Ascaris lumbricoides exhibits density-dependent egg production, a process which has a marked impact on both the transmission dynamics and the stability of the parasite population. Evidence suggests that the egg production of female Ascaris is also associated with the size of the worm. If worm size is mediated by density-dependent processes then the size of female worms may have a causal impact upon patterns of Ascaris egg production.Ascaris is dependent on the number of infecting females (worm burden) following a pattern of initial facilitation followed by limitation. Applying a negative binomial (NB) generalized linear model (GLM) and a zero-inflated negative binomial (ZINB) model we confirm that the per host female mean weight is significantly associated with per host egg production. Despite these associations, the mean weight of female Ascaris has little causal impact on patterns of density-dependent egg output. The ZINB model is able to account for the disproportionately large number of zero egg counts within the data and is shown to be a consistently better fit than the NB model. The probability of observing a zero egg count is demonstrated as being negatively associated with both female worm burden and female mean weight.We analyse data collected from a cohort of human hosts, and demonstrate that the per host mean weight (a proxy for size) of female Ascaris is statistically significantly associated with egg output, and follows a consistent pattern of facilitation preceding limitation with increasing female worm burden. Despite these relationships, incorporation of female Ascaris mean weight into models of egg output has little effect on patterns of density dependence. The ZINB model is a superior fit to the data than the NB model and provides additional information regarding the mechanisms that result in a zero egg count. The ZINB model is shown to be a useful tool for the analysis of individual-based egg output data.The mean weight of female  Density-dependent population processes can occur at each stage of a parasite's lifecycle . For theAscaris lumbricoides infections of humans, density-dependent egg production has been reported; the per capita egg output decreasing with increasing number of worms per host (worm burden) , for teenagers and adults ≤12 years. Host age is a potentially important confounding factor associated with both the number of worms per host , andples see ). Thus, rd order) of the mean of the per host mean weight of each stratum. Stratum means were centred around their overall arithmetic mean value in order to minimise multicollinearity  to reflect the potential dependence of per host net egg output on per host female mean weight the following preliminary analyses were performed to determine appropriate functional forms to describe the relationship. Per host egg output data were stratified by per host mean weight, taking the arithmetic mean per stratum, and regressing these values against polynomial functions (up to 3inearity . A problinearity ) of theiinearity  and highinearity  and implinearity ,61. Moderd order relationship, Model 1 [equation (5)] was extended to define a full model describing the relationship between net egg output, female worm burden, and worm weight adjusting for host age,Using the 3Ascaris mean weight as, respectively, 1st order nd order Ascaris per host Equation (6) is denoted Model 4. Models 2 and 3 are defined as special cases of Model 4, modelling female Λ. Count data are typically modelled assuming either a Poisson or negative binomial distribution (NBD) . For a known value of k, equation (7) is of the form of the exponential family of probability distributions [μΛ is linearly related to the covariates described in the previous section [equations (5) and (6)] and so, for a given value of k, the parameters can be estimated within the GLM framework k is the probability of observing a zero count from the NBD. Just as μΛ is linearly related to covariates via the logarithmic link function, the logit function (ln[p/(1 - p)]) can be used to linearise the relationship between p and potential covariates , and the natural logarithm of the female worm burden [ln(n)] as covariates of the probability of observing a zero count. This model was fitted to the data in each population using standard GLM procedures implemented in R using the glm function [Here variates . Univari Figures  and 4. Efunction ,61.n) and ln(w) to be statistically significantly and negatively related to the probability of observing a zero count in each population (Table nd re-infection population age was found to be positively associated with p (i.e. the probability of observing a zero count is greater in teenagers and adults than in children)  Table . The reln) Table . These mp-values are unambiguous in the baseline and 1st re-infection populations , whereas the facilitation preceding limitation pattern was only marginally preferred over limitation alone in the 2nd re-infection population . AIC supported facilitation preceding limitation in all populations. The pattern of density dependence was similar in both age groups, whereas teenagers and adults tended to harbour slightly heavier worms  indicated a pattern of facilitation followed by limitation in all populations Table . The LRSs Figure .Ascaris as a covariate improved the fit of both the NB and ZINB models in all populations  varied across populations and with the assumed probability model . In the 2nd re-infection population there was also evidence that host age was positively associated with the probability of a zero count  since many of the zeros are accounted for in the Bernoulli component of the model (Table c (the inverse measure of density dependence) tend to be lower in the ZINB models  and after 6 months re-infection (re-infection populations). An association between the per host mean weight of female Ascaris and the per host egg output is demonstrated in the three analysed populations. The functional form of this relationship is different across populations and dependent on the assumed probability model used to estimate the unknown parameters. However, comparing the zero-inflated negative binomial (ZINB) models, which provide a better description of the observed data, we see that at baseline egg output initially rises with increasing per host female mean weight before falling at very high weights, whilst in the re-infection populations, egg output rises monotonically with increasing weight. Despite these findings, per host female mean weight has little discernable causal impact on the well-characterised patterns of density-dependent egg production in A. lumbricoides [The major objectives of this study were twofold: Firstly, to determine whether there is any evidence for density-dependent processes affecting the per host mean weight of female ricoides ,70.Heterakis gallinarum infecting the ring-necked pheasant (Phasianus colchicus) [Ascaris infection is small relative to that of a human host [Ascaris antigens, on average harboured heavier worms. Additionally, negative associations have been reported between various immunological markers and the intensity of Ascaris infections [S. ratti [T. circumcincta [The convex pattern of facilitation preceding limitation has been documented in one previous study of the GI-nematode lchicus) . Constraman host  althoughfections  and re-ifections , suggestS. ratti ,74 and sumcincta ,25. The A. lumbricoides and egg production. Sinniah and Subramaniam [Ascaris infections of humans. More interesting, however, is how this association influences the host-parasite interaction and ensuing population dynamics; do host responses limit the size of worms? Are some hosts more efficient than others at doing so? Such processes and heterogeneities are known to occur in model non-human nematode systems [Two previous studies have described a positive relationship between the size of female ramaniam  dissecteramaniam  took a dramaniam ,76, so i systems ,27,28.c) remains approximately equal in the null and best-fit models in each of the three populations (regardless of the probability model). This consistency shows that the severity of density dependence is not greatly altered by the effects of female weight. Thus, egg production is limited directly by increasing female worm burden and is not simply an artefact resulting from the density dependence of female mean weight, i.e. the association between egg output and female weight does not cause density-dependent fecundity. It is noteworthy that no statistically significant density-dependent fecundity was detected in the 1st re-infection population . This is congruent with the biological interpretation of this functional form representing a decline in egg production in heavier (inferred older) worms. This would be expected to be unimportant in the populations after six months of re-infection since the life-expectancy of  2 years .β = -0.28, p-value < 0.0001, Table nd re-infection population .A. lumbricoides eggs in faecal samples [We have shown that a mixture of the negative binomial and Bernoulli distributions (ZINB model) provides a superior description of the distribution of egg output data than a negative binomial (NB model) distribution alone. Similar zero-inflated models have been used frequently in the ecological literature where datasets with many zeros are commonplace (for a review see ). In par samples .a priori in order to simplify analyses aimed at detecting epidemiologically significant covariates (i.e. covariates that directly impact upon the release of transmission stages). In taking such an approach one must again choose an appropriate distribution with which to model the now zero truncated data. Two suitable contenders are the log-normal and zero-truncated negative binomial distributions. The advantage of the former is that, via a logarithmic transformation, ordinary least squares estimation procedures can be used. For the latter, numerical maximisation of the appropriate log-likelihood function is required [The results presented in Table required ,44. Figurequired ,82 (for required ). Therefrequired .A. lumbricoides infecting a cohort of human hosts follows a pattern of facilitation preceding limitation with increasing worm burden. We verify that weight is associated with net egg output but demonstrate that this has little causal impact on patterns of density-dependent egg production. We show that a zero-inflated negative binomial (ZINB) probability distribution is superior to a negative binomial distribution in modelling individual egg output data.In this study we have demonstrated that the mean weight of female The authors declare that they have no competing interests.MW outlined the paper, performed the analyses and wrote the manuscript. AH collected the data and helped in the interpretation of the analyses. M-GB edited the manuscript for intellectual content. RMA, M-GB and AH jointly supervised the work and helped conceive the paper.Probability distribution, variance and expected value for the zero-truncated negative binomial and log-normal distributions. A file containing the probability distribution, variance and expected value for the zero-truncated negative binomial and log-normal distributions.Click here for file


Lineage-specific gene expression has been used for the identification of metastasis of cancers with unknown primary site or of disseminated cancer cells in haemopoietic compartments such as bone marrow or in lymph nodes. For the muc1, cytokeratin-19 and the CEA genes, the transcription in haemopoietic cells has been shown recently. Here, the expression of the mammary epithelium related antigens BA46 (lactadherin) and BA70 in lymphoid and myeloid cell lines, and in clinical specimens is analysed. By Northern-hybridization with specific oligonucleotides an ubiquitous transcription of both genes, independent from the provenance of cells or the chromosomal gender was found. Both mRNA molecules were amplified by rtPCR from the samples and the specificity could be confirmed by sequence analysis. Peptide-specific antibodies were raised in rabbits and used for Western-blot analysis and for immunocytochemical studies. Both antibodies reacted with total cell lysates from myeloid and lymphatic cells. In immunocytochemistry antibody P717 (anti-lactadherin) had a significant strong staining of the myeloid cell lines K562 and HL60 suggesting a participation of lactadherin in leukocyte-function. Using antibody P718, strong stains were seen in myeloid line K562 and lymphoid line ST486. In conclusion, our findings expand the results that the concept of lineage-specific gene expression is no longer valid at the molecular level. © 2000 Cancer Research Campaign


Thymic organ cultures established from mice of varyingMHC haplotypes were incubated with antigen, and the efficiency of clonal deletionassessed. We show here that clonal deletion of CD4+8+ thymocytes is sensitive to both thegene dosage and the allelic variation of MHC class II molecules expressed on thymicantigen-presenting cells. We also find that when epithelial cells in the thymic cortex are theonly antigen-presenting cells expressing the appropriate MHC class II molecules, negativeselection of CD4+8+ cells is as efficient as when antigen is presented on all thymicantigen-presenting cells. These studies demonstrate that the induction of self-tolerance viaclonal deletion in the thymus is a function not only of antigen concentration, but also ofMHC class II cell-surface density. In addition, together with the reports of others, theseresults confirm that cortical epithelial cells can mediate negative selection, and demonstratethat they do so in the intact thymic microenvironment.One of the major mechanisms for establishing self-tolerance is the clonal deletion ofself-reactive T cells during their development in the thymus. Using a TCR transgenic mousemodel, we have established a quantitative


Prostate cancer is the second most common malignancy in males and the leading cause of cancer death. Prostate cancer is initially androgen dependent and relies upon the androgen receptor (AR) to mediate the effects of androgens. The AR is also the target for therapy using antiandrogens and LHRH analogues. However, all cancers eventually become androgen independent, often referred to as hormone refractory prostate cancer. The processes involved in this transformation are yet to be fully understood but research in this area has discovered numerous potential mechanisms including AR amplification, over-expression or mutation and alterations in the AR signaling pathway. This review of the recent literature examines the current knowledge and developments in the understanding of the molecular biology of prostate cancer and hormone refractory prostate cancer, summarizing the well characterized pathways involved as well as introducing new concepts that may offer future solutions to this difficult problem. Prostate cancer is the commonest malignancy in men, accounting for 24% of all cancers in the UK in 2003. The treaAs a result, treatment for locally advanced and metastatic prostate cancer targets the AR by reducing the levels of androgens or by inhibiting the activation of the AR. Androgens are removed by either surgical or chemical methods using luteinising-hormone-releasing-hormone (LHRH) analogues with or without the addition of antiandrogens. Initially, prostate tumors regress in response to androgen deprivation in up to 80% of cases. However,Androgens are essential to the normal development and biology of the prostate. The majority of testosterone is produced by the testes, with a smaller contribution of androgens (5%) from the adrenal glands. These androgens are metabolized by 5α-reductase to dihydrotestosterone (DHT) which binds to the androgen receptor (AR). Ligand binding initiates phosphorylation, homodimerisation of the AR and dissociation of heat-shock proteins, allowing translocation of the AR complex to the nucleus. Here the AR binds to specific DNA sequences called androgen response elements (ARE) promoting transcription of androgen-responsive genes. Such genes control a range of cellular events such as growth, differentiation and apoptosis . The AR As hormone refractory prostate cancer continues to grow in the presence of antiandrogens the term hormone independence may be misleading as it implies that the AR is no longer required for growth. However, the AR is expressed throughout the progression of prostate cancer, including >80% of hormone refractory tumors, suggesting that AR signaling remains essential.11 It haset al demonstrated that over-expression of AR cDNA, mRNA and protein levels were the only consistent and significant differences.[Amplification of the AR gene is rarely identified in untreated cases of prostate cancer. Using comparative genome hybridization (CGH) and fluorescent in-situ hybridization (FISH), 30% of treated cases exhibited AR amplification.1415 Pati1417ferences. In patieferences.Despite medical or surgical castration, tumor levels of androgens in human prostate samples, in particular DHT, have been shown to remain at levels sufficient to transactivate the AR in cell line studies. AlthoughMutations in the AR are uncommon (0-4%) in untreated prostate cancer and those treated with surgical castration. However, in hormone refractory tumors the incidence of mutations increases by up to 50%. Over 70 Modulation of AR activity by co-repressors and co-activators The ARE-bound AR binds a number of proteins to enable efficient recruitment of the basal transcriptional machinery and transcription of androgen-regulated genes. The transcriptional activity of the AR is enhanced by co-activators and inhibited by co-repressors although some proteins can either promote or repress transcription depending upon the cellular context. Co-activ37et al[et al found no significant difference in expression.[The p160 co-activators are known to interact with CREB-binding protein (CBP) and its homologue p300 which have intrinsic HAT activity.40 The pret al showing pression. As yet npression.et al found a decrease in the median expression of SRC-1 suggesting that sample collection, processing and the sensitivity of the detection method may influence co-activator expression studies.[Probably the best characterized co-activator of the AR is SRC-1. In cell line studies reduction of SRC-1 expression significantly reduced growth and altered AR target gene regulation in the LNCaP cell line whereas it had no effect on the growth of the AR-negative PC-3 and DU145 prostate cancer cell lines, further emphasizing the need for an intact AR.45 However, studies.GRIP-1/TIF-2 has previously been shown to bind the steroid receptors including the AR via its LBD and promote transcription of androgen-regulated reporter genes. The AR mutation N727K results in sub-fertility at least in part by abrogating GRIP-1/TIF-2 binding. Using domain constructs it was shown that GRIP-1/TIF-2 enhances AF-2 but not AF-1 mediated AR transactivation. BicalutaExpression of RAC-3  was higher in prostate cancer cell lines expressing the AR and has been shown to promote ligand-independent activation of the Akt pathway. RAC-3 mRNA and protein expression in prostate cancer cells has been shown to correlate with tumor grade and stage and increased expression correlates with poor survival in clinical studies.Adaptor proteins associated with receptor internalization at the cell surface have also been reported to be prostate cancer biomarkers and to act as transcriptional co-regulators. Two examples of these proteins are Huntingtin Interacting Protein 1 (HIP1) and cyclin G-associated kinase (GAK), both of which were initially implicated in clathrin-mediated receptor trafficking.52 Subseq535554Steroid receptor activity can also be modified by co-repressors which inhibit transcription by blocking co-activators binding and recruiting histone deacetylases (HDACs) and repressor proteins such as Sin3A. This HDA59Classically, activation of the AR via the binding of androgens initiates receptor phosphorylation and/or acetylation, homodimerization dissociation of heat-shock proteins, allowing translocation of the AR complex to the nucleus. The AF-1 region of the N-terminal of the AR can be activated even in the absence of ligand thereby circumventing current hormonal therapies. Ligand-independent activation induces phosphorylation and acetylation of the AR altering its conformational and subsequent transactivation. Phosphorylation increases AR stability and stabilizes AR homodimers increasing AR signaling without ligand. However,The PI3K-Akt pathway is involved in processes controlling cell growth, survival, cycle regulation and apoptosis. Following growth receptor activation, PI3K phosphorylates phosphatidylinositol -bisphosphate (PIP2) to phosphatidylinositol -trisphosphate (PIP3). Akt and its activating kinases, phosphoinositide-dependent kinases 1 and 2 (PDK1 and PDK2), then localize to the membrane. Here, activated Akt can activate a myriad of substrates and consequently a vast number of intracellular events including phosphorylation of AR. A recentet al reported that although there was a slight increase in ERK and p38 in well-differentiated cancers, cells from hormone refractory prostate cancer had reduced or absent activated expression of isoforms.[et al found a decrease in activated form phospho-MAPK/ERK in high-grade tumors.[Mitogen-activated protein kinases (MAPK) are a family of serine/threonine protein kinases involved in many cellular programs such as cell proliferation, cell differentiation and apoptosis. The MAPK signaling cascades are organized hierarchically into three-tiered modules: MAPK-kinase kinases (MAPKKKs) are in activated by interaction with the family of small GTPases and/or other protein kinases. MAPKKKs are phosphorylated and activate (MAPKKs), which in turn phosphorylate and activate MAPK-kinases (MAPKs). The MAPK pathways terminate with the proteins JNK, ERK and p38 which are known to be involved in both anti- and pro-apoptotic processes. There is conflicting evidence regarding the significance of the MAPK pathway in prostate cancer progression. Initial reports suggested a significant correlation between the activation of MAPK enzymes ERK1 and ERK2 and tumor grade, with 70% of high-grade tumors exhibiting activation. In two pisoforms. Furtherme tumors.Her-2/Neu is known to play a significant role in the progression of breast cancer raising interest in this molecule as a potential target in prostate cancer. Her2/Neu can activate AR via the MAPK and PI3K-Akt pathways and over-expression in LNCaP cells inhibits growth arrest by 35% compared to wild-type LNCaP cells. The potential importance of Her-2/Neu was highlighted in a xenograft model used to produce progressively more androgen-independent tumors, in which the level of Her-2/Neu expression increased 25-fold. This is reinforced by human immunohistochemical studies that demonstrate a significantly positive correlation between Her-2/Neu expression and hormone independent status when comparing hormone-naïve and advanced hormone refractory disease.71et al compared biopsy samples from the same patient taken before and after the development of hormone refractory disease and found a significant increase in EGFR from 23 to 43% after hormone relapse.[Growth factors and their receptors have previously been shown to be essential for prostate growth and differentiation during development, in particular FGF-7 and 10. FGF-8 an relapse. Other st relapse. While thIn addition to growth factor signaling other extracellular proteins are known to activate cell surface receptors and the AR. The best characterized of these proteins is interleukin-6 (IL-6), a cytokine previously linked to a number of malignancies including renal, myeloma and prostate. IL-6 has wide-ranging cellular effects consistent with activation of multiple pathways including MAPK and PI3-Akt. Cell studies have confirmed that IL-6 can induce ligand-independent AR transactivation via a mechanism which is blocked by bicalutamide and inhibitors of MAPK and protein kinase A. When IL-2β1 and CD133 as markers.[The classical stochastic model of cancer development is based on the theory that every cell within a tumor has the potential to form a new tumor colony. However, the stem cell model of tumorigenicity proposes that it is a minority of specialized stem cells that give rise to cancer cells. Prostate markers. However,The development and progression of prostate cancer is a complex process. The androgen signaling pathway and its interaction with other pathways impacts on cellular processes from growth, cell cycle, differentiation to growth arrest and apoptosis. Through adaptation and alteration cells become tumorigenic. Initially this process can be halted by manipulating the cells’ requirement for androgens although eventually this treatment fails and cancer cells resume growth. The terms ‘androgen independent’ and ‘hormone refractory’ may be misnomers as the AR appears to maintain a role in cancer progression as demonstrated by its continued and even increased expression. There is also evidence that despite castration, both surgical and medical, the prostate retains a level of androgen that is high enough to induce AR transactivation in prostate cancer cell lines. The AR mutations and over-expression also enable transactivation to occur at low levels of androgen as well as decreasing ligand specificity. The upregulation of co-activators and possible downregulation of co-repressors further potentiate these effects. Alternative pathways involving growth factors and receptors and IL-6 have been shown to interact with the androgen signaling pathway enabling transactivation to occur even in the absence of ligand.These processes are unlikely to operate independently. In fact the heterogeneity of prostate cancer, both hormone-naïve and hormone refractory, indicate that a multifactorial, multistep process is the most plausible. This could be a double-edged sword. The presence of numerable potential targets and markers is encouraging, particularly if tumor profiling can be utilized. However, it is also an indication of the likely complexities to be faced when designing therapies for the multiple types of prostate cancers. Recent advances have highlighted many potential and targets for pathway inhibition. By targeting multiple pathways, including AR signaling, it is feasible that it may possible to treat patients with tumor-specific ‘tailor-made’ therapies in the future.


Because Endomyocardial Biopsy has low sensitivity of about 20%, it can be performed near to myocardium that presented as Late Gadolinium Enhancement (LGE) in cardiovascular magnetic resonance (CMR). However the important issue of comparing topography of CMR and histological findings has not yet been investigated. Thus the current study was performed using an animal model of myocarditis.In 10 male Lewis rats Experimental Autoimmune myocarditis was induced, 10 rats served as control. On day 21 animals were examined by CMR to compare topographic distribution of LGE to histological inflammation. Sensitivity, specificity, positive and negative predictive values for LGE in diagnosing myocarditis were determined for each segment of myocardium. Latter diagnostic values varied widely depending on topographic distribution of LGE and inflammation as well as on the used CMR sequence. Sensitivity of LGE was up to 76%  and positive predictive values were up to 85% , whereas sensitivity and positive predictive value dropped to 0-33% (left inferior myocardium).Topographic distribution of LGE and histological inflammation seem to influence sensitivity, specifity, positive and negative predictive values. Nevertheless, positive predictive value for LGE of up to 85% indicates that Endomyocardial Biopsy should be performed "MR-guided". LGE seems to have greater sensitivity than Endomyocardial Biopsy for the diagnosis of myocarditis. The diagnosis of acute myocarditis is still challenging as its clinical presentation is variable. It can mimic acute myocardial infarction with symptoms of acute heart failure as well as present as silent course . ElevateTo date the important issue of comparing the topographic distribution of LGE to the histologically proven topographic distribution of myocardial inflammation in the whole myocardium has not been investigated. Most clinical studies compared CMR-findings to Endomyocardial Biopsy, thus data concerning sensitivity and positive predictive value for LGE in CMR, validated in animal model of myocarditis with the possibility to examine the whole myocardium is missing. Experimental Autoimmune Myocarditis (EAM) in a rat model is an established animal model to display acute human myocarditis-8 as itsThe main aim of the current study was to evaluate, if areas of LGE have identical topographic distribution as compared to histologically proven areas of inflammation; further to explore possible correlations between LGE and serology  and between LGE and histological severity of myocarditis.Twenty male Lewis rats , aged 6-8 weeks, weighing 250-300 g were used in this study. Animals were randomized to control (n = 10) and to experimental group (n = 10). Animals were kept under standard conditions with a mean temperature of 22°C ± 2°C, a mean relative humidity of 55% ± 10 and a defined day-and-night-rhythm of 12 h light and 12 h dark. The study was approved by the governmental committee and our institutional animal research review board.Induction of EAM was performed as described before . BrieflyOn days 1, 7 and 21 the retrobulbar venous plexus of all animals was punctured, 0.5 ml blood was extracted and serological levels of troponinT, NT-proBNP and haptoglobin were determined. In humans as well as in rodents troponinT is a sensitive marker for cardiac damage whereas All animals were examined by clinical CMR  using a human finger-surface-coil as receiver fixed on the animals chest on day 21. The value of such coil is to maximise the signal to noise ratio (SNR), as the SNR for a coil drops as a function of the square of the distance between the coil and tissue. Consequently, this increases the sensitivity of image analysis . All CMRAs recommended in literature inversioFollowing IR-Turbo-FLASH-examination, cardiac arrest was achieved by overdosing propofol and Turbo-Spin-Echo-Sequences (TSE) (FoV read 100 mm/FoV phase 57.8%/Slice thickness 2 mm/TR 742 ms/TE 17 ms/Averages 3/Flip angle 180°/Fat saturated/base resolution 448/Phase resolution 100%) with a higher signal-to-noise-ratio were performed, first without and directly afterwards with fat saturation.Two radiologists, who were blinded to the results of histopathological examination, with 5 and 8 years experience in CMR analysed MR images in consensus. Areas of LGE were traced by manually drawing regions of interest (ROI) using a commercially available PACS-System . For each CMR-sequence  in three representative slices from heart base to apex the area of myocardium that showed LGE was calculated as a percentage of the whole surface area of the myocardium in the respective slice; percentages of LGE-areas were summed up for the respective CMR-sequence and for each animal separately.In identical slices topography of LGE was classified according to a 7-segment-model of the myocardium  and finally embedded in paraffin. In 2 μm thick, Hematoxylin-Eosin (H.E.) stained slices the severity of myocardial inflammation was determined by the following histological criteria according to our previous research :densitiy of inflammatory infiltration (graded 0-3), strength of inflammatory destruction with rarefaction and pushing-apart of heart muscle fibres (graded 0-3), occurrence of necrosis (graded 0-3), occurrence of pericarditis (graded 0-2). Results were allied into a mircoscopic-score-system, with a maximum score of 11 points, to express severity of myocarditis.® 5.0, Soft Imaging System, Münster, Germany). In identical slices distribution of inflammation was encoded using the same segment model as for LGE-distribution.For comparison of LGE-areas with histologically proven areas of inflammation, infiltrated areas were bordered manually in three representative slices from base to apex in a way similar to ROI drawing in CMR images. Area of inflammation was expressed as percentage of the whole slice. Measurement was performed using a dedicated software .All statistical analyses were performed with dedicated software . Due to non-symmetric distribution of serological parameters  and ordinal scale of macroscopic and histopathological scores we had to use non-parametric statistics on these data. Thus, all correlations were calculated by bivariate correlation analysis using Spearman's correlation coefficient; significant differences of serological parameters between experimental and control group were evaluated by the Mann-Whitney test. Averages; averages for macroscopic and histopathological scores are expressed as median.In each CMR-sequence with associated slices, four-field-tables, expressing sensitivity, specificity, positive and negative predictive values for LGE, were used to display accuracy of CMR. Histopathological analysis was defined as gold standard.Results were considered to be significant at p < 0.05.All animals of the control group were histopathologically healthy and none revealed LGE by CMR-examination, in contrast all animals of the experimental group (n = 10) had histologically proven myocarditis.Histologically proven inflammation was predominantly located in the anterior and lateral wall of right and left ventricle  sensitivity and positive predictive value were best "left anterior" and "left lateral"  sensitivity and positive predictive value were highest if LGE was located "left anterior" and "left lateral" .A high density of inflammatory infiltration with a subepicardial accentuation in combination with destructed heart muscle fibres that were pushed apart was a typical histological finding in the experimental group; the median microscopic score was 9 (range 1-11). All animals of the control group presented with histologically healthy myocardial tissue.The extent of LGE-areas measured in Turbo-FLASH-sequences correlated highly with the histopathological severity of myocarditis  by MR examination is more difficult and resulted in low sensitivity. On the other hand it is possible that myocardial inflammation located in the left inferior ventricular wall and in the septum had caused mainly extracellular edema and hardly histologically verifiable myocardial damage as found in histology. In consequence raised interstitial space could lead to LGE without a histologically verifiable, corresponding myocardial inflammation, resulting in low positive predictive values. Furthermore, technical issues such as field inhomogenity of reception coil and motion artefacts could have an influence on our described results and might lead to differences in accuracy of CMR for different myocardial locations.As described in results, sensitivity as well as positive predictive values varied widely dependending on the location of LGE and examined CMR-sequence. In general, inflammations located in the left anterior and lateral ventricular wall were identified by Turbo-FLASH-sequences in 61.54-76.92% whereas sensitivity dropped to 0-20% for inflammations located in the left inferior myocardium and in the septum; LGE located in the left anterior and lateral ventricular wall had high positive predictive values (75%-80%) in Turbo-FLASH-examination. Possible hypotheses for dependence on location of LGE  and inflammation (sensitivity) could be: We believe that in Experimental Autoimmune myocarditis inflammation occurs primarily in the left anterior and lateral ventricular wall and delayed in the left inferior myocardium and septum and thus on day 21 inflammation could have been on different stages inside the myocardium as proved by histology. Cardiac lesions located "left inferior" and "septum" were of small size and only found in three animals. As it is challenging to compare histological segments with exactly corresponding MR-slices, we think that finding cardiac lesions with a small extent  and MR examination (3 mm) has to be seen critically. As the histologically proven area of inflammation stretched across several slices, we do not think that differences in slice thicknesses had a strong influence on data analyses. Another limitation of the study is that criteria used for evaluation is center specific which may be difficult to put the results into perspective with other reports. We did not use Dallas criteria as their use often results in false-negative cases of myocarditis and they seem to be no predictor of outcome in myocarditis; insteadThe current study is based on an animal model for acute autoimmune myocarditis. In humans acute myocarditis is mostly caused by viral infection. However, in our animal model it is possible to perform CMR-examination and histolgical analysis of the whole myocardium on the same day. As we wanted to show the reliability of CMR in showing topography of myocardial inflammation, we do not think that different aetiologies  inhibits transfer of current study results to humans.Using a 1.5T clinical scanner in combination with clinical MR-sequences has to be seen as a limitation regarding spatial resolution. However most centers use 1.5T scanners, thus we think, in this way our result can be compared to further studies more easily. Finally, we did not provide data about early enhancement, nor about T2-weighed images as proposed by Friedrich et al .We were able to show that EAM as a model of human myocarditis can be detected by clinical CMR providing the opportunity for further fundamental research. The extent of LGE correlates to the histological severity of myocarditis and to serum-levels of troponinT on day 21. Areas of LGE have nearly identical topographic distribution as compared to histologically proven areas of inflammation. Late gadolinium enhancement seems to depict cardiomyocytes necrosis and thus should be regarded as a marker indicating more severe myocarditis. In conclusion, the accuracy of CMR in diagnosing myocarditis is high enough to guide endomyocardial biopsy.The authors declare that they have no competing interests.HK conceived the study and together with PE carried out the induction of myocarditis as well as MRI- measurement and -analysis. FH adapted MR-sequences to the animal conditions. RB performed histopathological analysis. HA accomplished together with HK and PE statistical analysis. TJV was involved in drafting the manuscript and revised it critically. All authors read and approved the final manuscript.


Border disease virus (BDV) causes important reproductive losses, and eradication strategies focus on the identification and removal of persistently infected animals arising after in uterine infection. BDV infection dynamics were studied in 13 ewes experimentally infected with BDV-4 genotype at 3 phases of pregnancy  by quantification of viral RNA in blood collected on days -1 to parturition using quantitative real-time RT-PCR (qRT-PCR). Viral RNA loads were also measured in blood/foetal fluid and tissue samples from their offspring at lambing . qRT-PCR results were compared with those obtained by conventional RT-PCR and used to predict persistent infections.Viral RNA was detected in the ewes between days 2-15 p.i. The viraemia reached its highest peak between days 6-7 p.i. with a second peak at days 11-12 p.i. qRT-PCR was significantly faster to perform (less than 1 h) than conventional RT-PCR and detected BDV RNA in more ewes, being detection more continuous and prolonged in time. The virus was detected in peripheral blood in a higher percentage of lambs than in tissues, where differences in viral genome copies were more marked. Skin and cerebral cortex showed the highest viral RNA loads, and spleen and spinal cord the lowest. High viral RNA loads were observed in several animals in group B and all in group C, infected during middle and early foetal development, respectively, but also in one lamb from group A, infected during late foetal development. Serology and viral genome copy number estimates in blood and tissues were used to establish a quantitative cut-off threshold for transient viraemia.Viral RNA quantification showed potential for the discrimination between persistent infections and transient viraemia using single-time point blood sampling and raised questions regarding foetal immune system development and the occurrence of persistent infections. The genus Pestivirus (family Flaviviridae) comprises four main species: bovine viral diarrhoea virus types 1 and 2 (BVDV 1 and BVDV 2), border disease virus (BDV) of sheep, and classical swine fever virus (CSFV), each of them subdivided into several genetic subtypes. In sheep, infection of pregnant ewes with BDV during early or mid gestation results in abortion, stillbirths, or unviable lambs. Infections during early embryonic and foetal development can lead to the birth of immunotolerant and seronegative persistently infected (PI) animals that shed the virus throughout their lifetime and are the continuous source of infection within and among flocks. Border disease (BD) has been reported in several regions in Spain  where itPestiviruses are small enveloped viruses with a genome consisting of a positive-sense single stranded RNA molecule of approximately 12.3 kb. It is comprised of a long single open reading frame flanked by untranslated regions (UTR) of about 380 nucleotides at the 5'-end, and 230 nts at the 3'-end . The 5'-In this article, we describe the performance of a real-time RT-PCR assay for the detection and quantification of pestiviruses on different types of samples obtained from an experimental infection carried out on pregnant ewes challenged with the local ovine pestivirus (BDV-4 genotype) in different gestation periods as described elsewhere . BDV infEU711348). The outcomes of pregnancy included 3 aborted foetuses, 7 stillborns and 15 lambs.Samples were obtained from an experimental infection carried out on pregnant ewes as described elsewhere . BrieflyIn experimental ewes, blood samples were collected daily during the first two weeks and weekly until lambing, adding up to a total of 293 blood samples. Regarding the offspring, pre-colostral blood samples were taken from live lambs just after lambing, and cardiac blood or foetal fluids were collected from stillborns and foetuses. Presence of BDV antibodies in the offspring as determined by ELISA had been reported elsewhere . Live laRNA was extracted with a QIAamp Viral RNA Mini kit (Qiagen) as previously described . Blood a8-10 copies) of the RNA positive control in triplicate for the standard curve. The efficiency of the real-time PCR amplification (E) was calculated for each experiment using the formula E = 10-1/m, where m is the slope for the standard curve. Three non-template negative controls were also included in each plate.Detection capacity of the kit assessed by bioinformatic analysis of all the pestivirus sequences available in GenBank as of May 2009 indicated that the primers and probe used would recognise 99.9% of the pestivirus isolates. Furthermore, a panel of pestiviruses of different types including CSFV , BDV  and BVDV  was empirically tested. The analytical specificity was evaluated using RNA from Tick-borne encephalitis virus, Spanish sheep encephalitis virus, bluetongue virus, influenza virus, maedi-visna virus and pulmonary adenomatosis virus. The linearity and analytical sensitivity of the real-time RT-PCR quantification protocol were assessed on 10-fold serial dilutions of a recombinant RNA standard (synthesised in vitro from a cloned RT-PCR fragment in plasmid DNA). For viral RNA load quantification, samples were analysed in triplicate, and each plate contained six to eight ten serial dilutions  procedure of the SAS statistical package version 9.1 . In addition, comparison of the slopes was performed using the CONTRAST statement of the GLM procedure in the SAS statistical package.The level of agreement between methods , but none of the non-pestiviral RNA samples. In spite of the reduced number of viruses used, neither the flaviviruses  nor other common viruses of sheep  used to test the analytical specificity, showed any cross-reaction.2) was 0.998. Quantification was linear over at least 7 log units and the analytical sensitivity was set at 10 copies/reaction. The analyses of variance of the Ct values of the standard curves showed no replicate nor plate effect (p > 0.25). Similarly, the slopes of the standard curves from the different plates did not significantly differ (p > 0.40), demonstrating a good reproducibility from run to run.The amplification efficiency reached 1.91 and the correlation coefficient  than that observed in lambs from group C , but no statistical differences were observed between lambs from groups A and B or B and C  were negative in all 10 tissues tested, though only 2 of them (Nos. 6 and 16) were also negative in blood (Table P < 0.05), with significantly higher viral RNA loads in group C. Animals from group A had significantly lower viral RNA loads in every tissue analysed compared to those in group C. The only exception was lamb No. 4, born to a ewe from group A, which was positive in blood and all 10 tissues, with particularly high viral RNA loads in spleen, thymus, thyroid and kidney. No differences were observed between animals from groups B and C. Mean tissue genome copy numbers and organs with highest viral RNA load are indicated for each lamb in Table Differences in viral genome copies were more marked in tissues than in blood. Taking into account the positive animals (at least one positive tissue), differences were observed among groups , we assessed the usefulness of qRT-PCR to discriminate between a persistent infection and a transient viraemia using single-time point blood sampling. Classifying as transient viraemic animals those with non-colostral antibodies or without antibodies but low levels of viral RNA in blood  and tissues , kidney and thyroid gland appeared to be the most reliable tissues for detecting the highest viral RNA loads. In a previous work, thyroid gland and kidney also gave the highest percentages of positivity by conventional RT-PCR, together with lymph nodes . ConversThe qRT-PCR tested here showed to be a rapid and highly sensitive method for the detection and quantification of pestiviruses in blood and different types of ovine tissues. Quantitative detection by qRT-PCR allowed us to monitor the BDV infection dynamics in experimentally infected sheep and study the distribution of viral RNA genome loads in different tissues from their offspring in relation with the moment of infection during gestation. Viral RNA quantification also proved to be an additional powerful tool for diagnosis and monitoring pestivirus infection in sheep. Although further studies are needed, questions regarding foetal immuno system development and the occurrence of persistent infections were raised.Vacunek S.L., the company manufacturing the qRT-PCR kit used in this study, is a spin-off from NEIKER and the authors from NEIKER are holders of a symbolic share in an organization linked with Vacunek.AH participated in the molecular design and the coordination of the study and drafted the manuscript. IS participated in the molecular design and carried out the molecular analyses. FB participated in the molecular design and critically revised the manuscript. EM participated in the experimental infection and critically revised the manuscript. RAJ performed the statistical analyses and participated in the critical reading of the publication. ALG conceived of the study and participated in its design and coordination, and helped to draft the manuscript.


The AI showed a positive correlation to the mitotic activity index (MAI) (P = 0.0001), histological grade (P< 0.0001) and worse tumour differentiation. Patients with high AI showed shorter overall survival than patients with low AI in the total group as well as in the lymph node-positive group. Tumour size, MAI, lymph node status and AI were independent prognostic indicators in multivariate analysis. The AI was shown to be of additional prognostic value to the MAI in the total patients group as well as in the lymph node-positive group. The correlation between the AI and the MAI points to linked mechanisms of apoptosis and proliferation. Since apoptotic cells can be counted with good reproducibility in H&E-stained tumour sections, the AI may be used as an additional prognostic indicator in invasive breast cancer. © 2000 Cancer Research CampaignApoptosis plays an important role in tumorigenesis. Tumour growth is determined by the rate of cell proliferation and cell death. We counted the number of apoptotic cells in haematoxylin and eosin (H&E)-stained tumour sections in series of 172 grade I and II invasive breast cancers with long-term follow-up. The number of apoptotic cells in ten high-power fields were converted to the number of apoptotic cells per mm


Mass spectrometry is increasingly being used to discover proteins or protein profiles associated with disease. Experimental design of mass-spectrometry studies has come under close scrutiny and the importance of strict protocols for sample collection is now understood. However, the question of how best to process the large quantities of data generated is still unanswered. Main challenges for the analysis are the choice of proper pre-processing and classification methods. While these two issues have been investigated in isolation, we propose to use the classification of patient samples as a clinically relevant benchmark for the evaluation of pre-processing methods.Two in-house generated clinical SELDI-TOF MS datasets are used in this study as an example of high throughput mass-spectrometry data. We perform a systematic comparison of two commonly used pre-processing methods as implemented in Ciphergen ProteinChip Software and in the Cromwell package. With respect to reproducibility, Ciphergen and Cromwell pre-processing are largely comparable. We find that the overlap between peaks detected by either Ciphergen ProteinChip Software or Cromwell is large. This is especially the case for the more stringent peak detection settings. Moreover, similarity of the estimated intensities between matched peaks is high.We evaluate the pre-processing methods using five different classification methods. Classification is done in a double cross-validation protocol using repeated random sampling to obtain an unbiased estimate of classification accuracy. No pre-processing method significantly outperforms the other for all peak detection settings evaluated.We use classification of patient samples as a clinically relevant benchmark for the evaluation of pre-processing methods. Both pre-processing methods lead to similar classification results on an ovarian cancer and a Gaucher disease dataset. However, the settings for pre-processing parameters lead to large differences in classification accuracy and are therefore of crucial importance. We advocate the evaluation over a range of parameter settings when comparing pre-processing methods. Our analysis also demonstrates that reliable classification results can be obtained with a combination of strict sample handling and a well-defined classification protocol on clinical samples. With the use of mass spectrometry techniques such as MALDI-TOF and SELDI-TOF, it has become possible to analyse complex protein mixtures as found in serum relatively quickly. This has led to the discovery of a large number of proteins and protein profiles associated with various types of diseases -4. HowevIn this study we investigate some of the problems associated with the generation and analysis of SELDI-TOF MS datasets. In order to eliminate potential pre-analytical biases due to sample handling, we used strict protocols for sample collection, storage and experiments .et al. -propane-sulfonicacid), and 1% dithiothreitol (DTT)) at room temperature for 60 minutes. 10 μl of this solution was mixed with 90 μl binding buffer  and added to a CM10 ProteinChip array. For the Q10 ProteinChip array 10 μL of this solution was mixed with 90 μL binding buffer (50 mM Tris [tris(hydroxymethyl)aminomethane] HCl, pH 8.0, 0.1% Triton X-100), before being added to the ProteinChip array. Before incubation with serum samples, the ProteinChip arrays were washed twice for 5 minutes with binding buffer . In bothAfter 45 minutes incubation at room temperature the ProteinChips were washed with binding buffer . Next, the CM10 ProteinChip arrays were washed with 50 mM phosphate buffer, pH 6  and the Q10 ProteinChip arrays with Tris buffer pH 8 . After the final buffer wash each chip was quickly washed with HPLC-grade water and allowed to dry. 5 μL of matrix (sinapinic acid (10 mg/ml) in 50% acetonitrile and 1% trifluoroacetic acid) was added to each spot on the ProteinChip array twice, allowing the applied matrix solution to dry between applications.The arrays were read on a PBSII reader  with laser intensities of 175 (ovarian cancer) and 165 (Gaucher), a detector sensitivity of 6 and a detection size range between 1.5 and 20 kDa (ovarian cancer), 1 and 10 kDa (Gaucher). The spectra were calibrated using the All-in-one Peptide Molecular Weight mix . Peptides used for calibration were bovine Insulin β-chain (3495 Da), Human Insulin (5807 Da) and Hirudin BHVK (7033 Da). Calibration was performed once before measuring the CM10 ProteinChip arrays in rapid succession. Q10 ProteinChip arrays were calibrated individually by using a spot on every ProteinChip array for calibration mixture.Pre-processing was done with the commercial ProteinChip Software  and its Biomarker Wizard module. Baseline correction was applied to all spectra. The algorithm is a modified piecewise convex-hull that attempts to find the bottom of the spectra and correct the peak height and area . SpectraOn the Gaucher dataset spot-to-spot calibration was performed. A set of peaks that is present in all our spectra was chosen to determine the correction factors for the different positions on a ProteinChip array. The correction factors were applied to the corresponding mass spectra and used in the recalculation of the masses.Peak detection was performed with the Biomarker Wizard module in the mass range from 1.5 to 50 kDa (ovarian cancer), 1 to 10 kDa (Gaucher). Biomarker Wizard groups peaks of similar molecular weight across spectra. The algorithm is divided in two passes, the first pass detects well-defined peaks with a high specificity and forms clusters around them. In the second pass smaller peaks are added to an existing cluster. Four parameters have to be specified for peak detection with Biomarker Wizard: (i) First Pass ), (ii) Min Peak Threshold , (iii) Cluster Mass Window (% of mass), and (iv) Second Pass (S/N). The First Pass S/N threshold specifies the sensitivity of the first pass of peak detection. The Min Peak Threshold is the minimum number of spectra, as a percentage of all spectra, in which a peak must be present in order to form a cluster. A cluster will not be formed around a peak if it is not present in the requisite number of spectra, and the label is deleted. Cluster Mass Window specifies the width of the mass window as a percentage of a peak's mass. This determines the width of a cluster as a function of molecular weight. The Second Pass S/N threshold specifies how to populate the clusters from the first pass with peaks that were too small to be found in the first pass.For both datasets, we used three typical different peak detection settings with increasing stringency  scripts in various ways. A script was written to read in the raw data (XML) into an appropriate Matlab structure. Furthermore, in order to fit an accurate baseline, the low-mass area of the spectra that is saturated with matrix peaks was ignored using a conservative cut-off of 1500 Da (ovarian cancer dataset) or 1000 Da (Gaucher dataset). The spectra were also truncated at their high-mass end with a cut-off of 50000 Da (ovarian cancer dataset) or 10000 Da (Gaucher dataset). This was done because a long noisy tail can bias smoothing towards the noise. A further addition to the original Cromwell software as described by Coombes et al.  was madeAs with Ciphergen pre-processing, we used three different peak detection settings with increasing stringency for S/N. We used S/N settings of 1, 3, and 5 (Cromwell A-C). This way we covered a broad range of detected peaks, going from about 100 (setting C) to 200–500 (setting A). Note that a signal-to-noise ratio of 3–5 has been recommended by the developers of Cromwell .For the ovarian cancer dataset, CM10 and Q10 ProteinChip array data were analyzed with three different pre-processing settings for both Cromwell and Ciphergen (12 configurations). For each pre-processing method and settings we also made a combined CM10/Q10 dataset by taking the union of the CM10 and Q10 peak intensities for each sample (6 configurations). In total we therefore used 18 configurations for investigation of differential expression and prediction of patient status for cancer versus control. For the Gaucher dataset, CM10 ProteinChip array data was analyzed with three different pre-processing settings for both Cromwell and Ciphergen (6 configurations).T-tests were used to identify differentially expressed peaks between patient and control groups. Analysis of variance (ANOVA) was also used to assess the importance of label (patient versus control), chip (array), and interaction effects between label and chip within the dataset. Resulting p-values were corrected for multiple testing using the Benjamini-Hochberg False Discovery Rate (FDR) adjustment . Tests wTo test whether patient status (control/diseased) can be predicted from the peak profiles obtained, five classification methods often used for microarray and proteomics data were compared. The models are classification trees, linear support vector machines (SVM), DLDA , naive Bayes with Gaussian class-conditional densities )  and PCDAet al. [N samples were performed to generate 1000 (ovarian cancer dataset) or 500 (Gaucher dataset) different training sets (size n) and 1000 respectively 500 associated test sets (size N-n). In each of the random splits, the number of samples for both classes was balanced in both training and test set. The accuracy of the resulting classifier was assessed on the corresponding test set. We report average accuracy on the test sets and its corresponding confidence interval. To investigate the influence of the training set size on the accuracy of the classifier, we also varied the training set size . Estimation of the optimal values for hyperparameters of the models was done with 5-fold cross-validation on the training set. Such a double cross-validation scheme provides an almost unbiased estimate of the true error [The models were validated with repeated random sampling methodology as advocated by Michiels et al. . Random ue error . HyperpaAll classifiers were used under three different regimes. In the first regime, all peaks are used to estimate the model parameters. The second regime uses feature selection to extract the peaks most informative for predicting patient status. For each training set, an optimal classifier was identified from the 10, 20,...,50 peaks for which expression was most highly correlated with disease as determined by the t-statistics between the two classes. The optimal number of peaks was again selected with 5-fold cross-validation on the training set. In the third regime, class labels were permuted to obtain an estimate of the performance of the classifiers on random data. Statistical comparisons for classifiers over multiple configurations were performed with a non-parametric Friedman test for repeated measures and the Wilcoxon-Nemenyi-McDonald-Thompson post-hoc test . StatistFor both Ciphergen and Cromwell pre-processing, three different peak detection settings were chosen. More stringent peak detection parameters indeed resulted in a decrease in the number of peaks selected Table . First, Figure Figure et al. [As Morris et al.  observedx (Ciphergen) and y (Cromwell) if | x - y | < max, that is, if the mass difference between the two peaks is less than 0.4% of the mass of both peaks. The factor 0.004 was chosen since it corresponds to the setting used for the 'Cluster Mass Window' parameter in Ciphergen pre-processing  the median correlation for the matched peaks is 0.63 (range -0.23 – 0.97).Not withstanding these specific differences, generally the overlap between the peaks detected by either Ciphergen or Cromwell is large. We matched peaks ng Table . In thisReproducibility of the pre-processed spectra was addressed by calculating the coefficient of variation (CV) over all peaks and all spectra  is highly relevant for clinical datasets. Since both our datasets consist of two biologically very distinct classes, we expect a good pre-processing method to identify many peaks with a small FDR when comparing patients and controls. Therefore, an ANOVA was performed to assess the importance of label (patient versus control), chip (array), and interaction effects between label and chip. Both pre-processing methods led to a considerable number of peaks that are differentially expressed between the patient and the control group even when correcting for multiple testing (Table The ANOVA results in Table A notable difference between the two methods is the way in which the peak intensities are estimated. Ciphergen takes a two-pass approach to find peaks. If a peak is found in a minimum number of spectra (as determined by the Min Peak Threshold parameter) within a certain mass window, intensities are assigned to spectra without a peak by taking their intensity at the average m/z value of the cluster. In general, this extrapolation will not correspond to a peak in a spectrum. Looking at the peaks with small adjusted p-values as given by the ANOVA Table , the proClassification was done using five different classification methods on both datasets and all configurations. For clarity, results for only one specific setting are summarized in Tables We also varied the training set size to investigate its influence on the accuracy of the classifier. Figure Different peak detection settings using Ciphergen pre-processing had a considerable influence on classification accuracy. For the ovarian cancer dataset more stringent settings for peak detection, resulting in fewer detected peaks, gave better overall accuracy. Use of feature selection also often led to better classification results in all of the models used apart from SVMs  data, quality control data , or simuOur comparison of pre-processing methods consisted of the commercial ProteinChip Software of Ciphergen and the mean spectrum approach of Cromwell, a set of publicly available Matlab scripts. While these and other pre-processing methods described in the literature consist of the same basic ingredients , the combination of these steps is very different between Ciphergen and Cromwell . Despite these differences our results indicate that with respect to reproducibility, Ciphergen and Cromwell pre-processing are largely comparable. A recent comparison of various pre-processing algorithms including Ciphergen and Cromwell on quality control data also concluded that, at least for these two pre-processing methods, the difference in reproducibility is small . A compaet al. [Regarding peak detection we found that the overlap between peaks detected by either Ciphergen or Cromwell is large. This was especially the case for the more stringent peak detection settings. Moreover, similarity of the estimated intensities between matched peaks was high. Also the overlap between the most differentially expressed peaks detected by either Ciphergen or Cromwell is large Table  and estiet al.  who founAs stated above, clinical datasets lack a gold standard that tells us the location of true peaks. However, they in general consist of patient samples of known types or classes. Prediction of patient status therefore offers a highly relevant benchmark for comparison of pre-processing methods on a measurable and objective goal, namely maximization of classification accuracy. We compared five different classification methods and two pre-processing methods on an ovarian cancer and a Gaucher disease dataset generated with two types of ProteinChips. Special care was taken to adequately validate the resulting classifiers. We randomly sampled multiple training and test sets for a range of training set sizes to study the stability of the classifier accuracy. A nested cross-validation procedure was used to simultaneously optimize the number of peaks included in the model and provide an almost unbiased estimate of the true error.Regarding classification, we conclude that PCDA, SVM, and to a lesser degree DLDA, perform significantly better on all our datasets than naive Bayes and classification trees. A similar observation has been made in a recent comparison of normalization methods for SELDI-TOF MS datasets . In thatWhen comparing the classification results from the datasets pre-processed by the two different pre-processing methods, no pre-processing method significantly outperforms the other for all peak detection settings evaluated. However, significant differences are detected within and between pre-processing methods for specific settings. For example, Ciphergen pre-processing with stringent settings (C) on the CM10/Q10 ovarian cancer dataset significantly outperforms Cromwell with stringent settings. Previous comparisons of pre-processing methods were based on one specific parameter setting for each method, see for example . TherefoIn this study, we did not identify the proteins corresponding to the discriminatory peaks, since our focus was on the comparison of different pre-processing and classification methods. Although one does not need to know the protein behind a discriminatory peak for accurate classification, identification of such peaks does give us important additional information. It will help us understand their connection to a specific type of disease and help us discriminate disease-related proteins from artifacts created, for example, during sample preparation.We have found that careful patient selection in combination with stringent sampling protocols generates datasets that are suitable for further investigation. Our systematic comparison of two different pre-processing methods using five different classification methods has shown that different pre-processing parameter settings lead to significantly different classification results within and between pre-processing methods. However, for both pre-processing methods, settings could be found that gave comparable maximal classification accuracy on an ovarian cancer and a Gaucher disease dataset. Therefore, we advocate evaluation over a range of different parameter settings when comparing pre-processing methods for mass-spectrometry generated datasets such as SELDI-TOF MS datasets. Also the choice of a suitable classification method is of vital importance for a good classification outcome. Our comparison indicated that PCDA, SVM, and to a lesser degree DLDA, outperform naive Bayes and classification trees, at least on our two datasets.Comparing different pre-processing methods and parameter settings using maximization of classification accuracy on clinical datasets as prime objective does not only give insight in the quality and reproducibility of the data, but also indicates which pre-processing methods and settings are best suited for a particular dataset. Given the abundance of clinical mass spectrometry generated datasets, a classification-based comparison of pre-processing methods on clinical data is a valuable complement to the use of calibration or simulated data for that purpose.ANOVA: analysis of variance; BMI: body mass index; CI: confidence interval; CV: coefficient of variation; DLDA: diagonal linear discriminant analysis; FDR: false discovery rate; FIGO: Fédération Internationale de Gynécologie Obstétrique; HUPO: Human Proteome Organization; MALDI: matrix-assisted laser desorption ionisation; MS: mass spectrometry; PCDA: principal component discriminant analysis; m/z: mass/charge; SD: standard deviation; SELDI: surface enhanced laser desorption ionisation; SN: signal-to-noise; SVM: support vector machines; TIC: total ion current; TOF: time of flight; UDWT: undecimated discrete wavelet transform.The authors declare that they have no competing interests.WW collected samples and clinical information, carried out the SELDI-TOF experiments, interpreted results and drafted the manuscript. PDM carried out the statistical analyses, interpreted the results and drafted the manuscript. MRB was responsible for the design of the study and sample collection. EVLvT contributed to data pre-processing and statistical analyses. BB carried out the SELDI-TOF experiments. HCJH advised on statistical analyses and interpretation of results. CGdK and JMFGA contributed materials and were responsible for the design of the study. All authors read and approved the final manuscript.Variance analysis (ovarian cancer dataset). Boxplots of the coefficient of variation . Left panel: CV for all combinations of pre-processing method  and peak selection setting  for the CM10 chip. Right panel: idem for Q10 chip.Click here for fileVariance analysis (Gaucher dataset). Boxplots of the coefficient of variation . CV for all combinations of pre-processing method  and peak selection setting .Click here for fileCumulative plot of significance of detected peaks (ovarian cancer dataset. CM10). For each combination of pre-processing method and peak selection settings, the cumulative percentage of peaks with a p-value smaller than the value on the x-axis are shown. P-value of a peak is based on a t-test between the normalized intensities of the cancer and the control group.Click here for fileCumulative plot of significance of detected peaks . For each combination of pre-processing method and peak selection settings, the cumulative percentage of peaks with a p-value smaller than the value on the x-axis is shown. P-value of a peak is based on a t-test between the normalized intensities of the cancer and the control group.Click here for fileCumulative plot of significance of detected peaks (Gaucher dataset). For each combination of pre-processing method and peak selection settings, the cumulative percentage of peaks with a p-value smaller than the value on the x-axis is shown. P-value of a peak is based on a t-test between the normalized intensities of the Gaucher and the control group.Click here for fileComparison of classifiers and pre-processing methods (ovarian cancer dataset). Average classification accuracy on 1000 test sets  for each specific combination of pre-processing method and peak selection settings.Click here for fileComparison of classifiers and pre-processing methods (Gaucher dataset). Average classification accuracy on 500 test sets  for each specific combination of pre-processing method and peak selection settings.Click here for fileComparison of classifiers and pre-processing methods (ovarian cancer dataset). Each combination of chip type, pre-processing method and peak selection was ranked by its average classification accuracy on 1,000 test sets  for each classifier. The heatmap gives a colour coding of the ranks from 1  to 18 . Columns of the heatmap are ranked by their average rank over all classifiers, with Ciphergen pre-processing using setting C and the combined CM10/Q10 data getting the highest rank. Classifiers are ordered by their average rank over all pre-processing combinations, with DLDA being the best ranked classifier.Click here for fileComparison of classifiers and pre-processing methods (Gaucher dataset). Each combination of pre-processing method and peak selection was ranked by its average classification accuracy on 500 test sets  for each classifier. The heatmap gives a colour coding of the ranks from 1  to 6 . Columns of the heatmap are ranked by their average rank over all classifiers, with Ciphergen pre-processing using setting A getting the highest rank. Classifiers are ordered by their average rank over all pre-processing combinations, with SVM being the best ranked classifier.Click here for file


N-methyl [11C]2-(4'-methylaminophenyl)-6-hydroxy-benzothiazole, [11C]-PIB. The aim of the present study was to explore whether results obtained using the newly introduced method, Masked Volume Wise Principal Component Analysis, MVW-PCA, were similar to the results obtained using reference Logan.Kinetic modeling using reference Logan is commonly used to analyze data obtained from dynamic Positron Emission Tomography (PET) studies on patients with Alzheimer's disease (AD) and healthy volunteers (HVs) using amyloid imaging agent MVW-PCA and reference Logan were performed on dynamic PET images obtained from four Alzheimer's disease (AD) patients on two occasions (baseline and follow-up) and on four healthy volunteers (HVs). Regions of interest (ROIs) of similar sizes were positioned in different parts of the brain in both AD patients and HVs where the difference between AD patients and HVs is largest. Signal-to-noise ratio (SNR) and discrimination power (DP) were calculated for images generated by the different methods and the results were compared both qualitatively and quantitatively.MVW-PCA generated images that illustrated similar regional binding patterns compared to reference Logan images and with slightly higher quality, enhanced contrast, improved SNR and DP, without being based on modeling assumptions. MVW-PCA also generated additional MVW-PC images by using the whole dataset, which illustrated regions with different and uncorrelated kinetic behaviors of the administered tracer. This additional information might improve the understanding of kinetic behavior of the administered tracer.MVW-PCA is a potential multivariate method that without modeling assumptions generates high quality images, which illustrated similar regional changes compared to modeling methods such as reference Logan. In addition, MVW-PCA could be used as a new technique, applicable not only on dynamic human brain studies but also on dynamic cardiac studies when using PET. N-methyl [11C]2-(4'-methylaminophenyl)-6-hydroxy-benzothiazole, [11C]-PIB -GR205171 ([11C]-GLD), [11C]-5-hydroxytryptophan ([11C]-HTP), [11C]L-dihydroxyphenylalanine ([11C]-L-DOPA) and [11C]-PIB -PIB. In other words, the aim of the study was to explore whether images generated by MVW-PCA illustrate similar regional retention patterns compared to reference Logan images. Another aim was to study and compare these methods with respect to signal extraction based on calculating SNR and discrimination power (DP).The objectives of the current study were to explore the capabilities of MVW-PCA compared to kinetic modeling using the reference Logan method on the same dataset. The methods were used to extract signals which improve the discrimination between AD patients and HVs in a human brain study using PET and -PIB -PIB . This me11C]-PIB .However, in this work, only the first three MVW-PCs were explored since higher components contained only noise.The software used for the application of MVW-PCA on dynamic PET images was developed in-house by one of the authors (PR) using Matlab 7.2  with installed statistical and image processing toolboxes.The reference Logan graphical analysis is a regression method, which is appropriate for tracers with reversible kinetics. The method describes the kinetics of the tracer in a receptor-containing region and in a reference region devoid of specific binding, such that after a certain time there is a linear relationship between the reference Logan variables. The linear slope gives directly the distribution volume ratio (DVR), which corresponds to the ratio of the distribution volume (DV) of a receptor-containing region to the DV of a reference region. The DVR is widely used as a model parameter in PET studies since it is a linear function of the receptor availability. Parametric maps, in which the DVR is calculated for each pixel in the PET image, were generated using 25–60 min (last six frames) for 4 × 2 AD patients (each at both baseline and follow-up) and four HVs.Eq. 2 is used in the reference Logan graphical analysis is given by:where ROI(t) and REF(t) are the radioactivity concentrations in a region of interest and a reference region, respectively. The term int' is the intercept and S, and noise as the standard deviation of pixel intensities, N, within the same outlined ROI. SNR is calculated using Eq. 3Signal-to-noise ratio, SNR, measures the strength of the signals association to the quantity noise of the data in either sinogram (raw data) or image domain . In this11C]-PIB retention between AD patients and HVs is largest in these areas. SNR was calculated for all ROIs in images generated by the different methods and the mean results of the SNR were compared and plotted.The following four ROIs of similar sizes representing different parts of the brain were drawn, in both AD patients and HVs: frontal cortex sinister (Fsin), frontal cortex dexter (Fdx), parietal cortex sinister (Psin) and parietal cortex dexter (Pdx). According to the study by Klunk  the diff1 and σ2) -PIB in the cortical regions of the cerebrum. The binding was highest in the frontal cortex, thus corroborating the finding in most previous [11C]-PIB studies [11C]-PIB was seen in the cerebellum of either AD patients or HVs. Fig. The images obtained in each of the four AD patients (both at baseline and follow-up) showed substantial binding of -PIB retention in white matter in the HVs . To overcome these drawbacks we have previously introduced a new approach for application of PCA, and more specifically MVW-PCA, on dynamic PET images ,6. The i11C]-PIB retention between affected and unaffected regions in the human brain in patients with AD as compared with HVs. Moreover, we also compared the images generated using MVW-PCA and reference Logan with respect to signal extraction based on calculating SNR and differentiation between AD patients and HVs using DP.The aim of the present study was to explore whether results obtained using MVW-PCA give similar results as using a kinetic modeling method such as reference Logan. We studied the detection and visualization of regional differences in [Results obtained from this work show that MVW-PCA generates images which demonstrate similar regional changes in kinetic behavior of administered tracer in human brain in both AD patients and HVs as images generated using reference Logan. Moreover, several MVW-PC images are generated when applying MVW-PCA, images that provide additional information by discriminating and visualizing regions with different types of kinetics in the different MVW-PCs. It is thus possible to obtain separate images of e.g. regions with specific binding vs regions with nonspecific binding or vs. blood compartment. This is a property of great value that is not obtained when using reference Logan. This might improve the understanding of the kinetic behavior of administered tracer by illustrating additional differences in different parts of the brain. The MVW-PCA method is automated; faster and fewer numbers of clinical experiments are required to determine efficiency of the tracer or tracers of interest used in human PET studies. Furthermore, these images show slightly improved SNR and DP compared to the images generated using reference Logan.So far, MVW-PCA does not yield absolute quantitative binding data, but only relative data. The reference Logan method is however a quantitative method that estimates the distribution volume ratio of the tracer, which is a linear function of receptor availability. MVW-PCA retains the relative proportions between different regions with different amyloid retention with higher qualitative values, but can so far only be used as a qualitative tool. Future studies will be performed to enable quantitative analysis of images generated using MVW-PCA.To conclude, the results obtained from this study demonstrate the potential of MVW-PCA as a multivariate method that by using the whole dynamic dataset without modeling assumptions generates high quality images. Generated images using MVW-PCA demonstrate similar regional changes in kinetic behavior of administered tracer as compared with images generated using the reference Logan kinetic modeling method with the cerebellum as a reference region. In addition, MVW-PCA generates images with an enhanced contrast and higher SNR and DP. The present evaluation shows that MVW-PCA can be used in the study of beta amyloid distribution in AD patients as compared to HVs. This might improve the clinical interpretation and diagnosis of the PET studies on the human brain when using newly developed tracers or when using existing tracers in new clinical applications where kinetic behavior of employed tracer is not known. In addition, MVW-PCA could be used as a new technique, applicable not only on dynamic human brain studies but also on dynamic human cardiac studies when using PET.The authors declare that they have no competing interests.Authors PR, AR, HE participated in the design of the study. They created the introduced method, performed the image and data analysis, and drafted the manuscript.HH and BL contributed to some of the practical approaches and the writing of the paper.The pre-publication history for this paper can be accessed here:


ZK 200775 is an antagonist at the α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionate (AMPA) receptor and had earned attention as a possible neuroprotective agent in cerebral ischemia. Probands receiving the agent within phase I trials reported on an alteration of visual perception. In this trial, the effects of ZK 200775 on the visual system were analyzed in detail.In a randomised controlled trial we examined eyes and vision before and after the intravenous administration of two different doses of ZK 200775 and placebo. There were 3 groups of 6 probands each: Group 1 recieved 0.03 mg/kg/h, group 2 0.75 mg/kg/h of ZK 200775, the control group received 0.9% sodium chloride solution. Probands were healthy males aged between 57 and 69 years. The following methods were applied: clinical examination, visual acuity, ophthalmoscopy, colour vision, rod absolute threshold, central visual field, pattern-reversal visual evoked potentials (pVEP), ON-OFF and full-field electroretinogram (ERG).No effect of ZK 200775 was seen on eye position or motility, stereopsis, pupillary function or central visual field testing. Visual acuity and dark vision deteriorated significantly in both treated groups. Color vision was most remarkably impaired. The dark-adapted ERG revealed a reduction of oscillatory potentials (OP) and partly of the a- and b-wave, furthermore an alteration of b-wave morphology and an insignificantly elevated b/a-ratio. Cone-ERG modalities showed decreased amplitudes and delayed implicit times. In the ON-OFF ERG the ON-answer amplitudes increased whereas the peak times of the OFF-answer were reduced. The pattern VEP exhibited lower amplitudes and prolonged peak times.The AMPA receptor blockade led to a strong impairment of typical OFF-pathway functions like color vision and the cone ERG. On the other hand the ON-pathway as measured by dark vision and the scotopic ERG was affected as well. This further elucidates the interdependence of both pathways.NCT00999284ClinicalTrials.gov  Glutamate is an important excitatory neurotransmitter of the retina Non-NMDA receptors predominate in the retinal OFF-pathway of the mammalian retina. In animal experiments, AMPA receptor subunits have been localized in the inner and outer plexiforme layer, in amacrine, bipolar and horizontal cells as well as in ganglion cells and Muller glial cells ZK 200775 was developed by Schering AG  as an antagonist at the AMPA receptor. It raised expectations as a possible neuroprotective agent in cerebral ischemia. The data presented here was obtained in the resarch phase I to evaluate the safety, tolerability and pharmacokinetics of the drug In the meanwhile, further development of the drug has been aborted because of intolerable, but vision unrelated adverse reactions On a microscopic level, distribution and physiology of retinal AMPA receptors have been studied exhaustively. The advent of a phase I trial of ZK200775 opened the unique opportunity to investigate the effects of a receptor blockade in vivo, i.e. to elucidate the function of AMPA receptors on visual perception in humans.The administration of ZK 200775 had no effect on eye position  and motiVisual acuity deteriorated significantly in both verum groups post-treatment (p = 0.038 in group 1 and p = 0.004 in group 2). After 22 hours the baseline level was almost restored. The right eye was not tested as the pupil was dilated. See The most pronounced effect of ZK 200775 was seen on color vision as estimated with the desaturated Lanthony Panel D-15 test. The differences between the baseline and post-treatment error scores were significant for both treated groups being 22.16 and 39.15 in group 1 and 2, respectively, but only 0.17 in the control group. After 22 hours error scores of the treated groups returned to the baseline level .Likewise, dark vision was impaired after drug administration. A significant elevation of the absolute rod threshold could be observed in both treated groups at 4 hours (p = 0.002 for both groups) and in group 2 even at 22 hours (p = 0.026). ZK 200775 administration exerted various effects on the electrophysiologic recordings. In the statistic calculation we included amplitudes and peak times as measured in the single recordings. The mean values that can be read out of the diagrams , and 7 mThere was a small but obvious difference of the b-wave morphology before and after drug administration , Table 4All photopic ERG responses showed a dose-dependent amplitude reduction in the treated groups , Table 6In group 1 the recordings of only 4 of 6 probands were considered due to unrecognizable OFF-answers in 2 probands.The amplitude of the ON-response virtually showed a dose-dependent increment in both treated groups without reaching a significant level , Table 7Also the pVEP was affected by the administration of ZK 200775 , Table 8ZK 200775 is a glutamate antagonist at the AMPA receptor and was tested in clinical trials for its neuroprotective effects in cerebral ischemia. Probands receiving ZK 200775 constantly reported an alteration of their visual perception. This clinical trial offered the opportunity to objectify the impact of an AMPA receptor blockade on the visual system by psychophysical and electrophysiological means in vivo.The antagonization of AMPA receptors by ZK200775 led to alterations of color and dark vision, visual acuity, cone ERG modalities and the pVEP and to a lesser extent on the scotopic ERG. ZK 200775 did not alter eye morphology, functioning of the extraocular muscles, binocular vision, visual fields or the pupil.All subjective and objective symptoms found in this study which could be correlated to the administration of the AMPA antagonist ZK 200775 are most likely reversible. All parameters that were altered immediately after administration returned to the normal range or showed a strong tendency to this after 22 hours.Most of our psychophysical and electrophysiologic findings are consistent with the localization of AMPA receptors in the retinal layers as it was reported by previous experimental research. There are many indications that AMPA-antagonists compromise the glutamate action of the middle and inner retina to a larger extent than the function of outer retinal layers. The alterations of the flash ERG were subtle and the components representing photoreceptor function (flash ERG a-wave) were only mildly reduced. On the other hand, ERG OFF-response and the OPs, all representing more interior retinal function, were reduced more markedly in the treated groups.Our results especially hint at the affection of horizontal and amacrine cell function. It is known that both cell types play a role in color vision as well as in the integration of luminance detection. A functional defect of these cells may therefore lead to a deterioration of color vision as well as to a reduction of dark vision. The altered OPs can be regarded as the electrophysiologic correlate of the impaired amacrine cell function.Separating the ON- and OFF-pathway, our results are largely in agreement with earlier findings. Rods connect primarily to ON bipolar cells, whereas cones connect to ON or OFF bipolar cells. AMPA receptors mainly participate in the OFF-pathway but are also said to be expressed by some ON bipolar cells The most conspicuous finding of this study is the deterioration of color vision as measured by the Panel D-15 test. After infusion of ZK200775 the error-score increased significantly in both treated groups being an almost predictable result of the OFF-pathway blockade.The preponderance of non-NMDA receptors in the OFF-pathway also makes an impairment of central visual acuity after a partial pharmacological blockade very likely. In this study the treated probands showed an impairment of visual acuity between one and two lines.On the other hand we observed an impairment of dark vision of approximately 1 log unit that would not be primarily expected from a pure OFF-pathway blockade. Beside the potential effect of horizontal cell impairment on scotopic vision additional effect can be hypothesized. However, recent findings from animal experiments questioning the concept of two strictly independent rod and cone pathways make it well conceivable that an AMPA blockade influences scotopic vision as seen in our trial:Several authors reported the expression of AMPA receptors even in ON bipolar cells and rods Concerning the rodent retina, Hack et al. and Tsukamoto et al. proved the existence of small populations of OFF bipolar cells that connect to both cones The rod pathway is directly connected to the cone pathway via gap-junctions between cone and rod photoreceptors. Therefore, the cone OFF bipolar cells also recieve input from rods Concerning the dark adapted full-field ERG, ZK 200775 decreased both the a- and b-wave. At high stimulus intensities amplitudes were reduced to a greater extent than at small intensities. The b/a-ratio was slightly elevated in both treated groups four hours after administration without reaching a significant level.The b-wave of the dark-adapted ERG is generated mainly by the rod bipolar cells, the a-wave appears at higher stimulus intensities and reflects the activity of the rods. Again, as to dark vision, the small influence on the dark-adapted ERG can be explained with the minor part AMPA receptors are assumed to play in the ON-pathway and therefore in scotopic vision. The dependance between stimulus intensity and ERG alteration can be explained by the increasing influence of the cones on the ERG morphology at brighter flashes In the ON-OFF-ERG flashes of longer duration are used to separate the activities of both pathways. The ON-answer consists of the a- and b-wave. The difference to the scotopic ERG is that the photopic ERG b-wave results from opposing field potentials not only generated by depolarizing (ON) but also by hyperpolarizing (OFF) bipolar and horizontal cells as well as third-order neurons We observed a dose-dependent ON-response amplitude increment which corresponds to the results of Sieving et al. and probably reflects the fading influence of opposing third order OFF-neurons being blocked by ZK 200775.The OFF-answer (or d-wave) appears after stimulus cessation and can be separated from the b-wave only if the stimulus is long enough. It is said to be generated in OFF-bipolar cells. The OFF-amplitudes we measured were almost unaffected by the drug but surprisingly OFF-peak times were shortened significantly. These are paradoxical findings that defy explanation with the hitherto existing data. Earlier research using DNQX to selectively block AMPA and KA GluRs even showed a reversed polarity of the OFF-answer The rod-response to flashing stimuli is too slow to allow a stimulation of rods by flickering light at 30 Hz. Therefore the flicker-ERG is a parameter of cone function. In the treated groups, the cone-mediated answers showed reduced amplitudes (flicker-response and red light and single-flash answer) and delayed peak times (flicker-response). Yet, all cone answers were still recognizable. This again proves the influence of ZK200775 on the OFF-pathway but argues against its complete blockade.The VEP is a parameter for the integrity of the entire visual pathway Our results maintain that AMPA receptors predominate in the OFF-pathway and play a minor role in the ON-pathway. Nevertheless, the interdependence of both pathways becomes apparent. Surprising findings were the partial preservation of visual acuity, deteriorated dark vision, the persistent OFF-answer with it's shortened peak time and the peak time delay of the pVEP.Although the results of this study do not allow a precise definition of the role of AMPA receptors in the human retina they render some information concerning the relevance of glutamate for vision and for the components of the electroretinogram. Whereas the latter could also be studied in animals, this study offered a unique chance to elucidate the impact of AMPA on the psychophysically examined vision in humans.The protocol for this trial and supporting CONSORT checklist are available as supporting information; see This clinical trial was approved by the “Ethikkommission der Berliner Aerztekammer”  and was conducted according to the Declaration of Helsinki. All probands gave written informed consent to participate in the study.18 healthy probands were recruited for this study. Recruitment was done vía random selection of probands from the central Schering database on the basis of inclusion and exclusion criteria . RecruitFor recruitment of the probands, a physical and ophthalmological examination screened out any relevant medical or vision disorders. If the proband was included in the study this checkup also served as baseline examination and encompassed:Medical and opthalmological historyVisual acuityStereopsis (Titmus-test)Eye position, motility, pupillary reactionColor vision (Lanthony Panel D-15 desaturated)To calculate the error score of the Panel test the differences of the values of every two connected Panels were calculated and added (sums up to 15 for an entirely correct test). Then, 15 was subtracted from the sum (as the error score for a correct test must be 0).Central visual field (Amsler grid)Applanation tonometry (Goldmann)Slit lamp examination of the anterior segmentFunduscopy.Randomization was executed via stratification. A sequential  strategy beginning with the low-dose stratum and continuing to the high-dose stratum was planned. There were two strata, one for each dosage group (0.03 an 0.75 mg/kg/h). In every stratum there were two possible treatments: ZK200775 or placebo. The verum-group included 6 participants, the placebo group 3 participants per dosage group. In total, 18 participants were allocated to the treatments with a ratio of 2∶1  and 22 hours after onset of drug administration. These examinations comprised the points mentioned above except history and tonometry. Additionally, the rod absolute threshold was tested in the right eye with dilated pupil with a Hartinger adaptometer  after 30 minutes of dark adaptation.Electrophysiologic examinations were also performed before, immediately after and 22 hours after drug administration. For the full-field ERG the pupil of the right eye was dilated with tropicamide. For the remaining examinations the pupil of the left eye remained neutral. For electrophysiological recordings a Nicolet Bravo® unit was employed . Thread conjunctival electrodes were used for electroretinography. All recordings were made according to the Standard of the International Society of Clinical Electrophysiology of Vision (ISCEV).Four scotopic responses with increasing stimulus intensity following dark adaptation.Initial dark adaptation. High pass filter: 100 Hz.−2). Recording of single-flash cone response, cone red light answer and response to 30 Hz flicker.Initially ten minutes of light adaptation .Post-treatment values at 4 and 22 hours  were compared to baseline measurements using the t-test. P-values <0.05 were regarded as statistically significant.Checklist S1Consort Checklist(0.19 MB DOC)Click here for additional data file.Protocol S1Trial Protocol(108.83 MB PDF)Click here for additional data file.Figure S1Glutamate receptor subtypes.(0.02 MB TIF)Click here for additional data file.Table S1http://webvision.med.utah.edu, author: Vikki P. Connaughton). Some papers could not be considered in this survey.Ionotropic glutamate receptor expression in retinal neurons and retinal layers. Immunocytochemistry, in situ hybridization and polymerase chain reaction. Based on Webvision, completed by the authors ((0.15 MB DOC)Click here for additional data file.Table S2Eye position. Data for both eyes for each group before infusion and 4 and 22 hours after infusion of ZK 200775. No significant changes occurred.(0.05 MB DOC)Click here for additional data file.Table S3Eye Motility. Data for both eyes and each group before infusion and 4 and 22 hours after infusion of ZK 200775. No significant changes occurred.(0.05 MB DOC)Click here for additional data file.Table S4Pupil light response. Data of the left eye for each group before infusion and 4 and 22 hours after infusion of ZK 200775. No significant changes occurred.(0.03 MB DOC)Click here for additional data file.Table S5Amsler Card examination. Data of the left eye for each group before infusion and 4 and 22 hours after infusion of ZK 200775. No significant changes occurred.(0.04 MB DOC)Click here for additional data file.Table S6Inclusion and exclusion criteria.(0.04 MB DOC)Click here for additional data file.