Clinical and epidemiological profile of children and adolescents submitted to the hematopoietic cell transplantation

The Hematopoietic stem cell transplantation (HSCT) is used in children as a definitive treatment for various oncological, immune deficiencies, hemoglobinopathy, and malignancies diseases that involve the hematological system, congenital metabolism disorders, among others. To characterize the clinical and epidemiological profile of children and adolescents submitted to HSCT at a referral service in the state of Rio Grande do Norte. This is a quantitative, retrospective, observational, descriptive and analytical quantitative approach approaching the medical records of children and adolescents submitted to HSCT in a referral hospital service for this type of transplantation in the state of Rio Grande do Sul North (RN). The final sample consisted of 35 records patients aged between 2 and 18 years old who underwent HSCT from February 2008 to December 2015 and who presented the data necessary for the study. The records analyzed showed a little majority of male patients (51.42%) and 60.00% of these men were students and 71.42% lived in the state of the Rio Grande do Norte. According to the clinical characteristics, 34.3% of the patients had Acute Lymphoblastic Leukemia and 25.71% had Acute Myeloid Leukemia as the main diagnosis. Gastrointestinal toxicities were the most frequent (97.1%) and all patients received antineoplastic/chemotherapeutic and antiemetic treatment. The allogeneic HSCT was the most frequently performed (57.14%) and the most used source of Hematopoietic progenitor cells (HPC) was the peripheral blood (54.29%) and 5.71% of these patients developed the Graft versus Host Disease (GVHD), of which one was affected by acute GVHD and another by chronic GVHD. Septsis was the most frequent cause of death (60%). The profile of the clinical variables presented by the children and adolescents of this study shows that the most prevalent diagnosis was ALL, the most frequent toxicities were gastrointestinal, cardiac, respiratory and hematological, the most common HSCT was allogeneic peripheral blood and the greatest cause of mortality was sepsis. These data are similar to studies conducted in North America, Europe and Asia

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