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This work analyzes hemodynamic phenomena within the aorta of two elderly patients and their impact on blood flow behavior, particularly affected by an endovascular prosthesis in one of them (Patient II). Computational Fluid Dynamics (CFD) was utilized for this study, involving measurements of velocity, pressure, and wall shear stress (WSS) at various time points during the third cardiac cycle, at specific positions within two cross sections of the thoracic aorta. The first cross-section (Cross-Section 1, CS1) is located before the initial fluid bifurcation, just before the right subclavian artery. The second cross-section (Cross-Section 2, CS2) is situated immediately after the left subclavian artery. The results reveal that, under regular aortic geometries, velocity and pressure magnitudes follow the principles of fluid dynamics, displaying variations. However, in Patient II, an endoprosthesis near the CS2 and the proximal border of the endoprosthesis significantly disrupts fluid behavior owing to the pulsatile flow. The cross-sectional areas of Patient I are smaller than those of Patient II, leading to higher flow magnitudes. Although in CS1 of Patient I, there is considerable variability in velocity magnitudes, they exhibit a more uniform and predictable transition. In contrast, CS2 of Patient II, where magnitude variation is also high, displays irregular fluid behavior due to the endoprosthesis presence. This cross-section coincides with the border of the fluid bifurcation. Additionally, the irregular geometry caused by endovascular aneurysm repair contributes to flow disruption as the endoprosthesis adjusts to the endothelium, reshaping itself to conform with the vessel wall. In this context, significant alterations in velocity values, pressure differentials fluctuating by up to 10%, and low wall shear stress indicate the pronounced influence of the endovascular prosthesis on blood flow behavior. These flow disturbances, when compounded by the heart rate, can potentially lead to changes in vascular anatomy and displacement, resulting in a disruption of the prosthesis-endothelium continuity and thereby causing clinical complications in the patient.

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Worldwide urban landscapes are expanding because of the growing human population. Urban ecosystems serve as habitats to highly diverse communities. However, studies focusing on the diversity and structure of ectomycorrhizal communities are uncommon in this habitat. In Colombia, Quercus humboldtii Bonpl. is an ectomycorrhizal tree thriving in tropical montane forests hosting a high diversity of ectomycorrhizal fungi. Q. humboldtii is planted as an urban tree in Bogotá (Colombia). We studied how root-associated fungal communities of this tree change between natural and urban areas. Using Illumina sequencing, we amplified the ITS1 region and analyzed the resulting data using both OTUs and Amplicon Sequence Variants (ASVs) bioinformatics pipelines. The results obtained using both pipelines showed no substantial differences between OTUs and ASVs for the community patterns of root-associated fungi, and only differences in species richness were observed. We found no significant differences in the species richness between urban and rural sites based on Fisher's alpha or species-accumulation curves. However, we found significant differences in the community composition of fungi present in the roots of rural and urban trees with rural communities being dominated by Russula and Lactarius and urban communities by Scleroderma, Hydnangium, and Trechispora, suggesting a high impact of urban disturbances on ectomycorrhizal fungal communities. Our results highlight the importance of urban trees as reservoirs of fungal diversity and the potential impact of urban conditions on favoring fungal species adapted to more disturbed ecosystems.

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X-ray diagnostics are widely used to detect various diseases, such as bone fracture, pneumonia, or intracranial hemorrhage. This method is simple and accessible in most hospitals, but requires an expert who is sometimes unavailable. Today, some diagnoses are made with the help of deep learning algorithms based on Convolutional Neural Networks (CNN), but these algorithms show limitations. Recently, Capsule Networks (CapsNet) have been proposed to overcome these problems. In our work, CapsNet is used to detect whether a chest X-ray image has disease (COVID or pneumonia) or is healthy. An improved model called DRCaps is proposed, which combines the advantage of CapsNet and the dilation rate (dr) parameter to manage images with 226 × 226 resolution. We performed experiments with 16,669 chest images, in which our model achieved an accuracy of 90%. Furthermore, the model size is 11M with a reconstruction stage, which helps to avoid overfitting. Experiments show how the reconstruction stage works and how we can avoid the max-pooling operation for networks with a stride and dilation rate to downsampling the convolution layers. In this paper, DRCaps is superior to other comparable models in terms of accuracy, parameters, and image size handling. The main idea is to keep the model as simple as possible without using data augmentation or a complex preprocessing stage.

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Human Immunodeficiency virus (HIV) and its clinical entity, the Acquired Immunodeficiency Syndrome (AIDS) continue to represent an important health burden worldwide. Although great advances have been made towards determining the way viral genetic diversity affects clinical outcome, genetic association studies have been hindered by the complexity of their interactions with the human host. This study provides an innovative approach for the identification and analysis of epidemiological associations between HIV Viral Infectivity Factor (Vif) protein mutations and four clinical endpoints (Viral load and CD4 T cell numbers at time of both clinical debut and on historical follow-up of patients. Furthermore, this study highlights an alternative approach to the analysis of imbalanced datasets, where patients without specific mutations outnumber those with mutations. Imbalanced datasets are still a challenge hindering the development of classification algorithms through machine learning. This research deals with Decision Trees, Naïve Bayes (NB), Support Vector Machines (SVMs), and Artificial Neural Networks (ANNs). This paper proposes a new methodology considering an undersampling approach to deal with imbalanced datasets and introduces two novel and differing approaches (MAREV-1 and MAREV-2). As theses approaches do not involve human pre-determined and hypothesis-driven combinations of motifs having functional or clinical relevance, they provide a unique opportunity to discover novel complex motif combinations of interest. Moreover, the motif combinations found can be analyzed through traditional statistical approaches avoiding statistical corrections for multiple tests.

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The World Health Organization (WHO) African Region is struggling with increasing harm associated with alcohol consumption. Legislators of Sao Tome and Principe, concerned about this harm and the high prevalence of alcohol use disorders, designed a comprehensive alcohol control bill to tackle this situation. Input into the design of the bill was obtained through interviews involving many stakeholders. The process had five phases: (i) scoping the problem to understand the social burden of the harm caused by alcohol consumption; (ii) updating the evidence on alcohol policies and identifying areas for legislative interventions; (iii) drafting the bill; (iv) aligning the legislative framework of the bill; and (v) initiating the parliamentary procedure. The new bill scored 92/100 using a standardized alcohol control policy scale. The bill covers all domains of WHO's 2010 global strategy to reduce the harmful use of alcohol, and includes the three most cost-effective interventions for reducing alcohol consumption: increased excise taxes on alcohol; bans or comprehensive restrictions on exposure to alcohol advertising; and restrictions on the availability of retailed alcohol through reduced hours of sale. The National Assembly plenary session upheld the bill, which is now under evaluation of the specialized First Commission on Political, Legal, Constitutional and Ethical Affairs. Approval of the bill requires the final voting once it is back with the National Assembly and its promulgation by the President. Drafting an alcohol control bill which is country-led, inclusive, evidence-based and free of interference by the alcohol industry helps prioritize public health objectives over other interests.

La Région africaine de l'Organisation mondiale de la Santé (OMS) fait face à une hausse des dégâts causés par l'alcool. Préoccupés par la situation et par la forte prévalence des troubles liés à cette consommation, les législateurs de Sao Tomé-et-Principe ont élaboré un projet de loi détaillé afin d'y remédier. À l'origine de sa conception, plusieurs entretiens avec différentes parties prenantes. Le processus s'est divisé en cinq phases: (i) définir l'étendue du problème pour évaluer le fardeau que les dégâts provoqués par l'alcool font peser sur la société; (ii) actualiser les données probantes relatives aux politiques en matière d'alcool et identifier les domaines nécessitant une intervention législative; (iii) rédiger le projet de loi; (iv) aligner le cadre législatif du projet de loi; et enfin, (v) initier la procédure parlementaire. Le nouveau projet de loi a obtenu un score de 92/100 sur une échelle d'évaluation standard des mesures de lutte contre l'alcool. Il couvre tous les thèmes repris dans la Stratégie mondiale de l'OMS visant à réduire l'usage nocif de l'alcool, publiée en 2010. Il prévoit également les trois interventions les plus rentables en termes de diminution de la consommation d'alcool: l'augmentation des taxes d'accise sur l'alcool; l'interdiction ou l'instauration de conditions strictes en matière d'exposition à la publicité pour l'alcool; et une disponibilité restreinte des boissons alcoolisées dans le commerce en limitant les heures de vente. L'Assemblée nationale a soutenu le projet de loi en séance plénière. Il est désormais en cours d'évaluation au sein de la première Commission spécialisée en affaires politiques, juridiques, constitutionnelles et éthiques. Pour être adopté, le projet de loi doit revenir à l'Assemblée nationale pour un vote final, puis être promulgué par le président. Une loi globale de lutte contre l'alcool, élaborée par le pays lui-même, fondée sur des faits et n'ayant subi aucune ingérence de la part de l'industrie de l'alcool contribue à faire passer les objectifs de santé publique avant d'autres intérêts.

La Región de África de la Organización Mundial de la Salud (OMS) está tratando de hacer frente a los crecientes daños derivados del consumo de alcohol. Los legisladores de Santo Tomé y Príncipe, preocupados por estos daños y por la alta prevalencia de los trastornos por consumo de alcohol, diseñaron un proyecto de ley integral para el control del alcohol con el fin de solucionar esta situación. Las contribuciones al diseño del proyecto de ley se obtuvieron a través de entrevistas en las que participaron muchas partes interesadas. El proceso constó de cinco fases: (i) la delimitación del problema para comprender la carga social de los daños causados por el consumo de alcohol; (ii) la actualización de los datos sobre las políticas de alcohol y la identificación de las áreas de intervención legislativa; (iii) la redacción del proyecto de ley; (iv) la adaptación del marco legislativo del proyecto de ley; y (v) el inicio del procedimiento parlamentario. El nuevo proyecto de ley obtuvo una puntuación de 92/100 según una escala estandarizada de políticas para el control del alcohol. El proyecto de ley abarca todos los ámbitos de la estrategia mundial que la OMS puso en marcha en 2010 para reducir el uso nocivo del alcohol, e incluye las tres intervenciones más rentables para reducir el consumo de alcohol: el aumento de los impuestos especiales sobre el alcohol; la prohibición o la restricción general de la exposición a la publicidad del alcohol; y la restricción de la disponibilidad del alcohol al por menor mediante la reducción del horario de venta. La sesión plenaria de la Asamblea Nacional respaldó el proyecto de ley, que ahora está bajo evaluación de la Comisión Primera especializada en Asuntos Políticos, Jurídicos, Constitucionales y Éticos. La aprobación del proyecto de ley requiere la votación final una vez que regrese a la Asamblea Nacional y que el Presidente lo promulgue. La elaboración de un proyecto de ley para el control del alcohol que sea liderado por el país, inclusivo, basado en la evidencia y libre de interferencias por parte de la industria del alcohol ayuda a priorizar los objetivos de salud pública sobre otros intereses.

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Video tracking involves detecting previously designated objects of interest within a sequence of image frames. It can be applied in robotics, unmanned vehicles, and automation, among other fields of interest. Video tracking is still regarded as an open problem due to a number of obstacles that still need to be overcome, including the need for high precision and real-time results, as well as portability and low-power demands. This work presents the design, implementation and assessment of a low-power embedded system based on an SoC-FPGA platform and the honeybee search algorithm (HSA) for real-time video tracking. HSA is a meta-heuristic that combines evolutionary computing and swarm intelligence techniques. Our findings demonstrated that the combination of SoC-FPGA and HSA reduced the consumption of computational resources, allowing real-time multiprocessing without a reduction in precision, and with the advantage of lower power consumption, which enabled portability. A starker difference was observed when measuring the power consumption. The proposed SoC-FPGA system consumed about 5 Watts, whereas the CPU-GPU system required more than 200 Watts. A general recommendation obtained from this research is to use SoC-FPGA over CPU-GPU to work with meta-heuristics in computer vision applications when an embedded solution is required.

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The study of infectious disease behavior has been a scientific concern for many years as early identification of outbreaks provides great advantages including timely implementation of public health measures to limit the spread of an epidemic. We propose a methodology that merges the predictions of (i) a computational model with machine learning, (ii) a projection model, and (iii) a proposed smoothed endemic channel calculation. The predictions are made on weekly acute respiratory infection (ARI) data obtained from epidemiological reports in Mexico, along with the usage of key terms in the Google search engine. The results obtained with this methodology were compared with state-of-the-art techniques resulting in reduced root mean squared percentage error (RMPSE) and maximum absolute percent error (MAPE) metrics, achieving a MAPE of 21.7%. This methodology could be extended to detect and raise alerts on possible outbreaks on ARI as well as for other seasonal infectious diseases.

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Despite the importance of Aedes, Haemagogus and Sabethes in the transmission of yellow fever virus (YFV) and the public health impacts of recent YFV epidemics in the Americas, relatively little has been reported on the biology and ecology of these vectors. Many Aedes, Haemagogus and Sabethes spp. in the American tropics inhabit and develop in the forest canopy and are difficult to sample with conventional entomological surveillance methods. We tested the utility of two previously developed phytotelmata-style oviposition traps (bamboo Guadua angustifolia) and (monkey-pot Lecythis minor), for collecting immature forms of these mosquitoes in a forest near the community of Aruza Abajo, Darién Province, Panama. Our results showed distribution of mosquito species emerging from the two types of traps was found to be significantly different (X2 = 210.23; df = 14; P < 0.001), with significantly greater numbers of Sabethes (Peytonulus) aurescens (Lutz) and Sabethes (Peytonulus) undosus (Coquillett) emerging from the bamboo traps. More females of Sabethes (Sabethes) cyaneus (Fabricius) were captured in the monkey-pot traps, although the difference was not significant. No differences were observed in the average time to emergence for the two traps. These results suggest that various phytotelmata-style traps, including monkey-pot and bamboo, could be used to improve entomological surveillance of YFV vectors in the American tropic.

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Killer-cell immunoglobulin-like receptors (KIRs) are membrane proteins expressed by cells of innate and adaptive immunity. The KIR system consists of 17 genes and 614 alleles arranged into different haplotypes. KIR genes modulate susceptibility to haematological malignancies, viral infections, and autoimmune diseases. Molecular epidemiology studies rely on traditional statistical methods to identify associations between KIR genes and disease. We have previously described our results by applying support vector machines to identify associations between KIR genes and disease. However, rules specifying which haplotypes are associated with greater susceptibility to malignancies are lacking. Here we present the results of our investigation into the rules governing haematological malignancy susceptibility. We have studied the different haplotypic combinations of 17 KIR genes in 300 healthy individuals and 43 patients with haematological malignancies (25 with leukaemia and 18 with lymphomas). We compare two machine learning algorithms against traditional statistical analysis and show that the "a priori" algorithm is capable of discovering patterns unrevealed by previous algorithms and statistical approaches.

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