ABSTRACT Deforestation and high human mobility due to mining activities have been key to the increase in malaria cases in the Americas. Here, we review the epidemiological and control aspects of malaria in the Amazon mining areas. Epidemiological evidence shows: 1) a positive correlation between illegal mining activity and malaria incidence, mostly in the Amazon region; 2) most Brazilian miners are males aged 15-29 years who move between states and even countries; 3) miners do not fear the disease and rely on medical care, diagnosis, and medication when they become ill; 4) illegal mining has emerged as the most reported anthropogenic activity within indigenous lands and is identified as a major cause of malaria outbreaks among indigenous people in the Amazon; and 5) because mining is largely illegal, most areas are not covered by any healthcare facilities or activities, leading to little assistance in the diagnosis and treatment of malaria. Our review identified five strategies for reducing the malaria incidence in areas with mining activities: 1) reviewing legislation to control deforestation and mining expansion, particularly in indigenous lands; 2) strengthening malaria surveillance by expanding the network of community health agents to support rapid diagnosis and treatment; 3) reinforcing vector control strategies, such as the use of insecticide-treated nets; 4) integrating deforestation alerts into the national malaria control program; and 5) implementing multi-sectoral activities and providing prompt assistance to indigenous populations. With this roadmap, we can expect a decrease in malaria incidence in the Amazonian mining areas in the future. Americas Here shows 1 region 2 1529 15 29 15-2 countries 3 care ill 4 5 expansion insecticidetreated insecticide treated nets program multisectoral multi sectoral populations roadmap future 152 15-

ABSTRACT In this review, we discuss dengue surveillance, prevention, and control measures in Brazil. Data on dengue epidemics between 2000 and 2024 indicates an increase in the number of dengue cases and deaths. Global climate change is a key driver of this growth. Over the past 25 years, nearly 18 million Brazilians have been infected with the dengue virus, and the highest number of dengue cases in Brazil's history is projected to reach 2024. Dengue mortality in Brazil increased geographically over time. As of June, there were approximately 6 million probable cases and 4,000 confirmed deaths in Brazil, which represents the greatest dengue epidemic to date. Several technologies have been developed to control Aedes aegypti, including the deployment of Wolbachia-infected mosquitoes, indoor residual spraying, sterile insect techniques, and mosquito-disseminated insecticides. The Ministry of Health recommends integrating these technologies into health services. Brazil is the first country to incorporate the Takeda vaccine into its public health system, and the Butantan vaccine is currently undergoing Phase 3 clinical trials. Increasing the vaccination coverage and implementing novel Ae. aegypti control technologies could reduce the number of dengue cases in Brazil in the coming years. Community activities such as home cleaning and elimination of potential mosquito breeding sites, facilitated by social media and health education initiatives, must continue to achieve this reduction. Ultimately, a multisectoral approach encompassing sanitary improvements, mosquito control, vaccination, and community mobilization is crucial in the fight against dengue epidemics. review surveillance prevention 200 202 growth 2 years 1 virus Brazils s time June 4000 4 000 4,00 date Wolbachiainfected Wolbachia mosquitoes spraying techniques mosquitodisseminated disseminated insecticides services system trials Ae sites initiatives reduction Ultimately improvements 20 400 00 4,0 40 0 4,

ABSTRACT Background: Chagas disease is a silent illness with high mortality burden in many Latin American countries, such as Brazil. Bahia has the fourth highest mortality rate in Brazil. This study analyzed the temporal trends and regional differences in the mortality rate of Chagas disease in Bahia State from 2008 to 2018. Methods: A time-series analysis of Chagas disease-related deaths was conducted using data from the Mortality Information System of Brazil. We compared the mortality rate due to Chagas disease as the primary cause and mention of the disease in the death certificate, standardized by age and health macroregion/residence municipality, and mapped hot and coldspots. Results: The Chagas Disease Mortality Rate in Bahia during the study period revealed a stationary trend, ranging from 5.34 (2008) to 5.33 (2018) deaths per 100,000 inhabitants. However, the four health macroregions showed an upward trend in mortality rates. The mortality rate (age-adjusted) ranged from 4.3 to 5.1 deaths per 100,000 inhabitants between 2008 and 2018. We observed a upward trend in the mortality rate among individuals aged ≥70 years and a higher incidence of death among men than among women. Of the total number of deaths (8,834), 79.3% had Chagas disease as the primary cause and the death certificates of 20.7% mentioned the disease. Cardiac complications were reported in 85.1% of the deaths due to Chagas disease. Conclusions: The regional and individual differences in the mortality rate of Chagas disease highlighted in this study may support health planning that considers the peculiarities of the territory. Background countries Brazil 200 2018 Methods timeseries time series diseaserelated related certificate macroregionresidence macroregion residence municipality coldspots Results 534 5 34 5.3 (2008 533 33 (2018 100000 100 000 100,00 However rates ageadjusted adjusted (age-adjusted 43 4 3 4. 51 1 5. 70 ≥7 women 8,834, 8834 8,834 , 8 834 (8,834) 793 79 79.3 207 20 7 20.7 851 85 85.1 Conclusions territory 201 53 (200 (201 10000 10 00 100,0 ≥ 883 8,83 83 (8,834 79. 2 20. 85. (20 1000 0 100, 88 8,8 (8,83 (2 8, (8,8 ( (8, (8

Abstract Our hypothesis was that different sources of unsaturated fatty acids from oilseeds (sunflower, soybeans, and cottonseed) could alter milk yield, fatty acid profile, and the amount of unsaturated fatty acids yielded in milk. It aimed to evaluate the effects of lipid sources on yield and composition and fatty acids in milk of primiparous Girolando cows. Five cows in lactation (35 ± 8 days), with 410 ± 7.15 kg BW were randomly distributed in a 5 x 5 Latin square. Five experimental diets, namely a control diet without an additional source of lipid and four diets with different lipid sources: cottonseed, sunflower seed, whole soybean, or soybean oil, as lipid source, to reach 70 g/kg of ethereal extract dry matter basis were used. Cottonseed and soybean oil addition reduced daily yield by 15 and 22%. Oilseed can alter fatty acid profile in milk. Whole soybean provided greater daily milk and fatty acids yields.

ABSTRACT Background: Neglected tropical diseases are a growing threat to global health, and endemic Chagas disease has emerged as one of the most important health problems in America. The main strategy to prevent Trypanosoma cruzi transmission is chemical control of vectors. This study presents a descriptive analysis of synanthropic triatomines before and after the implementation of a vector-control program in Bahia, Brazil. Methods: Descriptive analysis and geospatial statistics were performed on triatomine data, (1) the relative abundance and (2) proportional spatial distribution, from Bahia during two periods: (A) 1957 to 1971 and (B) 2006 to 2019. Results: We observed a decrease in the relative abundance of Panstrongylus megistus (A: n=22.032, 61.9%; B: n=1.842, 1.0%) and Triatoma infestans (A: n=1.310, 3.7%; B: n=763, 0.43%), as well as an increase in the relative abundance of T. sordida (A: n=8.314, 23.4%, B: n=146.901, 81.6%) and T. pseudomaculata (A: n=894, 2.5%, B: n=16.717, 9.3%). Conclusions: Our results indicate a clear reduction in the occurrence of P. megistus and T. infestans (last record in 2015) and an increase in the relative abundance and geographical distribution of T. sordida and T. pseudomaculata after 40 years of the vector-control program. The high frequency of other triatomine species in the municipalities of the state of Bahia and their abundance in recent years highlight the need to reinforce permanent entomological surveillance actions to prevent Chagas disease.

Abstract INTRODUCTION: We aimed to study intraspecific variation in Triatoma costalimai, a potential vector of Chagas disease present in Brazil and Bolivia. METHODS: We analyzed phenotypic (connexivum color patterns, wing morphometrics) and genetic variation (16S mtDNA) of three Brazilian T. costalimai populations. We compared 16S sequences with those of putative Bolivian T. costalimai and its sister species, T. jatai. RESULTS: Brazilian populations had different connexivum color patterns and forewing shapes. A 16S mtDNA haplotype network showed a clear separation of Brazilian T. costalimai from both T. jatai and Bolivian T. costalimai. CONCLUSIONS: We report considerable variability in T. costalimai populations.

RESUMO Deep Learning é uma técnica de aprendizado de máquina na qual o programa computacional aprende padrões diretamente a partir de imagens classificadas previamente. O presente ensaio objetivou apresentar essa técnica e algumas de suas aplicações para diagnóstico de doenças e identificação de insetos vetores para incentivar profissionais da saúde que não tenham conhecimento aprofundado em informática e que desejem utilizar a ferramenta para realizar análises automatizadas. Deep Learning tem sido aplicado para diagnóstico de câncer, fibrose cardíaca, tuberculose, detecção de parasitos como Plasmodium e Leishmania e ainda para identificação de insetos vetores. Na Universidade de Brasília, a técnica tem sido aplicada para desenvolver uma ferramenta para identificar lesões ulceradas de leishmaniose em diagnóstico diferencial e para detectar Leishmania em lâminas de estudos histopatológicos. Além disso, Deep Learning tem sido usado para identificar as espécies de vetores da doença de Chagas – o que é importante para auxiliar na vigilância epidemiológica. O uso da tecnologia envolve desafios éticos e procedimentais que são discutidos no presente ensaio. O ensaio aponta perspectivas de desenvolvimento de aplicativos que auxiliem os profissionais de saúde no diagnóstico de Leishmaniose e de vetores da doença de Chagas, o que vai ao encontro dos objetivos da pesquisa translacional.

ABSTRACT Deep Learning is a machine learning technique in which the computational algorithm learns patterns directly from images previously classified. The present essay aims to show some of its applications for clinical diagnosis and identification of insect vectors to encourage health professionals who do not have deep knowledge of computer science and who wish to use the tool to perform automated analyzes. Deep Learning has been applied to the diagnosis of cancer, cardiac fibrosis, tuberculosis, detection of parasites such as Plasmodium and Leishmania, and to identify insect vectors. At the University of Brasília, Deep Learning has been used to develop a tool to identify ulcers caused by leishmaniasis, as well as to detect Leishmania parasites. Moreover, Deep Learning was applied to identify the species of vectors of Chagas disease, an important contribution to the epidemiological surveillance of the disease. The use of Deep Learning involves some ethical and procedural issues that are discussed in this paper. Finally, the essay points out perspectives of development of apps that assist health professionals in the diagnosis of Leishmaniasis and Chagas disease vectors, which meets the goals of translational research.

RESUMO Deep Learning é uma técnica de aprendizado de máquina na qual o programa computacional aprende padrões diretamente a partir de imagens classificadas previamente. O presente ensaio objetivou apresentar essa técnica e algumas de suas aplicações para diagnóstico de doenças e identificação de insetos vetores para incentivar profissionais da saúde que não tenham conhecimento aprofundado em informática e que desejem utilizar a ferramenta para realizar análises automatizadas. Deep Learning tem sido aplicado para diagnóstico de câncer, fibrose cardíaca, tuberculose, detecção de parasitos como Plasmodium e Leishmania e ainda para identificação de insetos vetores. Na Universidade de Brasília, a técnica tem sido aplicada para desenvolver uma ferramenta para identificar lesões ulceradas de leishmaniose em diagnóstico diferencial e para detectar Leishmania em lâminas de estudos histopatológicos. Além disso, Deep Learning tem sido usado para identificar as espécies de vetores da doença de Chagas – o que é importante para auxiliar na vigilância epidemiológica. O uso da tecnologia envolve desafios éticos e procedimentais que são discutidos no presente ensaio. O ensaio aponta perspectivas de desenvolvimento de aplicativos que auxiliem os profissionais de saúde no diagnóstico de Leishmaniose e de vetores da doença de Chagas, o que vai ao encontro dos objetivos da pesquisa translacional.

ABSTRACT Deep Learning is a machine learning technique in which the computational algorithm learns patterns directly from images previously classified. The present essay aims to show some of its applications for clinical diagnosis and identification of insect vectors to encourage health professionals who do not have deep knowledge of computer science and who wish to use the tool to perform automated analyzes. Deep Learning has been applied to the diagnosis of cancer, cardiac fibrosis, tuberculosis, detection of parasites such as Plasmodium and Leishmania, and to identify insect vectors. At the University of Brasília, Deep Learning has been used to develop a tool to identify ulcers caused by leishmaniasis, as well as to detect Leishmania parasites. Moreover, Deep Learning was applied to identify the species of vectors of Chagas disease, an important contribution to the epidemiological surveillance of the disease. The use of Deep Learning involves some ethical and procedural issues that are discussed in this paper. Finally, the essay points out perspectives of development of apps that assist health professionals in the diagnosis of Leishmaniasis and Chagas disease vectors, which meets the goals of translational research.

ABSTRACT Consumption of ready-to-eat (RTE) vegetables is quick, easy and healthy, especially when eaten without cooking. However, they might be a source of foodborne pathogenic microorganisms. The objective of this study was to evaluate the microbiological and parasitological contamination of fresh RTE vegetables produced in agroindustries in the Federal District of Brazil (FD), and to correlate contamination with good manufacturing practices (GMP). One hundred and three samples of RTE vegetables were collected from six agroindustries for microbiology and parasitology analyses and correlate with GMP; 54 samples were collected from three hypermarkets for parasitological evaluation. None of the samples analyzed were positive for Salmonella sp. and for thermotolerant coliforms, but they were contaminated with total coliforms. All analyzed samples were contaminated with at least one species of enteroparasistes or commensals, which were identified as Ascaris sp., Balantidium coli, Entamoeba histolytica/dispar, Hookworm, Strongyloides sp., Trichuris sp., Entamoeba sp., eggs and larvae of Nematoda, insects and fungi. Agroindustries that adopted GMP showed less contamination with helminths. RTE vegetables sold in hypermarkets of the FD are unfit for human consumption. It is important to guide farmers in the FD on the need to adopt good practices in the production and processing of vegetables to reduce the microbial contamination.

Abstract We report an Acanthamoeba keratitis case associated with the use of contact lens in a 28-year-old female from Brasília, Brazil. Samples from corneal scraping and contact lens case were used for culture establishment, PCR amplification, and partial sequencing (fragments of ~400kb) of small subunit rDNA; both culture and PCR were positive. The sequence analyses of the cornea and of isolates from the contact lens case showed similarity with the T4 genotype. To the best of our knowledge, this is the first report of T4 Acanthamoeba keratitis case from the Midwest region of Brazil.

Abstract INTRODUCTION: Chagas disease surveillance requires current knowledge on synanthropic triatomines. We analyzed the occurrence and Trypanosoma cruzi infection rates of triatomine bugs in central Brazil, during 2012-2014. METHODS: Triatomines were collected inside or around houses, and T. cruzi infection was determined by optical microscopy and conventional/quantitative polymerase chain reaction. RESULTS: Of the 2706 triatomines collected, Triatoma sordida was the most frequent species in Goiás State, whereas Panstrongylus megistus predominated in the Federal District. Parasites identified were T. cruzi, T. rangeli, and Blastocrithidia sp. CONCLUSIONS: P. megistus and T. sordida sustained the risk of T. cruzi transmission to humans in central Brazil.

BACKGROUND Knowledge on synanthropic phlebotomines and their natural infection by Leishmania is necessary for the identification of potential areas for leishmaniasis occurrence. OBJECTIVE To analyse the occurrence of Phlebotominae in gallery forests and household units (HUs) in the city of Palmas and to determine the rate of natural infection by trypanosomatids. METHODS Gallery forests and adjacent household areas were sampled on July (dry season) and November (rainy season) in 2014. The total sampling effort was 960 HP light traps and eight Shannon traps. Trypanosomatids were detected in Phlebotominae females through the amplification of the SSU rDNA region, and the positive samples were used in ITS1-PCR. Trypanosomatid species were identified using sequencing. FINDINGS A total of 1,527 sand flies representing 30 species were captured in which 949 (28 spp.) and 578 (22 spp.) were registered in July and November, respectively. In July, more specimens were captured in the gallery forests than in the HUs, and Nyssomyia whitmani was particularly frequent. In November, most of the specimens were found in the HUs, and again, Ny. whitmani was the predominant species. Lutzomyia longipalpis was commonly found in domestic areas, while Bichromomyia flaviscutellata was most frequent in gallery forests. Molecular analysis of 154 pools of females (752 specimens) identified Leishmania amazonensis, L. infantum, and Crithidia fasciculata in Ny. whitmani, as well as L. amazonensis in Lu. longipalpis, Trypanosoma sp. and L. amazonensis in Pintomyia christenseni, and L. amazonensis in both Psathyromyia hermanlenti and Evandromyia walkeri. MAIN CONCLUSIONS These results show the importance of gallery forests in maintaining Phlebotominae populations in the dry month, as well as their frequent occurrence in household units in the rainy month. This is the first study to identify Leishmania, Trypanosoma, and Crithidia species in Phlebotominae collected in Palmas, Tocantins, Brazil.