碳水化合物——蛋白质饮料对运动耐力的影响

人在长时间运动后的疲劳和体内存储的肌糖原的消耗密切相关,因此运动后糖原合成的速度是短时间内运动恢复的关键因素。接下来的实验有效地研究了运动后补充的营养成分对于再次运动时耐力表现的影响。     

Recent advances refining galactooligosaccharide production from lactose

The production of prebiotic galactooligosaccharides (GOS) by the β-galactosidase catalysed conversion of lactose has become commercially important. Yet it remains a challenge to sufficiently understand the structure and activity of β-galactosidase, to increase the efficiency of transgalactosylation and GOS production and to improve the quality of GOS products in a rational way. This review covers the broad but related aspects of GOS synthesis including: the structure and reaction mechanism of β-galactosidase, factors effecting yield and productivity of GOS synthesis systems, the structure of GOS products, models for the kinetics of GOS synthesis and reactor configurations for GOS synthesis. It aims to couple recent discoveries with established knowledge to enhance understanding of the complex biochemistry of GOS synthesis.     

Biogeochemical processes in ethanol stimulated uranium-contaminated subsurface sediments

A laboratory incubation experiment was conducted with uranium-contaminated subsurface sediment to assess the geochemical and microbial community response to ethanol amendment. A classical sequence of terminal electron-accepting processes (TEAPs) was observed in ethanol-amended slurries, with NO3- reduction, Fe(III) reduction, SO4(2-) reduction, and CH4 production proceeding in sequence until all of the added 13C-ethanol (9 mM) was consumed. Approximately 60% of the U(VI) content of the sediment was reduced during the period of Fe(III) reduction. No additional U(VI) reduction took place during the sulfate-reducing and methanogenic phases of the experiment Only gradual reduction of NO3-, and no reduction of U(VI), took place in ethanol-free slurries. Stimulation of additional Fe(III) or SO4(2-) reduction in the ethanol-amended slurries failed to promote further U(VI) reduction. Reverse transcribed 16S rRNA clone libraries revealed major increases in the abundance of organisms related to Dechloromonas, Geobacter, and Herbaspirillum in the ethanol-amended slurries. Phospholipid fatty acids (PLFAs) indicative of Geobacter showed a distinct increase in the amended slurries, and analysis of PLFA 13C/12C ratios confirmed the incorporation of ethanol into these PLFAs. A increase in the abundance of 13C-labeled PLFAs indicative of Desulfobacter, Desulfotomaculum, and Desulfovibrio took place during the brief period of sulfate reduction that followed the Fe(III) reduction phase. Our results show that major redox processes in ethanol-amended sediments can be reliably interpreted in terms of standard conceptual models of TEAPs in sediments. However, the redox speciation of uranium is complex and cannot be explained based on simplified thermodynamic considerations.     

Microbial incorporation of 13C-labeled acetate at the field scale: detection of microbes responsible for reduction of U(VI)

A field-scale acetate amendment experiment was performed in a contaminated aquifer at Old Rifle, CO to stimulate in situ microbial reduction of U(VI) in groundwater. To evaluate the microorganisms responsible for microbial uranium reduction during the experiment, 13C-labeled acetate was introduced into well bores via bio-traps containing porous activated carbon beads (Bio-Sep). Incorporation of the 13C from labeled acetate into cellular DNA and phospholipid fatty acid (PLFA) biomarkers was analyzed in parallel with geochemical parameters. An enrichment of active sigma-proteobacteria was demonstrated in downgradient monitoring wells: Geobacter dominated in wells closer to the acetate injection gallery, while various sulfate reducers were prominent in different downgradient wells. These results were consistent with the geochemical evidence of Fe(III), U(VI), and SO(4)2- reduction. PLFA profiling of bio-traps suspended in the monitoring wells also showed the incorporation of 13C into bacterial cellular lipids. Community composition of downgradient monitoring wells based on quinone and PLFA profiling was in general agreement with the 13C-DNA result. The direct application of 13C label to biosystems, coupled with DNA and PLFA analysis,     

Improved fallow: growth and nitrogen accumulation of five native tree species in Brazil

Nitrogen (N) is the most important yield-limiting factor in agricultural systems, however, N application can lead to emissions and environmental problems such as global warming (N₂O) and groundwater contamination (NO₃ ^?). This study analyses the N balance, nitrogen-use efficiency, and N loss potential of conventional farming systems (arable farming, improved arable farming, and agroforestry) and organic farming systems (mixed farming, arable farming, and agroforestry) based on long-term field experiments in southern Germany. The effects of the conversion of farm structure and N management are identified. The conventional farming systems in this study were high N-input and high N-output systems. The conventional arable farming system had the lowest nitrogen-use efficiency and the highest N surplus. An optimised N management and the use of high-yielding crop varieties improved its nitrogen-use efficiency. The establishment of conventional agroforestry resulted in the reduction of N input, N output and N surplus, while maintaining high yields. The organic mixed farming system is characterised by a relatively high N input and N output, the accumulation of soil organic nitrogen, the highest nitrogen-use efficiency, and the lowest N surplus of all analysed systems. These good results can be attributed to the intensive farm N cycle between soil–plant–animal. The shift from organic mixed farming to organic arable farming system extensified the N cycle, reduced N input, crop yield and N output. The change from organic arable farming to organic agroforestry reduced the N input, increased the biomass yield, and remained the N surplus within an optimal range.     

Mechanisms of Enhanced Catalysis in Enzyme–DNA Nanostructures Revealed through Molecular Simulations and Experimental Analysis

Understanding and controlling the molecular interactions between enzyme substrates and DNA nanostructures has important implications in the advancement of enzyme–DNA technologies as solutions in biocatalysis. Such hybrid nanostructures can be used to create enzyme systems with enhanced catalysis by controlling the local chemical and physical environments and the spatial organization of enzymes. Here we have used molecular simulations with corresponding experiments to describe a mechanism of enhanced catalysis due to locally increased substrate concentrations. With a series of DNA nanostructures conjugated to horseradish peroxidase, we show that binding interactions between substrates and the DNA structures can increase local substrate concentrations. Increased local substrate concentrations in HRP(DNA) nanostructures resulted in 2.9‐ and 2.4‐fold decreases in the apparent Michaelis constants of tetramethylbenzidine and 4‐aminophenol, substrates of HRP with tunable binding interactions to DNA nanostructures with dissociation constants in the micromolar range. Molecular simulations and kinetic analysis also revealed that increased local substrate concentrations enhanced the rates of substrate association. Identification of the mechanism of increased local concentration of substrates in close proximity to enzymes and their active sites adds to our understanding of nanostructured biocatalysis from which we can develop guidelines for enhancing catalysis in rationally designed systems.     

Capture‐Tag‐Release: A Strategy for Small Molecule Labeling of Native Enzymes

A strategy for labeling native enzymes in a manner that preserves their activity is reported: capture–tag–release (CTR). Key to this approach is the small molecule CTR probe that contains an enzyme inhibitor, benzophenone crosslinker, and aryl phosphine ester. After UV‐derived capture of the enzyme, addition of an azide‐containing tag triggers a Staudinger ligation that labels the enzyme. A further consequence of the Staudinger ligation is fragmentation of the CTR probe, thus releasing the inhibitor and restoring enzymatic activity. As a proof‐of‐principle, the CTR strategy was applied to the hydrolase β‐galactosidase. The enzyme was efficiently labeled with biotin, and the kinetic data for the biotinylated enzyme were comparable to those for unlabeled β‐galactosidase. The CTR probe exhibits excellent targeting specificity, as it selectively labeled β‐galactosidase in a complex protein mixture.     

Automated spectral smoothing with spatially adaptive penalized least squares

A variety of data smoothing techniques exist to address the issue of noise in spectroscopic data. The vast majority, however, require parameter specification by a knowledgeable user, which is typically accomplished by trial and error. In most situations, optimized parameters represent a compromise between noise reduction and signal preservation. In this work, we demonstrate a nonparametric regression approach to spectral smoothing using a spatially adaptive penalized least squares (SAPLS) approach. An iterative optimization procedure is employed that permits gradual flexibility in the smooth fit when statistically significant trends based on multiscale statistics assuming white Gaussian noise are detected. With an estimate of the noise level in the spectrum the procedure is fully automatic with a specified confidence level for the statistics. Potential application to the heteroscedastic noise case is also demonstrated. Performance was assessed in simulations conducted on several synthetic spectra using traditional error measures as well as comparisons of local extrema in the resulting smoothed signals to those in the true spectra. For the simulated spectra, a best case comparison with the Savitzky-Golay smoothing via an exhaustive parameter search was performed while the SAPLS method was assessed for automated application. The application to several dissimilar experimentally obtained Raman spectra is also presented.     

Hierarchical Alignment and Full Resolution Pattern Recognition of 2D NMR Spectra: Application to Nematode Chemical Ecology

Nuclear magnetic resonance (NMR) is the most widely used nondestructive technique in analytical chemistry. In recent years, it has been applied to metabolic profiling due to its high reproducibility, capacity for relative and absolute quantification, atomic resolution, and ability to detect a broad range of compounds in an untargeted manner. While one-dimensional (1D) (1)H NMR experiments are popular in metabolic profiling due to their simplicity and fast acquisition times, two-dimensional (2D) NMR spectra offer increased spectral resolution as well as atomic correlations, which aid in the assignment of known small molecules and the structural elucidation of novel compounds. Given the small number of statistical analysis methods for 2D NMR spectra, we developed a new approach for the analysis, information recovery, and display of 2D NMR spectral data. We present a native 2D peak alignment algorithm we term HATS, for hierarchical alignment of two-dimensional spectra, enabling pattern recognition (PR) using full-resolution spectra. Principle component analysis (PCA) and partial least squares (PLS) regression of full resolution total correlation spectroscopy (TOCSY) spectra greatly aid the assignment and interpretation of statistical pattern recognition results by producing back-scaled loading plots that look like traditional TOCSY spectra but incorporate qualitative and quantitative biological information of the resonances. The HATS-PR methodology is demonstrated here using multiple 2D TOCSY spectra of the exudates from two nematode species: Pristionchus pacificus and Panagrellus redivivus. We show the utility of this integrated approach with the rapid, semiautomated assignment of small molecules differentiating the two species and the identification of spectral regions suggesting the presence of species-specific compounds. These results demonstrate that the combination of 2D NMR spectra with full-resolution statistical analysis provides a platform for chemical and biological studies in cellular biochemistry, metabolomics, and chemical ecology.     

Nanostructuring polymeric materials by templating strategies

This contribution summarizes efforts in designing, assembling/synthesizing, and structurally and functionally characterizing nanostructured materials using anodized aluminum oxide (AAO) as a thin-film template. Optical waveguide spectroscopy, using a nanoporous template as the guiding structure, is a particularly powerful analytical tool. The layer-by-layer approach for the fabrication of multilayer assemblies is shown to allow the fabrication of nanotube arrays. In addition to using dendrimers as building blocks, semiconducting nanomaterial (e.g., quantum dot) hybrid architectures with very interesting photophysical properties can be assembled. These can be employed, for example, in biosensing applications. Other strategies for using the AAO layers as templates include the growth of polymeric nanorod arrays from different functional monomers, which, after the dissolution of the template, are still able to guide light. This opens up novel concepts for integrated optics platforms with nanostructured materials.