Motivos de consultas mais comuns em ambuláorios de atenção primária.

Trabalho de Conclusão de Curso - Universidade Federal de Santa Catarina, Centro de Ciências da Saúde, Departamento de Clínica Médica, Curso de Medicina, Florianópolis, 199

Parasitose intestinal: alguns aspectos relacionados.

Trabalho de Conclusão de Curso - Universidade Federal de Santa Catarina, Centro de Ciências da Saúde, Departamento de Pediatria, Curso de Medicina, Florianópolis, 199

Seis novos casos confirmam o perfil clínico molecular de deficiência combinada de 17 alfa-hidroxilase/17,20-liase no Brasil

In 2004, Costa-Santos and cols. reported 24 patients from 19 Brazilian families with 17&#945;-hydroxylase deficiency and showed that p.W406R and p.R362C corresponded to 50% and 32% of CYP17A1 mutant alleles, respectively. The present report describes clinical and molecular data of six patients from three inbred Brazilian families with 17&#945;-hydroxlyse deficiency. All patients had hypogonadism, amenorrhea and hypertension at diagnosis. Two sisters were found to be 46,XY with both gonads palpable in the inguinal region. All patients presented hypergonadotrophic hypogonadism, with high levels of ACTH (&gt; 104 ng/mL), suppressed plasmatic renin activity, low levels of potassium (< 2.8 mEq/L) and elevated progesterone levels (&gt; 4.4 ng/mL). Three of them, including two sisters, were homozygous for p.W406R mutation and the other three (two sisters and one cousin) were homozygous for p.R362C. The finding of p.W406R and p.R362C in the CYP17A1 gene here reported in additional families, confirms them as the most frequent mutations causing complete combined 17&#945;-hydroxylase/17,20-lyase deficiency in Brazilian patients.Em 2004, segundo Costa-Santos e cols., p.W406R e p.R362C correspondiam a 50% e 32% dos alelos mutantes do gene CYP17A1, respectivamente, em 24 pacientes de 19 famílias brasileiras com deficiência da 17&#945;-hidroxilase. Apresentamos os dados cl&#957;nicos e moleculares de seis pacientes de três famílias consanguíneas brasileiras com deficiência da 17&#945;-hidroxilase. Todas as pacientes apresentavam hipogonadismo, amenorreia e hipertensão ao diagnóstico. Duas irmãs tinham cariótipo 46,XY, ambas com gônadas palpáveis na região inguinal. Todas tinham hipogonadismo hipergonadotrófico, com nível aumentado de ACTH (&gt; 104 ng/mL), atividade de renina plasmática suprimida, baixos níveis de potássio (< 2,8 mEq/L) e progesterona aumentada (&gt; 4,4 ng/mL). Três delas, incluindo duas irmãs, apresentaram homozigose para a mutação p.W406R e as outras três (duas irmãs e uma prima) foram homozigotas para a mutação p.R362C. A recorrência das mutações p.W406R e p.R362C no gene CYP17A1 aqui relatada em famílias adicionais confirma que essas são as mais frequentes causadoras do fenótipo completo da deficiência combinada de 17&#945;-hidroxilase/17,20-liase em pacientes brasileiros.71171

Six New Cases Confirm The Clinical Molecular Profile Of Complete Combined 17α-hydroxylase/ 17,20-lyase Deficiency In Brazil.

In 2004, Costa-Santos and cols. reported 24 patients from 19 Brazilian families with 17α-hydroxylase deficiency and showed that p.W406R and p.R362C corresponded to 50% and 32% of CYP17A1 mutant alleles, respectively. The present report describes clinical and molecular data of six patients from three inbred Brazilian families with 17α-hydroxlyse deficiency. All patients had hypogonadism, amenorrhea and hypertension at diagnosis. Two sisters were found to be 46,XY with both gonads palpable in the inguinal region. All patients presented hypergonadotrophic hypogonadism, with high levels of ACTH (> 104 ng/mL), suppressed plasmatic renin activity, low levels of potassium ( 4.4 ng/mL). Three of them, including two sisters, were homozygous for p.W406R mutation and the other three (two sisters and one cousin) were homozygous for p.R362C. The finding of p.W406R and p.R362C in the CYP17A1 gene here reported in additional families, confirms them as the most frequent mutations causing complete combined 17α-hydroxylase/17,20-lyase deficiency in Brazilian patients.54711-

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