Characteristics of illegal and legal cigarette packs sold in Guatemala

BACKGROUND: Guatemala, as a party to the Framework Convention on Tobacco Control (FCTC), is required to regulate cigarette packaging and labeling and eliminate illicit tobacco trade. Current packaging and labeling characteristics (of legal and illegal cigarettes) and their compliance with the FCTC is unknown. METHODS: We sought to analyze package and label characteristics of illegal and legal cigarettes sold in Guatemala. We visited the 22 largest traditional markets in the country to purchase illegal cigarettes. All brands registered on tobacco industry websites were purchased as legal cigarettes. Analysis compared labeling characteristics of illegal and legal packs. FINDINGS: Most (95%) markets and street vendors sold illegal cigarettes; 104 packs were purchased (79 illegal and 25 legal). Ten percent of illegal and none of the legal packs had misleading terms. Half of the illegal packs had a warning label covering 26 to 50% of the pack surface. All legal packs had a label covering 25% of the surface. Illegal packs were more likely to have information on constituents and emissions (85% vs. 45%, p < 0.001) and were less expensive than legal ones (USD 0.70 ± 0.7 and 1.9 ± 1.8, p < 0.001). CONCLUSIONS: In Guatemala, neither illegal nor legal cigarette packs comply with FCTC labeling mandates. Urgent implementation and enforcement of the FCTC is necessary to halt the tobacco epidemic

a cross-sectional study

Publisher Copyright: Copyright © 2023 Gonzalez Delgado, Cortes Gil, Rodriguez Araujo, Mira Solves, Rodriguez Gallo, Salcedo Monsalve, Arrieta Arteta, Villalba Toquica and Morales Ruiz.Objectives: Analyze the presence of acute stress response after adverse events in human talent in Colombian health institutions from 2017 to 2021. Methods: Cross-sectional study of prevalence, carried out on 838 members of the human talent in health (professionals, technicians, technologists, and auxiliaries) of Colombian health institutions in the study period with the application of the EASE instrument. Univariate analysis using descriptive statistical techniques, chi-square and Student’s t-test, and bivariate analysis with a Poisson regression model using the institucional SPSS v. 26. Results: The prevalence of adverse events in the last 5 years was 33.8%, presenting levels of acute stress qualifying as Medium-high emotional overload at 21.91%, while extreme acute stress was at 3.53%. The prevalence of risk for presenting acute stress after being involved in an adverse event was PR: 1.30 (CI: 1.24–1.36). Conclusion: Acute stress in human talent after adverse events is limiting health and care capacity and must be efficiently addressed by health institutions. Psychosocial risk is linked within the framework of the patient safety program and the institutional occupational health and safety management systems.publishersversionpublishe

Estudios de psicologia en ambientes procesales Un analisis de matamemoria

Centro de Informacion y Documentacion Cientifica (CINDOC). C/Joaquin Costa, 22. 28002 Madrid. SPAIN / CINDOC - Centro de Informaciòn y Documentaciòn CientìficaSIGLEESSpai

Variable Importance Analysis in Imbalanced Datasets: A New Approach

Decision-making using machine learning requires a deep understanding of the model under analysis. Variable importance analysis provides the tools to assess the importance of input variables when dealing with complex interactions, making the machine learning model more interpretable and computationally more efficient. In classification problems with imbalanced datasets, this task is even more challenging. In this article, we present two variable importance techniques, a nonparametric solution, called mh-&#x03C7;2, and a parametric method based on Global Sensitivity Analysis. The mh-&#x03C7;2 employs a multivariate continuous response framework to deal with the multiclass classification problem. Based on the permutation importance framework, the proposed mh-&#x03C7;2 algorithm captures the dissimilarities between the distribution of misclassification errors generated by the base learner, Conditional Inference Tree, before and after permuting the values of the input variable under analysis. The GSA solution is based on the Covariance decomposition methodology for multivariate output models. Both solutions will be assessed in a comparative study of several Random Forest-based techniques with emphasis in the multiclass classification problem with different imbalanced scenarios. We apply the proposed techniques in two real application cases in order first, to quantify the importance of the 35 companies listed in the Spanish market index IBEX35 on the economic, political and social uncertainties reflected in economic newspapers in Spain during the first quadrimester of 2020 due to the COVID-19 pandemic and second, to assess the impact of energy factors on the occurrence of spike prices on the Spanish electricity market

Single-cell characterization of metabolic switching in the sugar phosphotransferase system of Escherichia coli

The utilization of several sugars in Escherichia coli is regulated by the Phosphotransferase System (PTS), in which diverse sugar utilization modules compete for phosphoryl flux from the general PTS proteins. Existing theoretical work predicts a winner-take-all outcome when this flux limits carbon uptake. To date, no experimental work has interrogated competing PTS uptake modules with single-cell resolution. Using time-lapse microscopy in perfused microchannels, we analyzed the competition between N-acetyl-glucosamine and sorbitol, as representative PTS sugars, by measuring both the expression of their utilization systems and the concomitant impact of sugar utilization on growth rates. We find two distinct regimes: hierarchical usage of the carbohydrates, and co-expression of the genes for both systems. Simulations of a mathematical model incorporating asymmetric sugar quality reproduce our metabolic phase diagram, indicating that under conditions of nonlimiting phosphate flux, co-expression is due to uncoupling of both sugar utilization systems. Our model reproduces hierarchical winner-take-all behaviour and stochastic co-expression, and predicts the switching between both strategies as a function of available phosphate flux. Hence, experiments and theory both suggest that PTS sugar utilization involves not only switching between the sugars utilized but also switching of utilization strategies to accommodate prevailing environmental conditions

Retos para el gobierno de las universidades en el marco del EEES

The European Higher Education Area (EHEA) requires changes in the way universities are managed. It is an opportunity for correcting imbalances whilst at the same time being a challenge that can mark important differences between universities. This study seeks to identify the challenges and information/training requirements of Spanish university management teams in order to facilitate their integration in the EHEA. Methodology: The Delphi study with the participation of 115 chancellors, vice-chancellors, deans and heads of service of Spanish Universities (EUE) and 26 managers of non-Spanish Universities included in European university quality and management agencies (ENE). For preparing the Delphi study questionnaire, two groups were formed using qualitative research techniques: a first discussion group with the participation of 12 Spanish university managers and a second group in which the Nominal Group technique was applied, with the participation of 18 non-Spanish university managers. Results: The most important challenges are improvement in the quality of education and redefinition of each university's strategy. The EUE group considers it necessary to increase coordination between subjects in order to offer a comprehensive education and promote the renovation of teaching methodologies. The ENE group gives priority to the need for professionalizing university management. The information/training requirements of university managers are: quality management, strategic management and change leadership. Conclusions: There is a notable effort to identify how EHEA integration affects the different disciplines but it is less frequent to address the structural changes needed in universities to be able to successfully accomplish this integration. These include improving the quality of teaching and management, for which managers must have the capacity for innovation and change leadership

A web-based self-assessment model for evaluating multidisiciplinary cancer teams in Spain: development and validation pilot study

Background: Tumor boards constitute the main consensus and clinical decision-making body of multidisciplinary teams (MDTs) in cancer care. With the increasing clinical complexity of treatment options (eg, targeted therapies, multimodal treatments) and the progressive incorporation of new areas of intervention (eg, survivorship care), tumor boards are now required to play a central role in all cancer processes. However, although frameworks are in place to evaluate MDT quality, only few web-based tools are available for this purpose; indeed, no web-based MDT evaluation tools have been developed for or adapted to the Spanish National Health System. Objective: The first aim of this study was to develop a web-based self-assessment model (Autoevaluación de Equipos Multidisciplinares de Atención al Cáncer [AEMAC]) for evaluating multidisciplinary cancer teams in Spain and the second aim was to validate this tool by testing its metric properties, acceptability, and usability. Methods: We designed and validated the AEMAC program in 3 stages. In the first stage (research), we reviewed the available scientific evidence and performed a qualitative case study of good practice in multidisciplinary care within the Spanish National Health System (n=4 centers and 28 health care professionals). The results were used to define the thematic areas and quality criteria for the self-evaluation model, which were then discussed and validated by a group of experts. The second stage (development) involved the technological development of a web app that would be accessible from any mobile device. In the third stage (piloting and validation), we conducted 4 pilot tests (n=15 tumor boards, 243 professionals) and used the results to analyze the acceptability and usefulness of the tool. Results: We designed a self-assessment model based on 5 thematic areas encompassing a total of 25 quality components, which users rated on a 3-option development scale. The evaluation process, which was managed entirely from the web app, consisted of individual self-assessment, group prioritization, and creation of an improvement plan. Cronbach alpha (.86), McDonald's omega (0.88), and various fit indices (comparative fit index between 0.95 and 1 and goodness-of-fit index between 0.97 and 0.99 for all 5 aspects) confirmed internal consistency. The mean rating for overall satisfaction with the tool and for consistency between the content of the tool and the reality of tumor boards was 7.6 out of 10. Conclusions: The results obtained during the period of research and piloting of the AEMAC program showed that it has an appropriate structure and metric properties and could therefore be implemented in a real context and generalized to other hospitals. As a virtual tool, it helps to measure the key aspects of MDT quality, such as effectiveness of collaboration and communication, leadership, and the organizational environment