中性红染色液(Neutral Red,0.5%)

神经元轴突标志物Tau：Neuron Type of MAP; helps maintain structure of the axon----------------------------------------------------------------------------神经元树突标志物Drebrin、MAP、SAP102微管相关蛋白Microtubule-associated protein-2(MAP-2)：Neuron Dendrite-specific MAP; protein found specifically in dendritic branching of neuron 是组成神经元细胞骨架的重要组成成分，包括：MAP5、MAP1.2和MAP1(x)三种不同类型。

在神经系统发育、形成和再生过程的不同时期扮演着重要的角色。

其中MAP5为早期微观相关蛋白，在胚胎期和新生动物大脑中有较高表达，并随大脑的逐渐成熟而退化，对神经元突起的生长具有重要的引导作用。

MAP2包括三种亚型：MAP2a、MAP2b和MAP2c。

其中MAP2b和MAP2c出现较早。

随着年龄的增长MAP2被组织蛋白酶D所降解，在不同类型的神经元中表达量存在差异。

----------------------------------------------------------------------------------------------神经元早期标志物Tubulin、b-4tubulin ：Neuron Important structural protein for neuron; identifies differentiated neuron Nervous System微管蛋白为球形分子, 分为两种类型:a微管蛋白(a-tubulin)和β微管蛋白(β-tubulin), 这两种微管蛋白具有相似的三维结构, 能够紧密地结合成二聚体, 作为微管组装的亚基，能够聚合并且参与细胞分裂。

赫芬达尔 - 赫希曼指数为0.05赫芬达尔 - 赫希曼指数（Hirsch-index），简称h指数，是由物理学家赫希曼（J.E. Hirsch）于2005年提出的，用来评价一个学术研究者的学术产出量和学术影响力的指标。

具体而言，一个学者的h指数是指他的论文中至少被引用了h次的数量。

一个学者的h指数为20，意味着他至少有20篇论文被引用了至少20次。

同样，赫芬达尔 - 赫希曼指数为0.05意味着什么呢？1. 赫芬达尔 - 赫希曼指数为0.05的意义要理解赫芬达尔 - 赫希曼指数为0.05的意义，首先需要了解这个指数是如何计算的。

赫芬达尔- 赫希曼指数的数学表示是h，计算方法为：首先将研究者的所有论文按被引次数从高到低排列；然后找到最大的h使得至少有h篇论文被引用了至少h次。

当赫芬达尔 - 赫希曼指数为0.05时，意味着这位学者的论文中有一小部分被引用了相对较高的次数，但大部分论文被引用的次数较低。

这也说明该学者的学术成果较为分散，没有出现被广泛引用的高影响力的论文。

2. 赫芬达尔 - 赫希曼指数为0.05的学术影响力从赫芬达尔 - 赫希曼指数为0.05可以看出，这位学者的学术影响力并不算很高。

虽然有部分论文被引用了不少次，但大部分论文的影响力较低。

这可能意味着该学者的研究领域较为广泛，但专业领域内没有出现具有重大影响力的研究成果。

这个指数提醒我们，要提高学术影响力，需要在某一特定领域深耕，出现具有较高被引用次数的重要研究成果。

3. 如何提高赫芬达尔 - 赫希曼指数对于这位学者，要提高赫芬达尔 - 赫希曼指数，可以尝试以下几种方法：- 针对某一具体领域深入研究，提出有重大影响力的研究成果；- 发表高质量的综述性文章，能够对该领域的研究产生深远影响；- 多参与学术交流和合作，促进自己的研究成果被广泛传播和接受。

总结回顾通过对赫芬达尔 - 赫希曼指数为0.05的解析，我们对学术影响力的评价有了更深入的理解。

3'utr名词解释3' UTR是指转录本中的3'非翻译区（untranslated region）或非编码区，简称为3'UTR。

在转录过程中，转录酶从DNA模板合成RNA，其中包括编码区（coding region）和非编码区。

编码区包含了编码蛋白质所需的信息，而非编码区则包含了一些重要的调控元件。

3' UTR位于编码区之后，是转录本的末端区域。

这个区域通常包含了转录终止信号（transcription termination signal），用于标记RNA的终止点。

在3' UTR中还可以找到一些重要的调控序列，如poly(A)尾信号（polyadenylation signal）和启动元件（cis-regulatory elements）。

poly(A)尾信号是一段序列，用于标记RNA 的3'末端，并通过与细胞内的多聚腺苷酸聚合酶（poly(A) polymerase）互作，使RNA的3'末端添加一串腺嘌呤（Adenine）残基形成poly(A)尾。

而启动元件则用于调控转录过程中的启动和停止，包括转录因子结合位点和调节序列。

除了参与转录调控外，3' UTR还参与了转录本的稳定性和转运过程。

一些RNA结合蛋白质（RNA-binding proteins）可以通过与3' UTR中的特定序列结合，调控RNA的稳定性和转运。

此外，3' UTR中的一些序列还可以通过与microRNA结合，参与转录后基因表达的调控。

microRNA可以与3' UTR中的互补序列结合，形成RNA 复合物，从而抑制目标基因的翻译或降解目标RNA。

总之，3' UTR是转录本中的一个重要区域，通过包含转录终止信号、调控序列和与RNA结合蛋白及microRNA相互作用，参与了转录调控、RNA稳定性和转运以及基因表达的调控。

对于研究基因调控和理解基因功能，深入了解3' UTR的结构和功能具有重要意义。

NBER WORKING PAPER SERIESDAS (WASTED) KAPITAL:FIRM OWNERSHIP AND INVESTMENT EFFICIENCY IN CHINADavid DollarShang-Jin WeiWorking Paper 13103/papers/w13103NATIONAL BUREAU OF ECONOMIC RESEARCH1050 Massachusetts AvenueCambridge, MA 02138May 2007David Dollar, Country Director for China and Mongolia, World Bank; Shang-Jin Wei, Assistant Director and Chief of Trade and Investment Division, Research Department, International Monetary Fund and Research Associate and Director of the Working Group on the Chinese Economy at the NBER. The authors wish to thank Jahangir Aziz, Chong-en Bai, Marcos Chamon, Chang-Tai Hsieh, Cui Li, Anil Kashyap, Yingyi Qian, Raghu Rajan, and seminar/conference participants at the NBER and IMF, especially Francesco Givanzzi, Galina Hale, and Chang-Tai Hsieh for helpful comments, and Yuanyuan Chen, Chang Hong, Xuepeng Liu, and Eric von Uexkull for excellent research assistance. This paper represents the personal views of the authors, and not necessarily those of the World Bank, the IMF, the NBER, or any other organizations that the authors are affiliated with.© 2007 by David Dollar and Shang-Jin Wei. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.Das (Wasted) Kapital: Firm Ownership and Investment Efficiency in ChinaDavid Dollar and Shang-Jin WeiNBER Working Paper No. 13103May 2007JEL No. E22,F21,O1ABSTRACTBased on a survey that we designed and that covers a stratified random sample of 12,400 firms in 120 cities in China with firm-level accounting information for 2002-2004, this paper examines the presence of systematic distortions in capital allocation that result in uneven marginal returns to capital across firm ownership, regions, and sectors. It provides a systematic comparison of investment efficiency among wholly and partially state-owned, wholly and partially foreign-owned, and domestic privately owned firms, conditioning on their sector, location, and size characteristics. It finds that even after a quarter-of-century of reforms, state-owned firms still have significantly lower returns to capital, on average, than domestic private or foreign-owned firms. Similarly, certain regions and sectors have consistently lower returns to capital than other regions and sectors. By our calculation, if China succeeds in allocating its capital more efficiently, it could reduce its capital stock by 8 percent without sacrificing its economic growth (and hence could raise its household consumption and deliver a faster improvement to its citizens' living standard).David DollarThe World Bank1818 H St., NWWashington, DC 20433ddollar@Shang-Jin WeiInternational Monetary FundRoom 10-70019th Street, NWWashington, DC 20433and NBERswei@I. I NTRODUCTIONThe breakneck growth rate of the Chinese economy is in large part driven by capital accumulation (and exports). The country’s investment to GDP ratio at 40 percent in 2005 (even after the denominator was revised up by 16.8 percent by the government) is high compared with the world average, and even higher than most other East Asian countries which are also known for relying on capital accumulation for their growth. How efficient is the Chinese investment? Is it systematically related to its unfinished reforms in which state-owned firms continue to suck in a sizable chunk of new investment? The purpose of the paper is to assess the efficiency of capital allocation in China, including whether the country has succeeded in removing the bias in favor of state-owned firms after nearly three decades of economic reforms.We do so by using data from a firm survey that we carried out. One problem of usual official firm surveys is that ownership classification tends to rely on firm registration. Yet, many firms’ ownership may have evolved faster than what is recorded on the registration. We designed a survey of firms in China in early 2005 and carried it out during July-November, 2005. It covered 12,400 firms in 120 cities located all across China. We asked the firms to report actual breakdown of ownership (private, state, etc), and found that about 15 percent of the firms in the sample (169 out of 1122) that were still registered as state-owned had already become fully privately owned according to the actual breakdown of ownership. This suggests that it is important to reclassify ownership based on actual ownership information rather than the firm label at the time of its registration.Our paper is related to the literature on the role of financial sector in China’s growth. Allen, Qian and Qian (2005) suggest that the high rates of GDP growth must imply that the informal financial sector has sufficiently made up for the shortcomings of the formal financial system dominated by state-owned banks. Boyreau-Debray and Wei (2005), on the hand, provide evidence that capital mobility is low across Chinese regions, and households’ ability to engage in consumption risk sharing is also low in the 1990s. Hsieh and Klenow (2006) provide evidence of unequal returns to capital across firms within the same sector in China and India, but do not investigate systematic allocative efficiency across ownership or locations. Bai, Hsieh, and Qian (2006) provided estimates of returns to capital using aggregate data. Dobson and Kashyap (2007) discussed the problems associated with China’s gradualist strategy in reforming its banks.As a preview of the main findings, we will report strong evidence that state-owned firms have lower (marginal and average) returns to capital than either domestic private or foreign firms. In addition, there is also systematic dispersion in the returns to capital across locations and sectors. Based on these econometric estimates, we calculate that China could drastically reduce its investment-to-GDP ratio and raise its consumption without sacrificing its growth rate by improving the returns to capital on the stock of capital currently employed by state-owned firms.The rest of the paper is organized as follows. Section 2 describes a simple model that helps to interpret the subsequent econometric estimates. Section 3 is the meat of the empiricalanalysis. It starts by describing the survey from which we extract the data for the analysis,and then provides a sequence of estimations and analyses. Section 4 concludes.II. C ONCEPTUAL F RAMEWORKIn this section, we use a simple model to generate a prediction on the relationship betweenobserved returns to capital (or labor), and distortions on capital, labor, and output. It alsomotivates the econometric specifications that we will employ in the subsequent analysis.Firm’s ProblemConsider a representative firm j in sector s that is a price-taker in both output and inputmarkets. Let πj, y j, K j and L j be firm j’s profit, output, capital usage, and labor usagerespectively. Firm j aims to maximize its profit:πj = p j Y j - r j K j - w j L j (1)Maxwhere p j, r j, and w j denote the output price, gross interest (rental cost of capital), and wagerate faced by firm j, respectively. The firm subscript is used to stress the point that distortionsin the output and factor market could be firm specific (or at least ownership specific) andmake the firm’s effective output price and input costs deviate from the market prices. Wesuppress sector subscript for simplicity. Specifically, letp j = p (1-d j Y) (2) r j = r (1+d j K) (3) w j = w (1+d j L) (4) Where p, r, and w are the output price, rental cost of capital and wage rate common to allfirms in the same sector and location. d j Y summarizes all output distortions the firm faces,expressed in the form of a tax that it proportion to its output. d j K summarizes all distortionson the cost of capital. For example, if private firms face systematic discrimination by localbanks, or face greater hurdle in getting listed in local stock markets, that could be representedby a high (and positive) d j K for them. As another example, if state-owned firms receivesubsidized credit, then their d j K would be negative. d j L represents all distortions on the cost oflabor. For example, if a firm is not allowed to freely dismiss workers, then its d j L would behigh.On the production function side, we assume that all differences across firms in the samesector occur at the TFP level only:Y j = A j f(K j , L j) (5) Where A j represents firm-specific total factor productivity. For simplicity, we assume f(., .)takes a Cobb-Douglas functional form:f(K j , L j) = K jα L j1-α(6) Where α denotes the capital share in output and is the same for all firms in the same industry.The first order conditions of the profit maximization problem yield the familiar conditionsthat the marginal revenue product of capital (MRPK) and marginal revenue product of labor (MRPL) should be equal to (firm-specific) interest rate and wage rate:MRPK j≡ p j A j f’K(K j , L j) = r j (7)MRPL j≡ p j A j f’L(K j , L j) = w j (8)By the virtue of the Cobb-Douglas production function, marginal revenue products of capital (MRPK) and labor (MRPL) are also proportional to their average revenue product counterparts:ARPK j ≡ p j Y j /K j = (1/α) MRPK j (9)ARPL j ≡ p j Y j /L j = [1/(1-α)] MRPL j (10) Researcher’s ProblemAs not all distortions faced by the firm are observable by an economic researcher, we cannot measure average and marginal revenue products directly. Instead, our observed averagerevenue product of capital, denoted by ARPK j o, is given by,ARPK j o≡ pY j /K j(11) Making use of (2), (3), (7), and (9), together with (11), we haveARPK j o = p j Y j /[(1-d j Y)K j] = ARPK j /(1-d j Y) = [r (1+d j K)] / [α (1-d j Y)] (12)A log approximation of (12) gives a convenient linear expression:ARPK j o≈ ln(r/α) + d j K + d j Y (13)lnThis indicates that the deviation of log observed average revenue product of capital from the common component in any sector, ln(r/α), reflects a combination of firm-specific distortionson capital cost and output.The relationship between the observed average revenue product of labor and the distortionscan be derived similarly:ARPL j o≡ pY j /L j = ARPL j /(1-d j Y) = [w (1+d j L)] / [(1-α) (1-d j Y)] (14) andlnARPL j o≈ ln[w/(1-α)] + d j L + d j Y (15)The dispersion of the log observed average revenue product of labor across firms within asector reflects a dispersion in the combined labor and output distortions. From equations (13)and (15), it is clear that output distortion affects both ARPK j o and ARPL j o. On the otherhand, capital (labor) distortion only affects ARPK j o (ARPL j o).So far, we have assumed that the firm is a price-taker in both the output and input markets.Suppose we let the firm produce a differentiated product, and face a downward-slopingdemand curve as described byY j d = Y s {p j /[(1-d j Y)P s}-σ(16)where Y s and P s are the aggregated demand for output in sector s and the aggregated priceindex for sector s, respectively, and σ is the elasticity of substitution between differentvarieties in sector s2. As a reminder, all firm-specific variables also can have a sector ssubscript but omitted for simplicity.Since the firm’s profit equation is no longer homogeneous of degree one in capital and labor,the optimal levels of capital and labor can be worked out. However, for our purpose, we notethat there are still relationship similar to equations (13) and (15) between ARPK j o or ARPL j oand the various distortions. The only changes are the two constant terms. More precisely,with a differentiated product framework, we would haveARPK j o≈ ln (r/α) + 1/σ + d j K + d j Y (13)’lnandlnARPL j o≈ ln[w/(1-α)] + 1/σ + d j L + d j Y (15)’Econometric SpecificationsWhen we turn to the data, we are especially interested in finding out how the output, capitaland labor distortions vary by firm ownership types, conditioning on sector and locationcharacteristics of the firms. We will classify all firms into several ownership types, and createa set of dummies for them. In the subsequent empirical investigation, we will implement thefollowing panel regressions (for which time-subscripts are added where appropriate):ARPK j,t o = ∑βi ownership i,j + ∑ year-dummies + ∑ sector-dummiesln(17)+ ∑ location -dummies + other controls + error j,t2 See Hsieh and Klenow (2006) for a discussion.For a given firm j, at most one ownership dummy would take the value of one, and all otherswould take the value of zero. In the case of a domestic private firm (the benchmark case), allseven ownership dummies take the value of zero. With this specification, the coefficient βishould be interpreted as measuring the capital and output distortions for ownership type irelative to those for domestic private firms, holding sector, location, year, and other firmcharacteristics constant. For example, if wholly state owned firms receive subsidized loansbut private firms do not, or if private firms face more hurdles in obtaining a bank loan thanstate firms, or a combination of the two, then the βi coefficient for wholly state ownershipshould take a negative value in the econometric estimation.We implement a comparable specification for the observed average revenue product of labor:lnARPL j,t o = ∑γi ownership i,j + ∑ year-dummies + ∑ sector-dummies(18)+ ∑ location -dummies + other controls + error j,tIII. D ATAThe survey was conducted during July-November, 2005. It covers 12,400 firms in 120 cities,located in all provinces, autonomous regions, and directly administrated cities, with theexception of Tibet. In each city, a random sample of firms stratified along sector and size(sales) was chosen. The local sample size was 200 firms each in Beijing, Chongqin,Shanghai, and Tianjin (four “super cities” or central government directly administratedcities), and 100 firms each in the rest of cities.We make use of two parts of the survey. The first is three-year (2002-2004) accounting dataon sales, material, capital and labor, filled out by chief account and head of human resources.The second part is information on the general business environment faced by the firm filledout by the chief executive of the firm. The survey was pilot tested by World Bank staff withfirms in Beijing before it was rolled out nationwide. In September and November 2005, wealso visited some of the data points in our sample—three firms in the north and three more inthe south, interviewing the chief executive officers and the chief financial offers of thesefirms. At each of the firms, we went through a selection of the survey questions, and checkedif the respondents understood the questions in the way we intended. In the process, wediscovered that some firms made careless mistakes in recording their information for somesurvey questions, though a majority of the questions appear to be correctly answered. Thissuggests the usefulness of applying some filters to exclude possible outliers in the subsequentestimation.Definitions of OwnershipAs we will investigate possible allocative inefficiency across firm ownership, especiallypossible preferential access to financing by state firms and policy-induced liquidity constraintfaced by private firms, we need to have a reliable way to define firm ownership. Onecomplication is that, due to rapid changes in the economy, there can be serious mis-matchesbetween firms’ actual and notional (registered) ownership. Our survey asks for firmownership with two different questions. First, it asks (in the section to be filled out by firm chief executives) the ownership type according to the current firm registration form. Second, it asks the firm (in the section to be filled out by chief financial officers and heads of human resources) to break down ownership shares by owners’ types (state, collective, legal person, private individual, and foreign investors).It is clear from the responses that the actual ownership does not always correspond to the ownership type on a firm’s business registration. For example, 169 firms that are registered as state-owned firms (out of a total of 1122) and 208 firms that are registered as collectives (out of 869) are already wholly owned by domestic private capital by the time the survey took place. For our analysis, we classify all firms into eight mutually exclusive ownership types based on the actual ownership information. The ownership types are defined in the following way:(a) Wholly state-owned if state share = 100 percent;(b) Majority state-owned if 50 percent ≤ state share < 100 percent;(c) Minority state-owned 0 < state share < 50 percent;(d) Wholly foreign-owned if foreign share = 100 percent;(e) Majority foreign-owned if 50 percent ≤ foreign share < 100 percent (and no stateshares);(f) Minority foreign-owned if 0 < foreign share < 50 percent (and no state shares);(g) Collectively owned if registered as a collective, still with collective share > 50percent;(h) Domestic privately owned = all the rest.Note that our category of “domestic privately owned firms” is relatively broad, capturing not just de nova private firms, privatized formerly state or collectively owned firms. It also captures some of the so-called “round-tripping” foreign direct investment, namely firms that are registered as foreign invested firms (including those from Hong Kong, Macao and Taiwan) but that the chief financial officers know are actually owned by domestic private investors. In addition, some of the firms in this category could include state shares (but reported as legal person shares). The last possibility can reduce the estimated difference in returns to capital between partially state-owned and private firms.Out of the 12,400 firms in the survey, three are registered as majority privately-owned but are reported to have a state share in excess of 50 percent. Under the assumption that it is unlikely for the country to have nationalized formerly privately owned firms during this period, we choose to exclude them from our analysis.Variable DefinitionsThe key variables to be explained are the observed average returns to capital and labor (ARPK j o and ARPL j o). For each firm in a given year, we define value added, VA j,t, as VA j,t = value of output j,t – value of raw material j,t (19)Then, the observed average revenue product of capital is simply the ratio of value added to capital:ARPK j,t o = VA j,t / K j, t (20) Similarly, the observed average revenue product of labor is value added divided by total labor,ARPL j,t o = VA j,t / L j, t (21) Filtering Out Data Entry Errors and Extreme ValuesThe raw data may contain recording errors by the respondents at the firm level or data entry errors by the staff of local statistical bureaus that are not captured by their checks or those of the national bureau. In addition, missing values for certain variables (e.g., firm revenue) would render it impossible to compute the variables of interest. Therefore, we devise a number of filtering rules to minimize the influence of outliers and to exclude observations with missing key information.We filter out firm-years in which (a) either the firm revenue or the value of intermediate inputs is missing; (b) the annual growth rate of either the value of intermediate inputs, value added, or the ratio of value added to the value of intermediate inputs exceeds 500 percent in absolute value.For regressions involving ARPK j,t o, we further exclude observations for which (c) the annual growth rate of capital in absolute value exceeds 500 percent, and (d) measured ARPK j,t o exceeds 1,000 percent in absolute value. For regressions involving ARPL j,t o, we further exclude observations for which (e) the annual growth rate of labor in absolute value exceeds 500 percent, and (f) measured ARPL j,t o exceeds 600,000 yuans (about US$75,000) in absolute value. As a robustness check, we increase the threshold in (b), (c) and (e) from 500 percent to 1,000 percent, and the threshold in (d) from 1,000 percent to 10,000 percent. The changes do not change the qualitative results of the analysis.These rules are designed to filter out extreme outliers. The remaining sample could still contain recording errors. So when we turn to regressions, we will also employ an additional robustness check by trimming out certain percentage of the smallest and the largest values for each ownership type.IV. S TATISTICAL RESULTSWe start with some raw, or unconditional returns to capital across different ownership types. We then move to account for the influence of sectors and locations on the returns to capital using a regression framework.Different Sources of Financing Across OwnershipIt is commonly noted that private firms have a harder time than state-owned firms to obtain financing from local banks in China. An Enterprise Survey conducted by the International Finance Corporation, a part of the World Bank Group, supplies evidence consistent with this notion. The IFC survey measures the perceptions of business managers and other senior staff about the main obstacles faced by their company in a number of countries3. The China portion of the survey, conducted in 2002 and 2003, comprises a sample of 3948 registered businesses. Two questions are particularly useful for our purpose: one asks firms to report a breakdown of the sources of financing for their working capital, and the other asks for a breakdown of the sources of financing for investment.Table 2 lists the sources of financing for working capital as reported by firms of various ownership. While domestic private firms report to derive 22 percent of their working capital from Chinese banks, state-owned firms are 50 percent more likely to rely on local banks, deriving 36-38 percent of their working capital from them. In contrast, family and friends are an important source (8 percent) of working capital for private firms but not at all for state-owned firms.Table 3 tabulates the sources of financing for investment. The same basic patterns emerge. In particular, state-owned firms are much more likely to rely on domestic banks for financing than private firms (or foreign firms), though the magnitude of the difference is moderately smaller than for working capital. Private firms continue to rely on family and friends (8.7 percent) for investment financing while state-owned firms do not.The Chinese security regulatory agency also favors state-owned firms over private firms in its approval of initial public listings; this is reflected in the overwhelming share of listed companies that are majority state-owned. Therefore, it is reasonable to conclude that state-owned firms have relatively easy access to the formal financial system in China. Indeed, this is well known in the literature. However, how much difference in the cost of capital this actually translates into is not known. The rest of the paper aims to fill this void. Dispersion in Returns to Capital Across Firm Ownership: Summary StatisticsTable 4 reports the summary statistics on the ratio of value added (VA) to capital stock by firm ownership. The mean average revenue product of capital is 99 percent for wholly state-owned firms, and 151 percent for private firms. In other words, the average return to capital is more than 50 percentage points higher for private firms than for wholly-state owned firms. In fact, foreign-owned and domestic private owned firms have comparably high average returns to capital (148-158 percent). Interestingly, the average returns decline progressively from foreign or domestic private owned firms, to minority state-owned (133 percent), majority state-owned (124 percent), and wholly state-owned firms (99 percent). This suggests that state ownership is systematically associated with lower returns to capital. On3 More information on the survey methodology can be found at /Methodology.the other hand, collectively owned firms appear to have high returns to capital (172 percent), perhaps resulting from as severe discrimination in access to financing and other distortions in much the same way as domestic private firms.The average returns may appear high in absolute values for all types of ownership. This could be due to outliers in the sample (in addition to policy distortions to cost of capital and output). We consider two reduced samples that trim out additional possible outliers. Specifically, for each ownership type, we exclude the top and the bottom 5 percent (or 10 percent) of the firms in terms of the average returns. The resulting means for these two trimmed samples are reported in the next two columns in Table 4. The average returns do become lower for each ownership type as we trim out more extreme values. Interesting, the order of the returns by ownership is preserved, namely, wholly state-owned firms always have the lowest average return, followed by majority state-owned and minority state owned firms.Another reason for the high returns may result from under-valued capital stock. In particular, the value of capital stock on the firms’ book may not fully reflect (potentially higher) market value. This could make the ratio of VA/K artificially high. Of course, firms may not take enough depreciation on their capital stock, which could result in over-valued capital stock. If these measurement errors are not systematically related to ownership (though related to sector classification), then they should not affect the order the estimated returns to capital across ownership. Arguably, state-owned firms are more likely not to take enough depreciation (i.e., keeping some “dead” capital on the book). As a result, the true discrepancy in the returns to capital between state-owned and privately owned firms is likely to be even larger than reported in Table 3.Another way to look at “typical” returns by ownership that are less affected by extreme values is median return. By this measure, again, the same pattern of relative returns across ownership is exhibited. Specifically, wholly-state owned, majority state-owned, and minority state-owned firms have the three lowest median returns (57 percent, 71 percent, and 78 percent, respectively). Foreign-owned and domestic privately owned firms have returns, between 91-100 percent, or 20-40 percentage points higher than state-owned firms. The collectively owned firms are recorded to have the highest median returns.Regression Approach to Control for Sector, Year, and Size EffectsThe average returns to capital recorded in Table 4 do not take into account possible return differences across sectors, times or regions. For example, let us assume that state-owned firms do not have intrinsically lower returns. If private firms happen to be over-represented in higher-risk, higher-returns sectors, they would on average have higher returns than state firms. This speaks to the importance of controlling for sector-specific risks and other shocks. As another example, let us assume that the source of inefficiency lies in regional differences in returns to capital4. If state-owned firms happen to be over-represented in those regions4 Boyreau-Debray and Wei (2004) reported evidence of segmentation of regional capital markets in China.with more depressed returns, then we might incorrectly conclude that capital allocation is biased in favor of state-owned firms if we do not correct for the regional effects. In this sub-section, we employ a regression framework that explicitly decomposes return differentials into ownership, region, and sector/year components.We regress value added over capital (VA/K) on the seven ownership type dummies (with domestic private firms being the omitted benchmark type), industry—year fixed effects, and region fixed effects. The result is reported in the first column of Table 5. Even after accounting for year-specific sector shocks and location differences, the returns to capital are found to be statistically lower for state-owned firms than for domestic private firms, suggesting that private firms face greater capital and output distortions than state-owned firms. Wholly foreign-owned firms also exhibit lower returns than domestic private firms. On the other hand, collectively owned firms may face even greater capital and output distortions as they show higher returns than private firms.In addition to working with the full sample, we also trim out 5 percent (or 10 percent) of the extreme values on both ends for each ownership type. The new regression results with the trimmed samples are reported in Columns 2 and 3 of Table 5. The qualitative results are similar as before, except that the return to wholly foreign-owned firms is no longer lower than domestic private firms once we exclude 10 percent outliers on both ends. Taken together, these three regressions suggest that after accounting for region and sector shocks, wholly state owned and majority state-owned firms still have 45 percent and 22 percent lower returns, respectively, than domestic private and foreign firms. Collectively owned firms, on the other hand, continue to appear to face even more grave distortions.We also regress log of VA/K on the ownership type dummies, sector/year and region fixed effects. This specification corresponds to equation (13), allowing us to interpret the coefficients on the ownership dummies as reflecting relative capital and output distortions in percentage terms (tax equivalent). Parallel to the previous set of equations, we implement the regression on two trimmed samples as well as the whole sample. It turns out that the results are qualitatively similar to the earlier regression with un-logged dependent variables. Specifically, the combination of capital and output distortions is equivalent to giving wholly state-owned firms a subsidy of 54 percentage points relative to foreign and domestic private firms. Majority and minority state-owned firms are also found to face less distortions than private firms, which in tax equivalent terms, are on the order of 20 and 10 percentage points, respectively. We have also added a measure of firm size (total employment) to the regressions to see if the return to capital varies systematically with size (reported in Table 6). The answer turns out to be no.To summarize, the data strongly suggest that the ARPK is substantially lower for wholly and partially state-owned firms than for foreign and domestic private firms by as much as 11-54 percentage points. If all firms in the same industry have the same Cobb-Douglas production (but may differ in their levels of TFPs), then the marginal return to capital, or MRPK, (which is proportional to ARPK), is also substantially lower for state-owned firms than for foreign and domestic private firms.。

neutr前缀
Neutr前缀代表中立、无色的意思，常用在科学、技术等领域中。

在物理学中，neutr是“中性粒子”或“中子”，在语言学中，neutr语言（中性语言）是指没有语法性别特征的语言。

在化学中，neutr-pH 值是指在海洋或者林区等自然环境中水的 pH 值。

Neutr前缀的特点在于它所代表的词汇基本上都是中立的，不带有任何感情色彩。

它的纯中立性质使它在科学、技术、医学和其他领域发挥了十分重要的作用。

在化学中，neutr-pH值是水在不同环境下的酸碱度。

在分子结构和手性中，neutr立体化学可以去除分子中的手性、不对称和化学性质的影响。

在生物学中，neutr前缀也被广泛使用。

例如中性变异是指DNA序列的变异，但不影响基因的表达和功能，因此在进化中并不受选择的影响。

在医学中，neutr核磁共振成像技术（NMR）可以观察到没有放射性的活性物质，因此被作为一种无创性检测手段被广泛应用。

总之，neutr前缀在各个领域的应用都体现了中立、客观的特点，随着科技的发展，它的应用领域也越来越广泛。

中立化的元素给人们带来很大的帮助，在科学和技术研发中起到了重要的作用。

Scientia Horticulturae 150(2013)206–212Contents lists available at SciVerse ScienceDirectScientiaHorticulturaej o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /s c i h o r tiAn efficient cucumber (Cucumis sativus L.)protoplast isolation and transient expression systemHongyu Huang a ,b ,1,Zhenyu Wang a ,1,Jintao Cheng a ,Wenchao Zhao a ,Xin Li a ,Hongyun Wang a ,Zhenxian Zhang a ,Xiaolei Sui a ,∗a Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops,China Agricultural University,Beijing 100193,China bTianjin Kernel Cucumber Research Institute,Tianjin 300192,Chinaa r t i c l ei n f oArticle history:Received 18October 2012Accepted 14November 2012Keywords:Cucumber ProtoplastTransient expressionGreen fluorescent proteina b s t r a c tThe transient gene expression system using plant protoplasts has become widely used for high-throughput analysis and functional characterization of genes.In this work we investigated protoplast isolation and green fluorescent protein (GFP)transient transfection and their main affecting factors,such as mannitol concentration in enzymolysis solution,enzymolysis time,and polyethylene glycol (PEG)concentration and transfection time,on ‘xintaimici’cucumber.The results showed that when the enzyme solution had 1.5%cellulase R-10(w/v),0.4%macerozyme R-10(w/v),0.4M mannitol,20mM 2-morpholinoethanesulfonic acid,10mM CaCl 2,0.1%bovine serum albumin,and was at pH 5.8with an enzymolysis time of 8h,the protoplast yield was 6–7×106/g fresh weight.Viability was about 90%.GFP was used as the reporter gene to measure protoplast transformation efficiency.When the concentration of PEG4000was 20%and transfection time was 20or 30min,transformation efficiency was greater than 50%and the green fluorescent signal could be detected in the cytoplasm,chloroplasts,and plasma mem-brane.We show here an efficient PEG-mediated cucumber protoplast transient expression system using GFP reporter gene,laying a technical foundation for future research in cucumber molecular biology.©2012Elsevier B.V.All rights reserved.1.IntroductionGenetic transformation is an important technique for studying the molecular biology of plants and can be used to understand gene function and genetic improvement in plants.However,the relatively expensive and time-consuming process for stable gene expression in transgenic plants still limits the utilization of this approach for large-scale analyses of plant genes.Transient expres-sion technology is fast,simple,safe,and efficient while resulting in high expression levels comparable to long term stable expression systems (Chen et al.,2006).Accordingly,transient gene expression in a model system has become widely used for characteriza-tion of protein function,such as protein subcellular positioning and trafficking,protein–protein interaction,protein stability and degradation,as well as protein mon transient transfor-mation methods include biolistic bombardment,infiltration with Agrobacterium tumefaciens (agroinfiltration),and polyethylene gly-col (PEG)-mediated transformation of protoplasts.Although the method of microparticle bombardment can be used in a variety of plant species (Taylor and Fauquet,2002),most experiments∗Corresponding author.Fax:+861062734371.E-mail address:sui-office@ (X.Sui).1These authors contributed equally to this work.are done on the epidermis of onion (Allium cepa L.)scale leaves (Klein et al.,1987).Onion epidermis is easily removed and the large cells have excellent optical properties for in vivo microscopy.However,onion epidermal cells lack normally developed chloro-plasts,so it is challenging to use this method to transform many types of chloroplast-targeted proteins (Jaedicke et al.,2011).Agrobacterium -mediated transient expression has the advantages of simple operation and low price,but its transformation efficiency is variable and the types of plant materials that can be used are limited (Ueki et al.,2009).It is now over 50years since Cocking (1960)published the first paper describing a method for the isolation of plant proto-plasts.Protoplasts,which are osmotically fragile membrane-bound cells without cell walls,offer a versatile cell-based experimen-tal system.Macromolecules such as recombinant DNA plasmids can be delivered into protoplasts using a variety of different transfection techniques,e.g.,PEG-mediated,electroporation and microinjection.The transfected protoplasts are then used for fur-ther investigations.Therein,PEG-mediated protoplast transient expression has high transformation efficiency,so it is widely applied in plant molecular biology studies (Sheen,2001;Walter et al.,2004).The establishment of new and more economical,con-venient and sensitive reporter gene assays for ␤-glucuronidase (GUS),firefly luciferase (LUC)and later green fluorescent pro-tein (GFP)for plant cells has also facilitated the application of0304-4238/$–see front matter ©2012Elsevier B.V.All rights reserved./10.1016/j.scienta.2012.11.011H.Huang et al./Scientia Horticulturae150(2013)206–212207protoplast transient expression systems(Leffel et al.,1997;Sheen, 2001).Transient assay utilizing protoplasts has become a powerful tool for rapid gene functional analysis,and has been established in several plant species,including both dicotyledonous and mono-cotyledonous crops,such as Arabidopsis(Yoo et al.,2007;Wu et al., 2009),tobacco(Locatelli et al.,2003),maize(Sheen,2001)and rice (Chen et al.,2006;Zhang et al.,2011).Cucumber(Cucumis sativus L.)is an important vegetable and a model species for Cucurbitaceae plant.The sequencing of its genome(Huang et al.,2009)has laid the foundation for further study of cucumber molecular biology.However,transformation of cucumber has a low regeneration rate and its transgenic offsprings are unstable.These problems have been limiting the progress of research in thisfield(Punja et al.,1990).Although there were some early reports of free protoplasts obtained from cucumber cotyledons and true leaves(Orczyk and Malepszy,1985;Colijn-Hooymans et al.,1988;Kantharajah and Dodd,1990;Punja et al., 1990),these isolation methods were optimized for plant regen-eration from ter,Gradam et al.(1994)employed protoplast transient expression to dissect the functions of the malate synthase(MS)gene promoter in cucumber cell cultures. In this experiment,cucumber protoplasts were transfected with plasmid DNA containing MS promoter-GUS reporter gene via electroporation.Wieczorek and Sanfac¸on(1995)described an improved method for the generation and transfection of pro-toplasts from cucumber cotyledons.In this protocol,PEG and electroporation were compared for their effect on protoplast trans-fection with the GUS reporter gene.Greenfluorescent protein is increasingly being used in plant biotechnology research and applications.GFP is characterized by low molecular weight,stable structure,easy detection,and non-toxicity.GFP retainsfluorescence when fused to another pro-tein,which makes it an attractivefluorescent tag to monitor protein–protein interactions,protein trafficking and subcellular localization(Leffel et al.,1997;Cho et al.,2006;Ehlert et al., 2006).In our laboratory,transient transformation by microparti-cle bombardments and heterologous expression in chloroplast-free epidermis cells of onion were used to determine the subcellular location of the sucrose transport protein from cucumber(CsSUT4), when tagged with the reporter GFP(Hu et al.,2011).The results suggested that it was targeted to the plasma membrane in plants and may play an important role in the apoplasmic phloem unload-ing in developing cucumber fruits.Until now,however,there have been no reported studies of transient transformation using the pro-toplast system with GFP reporter in cucumber.In this study,using GFP as a reporter gene,we developed an efficient PEG-mediated cucumber protoplast transient expression system,laying a founda-tion for future research in cucumber molecular biology.The main affecting factors on the protoplast isolation and transient trans-fection,such as mannitol concentration in enzymolysis solution, enzymolysis time,PEG concentration and transfection time,were also investigated.2.Materials and methods2.1.Materials‘Xintaimici’cucumber(C.sativus L.)was used in this study. Full seeds were soaked in tap water at room temperature for 1–2h,peeled,disinfected with75%alcohol for30s,washed twice with sterile water,disinfected with3%sodium hypochlorite for 15–25min,washed4–5times with sterile water,and planted on MS media(3%sucrose,0.7%agar,pH5.8).The seeds were cultured at25±1◦C,under lighting of120␮mol m−2s−1with a cycle of16h/8h(light/darkness)for7–9d to obtain fully extended cotyledons,and for15–17d to obtain thefirst true leaf for protoplast isolation(Kantharajah and Dodd,1990;Wieczorek and Sanfac¸on,1995).The transient expression vector pUC-GFP (35S::GFP,size4.5kb)was kindly supplied by Dr.Junping Gao of the College of Agronomy and Biotechnology,China Agricultural University.Plasmid preparation was conducted with the plasmid extraction kit PL1401(Bomaide biotech Co.Ltd.,Beijing).2.2.Protoplast isolationProtoplast isolation was performed using the methods described by Guo et al.(2007),Yoo et al.(2007)and Guan et al. (2010),with some modifications.An enzyme solution was prepared containing1.5%(w/v)cellulase R-10,0.4%(w/v)macerozyme R-10,20mM2-morpholinoethanesulfonic acid(MES)and mannitol. To determine conditions for maximum protoplast yield,a manni-tol concentration gradient experiment(replicated three times)was conducted and varying concentrations of mannitol(0.2,0.4,0.6or 0.8M,with0.2M as control)were compared.The enzyme solution was placed in a water bath at55◦C for10min,cooled to room tem-perature,then bovine serum albumin[BSA,0.1%(w/v)]and CaCl2 (10mM)were added(pH adjusted to5.8),and the solution was sterilized using a0.45-␮mfilter,then stored for later use.Cotyle-dons or true leaves were cut intofine strip(∼1mm)with a blade along the direction vertical to the main vein.The strips were rapidly transferred to enzymolysis solution(0.3–0.4g/10ml),permeated in a vacuum and under weak light for30min,and then incu-bated in enzymolysis solution at25±1◦C in darkness with rotation (40–50r/min).To optimize the enzymolysis time,the tissues were digested for4,6,8,10or12h(with4h as control,replicated three times),respectively.After digestion,the enzymolysate was diluted with an equal volume of W5solution(2mM MES,154mM NaCl, 125mM CaCl2,5mM KCl,pH5.8)(Yoo et al.,2007)and mixed gently,thenfiltered through nylon membrane(200mesh).Thefil-trate was centrifuged at1000r/min for2min,the supernatant was discarded,and the protoplasts were washed one more time with W5.The supernatant was removed after centrifugation and the protoplasts were resuspended with W5solution at afinal con-centration of2×106protoplasts/ml(Yoo et al.,2007)for the next transient transfection.The purified protoplasts were diluted appropriately and counted with a hemacytometer under a microscope for protoplast yield statistics.Protoplast yield was calculated as follows:protoplast yield(protoplasts/g FW)=number of the protoplasts yielded in enzymolysis(protoplasts)/fresh weight of the material used in enzymolysis(g FW).Protoplast viability was detected withfluores-cein diacetate(FDA)dye(Larkin,1976).In solution,FDA is very weakfluorescent dye.In a living cell,enzymes called esterases in the cytosol cleave the two acetate molecules from a molecule of FDA,leaving highlyfluorescent Fluorescein.Under ultraviolet light,Fluorescein accumulated in viable protoplasts glows with a brilliant green hue.In this experiment,FDA stock solution was added to diluted protoplasts at afinal concentration of0.01%, and were then incubated in darkness for5min,washed twice with W5solution,then resuspended in WI solution(4mM MES, 0.5M mannitol,20mM KCl,pH5.8)(Yoo et al.,2007).Fluores-cence microscopy under ultraviolet light(Olympus B×51)was used to determine protoplast viability as follows:protoplast via-bility(%)=(fluorescent protoplast number in view/protoplast total number in view)×100%.2.3.PEG4000-Ca2+-mediated plasmid transfectionPEG4000-Ca2+transfection solutions were prepared by adding PEG4000(10%,20%,30%,40%and50%,w/v)in ddH2O contain-ing0.2M mannitol and100mM CaCl2.Isolated protoplasts were208H.Huang et al./Scientia Horticulturae 150(2013)206–212Fig.1.Effects of mannitol concentration (A)and enzymolysis time (B)on protoplast yield and protoplast viability from cotyledons of cucumber.Values represent means ±SD (n =3).The different letters indicate significant differences (P ≤0.05)according to the LSD test.FW:fresh weight.placed in an ice bath for 30min and precipitated by gravity.Super-natant was removed and the protoplasts were resuspended with an equal amount of MMG solution (4mM MES,0.4M mannitol,15mM MgCl 2,pH 5.8)(Yoo et al.,2007).A volume of 20␮l pUC-GFP plas-mid (1000ng/␮l)and 100␮l protoplasts (2×105protoplasts)were combined and mixed gently.An equal volume of a freshly prepared solution of PEG4000-Ca 2+(120␮l)was added and mixed by gentle inversion to obtain a 5%,10%,15%,20%or 25%PEG4000final con-centration (with 5%as control,replicated five times).To optimize the transfection time,the protoplasts were transfected for 5,10,20,30or 40min in the dark at room temperature (25±1◦C)(with 5min as control,replicated five times),respectively.The transfec-tion was stopped by diluting the mixture with 600␮l W5solution (Chen et al.,2006).The mixture was centrifuged at 1000r/min for 2min and the protoplasts were gently resuspended in 750␮l WI solution (Yoo et al.,2007).The transfected protoplasts were incubated at 25±1◦C while protected from light for 20–24h,centrifuged again at 1000r/min for 2min,then resuspended with an appropriate amount of WI solution.Fluorescence results were observed with blue light under fluorescence microscopy and the number of green fluores-cent protoplasts was used to calculate transformation efficiency:transformation efficiency (%)=(fluorescent protoplast number in view/total protoplast number in view)×100%.2.4.Statistical analysisExperimental data were statistically analyzed using analysis of variance (ANOVA)in SPSS software Version 14.0.Treatment means were separated by least significant difference (LSD)tests at P ≤0.05.3.Results and analysis3.1.Effects of mannitol concentration in enzymolysis solution and enzymolysis time on cotyledon protoplast isolationWhen mannitol concentration in the enzymolysis solution was varied over a gradient of 0.2,0.4,0.6and 0.8M,a significantly high yield of protoplasts was obtained at 0.4M (P ≤0.05),reach-ing 6–7×106protoplasts/g FW,with viability of 80–90%(Fig.1A).When a 0.6M and 0.8M concentration of mannitol was used,protoplast yield and viability tended to decrease significantly (Fig.1A).This indicated that the optimal concentration of mannitol for enzymolysis was 0.4M.The effects of enzymolysis time on protoplast yield and viabil-ity was determined at 4,6,8,10and 12h,respectively,shown as in Fig.1B.When enzymolysis time was 6h,viability was rela-tively high,reaching over 80%,but protoplast yield was very low and could not meet the requirements for subsequent experiments.When enzymolysis time was 8h,protoplast yield increased greatly,and protoplast viability stayed around 90%.With longer enzymoly-sis time,protoplast yield rose slowly,reaching the maximum yield at 12h.However,increasing enzymolysis time decreased proto-plast viability (Fig.1B)and increased protoplast debris (data not shown).The lowest viability was less than 70%at 12h.In summary,considering protoplast yield,protoplast viability,and impurities,the optimal enzymolysis time is between 8and 10h.Overall,cucumber cotyledon protoplast yield and viability were highest when mannitol concentration was 0.4M and enzymolysis time was 8h (Figs.1and 2).Additionally,the protoplasts were found with little debris (Fig.2).3.2.Effect of sampling position on protoplast yieldThe similar effects of mannitol concentration and enzymoly-sis time on protoplast isolation of true leaves were determined (data not shown).With the optimal mannitol concentration and enzymolysis time as determined above,protoplast yield from different enzymolysis materials was determined using 7–9d cotyledons and 15–17d first true leaves,respectively.The results showed that although protoplast yield from true leaves was a little lower (P >0.05)than from cotyledons,it still reached 4–5×106protoplasts/g FW (Fig.3).Therefore,cotyledons are the optimal enzymolysis material for protoplast preparation,but young true leaves can be used as the enzymolysis material if cotyledons are limited.3.3.Effect of PEG4000concentration and transfection time on transformation efficiencyIn this work,the transient expression vector pUC-GFP was used to study effects of PEG4000concentration and transfection time onH.Huang et al./Scientia Horticulturae150(2013)206–212209Fig.2.The detection of cucumber protoplast viability underfluorescence microscope(200×).(A)FDA dyed protoplast under the bright light;(B)FDA dyed protoplast under ultraviolet light.The protoplasts were isolated from cotyledons when mannitol concentration was0.4M and enzymolysis time was8h.More than90%of protoplasts wereviable,as determined byfluorescein accumulation in these protoplasts glowing with a brilliant greenhue.Fig.3.Effect of material source on protoplast yield.Values represent means±SD (n=3).The same letter above different bars indicates no significant difference (P>0.05)according to the LSD test.FW:fresh weight.cucumber protoplast transformation efficiency.The results showed that transformation efficiencyfirst increased,then declined,along with increased PEG4000concentration(5%,10%,15%,20%and25%, respectively)(Fig.4A).When PEG4000was at concentration of20%,transformation efficiency reached the maximum,approximately 57%.Subsequently,transformation efficiency reduced gradually. When PEG concentration was25%the transformation efficiency decreased to34%,and the ratio of abnormal protoplasts rose and protoplast debris increased(data not shown).For this reason,20% was chosen as the appropriate PEG4000concentration.Transfection time was varied at5,10,20,30and40min.The results showed that when transfection time was5min,the transfor-mation efficiency was40%(Fig.4B).As transfection time increased, transformation efficiency increased as well.Transfection efficiency reached its maximum value of57%at30min.However,when trans-fection time was increased to40min,transformation efficiency decreased significantly to33%.This indicated that optimal trans-fection time for high transformation efficiency was30min.Single-cell imaging of diversefluorescence marker proteins,e.g., GFP,fused to functional proteins have been extensively utilized to determine protein localization,protein–protein interactions and plant signaling pathway analyses.Our results showed that cucumber protoplast transformation efficiency was comparatively high when PEG4000concentration was20%and transfection time was20or30min with the transient expression vector pUC-GFP (Figs.4and5).The transfected protoplast in brightfield(Fig.5A and C)and chloroplast autofluorescence in darkfield(Fig.5D) could be observed.Moreover,after PEG-mediated transfection with the35S::GFP plasmid(pUC-GFP)and incubation for20–24h,the expression of a reporter gene GFP was clearly detected intheFig.4.Effects of PEG4000concentration(A)and transfection time(B)on protoplast transformation efficiency.Values represent means±SD(n=5).The different letters indicate significant differences(P≤0.05)according to the LSD test.210H.Huang et al./Scientia Horticulturae 150(2013)206–212Fig.5.Cucumber protoplast transfection with pUC-GFP plasmid mediated by PEG4000under fluorescence microscope.(A and C)The transfected protoplast under bright light;(D)chloroplast autofluorescence in dark field;(B and E)protoplasts expressing GFP driven by the constitutive 35S enhancer are shown in dark field under fluorescence microscope (A–B:100×;C–E:400×).cytoplasm,chloroplasts,and plasma membrane (Fig.5B and E),indicating effective transient transfection of the cucumber proto-plast.It is helpful to further research the molecular biology of the cucumber crop.4.DiscussionTransient expression is widely used to study protein subcellu-lar positioning,protein–protein interactions and protein activity in plant cellular biology and molecular biology.Until now,there have been reports of Arabidopsis (Damm et al.,1989;Yoo et al.,2007;Wu et al.,2009),tobacco (Locatelli et al.,2003),rice (Chen et al.,2006;Zhang et al.,2011)and strawberry (Nyman and Wallin,1992)plant protoplast transient expression systems.Yoo et al.(2007)described a protocol for a system of transient expression in Arabidopsis mesophyll protoplast (TEAMP).The protoplast isola-tion and PEG-calcium transfection of plasmid DNA took 6–8h,and the results can be obtained in 2–24h.Based on this method,Wu et al.(2009)developed a new procedure that they called the Tape-Arabidopsis Sandwich,which was a simpler and faster mesophyll protoplast isolation ing the green fluorescent reporter gene,two highly efficient transient protoplast systems in rice were established and were used for screening and characterizing genes involved in defence signaling pathways (Chen et al.,2006),or in studies of light/chloroplast-related processes (Zhang et al.,2011).In addition to showing high transformation efficiency,plant pro-toplasts also provided a powerful and versatile cell system for high-throughput dissection of plant signal transduction pathways (Sheen,2001).In general,establishment of an efficient transient expres-sion system requires both high-quality protoplasts and suitabletransformation means.Firstly,protoplast isolation is now rou-tine from a wide range of species.Factors affecting protoplast preparation mainly lie in enzymolysis material choice,enzymoly-sis solution’s osmotic pressure and enzymolysis time (Kantharajah and Dodd,1990;Davey et al.,2005).Young plant leaves are usually ideal materials for protoplast preparation.Mesophyll protoplasts freshly isolated from leaves have proven to be versatile systems for studying gene activity in several plant species,such as Arabidopsis,tobacco or maize.However,the isolation of mesophyll protoplasts from rice is difficult owing to its leaf structure and size.Accordingly,Chen et al.(2006)described a significantly improved method to isolate a large number of protoplasts from stem and sheath tissues of both young and mature rice plants.In addition,the selection of healthy leaves at the proper developmental stage is very important factor in protoplast experiment.The transfection efficiencies with the protoplasts from stressed leaves (e.g.,from drought,flooding,or extreme temperatures)were often lower than those from healthy leaves (Yoo et al.,2007).Thus,we used sterile cotyledons and true leaves of young cucumber seedlings grown under optimal condi-tions to prepare protoplasts,removing environmental effects from the material.Protoplasts are osmotically sensitive,as in a suspen-sion medium hypotonic to that of its protoplasm.Plasmolysis prior to enzymatic digestion of source tissues in enzyme solution reduces cytoplasmic damage.Addition of the osmotic pressure protective agent to the enzyme mixture was essential in maximizing proto-plast release from tissues and avoiding plasmarrhexis.The osmotic pressure protective agent can maintain the balance of interior and exterior osmotic pressures of the protoplasts to some extent to prevent the protoplasts from lysing.Those protective agents most commonly used are inorganic salts (KCl,NaCl,MgSO 4),or non-metabolizable sugars or sugar derivatives (mannitol,sucrose,H.Huang et al./Scientia Horticulturae150(2013)206–212211sorbitol),or combinations of these.Many studies suggest that the optimum concentration of the osmotic pressure protective agent depends on the species and cultivar(Yoo et al.,2007;Wu et al., 2009;Chen et al.,2006;Zhang et al.,2011).In the process of cucum-ber protoplast isolation,a concentration gradient of mannitol was performed to determine its optimum values(0.4M)when consid-ering protoplast yield,viability and amount of impurities(Fig.1A). Enzymolysis time is another important component to consider in addition to the choice of lytic enzymes.Enzymolysis time depends on the experimental goals,desirable responses and materials used, and it needs to be optimized empirically(Yoo et al.,2007).In addi-tion,to a certain degree,prolonging enzymolysis time has been shown to be helpful for releasing mesophyll protoplasts.Although protoplast yield from cotyledons increased with enzymolysis time, viability was declined(Fig.1B).In this report,under the optimum conditions,cucumber proto-plast yield can reach6–7×106protoplasts/g FW from cotyledons and4–5×106protoplasts/g FW from true leaves(Fig.3).This is slightly lower than Arabidopsis thaliana’s leaf protoplast yield (3×107protoplasts/g FW)(Wu et al.,2009),but higher than cucumber cotyledon protoplast yield(2–3×106protoplasts/g FW) using an isolation process with cellulose and pectase(Guo et al., 2003).Protoplast yield from true leaves was slightly lower than from cotyledons,but there was no significant difference between them,and true leaves were also used for transient expression as a suitable starting material.Although some attempts to isolate proto-plasts of cucumber were described about twenty years ago(Orczyk and Malepszy,1985;Colijn-Hooymans et al.,1988;Kantharajah and Dodd,1990;Punja et al.,1990),these isolation methods were optimized for protoplast culture and plant regeneration,with no strict requirement for protoplast purity.In our study,we obtained comparatively pure protoplasts with an improved method,laying a foundation for efficient protoplast transfection.Here,the PEG-mediated transfection procedure was applied to establish the protoplast transformation in cucumber.The trans-formation efficiency of the protoplast was measured by using GFP as a detecting marker.PEG is regarded as an effective proto-plast transfection agent.PEG interacts with protoplasts and allows target DNA to enter.Determining the optimal molecular weigh and concentration of PEG and incubation time with protoplasts is key to raising transformation efficiency.The molecular weight of PEG used in our cucumber transformation system was4000Da, with a series of different concentrations of the transfection solu-tion.The results showed that PEG4000concentration had a large impact on cucumber protoplast transformation efficiency(Fig.4A). As PEG concentrations increased,transformation efficiency rose significantly but impurities such as cell debris increased as well. However,work by Wieczorek and Sanfac¸on(1995)showed that PEG3250concentration(tested at40%and50%)had little or no effect on cucumber cotyledon protoplast transformation.This may be due to different PEG molecular weight or Ca2+concentrations in the buffers of the two experimental systems.Ca2+concentra-tion was100mM in our study while it was20mM in Wieczorek and Sanfacon’s research(1995).Furthermore,our results showed that when transfection time was5min,the transformation effi-ciency reached to40%(Fig.4B),indicating that PEG4000-mediated DNA transfection is a relatively rapid process.However,extended incubation with PEG,such as the transfection time of40min in this study,may possibly be harmful to protoplasts(Shillito et al., 1985).In summary,high transformation efficiency and the resulting GFP expression in this study was obtained through optimization of cucumber protoplast isolation,purification,and PEG4000-mediated transfection(Fig.5).This methodology,when combined with genetics,genomics and proteomics,will allow further research into the molecular breeding and biology of the cucumber.AcknowledgementsThis work was supported by Chinese National Natural Sci-ence Fund(30972004and31272169),and the Earmarked Fund for Modern Agro-industry Technology Research System in China (CARS-25-C-12).ReferencesChen,S.B.,Tao,L.Z.,Zeng,L.R.,Vega-Sanchez,M.,Umemura,K.J.,Wang,G.L., 2006.A highly efficient transient protoplast system for analyzing defence gene expression and protein–protein interactions in rice.Mol.Plant Pathol.7(5), 417–427.Cho,Y.H.,Yoo,S.D.,Sheen,J.,2006.Regulatory functions of nuclear hexokinase1 complex in glucose signalling.Cell127,579–589.Cocking,E.C.,1960.A method for the isolation of plant protoplasts and vacuoles.Nature187,927–929.Colijn-Hooymans, C.M.,Bouwer,R.,Dons,J.J.M.,1988.Plant regener-ation from cucumber protoplasts.Plant Cell an Cult.12, 147–150.Damm,B.,Schmidt,R.,Willimitzer,L.,1989.Efficient transformation of Arabidopsis thaliana using direct gene transfer to protoplasts.Mol.Gen.Genet.217,6–12. Davey,M.R.,Anthony,P.,Power,J.B.,Lowe,K.C.,2005.Plant protoplasts:status and biotechnological perspectives.Biotechnol.Adv.23,131–171.Ehlert,A.,Weltmeier,F.,Wang,X.,Mayer,C.S.,Smeekens,S.,Vicente-Carbajosa,J., Dröge-Laser,W.,2006.Two-hybrid protein–protein interaction analysis in Ara-bidopsis protoplasts:establishment of a heterodimerization map of group C and group S bZIP transcription factors.Plant J.46,890–900.Gradam,I.A.,Baker,C.J.,Leaver,C.J.,1994.Analysis of the cucumber malate synthase gene promoter by transient expression and gel retardation assays.Plant J.6(6), 893–902.Guan,Q.Z.,Guo,Y.H.,Wei,Y.X.,Meng,F.Z.,Zhang,Z.X.,2010.Regeneration of somatic hybrids of ginger via chemical protoplast fusion.Plant Cell an Cult.102, 279–284.Guo,D.Z.,Yan,Z.,Lai,Z.X.,Lin,Q.L.,Wang,J.F.,2003.Efficient culture and plant regen-eration from cotyledon protoplasts of‘Cui xiu’cucumber.Acta Hortic.Sinica30, 227–228(in Chinese with English abstract).Guo,Y.H.,Bai,J.H.,Zhang,Z.X.,2007.Plant regeneration from embryogenic suspension-derived protoplasts of ginger(Zingiber officinale Rosc.).Plant Cell an Cult.89,151–157.Hu,L.P.,Sun,H.H.,Li,R.F.,Zhang,L.Y.,Wang,S.H.,Sui,X.L.,Zhang,Z.X.,2011.Phloem unloading follows an extensive apoplasmic pathway in cucumber(Cucumis sativus L.)fruit from anthesis to marketable maturing stage.Plant.Cell Environ.34,1835–1848.Huang,S.W.,Li,R.Q.,Zhang,Z.H.,Li,L.,Gu,X.F.,et al.,2009.The genome of the cucumber,Cucumis sativus L.Nat.Genet.41,1275–1283.Jaedicke,K.,Rösler,J.,Gans,T.,Hughes,J.,2011.Bellis perennis:a useful tool for protein localization studies.Planta234,759–768.Kantharajah,A.S.,Dodd,W.A.,1990.Factors that influence the yield and viability of cucumber(Cucumis sativus L.)cotyledon protoplasts.Aust.J.Bot.38,169–175. Klein,T.M.,Wolf,E.D.,Wu,R.,Sanford,J.C.,1987.High-velocity microprojectiles for delivering nucleic acids into living cells.Nature327,70–73.Larkin,P.J.,1976.Purification and viability determinations of plant protoplasts.Planta128,213–216.Leffel,S.M.,Mabon,S.A.,Stewart Jr.,C.N.,1997.Applications of greenfluorescent protein in plants.BioTechniques23,912–918.Locatelli,F.,Vannini,C.,Magnani,E.,Coraggio,I.,Bracale,M.,2003.Efficiency of tran-sient transformation in tobacco protoplasts is independent of plasmid amount.Plant Cell Rep.21,865–871.Nyman,M.,Wallin, A.,1992.Transient gene expression in strawberry(Fra-garia×ananassa Duch.)protoplasts and the recovery of transgenic plants.Plant Cell Rep.11,105–108.Orczyk,W.,Malepszy,S.,1985.In vitro culture of Cucumis sativus L.V.Stabilizing effect of glycine on leaf protoplasts.Plant Cell Rep.4, 269–273.Punja,Z.K.,Tang,F.A.,Sarmento,G.G.,1990.Isolation,culture and plantlet regen-eration from cotyledon and mesophyll protoplasts of two pickling cucumber (Cucumis sativus L.)genotypes.Plant Cell Rep.9,61–64.Sheen,J.,2001.Signal transduction in maize and Arabidopsis mesophyll protoplasts.Plant Physiol.127,1466–1475.Shillito,R.D.,Saul,M.W.,Paszkowski,J.,Müller,M.,Potrykus,I.,1985.High efficiency direct gene transfer to plants.Nat.Biotechnol.3,1099–1103.Taylor,N.J.,Fauquet,C.M.,2002.Microparticle bombardment as a tool in plant sci-ence and agricultural biotechnology.DNA Cell Biol.21,963–977.Ueki,S.,Lacroix,B.,Krichevsky,A.,Lazarowitz,S.G.,Citovsky,V.,2009.Functional transient genetic transformation of Arabidopsis leaves by biolistic bombard-ment.Nat.Protoc.4,71–77.Walter,M.,Chaban,C.,Schütze,K.,Batistic,O.,Weckermann,K.,Näke,C.,Blazevic,D.,Grefen,C.,Schumacher,K.,Oecking,C.,Harter,K.,Kudla,J.,2004.Visualiza-tion of protein interactions in living plant cells using bimolecularfluorescence complementation.Plant J.40,428–438.。

quadriplex 四显性组合quadrivalent 四价的；四价体quadruplex 四显性组合quadruplex dna 四元dnaquartering 四分（法）quasidominance 准显性quasispecies 准种[由一种母序列和来自该序列的大量相关突变体所组成的病毒基因组]quasisymmetry 准对称quassin 苦木素quaternary 四级的；四元的；季quick stop mutation 快停突变[大肠杆菌中升温至42℃即停止复制的突变]quinacrine 喹吖因quinhydrone 醌氢醌quinidine 奎尼定[抗心律不齐药]quinochrome 醌色素quinoline 喹啉quinolizidine 喹嗪quinomycin 醌霉素quinone 醌quinoprotein 醌蛋白[以吡咯并喹啉醌为辅基]quinuclidinyl 奎宁环基rabbit hemorrhagic disease virus 兔出血病病毒[属杯状病毒科] rabbitpox virus 兔痘病毒rabies virus 狂犬病毒rabphilin rab亲和蛋白[rab蛋白是指ras相关gtp结合蛋白]raccoonpox virus 浣熊痘病毒racemase 消旋酶racemate 外消旋物racemic 外消旋的racemization 外消旋化raddicle 胚根radicin 根蛋白radioelectrophoresis 放射电泳radiograph 放射显影图，射线照相radiography 放射显影（法）radioimmunoassay 放射免疫测定，放射免疫分析radioimmunoelectrophoresis 放射免疫电泳radioimmunoimaging 放射免疫成像radioimmunology 放射免疫学radioimmunoprecipitation 放射免疫沉淀（法）radioiodinated 放射性碘化的radioiodination 放射性碘化radiolabeled 放射性标记的radiolabeling 放射性标记radioligand 放射性配体radiolysis 辐（射分）解（作用）radiometer 放射计，辐射计radionuclide 放射性核素radiopaque 不透射线的radioparent （可）透射线的radiophotoluminescence 放射光致发光radioprotectant 辐射防护剂radiosensitivity 辐射敏感性radiosensitization 辐射敏化radiosensitizer 辐射敏化剂radixin 根蛋白[可作用于肌动蛋白丝] radwaste 放射性废物raffinose 棉子糖ragweed 豚草raji cell raji细胞ramachandran map ramachandran图，拉氏图[指示蛋白质主链二面角允许值范围的图形]ranatensin 蛙（紧张）肽，豹蛙（紧张）肽rapamycin 纳巴霉素，雷帕霉素raphe 缝际；种脊rauwolscine 萝芙素reading frame 读框，阅读框架reagin 反应素reannealing 重退火reassociation 重缔合reassortment 重配rebound 回跳[用于神经系统]recognin 识别子，识别蛋白recombinant 重组子，重组体,重组的recombinase 重组酶recombulin [商]重组胰岛素[gibco公司商标]recon 重组子recoverin 恢复蛋白[见于脊椎动物视网膜的钙传感蛋白，可促进cgmp的重合成、钙通道的重开放及暗状态的恢复]red drop 红降red shift 红移reduced viscosity 比浓粘度regulon 调节子[受控于同一调节蛋白的多个操纵子]remnant 残迹[如用于描述分子进化]renin 肾素rennin 凝乳酶reovirus 呼肠（孤）病毒repeating dispenser 重复分液器[带有贮液装置并可连续反复多次放出液体的分液器]replicase 复制酶replicative eys 复制眼[长段非复制序列中的dna复制区]replicative recombination 复制重组[通过可动遗传因子从基因的一个位置复制到另一个位置]replicator 复制因子，复制基因replicon 复制子replisome 复制体[执行dna复制功能的多种蛋白质复合体]repolarization 复极化reporter 报道基因，报道分子reporter gene 报道基因，报告基因[处于另一基因下游并可反映转录及上游基因表达水平的基因]reporter molecule 报道分子[具有类似指示剂作用的分子]representation 表现度repression 阻抑，阻遏repressor 阻抑物，阻遏物，阻抑蛋白reptilia 爬行纲[节肢动物]resact 呼吸活化肽[一种海胆卵肽，可刺激精子的呼吸]reserpine 利血平resilin 节肢弹性蛋白resolvase 解离酶resorufin 试卤灵，9-羟基-3-异吩恶唑酮respirometer 呼吸计resting cell 静息细胞[具有生命代谢能力而处于停止分裂状态的细胞]restitope （依）托位[抗原呈递中，t细胞受体上与ⅱ类组织相容性复合体分子相互作用的部位]restorer 恢复系restorpin 网状内皮（作用）素restricted transduction 局限转导[在细菌细胞生活周期中易于接受外源dna的某种暂时状态下出现]retardin 阻滞素，延缓素reticulin 网硬蛋白；网硬素reticulocyte 网织红细胞reticuloendothelial system 网状内皮系统retina 视网膜retinal 视黄醛；视网膜的retinaldehyde 视黄醛retinene 视黄醛retinoblastoma 成视网膜细胞瘤的，rb的retinol 视黄醇retriever vector 挽回载体[携有野生型基因侧翼序列并可用于克隆相应突变基因的穿梭载体]retroegulation 反向调节[下游序列对翻译的调节]retroelement 逆转录因子retronphage 逆转录子噬菌体retroposon 逆转录子retropseudogene 逆转录假基因[关于假基因起源的一种假说]retrosynthesis 逆合成[从相反方向分析合成路线]retrotransposition 逆转录转座（作用）retrotransposon 逆转录转座子[转座过程中出现逆转录，如酵母tyl和果蝇copia]retrovir [商]叠氮胸苷retroviral vector 逆转录病毒载体retrovirus 逆转录病毒，反（转）录病毒reuptake 重摄取revaccination 疫苗再接种reverberation 回荡[用于神经系统]reverse band r带，（相）反带[与q带相反的带]reverse biochemistry 反向生物化学[通过克隆化基因的表达产物反过来研究体内蛋白质的生化特性]reversion 回复突变revertant 回复体revistin 制逆转录酶素rf value rf值，比移值rhabdovirus 弹状病毒rhamnose 鼠李糖rheogram 流变图rheology 流变学rhinovirus 鼻病毒rhizobia 根瘤菌rhizocaline 成根素rhizome 根（状）茎rhizomorph 菌索[见于真菌]rhizopin 根霉促进素rhizoplast 根丝体rhizopterin 根霉蝶呤rhizosphere 根际rhizospheric 根际的rhodamine 罗丹明rhodanese 硫氰酸酶rhodomorphin 红形素rhodophyta 红藻门rhodoplast 藻红体rhodopseudomonacin 红假单胞菌素rhodopsin 视紫红质，视紫质，紫红质，紫膜质rhodospirillum 红螺菌属rhodotoxin 玫红毒素，杜鹃花毒素ri plasmid ri质粒，毛根诱导质粒ribavirin 三氮唑核苷，病毒唑riboflavin 核黄素ribohomopolymer 核糖核酸同聚体ribolose 核酮糖ribonuclease 核糖核酸酶，rna酶ribonucleoprotein 核糖核蛋白ribophorin 核糖体结合（糖）蛋白，核糖体受体蛋白[见于糙面内质网]ribopolymer 核糖核酸多聚体ribose 核糖ribosomal 核糖体的ribosome 核糖体ribostamycin 核糖霉素ribosyl 核糖基ribosylation 核糖基化（作用）ribovirin 病毒唑ribozyme 核酶[可切割特异性rna序列的rna分子]ricin 蓖麻毒蛋白rickettsia 立克次氏体rickettsia burneti 伯氏q热立克次氏体rickettsia typhi 斑疹伤寒立克次氏体rider 游码rifampicin 利福平rifampin 利福平rifamycin 利福霉素rimocidin 龟裂杀菌素ristocetin 瑞斯托菌素ristomycin 瑞斯托霉素rna editing rna编辑[在初级转录物上增删或取代某些核苷酸而改变遗传信息]rna ladder rna梯[如大小不同的rna分子量标准参照物的电泳谱]rna transport rna转运[主要指rna从细胞核转运到细胞质]rnasin [商]rna酶蛋白质抑制剂[promega公司商标]robertsonian translocation 罗伯逊易位[非同源染色体端着丝粒之间融合，或两个近端着丝粒染色体相互易位而形成一个染色体] rod 杆菌；（视）杆细胞rosamicin 蔷薇霉素rosette （玫瑰）花结rotamase 旋转异构酶rotamer 旋转异构体rotavirus 轮状病毒rotenoid 鱼藤酮（类）生物碱rotenono 鱼藤酮rous sarcoma virus rous肉瘤病毒rubella virus 风疹病毒rubidomycin 红比霉素rubisco 核酮糖二磷酸羧化酶-加氧酶rubredoxin 玉红氧还蛋白[一种不含血红素的铁蛋白]ruffling [细胞]边缘波动ruminant 反刍动物；反刍（动物）的rutin 芸香苷，芦丁rutoside 芸香苷。

rfs、dfs曲线FS（Receiver Operating Characteristic curve，接收者操作特征曲线）和DFS（Decision Function curve，决策函数曲线）是用于评估分类模型性能的两种常见曲线。

1.RFS曲线（Receiver Operating Characteristic curve）：RFS曲线是通过绘制True Positive Rate（TPR，真正率）与FalsePositive Rate（FPR，假正率）之间的关系而得到的。

TPR表示预测为正例中实际为正例的比例，而FPR表示预测为正例但实际为负例的比例。

RFS曲线可以展示在不同的分类阈值下，模型的性能如何变化。

在绘制RFS曲线时，首先需要计算出一系列不同分类阈值下的TPR和FPR。

然后，将TPR作为纵坐标，FPR作为横坐标，绘制出RFS曲线。

曲线上的每个点表示在不同的分类阈值下模型的性能。

2.DFS曲线（Decision Function curve）：DFS曲线是通过绘制决策函数值与分类阈值之间的关系而得到的。

决策函数值表示模型对于样本的置信度或得分，分类阈值用于决定样本被分类为正例还是负例。

在绘制DFS曲线时，首先需要计算出一系列不同分类阈值下的TruePositive Rate（TPR）和False Positive Rate（FPR）。

然后，将决策函数值作为横坐标，TPR和FPR作为纵坐标，绘制出DFS曲线。

曲线上的每个点表示在不同的决策函数值下模型的性能。

这两种曲线都可以用于评估分类模型的性能，特别是在处理不均衡数据集或需要权衡分类错误类型时。

通过观察曲线上的点，可以选择合适的分类阈值或决策函数值，从而达到最佳的分类性能。

R语言内部验证校准曲线代码R语言内部提供了多种方法来验证和校准模型，其中之一就是绘制校准曲线。

下面是一个简单的R代码示例，用于生成校准曲线：```R# 加载相关库library(caret)# 加载数据集data(iris)# 划分训练集和测试集set.seed(123)trainIndex <- createDataPartition(iris$Species, p = 0.8, list = FALSE)train <- iris[trainIndex, ]test <- iris[-trainIndex, ]# 训练模型（这里以随机森林为例）model <- train(Species ~ ., data = train, method = "rf")# 生成预测概率值（用于后面的校准曲线）prob <- predict(model, newdata = test, type = "prob")# 绘制校准曲线plot(calibration(model, test), main = "Calibration Curve")```上述代码中，我们首先加载了`caret`库，并使用内置的`iris`数据集进行演示。

接着，我们使用`createDataPartition()`函数将数据集划分为训练集和测试集。

然后，我们使用`train()`函数训练一个随机森林模型，并使用`predict()`函数生成测试集上的预测概率值。

最后，我们使用`calibration()`函数生成校准曲线，并使用`plot()`函数将其可视化。

需要注意的是，在实际应用中，我们需要根据具体模型的情况来选择相应的校准方法和参数。

此外，还需要对模型进行交叉验证等评估，以确保其在新数据上的泛化能力。