Quality of life associated with treatment adherence in patients with type 2 diabetes: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Despite certain contradictions, an association has been identified between adherence to drug treatment and the quality of life in patients with type 2 diabetes. The contradictions observed emphasize the importance of using different methods to measure treatment adherence, or the association of psychological precursors of adherence with quality of life. For this reason, we have used an indirect method to measure adherence (pill count), as well as two adherence behaviour precursors (attitude and knowledge), to assess the association between adherence and the quality of life in type 2 diabetes patients.</p> <p>Methods</p> <p>A cross-sectional comparative study on a random sample of 238 type 2 diabetic patients was carried out over one year in four family medicine units of the Mexican Institute of Social Security (IMSS) in Aguascalientes, Mexico. Treatment adherence was measured using the indirect method of pill count to assess adherence behaviour, obtaining information at two home visits. In the first we recorded the medicine prescribed and in the second, we counted the medicine remaining to determine the proportion of the medicine taken. We also assessed two adherence behaviour precursors: the patients' knowledge regarding their medical prescription measured through a structured questionnaire; and attitudes to treatment adherence using a Likert scale. Quality of life was measured through the WHOQOL-100 (the WHO Quality of Life questionnaire). Information concerning both knowledge and attitude was obtained through interviews with the patients. A multiple linear regression model was constructed to establish the relationship between each quality of life domain and the variables related to adherence, controlling for covariates.</p> <p>Results</p> <p>There was no association between quality of life and treatment adherence behaviour. However, the combination of strong knowledge and a positive attitude was associated with five of the six quality of life domains.</p> <p>Conclusion</p> <p>The results suggest that it is important to explore psychological precursors of treatment adherence behaviour in type 2 diabetic patients. Indeed, we consider that it will be useful to carry out interventions that change negative attitudes towards treatment adherence and that promote medical prescription knowledge, which may help to improve the quality of life of such patients.</p

Temperature-Sensitive Gels for Intratumoral Delivery of β-Lapachone: Effect of Cyclodextrins and Ethanol

This work evaluated the potential of Pluronics (varieties F127 and P123) in combination with solubilizing agents to be used as syringeable in situ gelling depots of intratumoral β-lapachone (βLAP). Pluronic dispersions prepared at various concentrations in the absence and the presence of ethanol and randomly methylated β-cyclodextrin (RMβCD) were characterized regarding their rheological properties, drug solubilization capacity, and in vitro release. Pluronic F127 (18–23%) formulations combined high ability to solubilize βLAP (enhancement solubility factor up to 50), adequate gel temperature range (over 25°C), and gel strength at 37°C enough to guarantee the permanence of the formulation in the administration site for a period of time. βLAP release rate was finely tuned by the concentration of the polymer and the addition of RMβCD (diffusion coefficient ranging between 9 and 69 μg·cm−2). The ethanol increases βLAP release rate but simultaneously led to weak gels. This paper shows that βLAP formulations involving temperature-reversible Pluronic gels may be suitable for intratumoral drug delivery purposes

3D printing of medicines: Engineering novel oral devices with unique design and drug release characteristics

YesThree dimensional printing (3DP) was used to engineer novel oral drug delivery devices, with specialised design configurations loaded with multiple actives, with applications in personalised medicine. A filament extruder was used to obtain drug-loaded - paracetamol (acetaminophen) or caffeine - filaments of polyvinyl alcohol with characteristics suitable for use in fused-deposition modelling 3D printing. A multi-nozzle 3D printer enabled fabrication of capsule-shaped solid devices, containing paracetamol and caffeine, with different internal structures. The design configurations included a multilayer device, with each layer containing drug, whose identity was different from the drug in the adjacent layers; and a two-compartment device comprising a caplet embedded within a larger caplet (DuoCaplet), with each compartment containing a different drug. Raman spectroscopy was used to collect 2-dimensional hyper spectral arrays across the entire surface of the devices. Processing of the arrays using direct classical least squares component matching to produce false colour representations of distribution of the drugs showed clearly the areas that contain paracetamol and caffeine, and that there is a definitive separation between the drug layers. Drug release tests in biorelevant media showed unique drug release profiles dependent on the macrostructure of the devices. In the case of the multilayer devices, release of both drugs was simultaneous and independent of drug solubility. With the DuoCaplet design it was possible to engineer either rapid drug release or delayed release by selecting the site of incorporation of the drug in the device, and the lag-time for release from the internal compartment was dependent on the characteristics of the external layer. The study confirms the potential of 3D printing to fabricate multiple-drug containing devices with specialized design configurations and unique drug release characteristics, which would not otherwise be possible using conventional manufacturing methods.The full-text of this article will be released for public view at the end of the publisher embargo on 10 Oct 2016

Experimental Evaluation of the Factors That Influence CylindricalWater Projection Devices against IEDs

Terrorists usually employ Improvised Explosive Devices (IEDs) to cause maximum damage with a single action, in asymmetric war scenarios. In the counter-terrorism fight, bomb disposal specialists have to combat these instruments by safeguarding their lives, avoiding fortuitous IED explosion, and preserving evidence of the device that could lead to the capture of the perpetrators. Some very effective deactivation tools that combine these features are high-speed water-explosive projection devices. To understand and quantify the impacts of the many factors that intervene in their operation and effectiveness, extensive experimental tests should be conducted. However, Operations Research techniques allow robust results to be obtained by minimizing experiments. This study focuses on the use of Design of Experiments (DoE), with a factorial experiment plan divided into two levels, to analyze the influence of the amount of explosive, the diameter of the device (that is, the mass of water to be projected), the density of the water, the distance at which the IED is located, and the resistance of the inner tube material. Results show that the mass of explosive, the diameter of the device, the interaction of the mass of explosive and the density of the water, and the interaction between the resistance of the inner tube and the diameter of the container have a strong influence on the speed of projected water.This work was supported by the Cuerpo Nacional de Policía and Centro Universitario de la Defensa de Zaragoza (grant number: CUD2020-21)

Resumen de la tarea Rest-Mex en IberLEF 2022: Sistema de Recomendación, Análisis de Sentimiento y Predicción de Semáforo Covid para Textos Turísticos Mexicanos

This paper presents the framework and results from the Rest-Mex task at IberLEF 2022. This task considered three tracks: Recommendation System, Sentiment Analysis and Covid Semaphore Prediction, using texts from Mexican touristic places. The Recommendation System task consists in predicting the degree of satisfaction that a tourist may have when recommending a destination of Nayarit, Mexico, based on places visited by the tourists and their opinions. On the other hand, the Sentiment Analysis task predicts the polarity of an opinion issued and the attraction by a tourist who traveled to the most representative places in Mexico. We have built corpora for both tasks considering Spanish opinions from the TripAdvisor website. As a novelty, the Covid Semaphore Prediction task aims to predict the color of the Mexican Semaphore for each state, according to the Covid news in the state, using data from the Mexican Ministry of Health. This paper compares and discusses the participants’ results for all three tacks.Este artículo presenta el marco y los resultados de la tarea Rest-Mex en IberLEF 2022. Esta tarea consideró tres sub tareas: Sistema de recomendación, Análisis de sentimiento y Predicción de semáforo Covid, utilizando textos de lugares turísticos mexicanos. La tarea del Sistema de Recomendación consiste en predecir el grado de satisfacción que puede tener un turista al recomendar un destino de Nayarit, México, con base en los lugares visitados por los turistas y sus opiniones. Por otro lado, la tarea de Análisis de Sentimiento predice la polaridad de una opinión emitida y la atracción por parte de un turista que viajó a los lugares más representativos de México. Hemos construido corpus para ambas tareas teniendo en cuenta las opiniones en español de TripAdvisor. Como novedad, la tarea de Predicción de Semáforo Covid tiene como objetivo predecir el color del Semáforo Mexicano para cada estado, de acuerdo a las noticias Covid en el estado, utilizando datos de la Secretaría de Salud de México. Este documento compara y discute los resultados de los participantes para las tres sub tareas

Resumen de la tarea Rest-Mex en IberLEF 2023: Investigaci´on sobre An´alisis de Sentimiento para Textos Tur´ısticos Mexicanos

This paper presents the framework and results of the Rest-Mex task at IberLEF 2023, focusing on sentiment analysis and text clustering of tourist texts. The study primarily focuses on texts related to tourist destinations in Mexico, although this edition included data from Cuba and Colombia for the first time. The sentiment analysis task aims to predict the polarity of opinions expressed by tourists, classifying the type of place visited, whether it’s a tourist attraction, hotel, or restaurant, as well as the country it is located in. On the other hand, the text clustering task aims to classify news articles related to tourism in Mexico. For both tasks, corpora were built using Spanish opinions extracted from TripAdvisor and news articles from Mexican media. This article compares and discusses the results obtained by the participants in both sub-tasks. Additionally, a method is proposed to measure the easiness of a multi-class text classification corpus, along with an approach for system selection in a possible late fusion scheme.Este artículo presenta el marco y los resultados de la tarea Rest-Mex en IberLEF 2023, que se enfoca en el análisis de sentimiento y agrupamiento de textos turísticos. El estudio se centra principalmente en textos relacionados con destinos turísticos en México, aunque esta edición incluyó datos de Cuba y Colombia por primera vez. La tarea de análisis de sentimiento tiene como objetivo predecir la polaridad de opiniones expresadas por turistas, clasificando el tipo de lugar visitado, ya sea un atractivo turístico, un hotel o un restaurante, así como el país en el que se encuentra. Por otro lado, la tarea de agrupamiento de textos busca clasificar noticias relacionadas con el turismo en México. Para ambas tareas, se construyeron corpus utilizando opiniones en español extraídas de TripAdvisor y noticias de medios mexicanos. En este artículo, se comparan y discuten los resultados obtenidos por los participantes en ambas sub tareas. Además, se propone un método para medir la facilidad de un corpus de clasificación textual multi-clase, así como un enfoque para la selección de sistemas en un posible esquema de fusión tardía.The authors thank the Mexican Academy of Tourism Research (AMIT) for their support of the project ”Creation of a labeled database related to tourist destinations for training artificial intelligence models for classifying relevant topics” through the call ”I Research Projects 2022”, which originated this work

Sequencing of Non-model Plants for Understanding the Physiological Responses in Plants

From a genomic point of view, plants are complex organisms. Plants adapt to the environment, by developing different physiological and genetic properties, changing their genomic and expression profiles of adaptive factors, as exemplified by polyploidy studies. These characteristics along with the presence of duplicated genes/genomes make sequencing with early low-throughput DNA sequencing technologies in plants a challenging task. With the development of new technologies for molecular analysis, including transcriptome, proteome or microarray profiling, a new perspective in the genomic analysis was open, making possible to programs in species without genomic maps. The opportunity to extend molecular studies from laboratory model scale toward naturally occurring plant populations made it possible to precisely answer the longstanding important ecological and evolutionary questions. Some plant species have unique properties that could help to understand their adaptability to environment, crop production, pest protection or other biological processes. Molecular studies on non-model plants, including algae, mosses, ferns and plants with very specific characteristics are ongoing