This issue of CytoJournal contains an article on screening for anal intraepithelial neoplasia in high-risk male patients. This accompanying Editorial focuses on current understanding of this relatively new disease entity, with insights as to the potential role of screening cytopathology in the epidemiology, pathophysiology and clinical management of this HIV and HPV related anal lesion, which predominates in male patients living long-term with AIDS. Mention is made of techniques of obtaining samples, methods of preparation, and morphologic classification. Issues of anoscopic confirmation, as well as topical and surgical management are emphasized. The similarity of initial experiences in anal screening to problems encountered early in cervical cancer screening programs several decades ago, are highlighted. For corresponding research article please see Arian et al, 2005 The subject of anal screening cytology has entered the epidemiologic and cytopathologic literature as a topic of interest over the last decade, and is highlighted in this issue of CytoJournal in an article by Arain and colleagues. Until recently, anal cancer was not considered to be a neoplasm of major public health concern . It occuDuring the 1990s, in several European and North American cancer centers, an initially unaccountable increase in anal cancers was seen in younger people. It soon became apparent that HIV-positive homosexual males were affected in numbers greatly in excess of those expected. This was first noted in those urban areas in which large concentrations of homosexual men had been treated since the outbreak of the HIV epidemic. The term "males having sex with males" (MSM) was coined to cover these high-risk individuals. Preliminary information gleaned from screening programs in high HIV-positive incidence areas amongst MSM, showed detection rates of intraepithelial and early invasive neoplasia higher than any incidence ever recorded for cervical cancer screening. Further, HIV-negative homosexual MSMs, and HIV positive non-homosexual men (eg drug users) also exhibited an increased incidence of pre-malignant and invasive anal carcinomas. More recently, the syndrome of early onset anal cancer has been extended to include HIV-positive female patients, as well as females who are not HIV-positive, but who have genital HPV. All these groups show a higher incidence of abnormal anal cytopathology, though none quite as high as that found in HIV positive MSM. The unifying factor in most instances is ano-receptive intercourse, or extension of HPV infection from the genital tract to the anal mucosa, most obvious in the face of deficient immunity, or high viral load -6.Epidemiologic studies have indicated that a prolonged preclinical phase precedes the onset of anal cancer in these high-risk groups. Just as in the cervix, there is a transitional zone  in the anus. Rectal mucosa, with goblet cells, ends about one inch proximal to the external sphincter, giving way to a transitional epithelium, which in turn blends into a stratified squamous epithelium at the level of the anus.  Almost all anal cancers develop in the transitional zone, where atypical, dysplastic and in-situ lesions are identifiable histologically. The cytologic counterparts are those of atypical cells of uncertain significance (ASCUS), low grade squamous intraepithelial lesions (LSIL) and high grade squamous intraepithelial lesions (HSIL). Once this natural history had been demonstrated and confirmed, it seemed natural that exfoliative cytology could be investigated as an "anal Pap smear" ,8.As with the cervix, the technique of obtaining the anal sample is critical to the success of screening. Standard colonic preparation is not required, but the rectum should be emptied prior to obtaining the anal sample. Brushes, brooms and Dacron swabs have all been used, the type of spatula probably being less important than the skill of the operator. The instrument is inserted to a depth of one and a half inches beyond the external sphincter, and subsequently withdrawn in a firm downward spiral movement incorporating 10–12 rotations, to ensure the device has made contact with the full surface area of the transformation zone. Some have used direct smears onto glass slides with immediate wet fixation; most centers, however, employ immediate insertion of the scraping device into liquid fixative for thin layer preparation. This appears both to improve adequacy and preservation, and also to eliminate any fecal contamination; residual material in the vial can be used for HPV studies if required, or for the creation of a bank of teaching slides.There has been a relative dearth of literature on the cytomorphology of anal samples -11. ClasExperience over the last decade suggests that anal cancer may be as highly appropriate a target for screening as is the cervix, in selected populations. The neoplasm is frequently encountered in well-defined high-risk groups. It has a detectable pre-malignant phase, and is amenable to easy cytologic sampling. Cytodiagnosis is reasonably sensitive and highly specific, and histologic confirmation is relatively easily obtained by well-trained personnel. If there is a current area of deficiency in such programs, it may well be in the treatment of intraepithelial lesions, which, as yet, has not been adequately assessed in large numbers of patients. It is known that highly active anti-retroviral therapy (HAART) does not appear to alter the pathophysiology of anal lesions once initiated. A variety of topical agents such as podophyllotoxin and imiquimod have been tried, as has intralesional interferon; superficial ablative therapies including liquid nitrogen, electrocautery, laser and LEEP have been attempted with varying success rates. Circumferential surgical resection almost inevitably results in unacceptable loss of sphincter control and soiling, but anoscopy-directed limited excision may prove less morbid. The fact that so many options are available implies perhaps that no single modality is yet considered sufficiently effective, with minimal complication ,13. Thisineffective in these communities. The second feature dictating the institution of screening programs in developing countries relates to antiretroviral therapy. Anal intraepithelial neoplasia and cancer are not encountered early in the progression of HIV/AIDS. Rather, they are late complications of patients living long-term with AIDS, usually implying patients living long-term on HAART [An interesting consideration is whether or not anal cancer, and thereby anal cytopathology screening programs, would be of value in the developing world, particularly in Africa, India and China, where the bulk of the global incidence of HIV resides. This will depend on two very different factors. First is the nature of transmission. Unlike the situation in the developed world, AIDS in these regions is not essentially a disease of homosexual males; thus, without anal intercourse predominating, an upward trend in the incidence of anal cancer would seem unlikely. Anal screening programs would be unnecessary or cost-on HAART . Unless


Joel Cohen offers a historical and prospective analysis of the relationship between mathematics and biology Although mathematics has long been intertwined with the biological sciences, an explosive synergy between biology and mathematics seems poised to enrich and extend both fields greatly in the coming decades . BiologyThe discovery of the microscope in the late 17th century caused a revolution in biology by revealing otherwise invisible and previously unsuspected worlds. Western cosmology from classical times through the end of the Renaissance envisioned a system with three types of spheres: the sphere of man, exemplified by his imperfectly round head; the sphere of the world, exemplified by the imperfectly spherical earth; and the eight perfect spheres of the universe, in which the seven (then known) planets moved and the outer stars were fixed . The disMathematics broadly interpreted is a more general microscope. It can reveal otherwise invisible worlds in all kinds of data, not only optical. For example, computed tomography can reveal a cross-section of a human head from the density of X-ray beams without ever opening the head, by using the Radon transform to infer the densities of materials at each location within the head . CharlesConversely, mathematics will benefit increasingly from its involvement with biology, just as mathematics has already benefited and will continue to benefit from its historic involvement with physical problems. In classical times, physics, as first an applied then a basic science, stimulated enormous advances in mathematics. For example, geometry reveals by its very etymology (geometry) its origin in the needs to survey the lands and waters of Earth. Geometry was used to lay out fields in Egypt after the flooding of the Nile, to aid navigation, to aid city planning. The inventions of the calculus by Isaac Newton and Gottfried Leibniz in the later 17th century were stimulated by physical problems such as planetary orbits and optical calculations.In the coming century, biology will stimulate the creation of entirely new realms of mathematics. In this sense, biology is mathematics' next physics, only better. Biology will stimulate fundamentally new mathematics because living nature is qualitatively more heterogeneous than non-living nature. For example, it is estimated that there are 2,000–5,000 species of rocks and minerals in the earth's crust, generated from the hundred or so naturally occurring elements  (Harvey 1847), first published in 1628. Harvey's demonstration that the blood circulates was the pivotal founding event of the modern interaction between mathematics and biology. His elegant reasoning is worth understanding.The outstanding milestone in the early history of biological quantitation was the work of William Harvey, From the time of the ancient Greek physician Galen (131–201 C.E.) until William Harvey studied medicine in Padua , it was believed that there were two kinds of blood, arterial blood and venous blood. Both kinds of blood were believed to ebb and flow under the motive power of the liver, just as the tides of the earth ebbed and flowed under the motive power of the moon. Harvey became physician to the king of England. He used his position of privilege to dissect deer from the king's deer park as well as executed criminals. Harvey observed that the veins in the human arm have one-way valves that permit blood to flow from the periphery toward the heart but not in the reverse direction. Hence the theory that the blood ebbs and flows in both veins and arteries could not be correct.Harvey also observed that the heart was a contractile muscle with one-way valves between the chambers on each side. He measured the volume of the left ventricle of dead human hearts and found that it held about two ounces (about 60 ml), varying from 1.5 to three ounces in different individuals. He estimated that at least one-eighth and perhaps as much as one-quarter of the blood in the left ventricle was expelled with each stroke of the heart. He measured that the heart beat 60–100 times per minute. Therefore, the volume of blood expelled from the left ventricle per hour was about 60 ml × 1/8 × 60 beats/minute × 60 minutes/hour, or 27 liters/hour. However, the average human has only 5.5 liters of blood (a quantity that could be estimated by draining a cadaver). Therefore, the blood must be like a stage army that marches off one side of the stage, returns behind the scenes, and reenters from the other side of the stage, again and again. The large volume of blood pumped per hour could not possibly be accounted for by the then-prevalent theory that the blood originated from the consumption of food. Harvey inferred that there must be some small vessels that conveyed the blood from the outgoing arteries to the returning veins, but he was not able to see those small vessels. His theoretical prediction, based on his meticulous anatomical observations and his mathematical calculations, was spectacularly confirmed more than half a century later when Marcello Malpighi (1628–1694) saw the capillaries under a microscope. Harvey's discovery illustrates the enormous power of simple, off-the-shelf mathematics combined with careful observation and clear reasoning. It set a high standard for all later uses of mathematics in biology.Mathematics was crucial in the discovery of genes by Mendel  and in tOver the last 500 years, mathematics has made amazing progress in each of its three major fields: geometry and topology, algebra, and analysis. This progress has enriched all the biological sciences.In 1637, René Descartes linked the featureless plane of Greek geometry to the symbols and formulas of Arabic algebra by imposing a coordinate system  on the geometric plane and using numbers to measure distances between points. If every biologist who plotted data on x–y coordinates acknowledged the contribution of Descartes to biological understanding, the key role of mathematics in biology would be uncontested.Another highlight of the last five centuries of geometry was the invention of non-Euclidean geometries (1823–1830). Shocking at first, these geometries unshackled the possibilities of mathematical reasoning from the intuitive perception of space. These non-Euclidean geometries have made significant contributions to biology in facilitating, for example, mapping the brain onto a flat surface .Nine Chapters of the Mathematical Art; In algebra, efforts to find the roots of equations led to the discovery of the symmetries of roots of equations and thence to the invention of group theory, which finds routine application in the study of crystallographic groups by structural biologists today. Generalizations of single linear equations to families of simultaneous multi-variable linear equations stimulated the development of linear algebra and the European re-invention and naming of matrices in the mid-19th century. The use of a matrix of numbers to solve simultaneous systems of linear equations can be traced back in Chinese mathematics to the period from 300 B.C.E. to 200 C.E. . The questions and the domains of biology behave differently on different temporal and spatial scales. The opportunities and the challenges that biology offers mathematics arise because the units at any given level of biological organization are heterogeneous, and the outcomes of their interactions  on any selected temporal and spatial scale may be substantially affected by the heterogeneity and interactions of biological components at lower and higher levels of biological organization and at smaller and larger temporal and spatial scales , 1995.The landscape of applied mathematics is better visualized as a tetrahedron (a pyramid with a triangular base) than as a matrix with temporal and spatial dimensions.  The four main points of the applied mathematical landscape are data structures, algorithms, theories and models , and computers and software. Data structures are ways to organize data, such as the matrix used above to describe the biological landscape. Algorithms are procedures for manipulating symbols. Some algorithms are used to analyze data, others to analyze models. Theories and models, including the theories of pure mathematics, are used to analyze both data and ideas. Mathematics and mathematical theories provide a testing ground for ideas in which the strength of competing theories can be measured. Computers and software are an important, and frequently the most visible, vertex of the applied mathematical landscape. However, cheap, easy computing increases the importance of theoretical understanding of the results of computation. Theoretical understanding is required as a check on the great risk of error in software, and to bridge the enormous gap between computational results and insight or understanding.The landscape of research in mathematics and biology contains all combinations of one or more biological questions, domains, time scales, and spatial scales with one or more data structures, algorithms, theories or models, and means of computation . The following example from cancer biology illustrates such a combination: the question, “how does it work?” is approached in the domain of cells  with algorithms for correlation and hierarchical clustering.http://discover.nci.nih.gov/arraytools/). They used two kinds of information from the drug discovery program of the National Cancer Institute. The first kind of information described gene expression in 1,375 genes of each of 60 human cancer cell lines. A target matrix T had, as the numerical entry in row g and column c, the relative abundance of the mRNA transcript of gene g in cell line c. The drug activity matrix A summarized the pharmacology of 1,400 drugs acting on each of the same 60 human cancer cell lines, including 118 drugs with “known mechanism of action.” The number in row d and column c of the drug activity matrix A was the activity of drug d in suppressing the growth of cell line c, or, equivalently, the sensitivity of cell line c to drug d. The target matrix T for gene expression contained 82,500 numbers, while the drug activity matrix A had 84,000 numbers.Suppose a person has a cancer. Could information about the activities of the genes in the cells of the person's cancer guide the use of cancer-treatment drugs so that more effective drugs are used and less effective drugs are avoided? To suggest answers to this question, These two matrices have the same set of column headings but have different row labels. Given the two matrices, precisely five sets of possible correlations could be calculated, and Scherf et al. calculated all five. (1) The correlation between two different columns of the activity matrix A led to a clustering of cell lines according to their similarity of response to different drugs. (2) The correlation between two different columns of the target matrix T led to a clustering of the cell lines according to their similarity of gene expression. This clustering differed very substantially from the clustering of cell lines by drug sensitivity. (3) The correlation between different rows of the activity matrix A led to a clustering of drugs according to their activity patterns across all cell lines. (4) The correlation between different rows of the target matrix T led to a clustering of genes according to the pattern of mRNA expressed across the 60 cell lines. (5) Finally, the correlation between a row of the activity matrix A and a row of the target matrix T described the positive or negative covariation of drug activity with gene expression. A positive correlation meant that the higher the level of gene expression across the 60 cancer cell lines, the higher the effectiveness of the drug in suppressing the growth of those cell lines. The result of analyzing several hundred thousand experiments is summarized in a single picture called a clustered image map . This clWhat use is this? If a person's cancer cells have high expression for a particular gene, and the correlation of that gene with drug activity is highly positive, then that gene may serve as a marker for tumor cells likely to be inhibited effectively by that drug. If the correlation with drug activity is negative, then the marker gene may indicate when use of that drug is contraindicated.While important scientific questions about this approach remain open, its usefulness in generating hypotheses to be tested by further experiments is obvious. It is a very insightful way of organizing and extracting meaning from many individual observations. Without the microscope of mathematical methods and computational power, the insight given by the clustered image map could not be achieved.To realize the possibilities of effective synergy between biology and mathematics will require both avoiding potential problems and seizing potential opportunities.The productive interaction of biology and mathematics will face problems that concern education, intellectual property, and national security.Educating the next generation of scientists will require early emphasis on quantitative skills in primary and secondary schools and more opportunities for training in both biology and mathematics at undergraduate, graduate, and postdoctoral levels .Intellectual property rights may both stimulate and obstruct the potential synergy of biology and mathematics. Science is a potlatch culture. The bigger one's gift to the common pool of knowledge and techniques, the higher one's status, just as in the potlatch culture of the Native Americans of the northwest coast of North America. In the case of research in mathematics and biology, intellectual property rights to algorithms and databases need to balance the concerns of inventors, developers, and future researchers .A third area of potential problems as well as opportunities is national security. Scientists and national defenders can collaborate by supporting and doing open research on the optimal design of monitoring networks and mitigation strategies for all kinds of biological attacks . But opeMathematical models can circumvent ethical dilemmas. For example, in a study of the household transmission of Chagas disease in northwest Argentina, The future of a scientific field is probably less predictable than the future in general. Doubtless, though, there will be exciting opportunities for the collaboration of mathematics and biology. Mathematics can help biologists grasp problems that are otherwise too big (the biosphere) or too small (molecular structure); too slow (macroevolution) or too fast (photosynthesis); too remote in time (early extinctions) or too remote in space (life at extremes on the earth and in space); too complex (the human brain) or too dangerous or unethical (epidemiology of infectious agents). Here are five biological challenges that could stimulate, and benefit from, major innovations in mathematics.Understand cells, their diversity within and between organisms, and their interactions with the biotic and abiotic environments. The complex networks of gene interactions, proteins, and signaling between the cell and other cells and the abiotic environment is probably incomprehensible without some mathematical structure perhaps yet to be invented.Understand the brain, behavior, and emotion. This, too, is a system problem. A practical test of the depth of our understanding is this simple question: Can we understand why people choose to have children or choose not to have children ?http://www.life.umd.edu/labs/Delwiche/pubs/endosymbiosis.gif).Replace the tree of life with a network or tapestry to represent lateral transfers of heritable features such as genes, genomes, and prions (Couple atmospheric, terrestrial, and aquatic biospheres with global physicochemical processes.Monitor living systems to detect large deviations such as natural or induced epidemics or physiological or ecological pathologies.Here are five mathematical challenges that would contribute to the progress of biology.Understand computation. Find more effective ways to gain insight and prove theorems from numerical or symbolic computations and agent-based models. We recall Hamming: “The purpose of computing is insight, not numbers” , p. 31.Find better ways to model multi-level systems, for example, cells within organs within people in human communities in physical, chemical, and biotic ecologies.Understand probability, risk, and uncertainty. Despite three centuries of great progress, we are still at the very beginning of a true understanding. Can we understand uncertainty and risk better by integrating frequentist, Bayesian, subjective, fuzzy, and other theories of probability, or is an entirely new approach required?Understand data mining, simultaneous inference, and statistical de-identification . Are praSet standards for clarity, performance, publication and permanence of software and computational results.


Many real networks can be understood as two complementary networks with two kind of nodes. This is the case of metabolic networks where the first network has chemical compounds as nodes and the second one has nodes as reactions. In general, the second network may be related to the first one by a technique called line graph transformation . Recently, the main topological properties of the metabolic networks have been properly described by means of a hierarchical model. While the chemical compound network has been classified as hierarchical network, a detailed study of the chemical reaction network had not been carried out.C(k) is calculated for the transformed network. C(k) indicates the probability that two nearest neighbours of a vertex of degree k are connected to each other. While C(k) follows the scaling law C(k) ~ k-1.1 for the initial hierarchical network, C(k) scales weakly as k0.08 for the transformed network. This theoretical prediction was compared with the experimental data of chemical reactions from the KEGG database finding a good agreement.We have applied the line graph transformation to a hierarchical network and the degree-dependent clustering coefficient The weak scaling found for the transformed network indicates that the reaction network can be identified as a degree-independent clustering network. By using this result, the hierarchical classification of the reaction network is discussed. WWW. Most networks encountered in real world have scale-free topology, in particular networks of fundamental elements of cells as proteins and chemical substrates [P(k) ~ kγ -(i.e., frequency of the nodes that are connected to k other nodes). The degree of a node is the number of other nodes to which it is connected.Recent studies on network science demonstrate that cellular networks are described by universal features, which are also present in non-biological complex systems, as for example social networks or bstrates -4. In thBarabási-Albert [continuum theory framework. However, although that model was a milestone to understand the behavior of real complex networks, it could not reproduce all the observed features in real networks such as clustering dependence. The observed properties of networks with N nodes are: scale-free of degree distribution P(k) ~ kγ-, power-law scaling of clustering coefficient C(k) ~ k-1 and a high value for the average of the clustering coefficient <C > and its independence with network size. In particular, the dependence of C(k) ~ k-1 was one of the results obtained by [Ravasz et al. (the RSMOB model in what follows) suggested successfully a hierarchical and modular topology [One of the most successful models for explaining that scale-free topology was proposed by i-Albert , which iained by . In ordetopology ,8. In [8topology . It is atopology ,11. InteIt is interesting to note that the metabolic network is an example of bipartite networks . In a biP(k) and applied to some real networks can be found in [P(k) ~ kγ-, the transformed network preserves the scale-free topology and in most cases the exponent is increased by one unit as P(k) ~ kγ+1-.However, although the line graph transformation works fine on bipartite networks, the transformed network (in the particular case of metabolic networks) may not be totally the same as the reaction projection. This issue is discussed in detail later. In addition, we will show by comparing with the experimental data, that this fact does not affect our qualitative results. Furthermore, a detailed analysis of the line graph transformation focused on the degree distribution found in . In thatPereira-Leal et al. [It is also worth noting that the line graph transformation has recently been applied with success by l et al.  on the pl et al.  they areC(k) and <C > of the reaction network by using two approaches: Firstly, we derive mathematical equations of those coefficients in the transformed network. Secondly, we apply the line graph transformation to a hierarchical network. The results from both methods are compared with experimental data of reactions from KEGG database [C(k) between the compound network and the reaction network.The observed topological properties related to the clustering degree of the metabolic network  have been properly described by means of the RSMOB model. In the present work, our aim is to study the clustering coefficients database  showing C(k) follows the power-law k-1.1 for the initial hierarchical network (compound network), C(k) scales weakly as k0.08 for the transformed network (reaction network). Consequently, we conclude that the reaction network may not be classified as a hierarchical network, as it is defined in [In our work, the hierarchical network is generated by the RSMOB model, where the nodes correspond to chemical compounds and the edges correspond to reactions. While the RSMOB model reproduces successfully the hierarchical properties of the compound network, here we show that this hierarchical model also stores adequate information to reproduce the experimental data of the reaction network. Our study indicates that it is enough to apply the line graph transformation to the hierarchical network to extract that information. While C(k) ~ k-1, and high degree of clustering was called hierarchical network. Consequently, the RSMOB model shown in [C(k). Moreover, in a more recent work [C(k) is independent of k (i.e., flat plot of C(k)). In addition, analyses of C(k) were recently carried out in [Barabási et al, [In , a netwoshown in ,8 was deshown in ,8,17 soment work , it was d out in  to uncovi et al,  and conshierarchical path: a path between nodes i and j is called hierarchical if (1) the node degrees grow monotonously ("up path"), and it is followed by a path where the node degrees decrease monotonously ("down path") or (2) the node degrees along this path changes monotonously from one node to the other. The fraction of shortest paths in a network, which are also hierarchical paths is called H. If H is very close to 1, the network shows a hierarchical organization. This definition seems interesting, and consequently, as a future work it would be worth to examine some biological networks (in particular, metabolic networks) by using this approach. One remark about this concept is that it focuses on hierarchy and may not contain enough information about modularity or clustering. For a brief discussion of these issues, we refer to some very useful notes written by Dorogovtsev et al. [However, it is also worth noticing that another way to quantify the hierarchical topology of a network is recently introduced by ,21. It iv et al.  for furtP(k) ~ kγ-, power-law dependence of clustering coefficient C(k) ~ k-1 and independence with network size of the average clustering coefficient <C >, where N is the total number of nodes in a network [i as:Recent analyses have demonstrated that the metabolic network has a hierarchical organization, with properties as: scale-free degree distribution  network . The cluni denotes the number of edges connecting the ki nearest neighbors of node i to each other, Ci is equal to 1 for a node at the center of a fully interlinked cluster, and it is 0 for a node that is a part of a loosely connected cluster [where  cluster . An examni gives the number of triangles that go through node i. The factor ki(ki - 1)/2 gives the total number of triangles that could go through node i . In the case of Fig. C1 = 1/6.Geometrically, C > characterizes the overall tendency of nodes to form clusters as a function of the total size of the network N. The mathematical expression is:On the other hand, the average clustering coefficient <C(k), which is defined as the average clustering coefficient over nodes with the same node degree k. This function is written as:The structure of the network is given by the function Nk is the number of nodes with degree k, and the sum runs over the Nk nodes with degree k. A scaling law k-1 for this magnitude is an indication of the hierarchical topology of a network.where C > and C(k) are modified under the line graph transformation.Once the theoretical definitions have been introduced, our aim is to analyse how the coefficients <G, defined by a set of nodes V(G) and a set of edges E(G), we associate another graph L(G), called the line graph of G, in which V(L(G)) = E(G), and two nodes are adjacent if and only if they have a common endpoint in G (i.e., E(L(G)) = {{(u, v), (v, w)}|(u, v) ∈ E(G), (v, w) ∈ E(G)}). This construction of graph L(G) from the initial graph G is called line graph transformation [Given an undirected graph ormation .P(k) was studied by applying line graph transformation to synthetic and real networks. There it is assumed an initial graph G with scale-free topology as P(k) ≈ kγ-. As the degree of each transformed node (i.e., an edge in G) will be roughly around k, the distribution of the line graph L(G) should be k·kγ -= kγ+1 -with degree around k. Therefore, it is concluded that if we have a graph G with a probability distribution following a power-law as kγ-, then L(G) will follow a power-law as kγ+1-. The real networks under study were protein-protein interaction, WWW, and metabolic networks. In Fig. It is worth noting that in a previous work  the degrphysical line graph transformation. In the present work, we have applied this procedure to generate the reaction network by using experimental data from the KEGG database. Experimental data are shown later in Figs. However, it is important to point out one issue. In metabolic networks, there are cases where spurious nodes appear see Fig. . For exaG as it is depicted in Fig. a connects two nodes with degree k' and k". We apply the line graph transformation to this graph G and the result of this transformation is the line graph of G, L(G) shown in Fig. L(G) are the edges of G, with two nodes of L(G) adjacent whenever the corresponding edges of G are.We assume a graph a in the transformed network can be written by using Eq. (1) as:The clustering coefficient for the node k = k' + k" - 2, because the edge a vanishes in the graph L(G). This equation ignores cases where edges in the graph G, b and b' for example, have a common node as endpoint . This additional edge in L(G) connects two neighbors of node a. By following definition of Eq. (1), it means that na increases its value by one unit. We can consider these cases by increasing one unit the parameter l for each common node as endpoint of two edges in the graph G (for example, l = 1 means one common node). We write Eq. (4) after introducing the parameter l as:where l = 0 means that there are not loops and we recover Eq. (4). Though it is more realistic to consider the parameter l as a function of k' and k", we have considered l as an independent parameter. However, this simplification does not affect the qualitative features of our results. It should be noted that l always contributes to increasing the value of Ca(k) and Ca(k) ≤ 1 always holds from the definition. In order to study the limits of Eq. (5) we consider the following two cases:where if a) k' = k": We analyse the case where both degrees have the same value. We also consider the cases when l = 0 and l ≠ 0 in order to study the effect of triangles. We show the results in Fig. k', Eq. (5) goes asymptotically to 1/2 for l = 0 and l ≠ 0. We also see that for k' ≥ 25, all lines are very close to 1/2. For low k' and l = 0, Ca(k) takes values from 0.33 (k' = 3) to 0.48 (k' = 20). Hence, we see in Fig. l (more triangles) increase the values of Ca(k).• b) k" = constant, k' >>k": We plot in Fig. k" is fixed with constant values as k" = 5 (black), k" = 10 (red), k" = 20 (blue) and k' is a free parameter. We see that Ca(k) approaches to 1 when k' takes large values. For low k', the case k" = 5 shows a minimum with a few values of k' below 1/2. As we can see with dotted and dash-dotted lines in Fig. l ≠ 0) increases the value of Ca(k). Finally, for k" = 10 and k" = 20, we see that only a few values of Ca(k) are slightly below 1/2 for low k'. This analysis is complemented by calculating the minimum value of Ca(k) analytically as: . The value of k', where the function Ca(k) takes the minimum value, is given by:• Ca(k) for each configuration of l and k".where positive solution of the square root is written. By substituting this equation into Eq. (5), it is possible to calculate the minimum value of k' and k" >> 1)) and for highly clustered networks (many triangles l >> 1), the values of Ca(k) in the transformed network are between around [, 1].From these two cases, we can conclude that for hubs (i.e., those nodes with high degree (C(k) in the transformed space (CT(k)) we introduce the concept of assortativity. By assortative (disassortative) mixing in networks we understand the preference for nodes with high degree to connect to other high (low) degree nodes [Newman [k' and k" as ek'k". We also assume that the nodes of the initial network are following a power-law distribution kγ -and have no assortative mixing. Under these assumptions, the probability distribution ek'k" of edges that link together nodes with degree k' + k" can be written as:To calculate the distribution of ee nodes . By foll [Newman , we defik', k"), which can generate transformed nodes with degree k = k' + k" - 2. Thus, we obtain:We make a convolution between Eq. (4) and Eq. (7), by summing for all the possible degrees of the two nodes at either end of edges (CT(k) and the behavior of Ca(k) exposed above, CT(k) will grow smoothly for large k, i.e., scaling weakly with the node degree k. We have calculated numerically this expression and the results are discussed later in Fig. According to the structure of C >, and we have found that <C > has a size-independent behavior before and after the line graph transformation is done. We can write the number of nodes with degree k as:We have also calculated the analytical expression for <C(k) = A·k α-, where A is a constant. This constant changes when we consider hierarchical networks with different number of nodes in the initial cluster [P(k) ~ kγ -of the network also changes. For <C > before the transformation we can write:and we assume that  cluster . But it k = 1 because we renormalize over all the probability distribution.Note that the summation in the denominator begins with C > by using the RSMOB model (explained in next section in detail). This model starts by generating a fully connected cluster of m nodes, such that the connectivity of each node is k = m - 1. In the following iteration, m - 1 replicas of the initial cluster are generated, and linked to the central node of the original cluster in such a way that the central node of the original cluster gains (m - 1)·(m - 1) edges, and its total connectivity being k = m - 1 + (m - 1)2. By iterating these procedure, it is easy to see that hubs  will have connectivities , with j = 1, ..., logmN being the iteration number. Therefore, assuming that the degree distribution P(k) and the clustering coefficient C(k) are power-laws with exponents γ' and α respectively, the expression for <C > for the hubs reads as:Furthermore, we can obtain <A' is a constant adjusted so that <C >=1 holds for j = 1. The upper limit of the summation logmN is obtained by means of the expression mj = N, which gives the total number of nodes in the network and  denotes the exponent of the power-law distribution of hubs in the RSMOB model. We must note that in a hierarchical network, the number of nodes with different degree k is scarce, therefore the probability distribution of node degree is properly defined as P(k) = (1/Ntot)(Nk/Δk), where Nk is the number of nodes with degree k, Ntot is the total number of nodes, and Δk means that nodes with degree k are binned into intervals. In addition, we note that for the hierarchical model, Δk changes linearly with k. Hence, the exponent of the power-law is given by γ = 1 + γ', with  where m is the number of nodes in the initial module.where C > converges to a constant. In order to calculate <C > after the line graph transformation is applied (<CT >), we make the substitution C(k) → CT(k) in Eq. (10). As from Eq. (8) we have seen that CT(k) is almost constant, we can conclude that <CT > also has a constant behavior and it is almost independent with network size. While the scaling law of C(k) ~ k-1 was proved mathematically in [CT(k), <C > and <CT >.By using Eqs. 10) and (11), we will see later . In the next step four replicas are created and the peripheral nodes are connected again to produce 125-node modules (iteration n = 2, 53 = 125 nodes). This process can be repeated indefinitely [Fig. finitely .C(k), we have constructed three hierarchical networks with 3, 4, and 5 initial number of nodes. These networks were generated up to 7 (6561), 5 (4096), and 4 (3125) iterations (nodes), repectively. Once we have constructed these three networks, we apply the line graph transformation to them, and we calculate the CT(k) clustering coefficient for the transformed networks. In Fig. CT(k) for the transformed network with 3, 4, and 5 initial nodes, respectively. In Fig. CT(k) obtained from Eq. (8). From top to bottom the lines correspond to the networks of 3, 4 and 5 initial nodes, respectively. In Fig. CT(k) via Eq. (8) (lines) are in good agreement with the experimental data (diamonds) from the KEGG database [CT(k), we have binned into seven intervals the experimental data according to degree k (1 <k ≤ 8 < ,..., 128 <k ≤ 256, 256 <k ≤ 512), and averaged over the CT(k)'s obtained in that range (red circles). It shows a better agreement between KEGG results and the analytical curves. The only disagreement comes at k = 2. This is easy to understand because in the hierarchical model depicted in Fig. C(k = 2) = 1 for 3 initial nodes by construction of the network. However, in real networks, we could find nodes which have only two neighbors and, in some cases, these neighbors could be connected. In these cases the clustering coefficient takes value one.To evaluate database . Moreove up to 7 561, 5 (4CT(k) after the line graph transformation is applied to the hierarchical network generated by 4 initial nodes and up to 5 iterations. The results are shown with empty triangles (red) and fitted to the dashed line. We see that C(k) ~ k-1.1 changed into CT(k) ~ k0.08. We also see that the line graph transformation increases the average of the clustering value of the transformed network. These theoretical results were compared with the experimental data from KEGG [CT(k) for the reaction network.In Fig. rom KEGG , findingC > we have evaluated Eq. (10) for 3 different configurations. We have considered 3 initial nodes, 4 and 5 initial nodes nodes up to 7, 5 and 4 iterations, respectively. As it is explained in [C > approaches asymptotically to a constant value, being independent of the size of the network. The asymptotic value depends on the initial number of nodes. We calculated the values of γ corresponding to the degree distribution P(k) ~ kγ -for each network, and the related constant A, which appears in Eq. (10). We show in Table C > obtained by Eq. (10). These values, as it can be seen in Fig. C(k) is being overestimated by the scaling dependence k-1 and it provides a larger value of <C >. In [C > from hierarchical model were compared with the experimental values of 43 organisms. The values of <C > for each organism were around 0.15 – 0.25. By using the KEGG database we have evaluated the experimental value <C > for 163 organisms and we obtained an average value of 0.08.For <ated Eq. 0 for 3 dC > calculated for networks generated by 3 initial nodes (circles) and 4 initial nodes (triangles) by using the RSMOB model. We see that <C > approaches asymptotically to constant values around ~ 0.66 (circles) and ~ 0.74 (triangles), being independent of the size of the network. Once the line graph transformation is applied, we see that the corresponding values of <CT > also approach asymptotically to constant values. Hence, <CT > also is size-independent for large N (empty circles and triangles). In addition, we have averaged the experimental value of the clustering coefficient for reactions of 163 organisms found in KEGG database and we have obtained the value of <CT >= 0.74. We see that the experimental value <CT > for reactions is in good agreement with the asymptotic values obtained by the transformed network (empty triangles and circles).We show in Fig. C > by using Eq. (11). This equation should reproduce the results of <C > calculated by using the RSMOB model  and <C > of the reaction network by applying the line graph transformation to a hierarchical network. This hierarchical network was generated by using the RSMOB model, which reproduces properly the topological features of the metabolic network, in particular the compound network. Our results indicate that by applying the line graph transformation to the hierarchical network, it is possible to extract topological properties of the reaction network, which is embedded in the metabolic network. The RSMOB model stores the adequate information of the reaction network and the line graph transformation is one useful technique to evoke it.We have studied here the clustering coefficients C(k) scales as k-1.1 for the initial hierarchical network (compound network), we find C(k) ~ k0.08 for the transformed network (reaction network). This theoretical prediction was compared with the experimental data from the KEGG database, finding a good agreement. Our results indicate that the reaction network is a degree-independent clustering network. Furthermore, the weak scaling of C(k) for the reaction network suggests us that this network may not have hierarchical organization. However, further analyses of this network, and in general of all biological networks, by following the concept of hierarchical path are encouraged [While couraged ,21.C(k) and <C >. Expressions for these coefficients were calculated before and after the line graph transformation is applied to the hierarchical network. The agreement obtained by using these expressions was found acceptable, and consequently, they could be useful for further analyses in different networks .On the other hand, we have also conducted an analytical derivation for the clustering coefficients The line graph transformation has recently been applied on metabolic networks  to studyJCN conceived of the study, designed and implemented the analyses, and prepared the manuscript. NU carried out computational implementations and experiments. TY participated in the acquisition and processing of data from KEGG database. MK provided conceptual guidance and data from the KEGG database, and conceived the initial idea of the two complementary metabolic networks. TA provided guidance, coordinated and participated in the biological and theoretical analyses, and revised the manuscript. All authors read and approved the final manuscript.


In this review, we discuss estrogen actions on mitochondrial function and the possible implications on cell growth. Mitochondria are important targets of estrogen action. Therefore, an in-depth analysis of interaction between estrogen and mitochondria; and mitochondrial signaling to nucleus are pertinent to the development of new therapy strategies for the treatment of estrogen-dependent diseases related to mitochondrial disorders, including cancer. In contrast, "non-genomic" effects of estrogen are characterized by a rapid onset of action within seconds to minutes after hormone exposure through post-translation modification of signaling proteins. ER-mediated signaling pathways are considered to support the growth of normal, preneoplastic and neoplastic cells [Estrogen is considered to elicit different growth responses in various tissues through binding to the estrogen receptor (ER) α and ERβ -3. The mic cells -3. In coic cells . Recentlic cells . For insic cells . Similaric cells ,8. For iBesides apoptosis, respiration, and oxidative phosphorylation; mitochondria also control ion homeostasis and the synthesis of heme, lipids, amino acids, and nucleotides. Steroidogenesis is also controlled by mitochondria. Estrogen biosynthesis-related enzymes, 3 β-hydroxysteroid dehydrogenase and aromatase, have been demonstrated in the mitochondria of ovarian tumor epithelial cells .in vivo exposure of ovariectomized rats to tritiated 17-β-estradiol (E2) showed with increasing time, the translocation of this hormone from the plasmalemma mainly to the mitochondria (75%) rather than the nuclei in liver, adrenal gland, and spleen tissues [Although estrogen synthesis occurs in the mitochondria, exogenously added estrogen is also transported to this organelle. For instance,  tissues . The lip tissues . The upt tissues -13.The impact of estrogen on mitochondrial morphology has previously been reported in the human breast cancer cell line MCF7. Transmission electron microscopy (TEM) revealed that an 8 day treatment of MCF7 cells with E2 (10 nM) resulted in large, clear mitochondria . These a-8 M and 10-9 M) significantly increased the mitochondrial level of ERα and ERβ by 2.5-fold.The function of estrogen at the mitochondria is not clear, however, recent studies have identified ERα and ERβ within the mitochondria implicating its role in the regulation of mitochondrial genome transcription. Subcellular fractionation of rabbit ovarian and uterine tissue revealed isoforms of ERα and ERβ in the mitochondrial enriched fraction as detected by western Blot analysis using ER specific antibodies . More reAn increasing body of evidence has shown that mitochondrial transcription is enhanced by estrogen treatment. For instance, a 16-fold increase in cytochrome oxidase II (CO II) mRNA is reported in the GH4C1 rat pituitary tumor cell line when treated for 6 days with E2 (0.5 nM) . The mitThe mechanism of estrogen-induced mitochondrial gene transcription is not clearly understood. The involvement of estrogen responsive elements (EREs) and/or the ER may be a possible mechanism in the increase of these mitochondrial transcripts. Sequences with partial similarity to the ERE consensus sequence, (AGGTCANNNTGACCT), have been reported in the mouse mitochondrial genome . These p0F1-ATPase) [m). In human neuroblastoma cells, the following ER ligands: tamoxifen (30.2 μM), clomiphene (10.6 μM), and nafoxidine (2.8 μM); were reported to modulate ΔΨm while E2 did not change ΔΨm at concentrations up to 100 μM [m could result from an increased rate of electron transfer. The formation of ROS in mitochondria is reported to occur at high ΔΨm [m may be a possible mechanism for the generation of ROS. Whether physiologic concentrations of estrogen can increase ΔΨm in target tissues is not clear, but these lines of evidence suggest that estrogen may modulate ΔΨm in a dose- and tissue-specific manner. This effect is significant because estrogen-induced mitochondrial reactive oxygen species (ROS) may participate in cell signaling. In the following section, we provide a detailed review of the effects of E2 on mitochondrial respiratory complexes.Besides transcription of mitochondrial genes, estrogen has also been demonstrated to effect mitochondria at the protein level. Estrogen has been demonstrated in several studies to inhibit mitochondrial respiratory complex I, II, III, IV, and mitochondrial ATP synthase (F-ATPase) -31. Seve-ATPase) . The pre-ATPase) . Besides-ATPase)  and that-ATPase) , it is lo 100 μM . Assuminhigh ΔΨm ,38 and tThe effect of natural estrogens and synthetic estrogens on the mitochondrial ETC has been demonstrated in several studies. Human NADH dehydrogenase (complex I) is the largest respiratory chain complex consisting of 7 mitochondrial genome encoded subunits and more than 41 subunits encoded from the nuclear genome. This integral membrane protein is located within the mitochondrial inner membrane and the matrix. Two electrons enter the ETC from the oxidation of NADH by ubiquinone (CoQ) at complex I which is coupled with proton movement across the inner membrane from the matrix to the intermembrane space. Natural estrogens, 17-α-estradiol, E2, and estrone, at concentrations of approximately 10 μM were demonstrated to inhibit mitochondrial electron transport in homogenates of rat uterus, liver, and skeletal muscle . The syn2O2) production [2O2 production, it was suggested that the H2O2 source was the mitochondria. Although the biological significance of estrogen interaction with complex I is unknown, evidence of estrogen inhibition of electron transfer support a novel role of estrogen in the formation of mitochondrial ROS.There are very few reports that have investigated co-treatment of estrogen with mitochondrial inhibitors of oxidative phosphorylation (OXPHOS). Complex I inhibitors rotenone, piericidin A, and amytal have been used in co-treatment with DES and/or estrogens to elucidate the site of estrogen action on electron transfer ,39. In Moduction . Since a2 by CoQ at complex II. Although previous studies have reported complex I and cytochrome bc1 reductase (complex III) as the major sites of ROS generation, ubiquinone radicals have been reported to contribute to basal levels of ROS at complex II [m and ATP levels by estrogen when faced with 3-NPA toxicity was proposed to be due to the antioxidant effect and/or ATP increasing effects. At the 2 μM E2 dose an antioxidant effect is likely because estrogen is reported to be an effective neuroprotective antioxidant in the micromolar dose range [m and ATP levels, and the enhancement of succinate dehydrogenase activity.Human succinate dehydrogenase (complex II) is a membrane bound protein located on the matrix side of the inner mitochondrial membrane. Complex II consists of 4 subunits all encoded from the nuclear genome. Two electrons enter the mitochondrial ETC from the oxidation of FADHmplex II . Physiolmplex II . Researcmplex II ,47. To mmplex II . This stse range . Howeverse range . Estroge1 reductase (complex III) is an integral membrane protein located in the inner mitochondrial membrane consisting of 10 subunits encoded from the nuclear genome and 1 subunit encoded from the mitochondria. Complex III transfers electrons from ubiquinol (CoQH2) to cytochrome c which is coupled to proton movement across the inner membrane. The synthetic stilbene estrogen, DES (10 μM–50 μM), is reported to inhibit complex III at the site of electron flow from ubiquinone to cytochrome c1 [2) and preserve mitochondrial function by its action on complex III in isolated rat brain mitochondria [The human cytochrome bcES 10 μM– μM, is rhrome c1 . The phyhrome c1 ,52. Intechondria ,54. Besim and ROS formation may be controlled by a hormone mediated reversible phosphorylation of complex IV [In humans, the mitochondrial cytochrome c oxidase (Complex IV) is located in the inner membrane and catalyzes the transfer of electrons to oxygen with water being the final product of the reduction reaction coupled with proton movement across the inner membrane. The mitochondria genome encodes 3 subunits of complex IV while the other 10 subunits are encoded from the nuclear genome. The effect of estrogen and ER ligands on complex IV has been reported to increase and decrease enzymatic activity. During the oestrus cycle in rats, E2 decreased complex IV activity in brown adipose tissue, which suggests a role for E2 in the modulation of oxidative capacity . The ER mplex IV . Thus, t0F1-ATPase/Complex V) is composed of two distinct parts: 1) the F1-ATPase portion which protrudes into the matrix and synthesizes ATP when protons pass through it down their electrochemical gradient. 2) the F0-ATPase which forms a transmembrane proton channel through the inner membrane. F0F1-ATPase is encoded by 2 mitochondrial genome encoded subunits and 14 nuclear encoded subunits. F0F1-ATPase like respiratory chain complexes I-IV represents another enzyme in the mitochondrial inner membrane that is sensitive to estrogen. Inhibition of rat liver F0F1-ATPase by DES (10 μM) has been demonstrated and the F0 portion was reported to contain a distinct binding site for DES [0 portion has made DES a unique probe for the rapid isolation of functional F0 from rat liver mitochondria [0 and F1 subunits of F0F1-ATPase in mitochondria. The OSCP was proposed to be the specific site on F0F1-ATPase where estrogen modulates ATPase activity. Differential effects of estrogen on F0F1-ATPase activity in isolated rat heart, liver, and brain mitochondria were observed when treated with E2, DES, and resveratrol [0F1-ATPase activity in the heart by 10%, but not in the liver and brain. The phytoestrogen resveratrol (13–15 μM) inhibited F0F1-ATPase activity in the heart and liver while lower doses (133 pM–1.3 nM) stimulated F0F1-ATPase activity in the liver by 10%. Both phytoestrogens resveratrol (19 μM) and genistein (55 μM) can inhibit F0F1-ATPase activity in rat brain mitochondria [0F1-ATPase activity was inhibited by DES (6.7 μM) 61%–67% [0F1-ATPase activity at low concentrations of 15 nM and 3.4 nM, respectively, while 17α-E2 preserved mitochondrial function altered by the stress of anoxia-reoxygenation [0F1-ATPase have been shown in isolated mitochondrial preparations, F0F1-ATPase inhibition by E2 was demonstrated to occur with intact human osteolclastic FLG 29.1 cells [0F1-ATPase activity demonstrate that estrogens and estrogen-like compounds possess cell-type and dose-specific effects on mitochondrial function.Mitochondrial ATP synthase (F for DES . This spchondria . Using Echondria . The 23 veratrol . E2 (13 chondria . In rat  61%–67% . In rat genation . Althoug.1 cells . These s2•-), H2O2, and the hydroxyl free radical (•OH) [2) to form O2•- which is dismutated by manganese superoxide dismutase (MnSOD) to form H2O2 [2O2 [2O2 production under resting conditions. These results suggest that mitochondria produce low levels of ROS that can be effectively scavenged by the cell's antioxidant defenses at resting conditions. It is this point, the low basal level of ROS produced by the mitochondria at rest, which makes mitochondrial ROS ideal signaling molecules since its contribution to the intracellular level of ROS is not at so high a level to induce oxidative stress; instead, a low oxidant level provides a physiologically safe window for redox signaling which allows the cell to regulate mild to moderate oxidative changes and critically respond to them by activating cellular processes such as proliferation and differentiation rather than triggering cell death.Within the cell, mitochondria are considered to be a major source of ROS, which include superoxide anion  -66. Sincal (•OH) . As elecorm H2O2 ,68. Duri2O2 [2O2 . In supp2O2 [2O2 . In addi2•- production [2•- in L929 cells and this ROS generation is coupled to the cytokine by the TNF-α receptor [Mitochondria are a predominant source of ROS in most cell types with unique characteristics that may allow it to participate in growth signal transduction. First, mitochondria are unique because they are a regulatable source of ROS in response to external stimuli. For example, cortical neurons exposed to N-methyl-D-aspartate (NMDA) were reported to couple a rise in intracellular calcium with mitochondrial Ooduction . Tumor nreceptor ,72. Few receptor . Althoug2O2 or O2•- where it can participate in redox signaling. Within the mitochondria, MnSOD can dismutate O2•- to H2O2 which is a highly diffusible signaling molecule that can exit the mitochondria. In addition to H2O2, O2•- was demonstrated to be released by mitochondria to the cytosol via the voltage-dependent anion channels (VDACs) [nd messenger since they are short-lived (rapidly generated and degraded), produced in response to a stimulus, highly diffusible, and ubiquitously present in most cell types.Mitochondrial ROS can enter the cytosol as either H (VDACs) . In rega2O2 generated by mitochondria may become a specific signaling molecule as a function of location. For example, perinuclear mitochondria may generate H2O2 that only transduces signals to the nucleus or the subplasamlemmal mitochondria may only activate signal cascades of plasma membrane origin. Additionally, perinuclear, subplasmalemmal, and perigranular mitochondria were independently activated by intracellular calcium signals in their immediate environment, which supports distinct calcium functions for each type of mitochondria.Mitochondria are highly dynamic structures capable of changing their shape (by elongation, branching, swelling) and their location inside a living cell . It is b2, ATP, and pH resulting in specialized microzones that may facilitate signal specificity [2O2 produced within the mitochondria is highly diffusible in contrast to O2•-, which cannot diffuse through membranes making it easily compartmentalized. Thus, mitochondrial generated O2•- may be kept separated from the cytosol until an appropriate stimulus releases it through VDACs. Another route for O2•- release may be through the mitochondrial permeability transition pore (MPTP) as low molecular weight compounds up to molecular weight 1500, can be exchanged between the mitochondrial matrix and the cytosol via this pore [It is significant that mitochondria can create subcompartments or 'microzones' within the cytoplasm because signal transduction depends on the close proximity of substrates and effector molecules to be an efficient process. In addition, given the presence of other endogenous ROS sources besides the mitochondria such as NADPH oxidase, peroxisomes, cytochrome p450, xanthine oxidase, cyclooxygenase, lipooxygenase, and γ-glutamyl transpeptidase ; and beccificity . In the his pore . Since this pore .In addition to location and compartmentalization, protein scaffolds mediate the selective activation of the mitogen activated protein kinase (MAPK) signaling pathway which raises the question of whether mitochondria may also act as a protein scaffold for signaling complexes . A-kinas2•- is produced, was reported to occur on the cytosolic side by complex III and on the martix side of the inner membrane by complex I [Studies of the mitochondrial ETC have reported only two ROS forming sites, the FMN group of complex I and the ubiquinone site in complex III ,90. The omplex I . Estrogeomplex I . Whether10 (CoQ) oxidizes NADH and FADH2, respectively. CoQ functions as a mobile electron carrier within the mitochondrial inner membrane and transfers 2 electrons from both NADH and FADH2 to complex III [10. Other than its role as an electron carrier and antioxidant, CoQ is also reported to act as a pro-oxidant. Although the pro-oxidative action of CoQ within the mitochondria is a matter of debate, O2•- formation occurs from a single electron transfer from ubisemiquinone to molecular oxygen. Exogenously added CoQ has been demonstrated to enhance O2•- generation in isolated respiratory complex I and III [2O2 derived from decomposing O2•- was inhibited after the removal of CoQ [2O2 was detected again which indirectly demonstrated that the O2•- may originate from CoQ. Although some reports make a case for O2•- formation by CoQ redox cycling in mitochondria, arguments against its role as a source of O2•- come from a study which demonstrated that O2•- formation did not occur in a water-free nonpolar reaction system that mimics the lipophilic nature of the inner mitochondrial membrane [2•- formation by CoQ. Thus, it was proposed that under certain pathological conditions in which the inner mitochondrial membrane is protonated, CoQ becomes a significant source of O2•- [2O2 from mitochondria in the presence of antimycin A (2 μM) and to a lesser extent with Ca2+ (10 μM) [2+ pretreatment was thought to induce a leaky inner mitochondrial membrane thereby allowing protons to interact with CoQ and enhance ROS production by redox cycling.Electrons feed into the mitochondrial ETC at complex I and complex II. At complex I and complex II, ubiquinone or co-enzyme Qplex III . CoQ is plex III . It is a and III . Furtherl of CoQ . Upon thmembrane . However of O2•- . In line (10 μM) . The ant2•- [2O2 in the mitochondrial subfraction [2•- by estrogen at the level of electron transport could be one mechanism of increased mitochondrial ROS.Interestingly, CoQ shares similar characteristics to catechol metabolites of estrogen. The catechol metabolites 2- and 4-OH-E2 contain hydroxyl groups that can be oxidized to semiquinones, which in the presence of molecular oxygen can be further oxidized to quinones with the formation of O2•- . Since Cfraction ; and thafraction , the capfraction . Estrogefraction ,103. Bas2+, [Ca2+]m, accumulation is reported to promote the generation of ROS [2+]m was reported to stimulate H2O2 production by rat brain mitochondria in the presence of rotenone [2+]m with E2 (100 pg/ml) treatment of MCF7 cells [2+]m with E2 (10 ng/ml) treatment of hippocampal neurons [2+]m is not clear, however, the inhibition of Na-dependent Ca2+ efflux from mitochondria was reported to increase calcium retention in E2 (1 nM) treated synaptosomal mitochondria [2+-activated dephosphorylation [2+ may activate a mitochondrial protein phosphatase which dephosphorylates cytochrome c oxidase. In turn, cytochrome c oxidase is activated which results in a rise of ΔΨm and ROS [2+]m, it is possible for estrogen to signal the formation of mitochondrial ROS through a similar mechanism.Mitochondrial Can of ROS . For exarotenone . Using cF7 cells . Another neurons . The mecchondria . There irylation . A study and ROS . Interes and ROS . Since em and/or [Ca2+]m in favor of ROS generation.The inhibition of respiratory complex I is known to favor ROS generation. Rat brain mitochondria that respired on complex I substrates produced a substantial level of ROS when inhibited with rotenone concentrations as low as 20 nM . Since e2•- which is dismutated into the membrane permeable second messenger H2O2 [2O2. Interestingly, NO induced mitochondrial biogenesis has been demonstrated in several cell lines, which include brown adipocytes, 3T3-L1, U937, and HeLa cells [2+, we propose that an estrogen-induced rise in [Ca2+]m could stimulate mtNOS activity ultimately leading to the generation of ROS via NO-dependent inhibition of cytochrome c oxidase [Several isoforms of the enzyme nitric oxide synthase (NOS) are reported to exist which include inducible-(i), endothelial-(e), neuronal-(n), and mitochondrial-(mt) NOS. Estrogen has been reported to induce various isoforms of NOS. The activity of eNOS is modulated by estrogen in human aortic endothelial cells, uterine artery, heart, and skeletal muscle ,119. Estger H2O2 . Since eLa cells . We have oxidase .2O2 and/or O2•- has been demonstrated to stimulate cell growth in a variety of cell types including muscle cells, fibroblasts, amnion cells, prostate cancer cells, and aortic endothelial cells [i) mitochondria are the principal source of intracellular ROS in epithelial cells. (ii) the growth of adenocarcinomas occur in tissue of epithelial cell origin.The rapid stimulation of intracellular ROS by platelet-derived growth factor (PDGF), epidermal growth factor (EGF), and nerve growth factor (NGF) suggests that this underlying mechanism of cell growth may be shared with other growth factors including estrogen . Exogenoal cells . The molal cells . The proal cells . Althoug2O2 and NO have been demonstrated to stimulate mitochondrial biogenesis, a process that depends on the flow of molecules into and out of the organelle [2O2 levels. In addition, MnSOD displayed an increased pattern of activity similar to mtNOS [2•- production and therefore MnSOD may dismutate O2•- generated by NO-dependent inhibition into the signaling molecule H2O2. Ethinyl estradiol, E2, and estrogen catechol metabolites at a dose of 0.25 to 5 μM are reported to increase mitochondrial O2•- in cultured rat hepatocytes and HepG2 cells [2•- is not known at this time, ROS has been demonstrated to modulate ER protein expression in various cell lines. Treatment of human breast cancer cells MCF7 and T-47D with H2O2 (2.5 μM) increased the protein level of ERβ [A characteristic of rapidly dividing cancer cells is their capacity to produce significant amounts of intracellular ROS, which has been implicated in the promotion of accelerated cell cycle activity in neoplastic cells. Mitochondria have long been suspected to play a role in the development and progression of cancers. The ROS molecules Hrganelle ,129. Sinto mtNOS . NO has G2 cells . Althougl of ERβ . In addiin vitro estrogen-induced proliferation of Syrian hamster renal proximal tubular cells [2•- from human fibroblast cells. Co-treatment with an inhibitor of IL-1β and TNF-α synthesis, pentoxifylline, inhibited stilbene estrogen-induced increase in myeloperoxidase activities, 8-hydroxydeoxyguanosine (8-OHdG) formation, mutations in the testicular genome, and prevented estrogen-induced testicular preneoplastic lesions [Evidence for the involvement of redox signaling with estrogen-induced cell proliferation has been demonstrated in several studies. Liposomes containing SOD or catalase inhibited ar cells . The cyt lesions . Recentl lesions ,135. We  lesions . Therefo2•- production [Oxidative stress has been shown to affect mitochondrial proteins of chronically estrogenized Syrian hamster kidney. A decrease in thiol/sulfhydryl groups was reported in the mitochondrial fraction at a preneoplastic stage of carcinogenesis . Estrogeoduction . Evidencoduction . Since ooduction . Since Moduction , the abs1 to S phase transition, cell growth, and transcription of cell cycle genes was induced by TrxR2N expression. TrxR2DN expression was suggested to increase intracellular H2O2, which in turn signaled cell proliferation. Although it is not clear whether estrogen can modulate the H2O2 levels of mitochondria, estrogen (10 nM–100 nM) treatment of primary human endometrial stromal cells in vitro show an increase in Trx protein and mRNA which implicate Trx involvement in cell growth and differentiation of estrogen responsive tissue [The mitochondrial thioredoxin system has been demonstrated to play a role in cell cycle progression. In general, the two antioxidant oxidoreductase enzymes thioredoxin (Trx) and thioredoxin reductase (TrxR) that compose the system modulate signal transduction properties of ROS by the reduction of intracellular disulfides. Trx acts as a protein disulfide reductant for ribonucleotide reductase and several transcription factors including p53, NF-κB, and AP-1 . Once oxe tissue . Alterate tissue . Whethernd messenger since they are short-lived (rapidly generated and degraded), produced in response to a stimulus, highly diffusible (H2O2), and ubiquitously present in most cell types. It is not known whether mitochondrial ROS like H2O2 are involved in signaling pathways that control estrogen-induced cell proliferation. In this section, we provide evidence in support of redox signaling pathways of mitochondrial origin, which may be involved in cell cycle progression of estrogen-dependent cells.Mitochondrial ROS fulfill the characteristics of a 2Protein kinases are known to participate in phosphorylation signal cascades, however, zinc finger domains contained in some proteins may allow them to participate in redox signaling networks. Zinc finger structures within a protein consist of at least two zinc-coordinated thiolates. Upon oxidation zinc is released from the protein, which converts cysteine thiol groups to disulfide. A conformational change in the protein may result in either its activation or inhibition. There are several protein kinases such as a-raf and PKC that contain zinc finger domains. In addition, zinc finger domains are also found in hormone receptors such as the GR and ER . Both PK1 restriction point [1 checkpoint are independent from the MAPK signaling pathway, a new question rises of whether mitochondria can modulate cell growth by interacting with the cytoskeleton. Mitochondria are reported to be associated with three major cytoskeletal structures, which include microtubules, microfilaments of actin, and intermediate filaments [m by its interactions with VDAC [Mechanical signals associated with cytoskeletal tension generation and cytoskeleton restructuring are a requirement for anchorage dependent cells to pass through the late Gon point . Since tilaments . Mitochoilaments . The assith VDAC .Epithelial cell spreading results from the binding of integrins to the extracellular matrix which depends on the actin cytoskeleton ,163. The1 phase of the cell cycle but also starts in the late S phase [Mitochondria biogenesis is reported to occur in the G S phase . Althoug S phase . This ch S phase . Estroge S phase . Thus, e1, and core protein I of the cytochrome bc1 complex; the α and β subunits of F1 ATPase and subunit IV of cytorochrome oxidase [The mitochondrial protein cytochrome c is known to be released to the cytosol where it initiates a signal for apoptosis. Given the role of cytochrome c the existence of other mitochondrial protein signaling molecules is a likely possibility that could mediate a diverse number of cellular processes including cell growth. It has been shown that mitochondria have the capability to export mitochondrial-matrix proteins to other cellular compartments such as the nucleus, peroxisome, endoplasmic reticulum, and secretory vesicles . For exa oxidase . The mol oxidase . It was  oxidase ,178. Sin oxidase . In addi oxidase . Based o2+ dependent neutral protease [Several proteases are known to exist in the mitochondrial matrix such as ATP-dependent human Lon protease, ATP-dependent human Clp proteinase chain P (hClpP), and Caprotease -183. Sinprotease . Low molprotease . The 44-protease . It may protease . A signiprotease . Thus, tIn summary, mitochondria are a major target of estrogen. It appears that mitochondria through its interaction with the cytoskeleton, export of cleaved signaling peptides, and/or generation of ROS may transduce signals to the nucleus for the activation of transcription factors, such as, AP-1, NF-κB, and CREB involved in the cell cycle progression of estrogen-dependent cells. These interactions between estrogen and mitochondria merit furture investigations, which may shed new light on the role of mitochondria in cell growth.


The visit to the emergency department (ED) constitutes a brief, yet an important point in the continuum of medical care. The aim of our study was to evaluate the continuity of care of adult ED visitors.We retrospectively reviewed all ED discharge summaries for over a month 's period. The ED chart, referral letter and the patient's primary care file were reviewed. Data collected included: age, gender, date and hour of ED visit, documentation of ED referral and ED discharge letter in the primary care file.359 visits were eligible for the study. 192 (53.5%) of the patients were women, average age 54.1 ± 18.7 years (mean ± SD). 214 (59.6%) of the visits were during working hours of primary care clinics ("working hours"), while the rest were "out of hours" visits. Only 196 (54.6%) of patients had a referral letter, usually from their family physician. A third (71/214) of "working hours" visits were self referrals, the rate rose to 63.5% (92/145) of "out of hours" visits (p < 0.0001). The ED discharge letter was found in 50% (179/359) of the primary care files. A follow-up visit was documented in only 31% (111/359). Neither follow up visit nor discharge letter were found in 43% of the files (153/359).We have found a high rate of ED self referrals throughout the day together with low documentation rates of ED visits in the primary care charts. Our findings point to a poor continuity of care of ED attendees. The emergency department (ED) is intended to treat medical urgencies or emergencies, but a large proportion of visits are due to problems that could be treated in the primary care setting ,2. ED seThe visit to the ED constitutes a brief, yet an important point in the continuum of medical care. In today's era of cost effectiveness and increasingly competent primary care physicians, ambulatory investigation, treatment and follow-up have largely replaced prolonged and costly hospitalizations ,4. The EThe continuation of treatment between hospital departments and the primary care physician had been issued in several studies using discharge letters audit -7. RavalTo evaluate the continuity of care after ED visits, we evaluated the ED referral and discharge letters, their content, and the documentation of the ED visit in the patients' primary care files. We have focused on discharges from the internal medicine ED. We expected that in these cases the patients would be followed up by their family practitioner.The study was conducted in the district medical center (Kaplan), serving more than 500,000 inhabitants, and in 12 primary care clinics (32 family practitioners), of The Clalit Health Services in the Rehovot region, Israel.In Israel the entire population have a national health insurance by law and each citizen can choose to be a member of one of four HMOs. Every member of the Clalit Health Services, the largest HMO in Israel, is registered to a single family physician, and have a medical record in his physician's clinic. Visits to the emergency department are regulated in the national health insurance law. A referral by a physician or by ambulance is free of charge, but this referral should be with a referral letter and not by a phone call to the ED or to the patient. A self referral may cost the patient a co-payment of up to 100 USD.We reviewed retrospectively all the charts of the ED visits for a period of one month, excluding the visits to the pediatric and the gynecologic-obstetrics EDs (see flow-chart 1). 5,898 visits documented that month, resulted in 4,256 discharges and 1,642 hospitalizations. There were 1,564 discharges from the general ED. Trauma, surgery and orthopedics accounted 2,209 discharges and the rest 483 were from other specialties .Inclusion criteria were: visit to the general ED, age above 18 years, discharge to the community  at that visit, living and getting medical care in a family medicine group practice in the Rehovot region. Visits due to accidents, trauma, surgery, orthopedics, ENT, ophthalmology and other specialities were excluded from the study. The 1,564 discharges from the general ED were reviewed and 359 were found to be eligible to this study.Two physicians reviewed independently each ED medical chart. Data extracted included: age and gender of the patient, attendance date and hour, self referral, or a referral by a physician and the final diagnosis in the discharge letter. In cases of referrals the content and format of the referral letter were assessed, including: hand writing quality and whether the referring physician referred the patient with a specific question (for example: rule out new onset angina pectoris, suspected pneumonia, please make a chest X ray etc.).Continuity of communication and care: The primary care files of ED visitors were retrieved and checked for the existence of the ED discharge letter and comments about the visit in the follow-up chart. If the discharge letter and / or any comment on the ED visit in the follow-up chart had been found the case was defined as "a case with good continuity of care".The cases in which the family physician was the referring physician we looked for documentation of the encounter prior to ED attendance."working hours" visits – when the visit took place during working hours of primary care clinics in the community (Sunday to Thursday from 08:00 to 20:00, and Friday 08:00 to 14:00), and "out of hours" visits when primary care clinics in the community are closed (from 20:00 to 08:00 weekdays, and weekends from 14:00 on Friday to 08:00 on the following Sunday).Visits to the ED were divided into A referral letter was defined as "any document written by a medical authority in the community prior to the index ED visit", including referrals from family practitioners, other practitioners in the community and arrival by an ambulance.A recurrent visit to the ED was defined as a patient's visit to ED within less than two weeks from a previous visit with the same complaint, when in both cases the patient was not hospitalized.Diagnoses at discharge were coded for a specific diagnosis and for the system involved according to the ICPC coding system.Statistical analysis: Data was analyzed using distribution analysis and χ2 tests to investigate the association between categorized variables. Student's t tests were used to analyze continuous variables. The analysis was performed using the SPSS package.During the study period there were 359 ED visits that were eligible to be included in the study  patients had a referral letter, the rest were self-referrals. Referral letters were mainly from the family practitioner (147/196, 75%), 14 (7%) from other practitioners in the community, and 35 (18%) of referrals were by ambulance. The referral letters from the community were legible in 43.4% (70/161), 46.5% (75/161) were barely legible and 10% (16/161) illegible. In only 25/161 letters  a specific question was asked by the referring physician and in another 32 (20.2%) there was only a general question.The main diagnostic groups according to the ICPC were: respiratory (15.7%), digestive system (18.1%), musculo-skeletal (15.2%) and cardio-vascular (11%). In 9.6% of the cases the discharge letter did not contain a specific diagnosis and the diagnosis fell in the "general" category. The most common specific diagnoses were: chest pain (5.9%), abdominal pain (3.9%), other respiratory tract infections (3.7%), asthma (3.1%), back pain (2.8%), COPD exacerbation (2.8%) headache (2.5%), nephrolithiasis (2.5%), vertigo or dizziness (2.5%) and gastroenteritis (2.3%).The "out of hours" visitors tended to be younger (52.2 ± 17.5 vs. 55.4 ± 19.5, p = NS)  of primary care files. The ED discharge letter was found in 50% (179/359) of the primary care files. A follow-up visit was documented in only 31% (111/359). Neither follow up visits nor discharge letters were found in 43% of the files (153/359). No associations between clinic characteristics (size, place) or family practitioner qualification and ED visit documentation was found.The Emergency Department (ED) acts as a link between community and hospital based medicine. In Israel a patient who needs non elective admission to a hospital unit must pass through the ED, either with a referral note from a medical practitioner, or as a self referral. Most ED visits, however, do not result in hospitalization, and many could be regarded as primary health care problems ,2,9. TheThe increasing role played by the ED in treating primary care problems has been discussed in a number of recent articles -11.One aspect, which is important to the ED team, is the logistics and manpower needed to optimize the treatment of these non-urgent patients in ways that will not interfere with emergencies yet providing them adequate care. It is unclear whether the capability and quality of primary care services in the ED should be improved and compete with the community family physicians. This is true especially in Israel where there is a universal national health insurance and every patient can have a personal family practitioner.The continuity of comprehensive management is expected from the family practitioner, and is gaining importance nowadays . To achiThe modes of communication are the referral letter and the discharge letter. We have found that the referral letter can be improved both in style (printed instead of illegible hand writing) and content . These problems exist in discharge letters as well .Documentation in the primary care file was poor, only one third of referrals were documented and less than 60% of discharges. This figure is between the 27%–77% that was found by others [It is well known that medical notes are poor in other areas, Miller et al  found doWith the introduction of computerized medical files in primary care clinics in our region, the need of "double writing" will disappear, and this in turn should dramatically improve documentation rate of referrals and discharges to the ED; particularly if a computerized reminder system is used to encourage follow up of referrals by the family practitioner.Israeli health care system works in regard to ED use quite different from the US and other countries. Likewhise these results may not automatically be generalized to other health care systems. This study described the written communication between the emergency department and the primary care physician, which is the first and mandatory step in establishing continuation of care. This is only one of the four dimensions of continuity of care in family practice: chronological, geographical, interdisciplinary, and interpersonal . Each ofED visits may have important implications for the patient and his family practitioner. The high rate of ED self referrals together with low documentation rates of ED visits in the primary care charts result in poor continuity of care of ED visitors.None declared.All authors read and approved the final manuscript.VS Conceived and designed the study, participated in the collection, analysis and interpretation of data and drafted the manuscript. KE Participated in the statistical analysis, interpretation of data and draft of the manuscript.OY participated in the design of the study, data collection and interpretetio hand draft of the manuscript. SN participated in the design of the study, interpretation of data and draft of the manuscript. All authors have read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


The brain-derived protein S100B has been shown to be a useful marker of brain injury of different etiologies. Cognitive dysfunction after cardiac surgery using cardiopulmonary bypass has been reported to occur in up to 70% of patients. In this study we tried to evaluate S100B as a marker for cognitive dysfunction after coronary bypass surgery with cardiopulmonary bypass in a model where the inflow of S100B from shed mediastinal blood was corrected for.56 patients scheduled for coronary artery bypass grafting underwent prospective neuropsychological testing. The test scores were standardized and an impairment index was constructed. S100B was sampled at the end of surgery, hourly for the first 6 hours, and then 8, 10, 15, 24 and 48 hours after surgery. None of the patients received autotransfusion.In simple linear analysis, no significant relation was found between S100B levels and neuropsychological outcome. In a backwards stepwise regression analysis the three variables, S100B levels at the end of cardiopulmonary bypass, S100B levels 1 hour later and the age of the patients were found to explain part of the neuropsychological deterioration (r = 0.49, p < 0.005).In this study we found that S100B levels 1 hour after surgery seem to be the most informative. Our attempt to control the increased levels of S100B caused by contamination from the surgical field did not yield different results. We conclude that the clinical value of S100B as a predictive measurement of postoperative cognitive dysfunction after cardiac surgery is limited. Despite the fact that incidence figures between 4–79% have been reported for cognitive dysfunction after cardiac surgery , diagnosSeveral studies in humans suffering from stroke of different ethiologies, have shown a rather strong correlation between serum levels of S100B and size of lesion(s) as well as outcome -17.Lately a number of studies have addressed the question whether S100B can be considered as a marker for cognitive dysfunction after cardiac surgery; however the conclusions presented are disparate. One major reason for this could be the fact that S100B is present in high concentrations in shed mediastinal blood that is retransfused to the patient by cardiotomy suction and autotransfusion, thus obscuring the measured levels of S100B early after surgery. To date, only one study have been published where this contamination was taken into account . We receThe study group comprised 56 patients who underwent coronary artery bypass graft (CABG) surgery at the Division of Cardiac Surgery, University Hospital MAS, Malmoe, Sweden and Department of Cardiothoracic Surgery, Lund University Hospital, Lund, Sweden. Only patients planned for elective CABG with cardiopulmonary bypass (CPB) as their sole procedure were included. The study protocol was approved by the local ethics committee, and patients gave a written informed consent before the study protocol was initiated. Patients with a history of stroke, transient ischemic attack (TIA), reversible neurological disorder (RIND), known carotid artery disease or other brain diseases were excluded. In order to avoid possible influence of renal disorder on the elimination of S100B, patients with known renal failure (Creatinin > 160 μmol/L) were excluded.The patients were examined for signs of neurological dysfunctions daily during the hospital stay by either experienced cardiac anesthesiologists or by experienced cardiac surgeons.®, Roche, Basel, Switzerland) or propofol (Diprivan®, Zeneca Ltd, Cheshire, England) 10 mg/kg. It was subsequently maintained with fentanyl 10 μg/kg , a continuous infusion of propofol 3–6 mg/kg/h or inhalation of isoflurane 0,5–1% (Forene®, Abbott Laboratories). Nitrous oxide (Aga Industries, Stockholm, Sweden) was used before CPB but not during or after CPB.Anesthesia was induced with midazolam 3–5 mg iv  and administered in the ascending aorta and the anastomosed vein-grafts intermittently.CABG surgery was performed during aortic cross clamping with the distal anastomosis preceding the proximal anastomosis. A tangential occluder replaced the cross-clamp during the proximal anastomosis. Antegrade cold S:t Thomas crystalloid cardioplegia was used (Cardioplegi2 at normothermia. The perfusate was cooled to approximately 32°C. Heparin (400 U/kg bodyweight) was given prior to cannulation and reversed with equal doses of protamine sulphate at decannulation.Perfusion was performed with a roller pump (Cobe Industries, Denver, Colorado, USA). The perfusion catheters and circuit were made of polyvinylchloride in the line and silicon in the pumphead. The arterial cannulation was made in the ascending aorta and venous cannulation in the right atrium by a two-stage venous cannula. All circuits contained a heparin-coated 40 μm arterial filter (Cobe Sence, Cobe Industries) and a membrane oxygenator (Cobe Duo oxygenator, Cobe Industries). The circuit was primed with approximately 1000 ml of Ringer's lactate (Pharmacia-Upjohn), 250 ml 15% Mannitol (Pharmacia-Upjohn) and 75 mmol Addex tromethamine (Pharmacia-Upjohn). Perfusion flow was non-pulsatile with a flow rate of 2.4 l/min/mAfter surgery, the patients patient were transferred to the ICU for recovery and enrolled in the sampling scheme for S100B analysis. None of the patients received autotransfusion.Serum for S100B analysis was sampled before surgery, at the end of CPB, and then 1, 2, 3, 4, 5, 6, 8, 10, 15, 24 and 48 hours after surgery. The S100B levels at these time points will be referred to as T0, T1, T2....T48. Blood samples, both arterial and venous samples, were cooled and centrifuged within 5 hours. All samples were measured by a monoclonal two-site immunoluminometric assay .Since early levels of S100B are contaminated by S100B from cardiotomy suction, an attempt was made to exclude this S100B from the levels measured one and two hours after surgery. Assuming that all of the measured S100B at the termination of CPB was a contamination, this non-cerebral S100B was eliminated with a half-life of 25 minutes, as illustrated in figure e is the estimated true levels of S100B at time t, Ct = the measured concentration of S100B at T1 or T2, C0 the concentration at the end of CPB, t the time after T0 and t1/2 the half-life of S100B.where CWe have earlier suggested that the elimination rate could be used as another measure of cerebral release , and theThe patients underwent neuropsychological testing by the same trained neuropsychologist 1–2 days before and 5–7 days after surgery. The tests used were: Mental Control, Figural Memory, Logical Memory (A/B), Visual Reproduction, Rey Auditory/Verbal Learning Test (RAVLT), Trail Making A, Trail Making B, Digit Symbol, Digit Span, Visual Memory Span, Visual Paired Associates II or Verbal Paired Associates I and RAVLT, Delayed Retention. The tests were chosen from the Wechsler Memory Scale-Revised (WMS-R), the Wechsler Adult Intelligence Scale (WAIS – R) and the Halsted-Reitan Neuropsychological Battery ,21.Differences for each sub-test were first calculated and then standardized to z-values. All sub-tests were then aggregated to create an impairment index . The impAll results were analyzed with the Statistica version 5.0 for PC. Regression analysis was performed with the least square method with a casewise deletion of missing data. For the multiple regression a backwards stepwise regression was performed to determine which variables to include in the final analysis. The initial variables included in this analysis were age, gender, perfusion time, years of education, and S100B levels at all sampling times. A p-value < 0,05 was considered significant. Unless otherwise stated numerical values are presented as mean ± 1 standard deviation.Patient demographics are presented in table The appearance of S100B protein followed the same pattern in all patients with high levels at the end of CPB and a decrease or slight increase the first hour figure . ThereafWe found a correlation between patient age and S100B levels measured up to 24 hours after bypass Table . NeitherIn multiple regression analysis, measured S100B levels at the end of CPB (T0), one hour later (T1) and age were found to explain part of the neuropsychological impairment  declare that they have no competing interests.HJ: Principal investigator recruited, enrolled patients analyzed and wrote the paperPJ: Had an integral role in the planning and the analysis, also help with writingMB: Designed neuropsychological test battery. Analyzed neuropsychological dataCB: Performed all neuropsychological testing with patientsCA: Did the S100B-analyzesSB: Mentor an principal leader of the project, who also helped with the writing.The pre-publication history for this paper can be accessed here: