Culturele identiteit, taal en artistieke expressie

Niet-projectgebonden publicaties Nederlandse taal en cultuu

Start-up of autotrophic nitrogen removal reactors via sequential biocatalyst addition

A procedure for start-up of oxygen-limited autotrophic nitrification-denitrification (OLAND) in a lab-scale rotating biological contactor (RBC) is presented. In this one-step process, NH4+ is directly converted to N-2 without the need for an organic carbon source. The approach is based on a sequential addition of two types of easily available biocatalyst to the reactor during start-up: aerobic nitrifying and anaerobic, granular methanogenic sludge. The first is added as a source of aerobic ammonia-oxidizing bacteria (AAOB), the second as a possible source of planctomycetes including anaerobic ammonia-oxidizing bacteria (AnAOB). The initial nitrifying biofilm serves as a matrix for anaerobic cell incorporation. By subsequently imposing oxygen limitation, one can create an optimal environment for autotrophic N removal. In this way, N removal of about 250 mg of N L-1 d(-1) was achieved after 100 d treating a synthetic NH4+-rich wastewater. By gradually imposing higher loads on the reactor, the N elimination could be increased to about 1.8 g of N L-1 d(-1) at 250 d. The resulting microbial community was compared with that of the inocula using general bacterial and AAOB- and planctomycete-specific PCR primers. Subsequently, the RBC reactor was shown to treat a sludge digestor effluent under suboptimal and strongly varying conditions. The RBC biocatalyst was also submitted to complete absence of oxygen in a fixed-film bioreactor (FFBR) and proved able to remove NH4+ with NO2- as electron acceptor (maximal 434 mg of NH4+-N (g of VSS)(-1) d(-1) on day 136). DGGE and real-time PCR analysis demonstrated that the RBC biofilm was dominated by members of the genus Nitrosomonas and close relatives of Kuenenia stuttgartiensis, a known AnAOB. The latter was enriched during FFBR operation, but AAOB were still present and the ratio planctomycetes/AAOB rRNA gene copies was about 4.3 after 136 d of reactor operation. Whether this relates to an active role of AAOB in the anoxic N removal process remains to be solved

Effect of ingestion of dark chocolates with similar lipid composition and different cocoa content on antioxidant and lipid status in healthy humans

The association between in vitro antioxidant capacity of dark chocolates with different cocoa percentage and the in vivo response on antioxidant status was investigated. In a randomized crossover design, 15 healthy volunteer consumed 100 g of high antioxidants dark chocolate (HADC) or dark chocolate (DC). In vitro, HADC displayed a higher Total Antioxidant Capacity (TAC) than DC. In vivo, plasma TAC significantly peaked 2 h after ingestion of both chocolates. TAC levels went back to zero 5 h after DC ingestion whilst levels remained significantly higher for HADC. HADC induced a significantly higher urinary TAC in the 5-12 h interval time than DC. No change was detected in urinary excretion of F2-isoprostanes. Plasma thiols and triacylglycerol (TG) levels significantly increased for both chocolate with a peak at 2 h remaining significantly higher for DC after 5 h respect to HADC. Results provide evidence of a direct association between antioxidant content of chocolate and the extent of in vivo response on plasma antioxidant capacity. (C) 2011 Elsevier Ltd. All rights reserved

HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment. In this study, we compared four FLs trained with different sequence populations. Epistatic interactions were learned from three different cross-sectional BNs, trained with sequence from patients experienced with indinavir (BNT), all protease inhibitors (PIs) (BNP) or all PI except indinavir (BND). Scaling the fitness landscape was done using cross-sectional data from drug naïve and indinavir experienced patients (Fcross using BNT) and using longitudinal sequences from patients failing indinavir (FlongT using BNT, FlongP using BNP, FlongD using BND). Evaluation to predict the failing sequence and therapy outcome was performed on independent sequences of patients on indinavir. Parameters included estimated fitness (LogF), the number of generations (GF) or mutations (MF) to reach the fitness threshold (average fitness when a major resistance mutation appeared), the number of generations (GR) or mutations (MR) to reach a major resistance mutation and compared to genotypic susceptibility score (GSS) from Rega and HIVdb algorithms. In pairwise FL comparisons we found significant correlation between fitness values for individual sequences, and this correlation improved after correcting for the subtype. Furthermore, FLs could predict the failing sequence under indinavir-containing combinations. At 12 and 48 weeks, all parameters from all FLs and indinavir GSS (both for Rega and HIVdb) were predictive of therapy outcome, except MR for FlongT and FlongP. The fitness landscapes have similar predictive power for treatment response under indinavir-containing regimen as standard rules-based algorithms, and additionally allow predicting genetic evolution under indinavir selective pressure

Estimating the individualized HIV-1 genetic barrier to resistance using a nelfinavir fitness landscape

<p>Abstract</p> <p>Background</p> <p>Failure on Highly Active Anti-Retroviral Treatment is often accompanied with development of antiviral resistance to one or more drugs included in the treatment. In general, the virus is more likely to develop resistance to drugs with a lower genetic barrier. Previously, we developed a method to reverse engineer, from clinical sequence data, a fitness landscape experienced by HIV-1 under nelfinavir (NFV) treatment. By simulation of evolution over this landscape, the individualized genetic barrier to NFV resistance may be estimated for an isolate.</p> <p>Results</p> <p>We investigated the association of estimated genetic barrier with risk of development of NFV resistance at virological failure, in 201 patients that were predicted fully susceptible to NFV at baseline, and found that a higher estimated genetic barrier was indeed associated with lower odds for development of resistance at failure (OR 0.62 (0.45 - 0.94), per additional mutation needed, p = .02).</p> <p>Conclusions</p> <p>Thus, variation in individualized genetic barrier to NFV resistance may impact effective treatment options available after treatment failure. If similar results apply for other drugs, then estimated genetic barrier may be a new clinical tool for choice of treatment regimen, which allows consideration of available treatment options after virological failure.</p

RegaDB: Community-driven data management and analysis for infectious diseases

Summary: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB pr

Low emission development strategies in agriculture. An agriculture, forestry, and other land uses (AFOLU) perspective

As countries experience economic growth and choose among available development pathways, they are in a favorable position to adopt natural resource use technologies and production practices that favor efficient use of inputs, healthy soils, and ecosystems. Current emphasis on increasing resilience to climate change and reducing agricultural greenhouse gasses (GHG) emissions strengthens the support for sustainable agricultural production. In fact, reducing losses in soil fertility, reclaiming degraded lands, and promoting synergistic interaction between crop production and forests are generally seen as good climate change policies. In order for decision-makers to develop long-term policies that address these issues, they must have tools at their disposal that evaluate trade-offs, opportunities, and repercussions of the options considered. In this paper, the authors combine and reconcile the output of three models widely accessible to the public to analyze the impacts of policies that target emission reduction in the agricultural sector. We present an application to Colombia which reveals the importance of considering the full scope of interactions among the various land uses. Results indicate that investments in increasing the efficiency and productivity of the livestock sector and reducing land allocated to pasture are preferable to policies that target deforestation alone or target a reduction of emissions in crop production. Investments in livestock productivity and land-carrying capacity would reduce deforestation and provide sufficient gains in carbon stock to offset greater emissions from increased crop production while generating higher revenues