Evolution of Patterning Systems and Circuit Elements for Locomotion

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动物界模仿者英语小作文

动物界模仿者英语小作文
The phenomenon of mimicry is not merely a curious evolutionary quirk – it is a testament to the incredible adaptability and resourcefulness of life on our planet. These remarkable creatures have honed their skills over countless generations, developing intricate physical and behavioral adaptations that allow them to blend seamlessly into their environments, often to the detriment of their prey or the unsuspecting predators that attempt to hunt them.
Nor is mimicry confined to the animal kingdom. In the world of plants, the brilliant-hued flowers of the snapdragon plant have evolved to mimic the appearance of an open mouth, complete with "lips" and "teeth." This remarkable adaptation serves to attract pollinators, such as bees and butterflies, who mistake the flowers for the faces of small animals and are drawn to them, inadvertently aiding in the plant's reproductive success.

附加资料郑州大学2013年第八届研究生专业论文大赛获奖单位和

附加资料郑州大学2013年第八届研究生专业论文大赛获奖单位和
生命科学学院
崔振伟
优秀奖(23篇)
论文题目
院系
姓名
基于神经网络的多参数比较蛋白质相似度算法
电气工程学院
尹咪咪
基于改进的混沌蚁群算法的QoS网络路由优化研究
电气工程学院
侯文哲
一种新的面向非平衡分类问题的特征变换方法
信息工程学院
职为梅
大数据环境下基于MapReduce的数据倾斜优化
信息工程学院
高宇飞
零等待混合流水车间问题优化研究
用计算文体学的方法分析现代女性的语言特点—以奥巴马和米歇尔的演讲为例
外语学院
刘萌
中小学体育教学中实施形象礼仪教育的研究
体育系
巩月迎
我国城镇化建设影响因素分析
商学院
轩会永
理工科类(共计50)
一等奖(6篇)
论文题目
院系
姓名
Coal Mine Production Logistics System security Prediction Based on RS-WNN
生命科学学院
郭琪
Dispersal and hoarding of sympatric forest seeds by rodents in a temperate forest from north China
生命科学学院
张பைடு நூலகம்建
医科类(共计16篇)
一等奖(3篇)
论文题目
院系
姓名
新型核苷类似物FNC对Raji细胞侵袭力影响的实验研究
公共卫生学院
王炳源
煤焦沥青提取物对BEAS-2B细胞环氧化酶-2mRNA表达的影响
公共卫生学院
杨维超
人S100A8和S100A9原核载体的构建、鉴定及蛋白纯化

进化生物学概述

进化生物学概述

Charles Darwin
Charles Darwin
达尔文
(1809-1882)
The Struggle for existence
Observation 1:
Populations sizes would increase exponentially if all individuals born survived. Observation 2: Most populations are stable in size. Observation 3: No two individuals in a population are exactly the same. Observation 4: Much of this variation is heritable
进化生物学
综合进化理论
(Dobzhansky, Mayr, Simpson, Stebbins)
进化 = 遗传变异 + 变异的不均等传递 + 物种形成
突变 重组 基因流
选择
遗传漂变
隔离

进化生物学
进化生物学的基本研究内容
进化 = 遗传变异 + 变异的不均等传递 + 物种形成
突变 重组 基因流
选择
--- what ?

系统发育重建 (Phylogeny)
detect evolution at work, discovering its processes and interpreting its results
--- how ? --- why ? why ?

进化的过程和机制 (Evolution)
进化生物学
瓶颈效应 (bottlenect effect) Nhomakorabea

形态学变化英文

形态学变化英文

形态学变化英文Morphological TransformationThe study of morphological transformation is a fascinating field that delves into the intricate changes that occur in the form and structure of organisms over time. This process, driven by various evolutionary forces, can lead to the emergence of new species, the adaptation of existing ones, and the extinction of others. Understanding the mechanisms behind these transformations is crucial for biologists, as it sheds light on the complex interplay between an organism's genetic makeup, its environment, and the selective pressures that shape its development.At the heart of morphological transformation lies the concept of adaptation. As organisms face changing environmental conditions, they must adapt to ensure their survival and reproduction. This adaptation can manifest in various ways, such as the development of new physical features, the modification of existing ones, or the complete restructuring of an organism's form. The process of natural selection, where individuals with advantageous traits are more likely to survive and reproduce, plays a pivotal role in driving these transformations.One of the most well-known examples of morphological transformation is the evolution of the whale. Millions of years ago, whales were land-dwelling mammals that resembled small, four-legged creatures. Over time, as they adapted to an aquatic lifestyle, their bodies underwent remarkable changes. Their limbs transformed into flippers, their tails became flukes for propulsion, and their nostrils migrated to the top of their heads, allowing them to breathe while submerged. These adaptations, driven by the need to thrive in the marine environment, have resulted in the diverse array of whale species we observe today.Another intriguing example of morphological transformation is the metamorphosis of insects, such as butterflies and dragonflies. During their life cycle, these creatures undergo a remarkable transformation, transitioning from a larval stage (e.g., caterpillar or nymph) to a completely different adult form. This process involves the reorganization of the organism's body structure, the development of new organs and appendages, and the shedding of the larval exoskeleton. The transformation is orchestrated by complex hormonal signals and genetic pathways, allowing the insect to adapt to its changing environmental demands and reproductive needs.Morphological transformation is not limited to the animal kingdom; it is also observed in plants. For instance, the development of flowersfrom simple leaf-like structures is a remarkable example of morphological transformation. The petals, sepals, stamens, and carpels that make up a flower are all modified leaves, each serving a specific function in the plant's reproductive cycle. This transformation is driven by the expression of specific genes that regulate the development and patterning of these floral structures.Furthermore, the study of morphological transformation has important implications for understanding the evolution of species. By analyzing the fossil record and comparing the physical characteristics of related organisms, scientists can reconstruct the ancestral forms and trace the evolutionary pathways that have led to the diversity of life we observe today. This knowledge not only enhances our understanding of the past but also provides valuable insights into the future adaptations and transformations that may occur in response to environmental changes.In conclusion, the study of morphological transformation is a fundamental aspect of biology, offering a window into the dynamic and ever-changing nature of life on our planet. From the evolution of whales to the metamorphosis of insects and the development of flowers, these remarkable transformations illustrate the incredible adaptability and resilience of living organisms. As we continue to explore and unravel the mysteries of morphological transformation,we gain a deeper appreciation for the intricate processes that have shaped the diversity of life on Earth.。

刘缨-眼睛发育的基因调控2015

刘缨-眼睛发育的基因调控2015

研究意义 劳动、学习和生活
预防
其他器官发育 和疾病的机制
基各 因种 突诱 变变 :因 :素
诊断
治疗
眼睛发育的机制
致病机理研究
研究意义 ----------------------------------------确定引起各种先天性和后天性眼病的遗 传和环境因素,促进对其致病机理研究,提 高眼病预防、诊断和治疗水平。
1
?RNAi
protein antibody ?
CA pr. DN pr.
Functional analysis - Approaches
Gain-of-function
• DNA template transcription DNA (expression vector) knock-in enhancer
A model for Hox regulation (Garcia-Bellido, 1975)
Activator
"Activator" genes delimit the realm of expression of "Selector" genes. Maternal signal
Selector
劳动、学习和生活的能力
眼睛是发育过程中最易发生畸变的器官之一
管怀庆等, <<现代基础眼科学>>, 1998
眼睛是发育过程中最易发生畸变的器官之一 ------------------------------------------------------------
视觉器官各种遗传性 疾病的发病已达2%左右; 近视、斜视、散光等等在 我国青年中的发病率已达 到50%左右;眼睛的老视、 白内障几乎是每一个人进 入中老年都会遇到的问题。

Universities in Evolutionary Systems(系统变革中的大学)

Universities in Evolutionary Systems(系统变革中的大学)

Universities in Evolutionary Systems of InnovationMarianne van der Steen and Jurgen EndersThis paper criticizes the current narrow view on the role of universities in knowledge-based economies.We propose to extend the current policy framework of universities in national innovation systems(NIS)to a more dynamic one,based on evolutionary economic principles. The main reason is that this dynamic viewfits better with the practice of innovation processes. We contribute on ontological and methodological levels to the literature and policy discussions on the effectiveness of university-industry knowledge transfer and the third mission of uni-versities.We conclude with a discussion of the policy implications for the main stakeholders.1.IntroductionU niversities have always played a major role in the economic and cultural devel-opment of countries.However,their role and expected contribution has changed sub-stantially over the years.Whereas,since1945, universities in Europe were expected to con-tribute to‘basic’research,which could be freely used by society,in recent decades they are expected to contribute more substantially and directly to the competitiveness offirms and societies(Jaffe,2008).Examples are the Bayh–Dole Act(1982)in the United States and in Europe the Lisbon Agenda(2000–2010) which marked an era of a changing and more substantial role for universities.However,it seems that this‘new’role of universities is a sort of universal given one(ex post),instead of an ex ante changing one in a dynamic institutional environment.Many uni-versities are expected nowadays to stimulate a limited number of knowledge transfer activi-ties such as university spin-offs and university patenting and licensing to demonstrate that they are actively engaged in knowledge trans-fer.It is questioned in the literature if this one-size-fits-all approach improves the usefulness and the applicability of university knowledge in industry and society as a whole(e.g.,Litan et al.,2007).Moreover,the various national or regional economic systems have idiosyncratic charac-teristics that in principle pose different(chang-ing)demands towards universities.Instead of assuming that there is only one‘optimal’gov-ernance mode for universities,there may bemultiple ways of organizing the role of univer-sities in innovation processes.In addition,we assume that this can change over time.Recently,more attention in the literature hasfocused on diversity across technologies(e.g.,King,2004;Malerba,2005;Dosi et al.,2006;V an der Steen et al.,2008)and diversity offormal and informal knowledge interactionsbetween universities and industry(e.g.,Cohenet al.,1998).So far,there has been less atten-tion paid to the dynamics of the changing roleof universities in economic systems:how dothe roles of universities vary over time andwhy?Therefore,this article focuses on the onto-logical premises of the functioning of univer-sities in innovation systems from a dynamic,evolutionary perspective.In order to do so,we analyse the role of universities from theperspective of an evolutionary system ofinnovation to understand the embeddednessof universities in a dynamic(national)systemof science and innovation.The article is structured as follows.InSection2we describe the changing role ofuniversities from the static perspective of anational innovation system(NIS),whereasSection3analyses the dynamic perspective ofuniversities based on evolutionary principles.Based on this evolutionary perspective,Section4introduces the characteristics of a LearningUniversity in a dynamic innovation system,summarizing an alternative perception to thestatic view of universities in dynamic economicsystems in Section5.Finally,the concludingVolume17Number42008doi:10.1111/j.1467-8691.2008.00496.x©2008The AuthorsJournal compilation©2008Blackwell Publishingsection discusses policy recommendations for more effective policy instruments from our dynamic perspective.2.Static View of Universities in NIS 2.1The Emergence of the Role of Universities in NISFirst we start with a discussion of the literature and policy reports on national innovation system(NIS).The literature on national inno-vation systems(NIS)is a relatively new and rapidly growingfield of research and widely used by policy-makers worldwide(Fagerberg, 2003;Balzat&Hanusch,2004;Sharif,2006). The NIS approach was initiated in the late 1980s by Freeman(1987),Dosi et al.(1988)and Lundvall(1992)and followed by Nelson (1993),Edquist(1997),and many others.Balzat and Hanusch(2004,p.196)describe a NIS as‘a historically grown subsystem of the national economy in which various organizations and institutions interact with and influence one another in the carrying out of innovative activity’.It is about a systemic approach to innovation,in which the interaction between technology,institutions and organizations is central.With the introduction of the notion of a national innovation system,universities were formally on the agenda of many innovation policymakers worldwide.Clearly,the NIS demonstrated that universities and their interactions with industry matter for innova-tion processes in economic systems.Indeed, since a decade most governments acknowl-edge that interactions between university and industry add to better utilization of scienti-fic knowledge and herewith increase the innovation performance of nations.One of the central notions of the innovation system approach is that universities play an impor-tant role in the development of commercial useful knowledge(Edquist,1997;Sharif, 2006).This contrasts with the linear model innovation that dominated the thinking of science and industry policy makers during the last century.The linear innovation model perceives innovation as an industry activity that‘only’utilizes fundamental scientific knowledge of universities as an input factor for their innovative activities.The emergence of the non-linear approach led to a renewed vision on the role–and expectations–of universities in society. Some authors have referred to a new social contract between science and society(e.g., Neave,2000).The Triple Helix(e.g.,Etzkowitz &Leydesdorff,1997)and the innovation system approach(e.g.,Lundvall,1988)and more recently,the model of Open Innovation (Chesbrough,2003)demonstrated that innova-tion in a knowledge-based economy is an inter-active process involving many different innovation actors that interact in a system of overlapping organizationalfields(science, technology,government)with many interfaces.2.2Static Policy View of Universities in NIS Since the late1990s,the new role of universi-ties in NIS thinking emerged in a growing number of policy studies(e.g.,OECD,1999, 2002;European Commission,2000).The con-tributions of the NIS literature had a large impact on policy makers’perception of the role of universities in the national innovation performance(e.g.,European Commission, 2006).The NIS approach gradually replaced linear thinking about innovation by a more holistic system perspective on innovations, focusing on the interdependencies among the various agents,organizations and institutions. NIS thinking led to a structurally different view of how governments can stimulate the innovation performance of a country.The OECD report of the national innovation system (OECD,1999)clearly incorporated these new economic principles of innovation system theory.This report emphasized this new role and interfaces of universities in knowledge-based economies.This created a new policy rationale and new awareness for technology transfer policy in many countries.The NIS report(1999)was followed by more attention for the diversity of technology transfer mecha-nisms employed in university-industry rela-tions(OECD,2002)and the(need for new) emerging governance structures for the‘third mission’of universities in society,i.e.,patent-ing,licensing and spin-offs,of public research organizations(OECD,2003).The various policy studies have in common that they try to describe and compare the most important institutions,organizations, activities and interactions of public and private actors that take part in or influence the innovation performance of a country.Figure1 provides an illustration.Thefigure demon-strates the major building blocks of a NIS in a practical policy setting.It includesfirms,uni-versities and other public research organiza-tions(PROs)involved in(higher)education and training,science and technology.These organizations embody the science and tech-nology capabilities and knowledge fund of a country.The interaction is represented by the arrows which refer to interactive learn-ing and diffusion of knowledge(Lundvall,Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing1992).1The building block ‘Demand’refers to the level and quality of demand that can be a pull factor for firms to innovate.Finally,insti-tutions are represented in the building blocks ‘Framework conditions’and ‘Infrastructure’,including various laws,policies and regula-tions related to science,technology and entre-preneurship.It includes a very broad array of policy issues from intellectual property rights laws to fiscal instruments that stimulate labour mobility between universities and firms.The figure demonstrates that,in order to improve the innovation performance of a country,the NIS as a whole should be conducive for innovative activities in acountry.Since the late 1990s,the conceptual framework as represented in Figure 1serves as a dominant design for many comparative studies of national innovation systems (Polt et al.,2001;OECD,2002).The typical policy benchmark exercise is to compare a number of innovation indicators related to the role of university-industry interactions.Effective performance of universities in the NIS is judged on a number of standardized indica-tors such as the number of spin-offs,patents and licensing.Policy has especially focused on ‘getting the incentives right’to create a generic,good innovative enhancing context for firms.Moreover,policy has also influ-enced the use of specific ‘formal’transfer mechanisms,such as university patents and university spin-offs,to facilitate this collabo-ration.In this way best practice policies are identified and policy recommendations are derived:the so-called one-size-fits-all-approach.The focus is on determining the ingredients of an efficient benchmark NIS,downplaying institutional diversity and1These organizations that interact with each other sometimes co-operate and sometimes compete with each other.For instance,firms sometimes co-operate in certain pre-competitive research projects but can be competitors as well.This is often the case as well withuniversities.Figure 1.The Benchmark NIS Model Source :Bemer et al.(2001).Volume 17Number 42008©2008The AuthorsJournal compilation ©2008Blackwell Publishingvariety in the roles of universities in enhanc-ing innovation performance.The theoretical contributions to the NIS lit-erature have outlined the importance of insti-tutions and institutional change.However,a further theoretical development of the ele-ments of NIS is necessary in order to be useful for policy makers;they need better systemic NIS benchmarks,taking systematically into account the variety of‘national idiosyncrasies’. Edquist(1997)argues that most NIS contribu-tions are more focused onfirms and technol-ogy,sometimes reducing the analysis of the (national)institutions to a left-over category (Geels,2005).Following Hodgson(2000), Nelson(2002),Malerba(2005)and Groenewe-gen and V an der Steen(2006),more attention should be paid to the institutional idiosyncra-sies of the various systems and their evolution over time.This creates variety and evolving demands towards universities over time where the functioning of universities and their interactions with the other part of the NIS do evolve as well.We suggest to conceptualize the dynamics of innovation systems from an evolutionary perspective in order to develop a more subtle and dynamic vision on the role of universities in innovation systems.We emphasize our focus on‘evolutionary systems’instead of national innovation systems because for many universities,in particular some science-based disciplinaryfields such as biotechnology and nanotechnology,the national institutional environment is less relevant than the institu-tional and technical characteristics of the technological regimes,which is in fact a‘sub-system’of the national innovation system.3.Evolutionary Systems of Innovation as an Alternative Concept3.1Evolutionary Theory on Economic Change and InnovationCharles Darwin’s The Origin of Species(1859)is the foundation of modern thinking about change and evolution(Luria et al.,1981,pp. 584–7;Gould,1987).Darwin’s theory of natural selection has had the most important consequences for our perception of change. His view of evolution refers to a continuous and gradual adaptation of species to changes in the environment.The idea of‘survival of thefittest’means that the most adaptive organisms in a population will survive.This occurs through a process of‘natural selection’in which the most adaptive‘species’(organ-isms)will survive.This is a gradual process taking place in a relatively stable environment, working slowly over long periods of time necessary for the distinctive characteristics of species to show their superiority in the‘sur-vival contest’.Based on Darwin,evolutionary biology identifies three levels of aggregation.These three levels are the unit of variation,unit of selection and unit of evolution.The unit of varia-tion concerns the entity which contains the genetic information and which mutates fol-lowing specific rules,namely the genes.Genes contain the hereditary information which is preserved in the DNA.This does not alter sig-nificantly throughout the reproductive life-time of an organism.Genes are passed on from an organism to its successors.The gene pool,i.e.,the total stock of genetic structures of a species,only changes in the reproduction process as individuals die and are born.Par-ticular genes contribute to distinctive charac-teristics and behaviour of species which are more or less conducive to survival.The gene pool constitutes the mechanism to transmit the characteristics of surviving organisms from one generation to the next.The unit of selection is the expression of those genes in the entities which live and die as individual specimens,namely(individual) organisms.These organisms,in their turn,are subjected to a process of natural selection in the environment.‘Fit’organisms endowed with a relatively‘successful’gene pool,are more likely to pass them on to their progeny.As genes contain information to form and program the organisms,it can be expected that in a stable environment genes aiding survival will tend to become more prominent in succeeding genera-tions.‘Natural selection’,thus,is a gradual process selecting the‘fittest’organisms. Finally,there is the unit of evolution,or that which changes over time as the gene pool changes,namely populations.Natural selec-tion produces changes at the level of the population by‘trimming’the set of genetic structures in a population.We would like to point out two central principles of Darwinian evolution.First,its profound indeterminacy since the process of development,for instance the development of DNA,is dominated by time at which highly improbable events happen (Boulding,1991,p.12).Secondly,the process of natural selection eliminates poorly adapted variants in a compulsory manner,since indi-viduals who are‘unfit’are supposed to have no way of escaping the consequences of selection.22We acknowledge that within evolutionary think-ing,the theory of Jean Baptiste Lamarck,which acknowledges in essence that acquired characteris-tics can be transmitted(instead of hereditaryVolume17Number42008©2008The AuthorsJournal compilation©2008Blackwell PublishingThese three levels of aggregation express the differences between ‘what is changing’(genes),‘what is being selected’(organisms),and ‘what changes over time’(populations)in an evolutionary process (Luria et al.,1981,p.625).According to Nelson (see for instance Nelson,1995):‘Technical change is clearly an evolutionary process;the innovation generator keeps on producing entities superior to those earlier in existence,and adjustment forces work slowly’.Technological change and innovation processes are thus ‘evolutionary’because of its characteristics of non-optimality and of an open-ended and path-dependent process.Nelson and Winter (1982)introduced the idea of technical change as an evolutionary process in capitalist economies.Routines in firms function as the relatively durable ‘genes’.Economic competition leads to the selection of certain ‘successful’routines and these can be transferred to other firms by imitation,through buy-outs,training,labour mobility,and so on.Innovation processes involving interactions between universities and industry are central in the NIS approach.Therefore,it seems logical that evolutionary theory would be useful to grasp the role of universities in innovation pro-cesses within the NIS framework.3.2Evolutionary Underpinnings of Innovation SystemsBased on the central evolutionary notions as discussed above,we discuss in this section how the existing NIS approaches have already incor-porated notions in their NIS frameworks.Moreover,we investigate to what extent these notions can be better incorporated in an evolu-tionary innovation system to improve our understanding of universities in dynamic inno-vation processes.We focus on non-optimality,novelty,the anti-reductionist methodology,gradualism and the evolutionary metaphor.Non-optimality (and Bounded Rationality)Based on institutional diversity,the notion of optimality is absent in most NIS approaches.We cannot define an optimal system of innovation because evolutionary learning pro-cesses are important in such systems and thus are subject to continuous change.The system never achieves an equilibrium since the evolu-tionary processes are open-ended and path dependent.In Nelson’s work (e.g.,1993,1995)he has emphasized the presence of contingent out-comes of innovation processes and thus of NIS:‘At any time,there are feasible entities not present in the prevailing system that have a chance of being introduced’.This continuing existence of feasible alternative developments means that the system never reaches a state of equilibrium or finality.The process always remains dynamic and never reaches an optimum.Nelson argues further that diversity exists because technical change is an open-ended multi-path process where no best solu-tion to a technical problem can be identified ex post .As a consequence technical change can be seen as a very wasteful process in capitalist economies with many duplications and dead-ends.Institutional variety is closely linked to non-optimality.In other words,we cannot define the optimal innovation system because the evolutionary learning processes that take place in a particular system make it subject to continuous change.Therefore,comparisons between an existing system and an ideal system are not possible.Hence,in the absence of any notion of optimality,a method of comparing existing systems is necessary.According to Edquist (1997),comparisons between systems were more explicit and systematic than they had been using the NIS approaches.Novelty:Innovations CentralNovelty is already a central notion in the current NIS approaches.Learning is inter-preted in a broad way.Technological innova-tions are defined as combining existing knowledge in new ways or producing new knowledge (generation),and transforming this into economically significant products and processes (absorption).Learning is the most important process behind technological inno-vations.Learning can be formal in the form of education and searching through research and development.However,in many cases,innovations are the consequence of several kinds of learning processes involving many different kinds of economic agents.According to Lundvall (1992,p.9):‘those activities involve learning-by-doing,increasing the efficiency of production operations,learning-characteristics as in the theory of Darwin),is acknowledged to fit better with socio-economic processes of technical change and innovation (e.g.,Nelson &Winter,1982;Hodgson,2000).Therefore,our theory is based on Lamarckian evolutionary theory.However,for the purpose of this article,we will not discuss the differences between these theo-ries at greater length and limit our analysis to the fundamental evolutionary building blocks that are present in both theories.Volume 17Number 42008©2008The AuthorsJournal compilation ©2008Blackwell Publishingby-using,increasing the efficiency of the use of complex systems,and learning-by-interacting, involving users and producers in an interac-tion resulting in product innovations’.In this sense,learning is part of daily routines and activities in an economy.In his Learning Economy concept,Lundvall makes learning more explicit,emphasizing further that ‘knowledge is assumed as the most funda-mental resource and learning the most impor-tant process’(1992,p.10).Anti-reductionist Approach:Systems and Subsystems of InnovationSo far,NIS approaches are not yet clear and systematic in their analysis of the dynamics and change in innovation systems.Lundvall’s (1992)distinction between subsystem and system level based on the work of Boulding implicitly incorporates both the actor(who can undertake innovative activities)as well as the structure(institutional selection environment) in innovation processes of a nation.Moreover, most NIS approaches acknowledge that within the national system,there are different institu-tional subsystems(e.g.,sectors,regions)that all influence each other again in processes of change.However,an explicit analysis of the structured environment is still missing (Edquist,1997).In accordance with the basic principles of evolutionary theory as discussed in Section 3.1,institutional evolutionary theory has developed a very explicit systemic methodol-ogy to investigate the continuous interaction of actors and institutional structures in the evolution of economic systems.The so-called ‘methodological interactionism’can be per-ceived as a methodology that combines a structural perspective and an actor approach to understand processes of economic evolu-tion.Whereas the structural perspective emphasizes the existence of independent institutional layers and processes which deter-mine individual actions,the actor approach emphasizes the free will of individuals.The latter has been referred to as methodological individualism,as we have seen in neo-classical approaches.Methodological indi-vidualism will explain phenomena in terms of the rational individual(showingfixed prefer-ences and having one rational response to any fully specified decision problem(Hodgson, 2000)).The interactionist approach recognizes a level of analysis above the individual orfirm level.NIS approaches recognize that national differences exist in terms of national institu-tions,socio-economic factors,industries and networks,and so on.So,an explicit methodological interactionist approach,explicitly recognizing various insti-tutional layers in the system and subsystem in interaction with the learning agents,can improve our understanding of the evolution of innovation.Gradualism:Learning Processes andPath-DependencyPath-dependency in biology can be translated in an economic context in the form of(some-times very large)time lags between a technical invention,its transformation into an economic innovation,and the widespread diffusion. Clearly,in many of the empirical case studies of NIS,the historical dimension has been stressed.For instance,in the study of Denmark and Sweden,it has been shown that the natural resource base(for Denmark fertile land,and for Sweden minerals)and economic history,from the period of the Industrial Revolution onwards,has strongly influenced present specialization patterns(Edquist& Lundvall,1993,pp.269–82).Hence,history matters in processes of inno-vation as the innovation processes are influ-enced by many institutions and economic agents.In addition,they are often path-dependent as small events are reinforced and become crucially important through processes of positive feedback,in line with evolutionary processes as discussed in Section3.1.Evolutionary MetaphorFinally,most NIS approaches do not explicitly use the biological metaphor.Nevertheless, many of the approaches are based on innova-tion theories in which they do use an explicit evolutionary metaphor(e.g.,the work of Nelson).To summarize,the current(policy)NIS approaches have already implicitly incorpo-rated some evolutionary notions such as non-optimality,novelty and gradualism.However, what is missing is a more explicit analysis of the different institutional levels of the economic system and innovation subsystems (their inertia and evolution)and how they change over time in interaction with the various learning activities of economic agents. These economic agents reside at established firms,start-upfirms,universities,govern-ments,undertaking learning and innovation activities or strategic actions.The explicit use of the biological metaphor and an explicit use of the methodological interactionst approach may increase our understanding of the evolu-tion of innovation systems.Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing4.Towards a Dynamic View of Universities4.1The Logic of an Endogenous‘Learning’UniversityIf we translate the methodological interaction-ist approach to the changing role of universities in an evolutionary innovation system,it follows that universities not only respond to changes of the institutional environment(government policies,business demands or changes in scientific paradigms)but universities also influence the institutions of the selection envi-ronment by their strategic,scientific and entre-preneurial actions.Moreover,these actions influence–and are influenced by–the actions of other economic agents as well.So,instead of a one-way rational response by universities to changes(as in reductionist approach),they are intertwined in those processes of change.So, universities actually function as an endogenous source of change in the evolution of the inno-vation system.This is(on an ontological level) a fundamental different view on the role of universities in innovation systems from the existing policy NIS frameworks.In earlier empirical research,we observed that universities already effectively function endogenously in evolutionary innovation system frameworks;universities as actors (already)develop new knowledge,innovate and have their own internal capacity to change,adapt and influence the institutional development of the economic system(e.g., V an der Steen et al.,2009).Moreover,univer-sities consist of a network of various actors, i.e.,the scientists,administrators at technology transfer offices(TTO)as well as the university boards,interacting in various ways with indus-try and governments and embedded in various ways in the regional,national or inter-national environment.So,universities behave in an at least partly endogenous manner because they depend in complex and often unpredictable ways on the decision making of a substantial number of non-collusive agents.Agents at universities react in continuous interaction with the learn-ing activities offirms and governments and other universities.Furthermore,the endogenous processes of technical and institutional learning of univer-sities are entangled in the co-evolution of institutional and technical change of the evo-lutionary innovation system at large.We propose to treat the learning of universities as an inseparable endogenous variable in the inno-vation processes of the economic system.In order to structure the endogenization in the system of innovation analysis,the concept of the Learning University is introduced.In thenext subsection we discuss the main character-istics of the Learning University and Section5discusses the learning university in a dynamic,evolutionary innovation system.An evolution-ary metaphor may be helpful to make theuniversity factor more transparent in theco-evolution of technical and institutionalchange,as we try to understand how variouseconomic agents interact in learning processes.4.2Characteristics of the LearningUniversityThe evolution of the involvement of universi-ties in innovation processes is a learningprocess,because(we assume that)universitypublic agents have their‘own agenda’.V ariousincentives in the environment of universitiessuch as government regulations and technol-ogy transfer policies as well as the innovativebehaviour of economic agents,compel policymakers at universities to constantly respondby adapting and improving their strategiesand policies,whereas the university scientistsare partly steered by these strategies and partlyinfluenced by their own scientific peers andpartly by their historically grown interactionswith industry.During this process,universityboards try to be forward-looking and tobehave strategically in the knowledge thattheir actions‘influence the world’(alsoreferred to earlier as‘intentional variety’;see,for instance,Dosi et al.,1988).‘Intentional variety’presupposes that tech-nical and institutional development of univer-sities is a learning process.University agentsundertake purposeful action for change,theylearn from experience and anticipate futurestates of the selective environment.Further-more,university agents take initiatives to im-prove and develop learning paths.An exampleof these learning agents is provided in Box1.We consider technological and institutionaldevelopment of universities as a process thatinvolves many knowledge-seeking activitieswhere public and private agents’perceptionsand actions are translated into practice.3Theinstitutional changes are the result of inter-actions among economic agents defined byLundvall(1992)as interactive learning.Theseinteractions result in an evolutionary pattern3Using a theory developed in one scientific disci-pline as a metaphor in a different discipline mayresult,in a worst-case scenario,in misleading analo-gies.In the best case,however,it can be a source ofcreativity.As Hodgson(2000)pointed out,the evo-lutionary metaphor is useful for understandingprocesses of technical and institutional change,thatcan help to identify new events,characteristics andphenomena.Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing。

英语语言学复习资料

英语语言学复习资料

英语语言学复习资料一:名词解释1. Language (语言) is a system of arbitrary vocal symbols used for human communication.2. Linguistics(语言学) is generally defined as the scientific study of language.3. General linguistics(普通/一般语言学)The study of language as a whole is often called general linguistics.4. Phonetics(语音学) the study of sounds used in linguistic communication led to the establishment of phonetics.5. Phonology(语音体系) how sounds are put together and used to convey meaning in communication.6. Morphology(形态学) these symbols are arranged and combined to form words has constituted the branch of study called morphology.7. Syntax(句法学) then the combination of words to form grammatically permissible sentences in languages is governed by rules. The study of these rules constitutes a major branch of linguistic studies called syntax.8. Semantics(语意学) the study of meaning is known as semantics.9. Pragmatics(语用学) when the study of meaning is conducted, not in isolation, but in the context of language use, it becomes another branch of linguistic study called pragmatics.10. Phone(音素) is a phonetic unit or segment. The speech sounds we hear and produce during linguistic communication are all phones.11. Phoneme(音位) is a phonological unit; it is a unit that is of distinctive value. It is an abstract unit. It is not any particular sound, but rather it is represented or realized by a certain phone in a certain phonetic context.12. Allophones(音位变体) the different phones which can represent a phoneme in different phonetic environments are called the allophones.13. IPA(International Phonetic Alphabet国际音标) It’s a standardized and internationally accepted system of phonetic transcription. The basic principle of the IPA is using one letter selected from major European languages to represent one speech sound.14. Diacritics(变音符) it is a set of symbols which are added to the letter-symbols to bring out the finer distinctions.15. broad transcription(宽式标音) one is the transcription with letter-symbols only.16. narrow transcription(严式标音) the other is the transcription with letter-symbols together with the diacritics.17. open class words(开放类词) In English , open class words are nouns, verbs, adjectives and adverbs. We can regularly add new words to these classes. 18. closed class words(封闭类词) In English , closed class word are conjunctions, prepositions, articles and pronouns. New words are not usually added to them. 19. Morpheme(词素) the most basic element of meaning is traditionally called morpheme.20. bound morpheme(黏着词素) morphemes which occurs only before othermorphemes. They cannot be used alone.21. free morpheme(自由词素) it is the morphemes which can be used alone.22. suprasegmental features(超音段特征) the phonemic features that occur above the level of the segments are called suprasegmental features.23. Category(范畴) it refers to a group of linguistic items which fulfill the same or similar functions in a particular language such as a sentence ,a noun phrase or a verb.24. Phrases(短语) Syntactic units that are built around a certain word category are called phrases.二:简答题1. Three distinct of phonetics(语音学的三个分支?)Articulatory phonetics发音语音学; auditory phonetics听觉语音学; acoustic phonetics声光语音学.2. Main features of language(语言的主要特征?)Language is a system. Language is arbitrary. Language is vocal. Language is human-specific.3. Synchronic vs. diachronic(共识语言学与历史语言学的区别?)Language exists in time and changes through time. The description of a language at some point of time in history is a synchronic study; the description of a language as it changes through time is a diachronic study. A diachronic study of language is a historical study; it studies the historical development of language over a period of time.4. Speech and writing (言语与文字的区别?)Speech and writing are the two major media of linguistic communication. From the point of view of linguistic evolution, speech is prior to writing. The writing system of any language is always “invented” by its users to record speech when the need arises. Then in everyday communication, speech plays a greater role than writing in terms of the amount of information conveyed, speech is always the way in which every native speaker acquires his mother tongue, and writing is learned and taught later when he goes to school. Written language is only the “revised” record of speech.5. What are the branches of linguistic study?(语言学研究领域中的主要分支有哪些?)1) sociolinguistics; 2) psycholinguistics; 3)applied linguistics and so on.6. Traditional grammar and modern linguistics(传统语法与现代语言学的区别?) Firstly, linguistics is descriptive while traditional grammar is prescriptive. Second, modern linguistics regards the spoken language as primary, not the written. Traditional grammarians, tended to emphasize, maybe over-emphasize, the importance of the written word.Modern linguistics differs from traditional grammar also in that it does not force languages into a Latin-based framework.7. Prescriptive vs. descriptive (语言学中描写性与规定性的特征是什么?) Prescriptive and descriptive represent two different types of linguistic study. If a linguistic study aims to describe and analyze the language people actually use, it issaid to be descriptive; if the linguistic study aims to lay down rules for “correct and standard”behavior in using language, it is said to be prescriptive. 8. Design features of language (语言的识别特征?)Arbitrariness随意性,productivity生产性, duality 二重性, displacement 不受时空限制的特征, cultural transmission 文化传递系统.9. Competence and performance (语言能力与语言行为的区别?)Competence is defined as the ideal user’s knowledge of the rules of his language, and performance the actual realization of this knowledge in linguistic communication. Chomsky looks at language from a psychological point of view and to him competence is a property of the mind of each individual. 10. Organs of speech (发音器官)Pharyngeal cavity—the throat, oral cavity—the mouth, nasal cavity—the nose.11. Word-level categories(决定词范畴的三个标准)To determine a word’s category, three criteria are usually employed, namely meaning, inflection and distribution.三:问题回答1. Some rules in phonology(音位学规则)sequential rules(序列规则);assimilation rule (同化规则) ;deletion rule(省略规则)。

合成生物学

合成生物学
与传统生物学通过解剖生命体以研究其内在构造的办法不同的是,合成生物学的研究方向完全是相反的:它 是从最基本的要素开始一步步建立零部件。重塑生命,这正是合成生物学这一新兴科学的核心思想。该学科致力 于从零开始建立微生物基因组,从而分解、改变并扩展自然界在35亿年前建立的基因密码。
谢谢观看
理论背景
理论背景
合成生物学的研究依据自组织系统结构理论 -泛进化论(structurity, structure theory, panevolution theory),从实证到综合(synthetic )探讨天然与人工进化的生物系统理论,阐述了结构整合 (integrative)、调适稳态与建构(constructive)层级等规律;因此,系统(systems)生物学也称为“整 合(integrative biology)生物学”,合成(synthetic)生物学又叫“建构生物学(constructive biology)”(Zeng BJ.中译)。系统与合成生物学的系统结构、发生动力与砖块建构、工程设计等基于结构理 论原理,从电脑技术的系统科学理论到遗传工程的系统科学方法,是将物理科学、工程技术原理与方法贯彻到细 胞、遗传机器与细胞通讯技术等纳米层次的生物分子系统分析与设计。
自2000年《自然》(Nature)杂志报道了人工合成基因线路研究成果以来,合成生物学研究在全世界范围 引起了广泛的**与重视,被公认为在医学、制药、化工、能源、材料、农业等领域都有广阔的应用前景。国际上 的合成生物学研究发展飞速,在短短几年内就已经设计了多种基因控制模块,包括开关、脉冲发生器、振荡器等, 可以有效调节基因表达、蛋白质功能、细胞代谢或细胞间相互作用。
合成生物学(synthetic biology),也可翻译成综合生物学,即综合集成,“synthetic”在不同地方翻 译成不同中文,比如综合哲学(synthetic philosophy)、“社会-心理-生物医学模式”的综合(synthetic) 医学(genbrain biosystem network -中科院曾邦哲1999年建于德国,探讨生物系统分析学“biosystem analysis”与人工生物系统“artificial biosystem”,包括实验、计算、系统、工程研究与应用),同时也 被归属为人工生物系统研究的系统生物工程技术范畴,包括生物反应器与生物计算机开发。

关于芯片技术的英语作文

关于芯片技术的英语作文

关于芯片技术的英语作文Title: The Advancements and Challenges in Semiconductor Technology。

Semiconductor technology stands as the cornerstone of modern innovation, revolutionizing industries, from computing to telecommunications, and driving the global economy forward. In this essay, we delve into the intricacies of semiconductor technology, exploring its evolution, current state, and future prospects.Firstly, it's imperative to understand the fundamentals of semiconductor technology. Semiconductors are materials with electrical conductivity between that of a conductor and an insulator. The manipulation of these materials through processes like doping and fabrication of integrated circuits enables the creation of transistors, the building blocks of modern electronics.The journey of semiconductor technology began in themid-20th century with the invention of the transistor, which replaced bulky and unreliable vacuum tubes. This breakthrough paved the way for the development of integrated circuits (ICs) by combining multiple transistors on a single semiconductor substrate. Since then, the semiconductor industry has witnessed exponential growth, driven by Moore's Law, which predicts the doubling of transistor density roughly every two years.The relentless pursuit of miniaturization and performance improvement has fueled innovations in semiconductor fabrication techniques. From the early days of planar technology to the current era dominated by FinFET and beyond, semiconductor manufacturers have continuously pushed the limits of physics to shrink transistor dimensions and enhance device performance.One of the most significant advancements in semiconductor technology is the rise of nanoscale fabrication processes. As feature sizes approach atomic scales, new challenges and opportunities emerge. Techniques like extreme ultraviolet lithography (EUV) enable theprecise patterning of sub-10 nanometer features,facilitating the production of cutting-edge semiconductor devices with unprecedented speed and efficiency.Moreover, the integration of novel materials into semiconductor devices holds immense promise for future breakthroughs. Materials like gallium nitride (GaN) and silicon carbide (SiC) offer superior electrical properties, enabling the development of high-power and high-frequency devices crucial for applications such as electric vehicles, renewable energy, and 5G telecommunications.However, despite these remarkable advancements, semiconductor technology faces formidable challenges on multiple fronts. One of the most pressing concerns is the limitations of traditional silicon-based transistors. As transistor dimensions approach physical limits, issues like leakage current and power dissipation escalate, posing significant hurdles to further miniaturization and performance scaling.Furthermore, the increasing complexity of semiconductormanufacturing processes has led to soaring costs and technological barriers. Building state-of-the-art fabrication facilities requires billions of dollars in investment, limiting access to cutting-edge technology for all but a few major players in the industry. This concentration of resources raises concerns about market competition and innovation diversity.Additionally, the semiconductor industry grapples with sustainability and environmental impact issues. The manufacturing processes involve hazardous chemicals and consume vast amounts of energy, contributing to pollution and carbon emissions. Addressing these challenges necessitates the adoption of eco-friendly manufacturing practices and the development of energy-efficient semiconductor devices.In conclusion, semiconductor technology stands at the forefront of technological innovation, driving progress across diverse sectors of the economy. While significant advancements have been made, formidable challenges loom on the horizon, requiring collaborative efforts from industrystakeholders, researchers, and policymakers to overcome. By addressing these challenges and embracing emerging opportunities, the semiconductor industry can continue to shape the future of technology and usher in a new era of innovation.。

微电子专业英语课件

微电子专业英语课件

Principles and Design of Integrated Circuits
Integrated Circuit (IC) Basics
An IC is a miniaturized electronic circuit consisting of transistors, resistors, capacitors, and other components integrated onto a single silicon chip.
of microelectronics.
02
To develop students' ability to read, write, and communicate effectively in English within the context of
microelectronics.
03
To prepare students for future careers in the global microelectronics industry, where English is the lingua
Coverage of analog and digital circuit design principles, including circuit analysis techniques and design methodologies.
Course content and structure
Students should be able to communicate effectively in English during oral presentations, seminars, and discussions related to microelectronics.

三千多个 植物学名词中英文对照1

三千多个 植物学名词中英文对照1

盖高楼:全国科技名词审定委员会-植物学名词(1)盖高楼:全国科技名词审定委员会-植物学名词(2)01.001 植物学botany, plant science01.002 植物生物学plant biology01.003 植物个体生物学plant autobiology01.004 发育植物学developmental botany01.005 植物形态学plant morphology01.006 植物解剖学plant anatomy, phytotomy01.007 植物细胞学plant cytology01.008 植物细胞生物学plant cell biology01.009 植物细胞遗传学plant cytogenetics01.010 植物细胞形态学plant cell morphology01.011 植物细胞生理学plant cell physiology01.012 植物细胞社会学plant cell sociology01.013 植物细胞动力学plant cytodynamics01.014 植物染色体学plant chromosomology01.015 植物胚胎学plant embryology01.016 系统植物学systematic botany, plant systematics01.017 植物小分子系统学plant micromolecular systematics01.018 演化植物学evolutionary botany01.019 植物分类学plant taxonomy01.020 植物实验分类学plant experimental taxonomy01.021 植物化学分类学plant chemotaxonomy01.022 植物化学系统学plant chemosystematics 01.023 植物血清分类学plant serotaxonomy01.024 植物细胞分类学plant cellular taxonomy 01.025 植物数值分类学plant numerical taxonomy 01.026 植物分子分类学plant molecular taxonomy 01.027 植物病毒学plant virology01.028 藻类学phycology01.029 真菌学mycology01.030 地衣学lichenology01.031 苔藓植物学bryology01.032 蕨类植物学pteridology01.033 孢粉学palynology01.034 古植物学paleobotany01.035 植物生理学plant physiology01.036 植物化学phytochemistry01.037 植物生态学plant ecology, phytoecology01.038 植物地理学plant geography, phytogeography 01.039 植物气候学plant climatology01.040 植物病理学plant pathology, phytopathology 01.041 植物病原学plant aetiology01.042 植物毒理学plant toxicology01.043 植物历史学plant history01.044 民族植物学ethnobotany01.045 人文植物学humanistic botany 01.046 植物遗传学plant genetics01.047 植物发育遗传学plant phenogenetics 01.048 分子植物学molecular botany01.049 分类单位taxon 又称“分类群”。

考研复试面试英文翻译

考研复试面试英文翻译

英⽂写作翻译频道为⼤家整理的考研复试⾯试英⽂翻译,供⼤家参考:)⾃然科学理学 Natural Science 数学 Mathematics 基础数学 Fundamental Mathematics 计算数学 Computational Mathematics 概率论与数理统计 Probability and Mathematical Statistics 应⽤数学 Applied mathematics 运筹学与控制论 Operational Research and Cybernetics物理学 Physics 理论物理 Theoretical Physics 粒⼦物理与原⼦核物理 Particle Physics and Nuclear Physics 原⼦与分⼦物理Atomic and Molecular Physics 等离⼦体物理 Plasma Physics 凝聚态物理 Condensed Matter Physics 声学 Acoustics 光学Optics ⽆线电物理 Radio Physics化学 Chemistry ⽆机化学 Inorganic Chemistry 分析化学 Analytical Chemistry 有机化学 Organic Chemistry 物理化学(含化学物理) Physical Chemistry (including Chemical Physics)⾼分⼦化学与物理 Chemistry and Physics of Polymers天⽂学 Astronomy 天体物理 Astrophysics 天体测量与天体⼒学 Astrometry and Celestial Mechanics地理学 Geography ⾃然地理学 Physical Geography ⼈⽂地理学 Human Geography 地图学与地理信息系统 Cartography and Geographic Information System⼤⽓科学 Atmospheric Sciences ⽓象学 Meteorology ⼤⽓物理学与⼤⽓环境 Atmospheric Physics and Atmospheric Environment海洋科学 Marine Sciences 物理海洋学 Physical Oceanography 海洋化学 Marine Chemistry 海洋⽣理学 Marine Biology 海洋地质学 Marine Geology 地球物理学 Geophysics 固体地球物理学 Solid Earth Physics 空间物理学 Space Physics地质学 Geology 矿物学、岩⽯学、矿床学 Mineralogy, Petrology, Mineral Deposit Geology 地球化学 Geochemistry 古⽣物学与地层学(含古⼈类学) Paleontology and Stratigraphy (including Paleoanthropology) 构造地质学 Structural Geology 第四纪地质学 Quaternary Geology⽣物学 Biology 植物学 Botany 动物学 Zoology ⽣理学 Physiology ⽔⽣⽣物学 Hydrobiology 微⽣物学 Microbiology 神经⽣物学 Neurobiology 遗传学 Genetics 发育⽣物学 Developmental Biology 细胞⽣物学 Cell Biology ⽣物化学与分⼦⽣物学Biochemistry and Molecular Biology ⽣物物理学 Biophysics ⽣态学 Ecology系统科学 Systems Science 系统理论 Systems Theory 系统分析与集成 Systems Analysis and Integration 科学技术史 History of Science and Technology农业科学农学 Agriculture作物学 Crop Science 作物栽培学与耕作学 Crop Cultivation and Farming System 作物遗传育种学 Crop Genetics and Breeding 园艺学 Horticulture 果树学 Pomology 蔬菜学 Olericulture 茶学 Tea Science 农业资源利⽤学 Utilization Science of Agricultural Resources ⼟壤学 Soil Science 植物营养学 Plant Nutrition 植物保护学 Plant Protection 植物病理学 Plant Pathology 农业昆⾍与害⾍防治 Agricultural Entomology and Pest Control 农药学 Pesticide Science。

蛇的斑纹怎么介绍英文作文

蛇的斑纹怎么介绍英文作文

蛇的斑纹怎么介绍英文作文Snake Patterns: A Study in Nature's Artistry。

Snakes, with their sleek bodies and mesmerizing movements, have long captivated human curiosity. Among the many intriguing features of these reptiles, their patterns stand out as both beautiful and functional. In this essay, we will delve into the diverse world of snake patterns, exploring their significance, diversity, and evolutionary adaptations.One of the most striking aspects of snakes is undoubtedly their intricate patterns. These patterns serve various purposes, including camouflage, communication, and thermoregulation. Across different snake species, patterns can vary significantly, ranging from simple stripes to complex geometric shapes. 。

Camouflage is perhaps the most well-known function of snake patterns. Many species have evolved patterns thatallow them to blend seamlessly into their surroundings, making them less visible to predators and prey alike. For instance, the diamondback rattlesnake boasts a diamond-shaped pattern along its back, which helps it camouflage among rocks and desert terrain. Similarly, the green tree python displays a vibrant green coloration with irregular yellow markings, allowing it to disappear among foliage in its arboreal habitat.In addition to camouflage, snake patterns also play a crucial role in communication. Certain species use their patterns to signal aggression, submission, or mating readiness to other snakes. For example, the vibrant colors and intricate patterns of the coral snake serve as awarning to potential predators, indicating its potent venom and advising against confrontation. Similarly, during courtship rituals, male garter snakes display theirbrightly colored stripes to attract potential mates.Furthermore, snake patterns can aid in thermoregulation, helping these ectothermic animals maintain optimal body temperatures. Some species, such as the copperhead snake,exhibit patterns that absorb sunlight more efficiently, allowing them to bask in the sun and raise their body temperature. Conversely, snakes living in cooler environments may have darker patterns that absorb more heat, enabling them to stay warm in colder climates.The diversity of snake patterns is truly astounding, reflecting the adaptability of these creatures to a wide range of environments and ecological niches. From the intricate diamond patterns of pythons to the bold stripesof king cobras, each species has evolved patterns that are uniquely suited to its habitat and lifestyle. Moreover, within each species, individual variation in patterns can occur, further highlighting the complexity of snake patterning.Evolutionary biologists have long been fascinated bythe origins of snake patterns and the selective pressures that have shaped them over millions of years. Research suggests that patterns may have evolved in response to predation pressure, mate selection, or environmentalfactors such as habitat type and temperature. By studyingthe genetic basis of snake patterns, scientists hope to unravel the underlying mechanisms driving their diversity and evolution.In conclusion, snake patterns represent a fascinating intersection of art and science, showcasing the beauty and complexity of nature's design. From their role in camouflage and communication to their contribution to thermoregulation, patterns play a crucial role in the survival and success of these remarkable reptiles. By unraveling the mysteries of snake patterns, we gain valuable insights into the evolutionary processes that have shaped life on Earth.。

个体发生学 英文

个体发生学 英文

个体发生学英文Ontogeny: The Journey of Individual DevelopmentOntogeny, the study of the development of an individual organism from its inception to its mature form, is a fascinating and complex field of study. It encompasses the remarkable journey an organism takes, from a single cell to a fully-fledged, functioning being. This process, known as individual development, is a remarkable feat of nature, showcasing the intricate mechanisms that govern the transformation of a simple zygote into a complex, multifaceted organism.At the heart of ontogeny lies the process of embryogenesis, the initial stages of development where a fertilized egg, or zygote, undergoes a series of rapid cell divisions and differentiation. This initial stage is marked by the formation of the three primary germ layers – the ectoderm, mesoderm, and endoderm – which will eventually give rise to the various tissues and organs that make up the mature organism. The ectoderm, for instance, will form the nervous system and the outer layer of the skin, while the mesoderm will give rise to the muscular and skeletal systems, and the endoderm will form the digestive and respiratory systems.As the embryo develops, it undergoes a remarkable transformation, moving from a simple, undifferentiated mass of cells to a complex, organized structure with distinct organ systems. This process is guided by a intricate network of genetic and epigenetic factors, which work in concert to orchestrate the precise timing and patterning of cell division, migration, and differentiation. The expression of specific genes, the activation of signaling pathways, and the establishment of morphogen gradients all play crucial roles in shaping the developing organism.One of the most remarkable aspects of ontogeny is the phenomenon of morphogenesis, the process by which the embryo takes on its characteristic form and shape. This process is driven by a complex interplay of cell-cell interactions, mechanical forces, and biochemical signals, all of which work together to sculpt the developing organism. As the embryo grows and takes shape, it undergoes a series of dramatic changes, from the formation of the neural tube and the development of the limbs, to the closure of the body wall and the formation of the face and other features.Alongside the physical changes, the developing organism also undergoes a remarkable transformation in its physiology and behavior. As the various organ systems take shape, the embryo begins to exhibit basic functions, such as the beating of the heartand the movement of the limbs. As development progresses, these functions become increasingly complex, with the emergence of more sophisticated behaviors, such as the ability to sense and respond to environmental stimuli.One of the most fascinating aspects of ontogeny is the concept of developmental plasticity, the ability of an organism to adapt and respond to changes in its environment during the course of its development. This plasticity allows the organism to fine-tune its development in response to various cues, such as changes in temperature, nutrition, or other environmental factors. This ability to adapt and respond to environmental challenges is a key aspect of the evolutionary success of many species, as it allows them to thrive in a wide range of ecological niches.Another important aspect of ontogeny is the role of epigenetic factors in shaping the developing organism. Epigenetics, the study of heritable changes in gene expression that do not involve changes in the DNA sequence, has emerged as a critical field in the understanding of individual development. Epigenetic mechanisms, such as DNA methylation and histone modifications, can profoundly influence the expression of genes during the course of development, leading to the formation of distinct cell types and tissue-specific functions.The study of ontogeny has also yielded important insights into the evolutionary history of life on Earth. By examining the developmental patterns of various organisms, scientists have been able to uncover the evolutionary relationships between different species, and to understand the underlying mechanisms that have driven the diversification of life. The concept of recapitulation, for instance, which suggests that the development of an individual organism mirrors the evolutionary history of its species, has been a subject of intense study and debate within the field of evolutionary biology.In conclusion, the study of ontogeny is a rich and multifaceted field that offers a window into the remarkable complexity of life. From the initial stages of embryogenesis to the mature form of the organism, the journey of individual development is a testament to the remarkable adaptability and resilience of living systems. By continuing to explore the intricacies of this process, scientists and researchers hope to uncover new insights into the fundamental mechanisms that govern the development and evolution of life on our planet.。

半导体ddpf工艺流程

半导体ddpf工艺流程

半导体ddpf工艺流程Semiconductor DDPF technology, also known as double diffusion process with polycrystalline and field oxide, is a crucial process in the fabrication of integrated circuits. 半导体DDPF技术,也称为双扩散工艺与多晶和场氧化物,在集成电路制造过程中是一个至关重要的工艺。

It involves the formation of both n-type and p-type doped regions ona silicon substrate, which is essential for the creation of various electronic components on the chip. 它涉及在硅衬底上形成n型和p型掺杂区域,这对于在芯片上创建各种电子元件是必不可少的。

The DDPF process consists of several key steps, including oxidation, diffusion, and deposition, which are meticulously controlled to ensure the desired electrical properties and performance of the resulting integrated circuits. DDPF工艺包括几个关键步骤,包括氧化、扩散和沉积,这些步骤都经过精心控制,以确保最终集成电路的所需电气特性和性能。

Understanding the DDPF technology from a manufacturing perspective is essential in order to appreciate the complexities involved in producing high-quality semiconductor devices. 从制造角度了解DDPF技术对于欣赏生产高质量半导体器件所涉及的复杂性至关重要。

民国时期盘扣的造型艺术及流行变迁

民国时期盘扣的造型艺术及流行变迁

丝绸JOURNAL OF SILK历史与文化第58卷第5期民国时期盘扣的造型艺术及流行变迁冒绮(上海工程技术大学纺织服装学院,上海20I620)摘要:盘扣是重要的中国传统服装元素,在民国时期发展至顶峰,民国盘扣的造型艺术及流行变迁受到西风东渐的影响。

文章根据历史文献、实物和图像等资料,梳理了中国传统盘扣的历史沿革,分析了民国盘扣的造型艺术,探讨了民国盘扣流行变迁,并管窥民国社会文化观念变化,对中国传统服饰文化的传承发展提供了合理依据。

研究表明:一字扣体现极简风格,盘花扣体现装饰艺术,其他盘扣体现材料艺术,盘扣制作技艺弘扬了中国传统手工艺的工匠精神。

民国一字扣的渐变是对传统服饰的延续,盘花扣在民国时期突然流行,其嬗变受到欧洲新艺术运动的影响。

关键词:民国;盘扣;造型艺术;流行变迁;西风东渐;盘花;传统服饰中图分类号:TS94I.I2;K892.23文献标志码:B文章编号:I00I7003(2021)05009407引用页码:05I202DOI:I0.3969/j.issn.I00I-7003.2021.05.0I4Patterning art and popularity evolution of button knots in the Republic of China eraMAO Qi(School of Textiles and Fashion,Shanghai University of Engineering Science,Shanghai20I620,China)Abstract:Button knot as one of essential elements of traditional Chinese clothing evolved to its summit during the Republic of China.Its patterning art and popularity evolution during the Republic of China were affected by the western trendinto east.Based on historical literature,real objects and images,the historical evolution of Chinese ancient traditional buttonknots was sorted out,the patterning art in the Republic of China was analyzed,and the popularity evolution of button knots inthe Republic of China was discussed.Through an investigation of the changes in social and cultural concepts in the Republicof China,this study is hoped to provide a reasonable basis for the inheritance and innovation of traditional Chinese clothingculture.The study has shown that one-style-button-knots manifest minimalist style,flower-style-button-knots manifestdecorative art,other-style-button-knots reflect material art.The button knot manufacturing craftsmanship carries forward thecraftsman spirit of traditional Chinese handicrafts.The gradual change of one-style-button-knots in the Republic of China is acontinuation of traditional clothing.There was a sudden popularity of flower-style-button-knots during the Republic of China,and the evolution was influenced by Art Nouveau.Key words:the Republic of China;button knots;patterning art;popularity evolution;western trend into east;twining flowers;traditional clothing盘扣是中式服装重要组成部件,起到闭合服装开襟的作用[|]。

皮尔逊的社会达尔文主义_论文

皮尔逊的社会达尔文主义_论文

皮尔逊的社会达尔文主义摘要:英国哲人科学家卡尔•皮尔逊是一位社会达尔文主义者,他运用进化论思想探究了无机世界、人的历史进化、自然选择于道德、民族问题、人类和社会。

在这个过程中,他既提出了某些富有启发性的见解,也在一定程度上宣扬了种族主义和殖民主义的谬论。

关键词:皮尔逊进化论社会达尔文主义哲人科学家Abstract: English philosopher-scientist, Karl Pearson, is a social Darwinism. With the aid of the theory of evolution he probed into the inorganic world, human historical evolution, natural selection & morals, national problems, man & society. In his researches he advanced some enlightening views and also publicized absurd theories of racialism & colonialism.Key Words: K. Pearson the theory of evolution social Darwinism philosopher-scientist在整个19世纪,自然科学的方法和发现使社会说明革命化。

维多利亚女王(1819-1901)时代的社会理论家都坚持认为,实证科学不得不改造知识的逻辑,从而改造对伦理、政治和宗教的处理。

尤其是,在达尔文的《物种起源》(1859)出版之前,英国理论家就开始用进化的术语分析社会,不仅仅是用发展的术语(这具有更早的历史),而且特别用生物进化的术语。

在该世纪初,马尔萨斯在他的人口研究中就审查了自然定律对社会组织的影响。

斯宾塞在他的《社会静力学》(1851)中立足于孔德和生物科学的进化论陈述了他的社会学[ ]。

罗伊·阿斯科特|技术智力美学,后生物时代的100个术语和含义

罗伊·阿斯科特|技术智力美学,后生物时代的100个术语和含义

罗伊·阿斯科特|技术智力美学,后生物时代的100个术语和含义技术智力美学,后生物时代的100个术语和含义罗伊·阿斯科特著,袁小潆编,周凌、任爱凡译选自《未来就是现在:艺术、技术和意识》,金城出版社,2012年。

艺术(Art)相比传统上的艺术将重心放在对象的外表和其所代表的含义,今天的艺术关心的是互动、转换和出现的过程。

艺术画廊(Art Gallery)现在艺术家面向世界的窗口变成了通往数据空间之门。

随着画廊从橱窗展陈转变为运营中心,博物馆必然会成为一个合作实验室。

艺术家(Artist)智力航行环境的创造者,开放式网络进化系统的开拓者。

行为(Behaviour)古典美学处理形式行为,新美学处理行为形式。

生物学家园(Biohaus)我们需要一个生物学的建筑,它不像包豪斯那样虚张声势。

播种应代替设计,建筑物必须是能够种植的,并且能够获得生长。

生物神话(Bio-myths)我们仍然与神话探索密切关联。

现在的环境是生物化和行为化的,通过微观/宏观层面进行动能攒升。

为伟大的生物神话人工生命做准备。

仿生性(Bionicity)同步性是独立的事件发生在一个统一的时间内。

图像性是独立的数据融合成一个统一的形象。

仿生性是人工和生命系统结合成一个统一的意识。

生物远程通信(Bio-telematics)随着生物的渗入,我们与网络密切地联系在一起,意识问题变成了首要问题,并且艺术既定义生物远程通信,也在其中生存。

身体(Body)此前为自然属性,现在是仿生改造的站点,在这里我们可以重新创造自己和重新定义什么是人类。

计算机工艺美术(Computer Arts and Crafts)随着19世纪威廉·莫里斯(WilliamMorris)的工艺美术,当创作技巧取代创作思想的首要地位时,我们可以看到数字艺术从艺术逐渐下降为工艺。

连通性(Connectivity)联结主义是认知科学家的一种方式,联结主义是技术智力艺术家的一种方式。

发育生物学研究英语作文

发育生物学研究英语作文

发育生物学研究英语作文Developmental Biology: Unraveling the Mysteries of Life.Developmental biology delves into the intricate processes that guide the transformation of a single-celled zygote into a fully formed organism. This multifaceted discipline encompasses a wide array of scientific approaches, ranging from molecular genetics to embryology,to elucidate the fundamental principles governing the development and growth of organisms.During early embryonic development, a remarkable cascade of events unfolds, orchestrated by a complex interplay of genetic and environmental factors. Thefertilized egg undergoes a series of rapid cell divisions, forming a blastula and subsequently a gastrula, which establishes the primary germ layers—the building blocks from which all tissues and organs will arise.Underlying these developmental processes is a symphonyof molecular events. Gene expression, controlled by a myriad of regulatory elements, dictates the fate of differentiating cells, specifying their identity and function. Morphogens, signaling molecules that diffuse through tissues, create concentration gradients that guide the organization and patterning of the embryo.As development progresses, tissues begin to specialize and organize into organs, a process known as organogenesis. The heart, brain, and lungs are just a few examples of the intricate structures that emerge during this critical period. The formation of these organs involves a concerted interplay of cell migration, cell adhesion, and tissue remodeling.Modern developmental biology has witnessed significant advancements, particularly in the realm of molecular genetics. The advent of techniques such as gene editing and genome sequencing has empowered researchers to identify and manipulate genes involved in developmental processes. This has led to a deeper understanding of the molecular basis of congenital malformations and diseases.Moreover, the integration of computational modeling and bioinformatics has facilitated the creation of sophisticated simulations that can predict how developmental processes will unfold. Such models have proven invaluable for exploring the complex interactions between different molecular pathways and for elucidating the genetic basis of human traits.Furthermore, developmental biology has far-reaching implications for understanding evolution. By studying how genes regulate the development of organisms, scientists can gain insights into the evolutionary forces that have shaped the diversity of life on Earth. Comparative developmental biology, which explores similarities and differences in developmental processes across species, provides a unique perspective on evolutionary relationships.The knowledge gleaned from developmental biology has profound implications for human health. Developmental disorders, such as neural tube defects and limb malformations, can arise from disruptions in the intricatedevelopmental processes that guide fetal development. Understanding the molecular and genetic basis of these disorders holds the potential to improve diagnosis, treatment, and prevention strategies.Additionally, regenerative medicine, which aims to repair or replace damaged tissues, draws heavily upon the principles of developmental biology. By manipulating developmental pathways, researchers seek to stimulate the regeneration of tissues that have been lost or damaged due to disease or injury.In conclusion, developmental biology stands at the forefront of scientific discovery, bridging the gap between the microscopic and macroscopic worlds. By unraveling the intricate mechanisms that govern the development and growth of organisms, researchers are gaining a deeper understanding of life's origins, evolution, and the human condition. As the field continues to advance, it promises to provide transformative insights into human health and disease, and to illuminate the boundless possibilities of life itself.。

大空间尺度上物种多样性的分布规律_胡军华

大空间尺度上物种多样性的分布规律_胡军华

应用与环境生物学报 2007,13(5):731~735Chi n J App lEnvi ron B i o l =ISSN 1006 687X2007 10 25收稿日期:2006 07 17 接受日期:2006 09 21*广东省科学院人才基金(No .03 5)和广东省科学院台站基金(2004,2005) Supported by the Fund f or Tal en ts (N o .03 5)and t h e Fund for Fiel d S t ati on (2004,2005)fro m Guangdong Provi n ci alAcade my of S ci ences ,Ch i na**通讯作者 C orres ponding author (E m ai:l hu j h@gde.i gd .cn;ji angz g@i oz .ac .cn)大空间尺度上物种多样性的分布规律*胡军华1,2,3胡慧建1**蒋志刚1**(1中国科学院动物研究所动物生态与保护生物学重点实验室 北京 100080)(2华南濒危动物研究所 广州510260;3中国科学院研究生院 北京 100049)摘 要 物种多样性是生物多样性在物种水平上的表现形式.由于全球性保护行动的开展和多学科的相互渗透,把物种多样性研究推向大时空尺度方向发展,一些新的研究领域得到拓展.本文综述了物种多样性在大空间尺度上的经典研究(包括梯度变化格局、个体大小频次分布格局和物种-面积关系),同时着重探讨了经典研究的新认识及一些新领域内所揭示的新格局,主要有:生物类群间物种数的协同变化、物种和高级分类阶元的关系、局域物种多样性与区域物种多样性关系以及全球变化影响等等.参79关键词 物种多样性;大空间尺度;分布规律;分类单元CLC Q 14D istri bution Regul arities of Species D iversity at Large Spatial Scale*HU Junhua1,2,3, HU H uijian1**&JI A NG Zh i g ang1**(1K e y L abora t ory of Ani ma lE colo gy and Con serva tion,Institute o f Z oology,C hinese Acad e my o f S cie n ces ,Beiji ng 100080,Ch i n a)(2Sou t h Ch i na In stit u t e of E nd ang e re d A ni ma ls ,Guangzhou 510260,Ch i na)(3G raduate Un iversit y of Ch i nese A c ade my of Sciences ,B eiji ng 100049,C h i na)Abstract Spec i es divers it y i s the representa ti on o f biod i versity a t the level of spec i es .D ue to g l oba l conse rvation actions and m ulti disci p lines i nterpene trati on ,t he patterns o f spec i es d i versity have been deve l oped at l arge spa ti o te m pora l sca le .Th is paper rev i ews the classical patterns (i ncl uding the patterns of grad ient change ,frequency d i str i bution of body s i ze and spec ies ar ea curve),and discusses t he new arguments o f classical pa tterns and new ly developed patte rns i n so m e do m a i ns ,s uch as cova riation o f the nu mber of species a m ong tax ono m ic groups ,relations be t w een species and higher tax ono m ic taxa ,re lati ons bet ween l oca l and reg i onal spec i es d i versities and i m pacts of g loba l changes .R ef 79K eyword s species d i versity ;large spati a l sca l e ;distributi on regu l a rity ;taxon CLC Q 14物种多样性是生物多样性在物种水平上的表现形式[1].近年来,空间尺度对物种多样性分布的影响受到人们的重视.空间尺度大体可划分为个体空间、局域斑快、区域尺度、封闭系统和生物地理学尺度.其中,属于大空间尺度范畴的生物地理学尺度倍受关注[2].早在19世纪,人们就已发现物种多样性在大空间尺度上具有一定的规律性,随后对物种多样性的梯度变化格局、个体大小频次分布格局和物种-面积关系等展开了一系列的研究[3,4].近年来,随着对生物多样性全球性衰退以及全球变化认识的提高,人们越来越意识到人类活动对地球生命所造成的巨大破坏,但却还不了解这种破坏所造成的真正后果[5,6].因此,生物多样性在大空间尺度上的保护和研究已不再是单个地区或国家的事务,而是全球的共同责任和义务,多国间的和国际间的合作正在加强,这既有政府行为也有非政府组织的实践[7,8].也正是实践的需要,多学科(如生物地理学、古生物学、群落生态学等)在生物多样性的保护和研究中迅速渗透和结合,使得生物多样性在大时空尺度上的研究向更深更广的方向发展,生物多样性的全球格局研究成为关注的热点[9,10],宏生态学的产生则是其中典型的例子[11,12].如今,在对经典研究重新认识的基础上,物种多样性的大空间尺度格局研究主要是生物类群间物种数的协同变化、物种和高级分类阶元的关系、局域物种多样性与区域物种多样性关系以及全球变化影响等.这些为生物多样性的保护实践提供理论指导[11,13].1 经典研究及新认识1.1 梯度变化1.1.1 空间梯度格局 空间梯度变化是物种多样性大空间尺度格局的一个显著特征,许多综述性文献都有所涉及[1,4,9,13~15].经典研究中,纬度梯度格局最为典型[16],并存在于多种分类类群,如植物[17~19]、脊椎动物[20]、无脊椎动物[14]、海洋生物[21]和海洋生物化石[4].然而,关于纬度梯度格局的解释仍存在较大争议[4,22].这主要是由于不同的研究选择不同的空间尺度引起的[23],对一些在空间梯度格局中可能产生的变量的不同控制也是部分原因(例如,可利用面积或对物种地理分布的几何限制等)[22].其次是垂直梯度格局,包括海拔[24,25]和水深[26].再者是从海洋到内陆梯度格局[27].最后是经度梯度格局,但趋势不明显[28].1.1.2 影响因子与格局关系 许多研究认为物种多样性大空间尺度格局与环境因子密切相关,主要表现在3个方面:(1)在相关性分析中,物种丰富度往往与环境因子呈显著相关[25],有的甚至建立预测模型.张荣祖和林永烈(1985)和张荣祖(1999)在中国的研究发现,物种丰富度与年降水、年均温等因素显著相关[20,29];R etuerto(2004)通过梯度变化和地理分布分析估计植物对气候的适应性[30].有作者给出了能量与物种丰富度间的预测模型[31]和物种丰富度与营养级关系模型[26,32].(2)不同的物理因子与不同的类群之间相关性不同.张荣祖(1999)指出,不同动物类群多样性与年日照时间、降雨等有明显的相关性[29].(3)不同自然区域中各物理因子所起作用不同.在中国的青藏高原地区海拔是第一性的,在干旱和半干旱地区湿度是第一性的[20,29].除环境因子外,当地的历史和生境差异对空间格局也会产影响,如中国与美国维管束植物、被子植物丰富度间的差异[17~19,33~34],尼加拉瓜的鸟类格局[35].生境复杂多样的地方,物种丰富度高[36].1.1.3 机制 物种多样性大空间尺度格局的形成过程是由多因子决定的,是与生物进化历史相联系的复杂过程[9].其形成机制存在多种假说,蒋志刚(1997)列出了其中的8种,这些假说分别用了环境因子和生物因子进行解释,这么多假说的存在是由研究尺度或生物类群不同而造成的[1].有作者认为物种多样性大空间尺度格局一定有一个第一性的原因.一般认为,物理因子是第一性的,而生物间的相互关系是第二性的,能量可能是决定性因子[31,37].1.2 个体大小频次分布格局1.2.1 格局 H utch i nson&M acA rthur(1959)报道了美国密执安州和欧洲陆生兽类身体长度的频次分布图,发现体形中等的兽类物种数要明显多于体型较大或较小的兽类[38].以上格局被证实具有普遍性[39],所有生物物种的个体大小频次分布符合该格局[40].但是,个体大小频次分布被确认为右偏的log正态分布[3].Bro w n&N ico letto(1991)对比北美陆生兽类在大区域和小块生境中的体重频次分布,发现在小块生境中为均匀分布,而大尺度中具有右偏的l og正态分布[41].该结果表明,中等体型的物种占据小范围生境,而较大或较小体形的物种占据大范围生境.M arquet&Cofre(1999)对比了南、北美洲大陆兽类的体重频次分布,发现两大洲具有很大相似性.在南美洲兽类组成中,南、北美洲成分也都符合该规律[39].该结果表明体重频次分布受到起源和历史的影响.1.2.2 机制 Hu tch i nson&M ac A rt hur(1959)指出,该格局是由大量的 马赛克元素 (M o sa i c e le m en ts)组成,体型中等的物种所需元素要少于体形较大或较小的物种[38].由于l og正态分布是多个随机变量多重组合的结果,该解释不久被分形几何学说(F racta l geome try)所代替[42].以上解释忽略了体型较小物种的频次分布特征,所以人们尝试利用生理和生态异速生长来进行解释,涉及个体大小与多度、生长能量间的关系研究.B rown(1993)推导出最佳适宜体重模型,并根据现有生理实验结果,算出兽类最佳体重约为100g、鸟类约为30g,此结果得到实际观察的支持[43].在隔离条件下,一方面,兽类中体重大于100g的物种趋向小型化,而体重小于100g的物种趋向大型化[3];另一方面,兽类体重极大值和极小值分别与物种最大分布面积回归所得方程的交点在100g处[44].因此,上述结果较好地解释了个体大小频次分布格局的内在机制.1.3 物种-面积关系1.3.1 模型 物种-面积效应曲线是生物多样性研究中的经典模型,在生物多样性保护具有重要意义[45].特别是关于热带地区的物种-面积关系已被充分研究[46,47].物种-面积曲线存在4种不同的模式[4],人们通常采用P reston(1962)公式:S=CA z o r lg S=lg C+Z l g A(S为物种数,A为面积,C和Z 为参数)[48].Z值在同一区域的不同生物类群间或不同区域的同一生物类群中差异不明显,而在岛屿与大陆之间有明显差异(岛屿多为0.25~0.35,大陆为0.12~0.18)[4,49].物种数量与面积大小成指数关系源于关于物种丰度的假说或者是自相似性的概念.P l otk i n(2002)却发现这个规律在所有空间尺度上存在一致的离差,而且热带雨林在少于50 h m2的面积内没有自相似性[50].于是发展了一个广义的物种–面积关系模型,能够比任何其他途径都准确地从小尺度数据样本预测出大尺度物种多样性.1.3.2 生物学含义及机制 自P reston(1962)总结物种–面积关系后,许多研究人员尝试解释物种–面积方程及其参数的生物学含义[49].P reston(1962)认为,Z值在0.17~0.33之间是因为物种丰富度符合l og正态分布,加上非隔离区域在取样时有着较高的个体数/物种数比而使斜率低于岛屿值[48].H ansk i&G y llenberg(1997)利用异质种群(M etapopu l a ti on,又译为集合种群)理论提出岛屿-大陆模型和异质种群模型,发现岛屿-大陆模型的斜率要低于异质种群模型,而岛屿-大陆模型对应于岛屿格局而异质种群模型则对应于大陆格局[51].Sto rch(2003)认为物种-面积关系归因于样本效应,栖息地异质性、种群和集合种群过程引起的空间聚群.样本效应和栖息地异质性都不能单独解释观察到的物种-面积模型,两种模型所预测的物种丰富度都比实际高.适合的栖息地数量和样方地占有之间的关系对于2/3的物种来说都是无足轻重的.因此,物种-面积关系的斜率和形状受到栖息地异质性和空间聚集两方面的影响[52].2 新研究及格局2.1 生物类群间物种丰富度的协同变化由于物种多样性在大空间尺度上具有梯度变化格局,人们认为不同生物类群间物种丰富度在空间上存在正相关关系.该关系成为当前生物多样性4个重要研究领域之一[9].但是,相732 应用与环境生物学报 Chi n J App lEnvi ron B i o l 13卷关的研究结果却并不一致.有报道指出,不同生物类群间物种丰富度的相关关系很低而且没有预测价值[53~55];而其他报道称,不同生物类群间物种丰富度高度相关[9,29,56].G aston(2000a)认为,生物类群间物种丰富度的相关是由于受到相同决定性生态因子的影响[9].张荣祖(1999)发现受环境因子影响的相似类群之间物种丰富度具有强相关,两栖类和爬行类支持了该解释[29].中国不同地理尺度上和区域上鸟兽间物种数量具强相关支持G aston(2000a)的观点,并且利用物种-面积曲线可以推导出两类群间的相关模型[56].但是,协同变化的分析结果会受到分类类群、分类单元、数据质量、研究对象、调查时间和研究方法等多种因素影响[56].2.2 物种和高级分类阶元的关系物种和高级分类阶元的关系主要包括两个方面的内容:一是数量上的关系,即物种丰富度和属以上阶元的丰富度关系;二是频次分布关系,即属以上阶元所含物种数的频次分布. 物种和高级分类阶元在数量上具强相关关系,已在许多分类类群上被报道,如植物、兽类、鸟类、两栖类、鱼类等等[57].值得注意的是,这种关系具有普遍意义,无论是不同地理尺度和区域,还是不同类群间都存在[9].人们探讨利用高级分类阶元代替物种作为生物多样性的度量单位来进行热点地区的选择和评价,发现两者效果一致,但高级分类阶元的应用大大节约了时间和费用,因此具有应用价值[57,58].对物种和高级分类阶元的数量相关机理探讨较少,仅作为一种数量关系[59].根据蒋志刚和纪力强(1999)及Jiang&H u (2000a,b),属、科中物种数在鸟兽间具有强相关关系,这表明物种在科、属水平上的频次分布有一定规律性[59~62].因此,物种和高级分类阶元的数量相关应是规律性的.Bro w n(1995)在提出群落 组合规则 时指出物种与高级分类阶元的频次关系为1属1种出现的频次最多,然后是1属2种,再是1属3种,以此类推,并认为此格局是物种竞争的结果[3].然而,在实际研究中却很少有频次关系的相关报道.2.3 局域物种多样性与区域物种多样性间的关系以往,生物多样性方面研究多在小尺度进行,特别是群落生态学研究.这些研究占到生物多样性研究的75%以上[11].但是,越来越多的研究表明,生物多样性在不同空间尺度上有着不同的过程和组成方式[3,9,11].其中,区域的物种构成了局域地区的物种库,直接影响局域地区物种组成[9],并且局域与区域的关系讨论涉及到局域物种丰富度是否存在饱和问题.在局域与区域的物种多样性关系中,两种类型受到特别的重视:一是局域地区物种丰富度小于区域的,但与其成比例关系(类型 );一是局域地区物种多样性只在一定范围内随区域物种多样性增加而增加,到一定值后保持不变(类型 ).现有研究更多地发现类型 的存在.类型 的存在说明局域地区是没有饱和的,这与其他研究相矛盾[9].2.4 全球变化的影响全球变化(G l obal change)作为一个专用的科学名词和一门交叉学科,随着社会对地球环境问题的重视,日益被人们所认识[63].然而,近年来才把全球变化对物种多样性大空间格局影响作为全球变化研究中的重要科学问题之一[64,65].目前,大多数研究集中在CO2浓度增加对物种多样性的影响及生物入侵等问题上[66~72].S m ith(2000)发现,在北美洲西部沙漠地区CO2浓度增加是受全球变化驱使的,并对外来入侵植物有利的这种物种组成变化可能加速火灾发生周期,降低多样性和改变生态系统功能[68].R e ich(2001)则发现在CO2浓度升高和N2沉积的生态系统中,植物多样性和组成影响生物量的增加和碳的获得,物种组成贫乏的比物种组成丰富的增加得要少[69].Zava l eta(2003)模拟全球气候变化,指出C O2浓度的增加和N2的沉积能够减少植物多样性,而降雨量的增加则增加多样性,温度升高没有明显的作用[70].生物入侵被看成是全球变化的重要内容,正成为威胁各地物种多样性的重要因素之一,并即将上升为导致物种多样性丧失的第一位原因[67].生物入侵对物种多样性格局的影响具有两个长期的全球效应:第一,生物入侵将降低地域性动植物区系的独特性,并最终退化和失去服务功能;第二,生物入侵打破地理隔离,造成生物多样性的灾难性丧失[67].Jansson(2003)提出限制特有种的数量的全球模型是由1万~10万年时间内的气候变化引起的,这种关系是随着面积、纬度位置、前冰河作用的程度和海洋岛屿性的变化而变化的[71].Ju lliard(2004)探讨了全球变化中造成普通鸟类物种灭绝的重要因子[72].3 讨论大空间尺度上物种多样性研究受到关注,主要原因是: (1)当前生物学研究朝两个极端方向发展,即 微观更微,宏观更宏 .大空间尺度的研究代表了生物学在宏观上的发展趋势;(2)物种多样性和气候的全球变化正引起人们极大关注,而大空间尺度正迎合了人们了解全球变化的需求;(3)多学科,特别是各种宏观生物学(如宏生态学、宏进化、古生物学、群落生态学、生物地理学等等)在物种多样性研究上迅速渗透和结合,使得生物多样性的研究向大尺度方向发展.因此,物种多样性的大空间尺度研究是学科发展必然趋势.有关空间格局的研究,最主要的驱动力就是对地区乃至全球物种数量的预测及其产生的机制[58].作为一种发展趋势,物种多样性在大空间尺度上的研究已是一交叉性学科,而且还深深地影响了其他学科的发展.首先,不同的学科,如生态学、古生物学、进化生物学、生物地理学相交叉融合,大大促进了相关内容的研究及其机制的探讨.因此,多学科成果的跟踪和应用对大空间尺度上物种多样性分布规律的研究无疑是大有裨益的.p值得指出的是,物种多样性的丧失与其他全球性环境问题有密切关系,全球气候变化正对物种多样性产生深刻影响,而这一切都或多或少受人类活动的影响[73].在冻原或高山寒冷地带,气温的升高已证实能改变群落的物种组成[74,75];即便是哥斯达黎加的热带山区,过去二十几年的气温升高已造成二十多种蛙和蟾蜍等两栖动物的灭绝以及鸟类和爬行类物种的大量减少[76].物种多样性大空间尺度格局研究逐渐使人们意识到人类活动导致生境丧失和全球变化是对物种多样性的最大威胁.至20世纪80年代初,全球41%的热带雨林已经消失[77].F rankel等(1981)报道,大量的热带生物种类在生物学家还未来得及鉴定归类之间就会消失掉[78].据W ilson(1992)7335期胡军华等:大空间尺度上物种多样性的分布规律的估算,仅因热带雨林的破坏一年就造成了27000多种生物的灭绝[79].单纯保护某一个濒危物种的作用是十分有限的,所以应该在更大尺度上进行且是对生态系统的保护[1].R eferences1 蒋志刚,马克平,韩兴国.保护生物学.杭州:浙江科技出版社,19972 孙儒泳.动物生态学原理.北京:北京师范大学出版社,20013 B rown J H.M acroecol ogy.Ch i cago:Ch icago U n i vers it y Press,19954 Rosenw ei gM L.Speci es i n Space and T i 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Evolution of Patterning Systemsand Circuit Elements for LocomotionHeekyung Jung1and Jeremy S.Dasen1,*1Howard Hughes Medical Institute(HHMI),NYU Neuroscience Institute,Department of Neuroscience and Physiology,New York University School of Medicine,New York,NY10016,USA*Correspondence:jeremy.dasen@/10.1016/j.devcel.2015.01.008Evolutionary modifications in nervous systems enabled organisms to adapt to their specific environments and underlie the remarkable diversity of behaviors expressed by animals.Resolving the pathways that shaped and modified neural circuits during evolution remains a significant parative studies have revealed a surprising conservation in the intrinsic signaling systems involved in early patterning of bilaterian nervous sys-tems but also raise the question of how neural circuit compositions and architectures evolved within specific animal lineages.In this review,we argue that within the spinal cord aflexible system involving modulation of rostrocaudal positional information,acting in the context of a relatively uniform DV patterning system,can act to modify neuronal organization and connectivity within circuits governing a specific locomotor output.The earliest nervous systems are thought to have consisted of distributed populations of sensory neurons and motor neurons (MNs)that enabled animals to detect environmental changes and translate this information into specific motor actions (Holland,2003).Execution of appropriate motor responses to stimuli is essential to the survival of an organism and one of the most fundamental aspects of nervous system function. Even the most complex regions of vertebrate nervous systems, such as the human cortex,can be considered as processing centers whose primary role is to interpret sensory information and transform it into specific motor commands.In vertebrates,much of the activity of the CNS is channeled into the brain stem and spinal cord with the sole purpose of coor-dinating the activation of muscles.The most well-studied motor circuits in vertebrates are those that control walking and breath-ing,yet we know very little about the genetic modifications that facilitated the emergence of even these relatively simple animal behaviors.In the vertebrate lineage,fundamental changes in the nervous system coincided with the transition from aquatic to terrestrial terrains,and necessitated the modulation and rewiring of existing locomotor and respiratory neuronal net-works.A major goal has been to resolve how these essential motor circuits are constructed during development,and to determine how they evolved and diversified.Comparisons of transcription factor profiles among diverse bilaterian species suggest deep conservation in the intrinsic signaling pathways controlling early nervous system patterning. Perhaps the most dramatic example is seen in the development of the visual system.Studies in mice andflies have demon-strated that key aspects of early eye development are controlled by a relatively small number of conserved fate determinants (Gehring,2014).For example,the transcription factor Pax6/ eyeless has a central role in the development of photodetection systems in both vertebrates and insects,and misexpression of mouse Pax6can generate ectopic eyes in imaginal discs of Drosophila embryos(Halder et al.,1995).More recent studies indicated that a large number of transcription factors involved in early patterning along the dorsoventral(DV)and rostrocaudal axes are conserved in both vertebrates and invertebrates(Denes et al.,2007;Lowe et al.,2003),implying that the nervous system of the common ancestor to all bilaterians was already quite so-phisticated(De Robertis and Sasai,1996).Given the remarkable conservation in the expression of key patterning genes,how did nervous systems evolve to generate new motor behaviors within various animal lineages?In this re-view,we discuss how alterations in developmental pathways enabled nervous systems to construct,and in some cases deconstruct,motor circuits that govern genetically predeter-mined locomotor behaviors.Because the link between neuronal identity and circuit connectivity has been closely examined in the spinal cord,we focus on the circuits governing the development of vertebrate motor systems,and describe how early intrinsic patterning systems impact circuit assembly and function.We discuss evidence that small changes in transcription factor activ-ity can act as a major driving force for evolutionary modification of circuit architectures.Also,we argue that,within the spinal cord,aflexible system involving modulation of rostrocaudal po-sitional information,acting in the context of a relatively uniform DV patterning system,can act to modify neuronal organization and connectivity within circuits governing a specific locomotor output.Ancestral Origins of Neural Induction and Early PatterningDuring the earliest phases of neural development,regions of ectoderm are allocated to acquire neuronal characteristics. Naive neural ectoderm subsequently acquires regional identities that prefigure the organization of motor circuits in the adult.On the surface,there appears to be fundamental differences in how nervous systems develop in distantly related species.Sub-sequent to neural induction,the majority of neurons in Drosophila are specified in lineages that are governed through temporal specification codes,and a single progenitor can give rise to multiple neuronal classes(Kohwi and Doe,2013).In contrast, patterning in the vertebrate neural tube is driven by extrinsic morphogen-based signaling,and progenitors typically giverise408Developmental Cell32,February23,2015ª2015Elsevier Inc.to only a few classes of neurons(Jessell,2000).Despite these significant differences,many species appear to use a common set of intrinsic determinants during early neural patterning.In this section,we compare and contrast the mechanisms of neural induction and global patterning within the two major superphyla of bilaterians,protostomes(which includes arthropods and annelids)and deuterostomes(which includes chordates,hemi-chordates,and echinoderms)(Figure1A).Neural Induction and DV Patterning in BilateriansThe formation of bilaterian nervous systems is initiated through neural induction,a process where the neural plate is specified within a restricted region of ectoderm.In most species,neural in-duction involves bone morphogenetic protein(Bmp)signaling along the DV axis(De Robertis,2008).Bmp signaling suppresses neural differentiation,the default fate of ectodermal cells,and promotes epidermal differentiation.In vertebrates,Bmp antago-nists(noggin,chordin,and follistatin)are secreted from the dor-sal organizer,thereby differentiating ectodermal cells into neural tissue.Subsequently,gradients of dorsal Bmps,in conjunction with ventral sonic hedgehog(Shh)signaling,establish subdivi-sions of progenitor domains along the DV axis of the neural tube in chordates(Jessell,2000).Although there are significant morphological differences among bilaterian nervous systems,Bmp signaling plays a con-served role in both protostomes and deuterostomes(Figures 1A and1B).For example,the vertebrate Bmp antagonist Chordin acts similarly to its Drosophila homolog sog(short gastrulation) in promoting neuronal fate(Holley et al.,1995).The Drosophila Bmp homolog dpp can phenocopy Bmp4activity when ex-pressed in Xenopus.Early Bmp expression is inversely corre-lated with the position where the CNS develops in both proto-stomes and deuterostomes,although the relative position of where the nervous system forms is distinct in both phyla.In pro-tostomes the nerve cord forms ventrally,while in deuterostomes the nerve cord forms dorsally(Figure1A).This relationship suggested a DV inversion hypothesis,where the CNSs of all bilaterians have a common origin,and an inversion of the DV axis occurred during deuterostome evolution(Arendt and Nu¨-bler-Jung,1994;De Robertis and Sasai,1996).Further support for a common origin of bilaterian nervous sys-tems has emerged from studies of neural development in proto-stome annelids.These studies revealed that the transcriptional regulatory networks required for early DV patterning in the verte-brate nerve cord are present in protostomes(Denes et al.,2007). Like in other bilaterians Bmp signaling has a key role in annelid neural induction.Annelids also show a higher degree of similarity with vertebrates than Drosophila in the expression of neural patterning genes(Figure1B).For example,the ventral determi-nants Nkx2.2and Pax6are expressed in mutually exclusive do-mains in both vertebrates and annelids,but this pattern is not conserved infly(Kammermeier et al.,2001).In addition,like vertebrates,annelid MNs are generated from a ventral domain characterized by expression of the transcription factor Hb9, and these neurons are cholinergic.This contrasts with the em-bryonic CNS of Drosophila,where MNs are generated in multiple lineages and are typically glutamatergic.Repression of neural induction by Bmps appears to have been lost in hemichordates,although Bmp-Chordin signaling and or-thologs of DV target genes are expressed(Lowe et al.,2006).This phenomenon may be due to its unique nervous system or-ganization that consists of two nerve cords,one dorsal and one ventral,and a diffuse basiepidermal nerve net(Holland, 2003;Nomaksteinsky et al.,2009).A possible explanation pro-vided by Arendt and colleagues is that hemichordates,such as acorn worms,might have modified their trunk neuroarchitecture due to the evolutionary changes in locomotor behaviors(Denes et al.,2007).Furthermore,a recent study provided additional ev-idence for conserved DV patterning cues in hemichordates.The hedgehog receptor patched is expressed ventrally in the collar nerve cord,while hedgehog is expressed in the endoderm of the buccal tube and the stomochord,similar to the relationship between ptc in the neural tube and Shh in thefloor plate and notochord of vertebrates(Miyamoto and Wada,2013). Conservation of Rostrocaudal Patterning Cues in BilateriansSoon after neural induction in vertebrates,cells from the neural plate acquire rostrocaudal positional identities and segregate into four major regions:the forebrain,midbrain,hindbrain,and spinal cord.The anterior neural plate has three primary signaling centers that produce morphogens involved in rostrocaudal patterning:(1)the anterior neural ridge(ANR),(2)zona limitans in-trathalamica(ZLI),and(3)isthmic organizer(IsO).These neuro-ectodermal signaling centers were thought to have originated in the vertebrate CNS since they are either absent or divergent in other chordates(Bertrand et al.,2011;Holland et al.,2000; Imai et al.,2009;Irimia et al.,2010;Shimeld,1999;Takatori et al.,2002).Recently,Lowe and colleagues provided evidence that inductive centers homologous to the ANR,ZLI,and IsO are present in hemichordates,suggesting that they are ancient patterning systems that were present in early deuterostomes (Pani et al.,2012).Additionally,extensive analysis from Kirschner and colleagues revealed that the hemichordate nervous sys-tem shows remarkable conservation in rostrocaudal patterning (Lowe et al.,2003).While there are some differences in the ros-trocaudal expression domains within the22orthologs of chor-date neural patterning genes that were tested,the relative expression domains are very similar to vertebrates(Figure1C).Although the corresponding extrinsic signaling centers are absent from protostomes,early anteroposterior patterning has been reported in several species indicating that com-partmental-like boundaries existed in the common bilaterian ancestor(Figure1C).For example,recent studies revealed that the Drosophila brain has a tripartite ground plan similar to verte-brates and displays conserved expression of transcription factors that are key to the development of vertebrate nervous systems(otx2,gbx2,fezf,irx,pax2/5/8,and Hox)(Hirth et al., 2003;Irimia et al.,2010).Similarly,the segmental expression pattern of otx,gbx,and Hox genes in the protostome annelids parallels the pattern in Drosophila(Steinmetz et al.,2011).These results support the hypothesis that the nervous system of the common urbilaterian ancestor of all bilaterians had an organized CNS that was patterned by shared intrinsic signaling programs (De Robertis and Sasai,1996).Neuronal Class Specification,Guidance Systems,and Neuronal OrganizationIn vertebrates,early patterning systems act on neuronal pro-genitors to prefigure cells to express a set of cell identity Developmental Cell32,February23,2015ª2015Elsevier Inc.409Figure1.Neural Induction and Early Patterning in Bilateria(A)Traditional classification of bilateria.Bilaterians are a subgroup of eumetazoan animals characterized by a bilaterally symmetrical body plan and triploblastic development.Bilaterians are subdivided into protostomes(mouthfirst)and deuterostomes(mouth second).(Top)The CNS(in blue)forms ventrally in pro-tostomes and dorsally in deuterostomes.(Bottom)A simplified phylogenetic tree showing the evolutionary relationships among bilaterians and other metazoan phyla.(legend continued on next page)410Developmental Cell32,February23,2015ª2015Elsevier Inc.determinants at the time of cell-cycle exit.The pattern of tran-scription factor expression in newly born neurons generates a remarkable diversity in cell types,a defining feature of most an-imal nervous systems.How neuronal cell types are specified is a first step toward elucidating how neurons are interconnected to establish a specific circuit.Here we outline the mechanisms through which large classes of neurons are specified,and the strategies through which neuronal subtypes essential within mo-tor systems emerged in the vertebrate lineage.Recent evidence indicates that,in some cases,a transcription factor class present in multiple species can target the same genes that define the core physiological properties of a neuronal type.Cell Fate Specification and Neurotransmitter Identity Near the time of terminal differentiation,transcription factors act to define the core physiological properties of neurons as well as features that allow them to establish their initial connec-tivity patterns.The nervous systems of many species contain thousands of molecularly and anatomically distinct cell types, and it has historically been challenging to establish a unifying classification scheme(Masland,2004).For simplicity,we define the steps through which neurons acquire their identities as class and subtype specification programs.In vertebrates,neu-rons within a class typically derive from a single molecularly defined progenitor domain,use a common neurotransmission system,and form connections with similar types of neurons. Subtypes of neurons within a class are more loosely defined, but often express different sets of transcription factors, establish connections that are distinct from other subtypes, and can be morphologically distinct.In terms of evolutionary changes,neuronal classes are often present throughout animal species,whereas subtypes show the greatest evolutionary diversification.A defining characteristic of neurons within a single class is the expression of genes encoding elements of neurotransmitter systems,including proteins involved in neurotransmitter syn-thesis and release.Expression of neurotransmitter genes ap-pears to rely on the actions of transcription factors expressed in postmitotic cells,the identities of which have been resolved only in recent years.This question has been worked out in greatest clarity in C.elegans,where cohorts of genes involved in neurotransmission are controlled by a relatively small number of transcription factors acting on common cis-regulatory ele-ments(Hobert,2011).As these factors are capable of control-ling a large number of genes that act in the same synthetic pathway,they have been called terminal selectors.Terminal se-lectors are typically expressed throughout the life of an organ-ism,and their expression can be maintained through positive transcriptional autoregulation(Deneris and Hobert,2014). Many of the regulatory proteins defined in C.elegans are func-tionally conserved in vertebrates.For example the C.elegans ETS family transcription factor ast-1plays a critical role in regu-lating the battery of genes involved in dopamine synthesis (Flames and Hobert,2009).In vertebrate olfactory neurons, the ast-1homolog Etv-1directly controls the terminal synthetic enzyme required for dopamine synthesis,tyrosine hydroxylase. Similar conservation is observed in the regulation of glutama-tergic fates by Lim homeodomain(HD)factors(Serrano-Saiz et al.,2013).The regulatory factors that control neurotrans-mitter synthesis in C.elegans also are tied to programs that regulate other features of a neuronal class,such as expression of ion channels,cell adhesion molecules,and determinants of axonal and dendritic morphology(Kratsios et al.,2012; Serrano-Saiz et al.,2013).These observations indicate that terminal selectors act on common cis elements to establish and maintain the identity of a neuron throughout an animal’s lifespan.Similar to C.elegans,regulation of neurotransmitter identity in vertebrates is linked to gene networks governing multiple as-pects of neuronal identity and connectivity(Figure2A).The MNs of vertebrates use acetylcholine(Ach)as the primary neurotrans-mitter to activate muscle and other neurons.Cholinergic gene batteries are directly regulated through complexes formed be-tween the Lim HD proteins Isl1and Lhx3and their cofactor Lbd1(Cho et al.,2014;Lee et al.,2012).This complex also is required to regulate the gene encoding the transcription factor Hb9(Lee et al.,2008),a key determinant of multiple facets of MN subtype differentiation(Arber et al.,1999;Thaler et al., 1999).While vertebrates use Lim HD proteins to orchestrate Ach synthesis in MNs,C.elegans uses a distinct class of tran-scription factor,the COE family member unc-3(Kratsios et al., 2012).Nematodes do,however,use Lim HD factors to regulate Ach synthesis in interneuron subtypes(Zhang et al.,2014). Another layer of complexity is apparent when one considers how MNs activate muscles in different model organisms.While vertebrates and C.elegans MNs use the cholinergic system,em-bryonic MNs of Drosophila activate muscles using glutamate, although bothflies and mice require the same set of transcription factors(Hb9,Isl1,and Lhx3)for diversifying MNs into subtypes.(B)Conservation of gene expression patterns along the DV axis in protostomes(flies and annelids)and deuterostomes(hemichordates and vertebrates).In both protostomes and deuterostomes,expression of neural identity genes is patterned by Bmps along the DV axis of the nerve cord(Esteves et al.,2014).Ventral patterning cues are not portrayed here as they are not homologous in different species(e.g.,Dorsal inflies,Shh in vertebrates).As in vertebrates,cholinergic Hb9+ MNs derive from pax6+nk6+progenitors and directly innervate muscles in annelids(Denes et al.,2007).Inflies,there are MN populations(not depicted here)in addition to Hb9+MNs.Although Bmp-Chordin signaling is present in hemichordates,many DV-patterning genes are not expressed by the neuroectoderm(e.g., nk2.2in endoderm).The Mnx gene,which shares high homology with Hb9homeodomain,is expressed in the hemichordate ventral ectoderm,implicating possible conservation in MN specification(Lowe et al.,2006).Homologous genes are color coded.Schematics on the bottom represent cross-sections of the embryos.(C)Conservation of anteroposterior-patterning systems in bilaterians.Although protostomes do not have analogous neuroectodermal-signaling centers present in developing vertebrate brains,key genes determining their boundaries are conserved along the anteroposterior axis.The en gene is also expressed at par-asegmental boundaries in the epidermis offlies and annelids.In hemichordates,the expression of fezf(not shown here)is not adjacent to that of irx.Homologous genes are color coded for comparison.Pc,protocerebrum;dc,deutocerebrum;tc,tritocerebrum;seg,subesophageal ganglion;vnc,ventral nerve cord;pro, prostomium;peri,peristomium;tr,trunk(both in annelid and hemichordate);pr,proboscis;col,collar;tel,telencephalon;di,diencephalon;mb,midbrain;hb, hindbrain;sc,spinal parisons between species represented in(A and B)do not take into account gene expression differences and,therefore,do not represent a true cladistics analysis.Furthermore,this model does not fully take into account the development of animals with unsegmented nervous systems, such as in molluscs.(A)is modified from De Robertis(2008)and Philippe et al.(2011;(B)is modified from Denes et al.(2007)and Mizutani and Bier(2008).Developmental Cell32,February23,2015ª2015Elsevier Inc.411Protostome annelids also express class determinants similar to vertebrates,and their MNs are cholinergic (Denes et al.,2007).This observation supports the idea that the urbilaterian ancestorcontained MNs that were similar to those of modern vertebrates.Flies and nematodes therefore may have evolved distinct mech-anisms for controlling neurotransmitter systems inMNs.Figure 2.Motor Innervation Programs in Bilaterians(A)Conservation and divergence of MN cell fate specification programs in invertebrates and vertebrates,emphasizing known conserved transcription factors.Several key transcription factors involved in MN specification are not indicated.NA,not assessed.(B)Comparisons of MN organization and innervation patterns between mouse and zebrafish at trunk levels.Core MN determinants,Isl1/2,Hb9,and Lhx3,are expressed in different combinations in three distinct thoracic columns in mouse.Scg,sympathetic chain ganglia.Zebrafish embryos contain four classes of primary MNs as follows:vRoP (ventrally projecting rostral primary),dRoP (dorsally projecting RoP),MiP (medial primary),and CaP (caudal primary);they do not organize into tightly clustered columns (Menelaou and McLean,2012).They are classified by their specific innervation of axial muscles from dorsal to ventral.The stereotypic innervation patterns of each primary MN are depicted here.Although three Mnx proteins are detected within each primary MN subtype in zebrafish,Mnx proteints are only required in MiP MNs (Seredick et al.,2012).(C)MN organization and specification programs at limb/fin levels in mouse and zebrafish.In zebrafish,pectoral fin innervating MNs are considered to be sec-ondary due to their late development and ventrolateral position relative to primary MNs (Myers,1985).A GFP reporter under control of an Isl1enhancer indicates that Isl1+pectoral fin MNs selectively innervate abductor muscles (Uemura et al.,2005).Untested aspects of these models are shown in gray.412Developmental Cell 32,February 23,2015ª2015Elsevier Inc.Convergence of cell fate determinants and neurotransmitter systems is also apparent when comparing different neuronal classes that share the same neurotransmitter identity.In addition to spinal MNs,cholinergic neurons are present in specific neu-rons of the vertebrate forebrain.Interestingly,the logic of the transcription factor network regulating cholinergic gene batte-ries is very similar in both regions.In MNs,Lhx3and Isl1have key roles in regulation of cholinergic genes,while Lhx8and Isl1 serve similar roles in the forebrain(Cho et al.,2014;Lopes et al.,2012).Thus,in the context of neurotransmitter gene batte-ries,key targets can be regulated through highly conserved cis-regulatory elements.Evolutionary diversification of neurons using the same neurotransmitter system in principle could be achieved by utilization of multiple members of the same tran-scription factor family.Ancestry and Evolution of Genetic Programs for Muscle InnervationIn addition to neurotransmitter systems,a defining feature of neurons within a specific class is the types of cells with which they establish connections.Because of their central role in motor circuits,we emphasize the connectivity programs of MN sub-types.The MNs of most species are characterized by the exten-sion of axons outside the CNS,local connectivity with certain classes of interneurons and sensory neurons,as well as de-scending inputs from supraspinal areas.The basic program of peripheral connectivity with muscle is likely to be conserved across many bilaterian species,since determinants necessary for the selectivity of their peripheral projections are conserved in protostomes and deuterostomes.In mice andflies,ventrally projecting MNs can be defined by the expression of Hb9, Nkx6,and Lim HD proteins,with each class member also acting at later stages to define the peripheral connectivity of MN sub-types.A common feature of motor systems in many protostome and deuterostome species is the innervation of segmentally organized axial muscles by MNs.In tetrapods the selection of axial muscles is largely determined by the actions of Lim HD proteins and Hb9(Figure2B).Dorsal epaxial and ventral hypaxial muscles are innervated by motor columns that are defined by the expression of these factors.Hypaxial muscles, which include intercostal and abdominal muscles,are inner-vated by ventrally projecting MNs that express Isl1and Hb9, while dorsal epaxial muscles are innervated by MNs express-ing Lhx3and Hb9(Figure2B).Lhx3has a central role in differ-entiating dorsally from ventrally projecting MN subtypes,as misexpression of Lhx3can suppress all other MN subtype specification programs and force motor axons to select a dor-sal trajectory(Dasen et al.,2008;Sharma et al.,2000).In other species,the logic of the Lim code with respect to the periph-eral trajectories of motor axons is distinct.In zebrafish,there is no clear correlation between the selection of DV trajectories of primary MNs and the expression of specific Lim HD proteins (Figure2B),although MN subtypes can be distinguished based on differential expression of these factors(Appel et al.,1995). Similarly in Drosophila,the basic decision to project dorsally or ventrally involves a different class of transcription factors, where the Evx1homolog even-skipped is required in dorsally projecting MNs,with Lim HD factors and Hb9acting to define subtypes of ventrally projecting populations both in the embry-onic and adult nervous system(Lacin et al.,2014;Landgraf and Thor,2006).A significant evolutionary advancement in the vertebrate line-age was the generation of MN subtypes that enabled the articu-lation of muscles in the limb.However,it is largely unknown at what stage in vertebrate evolution the program for limb innerva-tion emerged.In vertebrates,limb innervating MNs are organized into the lateral motor column(LMC),and are defined by the expression of the transcription factor Foxp1and the retinoic acid synthetic enzyme Raldh2(Figure2C;Dasen and Jessell, 2009).Among Foxp1+limb MNs,those projecting to the dorsal limb compartment express Lhx1,while those projecting ventrally express Isl1(Dasen et al.,2008;Tsuchida et al.,1994).The establishment of this Lim HD code is essential for the peripheral connectivity of LMC axons.In the case of limb-innervating MNs, the effectors of these cell fate determinants have been well char-acterized and include members of the Eph/ephrin-signaling sys-tem,which are regulated by Lim HD proteins and determine the response of motor axons to ephrin signaling in the limb mesen-chyme(Kao et al.,2012).Analysis of limb-level MNs in other species suggests that some,but not all,aspects of appendage innervation programs are conserved among vertebrates(Figure2C).Representatives of each of the four main classes of tetrapods(birds,reptiles,am-phibians,and mammals)express similar profiles of transcription factors in LMC neurons(Jung et al.,2014).In zebrafish,the Lim HD code that defines the DV selection of motor axons appears to be conserved at the level of the pectoralfin(Uemura et al.,2005), and expression of Raldh2has been reported in pectoralfin-level MNs(Begemann et al.,2001).However,selective expression of Foxp1byfin-level MNs has not been reported,nor is there any direct evidence that rostrocaudal positional identity determinants(e.g.,Hox genes)have any role in MN subtype specification.Many arthropod species also bear appendages involved in walking,although it appears that their leg innervation program arose independently.The common ancestor to protostomes and deuterostomes is thought to have lacked appendages, and this limbless state was preserved in early chordates,sug-gesting that the Foxp1/Lim HD code emerged in the vertebrate lineage.As a consequence of the independent origins of limb innervation programs,many basic features of MN organization and connectivity have diverged between vertebrates and inver-tebrates.Evolution of MN Somatotopic OrganizationA highly varied feature of bilaterian motor systems is reflected in how MNs are organized.In tetrapods,MNs projecting to a com-mon target zone or specific muscle are clustered in longitudinally arrayed columnar and pool groups.This organization creates a somatotopic map within the spinal cord that links cell body posi-tion to the peripheral trajectory of motor axons.The clustering of MNs is present in all tetrapods that have been examined,as well as some species offish(Fetcho,1987;Jung et al.,2014).In Drosophila and C.elegans,as well as aquatic vertebrates such as zebrafish,MNs targeting specific muscles do not cluster into coherent columnar groups(Thor and Thomas,2002), although there is evidence that zebrafish MNs are dorsoventrally organized based on their activation at different locomotor speeds(Ampatzis et al.,2013).These observations raise the Developmental Cell32,February23,2015ª2015Elsevier Inc.413。

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