BACKGROUND: The beginning of the coronavirus disease (COVID-19) epidemic dates back to December 31, 2019, when the first cases were reported in the People's Republic of China. In the Czech Republic, the first three cases of infection with the novel coronavirus were confirmed on March 1, 2020. The joint effort of state authorities and researchers gave rise to a unique team, which combines methodical knowledge of real-world processes with the know-how needed for effective processing, analysis, and online visualization of data. OBJECTIVE: Due to an urgent need for a tool that presents important reports based on valid data sources, a team of government experts and researchers focused on the design and development of a web app intended to provide a regularly updated overview of COVID-19 epidemiology in the Czech Republic to the general population. METHODS: The cross-industry standard process for data mining model was chosen for the complex solution of analytical processing and visualization of data that provides validated information on the COVID-19 epidemic across the Czech Republic. Great emphasis was put on the understanding and a correct implementation of all six steps (business understanding, data understanding, data preparation, modelling, evaluation, and deployment) needed in the process, including the infrastructure of a nationwide information system; the methodological setting of communication channels between all involved stakeholders; and data collection, processing, analysis, validation, and visualization. RESULTS: The web-based overview of the current spread of COVID-19 in the Czech Republic has been developed as an online platform providing a set of outputs in the form of tables, graphs, and maps intended for the general public. On March 12, 2020, the first version of the web portal, containing fourteen overviews divided into five topical sections, was released. The web portal's primary objective is to publish a well-arranged visualization and clear explanation of basic information consisting of the overall numbers of performed tests, confirmed cases of COVID-19, COVID-19-related deaths, the daily and cumulative overviews of people with a positive COVID-19 case, performed tests, location and country of infection of people with a positive COVID-19 case, hospitalizations of patients with COVID-19, and distribution of personal protective equipment. CONCLUSIONS: The online interactive overview of the current spread of COVID-19 in the Czech Republic was launched on March 11, 2020, and has immediately become the primary communication channel employed by the health care sector to present the current situation regarding the COVID-19 epidemic. This complex reporting of the COVID-19 epidemic in the Czech Republic also shows an effective way to interconnect knowledge held by various specialists, such as regional and national methodology experts (who report positive cases of the disease on a daily basis), with knowledge held by developers of central registries, analysts, developers of web apps, and leaders in the health care sector.

• Klíčová slova
• COVID-19, CRISP-DM, Czech Republic, app, coronavirus disease, data mining, epidemiological overview, epidemiology, health data, interactive reporting, modeling, public health, virus, web app,
• MeSH
• Betacoronavirus * MeSH
• COVID-19 MeSH
• data mining MeSH
• internet MeSH
• koronavirové infekce epidemiologie   MeSH
• lidé MeSH
• pandemie MeSH
• SARS-CoV-2 MeSH
• software MeSH
• virová pneumonie epidemiologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika epidemiologie   MeSH

OBJECTIVE: Research on helicopter emergency medical services (HEMS) in major incidents is predominately based on case descriptions reported in a heterogeneous fashion. Uniform data reported with a consensus-based template could facilitate the collection, analysis, and exchange of experiences. This type of database presently exists for major incident reporting at www.majorincidentreporting.net. This study aimed to develop a HEMS-specific major incident template. METHODS: This Delphi study included 17 prehospital critical care physicians with current or previous HEMS experience. All participants interacted through e-mail. We asked these experts to define data variables and rank which were most important to report during an immediate prehospital medical response to a major incident. Five rounds were conducted. RESULTS: In the first round, the experts suggested 98 variables. After 5 rounds, 21 variables were determined by consensus. These variables were formatted in a template with 4 main categories: HEMS background information, the major incident characteristics relevant to HEMS, the HEMS response to the major incident, and the key lessons learned. CONCLUSION: Based on opinions from European experts, we established a consensus-based template for reporting on HEMS responses to major incidents. This template will facilitate uniformity in the collection, analysis, and exchange of experience.

• MeSH
• databáze faktografické MeSH
• delfská metoda MeSH
• konsensus * MeSH
• lékaři MeSH
• letecká záchranná služba * MeSH
• lidé MeSH
• urgentní zdravotnické služby MeSH
• výzkumná zpráva normy   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Evropa MeSH

UNLABELLED: The aim of the study was to identify the reasons for medication administration errors, describe the barriers in their reporting and estimate the number of reported medication administration errors. BACKGROUND: Providing quality and safe healthcare is a key priority for all health systems. Medication administration error belongs to the more common mistakes committed in nursing practice. Prevention of medication administration errors must therefore be an integral part of nursing education. DESIGN: A descriptive and cross-sectional design was used for this study. METHODS: Sociological representative research was carried out using the standardized Medication Administration Error Survey. The research study involved 1205 nurses working in hospitals in the Czech Republic. Field surveys were carried out in September and October 2021. Descriptive statistics, Pearson's and Chi-square automatic interaction detection were used to analyze the data. The STROBE guideline was used. RESULTS: Among the most frequent causes of medication administration errors belong name (4.1 ± 1.4) and packaging similarity between different drugs (3.7 ± 1.4), the substitution of brand drugs by cheaper generics (3.6 ± 1.5), frequent interruptions during the preparation and administration of drugs (3.6 ± 1.5) and illegible medical records (3.5 ± 1.5). Not all medication administration errors are reported by nurses. The reasons for non-reporting of such errors include fear of being blamed for a decline in patient health (3.5 ± 1.5), fear of negative feelings from patients or family towards the nurse or legal liability (3.5 ± 1.6) and repressive responses by hospital management (3.3 ± 1.5). Most nurses (two-thirds) stated that less than 20 % of medication administration errors were reported. Older nurses reported statistically significantly fewer medication administration errors concerning non-intravenous drugs than younger nurses (p < 0.001). At the same time, nurses with more clinical experience (≥ 21 years) give significantly lower estimates of medication administration errors than nurses with less clinical practice (p < 0.001). CONCLUSION: Patient safety training should take place at all levels of nursing education. The standardized Medication Administration Error survey is useful for clinical practice managers. It allows for the identification of medication administration error causes and offers preventive and corrective measures that can be implemented. Measures to reduce medication administration errors include developing a non-punitive adverse event reporting system, introducing electronic prescriptions of medicines, involving clinical pharmacists in the pharmacotherapy process and providing nurses with regular comprehensive training.

• Klíčová slova
• Hospital incident reporting, Medication administration error, Medication error, Nurse practice patterns, Nurses, Nursing research,
• MeSH
• lidé MeSH
• medikační omyly prevence a kontrola   MeSH
• personál sesterský nemocniční * MeSH
• průřezové studie MeSH
• průzkumy a dotazníky MeSH
• řízení rizik MeSH
• zdravotní sestry * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

OBJECTIVES: Our main objective is to design a method of, and supporting software for, interactive correction and semantic annotation of narrative clinical reports, which would allow for their easier and less erroneous processing outside their original context: first, by physicians unfamiliar with the original language (and possibly also the source specialty), and second, by tools requiring structured information, such as decision-support systems. Our additional goal is to gain insights into the process of narrative report creation, including the errors and ambiguities arising therein, and also into the process of report annotation by clinical terms. Finally, we also aim to provide a dataset of ground-truth transformations (specific for Czech as the source language), set up by expert physicians, which can be reused in the future for subsequent analytical studies and for training automated transformation procedures. METHODS: A three-phase preprocessing method has been developed to support secondary use of narrative clinical reports in electronic health record. Narrative clinical reports are narrative texts of healthcare documentation often stored in electronic health records. In the first phase a narrative clinical report is tokenized. In the second phase the tokenized clinical report is normalized. The normalized clinical report is easily readable for health professionals with the knowledge of the language used in the narrative clinical report. In the third phase the normalized clinical report is enriched with extracted structured information. The final result of the third phase is a semi-structured normalized clinical report where the extracted clinical terms are matched to codebook terms. Software tools for interactive correction, expansion and semantic annotation of narrative clinical reports has been developed and the three-phase preprocessing method validated in the cardiology area. RESULTS: The three-phase preprocessing method was validated on 49 anonymous Czech narrative clinical reports in the field of cardiology. Descriptive statistics from the database of accomplished transformations has been calculated. Two cardiologists participated in the annotation phase. The first cardiologist annotated 1500 clinical terms found in 49 narrative clinical reports to codebook terms using the classification systems ICD 10, SNOMED CT, LOINC and LEKY. The second cardiologist validated annotations of the first cardiologist. The correct clinical terms and the codebook terms have been stored in a database. CONCLUSIONS: We extracted structured information from Czech narrative clinical reports by the proposed three-phase preprocessing method and linked it to electronic health records. The software tool, although generic, is tailored for Czech as the specific language of electronic health record pool under study. This will provide a potential etalon for porting this approach to dozens of other less-spoken languages. Structured information can support medical decision making, quality assurance tasks and further medical research.

• Klíčová slova
• Narrative clinical report, classification systems, electronic health record, nomenclatures, structured information, tokens,
• MeSH
• elektronické zdravotní záznamy normy   MeSH
• mezinárodní klasifikace nemocí MeSH
• psaní normy   MeSH
• řízený slovník * MeSH
• sémantika * MeSH
• směrnice jako téma MeSH
• smysluplné využití normy   MeSH
• software MeSH
• správnost dat MeSH
• strojové učení * MeSH
• uživatelské rozhraní počítače MeSH
• zpracování přirozeného jazyka * MeSH
• zpracování textu normy   MeSH
• Publikační typ
• časopisecké články MeSH

This contribution reports the design, synthesis and photochemical properties of a novel cationic, water soluble, β-cyclodextrin (βCD) conjugate integrating an anthracene moiety and a nitroaniline derivative within the primary side of the βCD scaffold. Photoinduced energy transfer between the anthracene and the nitroaniline chromophores effectively suppresses the fluorescence of the anthracene unit. Excitation with visible light triggers the release of nitric oxide (NO) from the nitroaniline chromophore, accompanied to the concomitant revival of the anthracene fluorescence, which acts as an optical reporter for detecting the amount of the NO released. Furthermore, the anthracene moiety photogenerates singlet oxygen (1O2) sequentially to NO release. The conjugate is also able to accommodate hydrophobic guests within the βCD cavity, as proven by using naphthalene as a model compound. In view of the key role NO and 1O2 play as anticancer and antibacterial species, the present βCD derivative represents an intriguing candidate for further studies in biopharmaceutical research addressed to multimodal therapeutic applications.

• Klíčová slova
• Cyclodextrin, Fluorescence, Light, Nitric oxide, Singlet oxygen,
• MeSH
• beta-cyklodextriny chemie   MeSH
• fluorescence MeSH
• hydrofobní a hydrofilní interakce MeSH
• lékové transportní systémy * MeSH
• oxid dusnatý chemie   MeSH
• světlo MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• beta-cyklodextriny MeSH
• oxid dusnatý MeSH

Analyses of user experience in the electronic entertainment industry currently rely on self-reporting methods, such as surveys, ratings, focus group interviews, etc. We argue that self-reporting alone carries inherent problems-mainly the misinterpretation and temporal delay during longer experiments-and therefore, should not be used as a sole metric. To tackle this problem, we propose the possibility of modeling consumer experience using psychophysiological measures and demonstrate how such models can be trained using machine learning methods. We use a machine learning approach to model user experience using real-time data produced by the autonomic nervous system and involuntary psychophysiological responses. Multiple psychophysiological measures, such as heart rate, electrodermal activity, and respiratory activity, have been used in combination with self-reporting to prepare training sets for machine learning algorithms. The training data was collected from 31 participants during hour-long experiment sessions, where they played multiple video-games. Afterwards, we trained and compared the results of four different machine learning models, out of which the best one produced ∼96% accuracy. The results suggest that psychophysiological measures can indeed be used to assess the enjoyment of digital entertainment consumers.

• Klíčová slova
• digital entertainment, electroencephalography, enjoyment, galvanic skin response, heart rate, machine learning, modeling, psychophysiological measures, respiratory activity, user experience,
• MeSH
• algoritmy MeSH
• autonomní nervový systém fyziologie   MeSH
• dospělí MeSH
• galvanická kožní odpověď fyziologie   MeSH
• lidé MeSH
• mladý dospělý MeSH
• psychofyziologie metody   MeSH
• srdeční frekvence fyziologie   MeSH
• strojové učení MeSH
• videohry psychologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: The knowledge of cancer burden in the population, its time trends, and the possibility of international comparison is an important starting point for cancer programs. A reliable interactive tool describing cancer epidemiology in children and adolescents has been nonexistent in the Czech Republic until recently. OBJECTIVE: The goal of this study is to develop a new web portal entitled the Czech Childhood Cancer Information System (CCCIS), which would provide information on childhood cancer epidemiology in the Czech Republic. METHODS: Data on childhood cancers have been obtained from the Czech National Cancer Registry. These data were validated using the clinical database of childhood cancer patients and subsequently combined with data from the National Register of Hospitalised Patients and with data from death certificates. These validated data were then used to determine the incidence and survival rates of childhood cancer patients aged 0 to 19 years who were diagnosed in the period 1994 to 2016 (N=9435). Data from death certificates were used to monitor long-term mortality trends. The technical solution is based on the robust PHP development Symfony framework, with the PostgreSQL system used to accommodate the data basis. RESULTS: The web portal has been available for anyone since November 2019, providing basic information for experts (ie, analyses and publications) on individual diagnostic groups of childhood cancers. It involves an interactive tool for analytical reporting, which provides information on the following basic topics in the form of graphs or tables: incidence, mortality, and overall survival. Feedback was obtained and the accuracy of outputs published on the CCCIS portal was verified using the following methods: the validation of the theoretical background and the user testing. CONCLUSIONS: We developed software capable of processing data from multiple sources, which is freely available to all users and makes it possible to carry out automated analyses even for users without mathematical background; a simple selection of a topic to be analyzed is required from the user.

• Klíčová slova
• cancer epidemiology, children, data visualization, software development,
• MeSH
• analýza dat * MeSH
• dítě MeSH
• incidence MeSH
• informační systémy MeSH
• lidé MeSH
• mladiství MeSH
• nádory * epidemiologie   MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• mladiství MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Česká republika epidemiologie   MeSH

A nexus of natural and human variables mediate the success of non-native species that threaten global biodiversity and ecological stability. However, the relative importance and interplays among relevant factors has not been holistically approached. To identify spatial differences and potential connections in relevant natural and human drivers, we analyzed the number of non-native species established in European countries using a newly collated database of established non-native species. We employ a series of broadscale national predictors classified into 'research', 'economy', 'environment & culture', and 'land-use' to predict successful establishment. Our null models, which assume the distribution of non-native species mirrors that of each predictor, accurately predicted non-native species numbers across European countries. However, a few countries were identified as outliers, having significantly over- or underrepresented non-native species numbers based on adjusted quasi-Poisson distribution quantiles. A network analysis of non-native species compositions identified these regions to be central hubs (e.g. Germany, France, and Switzerland), but also highlighted distinct spatial similarities across European countries. Combinations of the predictors 'economy', 'research', and 'environment & culture' explained the largest shares of differences in the number of established non-native species among European countries as well as their reporting rates over time. Individual drivers alone were insufficient to wholly explain national differences, whereas interacting driver categories ultimately accounted for the largest shares of variance. This analysis demonstrates the breadth of predictors that mediate successful establishment, and particularly highlights the relevance of overlooked historical-cultural facets affecting biological invasions.

• Klíčová slova
• Biological invasions, Economy, Environmental change, Europe, Society and culture,
• MeSH
• biodiverzita * MeSH
• ekosystém MeSH
• lidé MeSH
• zachování přírodních zdrojů * MeSH
• zavlečené druhy * statistika a číselné údaje   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Evropa MeSH

DNA Modeller is a microcomputer program for interactively manipulating up to 20 bp in a DNA double helical arrangement. It calculates the van der Waals and electrostatic energies of base-base interactions using the AMBER potential, minimizes the energy with respect to the pair (buckle, propeller, opening, shear, stretch, stagger) and step (tilt, roll, twist, shift, slide, rise) parameters, calculates lengths of the canonical hydrogen bonds between the complementary bases, and calculates interatomic distances between the successive base pairs. Input/output files are simple lists of the step and pair parameters or lists of the atom specifications (N1, C2, etc.) and their Cartesian coordinates (compatible with the Desktop Molecular Modeller*.mol files). The program is supplied with a readbrk utility which transforms PDB/NDB to the *.mol format readable by DNA Modeller. The DNA crystal structures deposited in the PDB or NDB databases can thus be analyzed, and their bases visualized and interactively manipulated. In addition, DNA Modeller can calculate the base pair and step geometrical parameters and interaction energies. A plotter utility creates wire mono or stereo pictures of the bases. This program is designed for IBM-compatible computers working under DOS or can run as a DOS application under MS Windows 3.x or Merge (SCO Unix DOS emulator).

• MeSH
• DNA chemie   genetika   MeSH
• hodnotící studie jako téma MeSH
• konformace nukleové kyseliny MeSH
• molekulární modely * MeSH
• molekulární struktura MeSH
• software * MeSH
• zastoupení bazí MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• DNA MeSH

Linking up with the statistical aspects of dosing the active ingredient in the random powder mixture, the properties of non-random mixtures of micronized active ingredients with auxiliary substances of the particle size larger by an order are summed up. The review of literature aims to report the conditions of the development of interactive mixtures, possible more precise dosing of small amounts of active ingredients, and limitation of the risk of ordered unit segregation. From the technological standpoint, interactive mixtures are relevant primarily for direct compression of tablets and dosing of the micronized active ingredient in dry powder inhalers. From the theoretical standpoint, the data concerning a temporary increase in the solubility of some active ingredients after the development of an amorphous surface during long-term mixing of interactive powder mixtures are of interest.

• MeSH
• farmaceutická chemie MeSH
• fixní kombinace léků * MeSH
• nebulizátory a vaporizátory MeSH
• prášky, zásypy, pudry * MeSH
• tablety MeSH
• Publikační typ
• anglický abstrakt MeSH
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• fixní kombinace léků * MeSH
• prášky, zásypy, pudry * MeSH
• tablety MeSH