PURPOSE: The purpose of this narrative review is to provide a comparison of several countries with different legislation and approaches to pharmacovigilance and to point out how these impact the number of adverse drug reactions (ADRs) that are reported to national competent authorities. METHODS: Legislative and statistical data regarding ADR reporting from various national competent authorities' websites, databases, and pharmacovigilance centers were used. In combination with the WHO pharmacovigilance quantitative indicator that was applied to evaluate the effectiveness of particular national pharmacovigilance systems in our scope. RESULTS: The study compared pharmacovigilance systems in six countries, focusing on ADR reporting from 2010 onwards. All countries required MAHs to report ADRs, while healthcare professionals' obligations varied. Per-capita ADR reports increased in all countries with available data, with the United States having a significantly higher reporting rate, possibly due to FDA campaigns. Despite starting later, China's per-capita reporting rate surpassed that of the Czech Republic and Japan. The study highlighted various measures taken by countries to enhance ADR reporting systems since the inception of their programs, contributing to the overall increase in reporting rates. CONCLUSIONS: ADR reporting is a global priority, with efforts made by different countries to strengthen their pharmacovigilance systems. Some success can be seen in gradually improving per-capita ADR reporting rates. The varying reporting rates and measures taken by each country may serve as a basis for further research and exchange of best practices to improve drug safety monitoring worldwide.
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.
- 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
Time-resolved X-ray crystallography experiments were first performed in the 1980s, yet they remained a niche technique for decades. With the recent advent of X-ray free electron laser (XFEL) sources and serial crystallographic techniques, time-resolved crystallography has received renewed interest and has become more accessible to a wider user base. Despite this, time-resolved structures represent < 1 % of models deposited in the world-wide Protein Data Bank, indicating that the tools and techniques currently available require further development before such experiments can become truly routine. In this chapter, we demonstrate how applying data multiplexing to time-resolved crystallography can enhance the achievable time resolution at moderately intense monochromatic X-ray sources, ranging from synchrotrons to bench-top sources. We discuss the principles of multiplexing, where this technique may be advantageous, potential pitfalls, and experimental design considerations.
We present a novel system that leverages curators in the loop to develop a dataset and model for detecting structure features and functional annotations at residue-level from standard publication text. Our approach involves the integration of data from multiple resources, including PDBe, EuropePMC, PubMedCentral, and PubMed, combined with annotation guidelines from UniProt, and LitSuggest and HuggingFace models as tools in the annotation process. A team of seven annotators manually curated ten articles for named entities, which we utilized to train a starting PubmedBert model from HuggingFace. Using a human-in-the-loop annotation system, we iteratively developed the best model with commendable performance metrics of 0.90 for precision, 0.92 for recall, and 0.91 for F1-measure. Our proposed system showcases a successful synergy of machine learning techniques and human expertise in curating a dataset for residue-level functional annotations and protein structure features. The results demonstrate the potential for broader applications in protein research, bridging the gap between advanced machine learning models and the indispensable insights of domain experts.
- MeSH
- databáze proteinů MeSH
- lidé MeSH
- proteiny * chemie MeSH
- strojové učení * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
Článek se zabývá problematikou nebezpečných chemických látek v souvislosti s využitím české databáze nebezpečných látek Medis-Alarm. Databáze Medis-Alarm je v tomto příspěvku charakterizována a jsou naznačeny možnosti jejího využití na vysokých školách při výuce studentů. Dalším cílem je vyvolat diskusi o nutném zvýšení bezpečnosti jak obyvatel, tak záchranářů a zlepšení ochrany životního prostředí v České republice.
This article deals with the security of the population and the fire brigade, which uses the Czech database of hazardous substances, Medis-Alarm. This database is connected with the long-term operation of the proven safety transport system TRINS (transport, information and accident system) in the Czech Republic. The Medis-Alarm database is the most widespread one used in the Czech Republic. In this paper, this database is therefore characterized and described in detail, and various possibilities of its use at universities are indicated. The article also aims to provoke a public professional discussion on the necessary increase of the safety of both the population and rescuers and the improvement of environmental protection in the Czech Republic.
- MeSH
- chemické databáze MeSH
- first responder výchova MeSH
- lidé MeSH
- materiálové bezpečnostní listy MeSH
- nebezpečné látky * klasifikace toxicita MeSH
- řízení bezpečnosti MeSH
- studium vysokoškolské MeSH
- únik nebezpečných chemických látek prevence a kontrola MeSH
- výchova a vzdělávání MeSH
- Check Tag
- lidé MeSH
Recent advances in AI-based methods have revolutionized the field of structural biology. Concomitantly, high-throughput sequencing and functional genomics have generated genetic variants at an unprecedented scale. However, efficient tools and resources are needed to link disparate data types-to 'map' variants onto protein structures, to better understand how the variation causes disease, and thereby design therapeutics. Here we present the Genomics 2 Proteins portal ( https://g2p.broadinstitute.org/ ): a human proteome-wide resource that maps 20,076,998 genetic variants onto 42,413 protein sequences and 77,923 structures, with a comprehensive set of structural and functional features. Additionally, the Genomics 2 Proteins portal allows users to interactively upload protein residue-wise annotations (for example, variants and scores) as well as the protein structure beyond databases to establish the connection between genomics to proteins. The portal serves as an easy-to-use discovery tool for researchers and scientists to hypothesize the structure-function relationship between natural or synthetic variations and their molecular phenotypes.
Advancements in deep learning speech representations have facilitated the effective use of extensive unlabeled speech datasets for Parkinson's disease (PD) modeling with minimal annotated data. This study employs the non-fine-tuned wav2vec 1.0 architecture to develop machine learning models for PD speech diagnosis tasks, such as cross-database classification and regression to predict demographic and articulation characteristics. The primary aim is to analyze overlapping components within the embeddings on both classification and regression tasks, investigating whether latent speech representations in PD are shared across models, particularly for related tasks. Firstly, evaluation using three multi-language PD datasets showed that wav2vec accurately detected PD based on speech, outperforming feature extraction using mel-frequency cepstral coefficients in the proposed cross-database classification scenarios. In cross-database scenarios using Italian and English-read texts, wav2vec demonstrated performance comparable to intra-dataset evaluations. We also compared our cross-database findings against those of other related studies. Secondly, wav2vec proved effective in regression, modeling various quantitative speech characteristics related to articulation and aging. Ultimately, subsequent analysis of important features examined the presence of significant overlaps between classification and regression models. The feature importance experiments discovered shared features across trained models, with increased sharing for related tasks, further suggesting that wav2vec contributes to improved generalizability. The study proposes wav2vec embeddings as a next promising step toward a speech-based universal model to assist in the evaluation of PD.
- MeSH
- databáze faktografické * MeSH
- deep learning MeSH
- lidé středního věku MeSH
- lidé MeSH
- Parkinsonova nemoc * patofyziologie MeSH
- řeč * fyziologie MeSH
- senioři MeSH
- strojové učení MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Well-documented sleep datasets from healthy adults are important for sleep pattern analysis and comparison with a wide range of neuropsychiatric disorders. Currently, available sleep datasets from healthy adults are acquired using low-density arrays with a minimum of four electrodes in a typical sleep montage. The low spatial resolution is thus prohibitive for the analysis of the spatial structure of sleep. Here we introduce an open-access sleep dataset from 29 healthy adults (13 female, aged 32.17 ± 6.30 years) acquired at the Montreal Neurological Institute. The dataset includes overnight polysomnograms with high-density scalp electroencephalograms incorporating 83 electrodes, electrocardiogram, electromyogram, electrooculogram, and an average of electrode positions using manual co-registrations and sleep scoring annotations. Data characteristics and group-level analysis of sleep properties were assessed. The database can be accessed through ( https://doi.org/10.17605/OSF.IO/R26FH ). This is the first high-density electroencephalogram open sleep database from healthy adults, allowing researchers to investigate sleep physiology at high spatial resolution. We expect that this database will serve as a valuable resource for studying sleep physiology and for benchmarking sleep pathology.
- MeSH
- databáze faktografické MeSH
- dospělí MeSH
- elektroencefalografie * MeSH
- lidé MeSH
- polysomnografie * MeSH
- skalp * MeSH
- spánek * MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
BACKGROUND: This study outlines the development of a highly interoperable federated IT infrastructure for academic biobanks located at the major university hospital sites across Germany. High-quality biosamples linked to clinical data, stored in biobanks are essential for biomedical research. We aimed to facilitate the findability of these biosamples and their associated data. Networks of biobanks provide access to even larger pools of samples and data even from rare diseases and small disease subgroups. The German Biobank Alliance (GBA) established in 2017 under the umbrella of the German Biobank Node (GBN), has taken on the mission of a federated data discovery service to make biosamples and associated data available to researchers across Germany and Europe. METHODS: In this context, we identified the requirements of researchers seeking human biosamples from biobanks and the needs of biobanks for data sovereignty over their samples and data in conjunction with the sample donor's consent. Based on this, we developed a highly interoperable federated IT infrastructure using standards such as Fast Healthcare Interoperability Resources (HL7 FHIR) and Clinical Quality Language (CQL). RESULTS: The infrastructure comprises two major components enabling federated real-time access to biosample metadata, allowing privacy-compliant queries and subsequent project requests. It has been in use since 2019, connecting 16 German academic biobanks, with additional European biobanks joining. In production since 2019 it has run 4941 queries over the span of one year on more than 900,000 biosamples collected from more than 170,000 donors. CONCLUSION: This infrastructure enhances the visibility and accessibility of biosamples for research, addressing the growing demand for human biosamples and associated data in research. It also underscores the need for improvements in processes beyond IT infrastructure, aiming to advance biomedical research and similar infrastructure development in other fields.
- MeSH
- banky biologického materiálu * MeSH
- biomedicínský výzkum MeSH
- databáze faktografické MeSH
- lidé MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
- Německo MeSH
