25 research outputs found

    Bioprocess and biotecnology: effect of xylanase from Aspergillus niger and Aspergillus flavus on pulp biobleaching and enzyme production using agroindustrial residues as substract

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    This study compares two xylanases produced by filamentous fungi such as A. niger and A. flavus using agroindustrial residues as substract and evaluated the effect of these enzymes on cellulose pulp biobleaching process. Wheat bran was the best carbon source for xylanase production by A. niger and A. flavus. The production of xylanase was 18 and 21% higher on wheat bran when we compare the xylanase production with xylan. At 50°C, the xylanase of A. niger retained over 85% activity with 2 h of incubation, and A. flavus had a half-life of more than 75 minutes. At 55°C, the xylanase produced by A. niger showed more stable than from A. flavus showing a half-life of more than 45 minutes. The xylanase activity of A. niger and A. flavus were somehow protected in the presence of glycerol 5% when compared to the control (without additives). On the biobleaching assay it was observed that the xylanase from A. flavus was more effective in comparison to A. niger. The kappa efficiency corresponded to 36.32 and 25.93, respectively. That is important to emphasize that the cellulase activity was either analyzed and significant levels were not detected, which explain why the viscosity was not significantly modified.This work was supported by grants from Conselho de Desenvolvimento Científico e Tecnológico (CNPq). This work was part of Master Dissertation of NCAG (Laboratório de Bioquímica / CCBS, Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brasil). The authors gratefully for the support from the USP/Ribeirão Preto – SP, Brazil.This work was supported by grants from Conselho de Desenvolvimento Científico e Tecnológico (CNPq). This work was part of Master Dissertation of NCAG (Laboratório de Bioquímica / CCBS, Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brasil). The authors gratefully for the support from the USP/Ribeirão Preto – SP, Brazil

    A novel xylan degrading β-D-xylosidase: purification and biochemical characterization

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    Aspergillus ochraceus, a thermotolerant fungus isolated in Brazil from decomposing materials, produced an extracellular b-xylosidase that was purified using DEAE-cellulose ion exchange chromatography, Sephadex G-100 and Biogel P-60 gel filtration. b-xylosidase is a glycoprotein (39 % carbohydrate content) and has a molecular mass of 137 kDa by SDS-PAGE, with optimal temperature and pH at 70 C and 3.0–5.5, respectively.b-xylosidase was stable in acidic pH (3.0–6.0) and 70 C for 1 h. The enzyme was activated by 5 mM MnCl2 (28 %)and MgCl2 (20 %) salts. The b-xylosidase produced by A. ochraceus preferentially hydrolyzed p-nitrophenyl-b- D-xylopyranoside, exhibiting apparent Km and Vmax values of 0.66 mM and 39 U (mg protein)-1 respectively, and to a lesser extent p-nitrophenyl-b-D-glucopyranoside. The enzyme was able to hydrolyze xylan from different sources,suggesting a novel b-D-xylosidase that degrades xylan. HPLC analysis revealed xylans of different compositions which allowed explaining the differences in specificity observed by b-xylosidase. TLC confirmed the capacity.This work was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), and the Conselho de Desenvolvimento Científico e Tecnológico (CNPq). J. A. J. and M. L. T. M. P are Research Fellows of CNPq. M. M. was a recipient of a FAPESP fellowship and this work is part of her Doctoral Thesis. It is also part of the project SISBIOTA CNPq: 563260/2010-6 and FAPESP: 2010/52322-3

    Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

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    Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

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    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

    Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

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    Background Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. Methods We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI <18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For schoolaged children and adolescents, we report thinness (BMI <2 SD below the median of the WHO growth reference) and obesity (BMI >2 SD above the median). Findings From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%) with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and 42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents, the increases in double burden were driven by increases in obesity, and decreases in double burden by declining underweight or thinness. Interpretation The combined burden of underweight and obesity has increased in most countries, driven by an increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of underweight while curbing and reversing the increase in obesit

    Pervasive gaps in Amazonian ecological research

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    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
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