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Time-series forecasting is one of the most active research topics in artificial intelligence. Applications in real-world time series should consider two factors for achieving reliable predictions: modeling dynamic dependencies among multiple variables and adjusting the model's intrinsic hyperparameters. A still open gap in that literature is that statistical and ensemble learning approaches systematically present lower predictive performance than deep learning methods. They generally disregard the data sequence aspect entangled with multivariate data represented in more than one time series. Conversely, this work presents a novel neural network architecture for time-series forecasting that combines the power of graph evolution with deep recurrent learning on distinct data distributions; we named our method Recurrent Graph Evolution Neural Network (ReGENN). The idea is to infer multiple multivariate relationships between co-occurring time-series by assuming that the temporal data depends not only on inner variables and intra-temporal relationships (i.e., observations from itself) but also on outer variables and inter-temporal relationships (i.e., observations from other-selves). An extensive set of experiments was conducted comparing ReGENN with dozens of ensemble methods and classical statistical ones, showing sound improvement of up to 64.87% over the competing algorithms. Furthermore, we present an analysis of the intermediate weights arising from ReGENN, showing that by looking at inter and intra-temporal relationships simultaneously, time-series forecasting is majorly improved if paying attention to how multiple multivariate data synchronously evolve., Comment: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021

Objective: Today, stress monitoring on wearable devices is challenged by the tension between high-detection accuracy and battery lifetime driven by multimodal data acquisition and processing. Limited research has addressed the classification cost on multimodal wearable sensors, particularly when the features are cost-dependent. Thus, we design a Cost-Aware Feature Selection (CAFS) methodology that trades-off between prediction-power and energy-cost for multimodal stress monitoring. Methods: CAFS selects the most important features under different energy-constraints, which allows us to obtain energy-scalable stress monitoring models. We further propose a self-aware stress monitoring method that intelligently switches among the energy-scalable models, reducing energy consumption. Results: Using CAFS methodology on experimental data and simulation, we reduce the energy-cost of the stress model designed without energy constrains up to 94.37%. We obtain 90.98% and 95.74% as the best accuracy and confidence values, respectively, on unseen data, outperforming state-of-the-art studies. Analyzing our interpretable and energy-scalable models, we showed that simple models that use only heart rate (HR) or skin conductance level (SCL), confidently predict stress for HR >93.30 BPM and non-stress for SCL

Metformin is an oral hypoglycemic drug widely used in the management of type 2 diabetes mellitus. We have recently demonstrated that metformin exhibits activity in models of nociceptive and neuropathic pain. However, little is known about its effects in experimental models of inflammation and inflammatory pain. Thus, the present study aimed to evaluate the activity of metformin in experimental models of inflammation and inflammatory pain in mice, as well as the underlying mechanisms. Previous (1 h) per os (p.o.) administration of metformin (250, 500 or 1000 mg/kg) inhibited the mechanical allodynia and paw edema induced by intraplantar (i.pl.) injection of carrageenan (600 μg) and also the pleurisy induced by this stimulus (200 μg, intrapleural). In the model of mechanical allodynia and paw edema induced by carrageenan, metformin also exhibited activity when administered after (1 h) the inflammatory stimulus. Metformin (1000 mg/kg) reduced the production of tumor necrosis factor-α induced by i.pl. injection of carrageenan. Metformin antiallodynic effect was not affected by previous administration of naltrexone (5 or 10 mg/kg, intraperitoneal) or cyproheptadine (5 or 10 mg/kg, p.o). However, this effect was abolished by previous administration of glibenclamide (20 or 40 mg/kg, p.o). In conclusion, the results demonstrate the activity of metformin in models of inflammation and inflammatory pain. In addition, the results indicate that the activity of metformin may be mediated by activation of ATP-sensitive potassium channels and reduction of production of inflammatory mediators. Altogether, these results stimulate the conduction of studies aiming to evaluate whether metformin may be repositioned in the treatment of patients with painful and inflammatory disorders.

High-energy batteries for automotive applications require cells to endure well over a decade of constant use, making their long-term stability paramount. This is particularly challenging for emerging cell chemistries containing silicon, for which extended testing information is scarce. While much of the research on silicon anodes has focused on mitigating the consequences of volume changes during cycling, comparatively little is known about the time-dependent degradation of silicon-containing batteries. Here we discuss a series of studies on the reactivity of silicon that, collectively, paint a picture of how the chemistry of silicon exacerbates the calendar aging of lithium-ion cells. Assessing and mitigating this shortcoming should be the focus of future research to fully realize the benefits of this battery technology. Silicon-containing batteries are increasingly becoming a reality in the mass market, but their calendar aging behaviours have received comparatively little attention. Researchers from the Silicon Consortium Project discuss the issues surrounding the calendar lifetime of silicon anodes for lithium-ion batteries.

Candidiasis (e.g., oral, gastrointestinal, vaginal, urinary tract, systemic) is a worldwide growing problem, since antifungal resistance and immunosuppression states are rising. To address this problem, very few drugs are available for the treatment of

This study evaluated the presence of radiolucid lesions in digital panoramic radiographs from the archives of the State University of Paraiba (UEPB) Diagnostic Imaging Clinic, performed in 2017. After surveying the radiographs performed by the service in that year, those with radiolucent lesions were selected, being excluded those with poor quality and with patient positioning errors. By means of a structured form, the characteristics observed in the radiographs were recorded by a single trained and calibrated observer. The analysis took place through descriptive statistics and all ethical aspects were respected. There was a low prevalence (14.2%) of radiographs with radiolucent lesions, which mainly affected young female patients. These lesions were small in size, located predominantly in the posterior periapical region of the mandible, with a unilocular aspect, being associated with a posterior tooth, mainly premolar. Inflammatory lesions were the most prevalent, with a presumptive diagnosis highlighting the predominance of abscesses followed by cysts/granulomas. The dentigerous cyst was the third most prevalent odontogenic lesion, occurring in its entirety in females. Odontogenic keratocysts and Stafne's bone cavity were also detected.

International audience; The interest for patient trajectory prediction, a sort of computer-aided medicine, has steadily increased with the pace of artificial intelligence innovation. Notwithstanding, the design of effective systems able to predict clinical outcomes based on the history of a patient is far from trivial. Works so far are based on neural architectures with low performance, especially when using low-cardinality datasets; alternatively, complex inference approaches are hard to reproduce and/or extrapolate as they are designed for very specific circumstances. We introduce LIG-Doctor, an artificial neural network architecture based on two Minimal Gated Recurrent Unit networks functioning in a bidirectional parallel manner, benefiting from temporal events both forward and backward. In comparison to state-of-the-art works, consistent improvements were achieved in prognosis prediction, as assessed with metrics Recall@k, Precision@k, F1-score, and AUC-ROC. Besides the detailed delineation of our architecture, a sequence of experiments is reported with insights that progressively guided design decisions to inspire future works on similar problems. Our results shall contribute to the improvement of computer-aided medicine and, more generally, to processes related to the design of neural network architectures.

O presente estudo visa avaliar o perfil de risco cardiovascular de uma populacao voluntaria nas proximidades de uma unidade de atendimento terciario, com posterior construcao de um modelo piloto de educacao continuada. Objetiva relatar a experiencia profissional e academica na construcao e implementacao de um projeto de intervencao baseado em dados coletados por um planejamento situacional, a Campanha Nacional de Combate a Hipertensao Arterial.

Oral candidiasis are among the most common noncommunicable diseases, related with serious local and systemic illnesses. Although these infections can occur in all kinds of patients, they are more recurrent in immunosuppressed ones such as patients with HIV, hepatitis, cancer or under long antimicrobial treatments. Candida albicans continues to be the most frequently identified Candida spp. in these disorders, but other non- C. albicans Candida are rising. Understanding the immune responses involved in oral Candida spp. infections is a key feature to a successful treatment and to the design of novel therapies. In this review, we performed a literature search in PubMed and WoS, in order to examine and analyze common oral Candida spp.–bacteria/ Candida–Candida interactions and the host immunity response in oral candidiasis.

We investigate the complex band structure and forced response of flexural waves propagating in an elastic metamaterial thick plate. Mindlin-Reissner thick plate theory is considered. We study the influence of periodic arrays of spring-mass resonators attached to the surface of a homogeneous thick plate on the formation of Bragg-type and locally resonant band gaps. The plane wave expansion and extended plane wave expansion approaches are used to compute the complex band structure and wave shapes of the metamaterial thick plate with attached spring-mass resonators. An experimental analysis is conducted with a 3D-printed metamaterial plate with resonators. Modal shapes, forced response and band structure are computed by finite element and wave finite element methods. Analytical, numerical and experimental results present good agreement.

Soil ecosystem service (SES) approaches evidence the importance of soil for human well-being, contribute to improving dialogue between science and decision-making and encourage the translation of scientific results into public policies. Herein, through systematic review, we assess the state of the art of SES approaches in tropical regions. Through this review, 41 publications were identified; while most of these studies considered SES, a lack of a consistent framework to define SES was apparent. Most studies measured soil natural capital and processes, while only three studies undertook monetary valuation. Although the number of publications increased (from 1 to 41), between 2001 and 2019, the total number of publications for tropical regions is still small. Countries with the largest number of publications were Brazil (n = 8), Colombia (n = 6) and Mexico (n = 4). This observation emphasizes an important knowledge gap pertaining to SES approaches and their link to tropical regions. With global momentum behind SES approaches, there is an opportunity to integrate SES approaches into policy and practice in tropical regions. The use of SES evaluation tools in tropical regions could transform how land use decisions are informed, mitigating soil degradation and protecting the ecosystems that soil underpins. Made available in DSpace on 2021-04-01T02:26:10Z (GMT). No. of bitstreams: 1 Systematic-review-of-soil-ecosystem-services-2021.pdf: 968680 bytes, checksum: c21bd70cec854956f333a7af7e80d711 (MD5) Previous issue date: 2021

Staphylococcal scarlet fever is a rare infectious skin disease, with few cases reported in literature. The etiology is related to the staphylococcal epidermolytic toxin.

A previously healthy 14-year-old girl presented to an unscheduled consultation with recent symptoms of myalgias, sore throat, and rhinorrhea. Her physical examination was unremarkable except for bilateral, firm supraclavicular masses. Concern for malignancy lead to investigation and the radiologic diagnosis of bilateral, asymptomatic cervical ribs was made.

Access to early myoelectric training can be a crucial step in mastering prosthesis control. Controlling a prothesis is a cognitively demanding task with high rejection rates. Serious games not only provide patients with an opportunity to train their myoelectric control, but also help maintain their engagement throughout the extensive rehabilitation process. This work proposes a novel serious game design to train machine learning based myoelectric control, implemented in the form of a music-based app. The prototype of the game was evaluated by seven able-bodied participants and three clinical professionals with regard to system usability and motivation. Results showed positive outcomes in motivation, and a need for specific system usability improvements.

Objective: Feeding restriction in rats alters the oscillators in suprachiasmatic, paraventricular, and arcuate nuclei, hypothalamic areas involved in food intake. In the present study, using the same animals and experimental protocol, we aimed to analyze if food restriction could reset clock genes ( Clock, Bmal1 ) and genes involved in lipid metabolism ( Pgc1a, Pparg, Ucp2 ) through nutrient-sensing pathways ( Sirt1, Ampk, Nampt ) in peripheral tissues. Materials and methods: Rats were grouped according to food access: Control group (CG, food ad libitum ), Restricted night-fed (RF-n, food access during 2 h at night), Restricted day-fed (RF-d, food access during 2 h in the daytime), and Day-fed (DF, food access during 12 h in the daytime). After 21 days, rats were decapitated at ZT3 (0900-1000 h), ZT11 (1700-1800 h), or ZT17 (2300-2400 h). Blood, liver, brown (BAT) and peri-epididymal (PAT) adipose tissues were collected. Plasma corticosterone and gene expression were evaluated by radioimmunoassay and qPCR, respectively. Results: In the liver, the expression pattern of Clock and Bmal1 shifted when food access was dissociated from rat nocturnal activity; this phenomenon was attenuated in adipose tissues. Daytime feeding also inverted the profile of energy-sensing and lipid metabolism-related genes in the liver, whereas calorie restriction induced a pre-feeding increased expression of these genes. In adipose tissues, Sirt1 expression was modified by daytime feeding and calorie restriction, with concomitant expression of Pgc1a , Pparg , and Ucp2 but not Ampk and Nampt . Conclusion: Feeding restriction reset clock genes and genes involved in lipid metabolism through nutrient-sensing-related genes in rat liver, brown, and peri-epididymal adipose tissues.

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this necessity, a large number of specialised simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introducemsprimeversion 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure andtskitlibrary. We summarisemsprime’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialised alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

Resveratrol is a polyphenolic stilbene derivative widely present in grapes and red wine. Broadly known for its antioxidant effects, numerous studies have also indicated that it exerts anti-inflammatory and antiaging abilities and a great potential in cancer therapy. Regrettably, the oral administration of resveratrol has pharmacokinetic and physicochemical limitations such as hampering its effects so that effective administration methods are demanding to ensure its efficiency. Thus, the present review explores the published data on the application of resveratrol nanoformulations in cancer therapy, with the use of different types of nanodelivery systems. Mechanisms of action with a potential use in cancer therapy, negative effects, and the influence of resveratrol nanoformulations in different types of cancer are also highlighted. Finally, the toxicological features of nanoresveratrol are also discussed.

Resumen El uso de dispositivos supragloticos para el manejo de la via aerea ha aumentado en popularidad, principalmente debido a su alta tasa de exito y bajas complicaciones. Sin embargo, hay muy poca informacion disponible sobre las potenciales complicaciones y especificas, con respecto a su uso en ninos. Presentamos la primera descripcion de un nino que desarrollo enfisema subcutaneo despues del uso de una mascarilla laringea. Creemos que se necesita una mayor conciencia del riesgo de eventos adversos perioperatorios con la insercion de mascarillas laringeas en la poblacion pediatrica.

The use of supraglottic airway devices has been increasing in popularity, mostly due to their high success rate and low complications. However, there is very little information available about the potential and group specific concerns regarding their use in children. We present the first description of a child that developed subcutaneous emphysema after the use of a laryngeal mask. We believe that more awareness to the risk of perioperative adverse events with laryngeal mask insertion in the paediatric population is needed.

Content-based image retrieval (CBIR) aims to display, as a result of a search, images with the same visual contents as a query. This problem has attracted increasing attention in the area of computer vision. Learning-based hashing techniques are amongst the most studied search approaches for approximate nearest neighbors in large-scale image retrieval. With the advance of deep neural networks in image representation, hashing methods for CBIR have started using deep learning to build binary codes. Such strategies are generally known as deep hashing techniques. In this paper, we present a comprehensive deep hashing survey for the task of image retrieval with multiple labels, categorizing the methods according to how the input images are treated: pointwise, pairwise, tripletwise and listwise, as well as their relationships. In addition, we present discussions regarding the cost of space, efficiency and search quality of the described models, as well as open issues and future work opportunities.

Polymeric nanoparticles represent one major class of nanomaterials that has been proposed to improve the sustainability of agricultural operations by delivering organic agrochemicals such as pesticides more efficiently. Polymeric nanoparticles can improve efficiency through improved targeting and uptake, slow release, and lower losses of the chemicals, while also conferring the benefits of biodegradability and biocompatibility. This review provides a tutorial to environmental nanotechnology researchers interested in initiating research on the development and application of polymeric nanocarriers for delivery of agrochemicals, including pesticides and growth promoters for crops and antibiotics for livestock. In particular, this review covers the wider suite of methods that will be required beyond those typically used for inorganic metal or metal oxide nanoparticles, including synthesis of custom polymeric nanocarriers and characterization and tuning of agrochemical loading and release profiles. Benefits of polymeric nanocarriers are then discussed in terms of the physicochemical properties and fate and transport behaviors that contribute to higher efficiency and lesser environmental impacts compared to traditional (non-nano) formulations. Finally, opportunities for environmental nanotechnology researchers to collaborate with material scientists, microbiologists, and agricultural scientists to optimize the development of polymeric nanocarriers for agriculture are discussed.

Detection of spatial variability of data that can improve crop management is a key factor for precision agriculture. In agriculture, there is a need for tools to assist farmers in decision-making about proper nutrient management, aiming to achieve their full productive potential. Based on that, this study aimed to (1) determine the spatial correlations between the chlorophyll index (CI) and the foliar levels of nitrogen, phosphorus and potassium (NPK) in the coffee crop using geostatistical tools; and (2) to evaluate the potential use of this index as a tool for site-specific nutrient management in an irrigated coffee field. For that, a study was carried out in a 2.1 ha area under arabica coffee cultivation in Paula Cândido, Minas Gerais State, Brazil. Samplings of the CI were performed in 1141 plants using a portable chlorophyll meter (SPAD-502). Regarding the NPK analysis, leaf samples from one of each 10 plants used to measure the CI were taken for chemical analysis (114 plants). Then, the data were submitted to descriptive and geostatistical analysis. For the spatial correlation analysis, the Moran Bivariate Global (I) and the Local index (Ixy) were used. The results showed a moderate correlation between the CI and N (0.500), showing the potential of the chlorophyll meter as a tool for site-specific nitrogen management in the coffee crop. Differently, the CI is not recommended for P and K management since they were not well correlated. Lastly, as a tool that performs indirect measurements, the results from the chlorophyll meter should be validated by field measurements to local calibrations.

Chronic pelvic pain syndrome (CPPS) can be triggered by a various types of gynecological, gastrointestinal, urological, and musculoskeletal disorders. Recently, the role of the central nervous system has proven to be an integral part on the development of any chronic pain syndrome, including CPPS. However, owing to the complex and heterogeneous etiology and pathophysiology of CPPS, the establishment of effective therapeutic interventions remains challenging for both physicians and patients. Nonetheless, recent studies have pointed that medicinal plants and their secondary metabolites can be effectively used in CPPS therapy, besides contributing to restore the patients' quality of life and potentiate the conventional CPPS management. In this sense, this review aims to provide a careful overview on the biomedical data for the use of medicinal plants use and their secondary metabolites on CPPS management.

Human mobility has a significant impact on several layers of society, from infrastructural planning and economics to the spread of diseases and crime. Representing the system as a complex network, in which nodes are assigned to regions (e.g., a city) and links indicate the flow of people between two of them, physics-inspired models have been proposed to quantify the number of people migrating from one city to the other. Despite the advances made by these models, our ability to predict the number of commuters and reconstruct mobility networks remains limited. Here, we propose an alternative approach using machine learning and 22 urban indicators to predict the flow of people and reconstruct the intercity commuters network. Our results reveal that predictions based on machine learning algorithms and urban indicators can reconstruct the commuters network with 90.4% of accuracy and describe 77.6% of the variance observed in the flow of people between cities. We also identify essential features to recover the network structure and the urban indicators mostly related to commuting patterns. As previously reported, distance plays a significant role in commuting, but other indicators, such as Gross Domestic Product (GDP) and unemployment rate, are also driven-forces for people to commute. We believe that our results shed new lights on the modeling of migration and reinforce the role of urban indicators on commuting patterns. Also, because link-prediction and network reconstruction are still open challenges in network science, our results have implications in other areas, like economics, social sciences, and biology, where node attributes can give us information about the existence of links connecting entities in the network., Comment: 28 pages, 5 figures

Reproducible patient positioning is important in radiotherapy (RT) of head-and-neck cancer. We therefore compared set-up errors in head-and-neck RT resulting from three different patient positioning systems. Patients were either treated with a standard head support (SHS) and conventional treatment couch (SHS-3, n = 10), a SHS and rotational couch (SHS-6, n = 10), or an individual head support (IHS) and rotational couch (IHS-6, n = 10). Interfraction mean translation vector lenghts were significantly lower for IHS-6 compared to SHS-3 (0.8 ± 0.3 mm vs. 1.4 ± 0.7 mm, P = 0.001). Intrafraction displacement was comparable among cohorts. This study showed that the use of a six degrees of freedom couch combined with an IHS in head-and-neck RT resulted in better interfraction reproducibility. Keywords: Head-and-neck cancer, Immobilization, Head support, Set-up correction, Six degrees of freedom couch, Cone-beam CT

With an increasing range of products in global and local markets, more options are available for individuals to enhance their image and their (cognitive, social and physical) performance. These ‘performance consumptions’ relate to ideals of well‐being and improvement, and are based on constructed desires, expectations and needs that go beyond the (often blurred) dichotomy of health and illness. Drawing from mixed‐methods research in Maputo, Mozambique, this paper discusses individuals’ use of medicines and other substances – pharmaceuticals, food supplements, traditional herbs, cosmetics and energy drinks – for managing different aspects of their everyday lives. Through an overview of the main consumption practices, we explore the underlying purposes and strategies of users, and the perceived legitimacy and risks involved when using a variety of products accessible through formal and informal exchange channels. From tiredness to sexual and aesthetic management, we show how the body becomes the locus of experimentation and investment to perform in accordance with socially expected roles, individual aspirations and everyday tasks. With insights from individuals’ accounts in Maputo, we aim to add to discussions on pharmaceuticalisation of body management by showing how the emergence of new performance consumptions is articulated with the reconfiguration of more ‘traditional’ consumption practices. info:eu-repo/semantics/acceptedVersion

One of the major complications that patients experience during pharmacological treatment is the occurrence of adverse drug reactions (ADRs). The most affected organs are the liver, kidney, heart and the gastrointestinal-immune system. In comparison to the other organs, less progress has been made on human-relevant prediction of drug-induced intestinal toxicity, evidencing current large data gaps. The most widely used drugs that are associated with intestinal damage include chemotherapeutics, such as 5-Fluorouracil or Tyrosine Kinase Inhibitors (TKIs), as well as non-steroidal anti-inflammatory drugs (NSAIDs). Chemotherapeutics are regarded as inducers of acute intestinal toxicity whereas NSAIDs are associated with chronic inflammation of the intestine. In view of the fact that only a few studies have been dedicated to studying cellular and genomic responses in relation to drug-induced intestinal ADRs, little is known about how intestinal toxicity develops after exposure to such drugs or which molecular mechanisms are involved. Therefore, new models and experiments are required to establish transcriptomic responses and alterations of molecular markers induced by different medicines. This review summarizes the available information about transcriptomic responses and biomarkers of toxicity induced by 5-FU, NSAIDS or TKIs in different experimental models. Future investigation should address the challenges in predicting intestinal toxicity induced by drugs and unveil specific gene expression profiles that can be applied in the development of safer drugs.

During the last few decades many researchers have been interested in acoustic wave propagation in artificial periodic composites known as sonic crystals. Sonic crystals have received renewed attention because they exhibit acoustic band gaps where there are only evanescent waves. Sonic crystals consist of a periodic array of scatterers embedded in a host medium. The host medium and/or scatterers are fluids. We investigate the band structure of acoustic waves propagating in a sustainable sonic crystal composed by miriti fibers and air, regarding square and triangular lattices. Miriti fibers are extracted from buriti palm petiole (Mauritia flexuosa Mart.), which is a typical specie that grows in Amazonian region. We also study the influence of miriti fiber cross section, i.e. circular, hollow circular, square and rotated square with a 45° angle of rotation with respect to x, y axes. Plane wave expansion method is used to solve the wave equation. Acoustic band gaps are observed for all miriti fiber cross sections and lattices. The best performances of the sustainable sonic crystal are for triangular lattice, regarding circular and rotated square miriti fiber cross sections, and for square lattice with circular miriti fiber cross section. We suggest that the sustainable sonic crystal should be feasible for noise management.

In Ethiopia, home to the largest African herd of cattle, animal trypanosomiasis is a major constraint to the efforts made for food self-sufficiency. We searched for trypanosomes in tsetse flies caught in the Nech Sar National Park (NSNP), Southern Rifty Valley, Ethiopia, at the district of Arba Minch where intensive tsetse control is successfully improving cattle productivity. Despite narrow geographical and temporal scales of our survey, we found a remarkable diversity of trypanosomes using the sensitive and discriminative method of fluorescent fragment length barcoding. We also found a high density of Glossina pallidipes (47.8 flies/trap/day) showing relevant cytochrome oxidase I gene variability. The identification of blood meal sources through cytochrome b gene sequences revealed cattle and warthog as preferential ungulate hosts of tsetse flies in the study area. Our survey identified trypanosomes in 38% of the 287 flies examined (42% of proboscises and 32% of guts), and the following infection rates for each species: Trypanosoma vivax 23%, T. simiae 23%, T. congolense 22%, T. theileri 19.9%, T. (Trypanozoon) spp. 10.5%, T. godfreyi 9.4%, T. simiae Tsavo 6.3%, and mixed infections in proboscises (30%) and guts (61%). Phylogenetic analysis revealed T. vivax of the "West African-South American" genotype, T. congolense of Savannah (16.7%), Kilifi (3.5%) and Forest (2.1%) lineages, and new genotypes of T. simiae. To our knowledge, this is the first survey of trypanosomes in the NSNP, and the most comprehensive molecular characterisation of trypanosomes in tsetse flies of Ethiopia, including the comparison with samples from West and other East African countries. Our results support the diversification of T. vivax in East Africa, and the dispersion of the genotype herein identified in Ethiopia across West Africa and then in South America. Altogether, tsetse density and infection rate, repertoire of trypanosomes and feeding behavior indicate a high risk of transmission of trypanosomes pathogenic to ungulates by tsetse flies from the NSNP, a hotspot of tsetse infestation and trypanosome diversity. Our findings reinforce the need for constant surveillance, and the reliance on community efforts to prevent reinvasion of tsetse and animal trypanosomiasis in suppressed areas of Southern Rift Valley.

Plasma actuators are promising devices with several possible applications in active flow control field. One of the possible applications of these devices is wake reduction in ground vehicles. By delaying the flow separation and reducing the wake of the flow, these devices allow to reduce the drag which, in turns, leads to important savings in terms of fuel consumption. In the current work, the operation of dielectric barrier discharge plasma actuators is studied considering their application for active flow control in ground vehicles. A plasma actuator was fabricated and experimentally characterized in terms of electrical and mechanical features. A ground vehicle model, with different rear slant angles, was constructed and preliminary tests were performed in a wind tunnel. The dielectric barrier discharge plasma actuator was implemented on the top rear part of the model, in the first separation zone of the flow, in order to attach the flow to the surface and reduce the wake flow. The experimental tests were performed for rear slant angles of 30°, 45° and 60°. The different vehicle models were tested for a flow velocity of 5m/s. Flow visualization and velocity measurements were performed in order to analyze the flow behavior and the active flow control effect obtained by the plasma actuation. It is shown that by using plasma actuators on the rear of the model, the plasma actuation pulls the flow toward the surface and reduce the wake of the flow.

Dielectric Barrier Discharge (DBD) plasma actuators are simple devices with great potential for active flow control applications. Further, it has been recently proven their ability for applications in the area of heat transfer, such as film cooling of turbine blades or ice removal. The dielectric material used in the fabrication of these devices is essential in determining the device performance. However, the variety of dielectric materials studied in the literature is very limited and the majority of the authors only use Kapton, Teflon, Macor ceramic or poly(methyl methacrylate) (PMMA). Furthermore, several authors reported difficulties in the durability of the dielectric layer when the actuators operate at high voltage and frequency. Also, it has been reported that, after long operation time, the dielectric layer suffers degradation due to its exposure to plasma discharge, degradation that may lead to the failure of the device. Considering the need of durable and robust actuators, as well as the need of higher flow control efficiencies, it is highly important to develop new dielectric materials which may be used for plasma actuator fabrication. In this context, the present study reports on the experimental testing of dielectric materials which can be used for DBD plasma actuators fabrication. Plasma actuators fabricated of poly(vinylidene fluoride) (PVDF) and polystyrene (PS) have been fabricated and evaluated. Although these dielectric materials are not commonly used as dielectric layer of plasma actuators, their interesting electrical and dielectric properties and the possibility of being used as sensors, indicate their suitability as potential alternatives to the standard used materials. The plasma actuators produced with these nonstandard dielectric materials were analyzed in terms of electrical characteristics, generated flow velocity and mechanical efficiency, and the obtained results were compared with a standard actuator made of Kapton. An innovative calorimetric method was implemented in order to estimate the thermal power transferred by these devices to an adjacent flow. These results allowed to discuss the ability of these new dielectric materials not only for flow control applications but also for heat transfer applications.

Patients with severe COVID-19, such as individuals in intensive care units (ICU), are exceptionally susceptible to bacterial and fungal infections. The most prevalent fungal infections are aspergillosis and candidemia. Nonetheless, other fungal species (for instance, Histoplasma spp., Rhizopus spp., Mucor spp., Cryptococcus spp.) have recently been increasingly linked to opportunistic fungal diseases in COVID-19 patients. These fungal co-infections are described with rising incidence, severe illness, and death that is associated with host immune response. Awareness of the high risks of the occurrence of fungal co-infections is crucial to downgrade any arrear in diagnosis and treatment to support the prevention of severe illness and death directly related to these infections. This review analyses the fungal infections, treatments, outcome, and immune response, considering the possible role of the microbiome in these patients. The search was performed in Medline (PubMed), using the words “fungal infections COVID-19”, between 2020–2021.

The current coronavirus disease (COVID-19) outbreak is a significant threat to human health and the worldwide economy. Coronaviruses cause a variety of diseases, such as pneumonia-like upper respiratory tract illnesses, gastroenteritis, encephalitis, multiple organ failure involving lungs and kidneys which might cause death. Since the pandemic started there have been more than 107 million COVID-19 infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and ∼2.4 million deaths globally. SARS-CoV-2 is easily transmitted from person-to-person and has spread quickly across all continents. With the continued increase in morbidity and mortality caused by COVID-19, and the damage to the global economy, there is an urgent need for effective prevention and treatment strategies. The advent of safe and effective vaccines has been a significant step forward in the battle against COVID-19, however treatment of the symptoms associated with the disease still requires new anti-viral and anti-inflammatory drug therapies. To this end, scientists have been investigating available natural products that may be effective against SARS-CoV-2, with some products showing promise in fighting several viral infections. Since many natural products are dietary components or are prepared as dietary supplements people tend to consider them safer than synthetic drugs. For example, Traditional Chinese Medicines have been effectively utilized to treat SARS-CoV-2 infected patients with promising results. In this review, we summarize the current knowledge of COVID-19 therapies and the therapeutic potential of medicinal plant extracts and natural compounds for the treatment of several viral infections, with special emphasis on SARS-CoV-2 infection. Realistic strategies that can be employed for the effective use of bioactive compounds for anti-SARS-CoV-2 research are also provided.

Automated prognosis has been a topic of intense research. Many works have sought to learn from Electronic Health Records using Recurrent Neural Networks that, despite promising results, have been overcome by novel techniques. We introduce APEHR, a Transformer approach that leverages medical prognosis using the latest technology Neural Network Transformer, which has demonstrated superior results in problems whose data is organized in sequential fashion. We contribute with an innovative problem modeling along with a detailed discussion of how Transformers can be used in the medical domain. Our results demonstrate a prognostic performance that surpasses previous works by at least 6% for metric Recall@k in the public dataset MIMIC-III.

The perivascular adipose tissue (PVAT) differs from other fat depots and exerts a paracrine action on the vasculature. The spleen has an important role in the immune response, and it was observed to have either a protective role or a contribution to obesity-related diseases. However, the relation between spleen and PVAT is elusive in obesity. We investigated the role of spleen in the inflammatory profile of the mesenteric PVAT (mPVAT) from mice fed a high-fat diet (HFD) for 16 weeks. Male C57Bl/6 mice were sham-operated or splenectomized (SPX) and fed a HFD for 16 weeks. mPVAT morphology was evaluated by hematoxylin and eosin staining, infiltrated immune cells were evaluated by flow cytometry, inflammatory cytokines were evaluated by ELISA and the splenic cell chemotaxis mediated by mPVAT was evaluated using a transwell assay. In SPX mice, HFD induced adipocyte hypertrophy and increased immune cell infiltration and proinflammatory cytokine levels in mPVAT. However, none of these effects were observed in mPVAT from sham-operated mice. Spleen from HFD fed mice presented reduced total leukocytes and increased inflammatory markers when compared to the spleen from control mice. Chemotaxis of spleen cells mediated by mPVAT of HFD fed mice was reduced in relation to standard diet fed mice. The spleen protects mPVAT against the effects of 16-week HFD. This information was missing, and it is important because PVAT is different from other fat depots and data cannot be extrapolated from any type of adipose tissue to PVAT.

The objective of this study was to investigate potential correlates of dispositional optimism and quality of life in patients with depression and panic disorder. The study used a cross-sectional design. The analyzed sample consisted of 77 participants with panic disorder and 75 participants with depression attending two outpatient clinics at the Psychiatry Institute of the Federal University of Rio de Janeiro. Both groups presented similar impairments in optimism and quality of life. In the panic disorder group, optimism scores were significantly correlated with a decrease in anxiety and depression scores (r = 0.26 and r = 0.37, respectively); in the depression group, increases in optimism scores were significantly correlated with decreases in anxiety and depression scores (r = 0.23 and r = 0.3, respectively). The present study showed that high anxiety and depression are correlated with poor optimism and quality of life scores in panic disorder and depression groups. Thus, psychological treatments that can address these topics, besides acute symptoms, are crucial to the absolute recovery of patients.

Interactions between healthcare users and providers are an essential but often problematic element in therapeutic processes. In many settings worldwide, there has been a general recognition of the importance of adopting care approaches that understand patients as active agents, moving away from traditional paternalistic forms of interaction. Research shows that improving the quality of communication in therapeutic encounters fosters mutual understanding and cooperation in healthcare processes, helping to create the grounding conditions for building trusting relationships. But what are the communicative mechanisms through which trust in healthcare providers is cultivated? Going beyond the traditional 'doctor-patient' dyad analysis, and using data from a mixed-method study on medicine use in Maputo, Mozambique, this paper explores healthcare users' experiences and interpretations of their interactions with public healthcare professionals (medical doctors and prescribing nurses) and community pharmacy workers (pharmacists, technicians and other attendants). The analysis evolves around various communicative and relational aspects, emphasised by users as meaningful and underpinning different qualities of care, competence, integrity and trustworthiness. These attributes were assessed based on a combination of verbal conversation and information exchange, together with the use of other (non-verbal) situationally valued artefacts such as biomedical tools and communicative rituals performed by providers. This study shows that despite healthcare providers' different attributes of competence and authority, it is mainly their communicative performances during interactions that influence whether (symbolic) trust has the space to evolve or crystallise. Moreover, while performing certain rituals may be an effective form of communication, the lack of other (verbal and non-verbal) communicative elements during the interaction may compromise patient trust in what is being prescribed or advised. Efforts to improve the quality and responsiveness of healthcare services centred around citizens' needs should take users' perspectives into account and pay particular attention to these communicative and relational dimensions.

Candida auris is a novel and major fungal pathogen that has triggered several outbreaks in the last decade. The few drugs available to treat fungal diseases, the fact that this yeast has a high rate of multidrug resistance and the occurrence of misleading identifications, and the ability of forming biofilms (naturally more resistant to drugs) has made treatments of C. auris infections highly difficult. This review intends to quickly illustrate the main issues in C. auris identification, available treatments and the associated mechanisms of resistance, and the novel and alternative treatment and drugs (natural and synthetic) that have been recently reported. © 2021 by the authors. Licensee MDPI, Basel, Switzerland., L.. thanks the Slovak Research and Development Agency under contract No. APVV-15-0347 and the grant of VEGA 1/0537/19 from the Ministry of Education, Science, Research, and the Sport of the Slovak Republic. C.F.R. would like to acknowledge the UID/EQU/00511/2020 Project-Laboratory of Process Engineering, Environment, Biotechnology and Energy (LEPABE)-financed by national funds through FCT/MCTES (PIDDAC)., info:eu-repo/semantics/publishedVersion

Current carbon pricing and trading mechanisms, despite their efficacy in reducing GHG emissions from industry, will not be sufficient to achieve Net Zero targets. Current mechanisms that redress emissions are largely economic disincentives , in effect financial penalties for emitters. In order to attain Net Zero futures, financial incentives for activities that sequester carbon from the atmosphere are needed. Herein, we present the environmental and economic co-benefits of soil re-carbonization and justify support for soil carbon remuneration. With increasing momentum to develop green economies, and projected increases in carbon price, growth in the global carbon market is inevitable. The establishment of a soil-based carbon economy, within this emerging financial space, has the potential to deliver a paradigm shift that will accelerate climate change mitigation, and concurrently realize net gains for soil health and the delivery of soil ecosystem services. Pivotal to the emergence of a global soil carbon economy will be a consensus on certification instruments used for long-term soil carbon storage, and the development of robust institutional agreements and processes to facilitate soil carbon trading.

The pandemic experienced in recent months has raised questions that should be investigate in the clinical practice. Transplacental transmission of SARS-CoV-2 and the consequences to the fetus and newborn have called attention due to the increasing number of infections, contradicting previous evidences that there was no possibility of coronavirus transmission from the mother to the fetus. In this work we showed three cases of pregnant women with positive SARS-CoV-2 antibodies serology on admission in Naval Hospital Marcílio Dias (HNMD), Rio de Janeiro, Brazil. Samples of umbilical cord blood was double positive (IgM and IgG) for one patient, double negative for one patient and positive for IgG and negative for IgM for third patient. Maternal and neonatal nasopharyngeal swab samples analyzed by PCR for SARS-CoV-2 was positive for two maternal patients and negative for all newborns tested. It was possible to detect the SARS-CoV-2 in amniotic fluid and umbilical cord blood using the nested-PCR technics, thus being successfully evidenced transplacental transmission. We suggested that nasopharyngeal swab PCR test of neonates does not have a correlation with vertical transmission and thus, this molecular test is not useful for investigation of transplacental infection.

Background: Pregnant women are susceptible to the novel coronavirus (SARS-CoV-2), and the consequences for the fetus are still uncertain. Here, we present a case of a pregnant woman with subclinical hypothyroidism and a plasminogen activator inhibitor type 1 (PAI-1) 4G/5G polymorphism who was infected with SARS-CoV-2 at the end of the third trimester of pregnancy, with unexpected evolution of death of the newborn 4 days postpartum.Methods: Nested PCR was performed to detect the virus, followed by ssDNA sequencing.Results: Transplacental transmission of SARS-CoV-2 can cause placental inflammation, ischemia, and neonatal viremia, with complications such as preterm labor and damage to the placental barrier in patients with PAI-1 4G/5G polymorphism.Conclusion: We showed a newborn with several damages potentially caused due to the PAI-1 polymorphisms carried by the mother infected with SARS-CoV-2 during pregnancy.

Herein, we review aspects of leading-edge research and innovation in materials science that exploit big data and machine learning (ML), two computer science concepts that combine to yield computational intelligence. ML can accelerate the solution of intricate chemical problems and even solve problems that otherwise would not be tractable. However, the potential benefits of ML come at the cost of big data production; that is, the algorithms demand large volumes of data of various natures and from different sources, from material properties to sensor data. In the survey, we propose a roadmap for future developments with emphasis on computer-aided discovery of new materials and analysis of chemical sensing compounds, both prominent research fields for ML in the context of materials science. In addition to providing an overview of recent advances, we elaborate upon the conceptual and practical limitations of big data and ML applied to materials science, outlining processes, discussing pitfalls, and reviewing cases of success and failure.

Biofilms are the major way of life for both bacteria and fungi [...]

Access to genetic testing and counselling in remote areas such as the Madeira archipelago, in the Northern Atlantic Ocean, may be complex. Different counselling methods, including telegenetics, should be explored. In this study, we characterise the Hereditary Breast/Ovarian Cancer (HBOC) families with Madeira ancestry enrolled in our programme. Of a total of 3,566 index patients tested between January 2000 and June 2018, 68 had Madeira ancestry and 22 were diagnosed with a pathogenic germline variant (PV). As in the whole group, BRCA2 PV were more frequent in Madeira patients (68.4%: c.9382C>T (26.3%), c.658_659del (21%), c.156_157insAlu (10.5%), c.793+1G>A (5.3%) and c.298A>T (5.3%). However, the most frequently diagnosed PV in Madeira patients was the BRCA1 c.3331_3334del (31.6%). BRCA1/2 detection rates were 27.9% and 10.5% for Madeira and the whole group, respectively. This study is the first characterisation of HBOC patients with Madeira ancestry. A distinct pattern of BRCA1/2 variants was observed, and the geographic clustering of BRCA1 c.3331_3334del variant may support the possibility of a founder mutation previously described in Northern Portugal. The high detection rate observed reinforces the need to reduce gaps in access to genetic testing in Madeira and other remote areas. According to current guidelines, timely identification of HBOC patients can contribute to their ongoing care and treatment.

Background Sepsis is an emergency medical condition that can lead to death and it is defined as a life-threatening organ dysfunction caused by immune dysregulation in response to an infection. It is considered the main killer in intensive care units. Sepsis associated-encephalopathy (SAE) is mostly caused by a sepsis-induced systemic inflammatory response. Studies report SAE in 14–63% of septic patients. Main SAE symptoms are not specific and usually include acute impairment of consciousness, delirium and/or coma, along with electroencephalogram (EEG) changes. For those who recover from sepsis and SAE, impaired cognitive function, mobility and quality of life are often observed months to years after hospital discharge, and there is no treatment available today to prevent that. Inflammation and oxidative stress are key players for the SAE pathophysiology. Gold nanoparticles have been demonstrated to own important anti-inflammatory properties. It was also reported 20 nm citrate-covered gold nanoparticles (cit-AuNP) reduce oxidative stress. In this context, we tested whether 20 nm cit-AuNP could alleviate the acute changes caused by sepsis in brain of mice, with focus on inflammation. Sepsis was induced in female C57BL/6 mice by cecal ligation and puncture (CLP), 20 nm cit-AuNP or saline were intravenously (IV) injected 2 h after induction of sepsis and experiments performed 6 h after induction. Intravital microscopy was used for leukocyte and platelet adhesion study in brain, blood brain barrier (BBB) permeability carried out by Evans blue assay, cytokines measured by ELISA and real time PCR, cell adhesion molecules (CAMs) by flow cytometry and immunohistochemistry, and transcription factors, by western blotting. Results 20 nm cit-AuNP treatment reduced leukocyte and platelet adhesion to cerebral blood vessels, prevented BBB failure, reduced TNF- concentration in brain, and ICAM-1 expression both in circulating polymorphonuclear (PMN) leukocytes and cerebral blood vessels of mice with sepsis. Furthermore, 20 nm cit-AuNP did not interfere with the antibiotic effect on the survival rate of mice with sepsis. Conclusions Cit-AuNP showed important anti-inflammatory properties in the brain of mice with sepsis, being a potential candidate to be used as adjuvant drug along with antibiotics in the treatment of sepsis to avoid SAE

Energy Management Systems are equipments that normally perform the individual supervision of power controllable loads. With the objective of reducing energy costs, those management decisions result from algorithms that select how the different working periods of equipment should be combined, taking into account the usage of the locally generated renewable energy, electricity tariffs etc., while complying with the restrictions imposed by users and electric circuits. Forecasting energy usage, as described in this paper, allows to optimize the management being a major asset.