Leishmaniose recidiva cútis

Paciente do sexo masculino, 18 anos. Dois anos após tratamento insuficiente para leishmaniose tegumentar americana, apresentou, na mesma localização, lesão formada por cicatriz atrófica central e nódulos verrucosos na periferia. Era imunocompetente, hígido e negava qualquer trauma local. O diagnóstico de leishmaniose recidiva cutis foi feito através de cultura do aspirado da lesão. Realizou tratamento com N-metilglucamina (20mgSbV/kg/dia) associado à pentoxifilina (1200mg/dia) durante 30 dias alcançando cura clínica. Os casos semelhantes requerem atenção diferenciada pela dificuldade ao tratamento.We present a case of an 18-year-old male patient who, after two years of inappropriate treatment for cutaneous leishmaniasis, began to show nodules arising at the edges of the former healing scar. He was immune competent and denied any trauma. The diagnosis of recurrent cutaneous leishmaniasis was made following positive culture of aspirate samples. The patient was treated with N-methylglucamine associated with pentoxifylline for 30 days. Similar cases require special attention mainly because of the challenges imposed by treatment

Accuracy of mucocutaneous leishmaniasis diagnosis using polymerase chain reaction : systematic literature review and meta-analysis

The diagnosis of mucocutaneous leishmaniasis (MCL) is hampered by the absence of a gold standard. An accurate diagnosis is essential because of the high toxicity of the medications for the disease. This study aimed to assess the ability of polymerase chain reaction (PCR) to identify MCL and to compare these results with clinical research recently published by the authors. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement was performed using comprehensive search criteria and communication with the authors. A meta-analysis considering the estimates of the univariate and bivariate models was performed. Specificity near 100% was common among the papers. The primary reason for accuracy differences was sensitivity. The meta-analysis, which was only possible for PCR samples of lesion fragments, revealed a sensitivity of 71% [95% confidence interval (CI) = 0.59; 0.81] and a specificity of 93% (95% CI = 0.83; 0.98) in the bivariate model. The search for measures that could increase the sensitivity of PCR should be encouraged. The quality of the collected material and the optimisation of the amplification of genetic material should be prioritised

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

Recurrent cutaneous leishmaniasis Leishmaniose recidiva cútis

We present a case of an 18-year-old male patient who, after two years of inappropriate treatment for cutaneous leishmaniasis, began to show nodules arising at the edges of the former healing scar. He was immune competent and denied any trauma. The diagnosis of recurrent cutaneous leishmaniasis was made following positive culture of aspirate samples. The patient was treated with N-methylglucamine associated with pentoxifylline for 30 days. Similar cases require special attention mainly because of the challenges imposed by treatment.<br>Paciente do sexo masculino, 18 anos. Dois anos ap&#243;s tratamento insuficiente para leishmaniose tegumentar americana, apresentou, na mesma localiza&#231;&#227;o, les&#227;o formada por cicatriz atr&#243;fica central e n&#243;dulos verrucosos na periferia. Era imunocompetente, h&#237;gido e negava qualquer trauma local. O diagn&#243;stico de leishmaniose recidiva cutis foi feito atrav&#233;s de cultura do aspirado da les&#227;o. Realizou tratamento com N-metilglucamina (20mgSbV/kg/dia) associado &#224; pentoxifilina (1200mg/dia) durante 30 dias alcan&#231;ando cura cl&#237;nica. Os casos semelhantes requerem aten&#231;&#227;o diferenciada pela dificuldade ao tratamento