Projeto de habitação de interesse social sustentável para comunidades pesqueiras e o aproveitamento dos resíduos da maricultura / Sustainable social housing project for fishing communities and the use of mariculture waste

Desenvolvida no Laboratório de Eco Soluções – LabEcoS do IFPE Campus Recife, esta pesquisa tem por objetivo desenvolver uma proposta de habitação de interesse social, sustentável. Para tanto, e entendendo que para ser sustentável, uma proposta deve ser apropriada às diferentes realidades, a pesquisa definiu como objeto de estudo, a elaboração de um projeto arquitetônico desenvolvido para uma localidade específica, no caso, a Povoação de São Lourenço de Tejucupapo, no município de Goiana, litoral norte de Pernambuco. A escolha do local se deu a partir de visitas exploratórias que identificaram a grande produção de resíduos de maricultura, base da subsistência das comunidades pesqueiras, bem como a receptividade para com o grupo de pesquisa. A utilização destes resíduos por sua vez é a base para o desenvolvimento dos materiais de construção aqui estudados

Nanostructured transdermal hormone replacement therapy for relieving menopausal symptoms: a confocal Raman spectroscopy study

OBJECTIVE: To determine the safety and efficacy of a transdermal nanostructured formulation of progesterone (10%) combined with estriol (0.1%) + estradiol (0.25%) for relieving postmenopausal symptoms. METHODS: A total of 66 postmenopausal Brazilian women with climacteric symptoms of natural menopause received transdermal nanostructured formulations of progesterone and estrogens in the forearm daily for 60 months to mimic the normal ovarian secretory pattern. Confocal Raman spectroscopy of hormones in skin layers was performed. Clinical parameters, serum concentrations of estradiol and follicle-stimulating hormone, blood pressure, BI-RADS classification from bilateral mammography, and symptomatic relief were compared between baseline and 60 months post-treatment. Clinicaltrials.gov: NCT02033512. RESULTS: An improvement in climacteric symptoms was reported in 92.5% of women evaluated before and after 60 months of treatment. The serum concentrations of estradiol and follicle-stimulating hormone changed significantly (

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

Molecular characterization of the human erythrovirus B19 in the amazon region.

Para avaliar a circulação e freqüência dos genótipos de eritrovírus na região amazônica, foi analisado um total de 487 amostras de soros/plasmas colhidas de pacientes apresentando sintomas e sinais clínicos sugestivos de infecção pelos eritrovírus. O ensaio imunoenzimático foi utilizado para detecção de anticorpos específicos para B19, das classes IgM/IgG, e a reação em cadeia da polimerase/semi-nested PCR para detecção do DNA. Das 487 amostras examinadas, 117 (24%) mostraram a presença do DNA dos eritrovírus, sendo todas as 117 foram posteriormente seqüenciadas e genotipadas. A maioria dos isolamentos foi classificada como genótipo 1 (91% das amostras) e 3b (9% ). Também observamos três diferentes grupos dentro do genótipo 1 (A1, A2, B). Conseqüentemente, estas linhagens de B19 introduzidas em Belém apresentaram uma elevada taxa de mudanças dos aminoácidos, decorrência da pressão seletiva, gerando reinfecções consecutivas em uma pequena rede de transmissão, metaforicamente comparada a uma \"panela de pressão evolutiva\".To assess the circulation and relative frequency of erythrovirus genotypes in clinical samples from patients living in the Amazon region we screened a total of 487 samples from patients suffering from different clinical manifestations suggestive of erythrovirus infections. Enzyme-linked immunosorbent assay was used to detect B19-specific IgM/IgG antibodies and polymerase chain reaction/ semi-nested PCR for viral DNA detection. Of the 487 samples 117 (24%) were positive for the erythrovirus DNA and all 117 isolates were sequenced and genotyped analyzing a fragment of 476 bp of VP1 and VP2 gene sequences of the erythrovirus. The majority of isolates was classified as genotype 1 (91% of the samples) and 3b (9% of the samples). We also reported three different clusters (A1, A2, B) within genotype 1. Our analysis revealed a strikingly different pattern of evolutionary change for those viral lineages introduced in Belém, which exhibited a higher rate of nonsynonymous substitutions compared to those viruses sampled from other locations