Anthocyanins are among the best-known phenolic compounds and possess remarkable biological activities, including antioxidant, anti-inflammatory, anticancer, and antidiabetic effects. Despite their therapeutic benefits, they are not widely used as health-promoting agents due to their insta-bility, low absorption, and thus, low bioavailability and rapid metabolism in the human body. Recent research suggests that the application of nanotechnology could increase their solubility and/or bioavailability, and thus, their biological potential. Therefore, in this review, we decided to provide, for the first time, a comprehensive overview of in vitro and in vivo studies on nanocarriers used as delivery systems of anthocyanins, and their aglycones, i.e., anthocyanidins alone or com-bined with conventional drugs to the treatment or management of chronic diseases.

In this paper we investigate in different scenarios the feasibility of using massive multiple-input multiple-output (mMIMO) with Reconfigurable Intelligent Surfaces (RISs) to boost the throughput and coverage performances with high energy efficiency, considering sub-6 GHz, mmWave and THz bands. With that objective, a centralized radio access network (C-RAN) suitable for beyond fifth generation (B5G) systems is considered, where we integrate the base stations (BSs) with multiple RISs and devices or user equipment. RISs with a large number of quasi-passive reflecting elements constitute a low-cost approach capable of shaping the radio wave propagation and improve wireless connectivity. We consider a scenario where multiple RISs are combined with mMIMO in the uplink in order to provide connectivity to Smart City (thousands of active low power devices) wirelessly, in the 3.6GHz and 28GHz bands. We also address a scenario where RISs are adopted with mMIMO in the downlink so as to offer connectivity to a Stadium with Pitch, (thousands of active user equipment) in the 28GHz band. Finally, we have also studied the connectivity at 100GHz of a Factory where several RIS panels replacing most of the BSs equipped with mMIMO assure improved throughput and coverage. We concluded that RISs are capable of improving the performance in any of these analyzed scenarios at the different frequency bands, justifying that they are a key enabling technology for 6G.

Composite biomaterials that combine osteoconductive and osteoinductive properties are a promising approach for bone tissue engineering (BTE) since it allows osteogenesis stimulation while mimicking the extracellular matrix (ECM) morphology. In this context, the aim of the present research work was to produce polyvinylpyrrolidone (PVP) nanofibers containing mesoporous bioactive glass (MBG) 80S15 nanoparticles. These composite materials were produced by electrospinning technique. The design of experiments (DOE) was used to estimate the optimal electrospinning parameters to reduce average fiber diameter. The polymeric matrices were thermally crosslinked under different conditions, and the fiber’s morphology was studied using scanning electron microscopy (SEM). Evaluation of the mechanical properties of nanofibrous mats revealed a dependence on thermal crosslinking parameters and on the presence of MBG 80S15 particles inside the polymeric fibers. Degradation tests indicated that the presence of MBG led to a faster degradation of nanofibrous mats. On the other hand, MBG presence also leads to higher swelling capacity. The assessment of in vitro bioactivity in simulated body fluid (SBF) was performed in MBG pellets and PVP/MBG (1:1) composites to assess whether the bioactive properties of MBG 80S15 were kept when it was incorporated into PVP nanofibers. FTIR and XRD analysis along with SEM–EDS results indicated that a hydroxy-carbonate apatite (HCA) layer was formed on the surface of MBG pellets and nanofibrous webs after soaking in SBF over different time periods. In general, the materials revealed no cytotoxic effects on Saos-2 cell line. The overall results for the produced materials show the potential of the composites to be used in BTE.

This paper discusses the use of networks of Inertial Measurement Units (IMU) for the reconstruction of trajectories from sensor data. Logistics is a natural application domain, to verify the quality of the handling of goods. This is a mass application and the economics of logistics impose that IMUs to be used must be low cost and use basic computational devices. The approach in the paper converts a strategy from the literature, used in the multi-target following problem, to reaching a consensus in a network of IMUs. The paper presents results on how to achieve the consensus in trajectory reconstruction, along with covariance intersection data fusion of the information obtained by all nodes in the network.

In this work, we present a model of the atom that is based on a nonclassical logic called paraconsistent logic (PL), which has the main property of accepting the contradiction in logical interpretations without the conclusions being annulled. The proposed model is constructed with an extension of PL called paraconsistent annotated logic with annotation of two values (PAL2v), which is associated with an interlaced bilattice of four vertices. We use the logarithmic function of the Shannon entropy H_(s) to construct the paraconsistent equations and thus adapt a probabilistic model for representations in quantum physics. Through analyses of the interlaced bilattice, comparative values are obtained for some of the phenomena and effects of quantum mechanics, such as superposition of states, quantum entanglement, wave functions, and equations that determine the energy levels of the layers of an atom. At the end of this article, we use the hydrogen atom as a basis of the representation of the PAL2v model, where the values of the energy levels in six orbital layers are obtained. As an example, we present a possible method of applying the PAL2v model to the use of Raman spectroscopy signals in the detection of lubricating mineral oil quality.

Because most of the recognized causes of superior gluteal nerve (SGN) injury are iatrogenic, detailed knowledge of the anatomy of the SGN is crucial to prevent its injury associated with surgical procedures. This study aims to describe the precise location of SGN or its branches at the greater sciatic foramen, measure the distances of these nervous structures to palpable bony landmarks, and evaluate the possible correlation between these parameters and pelvis size. Twenty human cadaveric hemipelvises were studied. After dissection to expose the SGN or its branches at the greater sciatic foramen, the distances from these nervous structures to the greater trochanter (GT), to the anterior superior iliac spine (ASIS), to the posterior superior iliac spine (PSIS), to the ischial tuberosity (IT), and to the greater sciatic notch were measured. We found that at the greater sciatic foramen the SGN emerges as a common trunk in 75% of hemipelvises, and already divided in its superior and inferior branches in 25% of hemipelvises. When the SGN exits the pelvis as a common trunk, it does so, in most cases, in contact with the bone at the apex of the greater sciatic notch or superior to it. The median distance from the SGN at the greater sciatic notch to the PSIS, ASIS, GT and IT is 7.6 cm, 10.9 cm, 7.5 cm and 10.8 cm, respectively. We found a positive correlation between some of the analyzed parameters and the size of the pelvis. The anatomical data of this study may serve as pivotal guides during orthopedic pelvic surgery, contributing to minimize SNG iatrogenic lesions with significant implications in the patient's quality of life.

In the present paper four passive micromixers designs (G1, G2, G3 and G4) inspired on distillation columns trays were proposed. The devices performance was assessed by numerical simulations. The mixing performance was investigated for a Reynolds number range from 0.01 to 100 and channel height of 200 µm, 500 µm and 1000 µm for oil/ethanol flow. G1 and G4 designs provided high mixing index (> 0.975). The G1 device achieved superior mixing performance with a moderate pressure drop (about 0.5 MPa) due to the induced flow recirculation pattern for a relative high flow rate of 0.21 L/min, highlighting the potential use of such microdevice for scale-up and numbering-up of microdevices in modular chemical plant processing.

Commercial classification is essential to spatially describe commerce. Although most of the proposed classifications have been classic functional analyses, rooted on qualitative studies, some recent classifications efforts are found to rely heavily on more quantitative methods, due eventually to increasing data availability and technological advancements. In this paper, a classification is proposed, using k-means clustering and a minimal set of variables (density, diversity and clustering) to derive the commercial structure of Lisbon. The classification is implemented for 1995, 2002 and 2010, using a 150m-sided square grid. The cross-sectional analysis of the results shows the rise of shopping-malls against city centre decline and gentrification, along with changes in cluster composition considering 9 different commercial categories (6 categories of retail, and restaurants, cafes and bars). These findings are in line with literature, thus supporting the obtained classification. Since the classification can be used to accurately describe the commercial structure of the city in different time periods, it is implied that it may also be generalized to different cities. Furthermore, the potential use of cluster membership in retail location models, which is an advantage of the proposed classification, could help strengthen the relationship between location modelling and commercial classification, thus reinforcing the role of commercial studies in urban planning and policymaking.

Biocomposite membranes based on polylactic acid (PLA) and cellulose nanocrystals (CNCs) were developed using a scientific approach. Dicumyl peroxide (DCP) was used as a polymerization ini-tiator, while tin octoate (Sn(Oct)2) and triphenylphosphane (P(C6H5)3) were used as catalysts. A torque rheometer was used to mix the components of the biocomposite, and thin films was prepared by solvent casting. Fourier transform infrared (FTIR) spectroscopy confirmed the coupling between the PLA and CNCs. Field emission scanning electron microscopy (FESEM) showed that the CNCs were well-dispersed in the PLA matrix with an unimodal particle size distribution and a maximum particle size of around 200 nm. Thermogravimetric analysis (TGA) and differential scanning calo-rimetry (DSC) analysis demonstrated good thermal stability and improved biodegradability of the biocomposite membrane compared to pure PLA. Mechanical characterization showed a Young's modulus of 1.65 GPa, which is comparable to that of other composite materials, and a maximum tensile strength of 20.31 MPa, which is higher than that of pure PLA. These results suggest that the developed biocomposite membrane has potential applications in water filtration, food packaging, and biomedical devices.

The development of electric aircrafts is becoming an important technology for achieving the goals set by the European Commission for the reduction of gases emissions by 2050 in the aeronautical transportation system. However, there is a gap between the values of specific power in commercial electric machines and the ones required for aeronautical applications. Therefore, the search for alternative materials and non-conventional designs is mandatory. One emergent solution is using superconducting machines and systems to overcome the current limits of conventional electrical machines. This work reviews the new hybrid and all-electric aircraft tendencies, complementing it with recent research on the design and development of high specific power superconducting machines. This includes the main topologies for hybrid and all-electric aircraft, with an overview of the ongoing worldwide projects of these types of aircrafts, systematizing the main characteristics of their propulsion systems. It also includes the research on superconducting machines for the purpose of high specific power, considering the impact on the redesign of aircraft systems in the electrical, cooling, and fuel source sense.

Natural polysaccharides, which are described in this study, are some of the most extensively used biopolymers in food, pharmaceutical and medical applications, because they are renewable and have a high level of biocompatibility and biodegradability. The fundamental understanding required to properly exploit polysaccharides potential in the biocomposite, nanoconjugate, and pharmaceutical industries is depended on detailed research of these molecules. Polysaccharides are preferred over other polymers because of their biocompatibility, bioactivity, homogeneity, and bioadhesive. Natural polysaccharides have also been discovered to have excellent rheological and biomucoadhesive properties, which may be used to design and create a variety of useful and cost-effective drug delivery systems. Polysaccharide-based composites derived from natural sources have been widely exploited due to their multifunctional properties, particularly in drug delivery systems and biomedical applications. These materials have achieved global attention and are in great demand because to their biochemical properties, which mimic both human and animal cells. Although synthetic polymers account for a substantial amount of organic chemistry, natural polymers play a vital role in a range of industries, including biomedical, pharmaceutical, and construction. As a consequence, the current study will provide information on natural polymers, their biological uses, food and pharmaceutical applications.Keywords: Polymers Biopolymers, Excipient, Natural source, Food and Pharmaceutical applications.

Skin pigmentation ensures efficient photoprotection and relies on the pigment melanin, which is produced by epidermal melanocytes and transferred to surrounding keratinocytes. While the molecular mechanisms of melanin synthesis and transport in melanocytes are now well characterized, much less is known about melanin transfer and processing within keratinocytes. Over the past few decades, distinct models have been proposed to explain how melanin transfer occurs at the cellular and molecular levels. However, this remains a debated topic as up to four different models have been proposed, with evidence presented supporting each. Here, we review the current knowledge on the regulation of melanin exocytosis, internalization, processing and polarization. Regarding the different transfer models, we discuss how these might co-exist to regulate skin pigmentation under different conditions, i.e. constitutive and facultative skin pigmentation or physiological and pathological conditions. Moreover, we discuss recent evidence that sheds light on the regulation of melanin exocytosis by melanocytes and internalization by keratinocytes, as well as how melanin is stored within these cells in a compartment that we proposed to be named melanokerasome. Finally, we review the state of the art on the molecular mechanisms that lead to melanokerasome positioning above the nuclei of keratinocytes, forming supranuclear caps that shield the nuclear DNA from UV radiation. Thus, we provide a comprehensive overview of the current knowledge on the molecular mechanisms regulating skin pigmentation, from melanin exocytosis by melanocytes and internalization by keratinocytes, to processing and polarization within keratinocytes. A better knowledge of these molecular mechanisms will clarify long lasting questions in the field that are crucial for the understanding of skin pigmentation and can shed light on fundamental aspects of organelle biology. Ultimately, this knowledge can lead to novel therapeutic strategies to treat hypo- or hyper-pigmentation disorders, which have a high socio-economic burden to patients and healthcare systems worldwide, as well as having cosmetic applications.

In this paper, we introduce the application of Type-I fuzzy inference systems (FIS) as an alternative to improve the prioritization in the FMECA analysis applied in cyber-power grids. Classical FMECA assesses the risk level through the Risk Priority Number (RPN). The multiplication between three integer numbers computes this, called risk factors, representing the severity, occurrence, and detectability of each failure mode and are defined by a team of experts. The RPN does not consider any relative importance between the risk factors and may not necessarily represent the real risk perception of the FMECA team members, usually expressed by natural language; this is the main FMECA shortcoming criticized in the literature. Our approach considers fuzzy variables defined by FMECA experts to represent the uncertainty associated with the human language and a rule base consisting of 125 fuzzy rules to represent the risk perception of the experts. To test our approach, we select a cyber-power grid previously analyzed by the authors using the classical FMECA. The results reveal our proposed fuzzy approach as promissory to represent the uncertainty associated with expert knowledge and to perform an accurate prioritization of failure modes in the context of electrical power systems.

This paper proposes a method based on genetic algorithm (GA) for the security-constrained optimal dispatch of integrated natural gas and electricity networks, considering operating scenarios in both energy systems. The mathematical formulation of the optimization problem consists of a multi-objective function which aims to minimize both cost of thermal generation (diesel and natural gas) as well as the production and transportation of natural gas. The joint gas-electricity system is modeled by two separate groups of nonlinear equation, which are solved by the combination of Newton's method with the GA. The applicability of the proposed method is tested in the Belgian gas network integrated with the IEEE 14-bus test system and a 15-node natural gas network integrated with the IEEE 118-bus test system. The results demonstrate that the proposed method provides efficient and secure solutions for different operating scenarios in both energy systems.

Rocky Mountain or Brazilian spotted fever, caused by Ricketsia ricketssi, is a fulminant, seasonal, and neglected disease that occurs in focal points of North America and South America. Rapid detection are essential for a better prognosis and survival rate of the infected individual. However, disease diagnosis still faces challenges as the accuracy of many of the available laboratory tests fluctuates. Therefore, this review aimed to identify methods for antibody or antigen detection, its gaps, and evolution over time. A search was conducted to find all studies in the Pubmed database that described antibody or antigen detection for Ricketsia ricketsii infection. Initially, a total of 403 articles were screened. Of these articles, only 19 fulfilled the pre-established inclusion criteria and were selected. Among the different methods applied, the IFA technique was the one most frequently found in the studies. However, it presented varied results such as low specificity using the indirect method. Other techniques, such as ELISA and immunohistochemistry, were also found, although in smaller numbers and with their own limitations. Although some studies showed promising results, there is a pressing need to find new techniques to develop a rapid and effective Ricketsia ricketssi infection diagnosis.

Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. The results show that the strategies derived from the general heuristic are very interesting, all of them deploying roadside units in a circle pattern around the traffic epicenter.

Graphene is a two-dimensional nanostructured material with intrinsic properties that show promising performance in various applications, including electronics, renewable energy, medicine, mechanical enforcement and others. This study reports a bottom-up approach for the conversion of cyclohexane into graphene nanoflakes, which were then deposited onto fiberglass using a non-thermal generator. The composite was characterized using transmission electron microscopy, which revealed the formation of stacked few-layer graphene with a partially disordered structure and a d-spacing of 0.358 nm between the layers. X-ray diffraction confirmed the observations from the TEM images. SEM images showed the agglomeration of carbonaceous material onto the fiberglass, which experienced some delamination due to the synthesis method. Raman spectroscopy indicated that the obtained graphene exhibited a predominance of defects in its structure. Additionally, Atomic Force Microscopy (AFM) analyses revealed the formation of graphene layers with varying levels of porosity.

In the framework of the FireStorm project, four portable weather stations were installed in the Lousã/Estrela mountain range. Given that the Portuguese Institute for Sea and Atmosphere’s sur-face network has two weather stations installed in this region, the new data allows an improved monitoring of the vertical variability of near-surface variables in this mountainous region. As most of the wildfires in mainland Portugal affect areas with complex terrain with elevations below 1200 m and major fires continue to burn overnight, it is also relevant to monitor the vertical changes of meteorological variables in the nighttime period, as these may exhibit large variability. This study provides the first assessment of the available data, with focus on the summer seasons of 2021 and 2022. The results highlight the large variability that was observed in the region and suggest that the risk of extreme fire behaviour in the nighttime period may be underestimated.

In the present study, a numerical model was developed to predict the flow pattern inside a broiler building. The model intends to predict the velocities fields inside the domain and ammonia (NH3) emitted or released by litter from poultry housing. The numerical model developed in Computational Fluid Dynamics (CFD) commercial code, intends to represent a commercial broiler building, and intends to simulate the 3D and heat transfer, in steady state flow. The evaporative cooling pads were also included in the model. The validation of the model was based in experimental measurements obtained in previous studies. The simulations were focused on Summer, Winter and also Mid-Season situation. The numerical results of NH3 concentration were compared with the experimental measurements, and a quite good agreement was verified. The numerical results allowed the characterization of: the inside flow pattern developed for the summer and winter situation; the inside NH3 distribution, and the velocity field distribution inside the broiler building. It was found that NH3 concentration increases along the tunnel, especially in low flow rate imposed from the exhaust fan. Also, it was verified that the low velocities inside domain are no sufficient to remove the gaseous pollutants.

Little is known about how recreational triathletes prepare for an Olympic distance event. The aim of this study was to identify the training characteristics of recreational-level triathletes within the competition period and assess how their preparation for a triathlon influences their health and their levels of fatigue. During the 6 weeks prior to an Olympic distance triathlon, and the 2 weeks after, 9 recreational athletes (5 males, 4 females) completed a daily training log. Participants answered the Daily Analysis of Life Demands Questionnaire (DALDA), the Training Distress Scale (TDS), and the Alberta Swim Fatigue and Health Questionnaire weekly. The Recovery-Stress Questionnaire (REST-Q) was completed at the beginning of the study, on the day before the competition, and at the end of week 8. Training loads were calculated using session-based rating of perceived exertion (sRPE). The data from every week of training was compared to week 1 to determine how athletes’ training and health changed throughout the study. No changes in training loads, duration, or training intensity distribution were seen in the weeks leading up to the competition. Training duration was significantly reduced in week 6 (p=0.041, d = 1.58, 95% CI = 6.9, 421.9), while the number of sessions was reduced in week 6 (Z=2.32, p=0.02, ES = 0.88) and week 7 (Z = 2.31, p=0.02, ES = 0.87). Training was characterized by large weekly variations in training loads and a high training intensity. No significant changes were seen in the DALDA, TDS, or REST-Q questionnaire scores throughout the 8 weeks. Despite large spikes in training load and a high overall training intensity, these recreational-level triathletes were able to maintain their health in the 6 weeks of training prior an Olympic distance triathlon.

The separator membrane is an essential component of lithium-ion batteries, separating the anode and cathode and controlling the number and mobility of the lithium ions. Among the polymer matrices most investigated for battery separators are poly(vinylidene fluoride) (PVDF) and its copolymers poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE), poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), and poly(vinylidene fluoride-cochlorotrifluoroethylene) (PVDF-CTFE), due to their excellent properties such as high polarity and the possibility of controlling the porosity of the materials through binary and ternary polymer/solvent systems, among others. This review presents the recent advances on battery separators based on poly(vinylidene fluoride) (PVDF) and its copolymers for lithium-ion batteries. It is divided in the following sections: single polymer and co-polymers, surface modification, composites and polymer blends. Further, a critical comparison between those membranes and other separator membranes is presented, as well as the future trends on this area.

With the rising trends in elderly populations around the world, there is a growing interest in understanding how climate sensitivity is related to their thermal perception. Therefore, we analyzed the associations between mortality in the elderly due to cardiovascular (CVD) and respiratory diseases (RD) and meteorological variables, for three cities in the State of São Paulo, Brazil: Campos do Jordão, Ribeirão Preto and Santos, from 1996 to 2017. We applied the Autoregressive Model Integrated with Moving Average (ARIMA) and the Principal Component Analysis (PCA) in order to evaluate statistical associations. Results showed CVD as a major cause of mortality, particularly in the cold period, when a high mortality rate is also observed due to RD. The mortality rate was higher in Campos do Jordão and lower in Santos (and intermediate values in Ribeirão Preto). Campos do Jordão results indicate an increased probability of mortality from CVD and RD due to lower temperatures. In Ribeirão Preto, the lower relative humidity may be related to the increase in CVD and RD deaths. This study emphasizes that, even among subtropical climates, there are significant differences. Therefore, this can assist decision makers in the implementation of mitigating and adaptive measures.

Increased sugar intake is implicated in Type-2 diabetes and fatty liver disease. Mechanisms by which glucose and fructose components promote these conditions are unclear. We hypothesize that alterations in intestinal metabolite and microbiota profiles specific to each monosaccharide are involved. Two groups of six adult C57BL/6 mice were fed for 10-weeks with a diet where either glucose or fructose was the sole carbohydrate component (G and F, respectively). A third group was fed with normal chow (N). Fecal metabolites were profiled every 2-weeks by ¹H NMR and microbial composition was analysed by real-time PCR (qPCR). Glucose tolerance was also periodically assessed. N, G and F mice had similar weight gains and glucose tolerance. Multivariate analysis of NMR profiles indicated that F mice were separated from both N and G, with decreased butyrate and glutamate and increased fructose, succinate, taurine, tyrosine and xylose. Compared to N and G, F mice showed a shift in microbe populations from gram-positive Lactobacillus spp. to gram-negative Enterobacteria species. Substitution of normal chow carbohydrate mixture by either pure glucose or fructose for 10 weeks did not alter adiposity or glucose tolerance. However, F G and N mice generated distinctive fecal metabolite signatures with incomplete fructose absorption as a dominant feature of F mice.

This review focus on a critical analysis of nanocatalysts for Advanced Reductive Processes (ARP) and Oxidation Processes (AOP) designed for the degradation of poly/perfluoroalkyl substances (PFAS) in water. Ozone, ultraviolet and photocatalyzed ARP and/or AOP will be the basic treatment technologies. Besides the review of the nanomaterials with greater potential as catalyst for advanced processes of PFAS in water, the perspectives for its future development considering sustainability considerations will be discussed. Moreover, a brief analysis of the current state of the art of the ARP and AOP for the treatment of PFAS in water will be presented.

Tabebuia aurea (Silva Manso) Benth. & Hook. f. The ex S.Moore (yellow ipe), belonging to the Bignoniaceae family, used in the popular for fever, inflammation and healing of skin wounds. The extract was prepared by maceration, using 70% ethanol. Through HPLC analysis, it was possible to identify substances, mainly phenolic, such as lapachol, present in Bignoniaceae. The phenolic content was 21.36 mg / Eag in the antioxidant activity, the effective concentration of 50% was 53.03 ± 1.14 µg / mL. The antimicrobial activity against S.aureus, E. coli and C. albicans was evaluated by microdilution in broth, which verified action against the tested microorganisms. Cell viability has been inhibited for tumor cells, although this has not been observed for normal cells. The LD50 against A.aegypti mosquito larvae was 3504.6 mg / L and there was no mortality in the concentration tested for the snail B.glabrata. Nontoxic or low toxicity for A. salina and T. molitor, respectively, and did not exhibit hemolytic action at concentrations of antibacterial effect. Given the above, it was concluded that the bark extract of the studied species has bioprospecting potential for the future development of antimicrobial products.

In the context of Shared Autonomous Vehicles, the need to monitor the environment inside the car will be crucial. This article focuses on the application of deep learning algorithms to detect objects, namely lost/forgotten items to inform the passengers, and aggressive items to monitoring if violent actions may arise between passengers. For object detection algorithms was used public datasets (COCO and TAO) to train state-of-the-art algorithms, such as YOLOv5. For violent action detection was used the MoLa InCar dataset to train on state-of-the-art algorithms such as I3D, R(2+1)D, SlowFast, TSN and TSM. At the end an embedded automotive solution was used to demonstrate both methods running in real-time.

Biomass-derived carbon dots (CDs) are gaining much interest in recent times as it is a sustainable option with abundant availability, low cost, and tunable luminescence. Herein, we report a simple green synthesis method to produce highly fluorescent CDs from Eucalyptus globulus leaves using the one-pot hydrothermal approach. The fabricated CDs exhibit strong blue fluorescence with an excitation and emission maxima of 340 nm and 442 nm respectively. The highest quantum yield (QY) obtained was 60.7%. Due to its promising optical properties and biocompatibility, CDs can be a potential candidate for biosensing applications. Moreover, we employed a life cycle assessment (LCA) cradle-to-gate approach to study the environmental impacts of the synthesis strategy used for the fabrication of CDs. The results point out that citric acid is a main hotspot in CDs synthesis, regarding environmental impacts in most categories. This justifies the introduction of biomass, which reduces the amount of citric acid, thus leading to a more sustainable synthesis strategy for fabricating CDs.

Lightning discharges in electric power networks generate voltage and current surges that are propagated through the electrical network causing damage and shutdowns in the electrical system. To protect the system against these phenomena, surge arresters are very effective and widely used by electrical utilities in their electric grids. This paper presents a methodology for optimized surge arrester allocation based on genetic algorithm (GA), creating a simulation environment in the software ATP (Alternative Transients Program) to implement the proposed methodology. The optimized allocation procedure is based on a fitness function that minimizes the cost of surge arresters and maximizes the number of protected equipment. To carry out this optimized arrester allocation procedure using ATP may demand too much processing time when running large distribution grids. To overcome this difficulty a procedure is proposed to obtain an overvoltage severity description of the grid and select the most critical electric nodes for the incidence of lightning discharges, in the GA allocation procedure. The case study is applied to the IEEE 123-bus electrical feeder to demonstrate the effectiveness of the proposed methodology.

The study of velocimetry is important for characterizing and comprehending the effects of fluid flow, and the Particle Image Velocimetry (PIV) technique is one of the primary approaches for understanding the velocity vector field in a test section. Commercial PIV systems are expensive, with one of the main cost factors being high-speed camera equipment capable of capturing images at high frames per second (fps), rendering them impractical for many applications. This study proposes an evaluation of utilizing smartphones as image acquisition systems for PIV technique application. An experimental setup inspired by the known angular displacement of synthetic particles is proposed. A stepper motor rotates a plate containing an image of synthetic particles on its surface. The motion of the plate is captured by the smartphone camera, and the images are processed using PIVlab-MatLab® software. The use of two smartphones is assessed, with acquisition rates of either 240 fps or 960 fps and varying angular velocities. The results were satisfactory for velocities up to 0.7 m/s at an acquisition rate of 240 fps and up to 1.8 m/s at 960 fps, validating the use of smartphones as a cost-effective alternative for the PIV technique.

Genetic Programming (GP) is a powerful Machine Learning (ML) algorithm that can produce readable white-box models. Although successfully used for solving an array of problems in different scientific areas, GP is still not well known in Remote Sensing. The M3GP algorithm, a variant of the standard GP algorithm, performs Feature Construction by evolving hyper-features from the original ones. In this work, we use the M3GP algorithm on several sets of satellite images over different countries to create hyper-feature from satellite bands to improve the classification of land cover types. We add the evolved hyper-features to the reference datasets and observe a significant improvement of the performance of three state-of-the-art ML algorithms (Decision Trees, Random Forests and XGBoost) on multiclass classifications and no significant effect on the binary classifications. We show that adding the M3GP hyper-features to the reference datasets brings better results than adding the well-known spectral indices NDVI, NDWI and NBR. We also compare the performance of the M3GP hyper-features in the binary classification problems with those created by other Feature Construction methods like FFX and EFS.

Biological invasions represent a threat to ecosystems, through competition and habitat destruction, which may result in significant changes of the invaded community. Asparagopsis armata is a red macroalgae (Rodophyta) globally recognized as an invasive species. It is found from the intertidal to shallow subtidal areas, on rock or epiphytic, forming natural vegetation belts on exposed coasts. This study evaluated the variations on native intertidal seaweed and macroinvertebrate assemblages inhabiting rock pools with and without the presence of the invasive macroalgae A. armata. To achieve this, manipulation experiments on Atlantic (Portugal) rock pools were done. Three rock pools were maintained without A. armata by manual removal of macroalgae, and three others were not experimentally manipulated during the study period and A. armata was freely present. In this study the variations between different rock pools were assessed. Results showed different patterns in the macroalgae composition of assemblages but not for the macrobenthic communities. Ellisolandia elongata was the main algal species affected by the invasion of A. armata. Invaded pools tended to show less species richness, showing a more constant and conservative structure, with lower variation of its taxonomic composition than the pools not containing A. armata, where the variability between samples was always higher. Despite the importance of the achieved results, further data based on observation of long-term series are needed, in order to further understand more severe effects of the invader A. armata on native macroalgal assemblage.

One of the areas of research on materials for thin-film solar cells focuses on replacing In and Ga with more earth-abundant elements. In that respect, chalcostibite (CuSbS2) is being considered as a promising environmentally friendly and cost-effective photovoltaic absorber material. In the present work, single CuSbS2 phase have been synthesized directly by a short duration (2 h) mechanochemical synthesis step starting from mixtures of elemental powders. X-ray diffraction analysis of the synthesized CuSbS2 powders revealed a good agreement with the orthorhombic chalcostibite phase, space group Pnma, and a crystallite size of 26 nm. Particle size characterization revealed a multimodal distribution with a median diameter ranging from of 2.93 m to 3.10 m. The thermal stability of the synthesized CuSbS2 powders was evaluated by differential thermal analysis. No phase change was observed by heat treating the mechanochemically synthesized powders at 350 C for 24 h. By UV-VIS-NIR spectroscopy the optical bandgap was determined to be 1.41 eV, suggesting that the mechanochemically synthesized CuSbS2 can be considered suitable to be used as absorber materials. Overall, the results show that the mechanochemical process is a viable route for the synthesis of materials for photovoltaic applications.

Micro-nano-plastics (MNPs) are an important constituent of atmospheric aerosol. However, there is still no standard procedure for their sampling and size fractionation, which is an obstacle to the aggregation and critical analysis of results obtained by different research groups. This review focuses on the sampling and fractionation methodologies used for MNPs. Moreover, a straightforward optimized methodology for the sampling and fractionation is proposed.

In this paper we propose a computational framework that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large number of mechanistic models in SBML that are currently stored in public databases. With the proposed framework, existing SBML mechanistic models may be upgraded to hybrid systems through the incorporation of deep neural networks into the model core, using a freely available python tool. The so-formed hybrid mechanistic/neural network models are trained with a deep learning algorithm based on the adaptive moment estimation method (ADAM), stochastic regularization and semidirect sensitivity equations. The trained hybrid models are encoded in SBML and stored back in model databases, where they can be further analyzed as regular SBML models. The application of this approach is illustrated with three well-known case studies: the threonine synthesis model in Escherichia coli, the P58IPK signal transduction model, and the Yeast glycolytic oscillations model. The proposed framework is expected to greatly facilitate the widespread use of hybrid modeling techniques for systems biology applications.

Açaí, Euterpe oleracea Mart. is a native plant from the Amazonian and is rich in several phyto-chemicals with anti-tumor activities. The aim was to analyze the effects of açaí seed oil on colo-rectal adenocarcinoma (ADC) cells. In vitro analyses were performed on CACO-2, HCT-116, and HT-29 cell lines. The strains were treated with açaí seed oil for 24, 48, and 72 h, and cell viability, death, and morphology were analyzed. Molecular docking was performed to evaluate the inter-action between the major compounds in açaí seed oil and Annexin A2. The viability assay showed the cytotoxic effect of the oil in colorectal adenocarcinoma cells. Acai seed oil induced increased apoptosis in CACO-2 and HCT-116 cells and interfered with the cell cycle. Western blotting showed increased expression of LC3-B, suggestive of autophagy, and annexin A2, an apoptosis regulatory protein. Molecular docking confirmed the interaction of major fatty acids with annexin A2, suggesting a role of açaí seed oil in modulating annexin A2 expression in these cancer cell lines. Our results suggest the antitumor potential of açaí seed oil in colorectal adeno-carcinoma cells and contribute to the development of an active drug from a known natural product.

Hydrogels are water-absorbing polymers that can hydrate forage plants in the soil. The objec-tive was to evaluate the replacement of synthetic hydrogels derived from petroleum by biode-gradable hydrogels in Mombaça grass pastures (Megathyrsus maximum). The experimental treat-ments consisted of: No hydrogel (NH); Synthetic commercial hydrogel (CH), made from a syn-thetic polyacrylamide product; and Biodegradable test hydrogel (TH), obtained from cashew gum (Anacardium occidentale). The experimental design was randomized blocks with five replica-tions and three treatments. Morphogenesis, production, chemical and mineral composition of the Mombaça grass pasture were assessed. The data was subjected to analysis of variance and mean comparison by the Snott-Knott test at 5% probability. Leaf elongation rate was 42.3 mm day-1 in the TH treatment, which was higher (P<0.05) than NH (35.0 mm day-1). Green leaf mass yield was higher in TH in comparison to NH and CH. On the other hand, there was no effect of hydration on chemical composition. The mineral composition of Mombaça grass showed more Zn when TH was used. It can be concluded that biodegradable hydrogels can replace synthetic commercial hydrogels in pastures.

Pesticide exposure is a growing concern for public health. Although Brazil is the world's largest consumer of pesticides, few studies addressed the health effects among farmers. This study aimed to evaluate whether pesticide exposure is associated with respiratory outcomes among rural workers and relatives in Brazil during the crop and off-seasons. 82 family farmers were interviewed about occupational history and respiratory symptoms, and cholinesterase tests were conducted in the crop-season. Spirometry was performed during the crop and off-season. Respiratory outcomes were compared between seasons and multiple regressions were conducted to search for associations with exposure indicators. Participants were occupationally and environmentally exposed to multiple pesticides from an early age. During the crop and off-season, respectively, they presented a prevalence of 40% and 30.7% for cough, 30.7% and 24% for nasal allergies, and 24% and 17.3% for chest tightness. Significant relations between spirometry impairments and exposure indicators were found both during the crop and off-season. These findings provide complementary evidence about the association of pesticide exposure with adverse respiratory effects among family farmers in Brazil. This situation requires special attention as it may increase the risk of pulmonary dysfunctions, and the morbidity and mortality burden associated with these diseases.

Studies have demonstrated the positive effects of acupuncture on athletic performance. The aim of this study was to determine the acute effects of acupuncture on heart rate, the perceived exertion scale and lactate levels in recreational athletes. Fifteen competitive males engaged in HIIT. The characteristic was 29.86±2.51 years old, heart rate reserve 59.00±3.33, lactate 3.17±0.50 mM/DL. The subjects were submitted to two exercise sessions. Both training sessions consisted of 10 burpees, 12 thrusters and 14 box jumps (75 cm high) for 12 minutes. Activity intensity was between 85 and 95% of maximum heart rate. Acupuncture points: ST36, L3, LI11. The student’s t-test was adopted, Shapiro-Wilk test was applied for normality, and Pearson correlation. There was a positive correlation of r = 0.69 between lactate levels and heart rate. Lactate: Lac1 15.00±1.18 – Lac2 19.59± 1.46 p= 0.0001*; Heart 1rate: HRF 163.71±7.27 – HRF2 177.60±6.99 p=0.0001*; Blood pressure: SBP1 174.86±1.57 – SBP2 180.86±1.77 p= 0.0001*; PES1: 19.4±1.14; PES2 16.8±0.84 p= 0.0001*; weight1 – 182,57±12,05; weight 2 206,43±11,39 p=0.0325*. Acupuncture increased lactate accumulation, heart rate and blood pressure, suggesting that the exertion reached after acupuncture is higher than without acupuncture. The acupuncture technics improved the athlete performance.

The glucose-insulin regulatory system and its glucose oscillations is a recurring theme in the literature because of its impact on human lives, mostly the ones affected by diabetes mellitus. Several approaches were proposed, from mathematical to data-based models, with the aim of modeling the glucose oscillation curve. Having such a curve, it is possible to predict, when injecting insulin in type 1 diabetes (T1D) individuals. However, the literature presents prediction horizons no longer than 6 hours, which could be a problem considering their sleeping time. This work presents Tesseratus, a model that adopts a multi-agent approach to combine machine learning and mathematical modeling to predict the glucose oscillation up to 8 hours. Tesseratus uses the pharmacokinetics of insulins and data collected from T1D individuals. Its outcome can support endocrinologists while prescripting daily treatment for T1D individuals, and provide personalized recommendations for such individuals, to keep their glucose concentration in the ideal range. Tesseratus brings pioneering results for prediction horizons of 8 hours for nighttime, in an experiment with seven real T1D individuals. It is our claim that Tesseratus will be a reference for classification of glucose prediction model, supporting the mitigation of short- and long-term complications in the T1D individuals.

The conversion of caatinga vegetation areas into pastures in the Brazilian semiarid region has depleted soil fertility due to degradation. The natural regeneration of the caatinga has been the alternative adopted to restore soil fertility. However, the real effectiveness of this practice in re-covering organic carbon (SOC) and nutrient stocks is unknown. This work evaluated the effect of natural regeneration of the caatinga vegetation on the restoration of levels and stocks of SOC, N, and P as a strategy to maintain the sustainability of the environment. We collected soil samples every 5 cm, up to 20 cm deep, in areas of degraded pasture, caatinga in regeneration (10 years), and regenerated caatinga (35 years) to evaluate the levels and stocks of SOC, N, and P. The depth sig-nificantly affects the levels and stocks of SOC, N, and P. Stocks and levels of SOC, N, and P were higher in regenerated caatinga > regenerating caatinga > degraded pasture. The regenerated caatinga increased SOC, N, and P stocks by 115%, 110%, and 117%, respectively, compared to the degraded pasture. Although 35 years of regeneration of the caatinga has improved soil fertility, the levels and stocks of SOC, N, and P remain low.

Background: Changes in body weight are associated with the regulation of DNA methylation (DNAm). In this study, we investigated the associations between maternal gestational weight gain-related DNAm and foetal and neonatal body composition. Methods: Brazilian pregnant women from the Araraquara Cohort Study were followed up during pregnancy, delivery, and after hospital discharge. Women with normal pre-pregnancy BMI were allocated to two groups: adequate gestational weight gain (AGWG, n=45) and excessive gestational weight gain (EGWG, n=30). Foetal and neonatal body composition was evaluated by ultrasound and plethysmography, respectively. DNAm was assessed in maternal blood using Illumina Infinium MethylationEPIC BeadChip arrays. Linear regression models were used to explore the associations between DNAm and foetal and neonatal body composition. Results: Maternal weight, GWG, neonatal weight, and fat mass were higher in the EGWG group. Analysis of DNAm identified 46 differentially methyl-ated positions and 11 differentially methylated regions (DMRs) between the EGWG and AGWG groups. Nine human phenotypes were enriched for these 11 DMRs located in 13 genes (EMILIN1, HOXA5, CPT1B, CLDN9, ZFP57, BRCA1, POU5F1, ANKRD33, HLA-B, RANBP17, ZMYND11, DIP2C, TMEM232), highlighting the terms insulin resistance, and hyperglycaemia. Maternal DNAm was associated with foetal total thigh and arm tissues and subcutaneous thigh and arm fat, as well as with neonatal fat mass percentage and fat mass. Conclusion: The methylation pat-tern in the EGWG group indicated a risk for developing chronic diseases and involvement of ma-ternal DNAm in foetal lean and fat mass and in neonatal fat mass.

Copper-catalyzed and organocopper-involved reactions are of great significance in organic synthesis. To have a deep understanding of the reaction mechanisms, the structural characterizations of organocopper intermediates become indispensable. Meanwhile, the structure-function relationship of organocopper compounds would advance rational design and development of new Cu-based reactions and organocopper reagents. Compared to the mono-carbonic ligand, the C,N- and C,C-bidentate ligands better stabilize the unstable organocopper compounds. The bidentate ligands can chelate to the same copper atom via ?2-mode, forming a mono-cupra-cyclic compounds with at least one acute C-Cu-C angle. When the bidentate ligands bind to two copper atoms via ?1-mode at each coordinating site, the bimetallic macrocyclic compounds will form nearly linear C-Cu-C angles. The anionic coordinating sites of the bidentate ligand can also bridge two metals via ?2-mode, forming organocopper aggregates with Cu-Cu interactions and organocuprates with contact ion pair structures. The reaction chemistry of some selected organocopper compounds is highlighted, showing their unique structure-reactivity relationships.

The Covid-19 started in China and took over the world, becoming a pandemic. Especially in Latin America, the coronavirus arrived on the continent in mid-February 2020. The South American continent is going through a delicate political, economic and social moment, which is reflected in the fragility of our health systems and science and to reduce the rates of contagion and not overburden health services, including hospitals. Nevertheless, several studies are being carried out in Brazil and worldwide, with the objective sought to understand the characteristics, and even, the cure of people infected by the coronavirus. Therefore, we must consider science-based strategies to combat the pandemic and promote a health system that takes care of the population that needs it.

IHepatitis C virus (HCV) has a high genetic diversity, with seven genotypes with 86 subtypes. This genetic variability confers persistence in the infection and escape of the immune system with evolution to cirrhosis and cancer. Environmental factors can contribute to different disease progression, being essential to assess the viral genotype in the infection and discuss the environmental particularities of Eastern Amazon, and the frequencies of Liver fibrosis between different HCV genotypes in patients living in a region of the Brazilian Eastern Brazilian Amazon. Consists in an observational cross-sectional study. Sociodemographic and clinical data of 76 individuals diagnosed with Hepatitis C between 2019 and 2020 in public health services were selected. Data collected was tabulated in Microsoft Excel 2010TM spreadsheets and analysed in GraphPad Prism 5.0TM. Liver fibrosis was associated with genetic subtypes. Subtype 1b was predominant (42.1%), followed by 1a (13%) and 3a (1.3%). 69.7% of participants had chronic hepatitis, with mild fibrosis (F1/F2) being the most prevalent (38.1%). Severe fibrosis was detected in 75% of individuals infected with the subtype 1b, that is associated with more severe disease. We suggest further studies, to assess other communities in the region, as well as the monitoring of these patients with Liver Elastography to determine the disease evolution and its better management.

Over the last two decades, a considerable amount of equipment has been acquired (spreaders, seeders, sprayers, among others) to respond to the challenges of Precision Agriculture (PA) concept. Most of this equipment has been purchased at a high cost. However, many of them, despite still being functional and equipped with sensors, actuators, and electronic processing units capable of adjusting to variations in speed, have become obsolete in terms of communication, and incompatible with new monitoring and control systems based on the “Isobus” protocol. This work aims to present a solution for updating the control system (“Ferticontrol”) of a “Vicon RS-EDW” spreader with variable rate application (VRA), making it compatible with the “InCommand” system from “Ag Leader”. The solution includes low-cost “Arduino” and “Raspberry Pi” microcontrollers and open-source software. The development shows that it is possible to implement a solution that is accessible to farmers in general. It also provides a niche business opportunity for young researchers to set up small technology-based enterprises associated with universities and research centers. These partnerships guarantee permanent innovation and represent a decisive step towards modern, technological, competitive, and sustainable agriculture.

Quality control is a critical component in industrial manufacturing, directly influencing efficiency, product reliability, and ultimately, customer satisfaction. In the dynamic environment of industrial manufacturing, traditional methods of inspection may not adequately meet the evolving complexity, necessitating innovative approaches to bolster precision and productivity. In this study, we explore the application of mixed reality (MR) technology for real-time quality control in the assembly process. Our methodology involved the integration of smart glasses with a server-based image recognition system, designed to conduct real-time component analysis. The innovative aspect of our study lies in the harmonization of MR and computer vision algorithms, providing immediate visual feedback to inspectors and thereby improving the speed and accuracy of defect detection. YOLOv8 have been adopted in this study for detection object model. The project implementation occurred in a controlled environment to enable a comprehensive evaluation of the system functionality, the identification of possible problems and improvements in the system performance. The results indicated the viability of mixed reality as a powerful tool for enhancing traditional inspection processes. The fusion of MR and computer vision offers possibilities for future advancements in industrial quality control, paving the way for more efficient and reliable manufacturing ecosystems.

The use of cobalt-iron (VaCoFe) core is investigated as an alternative to silicon-iron (FeSi) on the design of interior permanent magnet synchronous motors (IPMSM). A spoke-type IPMSM geometry is optimized considering FeSi and VaCoFe cores for a torque range up to 40 N.m, providing a general comparative analysis between materials, considering the application of a 4-motor competition vehicle’s powertrain. A genetic optimization algorithm is applied over a hybrid analytical/finite-element model of the motor to provide sufficiently accurate electromagnetic and thermal results within a feasible time. VaCoFe can result in an estimated increase of up to 5 % in efficiency for the same torque, or up to 64 % torque increase for the same efficiency level. After optimization, and using a detailed time-dependent model, a potential 3.2 % increase in efficiency, a core weight reduction of 4.1 %, and a decrease of 9.6 % in the motor’s core volume was found for the VaCoFe at 20 Nm. In addition, for the same motor volume, the VaCoFe allows an increase of 51.9 % of torque with an increase of 1.1 % of efficiency, when compared with FeSi.

Microplastic pollution (MP) in marine environments around the globe is severe and enough precautions have not been taken so far for its prevention. The focus of this study is to quantify MPs from beach sediment and seawater samples and to identify their distribution and types along the western coast of Sri Lanka from the Kelani River estuary to the Mahaoya estuary. Nine sites along this 42 km stretch were selected and random sampling was employed to collect a minimum of 8 sediment samples from each site between October and December 2021. Water samples were also collected, parallel to the sediments, from the ocean surface. FTIR analysis revealed that most of the MPs found were polyethylene(PE), polypropylene(PP), polystyrene(PS), polyethylene terephthalate(PET), and phenol formaldehyde resin. The mean abundance of MPs varied from 2.0 ± 0.6 items/L to 161.0 ± 15.7 items/L in water samples and, from 3.0 ± 0.3 items/m2 to 656.0 ± 34.5 items/m2 in sediment samples. The MPs found were identified in different shapes as fragments (80.2%), pellets (14.9%), fibers (2.7%) and foams (2.5%). Analysis revealed that the beach sediments were contaminated with PS, phenol formaldehyde resin, PET, PP and PE, while surface seawater is dominated by phenol formaldehyde resin, PS, PP and PE.

Textile and clothing is one of the most important industrial sectors, not only due to the significant number of jobs generated, but also because it addresses one of the people’s fundamental needs (clothing). It is, however, a sector with a huge environmental impact, all over the world, and also an important social impact, especially in developing countries. Sustainability in the Textile &amp; Clothing value chain is a known issue, concerning both environmental, and economical-social facets of sustainability. One way to improve sustainability in this sector is by measuring the environmental, economic and social impacts of value chain activities and, ultimately, computing an Environmental and Circular score for each batch of textile and clothing product, and an Economical and Social score for each involved firm, reflected in their products. The consumer will then have the opportunity and responsibility for selecting products with the least negative environmental, economical and social impact. This article presents the results of STVgoDigital project - PPS1, developed in Portugal with the aim of implementing the traceability of textile and clothing products, boosting sustainability in this sector, and preparing the ground for the implementation of the circular economy. More exactly, a blockchain-based textile and clothing value-chain traceability platform is presented, for tracing textile product lots and activities, along the value chain, classifying them with a score, which measures their environmental and social impact. The environmental, economic and social impact scores are based on a set of proposed indicators. The results are assessed through the presentation of a case study of a face towel (home textile) and a case study of a T-shirt (clothing).

Electronic devices are sensitive to electromagnetic (EM) emissions requiring electromagnetic shielding protection to assure good operation, preventing noise, malfunctioning, or even burning. To assure protection, it is important to develop suitable material and design solutions for electronic enclosures. Most common enclosures are made with metal alloys by traditional manufacturing methods. However, resourcing to thermoplastic composites combined with additive manufac-turing (AM) technologies emerges as an alternative that enables to fabricate complex parts that are lightweight, consolidated and oxidation and corrosion resistant. In this research, an AM technique based in material extrusion was used to print 2 mm thick specimens with a multi-material made of micro-carbon fiber (CF) filled polyamide, reinforced, at specific layers, by continuous carbon fibers stacked with a 90° rotation to each other. Specimens electromagnetic shielding effectiveness (EMSE) was evaluated in the frequency band of 0.03 – 3 GHz by coaxial transmission line method. De-pending on the number of CF layers, the EM shielding obtained can up to 70 dB, with a specific shielding up to 60 dB.cm3/g, predominantly by absorption mechanism, being 22 times higher that without the CF layers. These findings fundament this innovative approach for lightweight cus-tomizable solutions for EM shielding applications.

Background/Aim: Stool gluten immunogenic peptides (GIP) determination is now considered a valuable tool for detecting dietary lapses in treated celiac disease (CeD) patients. Our study aims to explore the diagnostic performance of a qualitative lateral flow immunoassay point-of-care test (LFIA/PoCT) compared with a qualitative enzyme-linked immunosorbent assay (ELISA) for detection of stool GIP. Methods: The study is a post hoc analysis of stool samples collected in the real-life conditions from a cohort of gluten-free diet-treated CeD patients. Stool GIP was measured in µg/g of stool using an ELISA kit (iVYLISA GIP S®, Biomedal SL). For the qualitative evaluation of stool GIP, a LFIA/PoCT test (GlutenDetect®; Biomedal S.L) was employed, which reported results as positive or negative. The LFIA/PoCT performance was evaluated against ELISA, considered as the gold standard. GIP concentrations

Hepatitis C virus (HCV) is a major public health threat associated with serious clinical consequences worldwide. The WHO reports an estimated 58 million people globally living with chronic hepatitis C virus (HCV) infection, with 1.5 million new cases and over 350,000 deaths annually due to HCV-related diseases. Despite the existence of multiple diagnostic methods, the accessibility of diagnosis and treatment is often hindered across the continent by limited resources, insufficient healthcare infrastructure, and low public awareness of Hepatitis C virus Hepatitis C virus infection is a major public health concern in African countries, which have the highest prevalence rates of HCV in the world (1–26%). Egypt, African country which had the highest prevalence of Hepatitis C virus infection in the world. Its national hepatitis C elimination initiative emerges as an exemplary case of success an having screened over 60 million individuals, and treated more than 4 million, thereby markedly diminishing both the prevalence and incidence of the disease. The strategies employed by Egypt offer critical insights and adaptable frameworks for other African Countries facing analogous challenges. The Aim of this Review is to highlight the triumphs and hurdles of Egypt's approach, while also providing strategic guidance for African Countries to accelerate the journey towards the eradication of hepatitis C.

Microfluidic devices or microdevices refer to systems with a characteristic length in the micrometer range. Systems in this size allow handling small quantities of reagents and samples, with reduced residence time, better control of chemical species concentration, high heat and mass transfers, and high surface/volume ratio. These characteristics led to the application of these microdevices in several areas, such as biological systems, energy, liquid-liquid extraction, food, agricultural sectors, pharmaceuticals, flow chemistry, microreactors, and biodiesel synthesis. Microreactors are devices that have interconnected microchannels, in which small amounts of reagents are manipulated and react for a certain period of time. The traditional characteristics of microreactors are less quantities of reagents and samples, high surface area in relation to volume (10000 m² m^-3), reduction of resistance to heat and mass transfer, reduced reaction times, and narrower residence time distributions. In recent years, several studies have been carried out on biodiesel production in microreactors that explore the influence of operating conditions, mixing and reaction yield, numbering, and especially the microdevices design. Despite all the advantages of microreactors, the literature shows that there are only a few applications on an industrial scale. Two main reasons that hinder the adoption of this technology are the scale-up to a large enough volume to deliver the necessary production capacity and the costs related to industrial manufacturing microreactors. It is often stated that large-scale production of microreactors can be easily achieved by numbering-up. However, researches show that an incredibly high number of microdevices would be needed, which results in a technical unfeasibility and a strong impact on the construction costs of the industrial system. The present review aims to show whether microreactors can replace conventional biodiesel production processes and how this replacement technology could be carried out. The current chapter was divided into the following sections: Introduction, Synthesis and Purification of Biodiesel in Microreactors, Fundamentals of CFD, and Fundamentals of Scale-up. Finally, conclusions and future perspectives are exposed.

A rehabilitation technique for asphalt pavements with geosynthetic is the application of impregnated nonwoven geotextiles between deteriorated and new asphalt overlays. The performance investigation of impregnated geotextiles proves that they are enhancing in mechanical and hydraulic properties. Although, the installation process may cause severe impacts on these materials’ performance. During the installation, the geotextile suffers damage due to the traffic of high load vehicles, as compactors and pavers, and the friction with granular materials found under its layer or poured above it. This paper aims to investigate how the damage caused by granular materials on nonwoven geotextiles impregnated with different asphalt emulsions effect on their strength resistance and permittivity. From two types of nonwoven geotextiles: polypropylene and polyethylene terephthalate, the comparison uses geotextiles in three conditions: not impregnated, impregnated with asphalt emulsion of rapid setting, and impregnated with asphalt emulsion changed by an elastomeric polymer. Part of the samples followed the damage according to ISO 10722 procedure, placed between three different scenarios of granular materials, applying gravel, sand, and clay. After the damage process, the samples were submitted to mechanical and hydraulic properties evaluations.

Following the WHO's declaration of a public health emergency due to the COVID-19 outbreak, the subsequent quarantine and confinement measures that were adopted, including distance learning measures, were shown to have caused a significant deterioration in the mental health of medical students. The goal of this study was to explore the mediating role of resilience and life satisfac-tion in the relationship between perceived stress and burnout among medical students in the con-text of COVID-19. A transversal assessment was performed using an online questionnaire, to which 462 students responded. The instruments applied were the Perceived Stress Scale-10, the Resilience Scale-25 items, the Satisfaction with Life Scale (SWLS) and the Burnout Scale (Olden-burg Inventory). A regression model was estimated for each dimension of burnout. The results revealed that resilience and life satisfaction play a mediating role in the association between stress and the dimensions of burnout. This suggests that measures of promoting mental health based on resilience and improving perceptions of life should be implemented.

This review explores the transformative role of induced pluripotent stem cells (iPSCs) and organoids in advancing neuropathology research. Focused on Alzheimer's disease, epilepsy, Parkinson's disease, and spinal cord injury, iPSCs offer patient-specific disease modeling with regenerative therapy potential. The versatility of iPSCs, their ability to differentiate into the main neuronal cell types, and their integration into three-dimensional organoid models enable the recreation of complex tissues in vitro. Improvement of organoid and iPSCs generation protocols and the selection of appropriate donor cell types are highlighted as crucial steps toward the application of these new technologies to overcome tumorigenic potential and other challenges. iPSCs demonstrate promise in regenerative therapies, as evidenced by successful applications in animal models.

This study aimed to compare three different extracts of Saco sweet cherry, namely non-coloured fraction, coloured fraction and total extract concerning phenolic composition, antioxidant and antidiabetic potential, erythrocytes’ protection and effects on Caco-2 cells. A total of 22 phenolic compounds were identified by LC-DAD. Hydroxycinnamic acids were the most predominant in both non-coloured fraction and total extract, while cyanidin-3-O-rutinoside was the main anthocyanin found in the coloured fraction. The total extract was the most effective against DPPH, nitric oxide and superoxide radicals, and in the inhibition of α-glucosidase enzyme. Finally, the protective effect of the extracts to prevent oxidative damage in human erythrocytes was assessed. The coloured fraction revealed the best activity against hemoglobin oxidation and hemolysis. Regarding to Caco-2 cells, the coloured extract exhibited the most cytotoxic effects, while the total extract was the most efficient in protecting these cells against oxidative damage induced by t-BHP.

Intrusion Detection Systems play a crucial role in a network. They can detect different network attacks and raise warnings on them. Machine learning-based IDSs are trained on datasets that, due to the context, are inherently large, since they can contain network traffic from different time periods and often include a large number of features. In this paper, we present two contributions: the study of the importance of feature selection when using an IDS dataset, while striking a balance between performance and the number of features; and the study of the feasibility of using a low-capacity device, the Nvidia Jetson Nano, to implement an IDS in a low-capacity network. The results, comparing the GA with other well-known techniques in feature selection and reduction, show that the GA has a higher F1-score of 76%, although the time to find the optimal set of features surpasses other methods; the reduction of the number of features reduces the processing time without a significant impact in f1-score. The Jetson Nano allows the classification of network traffic with an overhead of 10 times in comparison to a traditional server.

The growing worldwide cancer incidence, coupled to the increasing occurrence of multidrug cancer resistance, requires a continuous effort towards the identification of new leads for cancer management. In this work, two C-scorpionate complexes, [FeCl2(κ3-Tpm)] (1) and [Co(κ3-TpmOH)2] (2), (Tpm = hydrotris(pyrazol-1-yl)methane and TpmOH = 2,2,2-tris(pyrazol-1-yl)ethanol), are studied as potential scaffolds for future anti-cancer drug development. Their cytotoxicity and cell migration inhibitory activity are analyzed, and an untargeted metabolomics approach is em-ployed to elucidate the biological processes significantly affected by these two complexes, using two tumoral cell lines (B16 and HCT116) and a non-tumoral cell line (HaCaT). While [FeCl2(κ3-Tpm)] did not display a significant cytotoxicity, [Co(κ3-TpmOH)2] was particularly cy-totoxic against the B16 cell line. While [Co(κ3-TpmOH)2] significantly inhibited cell migration in all tested cell lines, [FeCl2(κ3-Tpm)] displayed a mixed activity. From a metabolomics perspective, exposure to [FeCl2(κ3-Tpm)] is associated with changes in various metabolic pathways involving tyrosine, where iron-dependent enzymes are particularly relevant. On the other hand, [Co(κ3-TpmOH)2] is associated with dysregulation of cell adhesion and membrane structural pathways, suggesting its antiproliferative and anti-migration properties can be due to changes in the overall cellular adhesion mechanisms.

Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed with TB, it is critical that healthcare workers make the most appropriate treatment decision given the individual conditions of the patient and the likely course of the disease based on medical experience. Depending on the prognosis, delayed or inappropriate treatment can result in unsatisfactory results including the exacerbation of clinical symptoms, poor quality of life, and increased risk of death. This work benchmarks machine learning models to aid TB prognosis using a Brazilian health database of confirmed cases and deaths related to TB in the State of Amazonas. The goal is to predict the probability of death by TB thus aiding the prognosis of TB and associated treatment decision making process. In its original form, the data set comprised 36,228 records and 130 fields but suffered from missing, incomplete, or incorrect data. Following data cleaning and preprocessing, a revised data set was generated comprising 24,015 records and 38 fields, including 22,876 reported cured TB patients and 1,139 deaths by TB. To explore how the data imbalance impacts model performance, two controlled experiments were designed using (1) imbalanced and (2) balanced data sets. The best result is achieved by the Gradient Boosting (GB) model using the balanced data set to predict TB-mortality, and the ensemble model composed by the Random Forest (RF), GB and Multi-layer Perceptron (MLP) models is the best model to predict the cure class.

The whitefly leads extensive damage to plants through direct feeding, honeydew secretion, plant physiological disorders, and vectoring plant viruses. This study aimed to evaluate the physiological characteristics of susceptible and resistant soybean cultivars to B. tabaci. The experiments were conducted in a greenhouse. Eleven soybean cultivars were selected and infested with 100 adults of B. tabaci at the V3 stage. The evaluation of photosynthetic parameters, such as photosynthetic rate, leaf transpiration, stomatal conductance, and internal CO2 concentration, revealed that B. tabaci infestation influenced gas exchange in soybean plants. The photosynthetic rate was higher in cultivars AS3810 and M8349 during the V6 stage. Infestations led to alterations in photosynthetic parameters, suggesting increased energy demand to maintain photosynthetic activity. However, the response to infestation varied among different cultivars, indicating varying levels of resistance and tolerance to the whitefly's damage. Additionally, the impact of infestation was more significant during the vegetative phenological. In conclusion, B. tabaci infestation affects soybean plants' physiology, leading to changes in gas exchange parameters and water use efficiency. The response to infestation varied among soybean cultivars, suggesting potential differences in resistance to the pest. The study highlights the importance of evaluating the physiological impact of whitefly infestations on soybean.

Our research aimed to explore how resolving periodontal inflammation impacts cytokine expression in the colon of aged Wistar rats. Animal studies have been used to investigate the two-way relationship between periodontitis and Inflammatory Bowel Disease (IBD), where chronic inflammation in either the mouth or intestines can negatively affect the other. We allocated sixteen male Wistar rats, aged between 8-11 months, into four groups: (1) Ligature-induced periodontitis (LIP) without the resolution of periodontal inflammation (RPI) (LIP; n=4), (2) LIP + RPI (n=4), (3) LIP + DSS-induced colitis (DIC) without RPI (n=4), and LIP+DIC+RPI (n=5). We performed histopathological and immunological analyses on the periodontal and intestinal tissues and analysed cytokine expressions using a Rat Cytokine 23-Plex Immunoassay. Our findings showed that animals with and without DIC who underwent RPI showed significantly lower levels of IL-2, IL-4, IL-5, IL-10, IL-13, IL-17, IL-18, and TNF-α in the intestine compared to those without treatment. The RPI effectively reduced the number of inflammatory cells in the lamina propria and restored the epithelial barrier in the intestine in animals with DIC. The resolution of periodontal inflammation significantly reduced the levels of pro-inflammatory cytokines and chemokines in the intestine of aged rats with and without DSS-induced colitis.

This paper presents a new information technology platform specially tailored for infrastructure asset management of urban water systems operated by water utilities of lower digital maturity level, developed in the scope of DECIdE research project. This platform aims at the integration of different data from the water utilities with several information systems and the assessment of the system performance, in terms of water losses, energy efficiency and quality of service by using developed tools (i.e., water and energy balances and key performance indicators). This platform was tested with data from five small to medium size Portuguese water utilities with different maturity levels in terms of technological and human resources. Obtained results are very promising since the platform allows to assess the systems performance periodically which constitute an important part of the infrastructure asset management for small and medium-sized water utilities

Steel slag is a co-product of the steelmaking industry, this material is rarely used as a binder due to its low cementitious properties. Thus, it´s believed that the alkaline activation of steel slag can enable its use as a cementitious material. This work has the objective of making a systematic bibliographic review on the theme "slag melt as a precursor in activated alkali binders". To this end, the ProKnow-C method was used for the selection and analysis of relevant research on the topic. The portfolio resulted in 71 texts, mostly journals paper. Bibliometrics showed that the country with the most publications is China and the journal with the most publications is Construction and Building Materials. The critical analysis concluded that the XRD, XRF, and compressive strength tests are the most used for the characterization of the material. It is possible to establish that there are some knowledge gaps on the subject, such as better mechanical characterization and greater production of works with dosing by the one-part method.

This work reports the role of structure and composition on the determination of the performances of p-type SnOx TFTs deposited by rf magnetron sputtering at room temperature, followed by a post-annealed step up to 200 °C at different oxygen partial pressures (Opp), between 0% and 20%, but where the p-type conduction was only observed between 2.8–3.8%. The role of structure and composition were evaluated by XRD and Mössbauer spectroscopic studies. The study allows to identify the best phases/compositions and thicknesses (around 12 nm) to be used that lead to the production of TFTs with a bottom gate configuration, on glasses coated with conductive Indium Tin Oxide, followed by Aluminium Titanium Oxide dielectric layer with saturation mobility of 4.6 cm²V⁻¹s⁻¹ and on-off ratio above 7 × 10⁴, operating at the enhancement mode with a saturation voltage of −10 V.

Caffeine is a naturally occurring alkaloid found in various plants. It acts as a stimulant, antioxidant, anti-inflammatory and even an aid in pain management, and is found in several over-the-counter medications. This naturally derived bioactive compound is the best-known ingredient in coffee and other beverages, such as tea, soft drinks, and energy drinks, and is the most widely consumed substance worldwide. Therefore, it is extremely important to research the effects of this substance on the human body. With this in mind, caffeine and its derivatives have been extensively studied to evaluate its ability to prevent diseases and exert anti-aging and neuroprotective effects. This review is intended to provide an overview of the effects of caffeine on cancer, cardiovascular, immunological, inflammatory, and neurological diseases, among others. The heavily researched area of caffeine in sports will also be discussed. Finally, recent advances in the development of novel formulations, in the form of dietary supplements of caffeine and nanocarriers, to enhance the bioavailability of caffeine and its beneficial effects will be discussed. On the other hand, caffeine may contribute to elevated blood pressure, anemia, and migraine.

β-Ga2O3 is a well-known semiconductor material for power devices and other applications. Recently, β-Ga2O3 has also been reported as a scintillator material with a light yield of approximately 8400 ph./MeV, scintillation decay time of &lt;1 μs, and density of 6.44 g/cm3. In this study, 2-inch diameter β-Ga2O3 single crystals were prepared by oxide crystal growth using the cold crucible (OCCC) method under various oxygen partial pressures. In the OCCC method, as in the cold crucible method, a high frequency is applied directly to the oxide materials, which are heated and melted, and the melt is held by the outermost solid material itself that is cooled by water using a copper hearth. In the OCCC method, crystal growth is performed while rotating the seed crystal, as in the Czochralski method, to increase the crystal diameter. The optical properties and radiation responses of the crystals grown under various oxygen partial pressures were evaluated.

SARS-CoV-2 can induce vascular dysfunction and thrombotic events in patients with severe COVID-19; however, the cellular and molecular mechanisms behind these effects remain largely unknown. In this study, we used a combination of experimental and in silico approaches to explore the mechanisms behind the vascular and thrombotic events in COVID-19. Single-cell RNA-sequencing data from patients with COVID-19 and healthy subjects were obtained from the publicly available Gene Expression Omnibus (GEO) repository. In addition, HUVECs were treated with inactivated protein C before exposure to SARS-CoV-2 infection or a severe COVID-19 serum. An RT-qPCR array containing 84 related genes was used, and the candidate genes obtained were evaluated. Activated protein C levels were measured using an ELISA kit. We identified at the single-cell level the expression of several pro-inflammatory and pro-coagulation genes in endothelial cells from the patients with COVID-19. Furthermore, we demonstrated that exposure to SARS-CoV-2 promoted transcriptional changes in HUVECs that were partly reversed by the activated protein C pretreatment. We also observed that the serum of severe COVID-19 had a significant amount of activated protein C that could protect endothelial cells from serum-induced activation. In conclusion, activated protein C protects endothelial cells from pro-inflammatory and pro-coagulant effects during exposure to the SARS-CoV-2 virus.

Social plasticity, defined as the ability to adaptively change the expression of social behavior according to previous experience and to social context, is a key ecological performance trait that should be viewed as crucial for Darwinian fitness. The neural mechanisms for social plasticity are poorly understood, in part due to skewed reliance on rodent models. Fish model organisms are relevant in the field of social plasticity for at least two reasons: first, the diversity of social organization among fish species is staggering, increasing the breadth of evolutionary relevant questions that can be asked. Second, that diversity also suggests translational relevance, since it is more likely that “core” mechanisms of social plasticity are discovered by analyzing a wider variety of social arrangements than relying on a single species. We analyze examples of social plasticity across fish species with different social organizations, concluding that a “core” mechanism is the initiation of behavioral shifts through the modulation of a conserved “social decision-making network”, along with other relevant brain regions, by monoamines, neuropeptides, and steroid hormones. The consolidation of these shifts may be mediated via neurogenomic adjustments and regulation of the expression of plasticity-related molecules (transcription factors, cell cycle regulators, and plasticity products).

The critical systems, which the failure and malfunction may result in human, environment and financial severe damages, are essential components in various sectors and particularly in energy domains. Although unwished, integration error problems in supervision of critical systems occurs, incurring significant expenses because of operator’s subjective analysis and on hardware topology failures. In this work, a malleable model design approach is proposed to formulate and solve the integration error problem in the critical systems supervision in terms of reliability. A real Hybrid Power Plant (HPP) case is considered as a requirement for a study case with simulated data. A method framework with informal approach (C4 diagram) and formal approach (Hierarchical Coloured Petri Nets) in radial spectrum is applied to the HPP supervision design. Using formal methods, a formulation and solution to this problem through structured, scalable and compact mathematical representations are possible. This malleable model intends to guarantee functional correctness and then reliability of the plant supervision system based on system software architecture. Outcomes suggest corroboration that the malleable model is appropriate for energy domain, and can be used for other types of critical systems, bringing all the benefits of this methodology to the context in which it will be applied.

In this paper, we present a new concept of the generalized core orthogonality (called the C-S orthogonality) for two generalized core invertible matrices $A$ and $B$. $A$ is said to be C-S orthogonal to $B$ if $A^{\tiny\textcircled{S}}B=0$ and $BA^{\tiny\textcircled{S}}=0$, where $A^{\tiny\textcircled{S}}$ is the generalized core inverse of $A$. The characterizations of C-S orthogonal matries and the C-S additivity are also provided. And the connection between the C-S orthogonality and C-S partial order has been given using their canonical form. Moreover, the concept of the strongly C-S orthogonality is defined and characterized.

Since the discovery of transposable elements (TEs) in Maize in the 1940s by Barbara McClintock [1] transposable elements have been described as junk, as selfish elements with no benefit to the host, and more recently as major determinants of genome structure and genome evolution. TEs are DNA sequences that are capable of moving to new sites in the genome and make additional copies while doing so. To limit the propagation of TEs, host silencing mechanisms are directed at transposon-encoded genes that are required for mobilization. The mutagenic properties of TEs, the potential of TEs to form new genes and affect gene expression, together with the host silencing mechanisms shape eukaryotic genomes and drive genome evolution. While TEs constitute more than half of the genome in many higher eukaryotes, transposable elements in the nematode C. ele-gans form a relatively small proportion of genome, about 15% [2]. Genetic studies of transposon silencing and the discovery of RNAi in C. elegans, propelled C. elegans to the forefront of studies of RNA-based mechanisms that silence TEs. Here, I will review the transposable elements that are present and active in the C. elegans genome, and the host defense mechanisms that silence these elements.

C-reactive protein (CRP) and leukocytes are blood biomarkers involved in "Inflamm-Aging", which is a risk factor for the onset and progression of age-related diseases. Studies show that higher serum concentrations of these biomarkers are associated with functional disability, increased risk of low muscle strength, decreased muscle mass and mortality in the elderly. The objective was to estimate the predictive power and discriminating criteria of C-reactive protein and leukocyte concentrations for the risk of adverse health factors in the elderly within 30 days after hospital discharge (HD). Prospective cohort study using exploratory methods and blood biomarkers with 135 older adults admitted to medical and surgical clinics at a government hospital. The elderly were monitored at home after 30 days of HD for adverse health factors (rehospitalization, falls, amount of medication consumed, disability in basic and instrumental activities of daily living and mortality). CRP> 2.4; ≥ 0.7 and> 24.7 mg / dL and leukocytes ≥ 6.410; ≥ 8.690 and> 8.310 mm³ were discriminant for rehospitalization, falls and mortality within 30 days after HD, respectively. The cut-off points described may be used as a reference in the screening of hospitalized elderly vulnerable to adverse health events after hospital discharge.

This draft aims at opening a discussion about the adequacy of non-stratal, non-derivational models of phonology, such as Declarative Phonology, to give appropriate accounts of any kind of phonological variation of morphemes. Refuting the assumption that all variants of one single morpheme correspond to a unique underlying form consecutively respecified through ordered adjustments of phonological shape, Declarative Phonology seems able to integrate explanations of both suppletive and non-suppletive alternation. A rough application of this model to suppletive alternation in Portuguese will be sketched out.

The maturation process of Arabica coffee fruits is influenced by plant endogenous and external factors. The maturation stage of the fruits affects the bean's chemical composition, which is related to coffee beverage quality. During fruit maturation, the colour of the peel changes from green to red (cherry), which indicates the harvest time and supposedly that the fruits have high quality. However, many tones of red may define fruit maturity. This work aimed to study the dynamics of soluble sugar accumulation related to fruit redness in coffee fruit tissues. We classified the ripe fruits into six ripeness classes based on the intensity of the red colour of the epicarp using a colourimeter. Total soluble sugar, sucrose and starch were analyzed in the coat (exocarp+mesocarp), coat juice (obtained by squeezing the coat), and beans. We showed that endosperm sugar dynamics do not follow changes in the coat, indicating a separate control of sugar accumulation, mainly related to sucrose, an essential component of coffee quality. Our data show that there is no transfer of sucrose and reducing sugars from the red coat to the bean.

In this work, it is analyzed a Digital Signal Processor, DSP, based One Cycle Control, OCC, strategy for a Power Factor Corrector, PFC, rectifier, which presents Common-mode Voltage, CMV, immunity. The proposed strategy utilizes an emulated-resistance-controller in closed-loop configuration to set up dc-link voltage and achieve unity power factor, UPF. It is shown that if PFC can achieve UPF condition and if phase voltage is only affected by CMV, then phase current is free from CMV, as well as a lead-lag compensator, LLC, to average phase current. Another possible condition is also analyzed. The proposal is verified by simulation and experiments.

Background: The progression of periodontal diseases at national Portuguese level and its public awareness are of great interest, mainly due to the high burden of periodontitis. Objectives: To evaluate the prevalence progression of periodontal diseases in Portugal and correspondent public awareness, between 2004 and 2017, by using data from the Global Burden of Disease (GBD), Directorate-General of Health (DGH) and Google® Trends (GT). Methods: For the period 2004-2017, Portuguese national data of periodontal diseases prevalence were searched in the Institute for Health Metrics and Evaluation of GBD and DGH and for public awareness, GT comparison tool between Portuguese words for “Periodontitis”, “Gingivitis”, “Gums” and “Periodontal disease” trends was used. Results: For the period 2004-2017, the overall prevalence of periodontitis slightly increased from 11.3% to 11.7%. During that period the GT search term “Gums” (“Gengivas”) was the most relevant. It increased steadily over time while the search term “Periodontal disease” (“Doença periodontal”) decreased, being these search trends significantly correlated (

In our study, we investigated the prognostic significance of hematological markers—NLR (Neutrophil-to-Lymphocyte Ratio), PLR (Platelet-to-Lymphocyte Ratio), and RDW-CV (Red Blood Cell Distribution Width - Coefficient of Variation)—in 117 glioblastoma patients. Data collected from January 2016 to December 2018 included demographics, clinical scores, and treatment regimens. Unlike previous research, which often examined these markers solely before surgery, our unique approach analyzed them at multiple stages: preoperative, postoperative, and before adjuvant therapies. We correlated these markers with overall survival (OS) and progression-free survival (PFS) using statistical tools, including ANOVA, Cox regression, and Kaplan-Meier survival analyses, employing SPSS version 29.0. Our findings revealed notable variations in NLR, PLR, and RDW-CV across different treatment stages. NLR and PLR decreased after surgery, with some stabilization post-STUPP phase (NLR: p=0.007, η2p=0.06; PLR: p=0.001, η2p=0.23), while RDW-CV increased post-surgery and during subsequent treatments (RDW-CV: p &lt; 0.001, η2p=0.67). Importantly, we observed significant differences between the preoperative phase and other treatment phases. Additionally, higher NLR and RDW-CV at the second-line treatment and disease progression were associated with an increased risk of death (NLR at 2nd line: HR=1.03, p=0.029; RDW-CV at progression: HR=1.14, p=0.004). We proposed specific marker cutoffs that demonstrated significant associations with survival outcomes when applied to Kaplan-Meier survival curves (NLR at 2nd line &lt; 5: p&lt;0.017; RDW-CV at progression &lt; 15: p=0.007). Elevated NLR and RDW-CV at later treatment stages correlated with poorer OS and PFS. No significant preoperative differences were detected. These biomarkers may serve as non-invasive tools for glioblastoma management.

Multicore magnetic nanoparticles of manganese ferrite were prepared using carboxymethyl-dextran and melamine as agglutinating agents. The nanoparticles prepared using melamine exhibit a flower-shape structure, a saturation magnetization of 6.16 emu/g and good capabilities for magnetic hyperthermia. Magnetoliposome-like structures containing the multicore nanoparticles exhibit sizes in the range 250 – 400 nm. A new antitumor thienopyridine derivative was loaded in these nanocarriers with a high encapsulation efficiency of 98% ± 2.6%. Release profiles in absence and presence of an AMF indicate a transport by diffusion, with a maximum compound release of 31% under the AMF. A sustained and controlled drug release in anticipated from the results, pointing to suitable characteristics of the magnetoliposomes for dual cancer therapy (combined magnetic hyperthermia and chemotherapy).

The high flammability and lack of charrability of polystyrene (PS) pose significant limitations on its broader applications. Therefore, there is an urgent need for a straightforward and efficient method for the synthesis of flame-retardant PS, which still poses a considerable challenge. In this study, we present an efficient approach to enhance the flame-retardant properties of PS through direct phosphorylating aromatic C(sp2)-H bonds using commercially available and inexpensive manganese catalyst. A range of phosphonates served as reactive substrates to enable a tunable degree of polymer functionalization. The corresponding phosphorylated PS specimens were determined by means of 1H NMR, 31P NMR, FTIR spectroscopy and GPC. Microscale combustion calorimetry (MCC) tests indicate that this protocol indeed enhances the flame-retardant performance of PS. Moreover, other advantages associated with the incorporation of the phosphonate group have been observed, including improved thermal resistance and wettability. This cost-effective strategy of Mn-catalyzed C-H can also be utilized to directly obtain phosphonate modification of waste foamed PS and styrene acrylonitrile copolymer, providing a new method for the purpose of recycling and upgrading PS plastics.

This paper presents a comparison between rain gauges, C-band and X-band radar data over an instrumented and regulated catchment of the Paris region, as well as their respective hydrological impacts with the help of flow observations and a semi-distributed hydrological model. Both radars confirm the high spatial variability of the rainfall down to their space resolution (respectively one kilometer and 250 m) and therefore underscore limitations of semi-distributed simulations. The use of the polarimetric capacity of the Météo-France C-band radar was limited to corrections of the horizontal reflectivity and its rainfall estimates are adjusted with the help of a rain gauge network. On the contrary, neither calibration was performed for the polarimetric X-band radar of the Ecole des Ponts ParisTech (below called ENPC X-band radar), nor any optimization of its scans. In spite of that and the non-negligible fact that the catchment was much closer to the C-band radar than to the X-band radar (20 km vs. 40 km), the latter seems to perform at least as well as the former, but with a higher scale resolution. This characteristic was best highlighted with the help of a multifractal analysis of the respective radar data, which also shows that the X-band radar was able to pick up a few extremes that were smoothed out by the C-band radar.

For the last two decades, an increasing demand for low-cost adsorbents for drinking water treatment has been challenged in the rural areas of developing countries that have problems with arsenic (As) contamination. In this work, spent bleaching earth (SBE), a residual material that is formed during the process of refining vegetable oil, has been utilized to prepare the new magnetic adsorbent Fe-SBE/C by modifying its surface area through calcination and co-precipitation with iron. The experimental results demonstrate that Fe-SBE/C exhibits a substantial adsorption capacity towards both arsenite (As(III)) and arsenate (As(V)). Optimal pH conditions were found to be pH 10 for As(III) and pH 3 for As(V), resulting in adsorption percentages of 76.7% and 94.1%, respectively. Other experimental parameters such as calcination conditions, adsorbent dosage, iron-loading ratio, and the presence of co-existing ions were thoroughly investigated. The kinetic study revealed that the adsorption processes follow the Elovich and intraparticle diffusion models, suggesting a combined adsorption mechanism of boundary layer control and chemisorption. Furthermore, the isotherm followed the Langmuir model with a maximum adsorption capacity of 202.61 μg g-1 for As(III) and 187.61 μg g-1 for As(V). Through thermodynamic analysis and reinforcement by activation energy data, this research validates that the observed adsorption process is indicative through chemisorption. The regeneration study revealed the potential for multiple cycles of arsenic removal, highlighting the practical applicability of Fe-SBE/C in environmental contexts. In conclusion, the findings of this study underscore the efficacy of Fe-SBE/C in arsenic removal and present it as a promising and environmentally friendly solution for mitigating arsenic pollution.

The supply of mental health processes in primary care has gaps. This study aims to analyze the association of agreement criteria and flows between primary care teams and the Family Health Support Center (NASF) for mental health collaborative care, considering the difference between capital and non-capital cities in Brazil. This cross-sectional study was conducted based on secondary data from the Primary Care Access and Quality Improvement Program. Agreement criteria and flows were obtained from 3883 NASF teams of the matrix support or collaborative care. The Chi-square test and multiple Poisson regression were used; p &lt; 0.05 was considered statistically significant. Prevalence ratios of negative associations demonstrated protective factors for support actions: follow-up at Psychosocial Care Center, management of psychopharmacotherapy, offer of other therapeutic actions, care process for users of psychoactive substances, and offer of activities to prevent the use of psychoactive substances. Collaborative care in primary care was effective, and capital cities were a protective factor compared with non-capital cities.

L-Theanine, a unique non-protein amino acid, is an important bioactive component of green tea. Previous studies have shown that L-theanine has many potent health benefits, such as anti-anxiety effect, regulation of immune response, relaxing neural tension, reducing oxidative damage. However, little is known concerning whether L-theanine can improve the clearance of mitochondrial DNA (mtDNA) damage in organisms. Here, we reported that L-theanine treatment increased ATP production and improved mitochondrial morphology to extend the lifespan of UVC-exposed nematodes. Mechanistic investigations showed that L-theanine treatment enhanced the removal of mtDNA damage and extended lifespan by activating autophagy, mitophagy, mitochondrial dynamics, and mitochondrial unfolded protein response (UPRmt) in UVC-exposed nematodes. In addition, L-theanine treatment also up-regulated the expression of genes related to mitochondrial energy metabolism in UVC-exposed nematodes. Our study provided a theoretical basis for the possibility that tea drinking may prevent mitochondrial related diseases.

The electronic transport stability in nanodevices composed by metal/trans-polyacetylene /metal with different long length has contributed greatly for performance, homogeneity, stability, organization of the chains, reproducibility and higher conductivity. In this paper, we present an analytical study of the electronic transport characteristics from dimerized trans-polyacetylene (trans-PA) molecules containing an odd-even number of sites coupled to metal leads (left and right) in T-shaped geometry using the extended Su-Schrieffer-Heeger (SSH) model based on tight-binding Hamiltonian with the Non-Equilibrium Green´s Function (NEGF) via Heisenberg´s equation of motion and the Keldysh´s formalism. Due to the complexity of the T-shaped odd-even chain, our proposal was to test the effects on the finite-length network for three, four, five sites and furthermore foresee for 17-sites. We show how to tune dimerization strength () coupling to the parameters and T-shaped geometry of the device to which it affects the overlap integral localized at the three endpoints of the T-shaped system, making both the odd and even chains to undergo a metal-insulator transition in their electronic behavior. The results reached through control parity of the chain plane of the parameters governing () the electronic and experimental tunneling allow a better understanding of the subject.

Interferon-gamma (IFN-γ) is an important cytokine in host defense against tuberculosis infection. In some cases, administration of IFN-γ during tuberculosis infection can promote faster cure. In the present work, we have shown that in a mouse model, human interferon-gamma, exhibits some anti-tuberculosis activity, especially in combination with isoniazid.

The use of Artificial Neural Networks (ANN) is a great contribution to medical studies since the application of forecasting concepts allows the analysis of future diseases propagations. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation procedures and massive vaccination campaigns. There were proposed two methodologies to predict 28 days ahead the number of new cases, deaths, and ICU patients of five European countries: Portugal, France, Italy, United Kingdom, and Germany, and a case study of the results of massive immunization in Israel. The data input of cases, deaths, and daily ICU patients was normalized to reduce discrepant numbers due to the countries size, and the cumulative vaccination values by the percentage of population immunized, at least with one dose of vaccine. As a comparative criterion, the calculation of the mean absolute error (MAE) of all predictions presents the best methodology and targets other possibilities of use for the proposed method. The best architecture achieved a general MAE for the 1 to 28 days ahead forecast lower than 30 cases, 0,6 deaths and 2,5 ICU patients by million people.

This study describes the synthesis, and characterization of lead-free organic ferroelectric perovskite N-methyl-N’-diazabicyclo[2.2.2]octonium)-ammonium trichloride (MDABCO-NH4Cl3). The electrospinning technique was employed to obtain nanofibers embedded with this perovskite into PVC polymer for hybrid fiber production. The dielectric, piezoelectric and pyroelectric properties of these fibers were carefully examined. From measurements of the dielectric permittivity temperature and frequency dependence, together with the pyroelectric results, a transition from a high temperature paraelectric to a ferroelectric phase that remained down to room temperature, was found to occur at 438 K. A pyroelectric coefficient as high as 290 C K-1 m-2value obtained is within the same order of magnitude as that reported for MDABCO-NH4I3 and the semiorganic ferroelectric triglycine sulfate (TGS). The hybrid nanofibers exhibited good morphological characteristics and demonstrated very good piezoelectric properties. Specifically, a piezoelectric coefficient of 42 pC/N was obtained when a periodical force of 3 N was applied. The performance of these fibers is on par with materials discussed in the existing literature for fabrication of nano energy harvesting generators. Importantly, the perovskite nanocrystals within the fibers not harmed by oxidation, making them a promising environmentally friendly platform for flexible energy harvesting.

Background: We aimed to assess the association between DII and PD and the mediation effect of DII in the association of PD with systemic inflammation. Using the National Health and Nutrition Examination Survey (NHANES) 2009-2010, 2011-2012 and 2013-2014, participants that received periodontal exam and provided dietary recall data were included. The inflammatory potential of diet was calculated via DII. Periodontitis was defined according to the 2012 case definition. The clinical outcomes of interest were mean periodontal probing (PPD), mean clinical attachment loss (CAL) and thresholds of PPD and CAL. White blood cells (WBC), segmented neutrophils and C-reactive protein (CRP) were used as proxies for systemic inflammation. The periodontal measures were regressed across DII values using adjusted multivariate linear regression. Adjusted mediation analysis appraised the influence of DII in the association of periodontitis and systemic inflammation. 10,178 participants were included. DII was significantly correlated with mean PPD, mean CAL, thresholds of PPD and CAL, WBC, segmented neutrophils and DII (p&lt;0.01). A linear regression logistic adjusted for multiple confounding variables confirmed the association between DII and mean PPD (B = 0.02, Standard Error [SE]: 0.02, p&lt;0.001) and CAL (B = -0.02, SE: 0.01, p&lt;0.001). The association of mean PPD and mean CAL with both white blood cells and segmented neutrophils were mediated by DII (from 2.1 to 3.5%, p&lt;0.001). In the 2009-2010 subset, the association of mean CAL with serum CRP was mediated by DII (52.0%, p&lt;0.01). In conclusion, inflammatory diet and PD may be associated. Also, the inflammatory diet significantly mediated the association of leukocyte counts and systemic inflammation with periodontitis.

This article presents a comprehensive review of the relationship in sustainable tourism and blockchain technology. The aim of this research is to explore the potential of blockchain to promote sustainable tourism, as well as to evaluate the current state of research and practical implementations in this field. The findings demonstrate the potential of blockchain in enhancing sustainability practices in tourism, while also highlighting the challenges and limitations. The study provides valuable insights for policymakers, industry practitioners, and researchers, and proposes future research directions to further advance the field.

Latest evidence revealed a possible association between Parkinson’s disease (PD) and periodontitis. We explored the causal relationship of this association through two-sample Mendelian randomization (MR) in European ancestry populations. To this end, we used openly accessible data of genome-wide association studies (GWAS) on PD and periodontitis. As instrumental variables for periodontitis, seventeen single-nucleotide polymorphisms (SNPs) from a GWAS of periodontitis (1817 periodontitis cases vs. 2215 controls) and forty-five SNPs from a GWAS of PD (20,184 cases and 397,324 controls). Eight non-overlapping SNPs of periodontitis from an additional GWAS assisted in the validation of association being studied. Multiple approaches of MR were carried-out. There was no evidence of genetic liability of periodontitis being associated with a higher risk of PD (B= -0.0003, Standard Error [SE] 0.0003, P = 0.26). The eight independent SNPs (B= -0.0000, SE 0.0001, P = 0.99) validated this outcome. We found no association of genetically primed PD towards periodontitis (B= -0.0001, SE 0.0001, P = 0.19). This MR study found no conclusive evidence to support a bidirectional causal genetic liability between PD and periodontitis. Further GWAS studies are needed to confirm the consistency of these results.

Recent studies supported a clinical association between Parkinson’s Disease (PD) and periodontitis. Hence, investigating possible protein interactions between these two conditions is of interest. In this study, we conducted a protein-protein network interaction analysis with recognized genes encoding proteins for PD and periodontitis. Genes of interest were collected via GWAS database. Then, we conducted a protein interaction analysis using STRING database, with a highest confidence cut-off of 0.9. Our protein network casted a comprehensive analysis of potential protein-protein interactions between PD and periodontitis. This analysis may underpin valuable information for new candidate molecular mechanisms between PD and periodontitis and may serve new potential targets for research purposes. These results should be carefully interpreted giving the limitations of this approach.

Biological neural network (BNN) is the core brain for creature to accomplish its intelligent behaviors through unique network structure and mechanisms. It also inspires controlling human-designed autonomous agents including robots to generate more advanced intelligent behaviors by mimicking the neural control mechanism of creatures at a deeper and more interactive level. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of cellular synapse. The neural network simulation integrates computational programming and visualization of neurons and synapse connections of C. elegans, containing the specific controllable circuits summarization with their dynamic characteristics within the whole network. To illustrate its particular intelligent control capability in terms of robotics, we introduce the first innovative methodology for applying the BNN model to a 12-legged robot’s movement control based on the established numerical simulation platforms. We accomplished and designed two methods and corresponding encoding processes, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of BNN. Both simulation and experiment results indicate that the robot exhibits stronger autonomy and more intelligent moving performance under the control of BNN. We then summarized the contributions for digitalizing the C. elegans’ whole-brain neural network in real-time and utilizing it to control robot in a closed loop to validate its advanced intelligence control ability in terms of a scientific robot.

Background: Leishmaniasis is a significant global public health issue that is caused by parasites from Leishmania genus. With limited treatment options and rising drug resistance, there is a pressing need for new therapeutic approaches. Molecular chaperones, particularly Hsp90, play a crucial role in parasite biology and are emerging as promising targets for drug development. Objective: This study evaluates the efficacy of 17-DMAG in treating BALB/c mice from cutane-ous leishmaniasis through in vitro and in vivo approaches. Materials and Methods: We assessed 17-DMAG cytotoxic effect on bone marrow-derived mac-rophages (BMMΦ) and its effects against L. braziliensis promastigotes and intracellular amastigotes. Additionally, we tested the compound's efficacy in BALB/c mice infected with L. braziliensis via intraperitoneal administration to evaluate the reduction of lesion size and de-crease of parasite load in the ears and lymph nodes of infected animals. Results: 17-DMAG showed selective toxicity [selective index=432) towards Leishmania amastigotes, causing minimal damage to host cells. The treatment significantly reduced lesion sizes in mice and results in parasite clearance from ears and lymph nodes. It also diminished in-flammatory responses and reduced the release of pro-inflammatory cytokines (IL-6, IFN-g, TNF) and the regulatory cytokine, IL-10, underscoring its dual leishmanicidal and anti-inflammatory properties. Conclusion: Our findings confirm the potential of 17-DMAG as a viable treatment for cutaneous leishmaniasis and support further research into its mechanisms and potential applications against other infectious diseases.

An H-bond involves the sharing of a hydrogen atom between an electronegative atom to which it is covalently bound (the donor) and another electronegative atom serving as an electron acceptor. Such bonds represent a critically important geometrical force in biological macromolecules and, as such, have been characterized extensively. H-bond formation invariably leads to a weakening within the acceptor moiety due to the pulling exerted by the donor hydrogen. This phenomenon can be compared to a spring connecting two masses; pulling one mass stretches the spring, similarly affecting the bond between the two masses. Herein, we describe the opposite phenomenon when investigating the energetics of the C-H...O=C bond. This bond underpins the most prevalent protein transmembrane dimerization motif (GxxxG) in which a glycine C-H on one helix forms a hydrogen bond with a carbonyl in a nearby helix. We use isotope-edited FT-IR spectroscopy and corroborating computational approaches to demonstrate a surprising strengthening of the acceptor C=O bond upon binding with the glycine C-H. We show that electronic factors associated with the C-H bond strengthen the C=O oscillator by increasing the s-character of the -bond, lowering the hyperconjugative disruption of the -bond. In addition, a reduction of the acceptor C=O bond’s polarity is observed upon the formation of the C-H...O=C bond. Our findings challenge the conventional understanding of H-bond dynamics and provide new insights into the structural stability of inter-helical protein interactions.

Although the effect of thermal modification (TM) on teak wood color is well documented, a few studies were carried out in closed system processes, as well as it remains unclear the effect of different processes on the same material. This work aimed to verify the effect of closed and open system processes of TM on the color of fast-growing teak wood. Thermally modified wood was evaluated in a closed system at 160 °C (CS160) and in an open system at 185 °C and 210 °C (OS185 and OS210). We measured the moisture content (initial and final) of wood, and the corrected mass loss (CML). The chemical analyses encompassed the contents of alpha-cellulose, hemicelluloses, lignin, and extractives (total, in acetone and dichloromethane). Wood color was measured before and after TM according to the CIEL*a*b* color space. It was possible to achieve the same color using different processes of thermal modification (CS160 and OS210). TM reduced wood lightness (L*), red-green chromaticity coordinate (a*), and yellow-blue chromaticity coordinate (b*). L* and a* had the bigger and lower variations, respectively. The color of thermally modified wood was significantly changed, even at the mildest condition tested (OS185, 0.33% CML).

2019-n-CoV is the seventh coronavirus known to infect humans and cause serious illness, and due to its lethality there was a worldwide mobilization for the development of new drugs and new vaccines for Covid-19. Therefore, the present work aims to carry out a virtual screening of terpenes with potential anti SARS-CoV-2 activity. To perform the ligand-based virtual, a model was constructed regarding the compounds which already showed inhibitory activity of the SARS-CoV-2. The test series corresponded to terpenes isolated in the Fabaceae Family. The compounds that were most likely to activity were subjected to Molecular Docking and the best poses obtained were subjected to Molecular Dynamics (MD) simulations carried. The molecules under study were submitted to in vitro evaluation to assess inhibitory activity of compounds against SARS-CoV-2 in a phenotypic screening model of the virus. The compounds selected by in silico screening corresponded to triterpenoids from the lupane series. In the in vitro test, both demonstrated activity against the SARS-CoV-2 virus. The virtual screening performed managed to identify the compounds with the highest probability of activity, as well as the most stable compounds, and the method used was validated by the in vitro study carried out.

Glutathione (GSH) and melatonin (MLT) are two antioxidants that have been described as having a protective role against oxidative stress in several animal species, improving sperm quality and survival after cryopreservation. Since there is no knowledge on the simultaneous use of these two substances concerning its effects on ram semen cryopreservation, this study aimed to evaluate the effects of MLT, GSH, or their association, on in vitro parameters of ram semen after thawing. During eight weekly sessions, the semen from three Merino rams was pooled, divided into four aliquots, and diluted with an egg yolk-based semen extender without (control) and with antioxidants (MLT 1mM, GSH 5mM, and MLT 1mM + GSH 5mM). Diluted semen was evaluated before and after freezing process. Supplementation of fresh semen with GSH at 5 mM had a deleterious effect on total motility progressive (TPM), curvilinear velocity (VCL), straight-line velocity (VSL), average-path velocity (VAP), linearity (LIN), straightness (STR) and increased slow spermatozoon (%). MLT at 1 mM also has a negative effect on TPM, VSL, and STR in fresh semen. In thawed semen, 1 mM of melatonin increased the TPM regarding the group control. Also, the combination of both antioxidants attenuates the negative effect of GSH 5mM on TPM, VSL and BCF. These results indicate that 5mM GSH impairs or does not improve sperm kinetic parameters in fresh semen and suggest that melatonin when combined with GSH plays a protective role on these effects.

Given the importance of menstrual blood in the pathogenesis of endometriosis and the multifunctional roles of menstrual mesenchymal stem cells (MenSCs) in regenerative medicine, this issue has gained prominence in the scientific community. Moreover, recent reviews highlight how robust the integrated assessment of omics data is for endometriosis. To our knowledge, no study has applied the multi-omics approaches to endometriosis MenSCs. It is a case-control study at a university-affiliated hospital. MenSCs transcriptome and proteome data were obtained by RNA-seq and UHPLC-MS/MS detection. Among the differentially expressed proteins and genes, we emphasize ATF3, ID1, ID3, FOSB, SNAI1, NR4A1, EGR1, LAMC3, and ZFP36 genes and MT2A, TYMP, COL1A1, COL6A2, and NID2 proteins that were already reported in the endometriosis. Our functional enrichment analysis reveals integrated modulating signaling pathways such as epithelial-mesenchymal transition (↑) and PI3K signaling via AKT to mTORC1 (↓in proteome), mTORC1 signaling, TGF beta signaling, TNFA signaling via NFkB, and response to hypoxia via HIF1A targets (↑in transcriptome). Our findings highlight primary changes in the endometriosis MenSCs, suggesting that the chronic inflammatory endometrial microenvironment can modulate these cells, providing opportunities for endometriosis etiopathogenesis. Moreover, they identify challenges for future research leveraging knowledge for regenerative and precision medicine in endometriosis.

Introduction: The purposes of this study were to seek for overall ratio (OR) and anterior ratio (AR) patients data in normal occlusion and Angle’s malocclusion studies, and to assess if such results support Bolton’s standards as general references. Methods: Pubmed, Medline, CENTRAL and Scholar databases were searched up to February 2018 (CRD42018088438). Gray literature was explored through OpenGray. Non-randomized clinical studies, published in English and assessing Bolton’s OR and AR in normal occlusion and Angle’s malocclusion groups (Class I, Class II, Class II division 1, Class 2 division 2, Class III) patients were included. OR and AR means and standard deviations (SD) were collected. Potential covariates (study design, publication year, country where the study was conducted, number of cases, gender, mesiodistal measurement method, and calibration method) were also extracted. The National Health Heart Lung, and Blood Institute’s Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used to assess each included studies quality. Pairwise Random-Effects and Multilevel Bayesian Network Meta-Analyses were used to synthesize available data. Results: Fifty-two observational studies were included (8872 participants; male/females 2674/3272; 16 studies lacked gender information). For normal occlusion, global pooled estimates for OR and AR means were 91.74% (95% CI: 91.37-92.10) and 78.24% (95% CI: 77.85-78.63), respectively. We could identify on Angle’s Class III patients meaningful OR and AR mean deviations from normal occlusion (0.89, 95% credible interval [CrI], 0.66-1.12, and 0.66, 95% CrI, 0.38-0.94, respectively), while on Class I patients we found a meaningful mean deviation from normal occlusion only for OR (0.25, 95% CrI, 0.03-0.47). Concerning gender impact, male patients presented higher OR (0.30, 95% CI 0.00-0.59) and AR (0.41, 95% CI 0.00-0.83) mean values than females in Class I. Conclusions: The results show that global pooled OR and AR mean values for normal occlusion patients are slightly above Bolton’s original values. Class I, for OR mean values, and Class III, for both OR and AR, are proportionally larger than normal occlusion patients. Gender had almost no impact on teeth mesiodistal proportion.