De Souza

Accurate estimation of river discharge is fundamental for water resources management, flood forecasting, and drought monitoring in the Amazon River Basin. Rating curves, which relate water level (stage) to discharge, are the primary tool for streamflow estimation. This study evaluates traditional curve-fitting methods and machine learning algorithms for modeling rating curves at the two largest gauging stations in the Amazon River: Itacoatiara and Óbidos. The analysis is based on 70 stage–discharge measurements at Itacoatiara (2008–2023) and 176 measurements at Óbidos (1968–2023). Five modeling approaches were compared: Power Law, Linear Regression, Decision Tree, Random Forest, XGBoost, and Multi-Layer Perceptron (MLP). Model performance was assessed against official baseline rating curves maintained by Brazil’s National Water Agency (ANA) and the Geological Survey of Brazil (SGB/CPRM) using Root Mean Square Error (RMSE), coefficient of determination (r2), Mean Bias Error (MBE), Nash–Sutcliffe Efficiency (NSE) and Kling–Gupta Efficiency (KGE). Results indicate that ensemble-based machine learning methods, particularly XGBoost (RMSE = 7463 m3/s, NSE = 0.973 at Itacoatiara; RMSE = 18,378 m3/s, NSE = 0.872 at Óbidos), outperformed traditional methods. However, the Decision Tree exhibited overfitting that could not be resolved through pruning, depth limitation, or other strategies given the sample size. Traditional methods such as the optimized Power Law remain practical and transparent alternatives for operational use. The findings suggest that machine learning can complement traditional approaches for improving rating curve accuracy in large tropical rivers, with K-fold cross-validation used to assess variability and performance.

Fluoroquinolones are known for their antibacterial properties, but recent research has revealed their potential to inhibit the growth and proliferation of cancer cells. Thus, this study aimed to emphasize the repositioning and potential of fluoroquinolones as possible therapeutic tools in the fight against cancer, opening up new perspectives for the field of oncology. Thus, this paper consists of a descriptive literature review of recent studies published between 2013 and 2023 on the use of fluoroquinolones in anticancer therapy. The results indicate that fluoroquinolones can interfere with the cell cycle, induce apoptosis and oxidative stress, and impact factors associated with tumorigenesis, such as the transcription of ectopic expression of SNAI1 for epithelial–mesenchymal transition. In addition, studies show that combining fluoroquinolones with other antineoplastic agents can increase their efficacy, and the possibility of encapsulating these drugs in controlled-release systems is also emerging as a promising antitumor strategy. In conclusion, repositioning fluoroquinolones in antitumor therapy presents an expanding field of research, offering new perspectives for cancer treatment. However, more studies are needed to fully elucidate their potential and establish effective clinical use protocols.

Background: Diets composed of various components have been shown to influence inflammatory diseases such as asthma. While most studies have focused on fiber-rich diets to investigate their effects on the immune system and, consequently, on asthma, little is known about the impact of sugar-rich diets, particularly when such diets are consumed over short periods of time. Methods: To investigate the short-term effects of a sugar-rich diet on allergic airway inflammation, A/J mice were fed either a standard diet or a sugar-enriched diet and subsequently sensitized and challenged with ovalbumin or PBS. Airway inflammation was assessed by bronchoalveolar lavage (BAL) cell analysis, including eosinophil counts and cytokine levels (IL-4, TNF-α, IL-33), and by lung histology (H&E for inflammatory infiltrate and PAS for mucus). Serum IgE levels were also measured. In addition, glucose tolerance, visceral and subcutaneous adipose tissue mass, and inflammatory markers in visceral adipose tissue were evaluated. Results: Short-term consumption of a sugar-rich diet induced glucose intolerance and expansion of adipose tissue, particularly visceral fat, independent of ovalbumin sensitization. Gonadal adipose tissue analysis revealed a shift toward M1 macrophage polarization, characterized by elevated TNF-α, IL-6, and IL-1β, increased leptin levels, and reduced adiponectin. In OVA-sensitized mice, the sugar-rich diet significantly exacerbated eosinophil infiltration in BAL, increased IL-4, TNF-α, and IL-33, and enhanced PAS-positive mucus accumulation and inflammatory infiltrates in the lung. Moreover, total serum IgE was significantly higher in allergic mice fed the sugar-rich diet compared with allergic mice on the standard diet. Importantly, in non-sensitized mice fed the sugar-rich diet, no pulmonary inflammation was detected by BAL, demonstrating that HSD alone does not induce asthma but amplifies allergic responses when sensitization is present. Conclusions: Our findings demonstrate that short-term consumption of a sugar-rich diet is sufficient to exacerbate, but not initiate, allergic pulmonary inflammation. From a translational perspective, reducing dietary sugar intake may represent a valuable adjuvant strategy in the management of allergic asthma.

Artificial intelligence is increasingly used to support decision-making during hydrocarbon exploration drilling, but mud-gas interpretation remains challenging because gas signatures are influenced by mud properties, drilling parameters, degassing efficiency, and Drill Bit Metamorphism (DBM). Here, we present a machine-learning-assisted workflow for assessing how well reservoir-fluid signals are represented in Advanced Gas (AG) measurements acquired while drilling. A multi-domain dataset from 104 Brazilian exploration wells was quality controlled, harmonized, and integrated with laboratory pressure-volume-temperature (PVT) fluid compositions and expert geological interpretation. Two predictive products were developed: Reservoir Affinity Curves, which estimate the similarity between AG signatures and reference PVT fluids using C2- and C2C-based targets, and a DBM Severity Curve, which quantifies drilling-induced thermal alteration using ethylene-related behavior and operational variables. Kernel Ridge Regression was selected as the primary deployment model because it produced stable, smooth, and interpretable depth-dependent predictions, whereas XGBoost and LightGBM achieved the highest numerical accuracy as benchmark models. The workflow distinguished intervals dominated by representative formation-fluid signatures from zones affected by DBM or other operational artifacts. This approach supports earlier fluid characterization, improves fluid-sampling decisions, and reduces interpretation uncertainty before laboratory results become available.

The pathogenicity of P. aeruginosa is not only mediated by its resistance mechanisms but also by its ability to form persister cells. The persister state is a transient condition in which cells retain a dormant, non- or slow-growing state during exposure to stressors, such as high doses of bactericidal antibiotics, but can resume growth once the stress is removed. In this study, we investigated in vitro the virulence phenotype and stress-induced modulation of persisters in P. aeruginosa PA14 exposed to 30 × the minimum inhibitory concentration (MIC) of imipenem (60 µg/mL) or ciprofloxacin (3.75 µg/mL). Using a biphasic killing assay, we detected persisters with survival levels of 4.8 and 3.4 log10 CFU/mL at 24 h for imipenem and ciprofloxacin, respectively. MIC assays confirmed the absence of acquired resistance. Flow cytometry revealed a time-dependent accumulation of cells with intermediate redox activity and membrane integrity, consistent with the persister phenotype. Both planktonic and biofilm-associated populations harbored persisters, with biofilms exhibiting a greater amount of tolerant cells. Furthermore, persister cells displayed reduced pigment production, biofilm formation, and phagocytosis survival. Gene expression analysis revealed upregulation of higB and pqsA in persisters, along with distinct profiles in recovered cells. Pre-exposure to hydrogen peroxide (H2O2; 0.4%) increased survival by > 1 log10 following antibiotic treatment. Additionally, pretreatment with 5-fluorouracil (5-FU; 256 µg/mL) increased imipenem persistence by twofold. Altogether, our findings show that oxidative and genotoxic stresses promote persistence, and that macrophage interactions modulate persister physiology, offering insight into host–pathogen dynamics and potential therapeutic avenues.

A rapid and effective method to identify disease-specific antibodies from clinical patients is important for understanding autoimmune diseases and for the development of effective disease therapies. In neuromyelitis optica (NMO), the identification of antibodies targeting the aquaporin-4 (AQP4) membrane protein traditionally involves the labor-intensive and time-consuming process of single B-cell sorting, followed by antibody cloning, expression, purification, and analysis for anti-AQP4 activity. To accelerate patient-specific antibody discovery, we compared two unique approaches for screening anti-AQP4 antibodies from yeast antibody surface display libraries. Our first approach, cell-based biopanning, has strong advantages for its cell-based display of native membrane-bound AQP4 antigens and is inexpensive and simple to perform. Our second approach, FACS screening using solubilized AQP4 antigens, permits real-time population analysis and precision sorting for specific antibody binding parameters. We found that both cell-based biopanning and FACS screening were effective for the enrichment of AQP4-binding clones. These screening techniques will enable library-scale functional interrogation of large natively paired antibody libraries for comprehensive analysis of anti-AQP4 antibodies in clinical samples and for robust therapeutic discovery campaigns.

Background Gestational anemia remains an important public health problem, especially in developing countries, and is associated with adverse maternal and perinatal outcomes. Prophylactic iron supplementation during pregnancy is a simple and effective strategy to prevent this condition and is routinely recommended during prenatal care. In Brazil, supplements are provided free of charge through the public health system; however, adherence to treatment remains variable. This study aimed to identify the sociodemographic and healthcare-related factors associated with inadequate iron supplementation among pregnant women receiving care in the public health system. Methods This cross-sectional study was conducted between March 2023 and May 2024 at the Maternity Unit of the Irmandade da Santa Casa de Misericórdia de São Paulo, a quaternary teaching hospital located in São Paulo, Brazil, and a reference center for obstetric care within the Brazilian Unified Health System (SUS). Women aged ≥ 18 years who were evaluated within 24 h after delivery were eligible. The exclusion criteria included fetal death, multiple pregnancies, and the presence of major fetal malformations. Data, including sociodemographic information, clinical history, prenatal care characteristics, and iron supplementation during pregnancy, were obtained through a structured questionnaire administered during the immediate postpartum period. Results A total of 381 patients were included. Overall, 176 women (46.2%) had adequate iron supplementation during pregnancy and 205 (53.8%) had inadequate supplementation. Among the variables analyzed, drug use during pregnancy was the only sociodemographic factor that was significantly associated with inadequate iron supplementation (p = 0.001 crude OR 2.93, 95% CI 1.57–5.48). A trend toward greater adherence was observed among pregnant women followed exclusively within the public health system than among those receiving private, mixed, or overseas prenatal care, although this difference was not statistically significant. In multivariable logistic regression, self-reported drug use (aOR 2.54, 95% CI 1.33–4.87; p = 0.005), non-use of other vitamins during pregnancy (aOR 6.00, 95% CI 2.45–14.72; p < 0.001) and inadequate prenatal care (aOR 0.49 for adequate vs. inadequate prenatal care, 95% CI 0.25–0.94; p = 0.033) remained independently associated with inadequate iron supplementation. Conclusions Inadequate iron supplementation during pregnancy is associated mainly with social and behavioral vulnerability, particularly drug use. These findings suggest that adherence depends not only on the availability of supplements but also on the quality of prenatal care and professional guidance. Public health strategies aimed at health education, strengthening primary care, and longitudinal follow-up of pregnant women may contribute to improving adherence and reducing the prevalence of gestational anemia.

This study proposes a computational model based on the finite element method (FEM) to simulate the thermomechanical behavior of C-Mn steel under continuous cooling. Hot torsion tests were conducted at temperatures from 900 to 1100 °C, with strain rates of 0.1, 1.0, and 10 s−1, and a strain of $$\varepsilon$$ ε = 6.0, using an infrared radiation furnace, argon gas shielding, and a chromel–alumel K-type thermocouple. The experimental data were implemented in DEFORM™3D to formulate equations for dynamic recrystallization ( $${\varepsilon}_{0.5}$$ ε 0.5 , $${X}_{\text{D}\text{R}\text{X}}$$ X DRX ) and recrystallized grain size ( $${d}_{\text{D}\text{R}\text{X}}$$ d DRX ), yielding good agreement with DRX kinetic models and accurate numerical predictions. The results show that recrystallization time increases as temperature decreases, while strain-induced precipitation (SIP) begins after the seventh pass. Small variations in rolling temperature altered the microstructure and average grain size, emphasizing the need for strict process control. These findings confirm that controlled rolling is essential to prevent heterogeneous grain-size distributions that may impair mechanical performance. The main contribution of this study is the development of a thermomechanical computational model capable of evaluating a wide range of processing parameter combinations with high efficiency and reduced experimental effort, enabling accurate prediction of microstructural evolution during hot rolling.

This study aimed to evaluate the impact of increasing de-oiled wet distillers grains (WDG) inclusion on the structure, diversity, and composition of the ruminal bacterial community in Nellore cattle fed high-concentrate diets. Four ruminally cannulated Nellore bulls were assigned to a 4 × 4 Latin square design and fed diets containing 0, 150, 300, or 450 g de-oiled WDG/kg dry matter. Ruminal samples were collected for bacterial DNA extraction and 16S rRNA gene amplicon sequencing to assess alpha diversity, beta diversity, and taxonomic composition. Increasing dietary inclusion of de-oiled WDG did not affect bacterial richness (P = 0.35) or overall community structure (P = 0.26). Permutational multivariate analysis of variance revealed no significant treatment effects on bacterial community structure (P > 0.05), indicating high microbial stability across diets. Relative abundance analysis showed that Firmicutes and Bacteroidetes remained the dominant phyla across all treatments, with no significant differences detected after multiple-testing correction (P > 0.05). Exploratory analyses identified a limited number of taxa contributing to between-treatment dissimilarities, mainly affiliated with Firmicutes, Bacteroidetes, Verrucomicrobia, and Chloroflexi; however, none of these differences remained significant after false discovery rate adjustment. Overall, increasing inclusion of de-oiled WDG in high-concentrate diets did not induce substantial shifts in the ruminal bacterial community. These findings suggest that the rumen microbiome of feedlot Nellore cattle is resilient to dietary replacement of conventional ingredients with de-oiled WDG up to 450 g/kg DM, supporting its practical application as a sustainable coproduct in intensive beef production systems without compromising microbial ecosystem stability.