Structure−Activity Relationships of Cinnamate Ester Analogues as Potent Antiprotozoal Agents

Protozoal infections are still a global health problem, threatening the lives of millions of people around the world, mainly in impoverished tropical and sub-tropical regions. Thus, in view of the lack of efficient therapies and increasing resistances against existing drugs, this study describes the antiprotozoal potential of synthetic cinnamate ester analogues and their structure-activity relationships. In general, Leishmania donovani and Trypanosoma brucei were quite susceptible to the compounds in a structure-dependent manner. Detailed analysis revealed a key role of the substitution pattern on the aromatic ring and a marked effect of the side chain on the activity against these two parasites. The high antileishmanial potency and remarkable selectivity of the nitro-aromatic derivatives suggested them as promising candidates for further studies. On the other hand, the high in vitro potency of catechol-type compounds against T. brucei could not be extrapolated to an in vivo mouse model.     

Partitioning of predominant lipophilic bioactives (squalene, α-tocopherol and β-sitosterol) during olive oil processing

The partitioning of predominant lipophilic olive bioactives (squalene, β-sitosterol and α-tocopherol) in olive oil processing was studied for the first time using common integrated olive milling plant. 7% of the oil and 5% of the squalene present in the olives was lost in the last pomace. β-sitosterol and α-tocopherol, which are mainly concentrated in the seed of the olive fruit, was recovered in virgin olive oil to a lesser extent (66%, 67%) while 10% were lost in last pomace. Thus, the loss of β-sitosterol and α-tocopherol was higher than that of squalene and oil, due to nonrecovered bound forms. 19% of the α-tocopherol and 21% of the β-sitosterol loss was unaccounted for, which can be attributed to degradation of α-tocopherol and incomplete recovery of sterols from the olive and pomace matrices. This study provides a basis for process development studies.     

Ecophysiology and niche differentiation of Nitrospira-like bacteria, the key nitrite oxidizers in wastewater treatment plants.

Nitrite-oxidizing bacteria of the genus Nitrospira are key nitrifiers in wastewater treatment plants. Pure cultures of these organisms are unavailable, but cultivation-independent molecular methods make it possible to detect Nitrospira-like bacteria in environmental samples and to investigate their ecophysiology. Comprehensive screening of natural and engineered habitats and of public databases for 16S rRNA sequences of Nitrospira-like bacteria revealed a surprisingly high biodiversity in the genus Nitrospira, which comprises at least four phylogenetic sublineages. All Nitrospira-like bacteria detected in wastewater treatment plants belonged to the sublineages I and II. Subsequently, the population dynamics of different Nitrospira-like bacteria were monitored, by quantitative fluorescence in situ hybridization with rRNA-targeted probes, confocal laser scanning microscopy and digital image analysis, during incubation of nitrifying activated sludge in media containing different nitrite concentrations. These experiments showed that Nitrospira-like bacteria, which were affiliated with the phylogenetic sublineages I or II of the genus Nitrospira, responded differently to nitrite concentration shifts. Previously unknown properties of Nitrospira-like bacteria were discovered in the course of an environmental genomics project. Implications of the obtained results for fundamental understanding of the microbial ecology of nitrite oxidizers as well as for future improvement of nutrient removal in wastewater treatment plants are discussed.     

Sensor guided handling and assembly of active micro-systems

Positioning accuracies in the range of a few micrometers and below are necessary for the assembly of active micro-systems. In order to reach these accuracies, an assembly system for sensor guided micro-assembly is developed in the Collaborative Research Centre 516 “Design and manufacturing of active micro-systems”. The combination of a parallel robot with an integrated 3D vision sensor and a micro-gripper enables to reach relative positioning accuracies below 1 μm.     

Fast maximum intensity projections of large medical data sets by exploiting hierarchical memory architectures.

Maximum intensity projections (MIPs) are an important visualization technique for angiographic data sets. Efficient data inspection requires frame rates of at least five frames per second at preserved image quality. Despite the advances in computer technology, this task remains a challenge. On the one hand, the sizes of computed tomography and magnetic resonance images are increasing rapidly. On the other hand, rendering algorithms do not automatically benefit from the advances in processor technology, especially for large data sets. This is due to the faster evolving processing power and the slower evolving memory access speed, which is bridged by hierarchical cache memory architectures. In this paper, we investigate memory access optimization methods and use them for generating MIPs on general-purpose central processing units (CPUs) and graphics processing units (GPUs), respectively. These methods can work on any level of the memory hierarchy, and we show that properly combined methods can optimize memory access on multiple levels of the hierarchy at the same time. We present performance measurements to compare different algorithm variants and illustrate the influence of the respective techniques. On current hardware, the efficient handling of the memory hierarchy for CPUs improves the rendering performance by a factor of 3 to 4. On GPUs, we observed that the effect is even larger, especially for large data sets. The methods can easily be adjusted to different hardware specifics, although their impact can vary considerably. They can also be used for other rendering techniques than MIPs, and their use for more general image processing task could be investigated in the future.     

Occupational Factors and 5-Year Weight Change Among Men in a Danish National Cohort.

This study explored whether factors related to the work environment could predict changes in body mass index (BMI) and whether the effect of psychosocial factors was dependent on baseline BMI. The sample consisted of 1,980 male employees from the Danish National Work Environment Cohort Study. Changes in BMI between 1995 and 2000 were analyzed, by multiple regression, as a function of background variables and a series of occupational variables obtained in 1995. Age, baseline BMI, job insecurity, and psychological demands predicted changes in BMI. Job insecurity and high or low psychological demands increased the likelihood of weight gain among obese employees, whereas they increased the likelihood of weight loss among employees with a low BMI. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Quality Control for Scalable Media Processing Applications

Many media processing applications create a load that varies significantly over time. Hence, if such an application is assigned a lower processing-time budget than needed in its worst-case load situation, deadline misses are likely to occur. This problem can be dealt with by designing media processing applications in a scalable fashion. A scalable media processing application can run in multiple qualities, leading to correspondingly different resource demands. The problem we consider is to find an accompanying quality control strategy, which minimizes both the number of deadline misses and the number of quality changes, while maximizing the quality of processing. We present an initial approach to the above problem by modeling it as a Markov decision process (MDP). Our model is based on measuring relative progress at milestones. Solving the MDP results in a quality control strategy that can be applied during runtime with only little overhead. We evaluate our approach by means of a practical example, which concerns a scalable MPEG-2 decoder.