Global climate change primarily affects the spatiotemporal variation of physical quantities such as relative humidity, atmospheric pressure, ambient temperature, and notably, precipitation levels. Accurate precipitation predictions remain elusive, necessitating tools for detailed spatiotemporal analysis to better understand climate impacts on the environment, agriculture, and society. This study compares three learning models: ARIMA (Autoregressive Integrated Moving Average), RF-R (Random Forest Regression), and LSTM-NN (Long Short-Term Memory Neural Network), utilizing monthly precipitation data (in millimeters) from 757 locations in Boyacá, Colombia. The LSTM-NN model outperformed others, precisely replicating precipitation observations in both training and testing datasets, significantly reducing the root mean square error (RMSE) with average monthly deviations of approximately 19 mm per location. Evaluation metrics (RMSE, MAE, R², MSE) underscore the LSTM model’s robustness and accuracy in capturing precipitation patterns. Consequently, the LSTM model was chosen to predict precipitation over a 16-month period starting from August 2023, offering a reliable tool for future meteorological forecasting and planning in the region.

Today, computer programming is an essential pillar in the education of individuals. Even though technological evolution has eased the massive need for computer programming, a systematic lit-erature review shows some problems remain with teaching computer programing. To address such issues, in this paper we propose an adapted theory, a method, and a model for teaching some knowledge objects associated with the concepts of variables, expressions, comparisons, loops, and functions in programming fundamentals in computer sciences. The main contribution of this study comprises the extension of the concept of didactic transposition to improve teaching in context; in this paper, the idea is called didactic transposition in extensa sensu. The proposal involves the development of a linguistic corpus based on syllabi, textbooks, reference manuals, and a survey applied to experts in teaching programming fundamentals based on seventy-eight universities worldwide. An adapted theory, a method, and a model for teaching programming fundamentals using computational linguistics are produced. In addition, a template is created for designing teaching practices in this regard. The proposal generates an important alternative for the devel-opment of teaching strategies where the conditions of the context are addressed as a priority; ad-ditionally, several aspects are considered for elaborating teaching strategies using computational linguistic techniques from written documents.

This review focuses on the role of small extracellular vesicles in the pathophysiological mechanisms of retinal degenerative diseases. Many of these mechanisms are related or modulated by the oxidative burden of the retinal cells. It has been recently demonstrated that cellular communication in the retina involves extracellular vesicles and that their rate of release and cargo features might be affected by the cellular environment and in some instances also mediated by autophagy. The fate of these vesicles is diverse, and could end up in the circulation and be used as markers, or target neighbour cells modulating gene and protein expression and eventually also angiogenesis. Neovascularization in the retina promotes vision loss in diseases such as diabetic retinopathy and age-related macular degeneration. The importance of micro RNAs, either as small extracellular vesicles’ cargo or free circulating, on the regulation of retinal angiogenesis is also discussed.

Background: Strong nursing faculty is paramount to promote disciplinary leadership and to prepare future nurses for practice. Our understanding of the factors associated with or predictive of nurse faculty retention and/or turnover is lacking. Purpose: The aim of this review is to identify and synthesize the existing literature on factors contributing to nurse faculty shortage in Canada and implications on nursing practice. Methods: A scoping review based on the Arskey and O’Malley’s five stage framework for scoping reviews was undertaken. Utilising the PRISMA protocol, a comprehensive and structured literature search was conducted in five databases of studies published in English.Findings: Limited through search inclusion and relevance of research, nine studies out of 220 papers met the criteria for this review and were thematically analyzed. Identified themes were: supply versus demand; employment conditions; organizational support; and personal factors.Discussion: Impending retirement of faculty, unsupportive leadership, and stressful work environments were frequently reported as significant contributing factors to the faculty shortage.Conclusions: This scoping review provide insights into how Canada’s schools of nursing could engage in grounded efforts to lessen nursing faculty shortage, both nationally and globally. We identified a gap in the literature that indicates that foundational work is needed to create context-specific solutions. The limited studies published in Canada suggests that this is a critical area for future research and funding.

Our bodies produce a host of electrophilic species that can label specific endogenous proteins in cells. The signaling roles of these molecules are underactive debate. However, in our opinion it is becoming increasingly likely that electrophiles can rewire cellular signaling processes at endogenous levels. Attention is turning more to understanding how nuanced electrophile signaling in cells is. In this perspective, we describe recent work from our laboratory that has started to inform on different levels of context-specific regulation of proteins by electrophiles. We discuss the relevance of these data to the field, and to the broader application of electrophile signaling to precision medicine development, beyond the traditional views of their pleiotropic cytotoxic roles.

The main contribution of this paper is to develop a graphical tool to evaluate the suitability of a candidate parametric model to fit a data set. The practical motivation is to check the adequacy of the so called SAINT model proposed in Jarner and Kryger (2011). This model has been implemented in practice by an important European pension fund concerned with setting annuity reserves for all current or former employees of Denmark. So, one particular relevant question is whether this mortality model is actually fitting old-age. Our graphical test can be described as follows. First we transform the data by means of the parametric model which is being evaluated. Should the model be correct, the transformed data will be in accordance with an Exponential distribution with rate 1. Then we construct a family of local linear hazard estimates based on the data on the transformed scale. Finally we use the statistical tool SiZer to assess the goodness-of-fit of the Exponential distribution to the data on the transformed scale. If the model is correct the SiZer map should not reveal any significant feature in the family of kernel estimates. Our method allow us to establish a diagnostic regarding the validity of the SAINT model when describing mortality patterns in four different countries.

Hydrokinetic energy constitutes a significant promise as a renewable energy source, yet many regions experience flow velocities insufficient to support conventional turbine installations. According to this, the present work proposes a vertical axis hydrokinetic turbine aimed to environments where conven-tional turbines may not be feasible due to insufficient water velocity. This turbine is based on a biologi-cally inspired design which improves the traditional Savonius turbine. This innovative configuration is inspired by the Fibonacci spiral. The turbine's performance was analyzed through Computational Fluid Dynamics. A notable improvement was found in comparison with the traditional Savonius turbine, providing a 15.1% increment in the power coefficient.

Groundwater flow and transport models are essential tools for assessing and quantifying the mi-gration of organic contaminants at polluted sites. Uncertainties in the hydrodynamic and transport parameters of the aquifer have a significant effect on model predictions. Uncertainties can be quantified with advanced sensitivity methods such as Sobol’s High Dimensional Model Reduction (HDMR) and Variogram Analysis of Response Surfaces (VARS). Here we present the application of VARS and HDMR to assess the global sensitivities of the outputs of a transient groundwater flow model of the Gállego alluvial aquifer which is located downstream the Sardas landfill in Huesca (Spain). The aquifer is subject to the tidal effects caused by the daily oscillations of the water level in the Sabiñánigo reservoir. Global sensitivities are analysed for hydraulic heads, aquifer/reservoir fluxes, groundwater Darcy velocity and hydraulic head calibration metrics. Input parameters in-clude aquifer hydraulic conductivities and specific storage, aquitard vertical hydraulic conductiv-ities, and boundary inflows and conductances. VARS, HDMR and graphical methods agree to identify the most influential parameters which for most of the outputs are the hydraulic conduc-tivities of the zones closest to the landfill, the vertical hydraulic conductivity of the most permeable zones of the aquitard, and the boundary inflow coming from the landfill. The sensitivity of heads and aquifer/reservoir fluxes with respect to specific storage change with time. The aquifer/reservoir flux when the reservoir level is high shows interactions between specific storage and aquitard conductivity. VARS and HDMR parameter rankings are similar for the most influential parameters. However, there are discrepancies for the less relevant parameters. The efficiency of VARS was demonstrated by achieving stable results with a relatively small number of simulations.

Abstract: Comparing outcrop data to laboratory results is important to verify and validate experiments of analogue and reservoir materials especially regarding conditions for deformation experiments. This is important better understand highly complex carbonate reservoir strata and their response to changes in subsurface conditions, reducing subsurface uncertainty. This study develops methods to allow for a more straightforward comparison of outcrop data (m-scale) with experimentally created fracture arrays developed in cylindrical samples (cm-scale). The main objective is to assess usefulness of experimentally-produced fracture networks as analogues for subsurface structures, typically at the meter and above scale by developing new techniques to use the lab deformation. It analyses key characteristics of laboratory-induced fracture networks by adapting scanline methods to use with x-ray tomography (XRT) images to allow for comparison with outcrop and field data. To test and verify these new methods two low permeability carbonate samples were used for deformation testing and analysis. Applying the different scanline methods we show that they can be used to analyse lab induced fractures (mm to cm-scale) identified in XRT images for comparison with outcrop data (m-scale). In addition, these methods also allow for quantification of fracture network attributes e.g. fracture spacing, fracture apertures, orientation. This new data bridges the gap between micro-scanlines using thin sections and outcrop scanlines.

Water quality assessment stands as a fundamental step in water resource management. In addition to substances and organisms present in the water, land use and land cover are two factors affecting also water quality. This study analyzed the correlation and influence between water quality and land use and land cover in the Miranda River Basin (MRB) and the natural wetlands in the Pantanal Biome. Using a watershed-wide approach, results suggested that water quality management policies can be considered in terms of sub-basins (smaller planning units). The Water Quality Index (WQI) was considered GOOD or EXCELLENT throughout the MRB. It was observed that the natural wetlands have the capacity to contribute to improve WQI, with reductions in thermotolerant coliforms and turbidity; however, high values were found for thermotolerant coliforms, a temporal increasing trend of biochemical oxygen demand (BOD), and a reduction in dissolved oxygen and total phosphorus. Conversely, it was found in these flooded areas a trend of decrease in dissolved oxygen and an increase in BOD concentrations. Natural wetlands play important hydrological and ecological roles in water quality, storing, removing, and cycling nutrients. They are highly relevant areas for defining watershed management and conservation strategies, environmental protection, and providing ecosystem services.

This work presents the design, construction and performance evaluation of a photovoltaic greenhouse as an energy hub (EH) in modern agriculture that integrates battery energy storage (BES) and an electric vehicle charging station (EV). The greenhouse is composed of 48 semi-transparent PV panels with nominal transparency of 20% and 110 W capacity. The control of the PV greenhouse as EH was approached as an optimization problem with the aim of minimizing the cost of the energy used from the grid. Simulation results indicate that the integrated BES is capable of balancing power transactions within the microgrid. In addition, it was found that the case of slow charging of the EV at night was less demanding on the BES than fast charging during the day in terms of abrupt power transitions and average depletion of BES SOC (61% vs 53%). Empirical results also demonstrated the negative impact of dust generated by agricultural activity on the performance of solar panels. For a period analyzed of three years, an average yearly production loss of 6.8% was calculated.

LSUs (RESPONSE TO LOW SULFUR) are plant-specific proteins of unknown function that were initially identified during transcriptomic studies of the sulfur deficiency response in Arabidopsis. Recent functional studies have shown that LSUs are important hubs of protein interaction networks with potential roles in plant stress responses. In particular, LSU proteins have been reported to interact with members of the brassinosteroid, jasmonate signaling, and ethylene biosynthetic pathways, suggesting that LSUs may be involved in response to plant stress through modulation of phytohormones. Furthermore, in silico analysis of the promoter regions of LSU genes in Arabidopsis has revealed the presence of cis-regulatory elements that are potentially responsive to phytohormones such as ABA, auxin, and jasmonic acid, suggesting crosstalk between LSU proteins and phytohormones. In this review, we summarize current knowledge about the LSU gene family in plants and its potential role in phytohormone responses.

In this paper, we identify issues and possible solutions in the key area of large-scale antenna systems, also know as Massive Multiple Input Multiple Output (MIMO) systems. Additionally, we propose the use of Massive MIMO technology as a means to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), the capacity of the MTC network and, in turn, that of the whole system, can be increased by grouping Machine-Type Communication (MTC) devices into clusters and letting each cluster share the same time-frequency physical resource blocks. We study the feasibility of applying sub-optimal linear detection to the problem of detecting a large number of MTC devices sharing the same time-frequency resources at the uplink of a base station (BS) equipped with a large number of antennas, M. In our study, we derive the achievable lower-bound rates for the studied sub-optimal linear detectors and show that the transmitted power of each MTC device can be reduced as M increases, which is a very important result for powerconstrained MTC devices running on batteries. Our simulation results suggest that, as M is made progressively larger, the performance of sub-optimal linear detection methods approach the matched filter bound, also known as perfect interference-cancellation bound.

Diverse factors may have an impact in Carbon dioxide (CO₂) emissions; thus, three main contributors, energy consumption, exergy indicator and gross domestic product (GDP) are examined in this work. This study explores the relationship between economic growth and energy consumption by means of the hypothesis postulated for the Environmental Kuznets Curve (EKC). Panel data for 10 countries, from 1971 to 2014 have been studied. Despite all this wide gamma of research, the role of an exergy variable has not been tested to find the EKC; then exergy analysis is proposed. Exergy analyses were developed to propose an exergetic indicator as a control variable and a comparative empirical study is developed to study a multivariable framework with the aim to detect correlations between them. High correlation between CO₂, GDP, energy consumption, energy intensity and trade openness are observed, conversely not statistically significant values for trade openness and energy intensity. The results do not support the EKC hypothesis, however exergy intensity opens the door for future research once it proves to be a useful control variable. Exergy provides opportunities to analyze and implement energy and environmental policies in these countries, with the possibility to link exergy efficiencies and the use of renewables.

The local electrical response in alkaline-doped CuInSe₂ films prepared by single step electrodeposition onto Cu substrates was studied by current sensing atomic force microscopy. The CIS films were prepared from single baths containing the dopant ions (Li, Na, K or Cs) and were studied by X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy and photocurrent response. Increased crystallinity and surface texturing as the ion size increases was observed as well as enhanced photocurrent response in Cs doped CIS. Li and Na doped films have larger conductivity than the undoped film while the K and Cs doped samples display shorter currents and the current images indicate strong charge accumulation in the K and Cs doped films forming surface capacitors. Corrected CAFM IV curves were adjusted with Shockley equation.

The expression of the Fasciola hepatica Carboxylesterase type B (CestB) gene is induced in response to the anthelmintic triclabendazole (TCBZ), resulting in a significant increase in enzymatic specific activity. Furthermore, the amino acid sequence of CestB exhibits variations that could lead to substantial amino acid substitutions at the ligand-binding site. These substitutions have the potential to affect the interaction between the ligand and the protein, as well as the catalytic properties of the enzyme. The objective of this study was to identify new CestB polymorphisms in TCBZ-resistant parasites using 3D modeling against the metabolically oxidized form of the anthelmintic TCBZSOX. Our aim was to observe the formation of TCBZSOX-specific binding pockets that could potentially explain the resistance to anthelmintic agents. We identified a CestB polymorphism in a TCBZ-resistant strain of parasites exhibiting three radical amino acid substitutions at positions 147, 215, and 243, resulting in the formation of a TCBZSOX-affinity pocket capable of binding the anthelmintic drug. Additionally, our 3D modeling analysis revealed that these amino acid substitutions also had an impact on the configuration of the CestB catalytic site, affecting the enzyme's interaction with chromogenic carboxylic ester substrates and altering its catalytic properties; however, the identified TCBZSOX-binding pocket was located far from the enzyme's catalytic site, making the enzymatic hydrolysis of TCBZSOX theoretically impossible. Nonetheless, the increased affinity for the anthelmintic may explain a drug-sequestration type of anthelmintic resistance and lays the foundation for the development of a molecular diagnostic tool for identifying anthelmintic resistance in F. hepatica.

One of the most important challenges in the Machine and Deep Learning areas today is to build good models using small datasets, because sometimes it is not possible to have large ones. Several techniques have been proposed in the literature to address this challenge. This paper aims at studying the different available Deep Learning techniques and performing a thorough experimentation to analyze which technique or combination thereof improves the performance and effectiveness of the models. A complete comparison with classical Machine Learning techniques was carried out, to contrast the results obtained using both techniques when working with small datasets. Thirteen algorithms were implemented and trained using three different small datasets (MNIST, Fashion MNIST, and CIFAR-10). Each experiment was evaluated using a well-established set of metrics (Accuracy, Precision, Recall, F1, and the Matthews correlation coefficient). The experimentation allowed concluding that it is possible to find a technique or combination of them to mitigate a lack of data, but this depends on the nature of the dataset, the amount of data, and the metrics used to evaluate them.

In an era marked by digitization and automation, extracting relevant information from business documents, like electricity invoices, remains a major challenge. To address this, we need to use machine-learning techniques to automate the process, reduce manual labor, and minimize errors. This work introduces a new method for extracting key values from this type of invoice, including customer personal data, bill breakdown, electricity consumption, or marketer data. We evaluate several machine learning techniques, such as Naive Bayes, Logistic Regression, Random Forests, or Support Vector Machines. Our approach uses a bag-of-words strategy and custom-designed features specifically tailored for electricity data. We tested the method on the IDSEM dataset, which includes 75.000 electricity invoices with eighty-six different fields. The method converts PDF invoices into text and processes each word separately using a context of eleven words. The results of our experiments indicate that Support Vector Machines and Random Forests perform exceptionally well in capturing numerous values with high precision. The study also explores the advantages of our custom features and evaluates the performance of the model on unseen documents. The precision obtained with Support Vector Machines is 91,86%, peaking at 98,47% for one document template. These results demonstrate the effectiveness of our method in accurately extracting key values from invoices.

Background: The incidence of prostate cancer (PC) has been risen annually. Despite the diagnosis is made mainly with non-metastatic PC, mortality is explained by the metastatic disease (mPC). Without a doubt there is an intermediate scenario in which patients have no mPC but will have initiated a metastatic cascade through an epithelial-mesenchymal transition. There is indeed a need for more and better tools to predict what patients will progress in the future to non-localized clinical disease or already have micrometastatic disease, and therefore, will clinically progress after primary treatment. Biomarkers for predicting mPC are still under development; there are few studies and not much evidence of their usefulness. Summary: This review is focused on tissue-based genomic biomarkers (TBGB) for predicting metastatic disease. We developed four main research questions that will attempt to answer according to the current evidence. Why is important to predict metastatic disease? Which tests are available to predict metastatic disease? What impact should there be on clinical guidelines and clinical practice in predicting metastatic disease? What are current prostate cancer treatments? Key Messages: Knowing useful predict tools could help determine which patients may need multimodal or adjuvant treatment even with a localized disease, and in consequence, what patients do not need more than a single modality of treatment. The importance of predicting metastasis is fundamental, given that once metastasis is diagnosed, the quality of life (QoL) and survival drop dramatically.

Non-alcoholic fatty liver (NAFLD) is a metabolic disorder related with a chronic lipid accumulation within the hepatocytes. This disease is the most common liver disorder worldwide and it is estimated that is present in up to 25% of the world's population. However, the real prevalence of this disease and the associated disorders is unknown mainly because reliable and applicable diagnostic tools are lacking. It is known that the level of albumin, a pleiotropic protein synthetized by hepatocytes, is correlated with the correct function of the liver. The development of a complementary tool that allow the direct, sensitive, and label-free monitoring of albumin secretion in hepatocyte cell culture can provide insight about the mechanism and drugs action in NAFLD. With this aim, we have developed a simple integrated plasmonic biosensor based on gold nanogratings from periodic nanostructures present in commercial Blu-ray optical disc. This sensor allows the direct and label-free monitoring of albumin in a 2D fatty liver disease model under flow conditions using highly specific polyclonal antibody. This technology avoids both the amplification and blocking steps showing a limit of detection within pM range (≈ 0.39 ng/mL). Thanks to this technology, we identified the optimal fetal bovine serum (FBS) concentration to maximize the lipid accumulation within the cells. Moreover, we discovered that at third day from lipids challenge, the hepatocytes increased the amount of albumin secreted. These data demonstrate the ability of hepatocytes to respond to the lipid stimulation releasing more albumin. Further investigation needed to unveil the biological significance of that cell behaviour.

N-palmitoylethanolamine (PEA) is an endocannabinoid-like compound first encountered within lipid fractions of specific foods and has intrigued researchers since the 1950s due to its therapeutic effects. This study aims to explore the therapeutic promise held by PEA as an anti-inflammatory and immunomodulatory agent. Therapeutic impact of PEA reverberates across diverse physiological systems, as the central nervous system, gastrointestinal tract, vascular network, digestive and respiratory system. Additionally, it was effective in pain management, reduction of inflammation and immune responses. These attributes have fostered collaborations targeting conditions such as Alzheimer's disease, multiple sclerosis, cerebral ischemia, neuroinflammation, general inflammation, pain, coagulopathy, steatohepatitis, and acute lung injury. PEA operates both independently and in synergy with other compounds, like paracetamol, luteolin, and oxymetazoline. This efficacy stems from its interactions with pivotal targets including PPARα, PPAR-δ, PPAR-γ, CB1, CB2, GPR55, and TRPV1. Additionally, PEA exerts a direct influence on the inflammatory cascade, orchestrating precise adjustments in immune responses. Numerous animal studies have elucidated the inherent potential of PEA. Nevertheless, the imperative of reinforcing clinical investigation is evident. This review notably underscores the pivotal necessity for methodologically rigorous clinical trials to definitively establish the translational efficacy of PEA in ameliorating diverse inflammatory pathologies within the human milieu.

Inorganic pollutants in Colombian cocoa (Theobroma cacao L.) agrosystems cause problems in the production, quality, and exportation of this raw material. There has been an increased interest in bioprospecting studies of different fungal species focused on the biosorption of heavy metals. Furthermore, fungi constitute a valuable, profitable, ecological, and efficient natural soil resource that could be considered in the integrated management of cadmium mitigation. In this study, we report a new species of Talaromyces, isolated from cocoa soil from San Vicente de Chucurí-Colombia. The characterization of the culture was performed on six different standardized media and was distinguished by characteristic colony morphology: biverticillate and monoverticillate penicilli, acerose phialides, and slightly globose smooth-walled conidia. Culture was featured by bright yellow mycelium in young culture on CYA and CYAS medium. Colonies grew faster on Malt and Oat agar, attaining 36 and 32 mm diameter after seven days at 20 ºC. High acid production on CREA medium at 20-30 ºC was observed. Phylogenetic analysis was based on the ITS region and the RPB2, Calmodulin (CaM) and β-Tubulin genes that indicate that it is new to science and is named Talaromyces santanderensis sp. nov. This new species belongs to the Talaromyces section and is closely related to T. lentulus and related to T. soli, T. tumuli and T. pratensis (inside the T. pinophilus species complex) in the inferred phylogeny. Mycelia growth of the fungal strains was subjected to a range of 0-400 ppm Cd and incorporated into malt extract agar (MEA) in triplicates. Fungal radial growth was recorded every three days over a 13-days incubation period and In vitro cadmium tolerance tests showed a high tolerance index = 0,81 when the mycelium was exposed to 300 ppm of Cd. Results suggest T. santanderensis showed tolerance to Cd concentrations that exceed the permissible limits for contaminated soils, and it is promising for its use in bioremediation strategies to eliminate Cd from highly contaminated agricultural soils.

A new copper(I) complex, [Cu2(L)2dppm](PF6)2 (1) [L = 3-(2-Pyridyl)-5,6-diphenyl-1,2,4-triazine and dppm: Bis(diphenylphosphino)methane] was prepared and characterized by IR, 1H-NMR, 31P-NMR spectroscopy, elemental and thermogravimetric analysis, and single-crystal X-ray diffraction technique. Complex 1 is a dinuclear compound, showing that L and dppm act as tridentate and bidentate chelating ligands, respectively. The two Cu(I) atoms exhibit a distorted tetrahedral coordination sphere embedded in N3P environments. The supramolecular interactions in the solid-state structure are characterized by C−H···N, C−H···F, C-H···π and π···π intermolecular interactions that were analyzed by inspection of the Hirshfeld surface and fingerprint plots. Additionally, the complex was studied experimentally in solution by UV–Vis spectroscopy and cyclic voltammetry; also, theoretical studies with Time-Dependent Density Functional Theory (TD-DFT) were performed. Moreover, the optical and electrochemical properties have been studied, focusing on the band gap. Compound 1 has been used as a co-sensitizer in a dye-sensitized solar cell, showing good activity.

From June 18 to 19, 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24h in advance and could give an early warning of the extreme event 2.5 days before.

Framed in a context with an emerging economy and with a high percentage of school failure, this study aimed to identify the factors that turn students with socioeconomic disadvantages into resilient students. Two questions guided the research: Can resilience be supported in students in adverse socioeconomic situations? What factors influence building resilient students? A cross-sectional study was carried out from 2011 to 2015 in Chile, using a multilevel logistic regression model with three levels, considering the hierarchical data structure. The behavior of 63100 to 76400 sampled students was analyzed. Results show five relevant factors in building resilience: self-efficacy in language, minor aggressions and violence perceived by students, norms and values of the establishment, interest in study, and self-efficacy. Some risk factors identified were an atmosphere of less respect and trust, engagement in physical education activities and good performance in carrying them out. These results could orient educational leaders interested in supporting the educational community in order to improve the academic success of disadvantaged students.

Lupus, also known as systemic lupus erythematosus (SLE), is a chronic autoimmune disease that can lead to inflammation and damage to multiple organs and tissues in the body. The symptoms vary from patient to patient, which makes the disease manifest very differently, resulting in difficulty in diagnosing and treating patients. Some may experience fatigue, hair loss, joint pain, and more. In the past, a general approach of blanket immunosuppression was commonly used to treat lupus. These immunosuppressive drugs would broadly target the immune system and focus on reducing symptoms. However, recent research has shown that selective immunotherapies such as monoclonal antibodies (anifrolumab and belimumab) which target specific components of the immune system are more effective in managing lupus because of their ability to reach specific cells in the immune system rather than easing symptoms. Anifrolumab blocks the activity of type I interferons, while belimumab neutralizes BLyS to reduce the production of autoantibodies, the root cause of SLE.¹⁻² This paper will introduce the immunology of the disease, explore how the more traditional approach of blanket immunosuppressive drugs work compared to the newer selective immunotherapies, and review the results from the clinical trials of anifrolumab and belimumab.

Sphingolipids are lipids derived from an 18-carbons unsaturated amino alcohol, the sphingosine. Ceramide, sphingomyelins, sphingosine-1-phosphates, gangliosides and globosides, are part of this group of lipids that participate in important cellular roles such as structural part of plasmatic and organelle membranes maintaining their function and integrity, cell signaling response, cell growth, cell cycle, cell death, inflammation, cell migration and differentiation, autophagy, angiogenesis, immune system. The metabolism of these lipids involves a broad and complex network of reactions that convert one lipid into others through different specialized enzymes. Impairment of sphingolipids metabolism has been associated with several disorders, from several lysosomal storage diseases, known as sphingolipidoses, to polygenic diseases such as diabetes and Parkinson and Alzheimer diseases. Sphingolipids are mainly located in central nervous system, and their abundance and distribution depend on brain development state and cell type. Although several studies have expanded the knowledge about sphingolipids function both in health and disease, it is still necessary to continue their study to understand the cellular implications of novel sphingolipids. These studies will also contribute to the diagnosis and treatment of diseases in which these molecules are part of their pathophysiology. In this review, we summarize the main sphingolipid characteristics and current knowledge about the synthesis, catabolism, regulatory pathways, participation in action potential and ionic channels, among other relevant functions.

LSU (RESPONSE TO LOW SULFUR) proteins belong to a plant-specific gene family initially characterized by their strong induction in response to sulfate (S) deficiency. However, little is known about the LSU gene repertoire and evolution of this family in land plants. In this work, a total of 270 LSU family members were identified using 134 land plant species with whole genome sequence available. Phylogenetic analysis revealed that LSU genes belong to a Spermatophyta-specific gene family, and their homologs are distributed in three major groups, two for dicotyledons and one group for monocotyledons. Moreover, we analyzed the expression of LSU genes in one representative species of each phylogenetic group (wheat, tomato and Arabidopsis) and found a conserved response to S-deficiency, suggesting that these genes might play a key role in S stress responses. Accordingly, Arabidopsis lsu2 knockout mutant plants showed increased levels of internal sulfate content and lower levels of expression of different key genes involved in S deficiency and metabolism like SDI2 and APR3. In summary, our results indicate that LSU genes are evolutionarily conserved in angiosperms and that specific members of this family might play an important role regulation of S transport and assimilation.

The main point in the present article was the comparison of the Technical Efficiency (TE) in four years for milk production in Ecuador by the period 2018 – 2021, before and after the pandemic, and the determination of the factors related to the TE for the last year. The information from the official public database in the country were analyzed by the nonparametric technique called DEA including a bootstrap simulation. Once different variables were selected including aspects as livestock and labor, the TE with Variable Returns to Scale (VRS) with “output” orientation was calculated by each year and province. Among the provinces, statistically significant differences were found (P<0.1) for the TE means, and most of the efficient units were found throughout the Andean zone, in each year. Between the most important findings, it was important that the TE average after the beginning of the pandemic was statistically lower than the last 3 consecutive years under study (P<0.1) with 3% approximately of decrease, and the main factors related to this were multiple including labor characteristics, the field composition, and the supplies access during the pandemic. Finally, some implications for public policy were found around the gender in agriculture activities, the social security, and the difficulties in supplies access.

Microalgae are used in various biotechnological processes, such as biofuel production due to their high biomass yields, agriculture as biofertilizers, production of high-value-added products, de-contamination of wastewater, or as biological models for carbon sequestration. The number of these biotechnological applications is increasing, and as such, any advances that contribute to reducing costs and increasing economic profitability can have a significant impact. Nitrogen fixing organisms, often called diazotroph, also have great biotechnological potential, mainly in agri-culture as an alternative to chemical fertilizers. Microbial consortia typically perform more com-plex tasks than monocultures and can execute functions that are challenging or even impossible for individual strains or species. Interestingly, microalgae and diazotrophic organisms are capable to embrace different types of symbiotic associations. Certain corals and lichens exhibit this sym-biotic relationship in nature, which enhances their fitness. However, this relationship can also be artificially created in laboratory conditions with the objective of enhancing some of the biotech-nological processes that each organism carries out independently. As a result, the utilization of microalgae and diazotrophic organisms in consortia is garnering significant interest as a potential alternative for reducing production costs and increasing yields of microalgae biomass, as well as for producing derived products and serving biotechnological purposes. This review makes an effort to examine the associations of microalgae and diazotrophic organisms, with the aim of highlighting the potential of these associations in improving various biotechnological processes.

In this paper we use the Mellin convolution theorem, which is related to Perron's formula. Also we introduce new explicit formulae for arithmetic function which generalize the explicit formulae of Weil for other arithmetic functions different from the Von-Mangoldt function.

The objective of this study was to perform a systematic review and meta-analysis of the articles that addressed the effect BA or carnosine supplementation on physical exercise (PE)-induced oxidative stress (OS). Before May 2018 we searched throughout PubMed, CAPES Periodic and SPORTDiscus human model peer review, randomized control studies with chronic BA or carnosine supplementation on PE-induced OS. A total of 128 citations were found. Only four articles met criteria for inclusion. All four studies used healthy young sedentary, recreationally active or athletic participants. After a chronic BA or carnosine supplementation, the studies evaluated PE-induced OS both immediately and several hours after exercise (0.5 to 48 h). In response to PE-induced OS, when compared to placebo, BA/carnosine supplementation increased total antioxidant capacity [TAC; Effect Size (ES) = 0.35, 95% Confidence Interval (CI) 0.06 to 0.65, p = 0.02] and glutathione (GSH; ES = 0.75, 95% CI 0.32 to 1.19, p = 0.0007) concentrations while decreased direct OS markers (ES = −1.19, 95% CI −1.48 to −0.80, p < 0.01) and superoxide dismutase (SOD) activity (ES = − 0.58, 95% CI −1.10 to −0.06, p = 0.03). BA or carnosine supplementation did not prevent the increase in indirect OS markers (ES: 0.06, 95% CI −0.38 to 0.500, p = 0.80). In humans, following PE-induced OS, initial treatment trials of BA or carnosine supplementation seemed to increase TAC and GSH concentrations, while decreasing SOD activity. Also, albeit mitigating the acute increase in direct OS markers (reactive nitrogen and oxygen species), treatment did not decrease measured values of indirect OS markers (peroxidation or molecule oxidation).

In the last decade several projects have been developed for the digitization and semantization of cultural heritage data. They were developed to preserve and maintain this heritage, but bringing it closer to all types of users and allowing access to this information to other sectors such as tourism, education, etc. In these developments, web technologies are combined, along with the use of knowledge graphs and interactive visualisation tools. Although remarkably interesting projects have been developed, in those projects, the data visualization tools are usually focused on the project context. This makes it difficult to reuse these jobs. Additionally, there are peculiarities of cultural heritage data considered with little depth, such as uncertainty, spatial and temporal granularity, as well as other aspects, such as relationships between data. In this article, these problems are described and based on other works such as VUMO or VISO, the design of an ontology that formalizes how to visualise this information is proposed, considering these problems. In addition, the development of a platform that allows the visualisation of this information through a web application and its evaluation of its use in projects such as SILKNOW, or Arxiu Valencià del Disseny is exposed

This study examines HIV/AIDS-associated knowledge and attitudes towards treating disadvantaged communities among predoctoral dental students in U.S. dental schools who had not yet commenced their Community-Based Dental Education (CBDE) training. It also compares the difference in knowledge and attitudes between students with reported community engagement with PLWHA, and those without. Our study comprised 89 predoctoral dental students within their D1-D3 years of dental school who had not yet initiated their Community-Based Dental Education (referred to as pre-CBDE dental students). Responses were collected via an online survey. Participants were 68% females, 94% heterosexual, of mean age (years): 25.9 ± 3.5 SD. The majority (62%) were in their first (D1) and second (D2) years of dental education. Of the thirty knowledge questions, only five received a minimum of 90% correct responses. Similarly, we found no statistical differences in most of the knowledge/attitude sections, between those with and without prior PLWHA exposure. Encouragingly, 90% of our participants reported prior experience working with disadvantaged communities. Early community engagement fosters a sense of professional responsibility towards administering dental care to disadvantaged communities and we propose that it must be encouraged among aspiring dental school students.

Water scarcity is a worldwide concern, considering that water is a limited resource and essential for life. In Brazil, approximately 30% of its population lives in one of the areas that most suffer from lack of water, the semi-arid region covering about 20% of the country's territorial extension. The lack of water, mainly in the northeast of the country, has been a problem for years, where people who live in this territory have been suffering for months from the lack of water and the poor distribution of the resource, which increases the degree of inequality between the regions of the country. The research aims to show the effect of the hydrological cycle on the quality of vegetation and how such processing can end up affecting people's lives and the environment. The municipality of Floresta is within the scope of sub-basin 73, the territory is part of the municipalities benefited from the PISF- São Francisco River integration project works, and the study has raised discussion on the part of the scientific community regarding the effectiveness of the population project and the possible risks caused to the environment. This study carried out a temporal analysis, 1961-2021, to investigate water availability and how the hydrological system can affect society, raising the degree of its importance for a better quality of life and consequently reducing hydric inequalities. It was also evaluated how climate changes can interfere with these environmental changes and the quality of life at the local scale. The hydrological model system used to assess water availability was the Pernambuco Hydrological Response Units SUPer-System. In addition, this system helped to understand the changes that occurred in the studied sub-basin. Yet was used UAV-Unmanned Aerial Vehicles to view relationship between lives in house and environment conditions. The study can obtain accurate and necessary information to understand the dynamics of the hydrological system and the possible changes of social hydric inequalities. Thus, it is concluded that climate change will have different impacts on small scales and lives conditions due to different characteristic's environment. It is very important to carry out studies on a detailed scale to provide better public policies for mitigating the effects of climate change on people's lives.

Urban mobility is experiencing a profound change. On the one hand, mobility patterns are becoming more complex, and typical home-work-home travel is no longer the rule, as journeys now tend to connect multiple points in a rather inconstant pattern. This has changed the approach to transport planning, in that the existing transportation planning and operation approaches have been focussed on the ability to identify typical home-work/school-home travel and subsequently plan the transport system accordingly. The traditional approach has been: forecast -> plan -> deliver, as new mobility solutions are emerging. These are characterised by greater flexibility, in that they take advantage of the “sharing concept” and simultaneously provide solutions that have lower GHG emissions. Urban mobility follows a fuzzier pattern, with even the urban transportation system behaving like an active organism, where solutions are often quickly replaced. This dynamic and evolving environment raises several new challenges at different levels. The best digital solution system is the Mobility-as-a-Service (MaaS) one. This system transforms the physical transportation system into a commodity and takes advantage of the internet of things (IoT). However, the onset of MaaS solutions is anything but linear. Several business models have emerged, with different partners originating from different industries (e.g., technological, transport operators, infrastructure managers, etc.) developing their own solutions, often in competition with others. It is not unusual to find different MaaS solutions in the same city, which integrate different solutions.

1) Background: Climate change may subject forests to climate conditions to which they are not adapted. Elevated temperatures reduce net photosynthesis by increasing respiration rates and increasingly long droughts dramatically increase morbidity. CO₂ enrichment enhances productivity, but it is not clear to what extent CO₂ enrichment can offset the negative effects of elevated temperatures and longer droughts. 2) Methods: We used a mechanistic landscape model to conduct controlled simulation experiments manipulating CO₂ concentration, temperature, drought length and soil water capacity. 3) Results: We found that elevated CO₂ stimulates productivity such that it dwarfs the negative effect caused by elevated temperature. Energy reserves were not as strongly mitigated by elevated CO₂, and mortality of less competitive cohorts increased. Drought length had a surprisingly small effect on productivity measures, but had a marked negative effect on mortality risk. 4) Conclusions: Elevated CO₂ compensated for the negative effect of longer droughts in terms of productivity measures, but not survival measures.

Aging is a major risk factor for the higher incidence and prevalence of chronic conditions, such as cancer, cardiovascular and metabolic diseases, and neurodegenerative diseases. Closely linked with the onset of all these age-related diseases is immunosenescence, a condition defined as progressive reconfiguration of the immune functions leading to an increased susceptibility to infectious diseases, poorer response to vaccination, increased prevalence of cancer, rheumatoid arthritis, and other chronic diseases characterized by a pro-inflammatory state named inflammaging. Given that immunosenescence frames age-related diseases, it is natural to ask how these illnesses are related under the context of innate and adaptative components of the immune system. Knowledge processing by Formal Concept Analysis (FCA) of age-related diseases framed in an immunosenescence multivalued context shows that a hierarchy among these diseases emerges with a subconcept-superconcept nested structure, with two clusters, first made of metabolic diseases, cancer, and cardiovascular diseases. Second metabolic and neurodegenerative diseases and rheumatoid arthritis. Metabolic diseases seem to be a pivot illness and they must be a primary target given their global incidence and prevalence and their cost-effective treatments like regular physical activity, weight loss, healthy diet, stopping smoking, and reducing or managing stress. Another implication of the ontological analysis of age-related diseases is about the nature of immunosenescence, suggesting that initial symptoms of age-related diseases are mainly related to innate immune mechanisms, and developing of severe symptoms of age-related diseases like cancer, cardiovascular or neurodegenerative diseases depends on the activation of acquired immunity processes.

The article presents the results and conclusions of a series of tests of wedge-shaped blocks armoring carried out on a new experimental facility (‘Hydraulic Experimentation Facility - Luis Ruano’) in quasi-prototype conditions. The article describes the singular testing facility that was built at the inlet channel of the Acequia de Sora channel, immediately upstream of the Laverné reservoir (Zaragoza, Spain). The inflow of the testing facility has a maximum discharge of 9 m³s^-1. The aim is to perform experimental research on technologies to protect embankment dams and dikes against overflowing erosion under quasi-prototype conditions. The results of the tests showed the ability of the WSBs to withstand high unit discharges under extremely negative conditions. Furthermore, conclusions were drawn about potential threats to the sound behavior of the armor.

This article introduces simulations of theoretical material with controlled properties for the evaluation of the effect of key parameters, as volumetric fractions, elastic properties of each phase and transition zone on the effective dynamic elastic modulus (Ed). The accuracy level of classical homogenization models was checked regarding the prediction of Ed. Numerical simulations were performed with finite element method (FEM) for evaluations of the natural frequencies and their correlation with Ed, through frequency equations. An acoustic test validated the numerical results and obtained the elastic modulus of concretes and mortars at 0.3, 0.5 and 0.7 water-cement ratios (w/c). Hirsch calibrated according to the numerical simulation (x = 0.27) exhibited a realistic behavior for concretes of w/c = 0.3 and 0.5, with 5% error. Nevertheless, for w/c = 0.7, Ed approached Reuss model, similarly to theoretical triphasic materials. Hashin-Shtrikman bounds is not perfectly applied to theoretical biphasic materials under dynamic situations.

We consider a discrete-time random walk (xt) which at random times is reset to the starting position and performs a deterministic motion between them. We show that the quantity Prxt+1=n+1|xt=n,n→∞ determines if the system is averse, neutral or inclined towards resetting. It also classifies the stationary distribution. Double barrier probabilities, first passage times and the distribution of the escape time from intervals are determined.

While digitization can make the health industry faster and more efficient, there are many financial, social and organizational obstacles and barriers to its implementation. This article offers a systematic review of the main troubles detected from the literature review. Also there is a proposal of new kind of restrictions to pay attention. Finally, its offer an heterodox reading about the problem analyzed.

Dupilumab is used to treat atopic dermatitis patients who have proven to be refractory to previous treatments. The aim of this study was to assess evolution and patient reported outcome measures in adult patients with moderate-to-severe atopic dermatitis treated with Dupilumab in routine clinical practice. The outcomes were evaluated and registered at baseline and weeks-16, 40 and 52. The variables evaluated were: diseases severity, pruritus, stressful life events, difficulty to sleep, anxiety and depression, quality of life, satisfaction, adherence to the treatment, efficacy and safety. Eleven patients were recruited between Nov 14th 2017 and Jan 16th 2018. Demographic variables: 90% Caucasian, 82% women. Clinical variables: Mean duration of AD =17.7 (±12.8), 91% had severe disease severity. At baseline, SCORAD mean score = 61.7 (±15.5); itch was reported by 100% of patients; itch Visual Analogue Scale mean range of 8 (6-10); HADS mean total score =13.9 (±5.5); DLQI mean score =13.3 (±8.3): EQ-5D-3L mean range = 57 (30-99). At week-52 there is a significant reduction of SCORAD scores, HADS total score and improved quality of life. ¡This study confirms that Dupilumab, used for 52-weeks under routine clinical practice, maintains the improved atopic dermatitis signs and symptoms obtained at week-16, with a good safety profile.

This study proposes a methodology for identifying time intervals in which time-of-use (ToU) energy tariffs can be set. This is achieved by analyzing the variability in electric power demand and esti-mating the potential for demand flexibility. The proposed methodology is as follows: first, data preprocessing is performed, focusing on the organization and cleaning of individual consumption records. Subsequently, the data are processed and classified by using consumption variability analysis and clustering techniques. Then, representative clusters are selected and time intervals are analyzed to identify periods of high electric power consumption variability. This methodology was tested with real data from smart meters in the Colombian electrical system, in which time intervals with potential for settinh ToU tariffs were ultimately identified. This work promotes the implementation of demand response strategies that enhance sustainability and facilitate the transition to a more resilient energy landscape both nationally and internationally. The findings are expected to contribute to the formulation of tariff schemes that encourage con-scious changes in electric energy consumption patterns.

Wetlands are ecosystems that are essential to ecological balance and biodiversity, never-theless human activity is a constant threat to them. Excess nutrients are caused by inten-sive livestock and agricultural operations, pollution, and population growth, which in turn leads to uncontrolled microbiological development. This impairment in water quality can constitute a risk to animal, human, and environmental health. To thoroughly charac-terize the microbial communities, shotgun metagenomics was used to characterize the taxonomic and functional pattern of microorganisms that inhabit urban wetlands in the Los Lagos Region of Chile. The main objective was to identify microorganisms of veteri-nary relevance, assess their potential antibiotic resistance, and characterize the main vir-ulence mechanism. As expected, a high diversity of microorganisms was identified, in-cluding bacteria described as animal or human pathogens. Also, a diverse repertory of an-timicrobial-resistant genes (ARGs) was detected, which confers mainly resistance to be-ta-lactams, consistent with the families of antibiotics most used in Chile. Besides, a di-verse collection of virulence mechanisms was also identified. Given the significance of the relationship between environmental, animal, and human health—a concept known as One Health—there is a need to establish molecular surveillance programs. This work is the first report of the presence of these harmful biological elements in urban wetlands subjected to anthropogenic pressure, located in the south of Chile.

Tunable circular devices made of liquid crystals or other materials, like lenses, axicons or phase plates are often constrained by limitations in size, tunability, power and other parameters. These constrains restrict their use and limit their applicability. In this review, a thorough study of the use of light orbital angular momentum in LC devices manufacturing is presented. Twisted light amazingly fosters the simultaneous optimization of most critical parameters. Experimental demonstrations of unmatched performance of tunable LC lenses, axicons and other elements, in magnitudes such as lens diameter (> 1”), power and tunability (> ±6 diopters), fill factor (> 98%) and time response have been achieved by reversible vortex generation created by azimuthal phase delay. This phase delay can be eventually removed within the optical system, so that the lens performance is not affected.

Current pharmacological treatments of Fibromyalgia (FM) are merely symptom palliative, as clinical trials have so far failed to provide overall benefits without associated harms. Polypharmacy often leads to patient´s health deterioration and chronic drug use to an eventual lack of patient´s response. Emerging evidence support that physiotherapy treatments based on mechanical triggers improve FM symptoms and therefore could be used for therapeutic purposes by themselves, or in combination with current pharmacological treatments, as part of integrative medicine programs. However, a paucity of studies rigorously and systematically evaluating this possibility exists. This study uses scores from validated standardized questionnaires, algometer pressure point threshold (PPT) readings and responses from a custom self-developed questionnaire to determine the impact of a pressure-controlled manual protocol on FM hyperalgesia/allodynia, fatigue and patient´s quality of life. The results show that patient´s baseline sensitivity to pain inversely correlates with treatment response in FM. Moreover, patients presenting comorbid ME/CFS do not seem to respond to the applied therapy as those presenting FM only. Thus, pre-treatment PPTs and ME/CFS comorbidity may serve as indicators to predict patient´s response to physiotherapy programs based on mechanical triggers, as the one evaluated here. These unexpected findings grant further explorations including the study of gene expression profiles associating to patient´s treatment response in the blood collection of samples generated by this study.

As Chronic Non-Communicable Diseases (CNCD) increase, preventive approaches become more crucial. In this review, Calorie Restriction (CR) effects on human beings were evaluated, comparing benefits and risks of different CR diets: classic CR vs ketosis-inducing diets, including Intermittent Fasting (IF), Classic Ketogenic Diet (CKD), Fasting Mimicking Diet (FMD), Very-Low-Calorie Ketogenic Diet (VLCKD) and Spanish Ketogenic Mediterranean Diet (SKMD). Special emphasis on Insulin Resistance (IR) was placed, as it mediates Metabolic Syndrome (MS), a risk factor for CNCD, and predicts MS diagnosis. CR is the most robust intervention known to increase lifespan and health span, with high evidence and known biochemical mechanisms. CR improves cardiometabolic risk parameters, boosts exercise insulin sensitivity response, and there may be benefits of implementing moderate CR on healthy young and middle-aged individuals. However, there is insufficient evidence to support long-term CR. CKD is effective for weight and MS management, and may have additional benefits such as prevention of muscle loss and appetite control. SKMD has extreme significance benefits for all the metabolic parameters studied. Studies show inconsistent benefits of IF compared to classic CR. More studies are required to study biochemical parameters, reinforce evidence, identify risks, and seek effective and safe nutritional CR approaches.

Companion cropping involves growing two or more species together, benefiting the conservation of natural resources and improving fertilization and nutrient cycling by balancing chemical and organic sources. Studies, as in the case of tree tomato and Hass avocado, have shown a significant increase in yield compared to monocultures, highlighting the viability of this practice. In addition to their environmental benefit, companion crops offer economic advantages to producers by obtaining multiple products in a single harvest, strengthening food security and the economy of rural families. This study evaluated three levels of fertilization and interactions between fruit trees at different altitudes, observing differential behavior in the variables evaluated. The combination of cape gooseberry and blackberry showed significantly positive results, with more leaves and fewer pests, demonstrating the benefits of companion plants. A trend towards the combined use of chemical and organic fertilizers was observed, a potential strategy to reduce costs and improve crop growth. The results were shared with producers interested in implementing companion cropping, encouraging the adoption of this more sustainable and profitable agricultural practice. Companion crop agriculture represents a viable and promising strategy for a more efficient and sustainable agriculture, with both environmental and economic benefits.

Automated systems, regulated by algorithmic protocols and predefined set-points for feedback control, require the oversight and fine-tuning of skilled technicians. This necessity is particularly pronounced in automated greenhouses, where optimal environmental conditions depend on the specialized knowledge of dedicated technicians, emphasizing the need for expert involvement during installation and maintenance. To address these challenges, this study proposes the integration of data acquisition technologies using Internet of Things (IoT) protocols and optimization services via Reinforcement Learning (RL) methodologies. The proposed model was tested in an industrial production greenhouse for the cultivation of industrial hemp, applying adapted strategies to the crop, and was guided by an agronomic technician knowledgeable about the plant. The expertise of this technician was crucial in transferring the RL model to a real-world automated greenhouse equipped with IoT technology. The study concludes that the integration of IoT and RL technologies is effective, validating the model's ability to manage and optimize greenhouse operations efficiently and adapt to different types of crops. Moreover, this integration not only enhances operational efficiency but also reduces the need for constant human intervention, thereby minimizing labor costs and increasing scalability for larger agricultural enterprises. Furthermore, the RL-based control has demonstrated its ability to maintain selected temperatures and achieve energy savings compared to classical control methods.

Enzymatic polyethylene terephthalate (PET) recycling processes are gaining interest for their low environmental impact, use of mild conditions, and specificity. Furthermore, PET hydrolase enzymes are continuously being discovered and engineered. In this work, we studied a PET hydrolase (PET2), initially characterized as an alkaline thermostable lipase. PET2 was produced in a fusion form with a 6-histidine tag in the N-terminal. The PET2 activity on aromatic terephthalate and new indole-based polyesters was evaluated using polymers in powder form. Compared with IsPETase, an enzyme derived from Ideonella sakaiensis, PET2 showed a lower PET depolymerization yield. However, interestingly, PET2 gave significantly higher polybutylene terephthalate (PBT) and polyhexylene terephthalate (PHT) depolymerization yields. A clear preference was found for aromatic indole-derived polyesters over non-aromatic ones. No activity was detected on Akestra™, an amorphous copolyester with spiroacetal structures. Docking studies suggest that a narrower and more hydrophobic active site reduces its activity on PET but favours its interaction with PBT and PHT. Understanding the enzyme preferences of polymers will contribute to their effective use to depolymerize different types of polyesters.

The aim of the study was to evaluate the impact of probiotics obtained from agro-industrial substrates fermented with lactic acid bacteria and/or yeasts on the health and changes in the microbiota of the digestive tract of guinea pigs. Eighty male guinea pigs, Kuri breed, 30 days old and 250 g live weight, were randomly selected and divided into four groups of 20 animals each. T0, Control, T1, Lactobacillus acidophilus and L. bulgaricus. T2, Saccharomyces cerevisiae and Kluyveromyces fragilis and T3. L acidophilus, L bulgariccus, S cerevisiae and K. fragilis. T1, T2 and T3 contained molasses-vinasse substrate in their base, the dose administered was 0.75 mL/animal orally. The parameters evaluated were weight gain, occurrence of diarrhea and mortality, blood profile, macroscopic lesions in the digestive tract organs and changes in the microbiota of the stomach, caecum, small and large intestine. Treatments T1, T2 and T3 improved weight gain (p<0.05) and reduced the presence of guinea pigs with diarrhea (p<0.05) and there was no mortality; hematic indices did not vary significantly (p>0.05) between treatments; animals in the control group presented a greater amount (p<0.05) of macroscopic lesions in the digestive tract organs; in the T1, T2 and T3 group there was an improvement in the natural microbiota. It is concluded that the inclusion of microbial additive in young guinea pigs improves intestinal health, consequently, improves weight gain, reduces diarrhea and deaths, and normalizes the natural microbiota of the gastrointestinal tract.

Dinoflagellates are one of the largest groups of marine microalgae and exhibit diverse trophic strategies. Within these niches, dinoflagellates can produce secondary metabolites that are known to be toxic, which can lead to ecologically harmful blooms. Amphidinium carterae is one species of dinoflagellate that produces toxic compounds and is used as a model for dinoflagellate studies. The extent to which the microbiome surrounding A. carterae affects its growth and secondary metabolite synthesis is still being assessed, as well as the impact of bacterial data on sequencing and assembly. An antibiotic cocktail was previously shown to eliminate 16S amplification from the dinoflagellate culture. Even with drastically reduced bacterial numbers, bacterial populations are likely to be present. In this experiment we used novel Nanopore long-read sequencing techniques on A. carterae cultures to assemble 15 full bacterial genomes ranging from 2.9-6.0 Mb and found that the use of antibiotics decreased the percentage of reads mapping back to bacteria. We also identified shifts in the microbiome composition and identified a potentially deleterious bacterial species arising in the absence of the antibiotic-treatment. Multiple antibiotic-resistance genes were identified, as well as evidence that the bacterial population do not contribute to toxic secondary metabolite synthesis.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

Introduction: In recent decades, health literacy, in connection with a broad range of public 1 health terms, has become a burgeoning field. This study aims to explore trends and biases in this 2 area through a bibliometric analysis. Methods: A Random Forest Model was utilized to identify 3 keywords and other metadata that predict annual citations in the field. In order to supplement 4 this machine learning analysis, we have also implemented a bibliometric review of the corpus. 5 Results: Findings indicate a high positive coefficient for the keyword ’Covid-19’ and ’Male’, whereas a 6 negative coefficient was observed for ’Female’, suggesting potential biases. Evolving themes such as 7 Covid-19, Mental Health, and Social Media were discovered. A significant shift was noted in the main 8 publishing journals, while the major contributing authors remained the same. Discussion: The results 9 hint at the influence of the Covid-19 pandemic and potential gender biases on citation likelihood, as 10 well as changing publication strategies despite the fact that the main researchers remain as the ones 11 that have been studying health literacy since its creation.

Numerous protocols have been published for extracting DNA from phlebotomines. Nevertheless, their small size is generally an issue in terms of yield, efficiency, and purity, for large-scale individual sand fly DNA extractions when using traditional methods. Even though this can be circumvented with commercial kits, these are generally cost-prohibitive for developing countries. We encountered these limitations when analysing parasite infection in Lutzomyia spp. by PCR [1] and, for this reason, we evaluated various modifications on a previously published protocol ([2] and Acardi personal communication). The most significant variation was the use of a different lysis buffer [3] to which added Ca2+ (buffer TESCa), because this ion protects proteinase K against autolysis, increases its thermal stability, and could have a regulatory function for its substrate-binding site [4]. Individual sand fly DNA extraction success was confirmed by amplification reactions using internal control primers that amplify a fragment of the cacophony gene [5,6]. To the best of our knowledge, this is the first time a lysis buffer containing Ca2+ has been reported for the extraction of DNA from sand flies.

Despite the best efforts in air-purification, airborne infectious diseases do and will continue to spread due to continuous emission of bioaerosols by the host/infected person. To tackle the rapid spread of airborne infectious diseases, a shift in focus from air-purification to bioaerosol disinfection/ decontamination is urgently needed. In this work, we studied a cold plasma ionizer (CPI) and electrostatic precipitator (ESP)-coupled CPI (CPI-ESP) for disinfection and cleaning of bioaerosols. Using porcine respiratory coronavirus (PRCV) and E. coli in a testing chamber, we demonstrated that CPI coupled with ESP is an effective technology for inactivating aerosolized microorganisms and microorganisms spread on surfaces. In addition, we have demonstrated the efficiency of a CPI-ESP coupled device for disinfection of naturally occurring airborne microbials in a few indoor settings (i.e., an living room, a discussion room, a schoolroom and an office) to determine the treatment duration- and human activity-dependent efficacy. To understand the disinfection mechanism, we conduced fluorescence microscopy study to reveal different degree of bacteria cell membrane damage under CPI treatment.

Demyelinating diseases alter myelin or the coating surrounding most nerve fibers in the central and peripheral nervous systems. The grouping of human central nervous system demyelinating disorders today includes Multiple Sclerosis (MS) and Neuromyelitis Optica Spectrum Disorders (NMOSD) as distinct disease categories. Each disease is caused by a complex combination of genetic and environmental variables, many involving an autoimmune response. Even though these conditions are fundamentally similar, research into genetic factors, their unique clinical manifestations, and lesion pathology has helped with differential diagnosis and disease pathogenesis knowledge. This review aims to synthesize the genetic approaches that explain the differential susceptibility between these diseases, explore the overlapping clinical features, and pathological findings, discuss existing and emerging hypotheses on the etiology of demyelination, and assess recent pathogenicity studies and their implications for human demyelination. This review presents critical information from previous studies on the disease, which asks several questions to understand the gaps in research in this field.

Undisturbed ground temperature (UGT), thermal conductivity (TC) and heat capacity (HC) are essential parameters for the design of borehole heat exchanger (BHE) and borehole thermal energy storage systems. However, field methods to assess the thermal state and properties of the sub-surface are costly and time consuming. Moreover, HC is often not evaluated but arbitrarily selected from literature considering the geological materials intercepted by boreholes. Therefore, this work aims at proposing a field heat tracing method to infer the thermal diffusivity (TD) and HC with assumption of natural transient heat conduction in the subsurface. Empirical equations were developed to reproduce a UGT profile measured along a BHE. Experimental coefficients are found with a non-linear least square solver optimization and used to calculate the damping depth and TD. Subsequently, the TD is used to evaluate HC considering TC obtained from a thermal response test (TRT). Results from this proposed heat tracing method were verified and validated against a set of TRT results and oscillatory TRT analysis using a field dual probe concept to infer HC. The example here described highlights the advantages and novelty of this fast and simple field method relying only on a single UGT profile measured before a TRT.

Molybdenum (Mo) is vital for the activity of a small but essential group of enzymes called mo-lybdoenzymes. So far, specifically five molybdoenzymes have been discovered in eukaryotes: nitrate reductase, sulfite oxidase, xanthine dehydrogenase, aldehyde oxidase, and mARC. In order to become biologically active, Mo must be chelated to a pterin, forming the so-called Mo cofactor (Moco). Deficiency or mutation in any of the genes involved in Moco biosynthesis results in the simultaneous loss of activity of all molybdoenzymes, fully or partially preventing the normal development of the affected organism. To prevent this, the different mechanisms in-volved in Mo homeostasis must be finely regulated. Chlamydomonas reinhardtii is a unicellular, photosynthetic, eukaryotic microalga that has produced fundamental advances in key steps of Mo homeostasis over the last 30 years, which have been extrapolated to higher organisms, both plants and animals. These advances include the identification of the first two molybdate transporters in eukaryotes (MOT1 and MOT2), the characterization of key genes in Moco biosynthesis, the identification of the first enzyme that protects and transfers Moco (MCP1), the first characteriza-tion of mARC in plants, and the discovery of the crucial role of the nitrate reductase-mARC complex in plant nitric oxide production. This review aims to summarize all these advances made using C. reinhardtii as a model organism in Mo homeostasis and suggest how this microalga can continue to contribute to progress in this field.

Lung cancer is the leading cause of cancer mortality worldwide, and it is urgently necessary to diagnose it as early as possible. Usually, the diagnostic process begins with a radiological examination which, when a possible tumour is present, is followed by a biopsy to extract tissue samples from the patient's lungs. Therefore, the purpose of this study is the development of an artificial intelligence algorithm that will analyse the Whole Slide Image (WSI) generated by the digitisation of the glass slides obtained from the extracted samples and detect if there is a tumour. The developed learning algorithms as well as the tested neural networks (NNs) were trained on a dataset composed of previously annotated WSI tiles, classified as Tumour or Non-Tumour. From these, four developed convolutional neural networks stood out and were selected to be compared with each other and with the tested NNs. When the best result of each of the developed architectures was compared to the highest result of the tested NNs, it was possible to denote that version 4 of CancerDetecNN achieved an average accuracy of 89.749 \% and an average loss of 0.220. Furthermore, the results for the four selected versions are in agreement with the results reported in the literature, however, the limited size of the given dataset must be considered. Given the results obtained, the fourth version has the potential to optimise the lung cancer diagnosis process.

Tributyltin (TBT) is an environmental contaminant present on all continents, including Antarctica, with a potent biocidal action. Its use began to be intensified during the 1970s, being effectively banned in 2003, but remaining in the environment to this day due to several factors that increase its half-life and misuse despite the bans. In addition to the endocrine disrupting effect of TBT, that may lead to imposex induction in some invertebrate species, there are several studies that demonstrated that TBT also has an immunotoxic effect. The immunotoxic effects that have been observed experimentally in vertebrates using in vitro and in vivo models involve different mechanisms, but mainly alterations in the expression and/or secretion of cytokines. In this review, we summarize and update the literature on the impacts of TBT on the immune system, as well as discuss what still needs to be done to fill the knowledge gaps regarding the impact of this endocrine disrupting-chemical on immune system homeostasis.

Abstract: COVID-19 in 2020 brought challenges to the Brazilian public health system with an emerging virus with respiratory contagion called SARS-CoV-2. There are few studies in Brazil and in some countries, on the increased incidence of certain viral respiratory infections, includ-ing H1N1 and coronavirus and their association with low levels of vitamin D, zinc and iron. The aim of this study was to demonstrate that the deficit of vitamin D, zinc and iron has an impact on the infectious process of patients with COVID-19 and to establish new forms of prevention for the worsening of COVID-19 in the human body. Data were collected from medical records and test results from patients being followed up during the treatment period for COVID-19. Patients with low blood levels of vitamin D, zinc and iron during the treatment period of COVID-19 had a higher percentage of worsening and complications requiring hospitalization in intensive care beds. The ingestion of vitamin D, zinc and iron in the treatment period of patients with COVID-19 in addition to being an immunological protector against SARS-CoV-2 and alleviating the process of worsening the disease can also act as a biomarker in cases of this disease.

Groundwater degradation is a global problem linked to irrigation agriculture and aggravated by climate change. In drylands, where aquifer recharge is low, irrigation has emerged as an engine of economic growth. This problem falls under the paradigm of desertification, as it fits the definition of this complex problem in that the degradation of drylands is due to climatic variations and inappropriate human activities. Land Degradation Neutrality (LDN), the response of the United Nations Convention to Combat Desertification to the lack of progress in tackling desertification, is integrated into Sustainable Development Goal 15.3 and provides the adequate framework for implementing effective solutions. LDN prioritizes prevention strategies, and early warning systems coupled to integrated simulation models is a sound approach. We analyze the dynamics of a coastal aquifer in southern Spain, a “desertification landscape” according to the Spanish National Action Plan to Combat Desertification. For this purpose, we have (i) adapted a generic desertification model that considers socio-ecological systems as a particular case of predator-prey systems; and (ii) coupled to this model a risk analysis to calculate the probabilities of groundwater salinization under the current scenario of water resources use, driven by the expansion of greenhouse agriculture supported by external water transfer. The risk of desertification is close to 100%: groundwater salinity is 40 dS m-1 (well above tomato tolerance, 3.5 dS m-1), and 2.4 Mm3 yr–1 water transfer is needed to support the 631 ha of greenhouses. This worrying result suggests that complimentary solutions should be promoted to deactivate the ongoing process of desertification. Among them, we propose reclaimed water, diversifying the economy, or promoting crops adapted to aridity. This simulation framework shows how to explore the future of a socio-ecosystem under current scenarios and others that consider climate change, the energy crisis, or the impact of alternative solutions.

We advance binational link-tracing sampling design, an innovative data collection methodology for sampling from transnational social fields, i.e., transnational networks embedding migrants and non-migrants. This paper shows the practical challenges of such a design, the representativeness of the samples and the qualities of the resulted networks. We performed 303 face-to-face structured interviews on sociodemographic variables, migration trajectories and personal networks of people living in a Romanian migration sending community (Dâmbovița) and in a migration receiving Spanish town (Castellón), simultaneously in both sites. Inter-connecting the personal networks, we built a multi-layered complex network structure embedding 4,855 nominated people, 5,477 directed ties (nominations) and 2,540 edges. Results indicate that the participants’ unique identification is a particularly difficult challenge, the representativeness of the data is not optimal (homophily on observed attributes was detected in the nomination patterns), and the relational and attribute data allow to explore the social organization of the Romanian migrant enclave in Castellón, as well as its connectivity to other places. Furthermore, we provide methodological suggestions for improving link-tracing sampling from transnational networks of migration. Our research contributes to the emerging efforts of applying social network analysis to the study of international migration.

Background: The treatment plan of prosthetic restorations supported by dental implants require comprehensive scientific knowledge to deliver prostheses with good prognosis, even before the implant insertion. This review aims to analyze the main prosthetic determinants of the prognosis of implant-supported prostheses. Methods: A systematic review of the literature was conducted with a PICO question: "For partially or complete edentulous subjects treated with implant-supported prostheses, which prosthetic factors could affect clinical outcomes?". A literature search was performed electronically in PubMed (MEDLINE), Scopus and Cochrane Library with the following equation [PROGNOS* OR RISK] FACTOR IMPLANT DENTAL, and by hand search in relevant journals and throughout the selected papers. Results: This revision was carried out based on 50 papers focused on several prosthodontics-related risk factors that were grouped as follows: implant-connection, loading protocol, transmucosal abutments, prosthetic fit, provisionalization, type of retention, impression technique, fabrication technique, and occlusion. More than a half of the studies were systematic reviews (30%), meta-analysis (16%) or prospective evaluations of prosthesis with various kinds of events (18%). But also narrative reviews of literature (14%) and in vitro/animal studies (16%) were found. Conclusions: The current literature provides insufficient evidence for most of the investigated topics. However, based on the accumulated data, it seems reasonable to defend that the best treatment approach is the use of morse taper implants with transmucosal abutments, recorded by means of rigidly splinted copings through the pick-up technique, and screwed by milled prosthesis occlusally adjusted to minimize functional overloading.

We present an ontology log-OLOG- representation of the classical Miller-Urey experiment, usually considered as a paradigm for spontaneous generation of biomolecules on the prebiotic Earth and also, as a key in understanding the chemical evolution phenomena linked to the origins of life. Ologging The Miler-Urey experiment enables us, through the categorical notion of fibre product or pullback, to define the concept of Biogenic Space, as a space containing low complexity biogenic units subjected to appropriate physical and chemical conditions, facilitating the synthesis of highly complex organic molecules. Also, we characterize the Biogenic Space as a concrete universal object that could be associated with the preconditions for life inside various structures in the universe such as exoplanets and exomoons located in habitable zones, but also in interstellar and intergalactic organic clouds.

COVID-19 sepsis immune response remains unclear. Here we propose a new perspective in host response against pathogenic proteins that may lead to a vaccine design by polymerization of antigens of <70 kDa. In COVID-19, initial Th1 response kills infected cells releasing viral proteins. SARS-CoV-2 viral structural proteins are Spike (140 kDa), Nucleocapsid (50 kDa), Membrane (25 kDa) and Envelope (10 kDa). B cell receptor cannot capture antigens >70 kDa. The Spike protein (140 kDa) cannot be captured by B cells and triggers inflammatory Th1 response via the macrophages. Only proteins with a size <70 kDa can activate B cell receptor and trigger Th2 adaptative humoral response. Moreover, M-25 kDa and E-12 kDa glycoproteins can activate IgM-BCR like oligovalent or monovalent antigens. The sustained infected cells lysis overfeeds high levels of viral proteins <70 kDa, increases B cells activation and, in the shift from Th1 to Th2 immune response, triggers the cytokine storm. The continuous BCR activation increases IL-10 releasing and may lead to immune paralysis.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

Carbon nanotubes (CNTs) can be considered as semi-rigid all-carbon polymers. However, unlike conventional polymers that can form 3D networks such as hydrogels or elastomers through crosslinking with each other in solution, the cylindrical carbon lattice of CNTs was not believed to be directly crosslinkable in solution until our recent discovery of UV-defluorination driven direct CNT crosslinking. In this study, we further reveal that the UV-defluorination-driven crosslinked CNTs are metastable and can decompose more readily than fluorinated or pristine CNTs upon exposure to Raman laser irradiation. Specifically, we investigate the stability of UV-defluorinated single-walled and multi-walled fluoro-nanotubes using Raman spectroscopy under controlled varying laser power. The results indicate that both the defluorinated single-walled and multi-walled CNTs are thermally less stable than pristine CNTs or untreated fluorinated CNTs, which can be attributed to the strains on the crosslinking bonds created from the curved carbon lattice of linked CNTs. This instability, particularly evident under high-power laser irradiation, leads to combustion processes ignited at relatively lower temperatures that cause an extended burned area centered on the laser spot, offering potential future applications as mechanically robust, lightweight materials with feasible post-use degradation options.

Rare Earth Elements (REE), also known as Lanthanides (Ln3+), are a group of 17 elements showing peculiar physical and chemical properties. Unlike technological applications, very little is known about the physiological role and toxicity of Ln3+ on biological systems, in particular on microorganisms (e.g., bacteria), which represent the most abundant domains on our planet. Up to now, very limited studies have been conducted due to Ln3+ precipitation with some anions commonly present in the culture media. Therefore, the development of a minimal medium is essential to allow the study of Ln3+-microbial interactions, limiting considerably the precipitation as insoluble salts. In this regard, a new minimal culture medium capable of solubilizing large amounts of Ln3+, and allowing the growth of different microbial taxa, was successfully developed. Assays have shown that the medium is capable of solubilizing Ln3+ up to 100 times more than other common culture media and allowed the growth of 63 bacteria and 5 fungi. The kinetic growth of one yeast and one gram-positive bacterium has been defined, proving to support superior growth and biomass compared to other commonly used minimal media. Moreover, the sensitivity and uptake/absorption of a Bacillus stratosphericus strain was tested, highlighting its capability to tolerate concentrations up to 10 mM of either Cerium, Gadolinium or Lanthanum and accumulate different quantities of the three.

While significant efforts have been made to recycle metals like lithium or cobalt for sustainable development in the battery industry, other high-value materials in the renewable energy sector, such as fluorinated carbon nanotubes (FCNTs), have not been adequately explored for re-utilization after their quality has been downgraded. FCNTs are expensive and energy-intensive to produce, making their sustainable use crucial. This study explores the potential of reusing quality-downgraded fluorinated carbon nanotubes (QD-FCNTs) as eco-friendly nano-additives in microgel composites for water retention applications. By employing a surface treatment process that avoids additional energy costs and environmentally harmful chemicals, we successfully enhanced the interaction between QD-FCNTs and microgels. This treatment significantly improved water retention time by reducing rapid evaporation, enabling sustained water release. Our findings demonstrate a promising avenue for the sustainable application of quality-downgraded fluorinated carbon nanotubes in agricultural and environmental technologies.

Current antibiograms cannot discern the particular effect of a specific antibiotic when the bacteria are incubated with a mixture of antibiotics. To prove that this task is achievable, Escherichia coli strains were treated with ciprofloxacin for 45 min, immobilized on a slide and stained with SYBR Gold. In susceptible strains, the nucleoid relative surface started to decrease near the MIC, being progressively condensed as dose increased. The shrinkage level correlated with the DNA fragmentation degree. Ciprofloxacin-resistant bacilli showed no change. Additionally, E. coli strains were incubated with ampicillin for 45 min and processed similarly. The ampicillin-susceptible strain revealed intercellular DNA fragments that increased with dose, unlike the resistant strain. Co-incubation with both antibiotics revealed that ampicillin did not modify the nucleoid condensation effect of ciprofloxacin, whereas the quinolone partially decreased the background of DNA fragments induced by ampicillin. Sixty clinical isolates, with different combinations of susceptibility-resistance to each antibiotic, were co-incubated with the EUCAST breakpoints of susceptibility of ciprofloxacin and ampicillin. The morphological assay correctly categorized all the strains for each antibiotic in 60 min, demonstrating the feasible independent evaluation of a mixture of quinolone and beta-lactam. The rapid phenotypic assay may shorten the incubation times and necessary microbial mass currently required for evaluation.

Renewable methanol, obtained from CO₂ and hydrogen provided from renewable energy, has been proposed as a way to close the CO₂ loop. In industry, methanol synthesis using the catalyst CuO/ZnO/Al₂O₃ occurs at a high pressure. We intend to make certain modification on the traditional catalyst in order to work at lower pressure, maintaining high selectivity. Therefore, three heterogeneous catalysts have been synthesized by co-precipitation in order to improve the activity and the selectivity to methanol under mild conditions of temperature and pressure. Certain modifications on the traditional catalyst Cu/Zn/Al₂O₃ were employed such as the modification of the synthesis time and the addition of Pd as a dopant agent. The most efficient catalyst among those tested was a palladium-doped catalyst, 5% Pd/Cu/Zn/Al₂O₃. This had a selectivity of 64% at 210C and 5 bar.

Rising antimicrobial resistance (AMR) in Salmonella serotypes host-adapted to cattle is of increasing concern to the beef and dairy industry. The bulk of the existing literature focuses on AMR post-slaughter. In comparison, the understanding of AMR in Salmonella among pre-harvest cattle is still limited, particularly in Texas, which ranks top five in beef and dairy exports in the United States; inherently, the health of Texas cattle has nationwide implications for the health of the United States beef and dairy industry. In this study, long-read whole genome sequencing and bioinformatic methods were utilized to analyze antimicrobial resistance genes (ARGs) in 98 isolates from beef and dairy cattle in the Texas Panhandle. Fisher exact tests and elastic net models accounting for population structure were used to infer associations between ARGs and antimicrobial phenotypic profiles and metadata. Gene mapping was also performed to assess the role of mobile genetic elements in harboring ARGs. ARG were found to be statistically different between the type of cattle operation and Salmonella serotypes. Beef operations were statistically significantly associated with more resistance genes compared to dairy operations. Salmonella Heidelberg, followed by Salmonella Dublin isolates, were associated with the most ARGs. Additionally, specific classes of ARGs were only present within mobile genetic elements.

The extra precession of Mercury - 42.9 seconds of arc per century - explained by General Relativity (GR), is the result of a secular addition of 5.02 × 10⁻⁷ rad. at the end of every orbit around the Sun. We will analyze, the instantaneous precession and its addition along one orbit, determine the magnitude and oscillations around the mean value, comparing key theoretical proposals. This angular precession, should be the result reaction of Mercury to the gravitoelectric action produced by the geometric curve space-time at each single point of the elliptic orbit. The better we should know about this instantaneous precession, the better we will determine the external action and its quantum core nature, if that is the case. The Doppler tracking of the MESSENGER spacecraft, produces only 1 m error, enough precision to deduce the complete geodesic orbit of Mercury as an open free-fall path, isolated from other planets gravitational interference. The aim of this article is also to encourage JPL, IMCCE. and other scientific teams to do so because, as far as I know, it has not been entirely measured yet, by accurately tracking that motion.

The highly adaptable parasite Trypanosoma cruzi undergoes complex developmental stages to exploit host organisms effectively. Each stage involves the expression of specific proteins and precise intracellular structural organization. These morphological changes depend on key structures that control intracellular components’ growth and redistribution. In trypanosomatids, the flagellar attachment zone (FAZ) connects the flagellum to the cell body and plays a pivotal role in cell expansion and structural rearrangement. While FAZ proteins are well-studied in other trypanosomatids, there is limited knowledge about specific components, organization, and function in T. cruzi. This study employed the CRISPR/Cas9 system to label endogenous genes and conduct deletions to characterize FAZ-specific proteins during epimastigote cell division and metacyclogenesis. In T. cruzi, these proteins exhibited distinct organization compared to counterparts in T. brucei. TcGP72 is anchored to the flagellar membrane, while TcFLA-1BP is anchored to the membrane lining the cell body. We identified unique features in the organization and function of the FAZ in T. cruzi compared to other trypanosomatids. Deleting these proteins had varying effects on intracellular structures, cytokinesis, and metacyclogenesis. This study reveals specific variations that directly impact the success of cell division and differentiation of this parasite.

Vegetable oils contain fatty acids, phenolic compounds, natural antioxidants, and fat-soluble vitamins, which are beneficial against different diseases. Oil extraction methods can, however, affect their composition. This study aims to characterize the chemical composition of oils from two Andean seeds, cañihua (Chenopodium pallidicaule) and tarwi (Lupinus mutabilis), extracted with different organic solvents, petroleum ether, hexane, and ethanol. This study compares these oils with commercial sunflower, rapeseed, and olive oils. Results showed that oils extracted with hexane had the highest yield, while those extracted with ethanol had higher antioxidant activity and total phenolic compound content. Additionally, using ethanol makes the process more sustainable than non-green solvents. The composition of tarwi and cañahua oils extracted with ethanol includes fatty acids, tocopherols, antioxidants, and phenolic compounds associated with health benefits.

The binding affinity of trastuzumab and pertuzumab to HER2 has been studied using both experimental and in-silico methods. The experiments were conducted using the antibodies in their complete IgG form, as used in clinical therapy, and the extracellular domain of the HER2 protein in solution. This approach provides a precise, reproducible, and reliable view of the interaction between them in physiological conditions. Dynamic light scattering and size exclusion chromatography coupled with tetra detection were utilized to characterize the protein complexes, measure their concentrations, and calculate the equilibrium free binding energy, ΔGbind. In addition, PRODIGY, a QSAR-like model with excellent predictive ability, was employed to obtain in-silico ΔGbind estimations. The results obtained indicate that pertuzumab exhibits a slightly higher binding affinity to HER2 than trastuzumab. The difference in binding affinity was explained based on the contribution of the different interfacial contact (IC) descriptors to the ΔGbind value estimated by the PRODIGY model. Furthermore, experiments revealed that the pertuzumab IgG antibody binds preferentially to two HER2 proteins, one per Fab fragment, while trastuzumab mainly forms a monovalent complex. This finding was interpreted based on a geometrical model that identified steric crowding in the trastuzumab-HER2 complex as compared to the pertuzumab-HER2 complex.

Making sustainable business models, especially in manufacturing, is a key approach for organizations to adopt in order to create more sustainable processes. New technologies are needed to implement new policies that can minimize the economic, environmental, and social consequences of industrial activity. Sustainable maintenance is decisive to guarantee the availability, reliability, and safety of assets, surpassing traditional maintenance policies and embracing the principles of the circular economy. The main objective of Maintenance 4.0 is to increase the lifespan and availability of the equipment by preventing unplanned downtime, reducing planned shutdowns, and improving safety. This research focuses on the integration of advanced Industry 4.0 tools with conventional monitoring and control techniques in process industries. The article suggests that while complex neural networks might provide good predictions, simpler solutions can generalize well and have lower prediction errors because they can capture the underlying relationships between variables in a specific asset better. The combination of maintenance function, Industry 4.0 tools, and advanced statistical solutions to obtain sustainable processes can facilitate organizational change and aid decision-making in equipment management. These solutions seek to reduce interruptions and expenses through the unnecessary utilization of labor and spare parts. All these considerations improve communication and data processing, resulting in improved maintenance of a hydrogen compressor in the petrochemical industry.

Circadian rhythm disruption is increasingly considered an environmental risk factor for the development and exacerbation of inflammatory bowel disease. We have reported in a previous study that nychthemeral dysregulation is associated with an increase in intestinal barrier permeability and inflammation in mice with dextran sulfate sodium (DSS)-induced colitis. To investigate the effect of circadian rhythm disruption on the composition and diversity of the gut microbiota (GM). Sixty male C57BL/6J mice were divided initially to two groups, the shifted group (n=30) exposed to circadian shifts for three months and the non-shifted group (n=30) under a normal light-dark cycle. The mice of the shifted group were cyclically housed for five days under the normal 12:12 hour light-dark cycle followed by another five days under reversed light-dark cycle. At the end of the three months a colitis was induced by 2 % DSS given in the drinking water of 30 mice. Animals were then divided into four groups (n=15 per group), sham group non-shifted (Sham-NS), sham group shifted (Sham-S) and DSS non-shifted (DSS-NS) and DSS shifted (DSS-S). Fecal samples were collected from rectal content to investigate changes in GM composition by DNA extraction followed by high-throughput sequencing of the bacterial 16S rRNA gene. The mouse GM was dominated by three phyla: Firmicutes, Bacteroidetes and Actinobacteria. The Firmicutes/Bacteroidetes ratio decreased in mice with induced colitis. The richness and diversity of the GM were reduced in the colitis group, especially in the group with inverted circadian rhythm. Moreover, GM composition was also modified in the inverted circadian rhythm group, with an increase in Alloprevotella, Turicibacter, Bacteroides and Streptococcus genera. Circadian rhythm inversion exacerbates GM dysbiosis to a less rich and diversified extent in a DSS-induced colitis model. These findings shows a possible interplay between circadian rhythm disruption, GM dynamics, and colitis pathogenesis.

Lung cancer is a prevalent and aggressive neoplasm worldwide, contributing to significant mortality rates. Dehydroepiandrosterone (DHEA) constitutes the bulk of the steroid hormone in human plasma, has a robust antiproliferative effect, and induces cell death in various tumor cells. However, its role in lung cancer cells remains unexplored. This study aimed to investigate the influence of DHEA on the proliferation, viability, autophagy, and migration of several lung cancer cell lines, including A549, HCC827, and NCI-H2347. Cell proliferation was assessed through crystal violet staining; cell number and viability were evaluated using trypan blue staining; viability was confirmed by MTT reduction, a method that is also an indicator of metabolic activity; migration was assessed via a wound healing assay. Autophagy was evaluated using a specific kit, while cell death was determined by annexin-V-FITC/propidium iodide staining and caspase-3/7 activity assay. The results indicate that DHEA significantly reduced proliferation, cell number, metabolic activity, and migration in all examined lung tumor cells. These effects correlate with an increased autophagy induced by DHEA. No signs of apoptosis or necrosis were observed across the range of DHEA concentrations used. Although these findings are preliminary, they suggest that DHEA could hold promise as an alternative treatment option for various subtypes of lung cancer.

The brown seaweed Alaria esculenta is the second most cultivated species in Europe and it is therefore of interest to expand its application in developing food products. In this study, a lactic acid bacteria consortium (LAB consortium) consisting of three Lactiplantabacillus plantarum strains (relative abundance ~ 94%) and a minor amount of a Levilactobacillus brevis strain (relative abundance of ~ 6%) was investigated for its ability to ferment carbohydrates available in brown seaweed. The consortium demonstrated ability in fermenting glucose, mannitol, galactose, mannose, and xylose, of which glucose and mannitol were the most favored substrates; no growth was observed on fucose, mannuronic and guluronic acid. The consortium used different pathways for carbohydrate utilization and produced lactic acid as the main metabolite. In glucose fermentations, only lactic acid was produced, but use of mannitol as carbohydrate source, resulted in co-production of lactic acid, ethanol and succinate. Xylose fermentation resulted in acetate production. The consortium was also able to utilize laminari-oligosaccharides (DP 2-4), obtained after enzymatic hydrolysis of laminarin, and produced lactic acid as metabolite. The consortium could grow directly on A. esculenta, resulting in a pH decrease to 3.8 after 7 days of fermentation. Incubation of the same seaweed at corresponding conditions without inoculation resulted in spoilage of the seaweed by endogenous bacteria.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

Extensive genome structure variation, such as copy number variations (CNVs) and presence/absence variations, is the basis for the remarkable maize genetic diversity; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene, ZmLOX5, leads to increased resistance of maize to herbivory by fall armyworms (FAW). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into the herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either 2, 1 or 0 copies of the Yu796-2×LOX5 locus in the B73 background by six back crosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed enhanced drought tolerance likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into the productive, but susceptible, crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

Hybrid Renewable Energy Systems (HRES) integrate renewable sources, storage, and optionally conventional energies, offering an eco-friendly solution to fossil fuels. Microgrids (MGs) bolster HRES integration, enhancing energy management, resilience, and reliability at various levels. This study, emphasizing the need for refined optimization methods, investigates three themes: renewable energy, microgrid, and multiobjective optimization (MOO), through a bibliometric analysis of 470 Scopus documents from 2010-2023, analyzed with SciMAT software. It segments the research into two periods, 2010-2019 and 2020-2023, revealing a surge in MOO focus, especially in the latter period, with a 35% increase in MOO-related research. This indicates a shift towards com-prehensive energy ecosystem management that balances environmental, technical, and economic elements. The initial focus on MOO, genetic algorithms, and energy management systems has expanded to include smart grids and electric power systems, with MOO remaining a primary theme in the second period. The increased application of Artificial Intelligence (AI) in optimizing HMGS within the MOO framework signals a move towards more sustainable, intelligent energy solutions. Despite progress, challenges remain, including high battery costs, the need for reliable MOO data, the intermittency of renewable energy sources, and HMGS network scalability issues, highlighting directions for future research.

A hallmark of Alzheimer’s disease (AD) are the proteinaceous aggregates formed by the amyloid-beta peptide (Aβ) that is deposited inside the brain as amyloid plaques. The accumulation of aggregated Aβ may initiate or enhance pathologic processes in AD. According to the amyloid hypothesis any agent that has the capability to inhibit Aβ aggregation and/or destroy amyloid plaques represents a potential disease modifying drug. In 2023, a humanized IgG1 monoclonal antibody (lecanemab) against the Aβ soluble protofibrils was approved by US FDA for AD therapy thus providing compelling support to the amyloid hypothesis. To acquire a deeper insight on the in vivo Aβ aggregation, various animal models, including aged herbivores and carnivores, non-human primates, transgenic rodents, fish and worms are widely exploited. This review is based on the recent data obtained using transgenic animal AD models and presents experimental verification of the critical role in Aβ aggregation seeding of the interactions between zinc ions, Aβ with the isomerized Asp7 (isoD7- Aβ) and the α4β2 nicotinic acetylcholine receptor.

Natural fibers are being increasingly used in different areas of engineering, including as composite reinforcement. Among these fibers, carauá stands out for its good mechanical properties and adherence to resin. Nevertheless, little is known about the behavior of this material in the manufacture of a composite or whether classic failure theory can be used in this case. In this context, the present study assesses the mechanical properties of two laminas made of unidirectional curauá fiber with volumetric fiber percentages of 30 % and 22 %, and compares the results with the values obtained for four failure criteria reported in the literature, using analysis of variance (ANOVA). To that end, tensile tests were conducted in the direction of the fiber and at other loading angles, in addition to iosipescu shear tests. The results show that the maximum stress criterion does not represent the failure behavior of these materials and that the best was the Hashin criterion.

Soil-borne Trichoderma spp. have been extensively studied for their biocontrol activities against pathogens and growth promotion ability with plants. However, the beneficial effect of Trichoderma on inducing resistance against insect herbivores has been considered only recently. Among diverse Trichoderma species, consistent with previous reports, we showed that root colonization by T. virens triggered induced systemic resistance (ISR) to leaf-infecting fungal pathogens. Whether T. virens induces ISR to insect pests has not been tested before. In this study, we investigated whether T. virens affects jasmonic acid (JA) biosynthesis and defense against fall armyworm (FAW) and western corn rootworm (WCR). Unexpectedly, the results showed that T. virens colonization of maize seedlings grown in autoclaved soil suppressed wound-induced production of JA, resulting in reduced resistance to FAW. Similarly, the bacterial endophyte Pseudomonas chlororaphis 30-84 suppressed systemic resistance to FAW due to reduced JA. Further comparative analyses of the systemic effects of these endophytes when applied into sterile or non-sterile field soil showed that both T. virens and P. chlororaphis 30-84 triggered ISR against hemibiotrophic fungal pathogen Colletotrichum graminicola in both soil conditions, but only suppressed resistance to FAW in sterile soil. In contrast to the effect on FAW defense, T. virens colonization of maize roots suppressed WCR larvae survival and weight gain. This is the first report suggesting the potential role of T. virens as a biocontrol agent against WCR.

The present work was performed to evaluate the levels of phytochemical constituents and the antioxidant and antibacterial properties of marine red seaweed (Kappaphycus alvarezii) and seagrass (Cymodocea serrulata). Quantitative phytochemical analysis, antioxidant activity and antimicrobial activity against 5 potential pathogenic bacteria was investigated. In both cases were found presence of flavonoids, tannins, phenolic compounds, glycosides, steroids, carbohydrates and ashes. Alkaloids were only found in K. alvarezii, buy not in C. serrulata. The antimicrobial properties of both K. alvarezii and C. serrulata chloroform extracts were found to be antagonis-tically effective against the gram-positive bacterium Bacillus subtilis and the gram-negative bacterium Vibrio parahaemolyticus, Vibrio alginolyticus, Vibrio harveyi and Klebsiella pneu-moniae. GC‒MS analysis revealed the presence of 94 bioactive compounds in K. alvarezii and 104 C. serrulata, including phenol, decane, dodecane, hexadecane, vanillin, heptadecane, diphenyla-mine, benzophenone, octadecanoic acid, dotriaconate, benzene, phytol, butanoic acid, and 2-hydroxyl-ethyl ether, which played a vital role in antioxidant and antibacterial activities. Thus, in view of the results, both K. alvarezii and C. serrulata could be considered as sources of ingre-dients with appreciable nutritional and medicinal value.

The infodiet of young Spanish adults aged 18 to 25 was analysed to determine their attitude towards fake news. The objectives were: to establish whether they have received any training in fake news; to determine whether they know how to identify fake information; and to investigate whether they spread it. The study employed a descriptive quantitative method consisting of a survey of 500 representative interviews of the Spanish population aged between 18 and 25 through a structured questionnaire. The results indicate that they are aware of the importance of training, although generally they do not know of any course and when they do, they do not tend to enrol on one either due to lack of interest or time. These young adults feel that they know how to identify fake content and, moreover, that they know how to do so very well. However, they do not use the best tools. While they do not always verify information, they mainly suspect the credibility of information when it is meaningless. However, they do not tend to spread fake information. We conclude that media information literacy training (MILT) is necessary in educational centres that focuses on the main issues identified.

Climate change-induced temperature fluctuations pose a significant threat to crop production, particularly in the Southern Hemisphere. This study investigates the transcriptome and physiological responses of rapeseed to post-flowering temperature increases, providing valuable insights into the molecular mechanisms underlying rapeseed tolerance to heat stress. Two rapeseed genotypes, Lumen and Solar, were assessed under control and heat stress conditions in field experiments conducted in Valdivia, Chile. Results showed that seed yield and seed number were negatively affected by heat stress, with genotype-specific responses. Lumen exhibited a 9.3% average seed yield reduction, while Solar showed a 28.7% reduction. RNA-seq analysis of siliques and seeds revealed tissue-specific responses to heat stress, with siliques being more sensitive to temperature stress. Hierarchical clustering analysis identified distinct gene clusters reflecting different aspects of heat stress adaptation in siliques, with a role for protein folding in maintaining silique development and seed quality under high temperature conditions. In seeds, three distinct patterns of heat-responsive gene expression were observed, with genes involved in protein folding and response to heat showing genotype-specific expression. Gene coexpression network analysis revealed major modules for rapeseed yield and quality, as well as the trade-off between seed number and seed weight. Overall, this study contributes to understanding the molecular mechanisms underlying rapeseed tolerance to heat stress and can inform crop improvement strategies targeting yield optimization under changing environmental conditions.

Background: In healthy children, the frequency of anomalous persistence of primitive reflexes (PRs) and craniosacral blocks (CBs) are unknown, as well as their impact on neurodevelopment, behaviour disorders and related consequences. We aim to know the prevalence of anomalous PRs and CBs in apparently healthy children and its relationships with behavior and neurodevelopment anomalies. Methods: Participants (n=120) were evaluated through physical examination to detect PRs and CBs, an ad hoc parent survey to collect perinatal events, and children behavior assessment by teachers using Battelle score. Results: PRs were present in 89.5%. Moro (70.8%), cervical asymmetric (78.3%) and cervical symmetric PRs (67.5%) were the most frequent observed PRs. CBs were found in 83.2%, and the most frequent CBs were dura mater (77.5%) and sphenoid bone (70%) blocks. Moro, cervical asymmetric and cervical symmetric active primitive reflexes are significantly associated to cranial blocks of dura mater, parietal zones, and sphenoid bone sway. Gestational disorders or perinatal complications were associated to a higher frequency of PRs and CBs. The presence of PRs and CBs were associated with abnormal Battelle scores and neurobehavioral problems. Conclusion: Presence of PRs and CBs in children without diagnosed diseases are frequent and related with disturbances in childhood neurodevelopment.

Background In this study we investigated in detail the role of cannabidiol (CBD), Beta-caryophyllene (BC), or their combinations in diabetic peripheral neuropathy (DN). The key factors that contribute to DN include mitochondrial dysfunction, inflammation, and oxidative stress. Methods Briefly, Streptozotocin (STZ) (55 mg/kg) was injected intraperitoneally to induce DN in Sprague Dawley rats and performed procedures including Randall Sellito Calipers, Von Frey Aesthesiometer, hot plate, and cold plate methods to determine mechanical and thermal hyperalgesia in vivo. The blood flow to the nerves was assessed by using the Laser Doppler device. Schwann cells were exposed to high glucose (HG) at a dose of 30 mM to induce hyperglycemia and DCFDA, JC1 & Mitosox staining were done to determine mitochondrial membrane potential, reactive oxygen species and mitochondrial superoxides in-vitro. The rats were administered i.p with BC (30mg/kg), CBD (15mg/kg), or combination while Schwann cells were treated with 3.65 µM CBD, 75 µM BC, or combination to assess their role in DN amelioration. Results Our results revealed that exposure to BC and CBD diminished HG-induced hyperglycemia in Schwann cells, in part, through reducing mitochondrial membrane potential, reactive oxygen species and mitochondrial superoxides. Further, BC and CBD combination treatment in-vivo could prevent the deterioration of mitochondrial quality control system by promoting autophagy and mitochondrial biogenesis while improving blood flow. CBD and BC treatments also reduced pain hypersensitivity to hyperalgesia and allodynia with increased antioxidant and anti-inflammatory action in diabetic rats. These in vivo effects were attributed to significant upregulation of AMPK, SIRT3, Nrf2, PINK1, PARKIN, LC3B, Beclin1 and TFAM functions while downregulation of NLRP3 inflammasome, NFκB, COX2 and p62 activity was noted as determined by western blotting. Conclusion the present studies demonstrated that STZ & HG induced oxidative and nitrosative stress play a crucial role in the pathogenesis of diabetic neuropathy. We find, for the first time, that CBD and BC combination ameliorate DN via modulating the mitochondrial quality control system.

Background: Multiple system atrophy (MSA) is a rapidly progressive neurodegenerative disorder that has no curative treatment. Diagnosis is based on a set of criteria established by Gilman (1998 and 2008) and recently updated by Wenning (2022). We aim to determine the effectiveness of [123I]Ioflupane SPECT in MSA, especially at the initial clinical suspicion. Methods: Cross-sectional study of patients at initial clinical suspicion of MSA, referred for [123I]Ioflupane SPECT. Results: 139 patients (68 men, 71 women) were included, 104 being MSA-probable and 35 MSA-possible. MRI was normal in 89.2% while SPECT was positive in 78.45%. SPECT showed high sensitivity (82.46%) and positive predictive value (86.24), reaching maximum sensitivity in MSA-P (97.26%). Significant differences were found when relating both SPECT assessments in the healthy-sick and inconclusive-sick groups. We also found an association when relating SPECT to the subtype (MSA-C or MSA-P), as well as to the presence of parkinsonian symptoms. Lateralization of striatal involvement was detected (left side). Conclusions: [123I]Ioflupane SPECT is a useful and reliable tool for diagnosing MSA, with good effectiveness and accuracy. Qualitative assessment shows a clear superiority when distinguishing between the healthy-sick categories, as well as between the parkinsonian (MSA-P) and cerebellar (MSA-C) subtypes at initial clinical suspicion.

The varved sediments of the Pyrenean Lake Montcortès (Pallars Sobirà, Lleida) embody a unique continuous high-resolution (annual) paleoarchive of the last 3000 years for the circum-Mediterranean region. A variety of paleoclimatic and paleoecological records have been retrieved from these uncommon sediments that have turned the lake into a regional reference. Present-day geographical, geological, ecological and limnological features of the lake and its surroundings are reasonably well known but the lack of a local weather station has prevented characterization of current climate, which is important to develop modern-analog studies for paleoclimatic reconstruction and to forecast the potential impacts of future global warming. Here, the local climate of the Montcortès area for the period 1955-2020 is characterized using a network of nearby stations situated along an elevational transect in the same river basin of the lake. The finding of statistically significant elevational gradients for annual and monthly average temperature and precipitation has enabled to estimate these parameters and their seasonal regime for the lake site. A representative climograph has been shaped with these data that can serve as a synthetic descriptive and comparative climatic tool. The same analysis has provided climatic data for modern-analog studies useful to improve the interpretation of sedimentary records in climatic and ecological terms. In addition, the seasonal slope shifting of the climatic elevational gradients has been useful to gain insights about possible future climatic trends under a warming scenario.

The new digital infrastructure has become an important basis for the green development of agriculture. This paper selects provincial sample data from 2006 to 2022, constructs an indicator system to measure new digital infrastructure and agricultural green total factor productivity, and explores how new digital infrastructure can promote agricultural green development. The results show that: (1) the new digital infrastructure has a significant role in promoting the green development of agriculture, and this conclusion is still valid after processing endogeneity and heteroscedasticity; (2) Technology and land factors play an intermediary role in the promotion of green agricultural development by the new digital infrastructure, that is, the new digital infrastructure helps to improve the quality and technical level of cultivated land and thus promote green agricultural development; (3) Labor force factors optimize the mediating role of technology factors, that is, the higher the quality of labor force, the stronger the role of the new digital infrastructure in promoting the green development of agriculture through the technological path; (4) The effect of new digital infrastructure on the green development of agriculture is obviously heterogeneous, and the effect is more obvious in northwest China and the regions with lower marketization level, higher environmental regulation level. This study is helpful to clarify the relationship between new digital infrastructure and agricultural green development in China, and provide corresponding policy suggestions for promoting regional agricultural green development.

Important policy developments in dementia and palliative care in nursing homes between 2010 and 2015 in Flanders, Belgium might have influenced which people die in nursing homes and how they die. We aimed to examine differences between 2010 and 2015 in the prevalence and characteristics of residents with dementia in nursing homes in Flanders, and their palliative care service use and comfort in the last week of life. We used two retrospective epidemiological studies, including 198 residents in 2010 and 183 in 2015, who died with dementia in representative samples of nursing homes in Flanders. We found a 23%-point increase in dementia prevalence (P-value<0.001), with a total of 11%-point decrease in severe to very severe cognitive impairment (P=0.04). Controlling for this difference in resident characteristics, in the last week of life, there were increases in the use of pain assessment (+20%-point; P<0.001) and assistance with eating and drinking (+10%-point; P=0.02) but no change in total comfort. The higher prevalence of dementia in nursing homes with no improvement in residents’ total comfort while dying emphasize an urgent need to better support nursing homes in improving their capacities to provide timely and high-quality palliative care services to more residents dying with dementia.

The search for new antibacterial agents that could decrease bacterial resistance is a subject that is continuously developing. The Gram-negative and Gram-positive bacteria have a metalloproteins group belonging to the M4 family. That is the main virulence factor of these bacteria. In this work, we have used a computational protocol based on the comprehensive analysis of the results of docking, molecular dynamics simulation, MM-PBSA, ligand efficiency, and ADME-Tox properties of ligand designed in silico in the previous manuscript using the Thermolysin from Bacillus thermoproteolyticus, a metalloprotein of the M4 family as a target. The principal results obtained were the designed ligands were adequately oriented in the thermolysin active center. The Lig783, Lig2177, and Lig3444 compounds were those with better dynamic behavior, however, when analyzing the results extracted from the ADME-Tox properties, only Lig783 was the best antibacterial agent candidate.

The combination of interstitial hyperthermia treatment (IHT) with high dose rate brachytherapy (HDR-BT) for prostate cancer treatment and has the potential to improve clinical outcome, since it highly enhances the efficiency of cell kill, especially when applied simultaneously. Therefore, we have developed the ThermoBrachy applicators. To effectively apply optimal targeted IHT, treatment planning is considered essential. However, treatment planning in IHT is rarely applied since it is regarded difficult to accurately calculate the deposited energy in the tissue in a short enough time for clinical practice. In this study, we investigated various time-efficient methods for fast computation of the electromagnetic (EM) energy deposition resulting from the ThermoBrachy applicators. Initially, we investigated the use of an electro-quasistatic solver. Next, we extended our investigation to the application of geometric simplifications. Furthermore, we investigated the validity of the superpositioning principle, which can enable adaptive treatment plan optimization without the need for continuous recomputation of the EM field. Finally, we evaluated the accuracy of the methods by comparing them to the golden standard Finite-Difference Time-Domain calculation method using gamma-index analysis. The simplifications considerably reduced the computation time needed, improving from &gt;12 h to a few seconds. All investigated methods showed excellent agreement with the golden standard by showing a &gt;99% passing rate with 1%/0.5 mm Dose Difference and Distance-to-Agreement criteria. These results allow the proposed electromagnetic simulation method to be used for fast and accurate adaptive treatment planning.