Pará State University (Portuguese: Universidade do Estado do Pará, UEPA) is the only public university maintained by the state government of Pará, Brazil. The university has over 14,000 students enrolled in its 57 courses, from which 23 are undergraduate and 34 are graduate programs. Those programs are offered across UEPA's 20 campuses in the cities of Belém (five campuses), Paragominas, Conceição do Araguaia, Marabá, Altamira, Igarapé-Açu, São Miguel do Guamá, Santarém, Tucuruí, Moju, Redenção, Barcarena, Vigia de Nazaré, Cametá, Salvaterra, and Castanhal..
Microplastic pollution has become pervasive across freshwater ecosystems worldwide, including the Amazon Basin, where increasing levels of plastic contamination have been reported. Despite growing evidence of microplastic (MP) ingestion in aquatic organisms, studies focusing on threatened species remain extremely scarce, particularly for estuarine elasmobranchs. Rays present high extinction risk among vertebrates and in majority are apex predators, which enhance direct interaction with MPs. The present study investigated, for the first time, MPs ingestion by threatened stingray species from the Amazon Estuary, assessing particles' occurrence and characteristics. Twelve individuals belonging to four elasmobranch species, incidentally caught by artisanal fisheries in Marajó Bay, were examined. Microplastics were detected in all specimens, totaling 181 particles. Fibers predominated (97%), followed by fragments (3%), with black (30.9%) and blue (30.4%) being the most frequent colors. Raman spectroscopy identified Polyester and Polyamide (Nylon) as the dominant polymers (25% each), followed by Polyethylene, Polypropylene, and Polyurethane (16.7% each), a polymer composition consistent with the major anthropogenic plastic previously reported in the Amazon Basin. Although ingestion levels varied considerably among individuals and species, contamination was ubiquitous. This study provides the first record of microplastic occurrence for the stingray species investigated, expanding current knowledge of plastic exposure in threatened Amazonian elasmobranchs. By establishing a baseline for future monitoring, our findings support the incorporation of plastic pollution into conservation assessments of threatened freshwater and estuarine rays.
OBJECTIVE:To analyze the social representations of people with pulmonary tuberculosis regarding humanization of care in Primary Healthcare. METHOD:This descriptive, qualitative study is based on the Social Representation Theory's procedural approach. It was conducted in four Family Health Units in Belém, Pará, Brazil, with 30 individuals undergoing treatment for pulmonary tuberculosis. Between March and June 2022, individual semi-structured interviews were conducted, the corpus of which was submitted to the Analyse Lexicale par Contexte d'un Ensemble de Segments de Texte (version 2012) software. RESULTS:The corpus was divided into 470 Elementary Context Units, using 363 (77.23%). Five lexical classes were generated, with classes 2 and 3 standing out for highlighting the social representations of the topic. This context supported humanization of care by a sense of trust and good treatment, despite the limitations of the physical structure and material resources of the health units. CONCLUSION:Human relationships are important in care activities, especially given the challenges of multidisciplinary work in Primary Healthcare, encouraging the development and strengthening of bonds between teams and patients.
The aim of this study was to investigate the seasonal and circadian dynamics of the essential oil (EO) of Ageratum conyzoides (purple-inflorescence chemotype) and its relationship with acaricidal activity against Rhipicephalus microplus. Seasonal collections were performed monthly at 6 a.m. throughout 2023, while circadian profiles were obtained at 6, 9, and 12 a.m., and 3 and 6 p.m. in April (rainy season) and October (dry season). The EO was extracted by hydrodistillation, characterized by GC-MS, and evaluated using the larval immersion test. Yields ranged from 0.03% to 0.24% (v/w), with lower and more stable values in the rainy season and higher values in the dry season. A total of 96 constituents were identified, representing 89.62% of the oil composition, with predominance of sesquiterpenes. Major compounds included caryophyllene oxide, spathulenol, humulene epoxide II, α-cadinol, α-santalene, β-elemene, and p-cymene. Acaricidal activity varied markedly between seasons. Rainy-season samples showed low larval mortality across all concentrations, preventing LC₅₀ determination. In contrast, dry-season samples exhibited consistent activity, with LC₅₀ = 130 µg/mL. This enhanced activity was associated with a higher proportion of oxygenated sesquiterpenes, particularly spathulenol. Circadian variation had a secondary effect; however, early morning collections (6 a.m.) during the dry season showed greater chemical stability and improved biological response. These findings indicate that seasonal variation significantly influences the acaricidal efficacy of A. conyzoides EO, and that collection during dry periods and early morning may improve reproducibility and effectiveness for tick control applications.
Neglected infectious diseases (NIDs) remain a major public health challenge in the Amazon, particularly among quilombola populations living in rural and riverside territories marked by historical inequalities and structural limitations. This study examined the occurrence of NIDs in eight quilombola communities in the Lower Amazon, identified socioenvironmental factors associated with these conditions, and evaluated the performance of machine learning models in predicting individual risk of illness. This analytical cross-sectional study included 518 participants, with data collected through a structured questionnaire. Descriptive and bivariate analyses were conducted, followed by multivariable logistic regression, Poisson regression, cluster analysis, and predictive modeling using Random Forest, XGBoost, and Logistic Regression. Spatial analysis was performed in Google Colab. The overall prevalence of at least one NID was 34.7%. Lack of sanitation facilities, use of river or well water, precarious housing, inadequate waste disposal, low income, and residence in rural areas were significantly associated with both the occurrence and number of NIDs per individual. XGBoost and Random Forest achieved the best predictive performance (AUC-ROC 0.87 and 0.85, respectively). Cluster analysis revealed distinct vulnerability profiles, with the highest burden observed among groups characterized by multidimensional poverty and limited sanitation. The findings highlight the overlapping social and environmental determinants that sustain the persistence of NIDs in these territories, underscoring the need for structural, territorialized policies tailored to the specific realities of quilombola communities in the Amazon. The cross-sectional design and reliance on self-reported disease history should be considered when interpreting the findings.
BACKGROUND:Quilombola communities in the Brazilian Amazon face persistent social and territorial inequities that shape health outcomes and access to care. Geographic isolation, limited transportation, centralization of specialized services, and socioeconomic disadvantages contribute to unequal opportunities for timely diagnosis and treatment. Understanding how these determinants interact with patterns of multimorbidity is essential for guiding equiTable health policies and strengthening primary care in remote territories. METHODS:A cross-sectional epidemiological study was conducted with 518 adults from nine quilombola communities in Santarém, Pará. Data were collected through household surveys addressing sociodemographics, self-reported diseases, service utilization and resolvability. Geographic coordinates of communities and health services were mapped to classify accessibility as high, medium or low. Diseases were converted into a binary matrix to estimate prevalence and identify multimorbidity (≥2 conditions). Statistical analyses included chi-square tests, ANOVA, Spearman correlations and heatmap visualization. A Composite Access Index (CAI) integrating geographic distance, epidemiological burden and service-use indicators was developed. A Random Forest model was used to identify conditions most strongly associated with multimorbidity. RESULTS:Communities showed marked territorial heterogeneity. Pérola do Maicá had the highest accessibility, while Ituqui, Tiningu and Murumuru presented substantial geographic and logistical barriers. Service utilization ranged from 42.9% to 95.0%, and most communities relied on care outside their territory (70-95%). Complete problem resolution was reported by 72.5% of participants, though with variation among communities. The CAI identified Ituqui (0.550), Tiningu (0.480) and Murumurutuba (0.331) as the most vulnerable territories. The Random Forest model achieved 93.6% accuracy, with hypertension, diabetes, musculoskeletal diseases, arthritis/rheumatism and heart disease emerging as key predictors of multimorbidity. DISCUSSION:Findings indicate that social and territorial determinants are strongly associated with inequities in access to health services, continuity of care, and disease burden across quilombola communities. CONCLUSIONS:Geographic barriers and the distribution of health services are associated with distinct patterns of multimorbidity and health service access among quilombola populations. Strengthening primary care, transportation, and diagnostic support may help mitigate inequities and improve health conditions in remote Amazonian territories.
