Thermally induced cyclization of L‐isoleucyl‐L‐alanine in solid state: Effect of dipeptide structure on reaction temperature and self‐assembly

Thermal treatment of short‐chain oligopeptides is able to initiate the process of their self‐assembly with the formation of organic nanostructures with unique properties. On the other hand, heating can lead to a chemical reaction with the formation of new substances with specific properties and ability to form structures with different morphology. Therefore, in order to have a desired process, researcher needs to find its temperature range. In the present work, cyclization of _L‐isoleucyl‐_L‐alanine dipeptide in the solid state upon heating was studied. Kinetic parameters of this reaction were estimated within the approaches of the nonisothermal kinetics. The correlation between side chain structure of dipeptides and temperature of their cyclization in the solid state was found for the first time. This correlation may be used to predict the temperature, at which dipeptide self‐assembly changes to chemical reaction. The differences in self‐assembly of linear and cyclic dipeptides were demonstrated using atomic force microscopy. The effect of dipeptide concentration in a source solution and an organic solvent used on self‐assembly of dipeptides was shown. The new information obtained on the thermal properties and self‐assembly of linear and cyclic forms of _L‐isoleucyl‐_L‐alanine may be useful for the design of new nanomaterials based on oligopeptides, as well as for the synthesis of cyclic oligopeptides.     

Infrastructure and the environment in the Anthropocene

For centuries, man‐made infrastructure has been viewed as separate from natural systems. Yet in the past few centuries, as the scale and scope of human activities have dramatically increased, there is accumulating evidence that natural systems are becoming increasingly, and in some cases entirely, managed by humans. The dichotomy between infrastructure and the environment is narrowing, and natural systems are increasingly becoming human design spaces. This is already apparent with the management of hydrologic systems for urban water supply, wildlife, agriculture, forests, and even the atmosphere, and we can expect management of the environment to become more so as human activities grow. Yet our infrastructure largely remains obdurate. They are designed to last for long times even as changes in the environment and technology accelerate. As such, our current infrastructure paradigms fail at the level of the complex, integrated systems and behaviors that characterize the Anthropogenic Earth. Infrastructure in the future will need to be designed for adaptive capacity and the complexities associated with techno‐environmental systems.     

A general kinetic model for biological nutrient removal activated sludge systems: model development

In this article, a kinetic model is developed and presented for biological nutrient removal (BNR) activated sludge (BNRAS) systems in general, but for external nitrification (EN) BNRAS (ENBNRAS) systems in particular. The model is based on the UCTPHO model, but includes some significant modifications, such as anoxic P uptake and associated denitrification by phosphorus accumulating organisms (PAOs). Some key features of the model are described and discussed before the model is presented. Model evaluation will be addressed in another article (Hu et al., 2007).     

不同酿酒酵母菌株来源异麦芽糖酶IMA1的克隆、表达及表征

[目的]异麦芽糖酶IMA1在充分利用含有α-1,6-O-糖苷键的低聚糖中起着关键作用。[方法]在本研究中,对来自4株酿酒酵母菌株（包括3株嗜酸性菌株）来源的异麦芽糖酶IMA1进行克隆、表达、纯化和表征。[结果]研究发现,4种异麦芽糖酶IMA1表现出类似的pH和温度依赖性,但表现出不同的动力学参数和热稳定性。IMA1-A对α-MG（α-甲基葡糖苷）表现出最高的结合亲和力、转换数、催化效率和热稳定性。结构和序列分析表明,2个远离活性位点和底物结合位点的氨基酸的差异对异麦芽糖酶IMA1的动力学参数和热稳定性有重要影响。[结论]本研究结果对进一步研究异麦芽糖酶IMA1的结构-功能关系奠定了基础。     

Hybrid physics-based and data-driven modeling for bioprocess online simulation and optimization

Model-based online optimization has not been widely applied to bioprocesses due to the challenges of modeling complex biological behaviors, low-quality industrial measurements, and lack of visualization techniques for ongoing processes. This study proposes an innovative hybrid modeling framework which takes advantages of both physics-based and data-driven modeling for bioprocess online monitoring, prediction, and optimization. The framework initially generates high-quality data by correcting raw process measurements via a physics-based noise filter (a generally available simple kinetic model with high fitting but low predictive performance); then constructs a predictive data-driven model to identify optimal control actions and predict discrete future bioprocess behaviors. Continuous future process trajectories are subsequently visualized by re-fitting the simple kinetic model (soft sensor) using the data-driven model predicted discrete future data points, enabling the accurate monitoring of ongoing processes at any operating time. This framework was tested to maximize fed-batch microalgal lutein production by combining with different online optimization schemes and compared against the conventional open-loop optimization technique. The optimal results using the proposed framework were found to be comparable to the theoretically best production, demonstrating its high predictive and flexible capabilities as well as its potential for industrial application.     

Wood addition in the hatchery and river environments affects post‐release performance of overwintering brown trout

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Chromatographic approach to study the configurational stability of Ni(II) complexes of amino‐acid Schiff bases possessing stereogenic nitrogen

Herein, we disclose the design of a model Ni(II) complex of glycine Schiff base possessing single‐nitrogen stereogenic center, which was successfully used for high‐performance liquid chromatography (HPLC)‐assisted assessment of its configurational stability. The major finding is that the configurational stability of the Ni(II)‐coordinated nitrogen is profoundly dependent on the reaction conditions used, in particular the solvent, and can range from inconsequential (t_½ less than 5 min) to virtually completely stable (t_½ 90 y). The discovery reported in this study most likely to be of certain theoretical and synthetic value.     

Identifying ecological drivers of interspecific variation in song complexity in songbirds (Passeriformes,Passeri)

A diversity of selective pressures and stochastic processes have likely created substantial variation in song structure, creating difficulties in quantifying the influence of specific ecological factors. This problem is further compounded by differences in study taxa and methods of data analysis between studies. Large comparative studies offer the potential to mitigate some of these methodological difficulties by maximizing the power of statistical analyses and minimizing the probability of misidentifying the magnitude and direction of relationships between independent and dependent variables. In this study, we quantified song complexity for 367 species of globally distributed songbirds (Passeriformes, Passeri). We quantified eight individual acoustic variables that have previously been linked to audio complexity which we analyzed independently, and after applying multivariate statistics to the variables. We used Bayesian linear mixed effect models to test multiple hypotheses regarding song complexity: that it should be greater in open habitats, in migratory species, for sexually monomorphic species, at higher latitudes and altitudes, and that it should co‐vary with clutch size characteristics. Our results challenge perceptions of the effect of habitat structure on song complexity; for instance, counter to expectation, we found songs in closed environments to have reduced syllable diversity. Additionally, our results suggest song complexity may not be ubiquitously a means of communicating male quality, with no significant difference between recordings from monomorphic and dimorphic species. By estimating song complexity in multiple ways, and quantifying these over large taxonomic and spatial scales, we are able to gain a more nuanced understanding of how song complexity is potentially affected by a range of biotic and abiotic factors. Our results also suggest that caution is required when making generalized statements about the relative influence of different factors on song complexity; more densely‐sampled, group‐specific studies are necessary complements to this taxonomically broad analysis.