Pitiose gastrointestinal canina: relato de caso no Pantanal brasileiro a partir de uma abordagem diagnóstica

A pitiose é causada por um organismo aquático semelhante a um fungo (Pythium insidiosum) e considerada um importante problema de saúde pública, pois pode afetar animais e humanos. Este artigo relata um caso de pitiose gastrointestinal em um cão. O paciente ficou internado por quatro dias, período em que o animal recebeu tratamento de suporte e sintomático. No entanto, o tratamento aplicado não teve sucesso e o quadro clínico do cão piorou, culminando com a morte. Exames de imagem complementares, como radiografia e ultrassonografia, bem como exames hematológicos, foram realizados durante o período de internação. O diagnóstico definitivo foi feito na autópsia, pois as características macroscópicas e microscópicas sugeriam a presença de granuloma intestinal e acentuada enterite necrótica multifocal supurativa. Além disso, a avaliação histológica revelou estruturas morfológicas compatíveis com P. insidiosum. Além disso, a nested PCR foi realizada e mostrou amplificação parcial (105 pb) da região ITS1 do gene ribossomal de P. insidiosum.Pythiosis is caused by an aquatic fungus-like organism (Pythium insidiosum). It is considered an important public health issue as it can affect both animals and humans. This paper reports a case of gastrointestinal pythiosis in a dog. The patient was hospitalized for four days, during which the animal received supportive and symptomatic treatment. But the applied treatment was unsuccessful and the dog’s clinical condition worsened, culminating in death. Complementary imaging tests such as radiography and ultrasonography, as well as hematological tests, were performed during the hospitalization period. The definitive diagnosis was reached in the postmortem as macroscopic and microscopic characteristics suggested the presence of intestinal granuloma and accentuated multifocal suppurative necrotic enteritis. Additionally, the histological evaluation revealed morphological structures compatible with P. insidiosum. Also, the results of nested PCR performedshowed partial amplification (105 bp) of the ITS1 region of the ribosomal gene of P. insidiosum

Chitosan/mangiferin particles for Cr(VI) reduction and removal

AbstractIn this work, chitosan/mangiferin particles (CMP) were prepared by spray-drying technique and characterized by SEM, DLS, FTIR, HPLC–UV and adsorption studies to investigate a possible application as a preventive material in cases of human and animal contamination with Cr(VI). CMP presented sizes ranging from nano to micrometers. Chitosan and mangiferin (MA) presence in the powder was confirmed by FTIR and MA quantification (136μg/mg) was performed using a calibration curve prepared by HPLC–UV. Adsorption capacity of Cr(VI) onto CMP was compared with chitosan and investigated in a batch system by considering the effects of various parameters like contact time, initial concentration of adsorbent and pH. Cr(VI) removal is pH dependent and it was found to be maximum at pH 5.0. The results showed that CMP has a potential application as a preventive material in cases of human or animal contamination with Cr(VI)

Evaluation of Cardiometabolic Parameters among Obese Women Using Oral Contraceptives

BackgroundCombined oral contraceptive (COC) use has been associated with an unfavorable impact on carbohydrate and lipid metabolism in diverse populations of normal weight and obese women. The present study aimed to evaluate the cardiometabolic and inflammatory profiles of women in northeastern Brazil with respect to COC use and obesity.MethodsWe performed a cross-sectional study to verify cardiovascular parameters, including blood pressure (BP), fasting serum glucose, lipid, and inflammatory profile, in a population of women aged 15–45 years, considering obesity and COC use. Our sample consisted of 591 women, 481 women who were COC users, and 110 age-matched women who were COC non-users, classified as obese and non-obese according to BMI.ResultsCOC use and obesity were associated with increased systolic (p ≤ 0.001) and diastolic BP (p = 0.001), blood glucose (p ≤ 0.001), total cholesterol (p = 0.008), low-density lipoprotein cholesterol (p ≤ 0.001), very low-density lipoprotein cholesterol (p ≤ 0.001), triglycerides (p ≤ 0.001), ferritin (p = 0.006), C-reactive protein (CRP) (p ≤ 0.001), and nitric oxide metabolites (p ≤ 0.001), as well as decreased high-density lipoprotein cholesterol (HDL-c) (p ≤ 0.001) in comparison to controls. CRP and HDL-c levels in obese COC users were determined to be outside reference range values. The odds of having lower levels of HDL-c and elevated CRP increased among obese COC users. COC use was independently associated with low levels of HDL-c, especially second-generation progestins (p < 0.001; OR = 8.976; 95% CI 2.786–28.914).ConclusionObesity and COC use were associated with alterations in lipid and inflammatory cardiometabolic parameters, particularly increased CRP levels and decreased HDL-c, which are considered markers of cardiovascular disease (CVD) risk. Given the need to prevent unintended pregnancy among obese women, together with weight loss counseling, it is important to evaluate the most effective and safest contraceptive methods to avoid the potential risk of developing CVD

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries