure-based method for general binding site prediction that is not specifically tailored for cryptic sites. For sequence-based approaches, we trained a neural network to classify binding residues using protein language model embeddings. Our sequence-based approach outperformed PocketMiner and P2Rank across key metrics, including area under the curve, area under the precision-recall curve, Matthew's correlation coefficient, and F1 scores. These results provide baseline benchmark results for future CBS and potentially also non-CBS prediction endeavors, leveraging CryptoBench as the foundational platform for further advancements in the field. AVAILABILITY AND IMPLEMENTATION: The CryptoBench dataset, including the benchmark model, is available on Open Science Framework-https://osf.io/pz4a9/. The code and tutorial are available at the GitHub repository-https://github.com/skrhakv/CryptoBench/.
- MeSH
- benchmarking * MeSH
- databáze proteinů * MeSH
- konformace proteinů MeSH
- ligandy MeSH
- proteiny * chemie metabolismus MeSH
- vazba proteinů MeSH
- vazebná místa MeSH
- výpočetní biologie metody MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- ligandy MeSH
- proteiny * MeSH
Pathogens significantly influence natural and agricultural ecosystems, playing a crucial role in the regulation of species populations and maintaining biodiversity. Entomopathogenic fungi (EF), particularly within the Hypocreales order, exemplify understudied pathogens that infect insects and other arthropods globally. Despite their ecological importance, comprehensive data on EF host specificity and geographical distribution are lacking. To address this, we present EntomoFun 1.0, an open-access database centralizing global records of EF-insect associations in Hypocreales. This database includes 1,791 records detailing EF species, insect host taxa, countries of occurrence, life stages of hosts, and information sources. EntomoFun 1.0 is constructed based on 600 literature sources, as well as herbarium specimens of the Royal Botanical Gardens, Kew. This database is intended to test hypotheses, identify knowledge gaps, and stimulate future research. Contents of the EntomoFun 1.0 database are visualized with a global map, taxonomic chart, bipartite community network, and graphs.
