Intoxicação cutânea grave por Paraquat

Paraquat is a highly toxic non-selective herbicide and is responsible for high accidental or provoked lethality rates, mainly due to respiratory failure. Although oral poisoning is the primary and most severe, prolonged contact with the substance in a large body area can lead to similar toxicity and death – a fact that is little elucidated in the literature. This is the case report of a 22-year-old man admitted to a hospital due to complaints of malaise, nausea, fever, headache, abdominal pain, diarrhea, burns and dyspnea. The initial diagnostic suspicion was hantaviruses, leptospirosis, dengue and pulmonary thromboembolism, and there was subsequently proven exogenous intoxication with pesticides by inhalation and cutaneous route. Imaging tests revealed diffuse pulmonary fibrosis and he also hadrenal, hepatic and coagulation alterations. As there is no specific antidote, symptomatic and supportive treatment was performed using activated charcoal, antibiotics, corticosteroids, antioxidants and hemodialysis. However, the patient had a progressive worsening of the condition and died due to acute respiratory distress syndrome and pulmonary fibrosis. Paraquat, although banned in Brazil in 2020, continues to be used illegally. In addition, its substitute, the Diquat, has similar toxicity. Thus, it is essential that health professionals recognize the diagnosis of intoxication by such substances and their different exposure routes. New control measures for these substances and greater investment in health education are also needed to prevent accidental exposure, as reported.O Paraquat é um herbicida não seletivo altamente tóxico, sendo responsável por altas taxas de letalidade acidentais ou provocadas, devido, principalmente, à insuficiência respiratória. Apesar de a intoxicação por via oral ser a principal e mais grave, o contato prolongado com a substância em uma grande área corporal pode gerar uma toxicidade similar e levar ao óbito – fato pouco elucidado na literatura. Este é o relato de caso de um homem de 22 anos, que foi admitido em um hospital devido a queixas de mal-estar, náuseas, febre, cefaleia, dor abdominal, diarreia, queimaduras e dispneia. A suspeita diagnóstica inicial foi de hantavirose, leptospirose, dengue e tromboembolismo pulmonar e, posteriormente, foi comprovado intoxicação exógena com agrotóxico por via inalatória e cutânea. Exames de imagem revelaram fibrose pulmonar difusa e ele também apresentou alterações renais, hepáticas e coagulatórias. Como não há antídoto específico, foi empregado tratamento sintomático e suportivo, com uso de carvão ativado, antibióticos, corticoides, antioxidantes e hemodiálise. No entanto, o paciente teve uma piora progressiva do quadro, vindo a óbito devido à síndrome da angústia respiratória aguda e fibrose pulmonar. O Paraquat, embora proibido no Brasil em 2020, continua sendo utilizado de forma ilegal. Além disso, seu substituto, o Diquat, possui toxicidade semelhante. Assim, é fundamental que os profissionais da saúde reconheçam o diagnóstico da intoxicação por tais substâncias e suas diferentes vias de exposição. Também são necessárias novas medidas de fiscalização das substâncias e maior investimento em educação em saúde para evitar exposições acidentais, assim como relatado

Intoxicação cutânea grave por Paraquat

O Paraquat é um herbicida não seletivo altamente tóxico, sendo responsável por altas taxas de letalidade acidentais ou provocadas, devido, principalmente, à insuficiência respiratória. Apesar de a intoxicação por via oral ser a principal e mais grave, o contato prolongado com a substância em uma grande área corporal pode gerar uma toxicidade similar e levar ao óbito – fato pouco elucidado na literatura. Este é o relato de caso de um homem de 22 anos, que foi admitido em um hospital devido a queixas de mal-estar, náuseas, febre, cefaleia, dor abdominal, diarreia, queimaduras e dispneia. A suspeita diagnóstica inicial foi de hantavirose, leptospirose, dengue e tromboembolismo pulmonar e, posteriormente, foi comprovado intoxicação exógena com agrotóxico por via inalatória e cutânea. Exames de imagem revelaram fibrose pulmonar difusa e ele também apresentou alterações renais, hepáticas e coagulatórias. Como não há antídoto específico, foi empregado tratamento sintomático e suportivo, com uso de carvão ativado, antibióticos, corticoides, antioxidantes e hemodiálise. No entanto, o paciente teve uma piora progressiva do quadro, vindo a óbito devido à síndrome da angústia respiratória aguda e fibrose pulmonar. O Paraquat, embora proibido no Brasil em 2020, continua sendo utilizado de forma ilegal. Além disso, seu substituto, o Diquat, possui toxicidade semelhante. Assim, é fundamental que os profissionais da saúde reconheçam o diagnóstico da intoxicação por tais substâncias e suas diferentes vias de exposição. Também são necessárias novas medidas de fiscalização das substâncias e maior investimento em educação em saúde para evitar exposições acidentais, assim como relatado

Effects of salinity on the physiology of Salvinia auriculata Aubl. (Salviniales, Pteridophyta)

Salvinia auriculata Aubl. is reported to occur in different zones of the Capibaribe River, Pernambuco State, Brazil. This river varies in salinity in different areas. This study evaluated the growth, photosynthesis and pigment contents of S. auriculata at different salinity levels. Plant sections were collected in the Cursaí Reservoir, located in the municipality of Paudalho, Pernambuco, and were brought to a greenhouse, where they were put in glass flasks filled with 250 mL of liquid, placed on benches. The plants were exposed for 40 h to salinity levels of 0, 17 and 34, obtained with reservoir freshwater, 1:1 freshwater:seawater and pure seawater, respectively. At the end of the experimental period, the plants in salt water showed color changes, with brownish leaves. In addition, plant growth rates decreased. Salinity and time had a negative influence on photosynthetic responses such as Fv/Fm, ETRmax and ETR, which showed reductions under the highest salinity treatment. Response patterns may help to explain S. auriculata occurrence, and its distribution can be regulated by salinity

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