Tumor de Frantz em paciente do sexo feminino com diarreia: relato de caso de neoplasia pancreática rara

O tumor pseudopapilar sólido, também conhecido como tumor de Frantz, é um tumor raro do pâncreas. Relatamos o caso de uma paciente de 25 anos com dor abdominal, febre, diarréia e perda de peso.TC de abdome com contraste revelou pâncreas alargado com lesão hipodensa de aparência nodular e calcificações periféricas. Foi decidido realizar pancreatectomia subtotal com linfadenectomia e optou-se pela esplenectomia com biópsia hepática intra-operatória. O anatomopatológico da ressecção cirúrgica do tumor pancreático revelou tumor pseudopapilar sólido compatível com o tumor de Frantz. A imuno-histoquímica confirmou os achados histopatológicos. Ela evoluiu com fístula pancreática e pancreatite resolvida após 15 dias. Atualmente, está sendo acompanhada ambulatorialmente em nosso serviço com remissão completa dos sintomas.Solid pseudopapillary tumor, also known as frantz tumor, is a rare tumor of the pancreas. We report a case of 25-year-old female patient with abdominal pain, fever, diarrhea and weight loss. Contrast abdominal CT showed enlarged pancreas with a hypodense lesion of nodular appearance and peripheral calcifications.It was decided to perform subtotal pancreatectomy with lymphadenectomy, and opted for splenectomy and intraoperative liver biopsy. The pathology of surgical resection of the pancreatic tumor showed solid pseudopapillary tumor compatible with Frantz’s tumor. Immunohistochemistry confirmed histopathological findings. She evolved with pancreatic fistula and pancreatitis resolved after 15 days. Currently, it is being followed up in our service with complete remission of symptoms

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

Synthesis of piplartine analogs and preliminary findings on structure–antimicrobial activity relationship

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2018-04-23T14:10:54Z No. of bitstreams: 1 Fregnam AM Synthesis of piplartine.pdf: 1853217 bytes, checksum: 194ed12d0c7b2d0823762280877833fa (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2018-04-23T14:32:47Z (GMT) No. of bitstreams: 1 Fregnam AM Synthesis of piplartine.pdf: 1853217 bytes, checksum: 194ed12d0c7b2d0823762280877833fa (MD5)Made available in DSpace on 2018-04-23T14:32:48Z (GMT). No. of bitstreams: 1 Fregnam AM Synthesis of piplartine.pdf: 1853217 bytes, checksum: 194ed12d0c7b2d0823762280877833fa (MD5) Previous issue date: 2017FAPEMIG (APQ-01209-13), CAPES, CNPq and FINEP.Universidade Federal de Alfenas. Faculdade de Ciências Farmacêuticas. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Instituto de Química. Alfenas, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Hospital São Rafael. Centro de Biotecnologia e Terapia Celular. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Hospital São Rafael. Centro de Biotecnologia e Terapia Celular. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilUniversidade Federal de Alfenas. Instituto de Ciências Biomédicas. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Instituto de Ciências Biomédicas. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Instituto de Ciências Biomédicas. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Instituto de Ciências Biomédicas. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Instituto de Ciências Biomédicas. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Faculdade de Ciências Farmacêuticas. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Instituto de Química. Alfenas, MG, BrasilUniversidade Federal de Alfenas. Instituto de Química. Alfenas, MG, BrasilAbstract In this work it is described the synthesis, characterization and antimicrobial and toxicity evaluation of a series of analogs of piplartine, a piperamide found in Piper sp. The compounds structures were confirmed by infrared spectroscopy, 1H, 13C nuclear magnetic resonance, high resolution mass spectroscopy and were evaluated against strains of Candida spp., Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa. Derivative 24 was almost four-fold more potent (IC50: 48.83 μM) and five-fold less toxic (SI > 3) than piplartine (IC50: 189.2 μM; SI: 0.21) against Candida krusei, as well as two-fold more potent than fluconazole (IC50: 104.48 μM). This compound was also active against Candida tropicalis at 97.67 μM. Benzoyl derivative 17 was three-fold more potent (IC50: 85.2 μM) and more than five-fold less toxic (CC50: 231.71 μM) than piplartine (IC50: 315.33 μM and CC50: 41.14 μM) against Staphylococcus aureus. Given these findings, we have found analogs of piplartine which can be assumed as prototypes for the optimization and the development of new antimicrobial (compounds 24 and 17) agents

Comprehensive Analysis of <em>BRCA1</em>, <em>BRCA2</em> and <em>TP53</em> Germline Mutation and Tumor Characterization: A Portrait of Early-Onset Breast Cancer in Brazil

<div><p>Germline mutations in <i>BRCA1</i>, <i>BRCA2</i> and <i>TP53</i> genes have been identified as one of the most important disease-causing issues in young breast cancer patients worldwide. The specific defective biological processes that trigger germline mutation-associated and -negative tumors remain unclear. To delineate an initial portrait of Brazilian early-onset breast cancer, we performed an investigation combining both germline and tumor analysis. Germline screening of the <i>BRCA1, BRCA2</i>, <i>CHEK2</i> (c.1100delC<i>)</i> and <i>TP53</i> genes was performed in 54 unrelated patients <35 y; their tumors were investigated with respect to transcriptional and genomic profiles as well as hormonal receptors and HER2 expression/amplification. Germline mutations were detected in 12 out of 54 patients (22%) [7 in <i>BRCA1</i> (13%), 4 in <i>BRCA2</i> (7%) and one in <i>TP53</i> (2%) gene]. A cancer familial history was present in 31.4% of the unrelated patients, from them 43.7% were carriers for germline mutation (37.5% in <i>BRCA1</i> and in 6.2% in the <i>BRCA2</i> genes). Fifty percent of the unrelated patients with hormone receptor-negative tumors carried <i>BRCA1</i> mutations, percentage increasing to 83% in cases with familial history of cancer. Over-representation of DNA damage-, cellular and cell cycle-related processes was detected in the up-regulated genes of <i>BRCA1/2</i>-associated tumors, whereas cell and embryo development-related processes were over-represented in the up-regulated genes of <i>BRCA1/2</i>-negative tumors, suggesting distinct mechanisms driving the tumorigenesis. An initial portrait of the early-onset breast cancer patients in Brazil was generated pointing out that hormone receptor-negative tumors and positive familial history are two major risk factors for detection of a <i>BRCA1</i> germline mutation. Additionally, the data revealed molecular factors that potentially trigger the tumor development in young patients.</p> </div

Differentially expressed genes between BRCA1/BRCA2-negative and -positive mutation-driven tumors.

<p>(*)Concordant results in gene expression and array-CGH analysis.</p

Distribution of <i>BRCA1/2</i> status according to immunohistochemical characteristics and familial history.

<p>WT, wild type; UV, unclassifed variant; MUT, mutated; FH, cancer family history; HR, hormonal receptor tumor; TN, triple negative; NTN, non-triple negative; (+), positive; (−), negative; p, Pearson chi-square.</p><p>(*) Statistically significant with a 95% confidence interval; for familial history distribution the 54 unrelated young patients were considered; for distribution of HR, TN/NTN and HER2 status the 55 young patients (54 unrelated and one sister) were considered.</p