Odabir plijesni Aspergillus fumigatus za proizvodnju prebiotičkih ksilooligosaharida na podlozi od šećerne trske

Sugarcane bagasse is an important lignocellulosic material studied for the production of xylooligosaccharides (XOS). Some XOS are considered soluble dietary fibre, with low caloric value and prebiotic effect, but they are expensive and not easily available. In a screening of 138 fungi, only nine were shortlisted, and just Aspergillus fumigatus M51 (35.6 U/mL) and A. fumigatus U2370 (28.5 U/mL) were selected as the most significant producers of xylanases. These fungi had low β-xylosidase activity, which is desirable for the production of XOS. The xylanases from Trichoderma reesei CCT 2768, A. fumigatus M51 and A. fumigatus U2370 gave a significantly higher XOS yield, 11.9, 14.7 and 7.9 % respectively, in a 3-hour reaction with hemicellulose from sugarcane bagasse. These enzymes are relatively thermostable at 40–50 °C and can be used in a wide range of pH values. Furthermore, these xylanases produced more prebiotic XOS (xylobiose and xylotriose) when compared with a commercial xylanase. The xylanases from A. fumigatus M51 reached a high level of XOS production (37.6 %) in 48–72 h using hemicellulose extracted from sugarcane bagasse. This yield represents 68.8 kg of prebiotic XOS per metric tonne of cane bagasse. In addition, in a biorefinery, after hemicellulose extraction for XOS production, the residual cellulose could be used for the production of second-generation ethanol.Šećerna trska je važan lignocelulozni materijal koji se koristi za ispitivanje proizvodnje ksilooligosaharida. Neki se ksilooligosaharidi upotrebljavaju u prehrani kao topljiva vlakna niske kalorijske vrijednosti s prebiotičkim učinkom, ali su skupi i teško dostupni. Od 138 plijesni u uži je izbor ušlo samo njih devet, od kojih su odabrana samo dva soja što su proizvela najviše ksilanaza, i to Aspergillus fumigatus M51 (35,6 U/mL) i A. fumigatus U2370 (28,5 u/mL). Aktivnost β-ksilozidaze u tim sojevima bila je vrlo slaba, što je pogodovalo nastanku ksilooligosaharida. Djelovanjem ksilanaza su nakon tri sata iz šećerne trske razgradnjom hemiceluloze dobivene veće količine ksilooligosaharida, i to 11,9 % s pomoću plijesni Trichoderma reesei CCT 2768; 14,7 % s pomoću A. fumigatus M51 i 7,9 % s pomoću A. fumigatus U2370. Ti su enzimi relativno termostabilni na temperaturama od 40 do 50 °C, a mogu se koristiti pri različitim pH-vrijednostima. Osim toga, u usporedbi s komercijalnom ksilanazom, ove su ksilanaze proizvele više prebiotičkih ksilooligosaharida (ksilobioze i ksilotrioze). Razgradnjom hemiceluloze izolirane iz šećerne trske pomoću ksilanaze iz plijesni A. fumigatus M51 dobivena je znatna količina (37,6 %) ksilooligosaharida nakon 48-72 sata hidrolize, što odgovara prinosu od 68,8 kg prebiotičkih ksilooligosaharida po toni šećerne trske. Osim toga, nakon izdvajanja hemiceluloze za proizvodnju ksilooligosaharida, preostali dio celuloze može se upotrijebiti u rafineriji za proizvodnju druge generacije biogoriva

Chemical inhibition of the contaminant lactobacillus fermentum from distilleries producing fuel bioethanol

The purpose of this study was to determine the Minimum Inhibitory Concentration (MIC) of pure or mixed chemicals for Saccharomyces cerevisiae and Lactobacillus fermentum in the samples isolated from distilleries with serious bacterial contamination problems. The biocides, which showed the best results were: 3,4,4' trichlorocarbanilide (TCC), tested at pH 4.0 (MIC = 3.12 mg/l), TCC with benzethonium chloride (CBe) at pH 6.0 (MIC = 3.12 mg/l) and TCC mixed with benzalkonium chloride (CBa) at pH 6.0 (MIC = 1.53 mg /l). If CBa was used in sugar cane milling in 1:1 ratio with TCC, a 8 times reduction of CBa was possible. This formulation also should be tested in fermentation steps since it was more difficult for the bacterium to develop resistance to biocide. There was no inhibition of S. cerevisiae and there were only antibiotics as an option to bacterial control of fuel ethanol fermentation by S. cerevisiae573441447FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPSem informaçã

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

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

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

Immobilization of Papain on Chitin and Chitosan and Recycling of Soluble Enzyme for Deflocculation of Saccharomyces cerevisiae from Bioethanol Distilleries

Yeast flocculation (Saccharomyces cerevisiae) is one of the most important problems in fuel ethanol production. Yeast flocculation causes operational difficulties and increase in the ethanol cost. Proteolytic enzymes can solve this problem since it does not depend on these changes. The recycling of soluble papain and the immobilization of this enzyme on chitin or chitosan were studied. Some cross-linking agents were evaluated in the action of proteolytic activity of papain. The glutaraldehyde (0.1-10% w⋅v −1 ), polyethyleneimine (0.5% v⋅v −1 ), and tripolyphosphate (1-10% w⋅v −1 ) inactivated the enzyme in this range, respectively. Glutaraldehyde inhibited all treatments of papain immobilization. The chitosan cross-linked with TPP in 5 h of reaction showed the yield of active immobilized enzyme of 15.7% and 6.07% in chitosan treated with 0.1% PEI. Although these immobilizations have been possible, these levels have not been enough to cause deflocculation of yeast cells. Free enzyme was efficient for yeast deflocculation in dosages of 3 to 4 g⋅L −1 . Recycling of soluble papain by centrifugation was effective for 14 cycles with yeast suspension in time perfectly compatible to industrial conditions. The reuse of proteases applied after yeast suspension by additional yeast centrifugation could be an alternative to cost reduction of these enzymes

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