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Introdução: As complicações micro e macrovasculares da diabetes são resultado de um processo de caráter longo sobre a falta dos cuidados da diabetes, de que resultam problemas cardiovasculares, oftalmológicos e neuropáticos, requerendo por essas questões elevada atenção no tratamento. Descrição do caso: Apresenta-se o relato de caso de um paciente adulto de meia-idade, ex-fumador, com diagnóstico de diabetes mellitus, além da hipertensão e obesidade. A sua alimentação não saudável ao longo dos anos, sedentarismo e altos níveis de estresse resultou num quadro de isquemia vascular periférica, que intensificou as complicações da diabetes, ou seja, problemas micro e macrovasculares, entre eles, a retinopatia e a neuropatia. Por esse histórico, a farmacoterapia do paciente resultou entre as insulinas (regular e NPH), antiagregante plaquetátio, estatina, fibratos, psicotrópicos e os anti-hipertensores. Além disso, detetou-se que seus níveis glicémicos e hemoglobina glicada estão elevados. Ainda se verificaram alterações na lipoproteína de alta densidade (HDL) e triglicéridos. Algumas queixas do paciente no período noturno, como boca seca, tontura e sonolência, são problemas que podem estar relacionados com a terapia concomitante de venlafaxina, gabapentina e amitriptilina. Comentários: De forma geral, recomenda-se a este paciente a prática de exercício físico, como caminhada, por exemplo, diminuição do consumo de hidratos de carbono e sódio, além de algumas alterações na farmacoterapia do paciente.

The use of nature-based solutions (NbS) to address the risks posed by hydro-meteorological hazards have not yet become part of the mainstream policy response, and one of the main reasons cited for this, is the lack of evidence that they can effectively reduce disaster risk. This paper addresses this issue, by providing model-based evidence from five European case studies which demonstrate the effectiveness of five different NbS in reducing the magnitude of the hazard and thus risk, in present-day and possible future climates. In OAL-Austria, the hazard is a deep-seated landslide, and the NbS analysed is afforestation. Modelling results show that in today's climate and a landcover scenario of mature forest, a reduction in landslide velocity of 27.6 % could be achieved. In OAL-Germany, the hazard is river flooding and the NbS analysed is managed grazing with removal of woody vegetation. Modelling results show that the NbS could potentially reduce maximum flood water depth in the near-future (2031–2060) and far-future (2070–2099), by 0.036 m and 0.155 m, respectively. In OAL-Greece, the hazard is river flooding, and the NbS is upscaled natural storage reservoirs. Modelling results show that in a possible future climate the upscaled NbS show most potential in reducing the total flooded area by up to 1.26 km2. In OAL-Ireland, the hazard is surface and river flooding, and the NbS is green roofs. Results from a modelled upscaling analysis under two different climate scenarios show that both maximum flood water depth, and total flooded area were able to be reduced. In OAL-UK, the hazard is shallow landslides, and the NbS is high-density planting of two different tree species. Modelling results under two different climate scenarios show that both tree species were able to improve slope stability, and that this increased over time as the NbS matured. The significance of these results is discussed within the context of the performance of the NbS over time, to different magnitude events, impact with stakeholders in engendering wider support for the adoption of the NbS in the OALs, and the uncertainty in the modelling analyses.

Slicing of animal origin food affects the final quality of products and potentially transfers pathogenic microorganisms as it occurs after microorganism control and elimination steps, such as cooking and pasteurization. Therefore, the food industry needs to ensure the safety of food products to reduce the incidence of foodborne diseases. This requires an understanding of the dangers involved in each stage of production, along with the microorganisms transferred during processing. In this study, we aimed to understand the impact of industrial slicing on mozzarella cheese and ham by investigating the quality indicator microorganisms, aerobic mesophiles, psychrotrophs, total coliforms, Staphylococcus aureus, and pathogens, such as Escherichia coli, Salmonella spp., and Listeria monocytogenes. Samples were collected from pieces (20) and slices (20) of mozzarella cheese and ham. The number of mesophilic aerobes differed significantly before and after slicing (P 0.05). In total, 844 isolates were analyzed for pathogenic genes, and Salmonella spp. were identified in 40% of the piece and 20% of the sliced mozzarella cheese samples and in 30% of the piece and 50% of the sliced ham samples. Furthermore, S. aureus genes with the potential to produce enterotoxins C and D were identified in two sliced mozzarella cheese samples. Slicing of ready-to-eat food is an important step in food microbiology. Our results highlight the importance of maintaining hygienic practices during processing and demonstrate that the microbiological quality of the slicing sample affects the quality and safety of the sliced product.

Characterization of model errors is important when applying satellite-driven evapotranspiration (ET) models to water resource management problems. This study examines how uncertainty in meteorological forcing data and land surface modeling propagate through to errors in final ET data calculated using the Satellite Irrigation Management Support (SIMS) model, a computationally efficient ET model driven with satellite surface reflectance values. The model is applied to three instrumented winegrape vineyards over the 2017-2020 time period and the spatial and temporal variation in errors are analyzed. We illustrate how meteorological data inputs can introduce biases that vary in space and at seasonal timescales, but that can persist from year to year. We also observe that errors in SIMS estimates of land surface conductance can have a particularly strong dependence on time of year. Overall, meteorological inputs introduced RMSE of 0.33-0.65 mm/day (7-27%) across sites, while SIMS introduced RMSE of 0.55-0.83 mm/day (19-24%). The relative error contribution from meteorological inputs versus SIMS varied across sites; errors from SIMS were larger at one site, errors from meteorological inputs were larger at a second site, and the error contributions were of equal magnitude at the third site. The similar magnitude of error contributions is significant given that many satellite-driven ET models differ in their approaches to estimating land surface conductance, but often rely on similar or identical meteorological forcing data. The finding is particularly notable given that SIMS makes assumptions about the land surface (no soil evaporation or plant water stress) that do not always hold in practice. The results of this study show that improving SIMS by eliminating these assumptions would result in meteorological inputs dominating the error budget of the model on the whole. This finding underscores the need for further work on characterizing spatial uncertainty in the meteorological forcing of ET.Supplementary informationThe online version contains supplementary material available at 10.1007/s00271-022-00808-9.

Improved accuracy of evapotranspiration (ET) estimation, including its partitioning between transpiration (T) and surface evaporation (E), is key to monitor agricultural water use in vineyards, especially to enhance water use efficiency in semi-arid regions such as California, USA. Remote-sensing methods have shown great utility in retrieving ET from surface energy balance models based on thermal infrared data. Notably, the two-source energy balance (TSEB) has been widely and robustly applied in numerous landscapes, including vineyards. However, vineyards add an additional complexity where the landscape is essentially made up of two distinct zones: the grapevine and the interrow, which is often seasonally covered by an herbaceous cover crop. Therefore, it becomes more complex to disentangle the various contributions of the different vegetation elements to total ET, especially through TSEB, which assumes a single vegetation source over a soil layer. As such, a remote-sensing-based three-source energy balance (3SEB) model, which essentially adds a vegetation source to TSEB, was applied in an experimental vineyard located in California's Central Valley to investigate whether it improves the depiction of the grapevine-interrow system. The model was applied in four different blocks in 2019 and 2020, where each block had an eddy-covariance (EC) tower collecting continuous flux, radiometric, and meteorological measurements. 3SEB's latent and sensible heat flux retrievals were accurate with an overall RMSD ~ 50 W/m2 compared to EC measurements. 3SEB improved upon TSEB simulations, with the largest differences being concentrated in the spring season, when there is greater mixing between grapevine foliage and the cover crop. Additionally, 3SEB's modeled ET partitioning (T/ET) compared well against an EC T/ET retrieval method, being only slightly underestimated. Overall, these promising results indicate 3SEB can be of great utility to vineyard irrigation management, especially to improve T/ET estimations and to quantify the contribution of the cover crop to ET. Improved knowledge of T/ET can enhance grapevine water stress detection to support irrigation and water resource management.Supplementary informationThe online version contains supplementary material available at 10.1007/s00271-022-00787-x.

Irrigation and other agricultural management practices play a key role in land surface fluxes and their interactions with atmospheric processes. California's Central Valley agricultural productivity is strongly linked to water availability associated with conveyance infrastructure and groundwater, but greater scrutiny over agricultural water use requires better practices particularly during extended and severe drought conditions. The future of irrigated agriculture in California is expected to be characterized neither by perpetual scarcity nor by widespread abundance. Thus, further advancing irrigation technologies and improving management practices will be key for California's agriculture sustainability. In this study, we present micrometeorological observations from the Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project. Daily, seasonal, and inter-seasonal surface flux patterns and relationships across five vineyards over three distinct California wine production regions were investigated. Vineyard actual evapotranspiration showed significant differences at the sub-daily and daily scale when comparisons across wine production regions and varieties were performed. Water use in vineyards in the Central Valley was about 70% greater in comparison to the vineyards at the North Coast area due to canopy size, atmospheric demand, and irrigation inputs. Inter-annual variability of surface fluxes was also significant, even though, overall weather conditions (i.e., air temperature, vapor pressure deficit, wind speed, and solar radiation) were not significantly different. Thus, not only irrigation but also other management practices played a key role in seasonal water use, and given these differences, we conclude that further advancing ground-based techniques to quantify crop water use at an operational scale will be key to facing California's agriculture present and future water challenges.Supplementary informationThe online version contains supplementary material available at 10.1007/s00271-022-00784-0.

Robust information on consumptive water use (evapotranspiration, ET) derived from remote sensing can significantly benefit water decision-making in agriculture, informing irrigation schedules and water management plans over extended regions. To be of optimal utility for operational usage, these remote sensing ET data should be generated at the sub-field spatial resolution and daily-to-weekly timesteps commensurate with the scales of water management activities. However, current methods for field-scale ET retrieval based on thermal infrared (TIR) imaging, a valuable diagnostic of canopy stress and surface moisture status, are limited by the temporal revisit of available medium-resolution (100 m or finer) thermal satellite sensors. This study investigates the efficacy of a data fusion method for combining information from multiple medium-resolution sensors toward generating high spatiotemporal resolution ET products for water management. TIR data from Landsat and ECOSTRESS (both at ~ 100-m native resolution), and VIIRS (375-m native) are sharpened to a common 30-m grid using surface reflectance data from the Harmonized Landsat-Sentinel dataset. Periodic 30-m ET retrievals from these combined thermal data sources are fused with daily retrievals from unsharpened VIIRS to generate daily, 30-m ET image timeseries. The accuracy of this mapping method is tested over several irrigated cropping systems in the Central Valley of California in comparison with flux tower observations, including measurements over irrigated vineyards collected in the GRAPEX campaign. Results demonstrate the operational value added by the augmented TIR sensor suite compared to Landsat alone, in terms of capturing daily ET variability and reduced latency for real-time applications. The method also provides means for incorporating new sources of imaging from future planned thermal missions, further improving our ability to map rapid changes in crop water use at field scales.

Abstract Background Biological adaptation manifests itself at the interface of different biologically relevant ‘levels’, such as ecology, performance, and morphology. Integrated studies at this interface are scarce due to practical difficulties in study design. We present a multilevel analysis, in which we combine evidence from habitat utilization, leaping performance and limb bone morphology of four species of tamarins to elucidate correlations between these ‘levels’. Results We conducted studies of leaping behavior in the field and in a naturalistic park and found significant differences in support use and leaping performance. Leontocebus nigrifrons leaps primarily on vertical, inflexible supports, with vertical body postures, and covers greater leaping distances on average. In contrast, Saguinus midas and S. imperator use vertical and horizontal supports for leaping with a relatively similar frequency. S. mystax is similar to S. midas and S. imperator in the use of supports, but covers greater leaping distances on average, which are nevertheless shorter than those of L. nigrifrons. We assumed these differences to be reflected in the locomotor morphology, too, and compared various morphological features of the long bones of the limbs. According to our performance and habitat utilization data, we expected the long bone morphology of L. nigrifrons to reflect the largest potential for joint torque generation and stress resistance, because we assume longer leaps on vertical supports to exert larger forces on the bones. For S. mystax, based on our performance data, we expected the potential for torque generation to be intermediate between L. nigrifrons and the other two Saguinus species. Surprisingly, we found S. midas and S. imperator having relatively more robust morphological structures as well as relatively larger muscle in-levers, and thus appearing better adapted to the stresses involved in leaping than the other two. Conclusion This study demonstrates the complex ways in which behavioral and morphological ‘levels’ map onto each other, cautioning against oversimplification of ecological profiles when using large interspecific eco-morphological studies to make adaptive evolutionary inferences.

Abstract Accurate mitosis is coordinated by the spindle assembly checkpoint (SAC) through the mitotic checkpoint complex (MCC), which inhibits the anaphase-promoting complex or cyclosome (APC/C). As an essential regulator, Cdc20 promotes mitotic exit through activating APC/C and monitors kinetochore-microtubule attachment through activating SAC. Cdc20 requires multiple interactions with APC/C and MCC subunits to elicit these functions. Functionally assessing these interactions within cells requires efficient depletion of endogenous Cdc20, which is highly difficult to achieve by RNA interference (RNAi). Here we generated Cdc20 RNAi-sensitive cell lines which display a penetrant metaphase arrest by a single RNAi treatment. In this null background, we accurately measured the contribution of each known motif of Cdc20 on APC/C and SAC activation. The CRY box, a previously identified degron, was found critical for SAC by promoting MCC formation and its interaction with APC/C. These data reveal additional regulation within the SAC and establish a novel method to interrogate Cdc20.

Abstract Background Postoperative atrial fibrillation (POAF) is the most common arrhythmia following cardiac surgery (CS). It may occur between the 1st and the 4th postoperative day as acute POAF or between the 5th and the 30th as subacute (sPOAF). sPOAF is associated with higher thromboembolic risk, which consistently increase patients' morbidity. Neutrophil‐to‐lymphocyte ratio (NLR) is a low‐cost inflammatory index proposed as possible POAF predictor. Identification of patients' risk categories might lead to improved postoperative outcomes. Methods The aim was to assess the incidence of sPOAF and to identify possible predictors in patients performing cardiovascular rehabilitation (CR) after CS. A single‐center cohort study was performed on 737 post‐surgical patients admitted to CR on sinus rhythm. Continuous monitoring with 12‐lead ECG telemetry was performed. We evaluated the predictive role of anamnestic, clinical, and laboratory data, including baseline NLR. Results Subacute POAF was documented in 170 cases (23.1%). At the multivariate analysis, age (OR 1.03; p = .001), mitral valve surgery (OR 1.77; p = .012), acute POAF (OR 2.97; p

Central bank communication plays a crucial role in the conduct of monetary policy, yet the research on central bank communication, while growing, is still scarce. In this paper, we analyze the communication reaction function of the European Central Bank (ECB) through topic-based indices derived from the bank’s speeches. These indices are used as dependent variables in policy and communication reaction function models, as suggested by recent literature. The topics are extracted using Latent Dirichlet Allocation (LDA), a popular text mining algorithm for topic extraction. The ECB has recently reviewed its monetary policy strategy, which led to an increase in studies incorporating the new methods offered by text mining for analyzing the policy reaction function of the bank. We show how indices built through topic modelling can be used to study the communication reaction function of a central bank, and we examine which variables are significant for every topic communicated by the ECB.

The glomerular filtration barrier (GFB), composed of endothelial cells, glomerular basement membrane, and podocytes, is a unique structure for filtering blood while detaining plasma proteins according to size and charge selectivity. Structurally, the fenestrated endothelial cells, which align the capillary loops, are in close proximity to mesangial cells. Podocytes are connected by specialized intercellular junctions known as slit diaphragms and are separated from the endothelial compartment by the glomerular basement membrane. Podocyte-endothelial cell communication or crosstalk is required for the development and maintenance of an efficient filtration process in physiological conditions. In pathological situations, communication also has an essential role in promoting or delaying disease progression. Podocytes and endothelial cells can secrete signaling molecules, which act as crosstalk effectors and, through binding to their target receptors, can trigger bidirectional paracrine or autocrine signal transduction. Moreover, the emerging evidence of extracellular vesicles derived from various cell types engaging in cell communication has also been reported. In this review, we summarize the principal pathways involved in the development and maintenance of the GFB and the progression of kidney disease, particularly in kidney transplantation.

Every year Africa is hit by extreme floods which, combined with high levels of vulnerability and increasing population exposure, often result in humanitarian crises and population displacement. Impact-based forecasting and early warning for natural hazards is recognized as a step forward in disaster risk reduction, thanks to its focus on people, livelihoods, and assets at risk. Yet, the majority of the African population is not covered by any sort of early warning system. This article describes the setup and the methodological approach of Flood-PROOFS East Africa, an impact-based riverine flood forecasting and early warning system for the Greater Horn of Africa (GHA), with a forecast range of 5 d. The system is based on a modeling cascade relying on distributed hydrological simulations forced by ensemble weather forecasts, link to inundation maps for specific return period, and application of a risk assessment framework to estimate population and assets exposed to upcoming floods. The system is operational and supports the African Union Commission and the Disaster Operation Center of the Intergovernmental Authority on Development (IGAD) in the daily monitoring and early warning from hydro-meteorological disasters in eastern Africa. Results show a first evaluation of the hydrological reanalysis at 78 river gauging stations and a semi-quantitative assessment of the impact forecasts for the catastrophic floods in Sudan and in the Nile River basin in summer 2020. More extensive quantitative evaluation of the system performance is envisaged to provide its users with information on the model reliability in forecasting extreme events and their impacts.

Abstract Introduction To date, there are no known studies that have investigated the new need for volunteer services among cancer patients during the Covid-19 pandemic. However, it is essential for volunteer associations to heighten such knowledge to best guide their offer in this challenging period. Aim The present study aims to provide a mapping of the cancer patients’ needs for volunteer services followed at Istituto Nazionale dei Tumori in Milan (Italy) during the Covid-19 pandemic. Since there are no specific questionnaires for this purpose, we created an ad hoc tool for which we report the preliminary result. Method We used a mixed-method multiphase approach. Phase I: in April-May 2020 40 ad hoc paper questionnaires were distributed at the entrance of the aforementioned hospital, with the aim of investigating patients’ needs through two open-ended questions then analyzed through thematic analysis. Phase II: the contents that emerged from Phase I were transformed into items and submitted to the judgment of a small group of “peers” (patients) and “experts” (professionals) in November-December 2020 to evaluate their comprehensiveness, representativeness and intrusiveness. Phase III: in January-February 2021 paper questionnaires, containing the items reviewed in Phase II, were distributed within the hospital to a representative sample of cancer patients. We applied descriptive statistics, Exploratory Factor Analysis (EFA) and Cronbach’s Alpha. Results 32 patients completed Phase I, 3 “peers” and 9 “experts” participated in Phase II, 214 patients completed the questionnaire in Phase III. EFA highlights five kinds of needs during the Covid-19 pandemic, in order of priority: (1) need to be supported at the hospital; (2) need for emotional support; (3) need for daily errands; (4) need for practical support to family members; (5) need to share free time. Preliminary results on the tool are encouraging, although further studies are needed. These results will allow local volunteer associations to adapt their services during the pandemic.

The use of Additive Manufacturing (AM) technology has largely increased in the last years. Because of its large differences from conventional technologies, the use of AM in production systems might call for new strategies in production planning and control. To this aim, this paper proposes analytical models to predict aggregate performance measures such as flow time, work in process, and production throughput, for production systems characterised by Laser Powder Bed Fusion AM technology. These indicators could be used both in operations strategy development and in technology comparison. The proposed models differentiate for their detail of the analysis and the number of input parameters that need to be estimated. The results show that the level of detail of the model affects the analysis leading to quite different values of the performance measures, especially in the case of highly saturated systems. Also, a discussion about the applicability of the proposed model to other AM technologies show whether and to what extent the proposed models can be applied for modelling other AM technologies. [ABSTRACT FROM AUTHOR]

The manufacture of bipolar junctions is necessary in many 4H-SiC electronic devices, e.g., junction termination extensions and p + in diodes for voltage class > --> 10 kV. However, the presence of electrically active levels in the drift layer that act as minority charge carrier lifetime killers, like the carbon vacancy (V C), undermines device performance. In the present study, we compared p + n diodes whose anodes have been manufactured by three different methods: by epitaxial growth, ion implantation, or plasma immersion ion implantation (PIII). The identification of the electrically active defects in the drift layers of these devices revealed that a substantial concentration of V C is present in the diodes with epitaxial grown or ion implanted anode. On the other hand, no presence of V C could be detected when the anode is formed by PIII and this is attributed to the effects of strain in the anode region. Our investigation shows that PIII can be a useful technique for the manufacture of bipolar devices with a reduced concentration of lifetime killer defects. [ABSTRACT FROM AUTHOR]

This paper investigates how investments in automation affect the gender pay gap. The evidence of the effects of automation on the labor market is growing; however, little is known about the implications of automation for the gender pay gap. The data used in this paper are from a matched employer–employee dataset incorporating detailed information on firms, their imports, and employee–level data for Estonian manufacturing and service employers for the period of 2006–2018. Through the use of the imports of automation goods as a proxy for the introduction of automation at the firm level, this paper estimates the effect of automation using simple Mincerian wage equations. The causality of the effect is further validated using propensity score matching (PSM). We find that introducing automation enlarges the gender pay gap, and PSM confirms that this also has a higher causal effect on the wages of male employees than female employees. The results imply that a higher representation of women in higher-paid positions does not guarantee a reduction in the gender pay gap in the presence of automation, and appropriate measures in education and retraining are needed to tackle the effect of automation on gender inequality. [ABSTRACT FROM AUTHOR]