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Despite the huge potential of aquaculture in the Amazon, several producers have abandoned the activity due to a lack of assistance, technology, and innovation. Thus, the objective of this study was to identify factors that have contributed to the withdrawal of aquaculturists from the municipality of ‘Vigia de Nazaré’, state of Pará (Northern Region of Brazil). This case study took place in 2022 through a quanti-qualitative survey, applying structured questionnaires to former aquaculturists. A total of 30 fish farms were investigated, with 11 of them being abandoned. They are distributed across 10 rural communities that have developed fish farming, with ‘Vila de Itapuá’ (18.2%) being the most representative. When active, fish farming was practiced by men (100%) aged between 51 to 60 years (54.5%) with an incomplete primary education (100%), who carried out the activity for an average of 5 years (81.8%), quitting fish farming between the years 2019 and 2020 (72.7%). All former aquaculturists owned small properties, with excavated ponds in an extensive system and used family labor. The absence of technical assistance and the high cost of feed were pointed out as the main problems in the production chain. It is worth noting that the monoculture of Tambaqui (Colossoma macropomum) accounted for 63.6% of the species produced in rural communities. In conclusion, former aquaculturists express the desire to return to fish farming due to its socio-economic importance. For this, government actions supporting technical assistance and advanced studies in fish nutrition by educational, research, and extension institutions are necessary.

Enterococcus spp. are isolated from infections of domestic animals and can present resistance to different antimicrobials. This study aimed to identify the main species of Enterococcus and determine the phenotypic resistance to antimicrobials of isolates of this bacterial genus obtained from dogs and cats admitted to a veterinary hospital in southern Brazil. A total of 57 Enterococcus spp. were isolated from different clinical samples (urine, feces, ears and skin) in domestic animals admitted to the hospital over a period of three years (2016 to 2019). MALDI-TOF results demonstrated the occurrence of Enterococcus faecium (39; 68.4%), Enterococcus faecalis (17; 29.8%) and Enterococcus avium (1; 1.8%). In an overall analysis, resistance was observed to the antimicrobials rifampicin (46; 80.7%), tetracycline and streptomycin (42; 73.7%), ampicillin and imipenem (41; 71.9%), erythromycin (39; 68.4%), gentamicin (38; 66.7%), ciprofloxacin (36; 63.2%), norfloxacin (32; 56.1%), nitrofurantoin (10; 17.5%) and chloramphenicol (9; 15.7%). None of the Enterococcus spp. showed resistance to vancomycin and linezolid. Multidrug resistance (MDR) was detected in 45 (78.9%) isolates. In conclusion, E. faecium and E. faecalis with MDR are frequent in infections of hospitalized dogs and cats from southern Brazil.

The Salmonella enterica serovars Typhimurium (S. Typhimurium), Heidelberg (S. Heidelberg), and their monophasic variants (S. 1,4,[5],12:i:-, S. 1,4,[5],12:r:- and S. 1,4,[5],12:-:1,2) are highly disseminated in poultry farming and can contaminate chicken meat, eggs, and other foods of avian origin. A time-consuming bacteriological and serological analysis is usually required to identify serovars by traditional methods. Incomplete and inconclusive serological results are frequent in routine analysis, mainly due to the occurrence of bacterial isolates presenting similar antigenic profiles. Molecular biology assays have been developed to improve the detection of specific Salmonella serovars and strains. This study aimed to develop a multiplex real-time PCR (SHTAmp) for the rapid DNA detection of S. Typhimurium, S. Heidelberg, and their monophasic variants from poultry samples. The methodology was used in the analysis of 147 field isolates from Brazilian poultry flocks previously evaluated with serological analysis. The results demonstrated that it was able to specifically and rapidly detect 21 S. Typhimurium and 57 S. Heidelberg isolates with complete antigenic formulae. Furthermore, SHTAmp was able to differentiate nine S. Typhimurium and 44 S. Heidelberg isolates with incomplete serological formulae (monophasic and aphasic variants). The complete methodology was also successfully used to detect these bacteria directly from 34 poultry samples after pre-enrichment in buffered peptone water (BPW). In conclusion, SHTAmp is a fast and accurate method to detect the two frequent and concerning serovars S. Typhimurium and S. Heidelberg directly from poultry samples.

Leishmania infantum is a hemopathogen of importance for the health of domestic dogs (Canis lupus familiaris), causing canine leishmaniasis (CanL), and it is also the etiological agent of human visceral leishmaniasis (HVL). This parasite was not reported in southern Brazil until the early 2000s, but CanL and HVL were increasingly reported in the last 15 years, mainly in cities bordering Argentina. The present study aimed to detect L. infantum in domestic dogs and to determine the main clinical manifestations in infected animals from Uruguaiana, a city with a high incidence of CanL. Fifty-one dogs suspected of having CanL in the urban perimeter of the city were clinically examined by veterinarians and investigated for the occurrence of L. infantum with two immunoassays (rapid chromatography test and ELISA) and real-time PCR (polymerase chain reaction). Clinical signs were compared in positive and negative L. infantum animals. A total of 31 dogs (60.8%) were infected with L. infantum. The main clinical manifestations associated with CanL dogs were onychogryphosis and peeling (p < 0.05). L. infantum was frequently detected in urban dogs from Uruguaiana, highlighting the concerning situation regarding health in this city. The occurrence of some clinical signs (onychogryphosis/peeling) could help to detect CanL more frequently in the canine population.

Diabetic gastroparesis (DGP) delays gastric emptying in diabetes patients, notably impacting those with type 1 and long-standing type 2 diabetes. Symptoms include early satiety, fullness, appetite loss, bloating, abdominal pain, and vomiting, arising from slow stomach-to-intestine food movement. DGP’s unpredictable nature complicates diagnosis and blood glucose management, leading to severe complications like dehydration, malnutrition, and bezoar formation. Understanding DGP’s mechanisms is crucial for effective management. Vagal dysfunction, disturbances in the interstitial cells of Cajal, reduced neural nitric oxide synthase, and increased oxidative stress contribute to the complex pathophysiology. Accurate diagnosis demands a comprehensive approach, utilizing tools like gastric scintigraphy and the Gastric Emptying Breath Test. Considering the complex relationship between DGP and glycemia, managing blood glucose levels becomes paramount. Nutritional interventions, tailored to each patient, address malnutrition risks, emphasizing smaller, more frequent meals and liquid consistency. DGP’s complex nature necessitates collaborative efforts for enhanced diagnostic strategies, improved pathophysiological understanding, and compassionate management approaches. This comprehensive approach offers hope for a future where individuals with DGP can experience improved well-being and quality of life.

Microgrids have emerged as a crucial focus in power engineering and sustainable energy research, with utility-scale microgrids playing a significant role in both developed and developing countries like the Philippines. This study presents a comprehensive framework for utility-scale microgrid planning, emphasizing the sustainable integration of renewable energy resources to the distribution grid. The framework addresses the operational modes of grid-connected and islanded microgrids, emphasizing the seamless transition between these modes to ensure a continuous power supply. By leveraging local distributed energy resources, the microgrid aims to reduce dependence on the main transmission grid while enhancing resilience and reliability. The proposed planning framework not only eases the economic burden of constructing renewable energy sources but also aids distribution utilities in maximizing local resources to achieve sustainable energy goals. Through a detailed network analysis and modeling, the framework provides a robust foundation for optimizing the energy mix and enhancing the overall system performance. This research contributes to advancing microgrid technology as a key driver towards achieving UN Sustainable Development Goals, particularly in promoting clean and affordable energy access.

Type 2 diabetes mellitus (T2DM) is a prevalent chronic metabolic disorder characterized by insulin resistance and progressive beta cell dysfunction, presenting substantial global health and economic challenges. This review explores recent advancements in diabetes management, emphasizing novel pharmacological therapies and their physiological mechanisms. We highlight the transformative impact of Sodium-Glucose Cotransporter 2 inhibitor (SGLT2i) and Glucagon-Like Peptide 1 Receptor Agonist (GLP-1RA), which target specific physiological pathways to enhance glucose regulation and metabolic health. A key focus of this review is tirzepatide, a dual agonist of the glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 receptors. Tirzepatide illustrates how integrating innovative mechanisms with established physiological pathways can significantly improve glycemic control and support weight management. Additionally, we explore emerging treatments such as glimins and glucokinase activators (GKAs), which offer novel strategies for enhancing insulin secretion and reducing glucose production. We also address future perspectives in diabetes management, including the potential of retatrutide as a triple receptor agonist and evolving guidelines advocating for a comprehensive, multifactorial approach to care. This approach integrates pharmacological advancements with essential lifestyle modifications—such as dietary changes, physical activity, and smoking cessation—to optimize patient outcomes. By focusing on the physiological mechanisms of these new therapies, this review underscores their role in enhancing T2DM management and highlights the importance of personalized care plans to address the complexities of the disease. This holistic perspective aims to improve patient quality of life and long-term health outcomes.

Diabetes mellitus, which comprises a group of metabolic disorders affecting carbohydrate metabolism, is characterized by improper glucose utilization and excessive production, leading to hyperglycemia. The global prevalence of diabetes is rising, with projections indicating it will affect 783.2 million people by 2045. Insulin treatment is crucial, especially for type 1 diabetes, due to the lack of β-cell function. Intensive insulin therapy, involving multiple daily injections or continuous subcutaneous insulin infusion, has proven effective in reducing microvascular complications but poses a higher risk of severe hypoglycemia. Recent advancements in insulin formulations and delivery methods, such as ultra-rapid-acting analogs and inhaled insulin, offer potential benefits in terms of reducing hypoglycemia and improving glycemic control. However, the traditional subcutaneous injection method has drawbacks, including patient compliance issues and associated complications. Nanomedicine presents innovative solutions to these challenges, offering promising avenues for overcoming current drug limitations, enhancing cellular uptake, and improving pharmacokinetics and pharmacodynamics. Various nanocarriers, including liposomes, chitosan, and PLGA, provide protection against enzymatic degradation, improving drug stability and controlled release. These nanocarriers offer unique advantages, ranging from enhanced bioavailability and sustained release to specific targeting capabilities. While oral insulin delivery is being explored for better patient adherence and cost-effectiveness, other nanomedicine-based methods also show promise in improving delivery efficiency and patient outcomes. Safety concerns, including potential toxicity and immunogenicity issues, must be addressed, with the FDA providing guidance for the safe development of nanotechnology-based products. Future directions in nanomedicine will focus on creating next-generation nanocarriers with precise targeting, real-time monitoring, and stimuli-responsive features to optimize diabetes treatment outcomes and patient safety. This review delves into the current state of nanomedicine for insulin delivery, examining various types of nanocarriers and their mechanisms of action, and discussing the challenges and future directions in developing safe and effective nanomedicine-based therapies for diabetes management.

The dry stacking of filtered tailings is an option to deal with safety-related issues involving traditional slurry disposition in impoundments. Filtered tailings can be compacted to pre-define design specifications, which minimizes structural instability problems, such as those related to liquefaction. Yet, comprehending the tailing’s response under various stress states is essential to designing any dry stacking facility properly. Thus, the present research evaluated the mechanical response of cemented and uncemented compacted filtered iron ore tailings, considering different molding characteristics related to compaction degree and molding moisture content. Therefore, a series of one-dimensional compression tests and consolidated isotropically drained triaxial tests (CID), using 300 kPa and 3000 kPa effective confining pressures, were carried out for different specimens compacted at various molding characteristics. In addition, changes in gradation owing to both compression and shearing were evaluated using sedimentation with scanning electron microscope tests. The overall results have indicated that the 3% Portland cement addition enhanced the strength and stiffness of the compacted iron ore tailings, considering the lower confining pressure. Nevertheless, the same was not evidenced for the higher confining stress. Moreover, the dry-side molded specimens were initially stiffer, and significant particle breakage did not occur owing to one-dimensional compression but only due to shearing (triaxial condition).

In a conventional automotive manufacturing plant, the paint shop alone can represent 36% of the total energy consumption, making it the most demanding area in terms of electricity and fossil fuel energy consumption. This study explores the possibility of decentralizing the production of electrical power and heat simultaneously, using an Organic Rankine Cycle (ORC) system integrated with a Parabolic Trough Collector (PTC) in a paint shop. To date, no similar system has been explored or implemented by the automotive industry. To increase the efficiency of the integrated system, wasted heat generated during the paint manufacturing process is recovered and used to pre-heat the organic fluid in the ORC system. A 4E analysis (Energy, Exergy, Economic, and Environmental) is conducted to determine the practical viability of the proposed system. When applied to the southern region of the USA, this system’s installed capacity is projected to be 11 times higher than the two unique SORC pieces of equipment currently running in Louisiana and Florida. The goals are to reduce the reliance on external primary energy sources and decrease the carbon emission footprint from production activity. The system is evaluated for a location in Alabama, USA. The designed SORC, using toluene, can produce 712.2 kWel net and 13,132 kg/h of hot water, with an overall energy efficiency of 31.02%; exergy efficiency of 34.23; and ORC efficiency of 27.70%. This leads to an electrical energy saving of 5.9% for the manufacturing plant. The regenerative thermal oxidizer (RTO) heat exchanger, the secondary heat source of the system, has the highest exergy destruction—3583 kW. The system avoids the emission of 4521 tCO2 per year. A payback period of 10.16 years for the proposed system is estimated. Considering a planning horizon of 10 years, the investment in the system is also justified by a benefit–cost analysis.

Although walking methodologies (WMs) and machine learning (ML) have been objects of interest for urban scholars, it is difficult to find research that integrates both. We propose a ‘cyborg walk’ method and apply it to studying litter in public spaces. Walking routes are created based on an unsupervised learning algorithm (k-means) to classify public spaces. Then, a deep learning model (YOLOv5) is used to collect data from geotagged photos taken by an automatic Insta360 X3 camera worn by human walkers. Results from image recognition have an accuracy between 83.7% and 95%, which is similar to what is validated by the literature. The data collected by the machine are automatically georeferenced thanks to the metadata generated by a GPS attached to the camera. WMs could benefit from the introduction of ML for informative route optimisation and georeferenced visual data quantification. The links between these findings and the existing WM literature are discussed, reflecting on the parallels between this ‘cyborg walk’ experiment and the seminal cyborg metaphor proposed by Donna Haraway.

We describe a family of paraxial and quasi-monochromatic optical wave packets with finite energy and smoothly shaped amplitude in space and time that develops a singularity in the intensity when spatio-temporally focused by imparting a converging spherical wavefront and a negative temporal chirp. This singular behavior upon ideal focusing is manifested in actual focusing with finite apertures and in media with high-order dispersion with “exploding” behavior featuring an indefinitely increasing concentration of the energy when opening the aperture radius, thus exercising continuous control on the focal intensity and spatial and temporal resolution. These wave packets offer a new way of focusing that outperforms what can be achieved with standard Gaussian wave packets in terms of focal intensity and resolution, providing new possibilities in applications where energy concentration and its control are crucial.

The accurate detection of clouds is an important first step in the processing of remotely sensed satellite data analyses and subsequent cloud model predictions. While initial cloud retrieval technology began with the exploitation of one or two bands of satellite imagery, it has accelerated rapidly in recent years as sensor and retrieval technology, creating a new era in space observation exploration. Additionally, the initial emphasis in satellite retrieval technology focused on cloud detection for cloud forecast models, but more recently, cloud screening in satellite-acquired data is playing an increasingly critical role in the investigation of cloud-free data for the retrieval of soil moisture, vegetation cover, ocean color concentration and sea surface temperatures, as well as the environmental monitoring of a host of products, e.g., atmospheric aerosol data, to study the Earth’s atmospheric and climatic systems. With about 60% of the Earth covered by clouds, on average, it is necessary to accurately detect clouds in remote sensing data to screen cloud contaminate data in remote sensing analyses. In this review, the evolution of cloud-detection methodologies is highlighted with advancement in sensor hardware technology and machine learning algorithmic advances. The review takes into consideration the meteorological sensors usually used for atmospheric parameters estimation (thermodynamic profiles, aerosols, cloud microphysical parameters). Moreover, a discussion is presented on methods for obtaining the cloud-truth data needed to determine the accuracy of these cloud-detection approaches.

Thyroxine (T4) is a drug extensively utilized for the treatment of hypothyroidism. However, the oral absorption of T4 presents certain limitations. This research investigates the efficacy of CO2 nanobubbles in water as a potential oral carrier for T4 administration to C57BL/6 hypothyroid mice. Following 18 h of fasting, the formulation was administered to the mice, demonstrating that the combination of CO2 nanobubbles and T4 enhanced the drug’s absorption in blood serum by approximately 40%. To comprehend this observation at a molecular level, we explored the interaction mechanism through which T4 engages with the CO2 nanobubbles, employing molecular simulations, semi-empirical quantum mechanics, and PMF calculations. Our simulations revealed a high affinity of T4 for the water–gas interface, driven by additive interactions between the hydrophobic region of T4 and the gas phase and electrostatic interactions of the polar groups of T4 with water at the water–gas interface. Concurrently, we observed that at the water–gas interface, the cluster of T4 formed in the water region disassembles, contributing to the drug’s bioavailability. Furthermore, we examined how the gas within the nanobubbles aids in facilitating the drug’s translocation through cell membranes. This research contributes to a deeper understanding of the role of CO2 nanobubbles in drug absorption and subsequent release into the bloodstream. The findings suggest that utilizing CO2 nanobubbles could enhance T4 bioavailability and cell permeability, leading to more efficient transport into cells. Additional research opens the possibility of employing lower concentrations of this class of drugs, thereby potentially reducing the associated side effects due to poor absorption.

In regions heavily affected by recurrent typhoons, the need for more resilient electricity infrastructure is pressing. This emphasizes the importance of integrating resilience assessment, including incorporating resilience metrics, into the planning process of power distribution systems against any disruptive events. Although standardized metrics exist for assessing distribution system reliability, the absence of formalized resilience metrics hampers informed investments in critical infrastructure such as microgrid development. In this work, a set of resilience metrics is proposed by reconceptualizing reliability metrics. The metrics were formulated to account for both the type of extreme event and its specific impact on loads with varying levels of criticality. The effectiveness of the proposed metrics is demonstrated through a Philippine microgrid case study. A Monte Carlo framework incorporating an extreme event model, component fragility model, and system response model was used to quantify the resilience improvement before and after stand-alone microgrid operation of the power distribution system. Results show that the proposed metrics can effectively evaluate resilience enhancement and highlight the value of a holistic approach of considering critical loads and types of extreme events to strengthen societal and community resilience, making a compelling case for strategic investments in infrastructure upgrades such as microgrids.

The LABEXTRACT plant extract bank, featuring diverse members of the Myrtaceae family from Brazilian hot spot regions, provides a promising avenue for bioprospection. Given the pivotal roles of the Spike protein and 3CLpro and PLpro proteases in SARS-CoV-2 infection, this study delves into the correlations between the Myrtaceae species from the Atlantic Forest and these targets, as well as an antiviral activity through both in vitro and in silico analyses. The results uncovered notable inhibitory effects, with Eugenia prasina and E. mosenii standing out, while E. mosenii proved to be multitarget, presenting inhibition values above 72% in the three targets analyzed. All extracts inhibited viral replication in Calu-3 cells (EC50 was lower than 8.3 µg·mL−1). Chemometric analyses, through LC-MS/MS, encompassing prediction models and molecular networking, identified potential active compounds, such as myrtucommulones, described in the literature for their antiviral activity. Docking analyses showed that one undescribed myrtucommulone (m/z 841 [M − H]−) had a higher fitness score when interacting with the targets of this study, including ACE2, Spike, PLpro and 3CLpro of SARS-CoV-2. Also, the study concludes that Myrtaceae extracts, particularly from E. mosenii and E. prasina, exhibit promising inhibitory effects against crucial stages in SARS-CoV-2 infection. Compounds like myrtucommulones emerge as potential anti-SARS-CoV-2 agents, warranting further exploration.

Feline leukemia virus (FeLV) is a retrovirus distributed worldwide in domestic cats and with different outcomes (progressive, regressive, abortive, focal). The present study reports an epidemiological survey of FeLV frequency and the evaluation of some risk factors and the two main disease outcomes (progressive and regressive) in an urban cat population from Brazil. A total of 366 cats with sociodemographic information and p27 FeLV antigen test performed were included in the study. FeLV DNA (provirus) in the blood samples of all cats was detected via real-time polymerase chain reaction (qPCR). Plasma samples from 109 FeLV-positive and FeLV-negative cats were also submitted to reverse transcription (RT-qPCR) to determine the FeLV viral load. The results demonstrated that 112 (30.6%) cats were positive through the p27 antigen and/or qPCR. A risk factor analysis demonstrated that cats without vaccination against FeLV (OR 9.9, p < 0.001), clinically ill (OR 2.9, p < 0.001), with outdoors access (OR 2.7, p < 0.001), and exhibiting apathetic behavior (OR 3.1, p < 0.001) were more likely to be infected with FeLV. FeLV-infected cats were also more likely to present with anemia (OR 13, p < 0.001) and lymphoma (OR 13.7, p = 0.001). A comparative analysis of the different detection methods in a subset of 109 animals confirmed FeLV infection in 58 cats, including 38 (65.5%) with progressive, 16 (27.6%) with regressive, and 4 (6.9%) with probably focal outcome diseases. In conclusion, this study demonstrates a high prevalence of FeLV in this urban cat population from Brazil and highlights the need to establish more effective prevention strategies (such as viral testing, vaccination programs, specific care for FeLV-positive cats) to reduce diseases associated with this virus in Brazil.

Fish can tolerate prolonged periods of fasting more easily than endothermic organisms. However, these fasting periods are associated with pronounced lipid and protein catabolism and body weight loss. We evaluated the use of body reserves, growth performance, and the histology of the intestines and muscles of Colossoma macropomum subjected to prolonged fasting for 45 days and refeeding for 14 days. We used 66 juvenile C. macropomum (71.78 ± 10.75 g) distributed in 10 tanks of 100 L in a recirculating aquaculture system (RAS) and kept 6 fish in a separate tank, considered the basal group. The fish were divided into two groups: fed (continuously fed for 59 days) and fasted/refed (subjected to fasting for 45 days and subsequently refed for 14 days). The tambaqui juveniles showed the mobilization of their body reserves during 45 days of fasting but with a large deficit in their growth performance. The 14-day refeeding period was sufficient for fish to restore their energy but insufficient for recovering most growth parameters.

We previously demonstrated a beneficial effect of high-dose vitamin D in pregnancy on offspring bone and dental health. Here, we investigated the effect of maternal dietary patterns during pregnancy on the risk of bone fractures, bone mineralization and enamel defects until age 6 years in the offspring. Further, the influence of diet on the effect of high-dose vitamin D was analyzed in the COPSAC2010 mother–child cohort including 623 mother–child pairs. A weighted network analysis on FFQs revealed three specific maternal dietary patterns that associated (Bonferroni p < 0.05) with both offspring bone and dental health. The effect of prenatal high-dose (2800 IU/day) vs. standard-dose (400 IU/day) vitamin D on offspring bone mineral content (adjusted mean difference (aMD): 33.29 g, 95% CI: 14.48–52.09, p < 0.001), bone mineral density (aMD: 0.02 g/cm2 (0.01–0.04), p < 0.001), fracture risk (adjusted incidence rate ratio: 0.36 (0.16–0.84), p = 0.02), and enamel defects in primary (adjusted odds ratio (aOR): 0.13 (0.03–0.58), p < 0.01) and permanent molars (aOR: 0.25; (0.10–0.63), p < 0.01) was most pronounced when mothers had lower intake of fruit, vegetables, meat, eggs, sweets, whole grain, offal and fish. This study suggests that prenatal dietary patterns influence offspring bone and dental development, and should be considered in order to obtain the full benefits of vitamin D to enhance personalized supplementation strategy.

The Michaelis–Menten mechanism, which describes the binding of a substrate to an enzyme, is a simplification of the process on a molecular scale. A more detailed model should include the binding of the substrate to precatalytic binding sites (PCBSs) prior to the transition to the catalytic site. Our work shows that the incorporation of PCBSs, in steady-state conditions, generates a Michaelis–Menten-type expression, in which the kinetic parameters KM and Vmax adopt more complex expressions than in the model without PCBSs. The equations governing reaction kinetics can be seen as generalized symmetries, relative to time translation actions over the state space of the underlying chemical system. The study of their structure and defining parameters can be interpreted as looking for invariants associated with these time evolution actions. The expression of KM decreases as the number of PCBSs increases, while Vmax reaches a minimum when the first PCBSs are incorporated into the model. To evaluate the trend of the dynamic behavior of the system, numerical simulations were performed based on schemes with different numbers of PCBSs and six conditions of kinetic constants. From these simulations, with equal kinetic constants for the formation of the Substrate/PCBS complex, it is observed that KM and Vmax are lower than those obtained with the Michaelis–Menten model. For the model with PCBSs, the Vmax reaches a minimum at one PCBS and that value is maintained for all of the systems evaluated. Since KM decreases with the number of PCBSs, the catalytic efficiency increases for enzymes fitting this model. All of these observations are consistent with the general equation obtained. This study allows us to explain, on the basis of the PCBS to KM and Vmax ratios, the effect on enzyme parameters due to mutations far from the catalytic site, at sites involved in the first enzyme/substrate interaction. In addition, it incorporates a new mechanism of enzyme activity regulation that could be fundamental to search for new activity-modulating sites or for the design of mutants with modified enzyme parameters.

The search for alternatives that can replace conventional materials extracted from nature is crucial for environmental sustainability. This is especially the case for construction and geotechnical engineering, as this sector is a major consumer of the planet’s natural resources. This paper explores the use of ore sand (OS) tailings with fine aggregate characteristics, which are generated during exploration of iron ore and usually stored in stacks, in terms of their potential for replacing conventional aggregates (gravel, natural sand, and limestone sand) used in interlocking paving blocks for light-traffic pavement. A comparative life cycle assessment (LCA, cradle-to-gate) approach was applied for aggregates in interlocking blocks produced using OS compared to blocks produced with conventional aggregates. The OS was able to replace 24wt% of conventional aggregates (100% limestone sand and 13.3% natural sand), while maintaining compressive-strength performance similar to that of the conventional block (35 MPa). For all eleven environmental-impact categories evaluated in the LCA, the block with OS has improved environmental performance compared to the conventional block. Through the creation and use of a scoring indicator (SI), it was possible to determine that the transport distance of the OS is a limiting factor for the environmental efficiency of the alternative block. Nonetheless, the incorporation of OS mitigates the impacts of block production on eutrophication, acidification, fresh water, human toxicity, and abiotic depletion. The use of tailings reduces the demand for natural resources, decreasing the environmental impact of production and promoting sustainable construction practices.

(1) Background: Increasing evidence supports the anti-inflammatory and neuroprotective role of perampanel (PER), mediated by decreased expression of pro-inflammatory cytokines and by interference with apoptosis processes. Therefore, the use of PER to treat status epilepticus (SE) with suspected inflammatory etiology is appealing and deserves further investigation. (2) Methods: We retrospectively analyzed seven patients (five F, two M; median age: 62 years) with refractory and super-refractory SE due to a probable or defined inflammatory etiology and treated with PER. (3) Results: PER was administered as the third (4/7) or fourth drug (3/7), with a median loading dose of 32 mg/day (range: 16–36 mg/day) and a median maintenance dose of 10 mg/day (range: 4–12 mg/day). In five cases, SE was focal, while in two patients, it was generalized. SE was caused by systemic inflammation in three patients, while in the other four subjects, it was recognized to have an autoimmune etiology. SE resolution was observed after PER administration in all cases, particularly within 24 h in the majority of patients (4/7, 57.1%). (4) Conclusions: Our data support the efficacy of PER in treating SE when first- and second-line ASMs have failed and suggest a possible earlier use in SE cases that are due to inflammatory/autoimmune etiology.

pH regulation is essential to allow normal cell function, and their imbalance is associated with different pathologic situations, including cancer. In this study, we present the synthesis of 2-(((2-aminoethyl)imino)methyl)phenol (HL1) and the iron (III) complex (Fe(L1)2Br, (C1)), confirmed by X-ray diffraction analysis. The absorption and emission properties of complex C1 were assessed in the presence and absence of different physiologically relevant analytes, finding a fluorescent turn-on when OH− was added. So, we determined the limit of detection (LOD = 3.97 × 10−9 M), stoichiometry (1:1), and association constant (Kas = 5.86 × 103 M−1). Using DFT calculations, we proposed a spontaneous decomposition mechanism for C1. After characterization, complex C1 was evaluated as an intracellular pH chemosensor on the human primary gastric adenocarcinoma (AGS) and non-tumoral gastric epithelia (GES-1) cell lines, finding fluorescent signal activation in the latter when compared to AGS cells due to the lower intracellular pH of AGS cells caused by the increased metabolic rate. However, when complex C1 was used on metastatic cancer cell lines (MKN-45 and MKN-74), a fluorescent turn-on was observed in both cell lines because the intracellular lactate amount increased. Our results could provide insights about the application of complex C1 as a metabolic probe to be used in cancer cell imaging.

SARS-CoV-2 infection in children produces mild respiratory symptoms or no symptoms at all in most cases. Some pediatric patients develop a severe complication associated with high mortality, the multisystem inflammatory syndrome in children (MIS-C). In both scenarios, there are reports of neurological manifestations. This article aims to review the cases of pediatric patients with severe neurological issues and a coexisting positive SARS-CoV-2 test. A literature search was performed between March 2020 and May 2021. The results included the data from 41 studies, with 159 children with severe neurological manifestations, within an age range from 24 h to 17 years. The neurological disorders included 38 cases with stroke, 32 with encephalitis, 22 with encephalopathy, and 10 with Guillain–Barre syndrome. Sixty-five out of 159 cases with severe neurological manifestations were diagnosed with MIS-C. Direct neuroinvasion and the exaggerated immune response in some patients seem to be the most critical factors triggering these manifestations. Further research in the ongoing pandemic is needed to elucidate the precise mechanism.

Cyclic adenosine diphosphate ribose (cADPR) is a cyclic nucleotide involved in the Ca2+ homeostasis. In its structure, the northern ribose, bonded to adenosine through an N1 glycosidic bond, is connected to the southern ribose through a pyrophosphate bridge. Due to the chemical instability at the N1 glycosidic bond, new bioactive cADPR derivatives have been synthesized. One of the most interesting analogues is the cyclic inosine diphosphate ribose (cIDPR), in which the hypoxanthine replaced adenosine. The efforts for synthesizing new linear and cyclic northern ribose modified cIDPR analogues led us to study in detail the inosine N1 alkylation reaction. In the last few years, we have produced new flexible cIDPR analogues, where the northern ribose has been replaced by alkyl chains. With the aim to obtain the closest flexible cIDPR analogue, we have attached to the inosine N1 position a 2″,3″-dihydroxypentyl chain, possessing the two OH groups in a ribose-like fashion. The inosine alkylation reaction afforded also the O6-alkylated regioisomer, which could be a useful intermediate for the construction of new kinds of cADPR mimics.

The rapid emergence and spread of new variants of coronavirus type 2, as well as the emergence of zoonotic viruses, highlights the need for methodologies that contribute to the search for new pharmacological treatments. In the present work, we searched for new SARS-CoV-2 papain-like protease inhibitors in the PubChem database, which has more than 100 million compounds. Based on the ligand efficacy index obtained by molecular docking, 500 compounds with higher affinity than another experimentally tested inhibitor were selected. Finally, the seven compounds with ADME parameters within the acceptable range for such a drug were selected. Next, molecular dynamics simulation studies at 200 ns, ΔG calculations using molecular mechanics with generalized Born and surface solvation, and quantum mechanical calculations were performed with the selected compounds. Using this in silico protocol, seven papain-like protease inhibitors are proposed: three compounds with similar free energy (D28, D04, and D59) and three compounds with higher binding free energy (D60, D99, and D06) than the experimentally tested inhibitor, plus one compound (D24) that could bind to the ubiquitin-binding region and reduce the effect on the host immune system. The proposed compounds could be used in in vitro assays, and the described protocol could be used for smart drug design.

Salmonella infects poultry, and it is also a human foodborne pathogen. This bacterial genus is classified into several serovars/lineages, some of them showing high antimicrobial resistance (AMR). The ease of Salmonella transmission in farms, slaughterhouses, and eggs industries has made controlling it a real challenge in the poultry-production chains. This review describes the emergence, dissemination, and AMR of the main Salmonella serovars and lineages detected in Brazilian poultry. It is reported that few serovars emerged and have been more widely disseminated in breeders, broilers, and layers in the last 70 years. Salmonella Gallinarum was the first to spread on the farms, remaining as a concerning poultry pathogen. Salmonella Typhimurium and Enteritidis were also largely detected in poultry and foods (eggs, chicken, turkey), being associated with several human foodborne outbreaks. Salmonella Heidelberg and Minnesota have been more widely spread in recent years, resulting in frequent chicken/turkey meat contamination. A few more serovars (Infantis, Newport, Hadar, Senftenberg, Schwarzengrund, and Mbandaka, among others) were also detected, but less frequently and usually in specific poultry-production regions. AMR has been identified in most isolates, highlighting multi-drug resistance in specific poultry lineages from the serovars Typhimurium, Heidelberg, and Minnesota. Epidemiological studies are necessary to trace and control this pathogen in Brazilian commercial poultry production chains.

Triple-negative breast cancer (TNBC) is an aggressive cancer with limited targeted therapies. RNA aptamers, suitably chemically modified, work for therapeutic purposes in the same way as antibodies. We recently generated 2′Fluoro-pyrimidines RNA-aptamers that act as effective recognition elements for functional surface signatures of TNBC cells. Here, we optimized three of them by shortening and proved the truncated aptamers as optimal candidates to enable active targeting to TNBC. By using prediction of secondary structure to guide truncation, we identified structural regions that account for the binding motifs of the full-length aptamers. Their chemical synthesis led to short aptamers with superb nuclease resistance, which specifically bind to TNBC target cells and rapidly internalize into acidic compartments. They interfere with the growth of TNBC cells as mammospheres, thus confirming their potential as anti-tumor agents. We propose sTN145, sTN58 and sTN29 aptamers as valuable tools for selective TNBC targeting and promising candidates for effective treatments, including therapeutic agents and targeted delivery nanovectors.

Endoxylanases belonging to family 10 of the glycoside hydrolases (GH10) are versatile in the use of different substrates. Thus, an understanding of the molecular mechanisms underlying substrate specificities could be very useful in the engineering of GH10 endoxylanases for biotechnological purposes. Herein, we analyzed XynA, an endoxylanase that contains a (β/α)8-barrel domain and an intrinsically disordered region (IDR) of 29 amino acids at its amino end. Enzyme activity assays revealed that the elimination of the IDR resulted in a mutant enzyme (XynAΔ29) in which two new activities emerged: the ability to release xylose from xylan, and the ability to hydrolyze p-nitrophenyl-β-d-xylopyranoside (pNPXyl), a substrate that wild-type enzyme cannot hydrolyze. Circular dichroism and tryptophan fluorescence quenching by acrylamide showed changes in secondary structure and increased flexibility of XynAΔ29. Molecular dynamics simulations revealed that the emergence of the pNPXyl-hydrolyzing activity correlated with a dynamic behavior not previously observed in GH10 endoxylanases: a hinge-bending motion of two symmetric regions within the (β/α)8-barrel domain, whose hinge point is the active cleft. The hinge-bending motion is more intense in XynAΔ29 than in XynA and promotes the formation of a wider active site that allows the accommodation and hydrolysis of pNPXyl. Our results open new avenues for the study of the relationship between IDRs, dynamics and activity of endoxylanases, and other enzymes containing (β/α)8-barrel domain.

Failures of tailings dams, primarily due to liquefaction, have occurred in Brazil in recent years. These events have prompted the Brazilian government to place restrictions on the construction of new dams, as iron ore tailings deposited behind upstream dams by spigotting have been shown to have low in situ densities and strengths and are prone to failure. This work proposes a new trend for tailings disposal: stacking compacted filtered ore tailings–Portland cement blends. As part of the proposal, it analyses the behaviour of compacted iron ore tailings–Portland cement blends, considering the use of small amounts of Portland cement under distinct compaction degrees. With the intention of evaluating the stress–strain–strength–durability behaviour of the blends, the following tests were carried out: unconfined compression tests; pulse velocity tests; wetting–drying tests; and standard drained triaxial compression tests with internal measurement of strains. This is the first study performed to determine the strength and initial shear stiffness evolution of iron ore tailings–Portland cement blends during their curing time, as well friction angle and cohesion intercept. This manuscript postulates an analysis of original experimental results centred on the porosity/cement index (η/Civ). This index can help select the cement quantity and density for important design parameters of compacted iron ore tailings–cement blends required in geotechnical engineering projects such as the proposed compacted filtered iron ore tailings–cement blends stacking.

Dynamic numerical models of the atmosphere are the main tools used for weather and climate forecasting as well as climate projections. Thus, this work evaluated the systematic errors and areas with large uncertainties in precipitation over the South American continent (SAC) based on regional climate simulations with the weather research and forecasting (WRF) model. Ten simulations using different convective, radiation, and microphysical schemes, and an ensemble mean among them, were performed with a resolution of 50 km, covering the CORDEX-South America domain. First, the seasonal precipitation variability and its differences were discussed. Then, its annual cycle was investigated through nine sub-domains on the SAC (AMZN, AMZS, NEBN, NEBS, SE, SURU, CHAC, PEQU, and TOTL). The Taylor Diagrams were used to assess the sensitivity of the model to different parameterizations and its ability to reproduce the simulated precipitation patterns. The results showed that the WRF simulations were better than the ERA-interim (ERAI) reanalysis when compared to the TRMM, showing the added value of dynamic downscaling. For all sub-domains the best result was obtained with the ensemble compared to the satellite TRMM. The largest errors were observed in the SURU and CHAC regions, and with the greatest dispersion of members during the rainy season. On the other hand, the best results were found in the AMZS, NEBS, and TOTL regions.

The increasingly strong search for alternative materials to Portland cement has resulted in the development of alkali-activated cements (AAC) that are very effective at using industrial by-products as raw materials, which also contributes to the volume reduction in landfilled waste. Several studies targeting the development of AAC—based on wastes containing silicon and calcium—for chemical stabilization of soils have demonstrated their excellent performance in terms of durability and mechanical performance. However, most of these studies are confined to a laboratory characterization, ignoring the influence and viability of the in situ construction process and, also important, of the in situ curing conditions. The present work investigated the field application of an AAC based on carbide lime and glass wastes to stabilize fine sand acting as a superficial foundation. The assessment was supported on the unconfined compressive strength (UCS) and initial shear modulus (G0) of the developed material, and the field results were compared with those prepared in the laboratory, up to 120 days curing. In situ tests were also developed on the field layers (with diameters of 450 and 900 mm and thickness of 300 mm) after different curing times. To establish a reference, the mentioned precursors were either activated with a sodium hydroxide solution or hydrated with water (given the reactivity of the lime). The results showed that the AAC-based mixtures developed greater strength and stiffness at a faster rate than the water-based mixtures. Specimens cured under controlled laboratory conditions showed better results than the samples collected in the field. The inclusion of the stabilized layers clearly increased the load-bearing capacity of the natural soil, while the different diameters produced different failure mechanisms, similar to those found in Portland cement stabilization.

Based on the behavior of living beings, which react mostly to external stimuli, we introduce a neural-network model that uses external patterns as a fundamental tool for the process of recognition. In this proposal, external stimuli appear as an additional field, and basins of attraction, representing memories, arise in accordance with this new field. This is in contrast to the more-common attractor neural networks, where memories are attractors inside well-defined basins of attraction. We show that this procedure considerably increases the storage capabilities of the neural network; this property is illustrated by the standard Hopfield model, which reveals that the recognition capacity of our model may be enlarged, typically, by a factor 102. The primary challenge here consists in calibrating the influence of the external stimulus, in order to attenuate the noise generated by memories that are not correlated with the external pattern. The system is analyzed primarily through numerical simulations. However, since there is the possibility of performing analytical calculations for the Hopfield model, the agreement between these two approaches can be tested—matching results are indicated in some cases. We also show that the present proposal exhibits a crucial attribute of living beings, which concerns their ability to react promptly to changes in the external environment. Additionally, we illustrate that this new approach may significantly enlarge the recognition capacity of neural networks in various situations; with correlated and non-correlated memories, as well as diluted, symmetric, or asymmetric interactions (synapses). This demonstrates that it can be implemented easily on a wide diversity of models.

The scope of this work was to evaluate simulated carbon monoxide (CO) and aerosol optical depth (AOD) from the CAM-chem model against observed satellite data and additionally explore the empirical relationship of CO, AOD and fire radiative power (FRP). The simulated seasonal global concentrations of CO and AOD were compared, respectively, with the Measurements of Pollution in the Troposphere (MOPITT) and the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite products for the period 2010–2014. The CAM-chem simulations were performed with two configurations: (A) tropospheric-only; and (B) tropospheric with stratospheric chemistry. Our results show that the spatial and seasonal distributions of CO and AOD were reasonably reproduced in both model configurations, except over central China, central Africa and equatorial regions of the Atlantic and Western Pacific, where CO was overestimated by 10–50 ppb. In configuration B, the positive CO bias was significantly reduced due to the inclusion of dry deposition, which was not present in the model configuration A. There was greater CO loss due to the chemical reactions, and shorter lifetime of the species with stratospheric chemistry. In summary, the model has difficulty in capturing the exact location of the maxima of the seasonal AOD distributions in both configurations. The AOD was overestimated by 0.1 to 0.25 over desert regions of Africa, the Middle East and Asia in both configurations, but the positive bias was even higher in the version with added stratospheric chemistry. By contrast, the AOD was underestimated over regions associated with anthropogenic activity, such as eastern China and northern India. Concerning the correlations between CO, AOD and FRP, high CO is found during March–April–May (MAM) in the Northern Hemisphere, mainly in China. In the Southern Hemisphere, high CO, AOD, and FRP values were found during August–September–October (ASO) due to fires, mostly in South America and South Africa. In South America, high AOD levels were observed over subtropical Brazil, Paraguay and Bolivia. Sparsely urbanized regions showed higher correlations between CO and FRP (0.7–0.9), particularly in tropical areas, such as the western Amazon region. There was a high correlation between CO and aerosols from biomass burning at the transition between the forest and savanna environments over eastern and central Africa. It was also possible to observe the transport of these pollutants from the African continent to the Brazilian coast. High correlations between CO and AOD were found over southeastern Asian countries, and correlations between FRP and AOD (0.5–0.8) were found over higher latitude regions such as Canada and Siberia as well as in tropical areas. Higher correlations between CO and FRP are observed in Savanna and Tropical forests (South America, Central America, Africa, Australia, and Southeast Asia) than FRP x AOD. In contrast, boreal forests in Russia, particularly in Siberia, show a higher FRP x AOD correlation than FRP x CO. In tropical forests, CO production is likely favored over aerosol, while in temperate forests, aerosol production is more than CO compared to tropical forests. On the east coast of the United States, the eastern border of the USA with Canada, eastern China, on the border between China, Russia, and Mongolia, and the border between North India and China, there is a high correlation of CO x AOD and a low correlation between FRP with both CO and AOD. Therefore, such emissions in these regions are not generated by forest fires but by industries and vehicular emissions since these are densely populated regions.