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

Paraganglioma na coluna vertebral: relato de caso

Os paragangliomas são tumores neuroendócrinos raros com origem em células especializadas derivadas da crista neural, acometendo a região da carótida ou jugulotimpânica. São raros dentro do canal vertebral, e quando ocorrem são normalmente encontrados no compartimento intradural e extramedular da região lombossacra. Este relato apresenta o caso de um paciente de 26 anos, sexo masculino, com diagnóstico de fratura patológica da coluna torácica (T10), secundária a paraganglioma, causando lesão medular completa. Foi realizado tratamento cirúrgico no Hospital Geral do Estado da Bahia, que apresentou sangramento excessivo como complicação que indicou necessidade de embolização prévia. Com isso, os autores recomendam cautela ao avaliar e tratar esta rara lesão causadora de déficit neurológico, cujo planejamento cirúrgico deve ser criterioso a fim de evitar complicações catastróficas.Paragangliomas are rare neuroendocrine tumors that originate in specialized cells derived from neural crest cells, affecting the region of the carotid or jugular-tympanic artery. They are rare within the spinal canal and, when they occur, they are normally found in the extramedullary intradural compartment of the lumbosacral region. This report presents the case of a 26-year-old male patient who was diagnosed with pathological fracture of the thoracic spine (T10), secondary to paraganglioma, thus causing complete spinal cord injury. Surgical treatment was performed at the General Hospital of the State of Bahia and the complication of excessive bleeding occurred, which indicated that there had been a need for prior embolization. Because of this, the authors recommend caution when evaluating and treating this rare lesion that causes neurological deficits, with careful surgical planning in order to catastrophic complications

Paraganglioma na coluna vertebral: relato de caso

Os paragangliomas são tumores neuroendócrinos raros com origem em células especializadas derivadas da crista neural, acometendo a região da carótida ou jugulotimpânica. São raros dentro do canal vertebral, e quando ocorrem são normalmente encontrados no compartimento intradural e extramedular da região lombossacra. Este relato apresenta o caso de um paciente de 26 anos, sexo masculino, com diagnóstico de fratura patológica da coluna torácica (T10), secundária a paraganglioma, causando lesão medular completa. Foi realizado tratamento cirúrgico no Hospital Geral do Estado da Bahia, que apresentou sangramento excessivo como complicação que indicou necessidade de embolização prévia. Com isso, os autores recomendam cautela ao avaliar e tratar esta rara lesão causadora de déficit neurológico, cujo planejamento cirúrgico deve ser criterioso a fim de evitar complicações catastróficas

Estudo clínico epidemiológico das fraturas da coluna vertebral

OBJETIVO: Realizar um levantamento epidemiológico das fraturas da coluna vertebral. MÉTODOS: Estudo de revisão de prontuário, retrospectivo analisando dados clínicos e epidemiológicos no período de 1991 a 2010. Foram avaliados dados como: idade, sexo, procedência, escala de Frankel admissional, mecanismo de trauma, tipo de fratura, tratamento e complicações, nos prontuários de 1.917 pacientes submetidos a tratamento de fraturas da coluna vertebral. O teste do qui-quadrado foi utilizado para comparação entre as variáveis discretas e o teste t Student foi utilizado no caso de variáveis contínuas, adotando níveis de significância de p < 0,05. RESULTADOS: A maioria dos pacientes era do gênero masculino (85,2%), média de idade de 34 anos, procedência urbana (69,2%), sendo o mecanismo de trauma a queda de altura (40,4%). Quando a causa for mergulho em águas rasas, está associada a lesões na região cervical, pacientes mais jovens e tende a produzir déficit neurológico. As fraturas isoladas aconteceram em 75,6% dos casos, afetando mais o nível L1 (11,4%), sendo que o tratamento cirúrgico foi indicado em 88,2%, sem complicações pós-operatórias na maioria dos casos (61,7%). CONCLUSÃO: Os autores sugerem mudanças principalmente na área habitacional, com campanhas educacionais preventivas e orientações para jovens que gostam de fazer atividades recreativas como mergulho em água rasa

EPIDEMIOLOGY OF SPINE FRACTURES IN MOTORCYCLE ACCIDENT VICTIMS

ABSTRACT Objective: To analyze the incidence of spinal injuries between 2000-2010 due to motorcycle accidents and the relation to the increase in motorcycle sales in the same period, as well as the anatomical distribution of these spinal injuries. Methods: Data were collected from 1,295 records of patients who have suffered spinal injury resulting from motorcycle accidents admitted to the ward TRM (Spinal Cord Trauma) of the Hospital Geral do Estado da Bahia from 2000 to 2010 in this retrospective study. We selected 110 medical records and collected information on sex, age, neurological deficit on admission (according to Frankel scale), diagnosis, and level of injury. Results: Between 2000 and 2010 there was an increase of almost five times in the incidence of patients who have suffered spinal injury due to motorcycle accidents. More than half (51.4%) had cervical spine injury, 37.2% thoracic spine injury and 11.34% had lumbar spine injury. Only 34.3% of patients had no neurological deficit on admission and patients with thoracic spine fracture had a higher incidence and severity of lesion. The average age of patients was 30 years. Conclusions: The increased incidence of spinal injuries due motorcycle accidents occurred in the same period in which there was an increase in motorcycle sales in the country. Patients who have suffered those injuries were young, with higher incidence in the cervical and thoracic spinal levels and high rates of neurological deficit