Effect Of 4-(n,n-dimethylamino)phenethyl alcohol on degree of conversion and cytotoxicity of photo-polymerized CQ-based resin composites

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThe aim of this study was to evaluate the degree of conversion (DC) and the cytotoxicity of photo-cured experimental resin composites containing 4-(N,N-dimethylamino)phenethyl alcohol (DMPOH) combined to the camphorquinone (CQ) compared with ethylamine benzoate (EDAB). The resin composites were mechanically blended using 35 wt% of an organic matrix and 65 wt% of filler loading. To this matrix was added 0.2 wt% of CQ and 0.2 wt% of one of the reducing agents tested. 5x1 mm samples (n=5) were previously submitted to DC measurement and then pre-immersed in complete culture medium without 10% (v/v) bovine serum for 1 h or 24 h at 37 °C in a humidifier incubator with 5% CO2 and 95% humidity to evaluate the cytotoxic effects of experimental resin composites using the MTT assay on immortalized human keratinocytes cells. As a result of absence of normal distribution, the statistical analysis was performed using the nonparametric Kruskal-Wallis to evaluate the cytotoxicity and one-way analysis of variance to evaluate the DC. For multiple comparisons, cytotoxicity statistical analyses were submitted to Student-Newman-Keuls and DC analysis to Tukey's HSD post-hoc test (=0.05). No significant differences were found between the DC of DMPOH (49.9%) and EDAB (50.7%). 1 h outcomes showed no significant difference of the cell viability between EDAB (99.26%), DMPOH (94.85%) and the control group (100%). After 24 h no significant difference were found between EDAB (48.44%) and DMPOH (38.06%), but significant difference was found compared with the control group (p>0.05). DMPOH presented similar DC and cytotoxicity compared with EDAB when associated with CQ.The aim of this study was to evaluate the degree of conversion (DC) and the cytotoxicity of photo-cured experimental resin composites containing 4-(N,N-dimethylamino)phenethyl alcohol (DMPOH) combined to the camphorquinone (CQ) compared with ethylamine benzoate (EDAB). The resin composites were mechanically blended using 35 wt% of an organic matrix and 65 wt% of filler loading. To this matrix was added 0.2 wt% of CQ and 0.2 wt% of one of the reducing agents tested. 5x1 mm samples (n=5) were previously submitted to DC measurement and then pre-immersed in complete culture medium without 10% (v/v) bovine serum for 1 h or 24 h at 37 °C in a humidifier incubator with 5% CO2 and 95% humidity to evaluate the cytotoxic effects of experimental resin composites using the MTT assay on immortalized human keratinocytes cells. As a result of absence of normal distribution, the statistical analysis was performed using the nonparametric Kruskal-Wallis to evaluate the cytotoxicity and one-way analysis of variance to evaluate the DC. For multiple comparisons, cytotoxicity statistical analyses were submitted to Student-Newman-Keuls and DC analysis to Tukey's HSD post-hoc test (=0.05). No significant differences were found between the DC of DMPOH (49.9%) and EDAB (50.7%). 1 h outcomes showed no significant difference of the cell viability between EDAB (99.26%), DMPOH (94.85%) and the control group (100%). After 24 h no significant difference were found between EDAB (48.44%) and DMPOH (38.06%), but significant difference was found compared with the control group (p>0.05). DMPOH presented similar DC and cytotoxicity compared with EDAB when associated with CQ256538542FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO2013/04241-

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

Extração enzimática das proteínas da farinha de arroz Enzymatic extraction of proteins from rice flour

O presente trabalho teve como objetivo extrair enzimaticamente as proteínas de uma farinha comercial de arroz. Visando aumentar o Rendimento de Extração Protéica (REP), os seguintes parâmetros foram avaliados: tipo de enzima (protease alcalina e neutra); temperatura (40, 50 e 60 °C); pH (9,5, 10,5 e 11,0); tratamento físico da amostra (sem tratamento, ultra-turrax a 16.000 rpm e ultra-som a 120 W, ambos por 5, 10 e 15 minutos); relação Enzima:Substrato (E:S) de 5:100 e 10:100; e concentração inicial de matéria-prima (1:3, 1:5 e 1:10 p/v). Os teores de proteínas da farinha de arroz e dos resíduos foram determinados para o cálculo do REP. Os resultados mostraram que a melhor condição de extração protéica, que levou ao maior REP, foi a que empregou a concentração inicial de matéria-prima a 1:10 (p/v), sem tratamento físico, com pH 10,5, com a protease alcalina na relação E:S de 10:100, a 50 °C, tendo atingido um REP de 63,4%.<br>The enzymatic extraction of proteins from a commercial rice flour was studied in this work. In order to increase the Protein Extraction Yield (PEY), the following parameters were evaluated: enzyme type (alkaline and neutral protease); temperature (40, 50 and 60 °C); pH (9.5, 10.5 and 11.0); physical treatment of the sample (no treatment; Ultra-Turrax at 16.000 rpm and ultrasound at 120 W, both for 5, 10 and 15 minutes); enzyme:substrate ratio (E:S) of 5:100 and 10:100 and initial concentration of raw material (1:3, 1:5 and 1:10 w/v). The PEY was calculated using the protein contents of rice flour and the extraction residues. The results showed that the best condition for protein extraction, which gave the highest PEY (63.4%), was that using an initial concentration of raw material of 1:10 (w/v), no physical treatment, pH 10.5, the alkaline protease, an E:S of 10:100, at 50 °C

Efeito de parâmetros hidrolíticos na obtenção de hidrolisados proteicos de farinha de trigo com baixo teor de fenilalanina Effect of hydrolytic parameters in obtaining of protein hydrolysates of wheat flour with low phenylalanine content

Tendo como objetivo a obtenção de hidrolisados proteicos de farinha de trigo com baixo teor de fenilalanina (Phe), foram preparados, inicialmente, extratos proteicos da farinha de trigo, empregando-se método enzimático pela ação de protease de Bacillus licheniformis. Em seguida, esses extratos foram hidrolisados sob a ação do extrato enzimático bruto (EEB), obtido de casca de abacaxi, e de pancreatina comercial; e alguns parâmetros hidrolíticos foram avaliados, tais como temperatura (30; 35; 40; 50; e 70 °C), tempo (1 hora e 30 minutos; 2 horas e 30 minutos; 3 horas e 30 minutos), e pH de reação (6,0; 7,0; 8,0 e 9,0). Para a remoção de Phe, empregou-se o carvão ativado (CA) e a eficiência deste processo foi avaliada determinando-se o teor de Phe por espectrofotometria derivada segunda, na farinha de trigo, assim como nos hidrolisados após tratamento com CA. Para os três parâmetros estudados, observaram-se efeitos variados sobre a remoção de Phe, sendo que os melhores resultados foram encontrados ao se empregar a associação sucessiva de EEB (E:S 10:100, 1 hora e 30 minutos), com a pancreatina (E:S 4:100, 3 horas e 30 minutos), em pH 7,0 a 50 °C, tendo atingido 66,28% de remoção de Phe, o que corresponde a um teor final de Phe de 522,44 mg.100 g-1 de hidrolisado.With the aim of obtaining wheat flour hydrolysates with low-phenylalanine (Phe) content, protein extracts were prepared using an enzymatic method through the action of a protease from Bacillus licheniformis. Next, these protein extracts were hydrolyzed by a crude enzymatic extract (CEE) obtained from pineapple peel followed by a commercial enzyme (pancreatin). Some parameters, such as temperature (30, 35, 40, 50 and 70 °C), time (1 hour and 30 minutes, 2 hours and 30 minutes, 3 hours and 30 minutes), and pH of the reaction (6.0, 7.0, 8.0 and 9.0) were evaluated. Activated carbon (AC) was used for removing Phe and the efficiency of this process was evaluated by second derivative spectrophotometry, measuring Phe content in wheat flour as well as in its hydrolysates after AC treatment. Varied effects were observed for the three parameters studied, and the best results were found using successive association of CEE (E: S 10:100, 1 hour and 30 minutes) with pancreatin (E:S 4:100, 3 hour and 30 minutes) pH 7.0, at 50°C having reached a final Phe content of 522.44 mg.100 g-1 of hydrolysate

Discussões colaborativas em ambiente virtual: uma experiência com alunos do 9º ano

Este artigo apresenta uma pesquisa que foi desenvolvida com vinte alunos do 9º ano, do Ensino Fundamental de uma escola privada, da cidade de Campos dos Goytacazes, no estado do Rio de Janeiro. Teve como objetivo compreender, entre outros aspectos, as justificativas e as conjecturas elaboradas pelos educandos ao resolverem tarefas, envolvendo um problema real em um ambiente virtual. Os grupos foram divididos com 4 alunos, por intermédio de um Ambiente Virtual, onde realizaram discussões de modo colaborativo, objetivando a resolução de atividades propostas. As produções escritas dos educandos foram analisadas à luz da abordagem Qualitativa, tendo como base a Análise de Conteúdo para interpretação dos dados. A partir dos resultados, realizaram-se inferências e reflexões sobre como os educandos construíram conhecimentos em Matemática no ambiente. Pôde-se identificar que essa construção se apoiou no compartilhamento de reflexões, nos vínculos de colaboração e na utilização de conceitos em matemática que convergiram para algumas etapas procedimentais destacadas na Modelagem Matemática