The diagnosis of iron disturbances usually includes the evaluation of serum parameters. Serum iron is assumed to be entirely bound to transferrin, and transferrin saturation-the ratio between the ...serum iron concentration and serum transferrin-usually reflects iron availability. Additionally, serum ferritin is commonly used as a surrogate of tissue iron levels. Low serum ferritin values are interpreted as a sign of iron deficiency, and high values are the main indicator of pathological iron overload. However, in situations of inflammation, serum ferritin levels may be very high, independently of tissue iron levels. This presents a particularly puzzling challenge for the clinician evaluating the overall iron status of the patient in the presence of an inflammatory condition. The increase in serum ferritin during inflammation is one of the enigmas regarding iron metabolism. Neither the origin, the mechanism of release, nor the effects of serum ferritin are known. The use of serum ferritin as a biomarker of disease has been rising, and it has become increasingly diverse, but whether or not it contributes to controlling the disease or host pathology, and how it would do it, are important, open questions. These will be discussed here, where we spotlight circulating ferritin and revise the recent clinical and preclinical data regarding its role in health and disease.
Adult-onset growth-hormone (GH) deficiency (GHD) is a rare disorder, which most commonly results from pituitary or peripituitary tumors and their treatment, and is characterized by alterations in ...body composition, carbohydrate and lipid metabolism, bone mineral density, cardiovascular risk profile and quality of life, all of which may contribute to an increased morbidity and mortality. Since recombinant human GH (rhGH) became available in 1985, several studies have provided evidence of its beneficial effects, despite the potential risk of developing adverse effects, and much clinical experience has been accumulated. However, in adults, the precise therapeutic role of GH replacement therapy and the individual response to it remains highly variable and is still a matter of debate. In this article, we present a critical review of the available evidence on rhGH replacement therapy in GHD adults, emphasizing the pitfalls clinicians encounter in the diagnosis of GHD and monitoring of rhGH replacement therapy. We will cover all the relevant aspects regarding the potential usefulness of GH treatment, including the hot topic of mortality.
Background: The outbreak of severe acute respiratory syndrome β-coronavirus 2 (SARS-CoV-2) has the potential to become a long-lasting global health crisis. The number of people infected with the ...novel coronavirus has surpassed 22 million globally, resulting in over 700,000 deaths with more than 15 million people having recovered (https://covid19.who.int). Enormous efforts are underway for rapid vaccine and treatment developments. Amongst the many ways of tackling the novel coronavirus disease 2019 (COVID-19) pandemic, extracellular vesicles (EVs) are emerging. Summary: EVs are lipid bilayer-enclosed structures secreted from all types of cells, including those lining the respiratory tract. They have established roles in lung immunity and are involved in the pathogenesis of various lung diseases, including viral infection. In this review, we point out the roles and possible contribution of EVs in viral infections, as well as ongoing EV-based approaches for the treatment of COVID-19, including clinical trials. Key Messages: EVs share structural similarities to viruses and recent findings demonstrate that viruses exploit EVs for cellular exit and EVs exploit viral entry mechanisms for cargo delivery. Moreover, EV-virus interplay could be exploited for future antiviral drug and vaccine development. EV-based therapies, especially the mesenchymal stem cell-derived EVs, are being intensively studied for the treatment of COVID-19.
Sex and gender are important variables in health, although their incorporation in medicine has been very slow. If research is sensitive and yields fruitful sex and gender evidence, these results ...should be included in the guidelines for clinical practices. However, literature claims that clinical practice guidelines devote very little space to these categories. The present systematic review addresses the relevance of sex and gender dimensions through methodology documents for the development of clinical practice guidelines based on three sources: the AGREE Reporting Checklist, the GRADE Handbook, and the Spanish GuíaSalud NHS Clinical Guideline Program. Findings suggest that neglecting sex and gender issues in the biomedical approach may lead to continuing to ignore relevant evidence on biological and social dimensions that do indeed influence people's health and diseases.
The traditional method of measuring nitrogen content in plants is a time-consuming and labor-intensive task. Spectral vegetation indices extracted from unmanned aerial vehicle (UAV) images and ...machine learning algorithms have been proved effective in assisting nutritional analysis in plants. Still, this analysis has not considered the combination of spectral indices and machine learning algorithms to predict nitrogen in tree-canopy structures. This paper proposes a new framework to infer the nitrogen content in citrus-tree at a canopy-level using spectral vegetation indices processed with the random forest algorithm. A total of 33 spectral indices were estimated from multispectral images acquired with a UAV-based sensor. Leaf samples were gathered from different planting-fields and the leaf nitrogen content (LNC) was measured in the laboratory, and later converted into the canopy nitrogen content (CNC). To evaluate the robustness of the proposed framework, we compared it with other machine learning algorithms. We used 33,600 citrus trees to evaluate the performance of the machine learning models. The random forest algorithm had higher performance in predicting CNC than all models tested, reaching an R2 of 0.90, MAE of 0.341 g·kg−1 and MSE of 0.307 g·kg−1. We demonstrated that our approach is able to reduce the need for chemical analysis of the leaf tissue and optimizes citrus orchard CNC monitoring.
Hydrogen produced sustainably has the potential to be an important energy source in the short term. Biomass gasification is one of the fastest-growing technologies to produce green hydrogen. In this ...work, an air-blown gasification model was developed in Aspen Plus®, integrating a water–gas shift (WGS) reactor to study green hydrogen production. A sensitivity analysis was performed based on two approaches with the objective of optimizing the WGS reaction. The gasifier is optimized for carbon monoxide production (Case A) or hydrogen production (Case B). A CO2 recycling stream is approached as another intensification process. Results suggested that the Case B approach is more favorable for green hydrogen production, allowing for a 52.5% molar fraction. The introduction of CO2 as an additional gasifying agent showed a negative effect on the H2 molar fraction. A general conclusion can be drawn that the combination of a WGS reactor with an air-blown biomass gasification process allows for attaining 52.5% hydrogen content in syngas with lower steam flow rates than a pure steam gasification process. These results are relevant for the hydrogen economy because they represent reference data for further studies towards the implementation of biomass gasification projects for green hydrogen production.
Under ideal conditions of nitrogen (N), maize (Zea mays L.) can grow to its full potential, reaching maximum plant height (PH). As a rapid and nondestructive approach, the analysis of unmanned aerial ...vehicles (UAV)-based imagery may be of assistance to estimate N and height. The main objective of this study is to present an approach to predict leaf nitrogen concentration (LNC, g kg−1) and PH (m) with machine learning techniques and UAV-based multispectral imagery in maize plants. An experiment with 11 maize cultivars under two rates of N fertilization was carried during the 2017/2018 and 2018/2019 crop seasons. The spectral vegetation indices (VI) normalized difference vegetation index (NDVI), normalized difference red-edge index (NDRE), green normalized difference vegetation (GNDVI), and the soil adjusted vegetation index (SAVI) were extracted from the images and, in a computational system, used alongside the spectral bands as input parameters for different machine learning models. A randomized 10-fold cross-validation strategy, with a total of 100 replicates, was used to evaluate the performance of 9 supervised machine learning (ML) models using the Pearson’s correlation coefficient (r), mean absolute error (MAE), coefficient of regression (R²), and root mean square error (RMSE) metrics. The results indicated that the random forest (RF) algorithm performed better, with r and RMSE, respectively, of 0.91 and 1.9 g.kg−¹ for LNC, and 0.86 and 0.17 m for PH. It was also demonstrated that VIs contributed more to the algorithm’s performances than individual spectral bands. This study concludes that the RF model is appropriate to predict both agronomic variables in maize and may help farmers to monitor their plants based upon their LNC and PH diagnosis and use this knowledge to improve their production rates in the subsequent seasons.
More than 150 million tons of synthetic plastics are produced worldwide from petrochemical-based materials, many of these plastics being used to produce single-use consumer products like food ...packaging. The main goal of this work was to research the production and characterization of pullulan-apple fiber biocomposite films as a new food packaging material. The optical, mechanical, and barrier properties of the developed biocomposite films were evaluated. Furthermore, the antioxidant and antibacterial activities of the biocomposite films were additionally studied. The results show that the Tensile Index and Elastic Modulus of the pullulan-apple fiber films were significantly higher (
-value < 0.05) when compared to the pullulan films. Regarding the water vapor permeability, no significant differences (
-value < 0.05) were observed in water vapor transmission rate (WVTR) when the apple fiber was incorporated into the biocomposite films. A significant increase (
-value < 0.05) of water contact angle in both sides of the films was observed when the apple fiber was incorporated into pullulan, indicating an increase in the hydrophobicity of the developed biocomposite films. It is worth noting the hydrophobicity of the (rough) upper side of the pullulan-apple fiber films, which present a water contact angle of 109.75°. It was possible to verify the microbial growth inhibition around the pullulan-apple fiber films for all the tested bacteria.
This study explores potential non-linear and asymmetric interdependencies between oil price shocks and leading cryptocurrency returns. In addition, this research splits changes in crude oil prices ...into three relevant components: risk, demand, and supply shocks. By applying the NARDL methodology, this paper examines the connection between oil and cryptocurrencies in the period between November 20, 2018 and June 30, 2020, conducting a study of the first wave of the COVID-19 pandemic. Our results confirm that demand shocks show the greatest connection with the returns of the cryptocurrencies analysed. In addition, both short-term and long-term results show a greater interdependence between oil and cryptocurrencies in periods of economic turbulence, such as the SARS-CoV-2 coronavirus crisis.
•Non-linear and asymmetric interdependencies between oil and cryptocurrencies are analysed.•Shocks in crude oil prices are split into risk, demand, and supply shocks (Ready (2018) methodology).•A study of the COVID-19 pandemic is conducted.•A greater connection between oil and cryptocurrencies is observed in periods of economic turbulence (the coronavirus crisis).•Tether could act as a safe-have and be used for diversification strategies.
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