Governability Assessment for Fisheries and Coastal Systems: A Reality Check

In this article we argue that in order to understand why some governance systems deliver while others do not, we need to assess contributions and limitations of governability. Here, governability refers to a measure of how governable a particular fisheries and coastal system is. Such a system is always comprised of two parts: a system-to-be-governed and a governing system. Governability also depends on the interactions between these two systems. We provide key variables that must be assessed in order to determine governability related to these systems and their interactions. A governability assessment framework is proposed here to suggest that governance performance can only be judged from what is in the potential of the governing system, given the limitations of the governabiltiy of the system-to-be governed, the governing system itself, and their interactions. Such an assessment helps identify what exactly governing systems can and should do in order to enhance their performance.     

Dynamic Service Discovery for Mobile Computing: Intelligent Agents Meet Jini in the Aether

The emergence of ad-hoc pervasive connectivity for devices based on Bluetooth-like systems provides a new way to create applications for mobile systems. We seek to realize ubiquitous computing systems based on the cooperation of autonomous, dynamic and adaptive components (hardware as well as software) which are located in vicinity of one another. In this paper we present this vision. We also describe a prototype system we have developed that implements parts of this vision – in particular a system that combines agent oriented and service oriented approaches and provides dynamic service discovery. We point out why existing systems such as Jini are not suited for this task, and how our system improves on them.     

Evolution of complexity in miRNA-mediated gene regulation systems

Using Arabidopsis microRNA (miRNA)-mediated gene regulation system as a model, we investigated how complex systems evolve with special attention to selection to maintain the systems. We found that the copy number of miRNA genes within each system is a key factor to determine the complexity of the system, indicating a crucial role of gene duplication to increase the complexity. Furthermore, we show that the mode of selection to maintain the systems depend on their complexity levels.     

Chemical Reaction Systems with Toric Steady States

Mass-action chemical reaction systems are frequently used in computational biology. The corresponding polynomial dynamical systems are often large (consisting of tens or even hundreds of ordinary differential equations) and poorly parameterized (due to noisy measurement data and a small number of data points and repetitions). Therefore, it is often difficult to establish the existence of (positive) steady states or to determine whether more complicated phenomena such as multistationarity exist. If, however, the steady state ideal of the system is a binomial ideal, then we show that these questions can be answered easily. The focus of this work is on systems with this property, and we say that such systems have toric steady states. Our main result gives sufficient conditions for a chemical reaction system to have toric steady states. Furthermore, we analyze the capacity of such a system to exhibit positive steady states and multistationarity. Examples of systems with toric steady states include weakly-reversible zero-deficiency chemical reaction systems. An important application of our work concerns the networks that describe the multisite phosphorylation of a protein by a kinase/phosphatase pair in a sequential and distributive mechanism.     

Regulated gene expression from adenovirus vectors: a systematic comparison of various inducible systems

Positively and tightly regulated gene expression is essential for gene function and gene therapy research. The currently-used inducible gene expression systems include tetracycline (Tet-on and T-REx), ecdysone, antiprogestin and dimerizer-based systems. Adenovirus (Ad) vectors play an important role in gene function and gene therapy research for their various advantages over other vector systems. Previously, we reported the inferiority of the Tet-on system as an inducible gene expression system in the context of Ad vectors in comparison with the Tet-off system. In this study, to identify an optimal system for regulated gene expression from Ad vectors, we made a rigorous direct comparison of these five inducible gene expression systems in three cell lines using the luciferase reporter gene. The highest sensitivity to the respective inducer was that of the dimerizer system, followed by the antiprogestin system. The lowest basal expression and the highest induction factor were both characteristic of the dimerizer system. Furthermore, the dimerizer and T-REx systems exhibited much higher induced expression levels than the other three systems. The elucidation of the characteristic features of each system should provide important information for widespread and feasible application of these systems. Overall, these results suggest the most appropriate inducible gene expression system in the context of Ad vectors to be the dimerizer system.     

Design of a fault-tolerant decision-making system for biomedical applications

This paper describes the design of a fault-tolerant classification system for medical applications. The design process follows the systems engineering methodology: in the agreement phase, we make the case for fault tolerance in diagnosis systems for biomedical applications. The argument extends the idea that machine diagnosis systems mimic the functionality of human decision-making, but in many cases they do not achieve the fault tolerance of the human brain. After making the case for fault tolerance, both requirements and specification for the fault-tolerant system are introduced before the implementation is discussed. The system is tested with fault and use cases to build up trust in the implemented system. This structured approach aided in the realisation of the fault-tolerant classification system. During the specification phase, we produced a formal model that enabled us to discuss what fault tolerance, reliability and safety mean for this particular classification system. Furthermore, such a formal basis for discussion is extremely useful during the initial stages of the design, because it helps to avoid big mistakes caused by a lack of overview later on in the project. During the implementation, we practiced component reuse by incorporating a reliable classification block, which was developed during a previous project, into the current design. Using a well-structured approach and practicing component reuse we follow best practice for both research and industry projects, which enabled us to realise the fault-tolerant classification system on time and within budget. This system can serve in a wide range of future health care systems.     

Modeling adaptive biological systems

During the evolution of many systems found in nature, both the system composition and the interactions between components will vary. Equating the dimension with the number of different components, a system which adds or deletes components belongs to a class of dynamical systems with a finite dimensional phase space of variable dimension. We present two models of biochemical systems with a variable phase space, a model of autocatalytic reaction networks in the prebiotic soup and a model of the idiotypic network of the immune system. Each model contains characteristic meta-dynamical rules for constructing equations of motion from component properties. The simulation of each model occurs on two levels. On one level, the equations of motion are integrated to determine the state of each component. On a second level, algorithms which approximate physical processes in the real system are employed to change the equations of motion. Models with meta-dynamical rules possess several advantages for the study of evolving systems. First, there are no explicit fitness functions to determine how the components of the model rank in terms of survivability. The success of any component is a function of its relationship to the rest of the system. A second advantage is that since the phase space representation of the system is always finite but continually changing, we can explore a potentially infinite phase space which would otherwise be inaccessible with finite computer resources. Third, the enlarged capacity of systems with meta-dynamics for variation allows us to conduct true evolution experiments. The modeling methods presented here can be applied to many real biological systems. In the two studies we present, we are investigating two apparent properties of adaptive networks. With the simulation of the prebiotic soup, we are most interested in how a chemical reaction network might emerge from an initial state of relative disorder. With the study of the immune system, we study the self-regulation of the network including its ability to distinguish between species which are part of the network and those which are not.     

Interplay between plasmid partition and postsegregational killing systems

Active partition systems and postsegregational killing (PSK) systems are present together in naturally occurring low-copy-number plasmids. Theory suggests that PSK may act as the ultimate determinant of plasmid retention, whereas the partition system may minimize the growth penalty to the host, resulting in a near-ideal symbiosis when the systems combine. Here, we prove the validity of this principle for a specific case involving the P1par system and the mvp PSK system.     

Small universal spiking neural P systems

In search for small universal computing devices of various types, we consider here the case of spiking neural P systems (SN P systems), in two variants: as devices that compute functions and as devices that generate sets of numbers. We start with the first case and we produce a universal spiking neural P system with 84 neurons. If a slight generalization of the used rules is adopted, namely, we allow rules for producing simultaneously several spikes, then a considerable reduction, to 49 neurons, is obtained. For SN P systems used as generators of sets of numbers, we find a universal system with restricted rules having 76 neurons and one with extended rules having 50 neurons.     

Information flow in heterogeneously interacting systems

Motivated by studies on the dynamics of heterogeneously interacting systems in neocortical neural networks, we studied heterogeneously-coupled chaotic systems. We used information-theoretic measures to investigate directions of information flow in heterogeneously coupled Rössler systems, which we selected as a typical chaotic system. In bi-directionally coupled systems, spontaneous and irregular switchings of the phase difference between two chaotic oscillators were observed. The direction of information transmission spontaneously switched in an intermittent manner, depending on the phase difference between the two systems. When two further oscillatory inputs are added to the coupled systems, this system dynamically selects one of the two inputs by synchronizing, selection depending on the internal phase differences between the two systems. These results indicate that the effective direction of information transmission dynamically changes, induced by a switching of phase differences between the two systems.     

重组蛋白表达系统的研究进展

利用基因重组表达外源蛋白在现代生物学技术的发展与应用中起着重要的作用。根据外源基因表达宿主不同,可以将表达系统大致分为两类:原核和真核表达系统。该文比较了常见的几种表达系统的优缺点,并探讨了在选择适合的表达系统时所需要考虑的因素如目标蛋白的产量、生物学活性、用途及其物理化学性质以及表达系统本身的成本、便利性及其安全性等,以便于选择适合的表达系统,优化提高重组蛋白产量等,进而更好地服务于科学研究。     

优势种植被分类系统的逻辑分析与示例方案化

逻辑学原理是各种分类系统科学性及规范性的必要检验工具。本文采用逻辑学原理检验基于优势种的《中国植被》的植被分类系统, 结果发现目前常用的植被分类系统存在较多逻辑错误, 需要予以纠正。于是, 在强调植物生活型分类系统和植被分类系统一致性的基础上, 依据逻辑学原理给出建立植被分类系统的步骤和方法, 提出规范的植物生活型分类系统和植被分类系统示例方案。鉴于多建群种植被的客观存在及其存在形式多样, 在分类系统中给出相应的位置——多建群种植被纲。同时, 针对国内植被分类学界从未形成统一的植被命名规则, 且又有多种命名方式并存的现状, 提出了函数命名法。     

Targeted large fragment deletion in plants using paired crRNAs with type I CRISPR system

The CRISPR-Cas systems have been widely used as genome editing tools, with type II and V systems typically introducing small indels, and type I system mediating long-range deletions. However, the precision of type I systems for large fragment deletion is still remained to be optimized. Here, we developed a compact Cascade-Cas3 Dvu I-C system with Cas11c for plant genome editing. The Dvu I-C system was efficient to introduce controllable large fragment deletion up to at least 20 kb using paired crRNAs. The paired-crRNAs design also improved the controllability of deletions for the type I-E system. Dvu I-C system was sensitive to spacer length and mismatch, which was benefit for target specificity. In addition, we showed that the Dvu I-C system was efficient for generating stable transgenic lines in maize and rice with the editing efficiency up to 86.67%. Overall, Dvu I-C system we developed here is powerful for achieving controllable large fragment deletions.     

冰岛硫化叶菌遗传操作体系的研究进展

冰岛硫化叶菌是古菌研究中常用的模式菌株,为人们研究古菌复制、细胞周期以及CRISPR-Cas系统等作出了巨大贡献。冰岛硫化叶菌遗传操作体系的建立与完善对古菌学的全面深入研究起至关重要的作用。本文介绍了冰岛硫化叶菌遗传操作体系所使用的质粒载体、筛选标记和转化方法,论述了目前广泛使用的两类冰岛硫化叶菌基因敲除体系。最后提出了现有冰岛硫化叶菌基因操作体系存在的主要问题,并对其发展方向进行了展望。     

一类离散双线性生态系统的正规化控制

双线性系统能对非线性系统很好的近似,可对生态、生物等过程中的许多现象进行描述,对双线性系统研究具有一定的实际价值与理论意义.本文研究了一类离散双线性生态系统的全局渐近稳定问题.针对该系统,给出了一种简单的正规化反馈控制律.运用Lyapunov稳定性理论证明了在此控制律下的闭环系统是全局渐近稳定的.     

Epidemiological and evolutionary consequences of different types of CRISPR-Cas systems

Bacteria have adaptive immunity against viruses (phages) in the form of CRISPR-Cas immune systems. Currently, 6 types of CRISPR-Cas systems are known and the molecular study of three of these has revealed important molecular differences. It is unknown if and how these molecular differences change the outcome of phage infection and the evolutionary pressure the CRISPR-Cas systems faces. To determine the importance of these molecular differences, we model a phage outbreak entering a population defending exclusively with a type I/II or a type III CRISPR-Cas system. We show that for type III CRISPR-Cas systems, rapid phage extinction is driven by the probability to acquire at least one resistance spacer. However, for type I/II CRISPR-Cas systems, rapid phage extinction is characterized by an a threshold-like behaviour: any acquisition probability below this threshold leads to phage survival whereas any acquisition probability above it, results in phage extinction. We also show that in the absence of autoimmunity, high acquisition rates evolve. However, when CRISPR-Cas systems are prone to autoimmunity, intermediate levels of acquisition are optimal during a phage outbreak. As we predict an optimal probability of spacer acquisition 2 factors of magnitude above the one that has been measured, we discuss the origin of such a discrepancy. Finally, we show that in a biologically relevant parameter range, a type III CRISPR-Cas system can outcompete a type I/II CRISPR-Cas system with a slightly higher probability of acquisition.     

Tabletop Molecular Communication: Text Messages through Chemical Signals

In this work, we describe the first modular, and programmable platform capable of transmitting a text message using chemical signalling – a method also known as molecular communication. This form of communication is attractive for applications where conventional wireless systems perform poorly, from nanotechnology to urban health monitoring. Using examples, we demonstrate the use of our platform as a testbed for molecular communication, and illustrate the features of these communication systems using experiments. By providing a simple and inexpensive means of performing experiments, our system fills an important gap in the molecular communication literature, where much current work is done in simulation with simplified system models. A key finding in this paper is that these systems are often nonlinear in practice, whereas current simulations and analysis often assume that the system is linear. However, as we show in this work, despite the nonlinearity, reliable communication is still possible. Furthermore, this work motivates future studies on more realistic modelling, analysis, and design of theoretical models and algorithms for these systems.     

Sampling and monitoring in bioprocessing using microtechniques

In this review we describe aspects of interactions between bioreactors and analytical systems including microsystems. Principles of bioprocess monitoring are summarized, before we focus on the miniaturization of sampling systems guaranteeing bioprocess sterility and providing analytical systems with a liquid sample. The application of negative dielectrophoresis as a new principle for cell retention in a sampling system is described followed by theoretical aspects and results. Properties of micromachined silicon membranes as filters for sampling systems and for biosensor protection are discussed.