MEN1 gene. The protein sequence has no significant homology to known consensus motifs. In vitro studies have shown menin binding to JunD, Pem, Smad3, NF-kappaB, nm23H1, and RPA2 proteins. However, none of these binding studies have led to a convincing theory of how loss-of-menin leads to neoplasia.Multiple Endocrine Neoplasia type 1  is an autosomal dominant disorder characterized by endocrine tumors of the parathyroids, pancreatic islets and pituitary. The disease is caused by the functional loss of the tumor suppressor protein menin, coded by the Global gene expression studies on eight neuroendocrine tumors from MEN1 patients and 4 normal islet controls was performed utilizing Affymetrix U95Av2 chips. Overall hierarchical clustering placed all tumors in one group separate from the group of normal islets. Within the group of tumors, those of the same type were mostly clustered together. The clustering analysis also revealed 19 apoptosis-related genes that were under-expressed in the group of tumors. There were 193 genes that were increased/decreased by at least 2-fold in the tumors relative to the normal islets and that had a t-test significance value of p < = 0.005. Forty-five of these genes were increased and 148 were decreased in the tumors relative to the controls. One hundred and four of the genes could be classified as being involved in cell growth, cell death, or signal transduction. The results from 11 genes were selected for validation by quantitative RT-PCR. The average correlation coefficient was 0.655 (range 0.235–0.964).This is the first analysis of global gene expression in MEN1-associated neuroendocrine tumors. Many genes were identified which were differentially expressed in neuroendocrine tumors arising in patients with the MEN1 syndrome, as compared with normal human islet cells. The expression of a group of apoptosis-related genes was significantly suppressed, suggesting that these genes may play crucial roles in tumorigenesis in this syndrome. We identified a number of genes which are attractive candidates for further investigation into the mechanisms by which menin loss causes tumors in pancreatic islets. Of particular interest are: FGF9 which may stimulate the growth of prostate cancer, brain cancer and endometrium; and IER3 (IEX-1), PHLDA2 (TSS3), IAPP (amylin), and SST, all of which may play roles in apoptosis. MEN1 gene was classified as a tumor suppressor [MEN1 gene spans 9 kb of the genome, is comprised of 10 exons, and codes for a 610 amino acid protein termed menin [MEN1 gene were identified in our laboratory [Multiple Endocrine Neoplasia type 1  is an autosomal dominant disorder characterized by endocrine tumors of parathyroid, pancreatic islets and pituitary . Based oppressor ,3 and thppressor . The MENed menin . More thed menin . Recentlboratory . Menin iboratory .et al[Men1 was found to be expressed in testis (spermatogonia) at high levels [et al [et al [Studies on the function of menin have not yielded a clear picture as to the role of menin as a tumor suppressor; however, the results of these studies suggest some interesting possibilities. Two groups ,9, basedet al reportedet al. In posth levels . Lemmenss [et al  by screes [et al  suggest l [et al  observedl [et al  and a pul [et al  have beel [et al -21 and sDespite the above studies, a clear consensus of the molecular mechanisms leading to neoplasia, following the loss of menin, has not emerged. Very little is known about the gene expression changes in human neuroendocrine tumors following the loss of menin. Global gene expression analyses, using cDNA microarrays, have been used to classify other human tumors into clinically distinct categories -26. Wu  has discEight neuroendocrine tumors from six MEN1 patients were included in this study. The patient ages were 19, 22, 42, 51, 57, and 57 years at the time of surgery (Table The RNA isolated from 8 tumor specimens (6 patients) and 4 normal islet preparations was of acceptable quality for hybridization, as determined by preliminary small hybridizations on test chips. The dChip computer program returned data concerning the percent of genes judged to be present, and the percent of single and array outlier events Table . The expAverage expression and standard deviation was computed for each gene in both the group of 4 normal islets, and the group of 8 islet tumors and expressed as the coefficient of variation (CV). Genes with average expression levels less than 50 were excluded from this analysis. Figure The experimental groups were clustered figure  using a The genes were also clustered by the dChip software. A group of apoptosis-related genes was identified whose expression was significantly correlated with the Tumor/Normal assignment of the data. Twenty-four apoptosis-related genes represented by 26 different Affymetrix probes were identified in the overall hierarchical clustering. Nineteen of these genes were more highly expressed in the normal islets than in the islet tumors Figure . EighteeSince the Student's t-test was designed to compare only one parameter in two populations, the simultaneous measurement of multiple genes might lead to an excessive number of false positives. In order to empirically determine the potential false positive rate, we started with 923 genes which had a p value <=.05 and repeatedly scrambled the individual tests into groups 4 and 8 and then performed new t-tests. The average number of genes having a p value = < .05 in 20 such scrambles was 51 (5.5% of 923 genes). This was only slightly more than the 46 genes expected (0.05 × 923). We therefore concluded that there was little chance of excess false positives in repeatedly using the Student's t-test.In order to obtain a better picture of the nature of the tumors and normal islets in this study, the expression levels of the principal hormone RNA of pancreatic islets was examined Table . Tumors . There were 16 genes related to cell growth, 13 genes related to signal transduction, and 16 genes related to other functions which were increased in the group of tumors relative to the group of normal islets . The results are shown in Table Whether there were degradative processes acting on the tissues prior to or during or after the extraction of the RNA can be guessed by the quality of the RNA. Each RNA specimen in this study was tested on an Affymetrix test chip, and each was found to be acceptable. Additional quality assessment was made by the dChip software. Only one specimen, a normal control, had Array Outliers greater than 5%, suggesting that it was subnormal Table . HoweverAlthough, only solid tumor was utilized, there were undoubtedly a small percentage of blood, blood vessel, and connective tissue elements intermixed with the tumor tissue. Rarely, there might be a small amount of exocrine tissue. In the case of the normal islets used as controls, microscopic examination showed that greater than 90% of the tissue was islet. Any contaminants would probably have the effect of reducing the discriminant power to differentiate tumor from normal. Thus, t-test p values and fold changes would tend to under-represented and some, otherwise significant, genes might be missed. The actual data, represented by the hierarchical specimen clustering Figure , showed One might have expected more variation in the gene expression levels in the tumors than in the normal islets, since tumors are often heterogonous. However the data on the average CV of the genes in the normal and tumor groups suggested that there was no more variation in the tumors (average CV of 30%) than in the normals (average CV of 31%). The low CV in the tumors may relate to the single mode of tumor formation (induction by the loss of the menin tumor suppressor). However, there was increased variation noted when the tumors and normals were combined Figure . This waOf particular interest was the high proportion (3/8) of tumors expressing principally PP hormonal RNA. This was entirely consistent with pathological studies showing the preponderance of PP containing tumors in the pancreas of MEN1 patients . The facThe use of the Students t-test for comparison of multiple genes might be questioned because the test was designed for comparison of only two groups. In this study, we confirmed that comparison of 923 genes would not generate an excess number of false positive results. Nevertheless, in the group of 193 genes finally selected at a p < = .005, we can expect that 1 of those genes is a false positive.This study suggests that the overall effect of loss of function of menin is the suppression of gene expression. Nevertheless, there were 86 genes that were over-expressed in the tumors relative to the normals. Although we associate tumorigenesis with increased rates of growth, only two of eleven Cell Cycle and Cell Proliferation genes were increased in the tumors. Since tumor growth may also be significantly affected by rates of cell death, it is perhaps significant that there were no Cell Death genes significantly increased in the tumors relative to the controls.The correlation of GeneChip results with quantitative real-time PCR  of the genes delineated in this study are a direct and necessary affect of loss-of-menin tumorigenesis cannot be determined by this study alone. Firstly, the activity of many genes are regulated both by their levels of expression and by post-translation modifications, such as phosphorylation. Secondly, the microchips used in this study represent only about 1/3 of the total number of human genes. Thirdly, it is not certain that the initiating gene changes caused by loss-of-menin are persistent in the tumors that develop. However, there were some genes, which because of their association with growth or apoptosis are of special interest. The general suppression of apoptosis related genes noted in this study Figure  has beenet al,  who showet al, . Severalet al, -40. Soma in vivo -57.PHLDA in vivo , and may in vivo . IAPP  in the group of neuroendocrine tumors. The underexpression of these apoptosis-related genes may be related to neoplastic development or progression in these MEN1-related neuroendocrine tumors.Tumor specimens were obtained from patients with the MEN1 syndrome who had undergone surgery for islet-cell tumors of the pancreas. The specific germline mutations in the menin tumor suppressor gene were identified and previously reported  for eachApproximately 50 mg of tissue was removed from each frozen tumor specimen and homogenized with a mortar and pestle , and RNA was extracted using the Rneasy Mini Kit , and quantified by UV absorbance. RNA was similarly isolated from the normal human islet preparations.The RNA was submitted to the GeneChip facility of the Siteman Cancer Center at Washington University School of Medicine. There, biotin labeled cRNA was prepared and hybridized to U95Av2 microarray chips (Affymetrix). The fluorescence of individual spots was then measured and the data returned on compact discs. We analyzed the gene expression data and made comparisons between groups using the dChip computer program . FollowiThe same preparations of total RNA that were used to probe the GeneChips were also used to prepare c-DNA for quantitative RT-PCR analysis of gene expression. C-DNA was first prepared using Superscript II reverse transcriptase . Primers for each gene were designed to produce products of 100 to 150 bp that spanned exon boundaries (when possible). The primer pairs are shown in table in vitro islet tumor cell line was utilized.The Sybr Green technique on an Applied Biosystems model GeneAmp 5700 instrument was utilized. Relative quantitation using a standard c-DNA preparation from an The author(s) declare that they have no competing interests.All authors contributed equally to this manuscript.


Acquired resistance to chemotherapy is a major obstacle to successful cancer treatment. Understanding the mechanisms by which tumors become resistant to a particular agent is key to identifying new drugs or combination regimens.Kinases are signaling molecules that control many aspects of cell behavior, including cell proliferation, i.e., whether and how fast cells divide. Abnormally active kinases promoting tumor growth are found in many cancers and are a focus of rational cancer drug design. One target for kinase inhibitors is the epidermal growth factor receptor (EGFR). Two EGFR inhibitors, gefitinib and erlotinib, showed therapeutic benefits in a subset of patients with non-small cell lung cancer. Recent work has helped us understand why some patients respond and some don't: responsive tumors usually harbor activating mutations in the EGFR gene, which somehow make the tumors sensitive to treatment. Nearly all patients whose tumors initially respond to EGFR inhibitors, however, eventually become resistant to the drugs and progress despite continued therapy.William Pao and colleagues examined tumors from six patients with non-small cell lung cancer who initially responded to gefitinib or erlotinib but subsequently relapsed. Tumors from all six patients carried activating mutations in the EGFR gene. In addition, in three out of the six cases, the resistant tumor cells carried an identical second mutation in the EGFR gene. Whereas the activating mutation was present in tumor cells before treatment with erlotinib or gefitinib, the second mutation was not found in pre-treatment biopsies from these patients, nor in over 150 lung cancer samples from patients who had not been treated with either drug. Additional cell culture studies supported the notion that the secondary mutation causes resistance to gefitinib or erlotinib. It is clear, though, that this is only one mechanism of resistance, because in the three other cases resistance occurred in the absence of the second mutation. What caused the resistance in those tumors is not known.10.1371/journal.pmed.0020075), the initial identification three years ago of resistance mutations against imatinib led to the rapid development of alternative kinase inhibitors that work even against tumors with the resistance mutation. Similarly, the results by Pao and colleagues should help researchers develop second generation drugs for lung cancer.All kinases share some common features, and a resistance mutation very similar to the one identified here has also been found in other kinase genes from tumors with acquired resistance to imatinib, another kinase inhibitor. As Gary Gilliland and colleagues point out in an accompanying Perspective (DOI:


Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach  to identify differentially expressed genes. This leads to the discovery of 'population-level' markers, i.e., genes with the expression patterns A > B and B > A. We introduce the PPST test that identifies genes where a significantly large subset of cases exhibit expression values beyond upper and lower thresholds observed in the control samples.Interestingly, the test identifies A > B and B < A pattern genes that are missed by population-level approaches, such as the t-test, and many genes that exhibit both significant overexpression and significant underexpression in statistically significantly large subsets of cancer patients (ABA pattern genes). These patterns tend to show distributions that are unique to individual genes, and are aptly visualized in a 'gene expression pattern grid'. The low degree of among-gene correlations in these genes suggests unique underlying genomic pathologies and high degree of unique tumor-specific differential expression. We compare the PPST and the ABA test to the parametric and non-parametric t-test by analyzing two independently published data sets from studies of progression in astrocytoma.The PPST test resulted findings similar to the nonparametric t-test with higher self-consistency. These tests and the gene expression pattern grid may be useful for the identification of therapeutic targets and diagnostic or prognostic markers that are present only in subsets of cancer patients, and provide a more complete portrait of differential expression in cancer. Studies of differential expression of individual genes often find genes that are up-regulated in some tumors, and down-regulated in others. Microarray studies typically seek to identify differentially expressed genes using use fold-change , t-testss3(ABA) statistics . These are listed in Table Our initial results are compelling in that they suggest that we can expect biomarkers of high clinical significance for subsets of patients to be important for distinct subsets of patients. This also suggests that clinical validation of the utility of biomarkers should examine panels of expression biomarkers, not individual biomarkers. Disruption of genomic function via these patterns cannot be studied in the population level biomarker framework for the simple reason that methods that compare, say, group means, will find no difference between the sample groups if the number of case samples found in the two tails are even approximately equal. This is a sensible approach even from within the framework of population-based hypothesis testing, because the PPST test can be expected to be more robust to one or two outliers that might mislead simple parametric tests. Note that a number of genes are 'nearly significant' under the t-test but are strongly significant under the PPST test for the AB/BA patterns  that the most commonly applied tests for identifying differentially expressed genes will miss important genes that are dysregulated in only a fraction of patients, and 2) that important aspects of differential expression may be, to a degree, highly individualistic in most cancers. Some potentially important genes with this form of unusual differential expression , and that for many other methods of analysis, are accessible online in the Cancer Gene Expression Data Analysis tool We have developed a test we call the Permutation Percentile Separability Test (PPST), which attempts to refute a null hypothesis that is slightly different from A = B, but which is capable of detecting AB, BA, ABA and BAB patterns. Under this test, we are interested in the question "are there are statistically significant number of samples in group A  that exhibit expression intensities beyond a particular percentile of the observed expression intensities in group B ?" and vice versa. By 'statistically significant' we mean that the number of samples that exhibit apparent overexpression (or underexpression) exceeds that expected under the null distribution.th percentile of the samples in the opposite group. This provides two scores, s1, and s2, for each gene (PPST scores). s1 is the number of samples in group A that are beyond the upper percentile  of group B plus the number of samples in group B that are below the lower 95th percentile of group A. This measure will tend to be large when all samples in both groups are significantly distinct from the alternate group in the same way (comparisons consistent with A > B). It can also be significant when a surprising number of samples in only one group varies from the expression levels in the alternate group. s2 is the number of samples with correspondingly opposite pattern (comparisons consistent with B > A). Sample class label permutations are used to generate an arbitrarily large number of permuted data sets. These scores s1 and s2 are calculated in each permuted data set to produce unique null distributions for each gene. For the sake of convenience of interpretation, we use -s2 when reporting s2 to denote underexpression. Genes with values of s1 beyond the specified acceptable Type 1 error risk  are determined to be significantly overexpressed in sample group A relative to B. Individuals in sample group A with expression intensity values over the 95th percentile of sample group B for a given gene may be considered overexpressed. Similarly, genes with values of s2 beyond the specified Type 1 risk for s2 are deemed underexpressed in sample group B relative to A. Varying the percentile threshold allows direct control over the false discovery rate.To test these hypotheses, we count the number of samples in both groups that are found beyond the nboth significant s1 and s2 scores in this comparison may be considered 'ABA pattern genes'  that can expected to be distributed nth percentile tailsboth in the upper and lower  of the intensity distribution of that gene in the other group (B); i.e., in the ABA (s3) or BAB (s4) pattern. These scores are not redundant to but rather allow for exploration of distribution-wise (upper and lower) false discovery rates. The application of the PPST test to find ABA patterns is called the 'ABA' test. Under the ABA test, differential expression of a gene may be deemed to be significant in both directions at once, i.e., simultaneously significantly over-expressed and under-expressed in a surprising number of patients in the case population. Both the PPST test and the ABA test will perform optimally when the variation in expression intensities in the normal sample population is well characterized.Genes that exhibit [.A collection of published microarray data sets we have placed 'on-tap' in the caGEDA  web application  were sub,53. Deta studied PPST: permutation percentile separability test.ABA test: a test that can detect genes with both A > B (gene is overexpressed in sample A compared to sample group B) and B < A (gene is overexpressed in sample B compared to sample group A) patterns.s1, s2, s3, s4: measures of the number of samples that exhibit expression intensities beyond a specified percentile in an alternate group; used as scores in the determination of significance under the PPST and ABA tests.JLW conceived of the PPST and ABA tests and executed the analyses, SP encoded the methods in caGEDA, TG provided direction, input and scientific motivation for pursuing a test with the capabilities of the PPST and ABA tests, MJB provided, direction, input and coordination of the research. All authors read and approved the final manuscript.


The error threshold puts a limit on the amount of information maintainable in Darwinian evolution. The error threshold was first formulated in terms of genotypes. However, if a genotype-phenotype map involves redundancy , the error threshold should be formulated in terms of phenotypes since there is no unique fittest genotype. A previous study formulated the error threshold in terms of phenotypes, and their results showed that a rather low degree of mutational neutrality can increase the error threshold unlimitedly.We obtain an analytical formulation of the phenotypic error threshold by considering the "additive assumption", in which base substitutions do not influence each other (no epistasis). Our formulation shows that an increase of the error threshold due to mutational neutrality is limited. Computer simulations of RNA evolution are conducted to verify our formulation, and the results show a good agreement between the analytical prediction and the simulations. The comparison with the previous formulation illustrates that it is important for the prediction of the error threshold to consider that the number of base substitutions per replication is rather large near the error threshold. To examine the additive assumption, a detailed analysis of additivity and epistasis in RNA folding of a particular sequence is performed. The results show a high degree of epistasis in RNA folding; furthermore, the analysis also elucidates the reason of the success of the additive assumption.We conclude that an increase of the error threshold by mutational neutrality is limited, and that the additive assumption achieves a good prediction of the error threshold in spite of a high degree of epistasis in RNA folding because the average number of base substitutions of sequences retaining the phenotype per replication is sufficiently small to avoid of the effect of epistasis. The error threshold is a limit on the permissible mutation rate for which "survival of the fittest" holds in Darwinian evolution . The errThe error threshold was first formulated in terms of genotypes. However if some changes in genotype do not alter the phenotype or the fitness , there is no unique genotype which can be stably maintained. Instead, the survival of a phenotype should be considered, and thus the error threshold should be formulated in terms of phenotypes .In this paper, first we formulate the phenotypic error threshold analytically by employing the additive assumption, in which base substitutions do not influence each other. Under the additive assumption, we obtain the probability that a replication does not alter the phenotype  as a function of the number of base substitutions and the fraction of "neutral substitutions". Our results show a qualitative difference from the previous formulation . Second,x) and the others called mutants (denoted by y). The population size is assumed to be large enough to express the abundance of the phenotypes by normalized concentration. The population dynamics of the phenotypes is described asThe quasispecies equation describes (prebiotic) replicator dynamics in well-mixed systems . We trandx/dt = σQx + σΛ (1 - Q)x - Dx - Φx,dy/dt = y + σ (1 - Λ)(1 - Q)x - Dy - Φy     (1)σ (> 1) is the replication rate of x ; Q is the replication accuracy of x. Λ is the fraction of neutral mutants of x. D is the degradation rate (or the death rate) assumed to be uniform over the phenotypes. Φ = (σ - D)x + (1 - D)y is the excess production (or the mean fitness). The terms - Φx and - Φy induce a selection pressure. We neglect back mutation from y to x (this simplification will be discussed in the next section). From Eq. 1, we obtain the survival condition of x as Q + Λ (1 - Q) >σ-1, for which the stationary value of x is larger than zero. From this inequality, we will deduce the phenotypic error threshold, i.e., the maximum error rate of replication for which x can be stably maintained in the system.where x. We distinguish two classes of single base substitutions: neutral and deleterious substitutions. The class of a substitution is determined by the effect of the substitution on the phenotype when there are no other substitutions in the genotype: A substitution which retains the phenotype is a neutral substitution; otherwise it is a deleterious substitution. A beneficial substitution is not considered since the focus of the study is on the maintenance of Qe = Q + Λ (1 - Q), we assume that a mutant is neutral iff there is no deleterious substitution: The effect of a substitution on the phenotype is independent of the other substitutions; i.e., no epistasis is assumed (the additive assumption). Let λ denote the fraction of neutral substitutions in all possible single substitutions, and let d denote the number of substitutions per replication. Then, the probability that d substitutions are all neutral substitutions  is approximated by λd by assuming that the number of neutral substitutions in d substitutions follows the binomial distribution . This approximation is valid if the probability of correct replication per base (denoted by q) is sufficiently large so that d is small. Denoting the sequence length of replicators by N, the effective replication accuracy (Qe) is obtained asTo calculate the effective replication accuracy q and λ are uniform among the genotypes in x, that q is invariable over sequence positions, and that N is the same among the populations. , or (2) q is so large that most mutants have d = 1. The uniform distribution of neutral sets in the genotype space is not applicable in RNA folding as shown later. The latter possibility is discussed next.from  = Q + λ  - Q. Thiq so that most mutants have d = 1  is close to the error threshold, mutants can have on average d > 1 even if λ = 0, for which the error threshold is at the lowest error rate  per replication  is lower than the average d per replication. However at the error threshold, even the average d per neutral replication is larger than one for λ > 0.32 . [A neuet al. [λ approximation". This extension divides a sequence in four sub-sequences in order to take into account the fact that the fraction of neutral substitutions varies over the sequence position. This extension still overestimates Qe though less so than Eq. 5 because the approximation now permits four substitutions per replication as a side effect of the subdivision. Note that this extension makes a fairly good prediction on the error threshold , in terms of additivity and epistasis. The objective of this study is to understand how the additive assumption achieves a good prediction in spite of a high degree of nonlinearity in RNA folding ,13.We compare the secondary structure of randomly sampled mutants to that of the tRNAphe. Similar to the previous section, a mutant is neutral if its secondary structure is the same as that of the tRNAphe; otherwise, it is deleterious. To evaluate the deviation from the additive assumption, we categorize mutants into four classes as shown in Table δ > 0 are only considered, positive epistasis occurs very rarely compared to additive deleterious case: No more than 0.5% of the mutants are neutral at d = 5 if they carry at least one deleterious substitution. If mutants with δ = 0 are only considered, negative epistasis is rather frequent relative to additive neutral case: As much as 35% of the mutants are deleterious at d = 5 even if they carry only neutral substitutions. However, replication with δ > 0 occurs far more frequently than replication with δ = 0: As much as 99.7% of the replication contains at least one deleterious substitution at d = 5 and λ = 0.307. Therefore, the relative frequency of epistasis is flipped around. Consequently, the additive assumption underestimates the degree of mutational neutrality.  and that observed in RNA folding  near the error threshold.The effect of epistasis is already noticeable when see Fig. . Since tQe) including the effect of epistasis in order to compare it with Qe calculated under the additive assumption. The first trial was to include a "trivial" epistasis in base paired regions (helices) as a part of the additive effect . However, the analysis showed that epistasis occurs mainly in a "non-trivial" way (data not shown), and thus it is not sufficient for our sake to include a trivial epistasis. We next took a probabilistic approach to calculate Qe with epistasis (see Methods section – Probabilistic approach). The results of this method agree with the observation . As Fig. d per neutral replication is ca. 1.5 at the error threshold, which is much smaller than the average d per replication (ca. 3.8). This means that the main contribution to Qe under the additive assumption is from the mutants of d = 1 or 2 at the error threshold. According to Fig. d = 1 or 2. Therefore, the additive assumption accurately estimates Qe and thus the error threshold. When the average d per neutral replication reaches 3, the additive assumption substantially underestimates Qe . The results showed that the average d per neutral replication  at the error threshold was indeed smaller (ca. 1.2 substitutions with λ ≈ 0.35) than in the previous case of the shorter sequence length (ca. 1.5 substitutions with λ ≈ 0.4), and the additive assumption still predicts the results of the simulations closely (data not shown).In the above examination of the additive assumption, there are two points which must be examined further: (1) The analysis of epistasis was performed on a yeast tRNAphe, which comprises the initial population of the RNA evolution simulations, but the results may differ if the analysis is done for a sequence which appears later in the RNA evolution simulations. Thus, we performed the same analysis to a sequence which was chosen from the population of the fittest sequences after the evolution in the simulations (at the 20000th time step). The results, however, did not change our conclusion (data not shown). (2) If the length of sequences is larger, the average • The phenotypic error threshold was formulated under the additive assumption. The formulation asserted that mutational neutrality increases the error threshold but the increase is limited.• The importance of considering multiple substitutions per replication at the error threshold was illustrated.Qe) and thus the error threshold.• The comparison with the computer simulations and the analysis of epistasis showed that the additive assumption correctly estimates the effective replication accuracy  epistasis in RNA folding is that the average number of substitutions per λ is not uniform over the genotypes sharing the same phenotype, the effective replication accuracy (Qe) depends on the distribution of the genotypes in the population. In this case, Qe is calculated under the additive assumption asIf XI denotes the population of the focal phenotype (I), and xi (resp. λi) is the population  of the genotype i. The set SI denotes the set of genotypes which have the phenotype I. If xi and λi are known, the representative λ of the phenotype can be calculated from the following equation aswhere λ and the population average of λ was very small in the computer simulations. The difference between the representative Qe was to include this epistasis as a part of the additive effects of mutations as described in [It is trivial that epistasis occurs between bases which make a pair (hydrogen bond) in the reference secondary structure. Our first trial to include epistasis in the calculation of ribed in . In thisμ), which depends on the number of neutral base substitutions (denoted by v) and on that of deleterious base substitutions (denoted by δ). Then, the probability of neutral replication is obtained  asSince  epistasis makes it difficult to predict what happens to the phenotype given a specific change in genotype, we take the following probabilistic approach: We assume that a mutant is neutral with a certain probability  in the tRNAphe folding as shown in Fig. δ = 0 and v > 0, μ declines a little slower than exponentially as v increases due to negative epistasis  increases, saturates, and finally decreases as v increases  where β and γ are parameters. To obtain the parameters, we fitted Eq. 10 to the data in Fig. (d) was calculated from the above obtained parameters, and the calculated values match the observed ones (see the dashed line in Fig. where NT contributed to the entire part of the study. PHP contributed to the computer programing of the RNA evolution simulation. PH contributed to the conceptual development of the study and the manuscript preparation as the supervisor.


The geminivirus and nanovirus families of DNA plant viruses have proved to be a fertile source of viral genomic sequences, clearly demonstrated by the large number of sequence entries within public DNA sequence databases. Due to considerable conservation in genome organization, these viruses contain easily identifiable intergenic regions that have been found to contain multiple DNA sequence elements important to viral replication and gene regulation. As a first step in a broad screen of geminivirus and nanovirus intergenic sequences for DNA segments important in controlling viral gene expression, we have 'mined' a large set of viral intergenic regions for transcriptional enhancers. Viral sequences that are found to act as enhancers of transcription in plants are likely to contribute to viral gene activity during infection.Agrobacteria-infused Nicotiana tobacum leaf tissue. Of the 105 elements tested, 14 were found to reproducibly elevate reporter gene activity , while 91 elements failed to increase luciferase activity. A previously described "conserved late element" (CLE) was identified within tested repeats from 5 different viral species was found to have intrinsic enhancer activity in the absence of viral gene products. The remaining 9 active elements have not been previously demonstrated to act as functional promoter components.DNA sequences from the intergenic regions of 29 geminiviruses or nanoviruses were scanned for repeated sequence elements to be tested for transcription enhancing activity. 105 elements were identified and placed immediately upstream from a minimal plant-functional promoter fused to an intron-containing luciferase reporter gene. Transient luciferase activity was measured within Arabidopsis promoter regions. These data provide a useful starting point for virologists interested in undertaking more detailed analysis of geminiviral promoter function.Biological significance for the active DNA elements identified is supported by repeated isolation of a previously defined viral element (CLE), and the finding that two of three viral enhancer elements examined were markedly enriched within both geminivirus sequences and within  A relatin planta promoter activity using isolated or modified geminivirus or nanovirus intergenic sequences [To test the enhancer mining approach we chose to examine a collection of geminivirus and nanovirus intergenic sequences obtained from GenBank. There are a relatively large number of available sequences for these DNA viruses and due to conserved genomic organization they contain easily identifiable intergenic regions . Additioequences -21. Althequences , very feequences .in planta, any elements identified using this approach are likely to contribute to regulation of in vivo viral gene expression during plant infection. By allowing relatively large numbers of viral sequences to be examined using a defined system, the approach has the potential of generating data useful in comparing positively acting viral promoter elements within and between viral families. In addition, identification of elements that are active in planta in the absence of viral infection provides results pertinent to understanding virus-host interactions at the level of gene control. Finally, the resulting list of active and inactive viral sequences provides a valuable starting points for subsequent, more detailed, analysis of transcription regulation of individual viruses.The described enhancer mining of viral sequences is not intended to be a comprehensive analysis of viral promoter structure since by design it is limited to identification of promoter elements that up-regulate gene expression and that make use of endogenous plant transcription factors available within the un-infected test plant. However, based upon their iteration, location within intergenic regions, and ability to enhance transcription et al [The initial search for sequence repeats was performed on the major intergenic regions of 29 different geminivirus or nanovirus genomic sequences Figure . The seaet al , the resin vivo assay were subsequently tested using an in vitro dual-luciferase® system from Promega Corp. and produced levels of enhancement very similar to those obtained using the in vivo assay . The observed enhancement of promoter activity (~2 fold) is relatively modest compared to other viral transcriptional enhancers that have been isolated and tested  and, as controls, several well defined plant promoter element consensus sequences  and may, therefore, be similar or identical to endogenous plant promoter elements. In order to test for enhancement of viral enhancer sequences within higher plant promoters, the PatMatch page of the TAIR web site  was used factors ,34, and  factors ) and abs factors ).Arabidopsis genome sequence and PatMatch. As an alternative, screens were performed to determine frequencies of occurrence for viral enhancers (and control plant elements) within a sequence database consisting of all geminivirus or nanovirus GenBank entries as of May 13, 2004 [Arabidopsis PatMatch datasets. The searched viral sequence database has the potential for bias due to the existence of a numerous entries containing only coding regions or only intergenic sequences, as well as some duplication of sequences in separate entries. Any such bias should, however, similarly affect the baseline frequency values resulting from searches using the 18 matched random oligonucleotides  versus 'coding sequence' frequency comparisons that were possible using the fully annotated 13, 2004 , and theArabidopsis upstream databases  were normalized relative to the value obtained for each element's occurrence within the A. thaliana coding sequence database . In addition to the predicted frequency values, in each case, the element's observed frequency was also compared to a value generated using the average of 18 random oligomers having the same length and base composition as the element tested . Results for the DRE element were less convincing (2.13 vs 1.46 in the -1 to -500 dataset) and likely reflect lower functional usage of this element within the Arabidopsis genome [The results of the searches are displayed in Table Arabidopsis promoters is less obvious (CLE = 3.9 in the -1 to -500 database vs 2.79 for random sequences). The observed relatively small CLE enrichment is consistent with reports of a low frequency of occurrence for a CLE-like "TCP domain" binding consensus sequence (Gt/cGGNCCC) within Arabidopsis promoters [Arabidopsis promoters containing the TCP domain consensus binding element were found to function in transgenic tobacco and to show reduced activity after mutation of the element's core sequence [As expected, the CLE consensus sequence (GTGGNCCC) was found to be markedly enriched within the viral database, occurring 6 times more frequently than the mean of 18 random 8-mers of identical base composition . This frequency is similar to that found (17.11 vs 3.42) using a short sequence of identical base composition and length that matches a highly conserved replication stem-loop sequence (CGCGNCCA), a component that is evolutionarily conserved within the geminivirus population . Enhanceromoters . It is psequence .The test sequences for plant element occurrence within the viral database  provide further indication of the technique's utility. The G-box viral frequency is consistent with a previous report that a G-box element contributes to transcriptional regulation from the major intergenic region of Tomato Golden Mosaic Virus {TGMV, . Similar TC-rich regions have been reported within plant promoter regions [Of the remaining viral elements tested against the es Table , only th regions ,41, but Except for the CLE elements, none of the active elements identified in this work have been experimentally reported as regulatory components of viral promoters. This is likely a reflection of both the limited number of geminivirus and nanovirus promoters that have been examined in detail ,27,42,43Arabidopsis upstream sequences for at least the CLE and TC-rich (DR08/13) classes of elements, strongly supports participation of the enhancers in viral gene expression.This screen of viral intergenic repeats was undertaken to specifically identify general transcriptional enhancing elements contained within intergenic regions of a subset of geminivirus and nanovirus genomes. The screen was successful in demonstrating transcriptional enhancer activity from one proven viral promoter element and several previously unidentified elements. The occurrence of the repeated elements within intergenic regions, combined with the clear enrichment within viral sequences and The technique of testing isolated elements represents an alternative to normal promoter-by-promoter dissection and provides a useful tool for screening promoter regions for potential functional elements that have been implicated by any number of possible criteria . Although the number of elements tested is relatively small and, so far, only representative of promoters from the geminiviruses and nanoviruses classes of plant viruses, there is a clear trend suggesting that directly repeated elements  are more likely to play significant roles in the enhancement of transcription than inverted repeats. This work represents one of the first attempts to directly screen for individual plant promoter elements that are isolated from their native promoter context. It is therefore, difficult to gauge the actual contribution of any of the elements identified to viral gene regulation and biological activity. These results do, however, provide a useful starting point for more detailed analyses of not only geminivirus and nanovirus promoters, but also overall plant promoter structure-function relationships.The search for repeated DNA sequences was performed by visual inspection of computer-generated dot matrix comparisons . Dot matrices generated using each viral plus strand plotted against itself were used to identify direct repeats while inverted repeats were found by plotting each plus strand against its complement.Agrobacteria tumefaciens strain, EHA105 [Agrobacteria strains each contain, in addition to the test plasmids, a second, compatible, binary transformation vector expressing an intron-modified version of the Renilla reniformis luciferase gene (RiLUC) [The identified repeats were synthesized as DNA cassettes containing the duplicated elements in their original orientation, either directly repeated with spacer sequence , inversely repeated with spacer sequence 'IR', 45 elements), or palindromic inverted repeats without spacer . In order to limit the tested component to only the repeated elements themselves, any sequence occurring between the viral repeats  was replaced with a 10 bp randomized stuffer sequence (GAAGATAATC). The resulting cassettes were inserted immediately upstream from a minimal promoter  reporter system derived from the cauliflower mosaic virus (CaMV) 35S promoter fused to an intron-modified firefly luciferase (FiLUC) gene   under co (RiLUC) . The FiLAgrobacteria harboring the test and normalization binary plasmids were grown at 28°C in LB media containing the appropriate antibiotic selection (25 μg/mL kanamycin sulfate or 100 μg/mL spectinomycin) until an OD600 of 0.8 was achieved. The resulting cultures were centrifuged at 3000 rpm for 15 minutes, washed and re-suspended in an equal volume of infiltration media  before being mechanically infused (5 ml syringe) into multiple individual tobacco  leaves (2–4 leaves per test construct). Assays were performed in groups of 4–8 constructs and the resulting luciferase activities (both FiLUC and RiLUC) determined after 3–4 days using an in vivo floating leaf-disk assay developed for this enhancer screen [in vivo assays were each measured for light production in separate wells of a white-walled 96 well microtiter plate (FLUOstar Optima luminometer® from BMG Lab Technologies Inc.) and all elements that tested positive in the in vivo assay were subsequently confirmed using the in vitro dual-luciferase® from Promega Corp . Each test group included an infusion containing the 35S min construct . In order to compare the various assay systems, all activities were normalized to the activity of the 35S min construct included within each assay set (35S min activity arbitrarily set to 1.0).r screen . Test coA. thaliana genomic sequence at the TAIR, PatMatch web site [Arabidopsis coding sequences {"GI CDS "}, and various lengths of upstream regions {"Locus Upstream Sequences", -1 to -500, -1 to -1000 and -1 to -3000}. Results from the -500 search were subtracted from the -1000 results, to generate hits from -501 to -1000 and -1000 results subtracted from the -3000 data to calculate hits from -1001 to -3000. In order to allow direct comparison between searches in different databases, using sequence elements of differing length and base composition, the number of database hits was corrected for the size of the database (number of hits divided by the database size in mega-base pairs {Mbp}) and base composition (hits/Mbp divided by the predicted number of hits per Mbp using upon the element sequence and base composition of each search database). The dataset base compositions were determined from downloaded sequence files and are: A. thaliana CDS: A/T = 55.8%, G/C = 44.2%; A. thaliana upstream (-1 to -500): A/T = 67.43%, G/C = 32.57%; A. thaliana upstream (-501 to -1000): A/T = 66.24%, G/C = 33.76%; viral: A/T = 56.2%, G/C = 43.8%. The resulting frequency of occurrence is a corrected number of hits per mega-base pairs (cHits/Mbp). For ease of comparison between elements, all of the cHits/Mbp values have been normalized to the corresponding cHits/Mbp number from the A. thaliana CDS database (set arbitrarily to 1.0). Correction of the element's frequency using the calculated random probability of occurrence does not account for the possible impacted by intrinsic base-order bias that may occur within each sequence database, specifically the coding region database. These biases can potentially shift cHits/Mbp numbers markedly from those calculated using simple random base composition frequencies. To help confirm the significance of any observed enhancement in an elements frequency, mean cHits/Mbp values for 18 randomly generated sequences that match each test sequence for base composition and length were determined to provide a baseline value for comparison to that of the test element (shown in parenthesis, Table Since the element enrichment approach works best when applied to relatively short, core consensus sequences , databasweb site . The gemA patent application is being considered for synthetic plant promoters containing some of the elements described in this article.Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.in vivo assay used to quantify enhancer activity. All authors read and approved the final manuscript.JV conceived of the study, participated in its design and coordination and drafted the manuscript. KM performed much of the search for short repeats within viral sequences and contributed to development of protoplast-based reporter gene assays. CIC generated and tested all the elements examined and developed the Excel worksheet listing viral elements that fail to enhance expressionClick here for file


It has been shown that transthyretin (TTR) exists in different molecular variants. Besides point mutations associated with different diseases such as amyloidosis, other posttranslational modifications occur that might be of diagnostic interest.TTR levels as determined by ELISA in plasma and urine of healthy individuals were 489 ± 155 μg/ml plasma and 46 ± 24 ng/g creatinine, respectively. Average levels in urine of pregnant women were 45 ± 65 μg/g creatinine. The molecular heterogeneity of TTR was analyzed using a high-throughput mass spectrometric immunoassay system. TTR was extracted from plasma or urine onto an antibody-coated (via protein A) affinity chip surface (PS20) using the surface-enhanced laser desorption/ionization (SELDI) technique. Subsequently samples were subjected to time-of-flight mass spectrometry (TOF-MS). In healthy individuals, TTR in plasma occurred rather consistently in two variants of 13732 ± 12 and 13851 ± 9 Da for the native and S-cysteinylated forms and at a smaller signal of 14043 ± 17 Da for the S-glutathionylated form. In urine of pregnant women, various signals were observed with a dominant signal at 13736 ± 10 Da and a varying number of smaller immunoreactive fragments. These fragments are possibly the consequence of metabolism in plasma or kidney.This chip-based approach represents a rapid and accurate method to characterize the molecular variants of TTR including protein or peptide fragments which are either related to TTR or have resulted from its catabolism. These molecular variants may be of diagnostic importance as alternative or novel biomarkers due to their predominant relation to the TTR metabolism both in healthy and diseased individuals. Transthyretin  belongs to a group of proteins including thyroxine-binding globulin and albumin which bind and transport thyroid hormones in the blood. It is a single polypeptide chain of 127 amino acids 14 kDa) and is present in the plasma as a tetramer of non-covalently bound monomers. The major sites of TTR synthesis are the liver and choroid plexus . Under p kDa and The TTR variants described thus far have mostly been associated with variable degrees of cardiac and/or neural tissue amyloid deposits ,8. ThereWith regard to nutrition, TTR is a so-called visceral protein that is synthesized in the liver in response to nutritional supply. TTR plasma levels have thus been proposed as sensitive biochemical parameters of subclinical protein malnutrition, because both the adequacy and levels of protein as well as energy intakes are reflected in plasma levels. Plasma levels of TTR, however, are as well affected by acute and chronic diseases associated with an acute-phase response. Under these conditions, liver activity is converted to the synthesis of acute-phase response proteins, resulting in a dramatic drop in visceral proteins, despite nutritional support -3.This study was conducted to establish a sensitive and reproducible high-throughput SELDI-TOF-MS immunoassay for characterizing TTR variants in plasma and urine arising from amino acid substitutions, posttranslational modifications and/or products of protein degradation or proteolysis.TTR levels in plasma determined by ELISA in 10 healthy individuals were 489 ± 155 μg/ml. TTR levels in urine of the healthy individuals were one thousand times lower than in the 40 pregnant women with 46 ± 24 ng/g creatinine and 45 ± 65 μg/g creatinine, respectively.In Figure SELDI-TOF-MS immunoassays showed that in healthy non-pregnant and pregnant females as well as in males TTR in plasma occurred rather consistently in two major variants of 13732 ± 12 and 13851 ± 9 Da, of which generally the 13851 Da variant is the dominant one. The mass difference between these two variant was 120 ± 9 Da. In addition to the two major signals a minor one at 14043 ± 17 Da was observed in plasma. The mass difference to the signal at 13851 Da was 192 ± 11 Da. In urine, traces of TTR were detected in samples from non-pregnant females and from males. In the urine of pregnant women however strong mass signals were observed. As shown in Figure The SELDI platform can be readily adapted for developing an immunoassay format. This approach, using antibodies as an affinity capture device has been successfully used to detect and quantify different proteins by MS in complex biological mixtures . Unlike The results support and confirm previous studies with regard to molecular variants of TTR in plasma and urine -15. As iApart from the case of absence, some modifications might not be detected with this method due to limitations in resolution. Both methods, ELISA and SELDI immunoassay are sensitive enough to observe only trace amounts of TTR in body fluids as in the case of urine of healthy individuals. These amounts were not detected using immunoblotting. Despite the small signal it was obvious that additional variants to the ones in plasma are present in urine. Contrary to a pervious study using a different method  we were No study is available in which TTR has been described quantitatively in the urine of healthy individuals. In this study we are able to show for the first time that levels of TTR in urine of pregnant women are 1000-fold higher compared to the levels in urine of healthy non-pregnant individuals. The excretion of substantial amounts of TTR has only been described in individuals with different kidney diseases indicating disturbed glomerular filtration and/or insufficient tubular reabsorption . The invInterestingly, as shown by us also for the first time, TTR in the urine of pregnant women is present in different molecular variants. In contrast to plasma, the S-cysteinylated form dominant in plasma was if at all present only in trace amounts. It remains to be determined if this is limited to the excretion of TTR in pregnancy or if under other circumstances such as in different kidney diseases similar molecular variants occur as well. The lower molecular weight immunoreactive variants found in urine of pregnant women may arise from limited proteolysis. At this point it is not possible to determine location and extent of proteolysis within the molecule. The immunoreactive fragments might arise from a breakdown within the plasma or the kidney structures.The SELDI immunoaffinity-isolation of TTR in combination with mass spectrometry offers a rapid, highly reproducible and cost-effective system for the determination of molecular variants of microheterogenous proteins and peptides. This is of importance in "second phase" proteomics which is characterized by the repetitive investigation of the same protein to validate the protein phenotype in large population based studies. This provides the basis for a substantial progress in the diagnostic with regard to personalized medicine ,21. Withg, 10 min, 4°C) within 1–3 h after acquisition. Additionally, urine samples of the ten individuals and of healthy pregnant women (n = 40) undergoing routine medical examination, were collected and immediately mixed with protease inhibitors . Hematuria was tested using a routine dipstick method . Cells and other non-soluble material were cleared from the sample by brief centrifugation . Aliquots of centrifuged urine were stored at -80°C and processed as soon as possible. The study protocol was approved by the hospitals and University of Potsdam Ethics Committee. Informed consent was obtained from each participant.Paired plasma and urine samples from 10 healthy individuals were obtained. The plasma was prepared by centrifugation of the blood . TTR in plasma and urine was quantitatively determined by an enzyme-linked immunoassay (ELISA) method developed in our laboratory. To further assess the presence of TTR quantitatively and qualitatively, we performed a SDS-polyacrylamide gel electrophoresis (PAGE) immunoblot analysis as has been described .Protein A  at 0.1 mg/ml in PBS was added (5 μl) to the spots of a pre-activated ProteinChip® Array . The PS20 array consists of a surface with epoxy groups that dock proteins by covalently reacting with their amine groups. The arrays were incubated for 1 h at 25°C in a humidity chamber. After blocking residual active sites with 5 μl blocking buffer (0.5 M ethanolamine in PBS at pH 8.0) for 25 min, the array was washed three times in a 15 ml conical tube with PBS (pH 7.4). TTR antibody (4.1 μg/μl) was added to individual spots (2 μl) and incubated in a humidity chamber for 1.5 h with mixing. The unbound antibodies were removed by washing the array three times in a 15 ml conical tube with PBS (pH 7.4).2O. After drying, 0.6 μl of a saturated energy-absorbing molecule (EAM) solution (5 mg sinapinic acid dissolved in 75 μl acetonitrile and 75 μl 1% trifluoroacetic acid) was applied to the spot surface, and the sample was allowed to dry.Before incubation urine was diluted 1:1 (v:v) in PBS and plasma 1:100 (v:v) in PBS. A total volume of 10 μl was applied to each spot and incubated for 1.5 h at 25°C in a humidity chamber. Samples were washed on the spot with 5 μl PBS three times and finally with 5 μl HAfter insertion of the ProteinChip Array into the ProteinChip Reader, a laser pulse was focused on the sample under vacuum. The array was analyzed under the following settings: laser intensity 250/220, detector sensitivity 8, mass focus, molecular mass range 10 to 18 kDa, position 20–80 and a 150–200-shot average per sample.CytochromeC , myoglobin , GAPDH , albumin  and β-galactosidase  were used as calibrators.Mass resolution (defined as m/Δm) is routinely achieved below 300 and mass accuracy was within 0.1%. Peaks with amplitudes at least 3 times greater than the average background noise level were considered. The reproducibility was tested with different aliquots of the same sample on eight different spots of the protein chip array.None declared.FJS participated in the conception, design, data analysis and the writing of the manuscript, KW in data analysis and writing of parts of the manuscript. JR participated in the conception, data analysis and the writing of the manuscript. All authors have read and approved the last version of the manuscript.


Of the 200-plus different types of cells that form the mammalian body, most have a finite life span. Like nearly everything in biology, there are exceptions—neurons and muscle cells, for example, can last a lifetime—but the vast majority of cells eventually wear out and must be replaced. Among the most short-lived cells, blood cells are generated continuously, mainly in the bone marrow of an adult, recharging the bloodstream as their depleted predecessors are efficiently dispatched and removed from circulation every 120 days. Some 2.5 million new red blood cells are generated every second from a small pool of stem cells.Blood cell development, called hematopoiesis, passes through discrete stages in specific tissues in the developing embryo before converging in the bone marrow, where it continues throughout adulthood. Some researchers have proposed that hematopoietic stem cells (HSC) flood the bloodstream during short, precise intervals to build the developing hematopoietic system . Presenting an alternative model for HSC migration, Julie Christensen and her colleagues in Irving Weissman's lab at Stanford University report that HSC in mice gradually leave the fetal liver to colonize the developing spleen and bone marrow as the organs acquire the means to support them.In mouse embryos, HSC precursors develop first in the yolk sac and a region called the aorta-gonad-mesonephros (AGM), then they migrate to the liver, and later to the spleen, before finally settling into the bone marrow just before birth. It was thought that this migration occurs in distinct waves of HSC production because HSC numbers decrease in one region just before increasing in newly forming hematopoietic sites. Analyzing the concentration and activity of HSC, Christensen et al. found the cells in the blood at low but fairly constant levels during much of late fetal development, when they migrate from the liver to the spleen and bone marrow. Although the HSC population decreases in the liver at 15.5 days after conception, the authors propose that this drop occurs primarily because the HSC have differentiated into mature blood cells, not because they've exited the liver en masse to help build the spleen and bone marrow. On the other hand, the slight decrease in circulating HSC, which also occurs around this time, may be attributed to their recruitment from the bloodstream to these developing tissues.Christensen et al. also examined the impact of intercellular signaling proteins called chemokines, which help regulate fundamental developmental processes, on HSC migration. To effectively “seed” developing tissues, HSC must first be recruited from the blood, guided to the appropriate nascent tissue, then corralled and sustained. The chemokine SDF-1 attracts and retains HSC in the bone marrow but was thought to have a lesser effect on fetal liver HSC. Christensen et al. demonstrate not only that liver HSC migrate in response to this chemokine, but that their migratory response increases dramatically when both SDF-1 and a signaling protein called steel factor (SLF) are present. While adult marrow HSC respond to SDF-1, they do not respond to SLF alone and do not show improved migration in the presence of both SLF and SDF-1.Bone marrow transplants have become increasingly common for a number of hematological disorders, including leukemia and aplastic anemia. Since hematopoiesis occurs primarily in the bone marrow in both mice and humans after birth, these findings offer valuable insights into the migratory behavior of these stem cells and suggest how HSC migration might be applied to bone marrow transplants and other clinical therapies.


Sooner or later, a gardener looking for “nontoxic” ways to control the inevitable attack on a favorite plant will discover the nicotine remedy. Steep a cup of loose tobacco in a gallon of water, let it sit overnight, strain, and spray away. Caterpillars, aphids, and a diverse array of insects predisposed to devouring plants will soon abandon your vegetables and flowers in search of less disagreeable forage.The ultimate sitting duck, plants rely on an arsenal of chemical metabolites to fend off predators. Many of these chemicals harbor anti-herbivore properties, which have been exploited for commercial use. Nicotine, it turns out, is so toxic that it was one of the first chemicals used in agricultural insecticides. It's not clear, though, whether these toxic metabolites are really defending plants against hungry herbivores in their natural environment, especially since many insects can tolerate various plant chemicals and sometimes even incorporate them into their own defenses. Though scientists have cataloged a long list of these presumed resistance traits, there's no evidence that they offer plants a competitive advantage against their leaf-covetous foes in nature.With plant and plant-eater engaged in an ever-escalating battle of evolutionary one-upmanship and with plants capable of producing an array of defensive responses, teasing out the predator-resistant effects of individual plant metabolites has proved challenging. Theoretically, one could track down a resistance gene by breeding plants that are genetically identical save for the gene that controls expression of a particular resistance trait. In practice, however, traditional breeding techniques aren't that precise and tend to generate additional variations in genomic regions that are linked to the target gene and that might affect resistance as well.The tools of genetic engineering have largely overcome such limitations, allowing scientists far greater control and specificity. Following this approach, Ian Baldwin and colleagues use transgenic silencing (which introduces gene “constructs” into an organism to inactivate a gene of interest) to investigate a single resistance trait, nicotine production. Even though nicotine is one of the best-studied putative resistance traits, its specific role has been unclear.Nicotiana attenuata tobacco plant. Focusing on an enzyme, called putrescine methyl transferase (PMT), central to nicotine biosynthesis, the authors used two techniques that interfere with PMT production by silencing the gene, pmt, that encodes the enzyme. One of the techniques  proved far more effective at silencing pmt, producing 29 out of 34 plant lines with only 3%–4% of normal nicotine levels.To isolate the resistance effects of nicotine from possible confounding factors, Baldwin and colleagues blocked nicotine production in the N. attenuata's native habitat. A subset of the plants was also treated with a chemical known to increase both nicotine content and resistance to herbivore attack. Predictably, several of the plant's natural insect enemies made an appearance. Untreated nicotine-deficient transgenic plants fared the worst, losing twice as much foliage to herbivores as nonmutant plants. Transgenic plants treated with the chemical boost performed much better, showing about the same amount of damage as the nonmutants. Interestingly, tobacco hornworms—which, as their name implies, feed primarily on tobacco—preferred nicotine-free plants when given the choice. Though the worms have evolved strategies for coping with nicotine's deleterious effects, these adaptations come at a price: worms feeding on nicotine-deficient tobacco grew bigger and faster than those feeding on plants with normal nicotine levels.With suitably nicotine-deprived plants, Baldwin and colleagues could directly test nicotine's role in tobacco fitness. They transplanted the transgenic plants, along with nonmutant cultivated plants, in southwestern Utah, These results clearly show that nicotine protects tobacco plants in their native habitat, the authors conclude, and that tobacco-chewing insects “prefer low nicotine diets.” Removing nicotine from the equation reveals the relentless pressure that plants face from herbivores. Without such defenses, plants would be unceremoniously eliminated posthaste, leaving a world without greenery, not to mention oxygen. But these experiments also demonstrate the unprecedented power of transgenic tools to peel back the obfuscating layers inherent in ecological interactions to reveal the fundamental properties of those interactions. And that scientists working to unravel the tangled web of ecological interactions would do well to take advantage of the longest running experiment on earth—the natural environment.


We examined the association and interaction between maternal viral load and antibodies in vertical transmission of HIV in a non-randomized prospective study of 43 HIV-1 infected pregnant women who attended the San Juan City Hospital, Puerto Rico, and their 45 newborn infants. The women and infants received antiretroviral therapy.A nested PCR assay of the HIV-1 envelope V3 region and infant PBMC culture were performed to determine HIV status of the infants. Maternal and infant plasma were tested for HIV neutralization or enhancement in monocyte-derived macrophages.-1 dilution compared with HIV negative plasma. Infant plasma neutralized HIV (p = 0.001) at 10-2 dilution but maternal plasma lost neutralizing effect at this dilution. At 10-3 dilution both maternal and infant plasma increased virus replication above that obtained with HIV negative plasma but only the increase by maternal plasma was statistically significant (p = 0.005). There were good agreements in enhancing activity in plasma between mother-infant pairs, but there was no significant association between HIV enhancement by maternal plasma and vertical transmission.Twelve (26.7%) infants were positive by the HIV V3 PCR assay and 3 of the 12 were also positive by culture. There was a trend of agreement between high maternal viral load and HIV transmission by multivariate analysis . Both maternal and infant plasma significantly (p = 0.001 for both) reduced HIV replication at 10Although not statistically significant, the trend of association between maternal viral load and maternal-infant transmission of HIV supports the finding that viral load is a predictor of maternal-infant transmission. Both maternal and infant plasma neutralized HIV at low dilution and enhanced virus replication at high dilution. The antiretroviral treatments that the women received and the small sample size may have contributed to the lack of association between HIV enhancement by maternal plasma and vertical transmission. The rate of HIV-1 infection has been increasing rapidly among women of childbearing age. At the end of 2003 women accounted for 50% of adults living with HIV/AIDS worldwide ,5. HowevAlthough some studies show no association between the presence of HIV neutralizing antibodies in maternal sera and the risk of perinatal transmission ,7, otherin vitro by either Fc gamma receptor- or complement receptor-mediated endocytosis (FcγR-ADE or C'-ADE) have been identified in sera from HIV-1-infected individuals [in vitro study of antibody dependent enhancement (ADE) of HIV-1 infection in human term syncytiotrophoblast cell cultures suggested that both FcγR-ADE and C'-ADE may contribute to maternal-infant transmission of HIV-1 [In contrast to neutralizing antibodies, non-neutralizing antibodies may enhance HIV infection by binding to the virus and facilitating its uptake by cell types that carry immunoglobulin (Fc) or complement receptors. Antibodies that enhance HIV replication ividuals -25 and fividuals ,20. An iof HIV-1 . Pancinoof HIV-1 , reporteof HIV-1 , observeof HIV-1  and the Maternal plasma virus load has been shown to be strongly associated with perinatal transmission of HIV ,30,31 anHowever, the association of both viral load and enhancing activity (presumably by FcγR-ADE) in maternal plasma and vertical transmission of HIV has not formerly been examined. Thus, we examined the association of these factors (independently and combined) in vertical transmission using samples from mother-infant pairs from San Juan, Puerto Rico, previously described by Melendez-Guerrero et al . NeutralA cohort of 43 HIV-1 subtype B infected pregnant women attending antenatal clinic at the San Juan City Hospital, Puerto Rico, was enrolled into a prospective study from their first antenatal visit until delivery . Eleven 3 of blood with a mean count of 425 cells/mm3. Twenty-six of the 43 women delivered their babies by normal vaginal delivery; the remaining women had cesarean sections  of 45 infants were HIV V3 positive indicating that HIV transmission had occurred  compared to non-transmitting mothers . Maternal CD4 cell counts have been shown to be a less effective predictor of transmission of HIV than viral load [3 level which is used to define AIDS. Only one of the three women whose infants were HIV culture positive had AIDS (CD4 = 149 cells/mm3). The other two women had CD4 counts of 510 and 538 cells/mm3.The mothers of HIV V3 positive infants had a non-significantly higher mean CD4+ T count  from the mothers (transmitters and non-transmitters) and infants (HIV V3+ and HIV V3-) on HIV replication was examined in the neutralization/enhancement assay  and infants (HIV V3+/ HIV V3-) neutralized HIV. At 10-2 dilution the percentages of plasma that neutralized HIV dropped to approximately 75% for both groups of mothers and to 58% and 70% for HIV V3+ and HIV V3- infants respectively. The percentages again dropped at 10-3 dilution to ≤ 67% for mothers and ≤ 33% for infants (Table The effect of plasma (at 10-1) dilution when compared with HIV negative sera  reduced virus replication, but the maternal plasma lost neutralizing activity  above seronegative plasma and the infant plasma showed a non-significant increase (88%) in HIV replication . Examination of enhancing activity in plasma of mothers and infants showed that there were good agreements (60% or greater) in enhancement status between mother-infant pairs. For example, at 10-4 dilution, the plasma of 7 infants of 9 mothers (78%) whose plasma enhanced HIV replication also exhibited enhancement, and at 10-6 dilution, the plasma of 8 infants of 10 mothers (80%) whose plasma enhanced HIV replication also exhibited enhancement (data not shown). Comparison of p24 antigen between transmitter and non-transmitter mothers or their infants at 10-4 to 10-6 dilutions showed no significant difference between the two groups of mothers or infants. The lack of association of enhancing activity and HIV transmission in this study is similar to the findings for C'-ADE by Gras, et al. [in vivo by most HIV-1 variants [Sixty-nine percent (31/45) of plasma from mother-infant pairs were also tested in the neutralization/enhancement assay at higher dilutions  and low negative associations at higher dilutions (10-4 – 10-6). There were low positive associations between maternal viral load and the p24 antigen values of their infants at low dilutions (10-1 – 10-3) and low negative correlations at higher dilutions except at 10-5 dilution  and the infants' p24 antigen values. A correlation matrix showed a positive association between mothers' p24 antigen values and those of their infants . The combined effect of maternal viral load and enhancing antibodies as potential risk factors for the vertical transmission of HIV-1 was examined in a multivariable model. Log viral load was treated as a continuous variable in the model and enhancement was categorized as enhancement versus neutralization. There was a trend of association between maternal viral load and transmission of HIV-1 so that the higher the viral load, the more likely mothers were to transmit HIV-1 to their infants . This is in agreement with other studies discussed earlier that show viral load as a predictor of maternal-infant transmission ,30,31. T-1) dilution and enhanced virus replication at higher dilution (10-3). Neutralizing and enhancing antibodies can occur together in the blood of HIV positive individuals and the neutralizing effect can be lost at high plasma dilution.In agreement with published data, multivariate analysis showed a trend of association between maternal viral load and maternal-infant transmission of HIV. The non-significant difference in the mean log viral load of transmitting and non-transmitting mothers is probably due to the small sample size. No significant associations were found between HIV antiretroviral treatment protocols, classification of HIV disease, method of infant delivery and CD4+ T cell count of the mothers and vertical transmission of HIV. Both maternal and infant plasma significantly neutralized HIV infection at low  were stored frozen at -85°C. The HIV status of the infants was determined using a nested PCR assay of the HIV-1 envelope variable (V3) region as previously described [Blood samples were taken from the mothers during each trimester of pregnancy and during delivery. Blood samples from the infants were collected from the umbilical cord at birth and at 1–2, 3–4 and 5–12 months. Blood was collected in vacutainer tubes containing ACD anticoagulant and centrifuged at 2500 rpm for 15 minutes. The plasma was stored frozen (-20°C) for use in maternal viral load and HIV neutralization/enhancement assays. The remaining blood was diluted in phosphate-buffered saline (PBS) pH 7.4 and processed by Ficoll-hypaque density gradient for cell isolation. For virus isolation, one million cells from each mother or infant were co-cultured with HIV seronegative donor cells previously stimulated by PHA as described in the ACTG virology manual . The remescribed ,56. Thisgag gene was amplified by RT-PCR for viral load determination. The mean log viral load was calculated and compared between transmitting and non-transmitting mothers to determine the effect of maternal viral load on HIV vertical transmission.HIV RNA copies in maternal plasma was determined by the amplicor HIV monitor test  at the Puerto Rico ACTG-certified laboratory . A 142 b4.6 TCID50/ml) obtained from the NIH AIDS Research and Reference Reagent Program was used to inoculate fresh cultures of macrophages grown on 75 ml tissue culture flasks. The cultures were washed 24 hours later and incubated with fresh media. Supernatant fluids were harvested at 7 and 14 days post-infection, clarified by centrifugation at 1800 rpm for 10 minutes and used as stock virus for these studies. The stock contained 5 × 105 TCID50/ml.HIV-1BaL stock was prepared in primary macrophages as reported previously by Jolly . Briefly3 TCID50/ml of virus and pre-incubated at 37°C for 30 min. The mixtures were then inoculated into replicate cultures of monocyte-derived macrophages as prepared previously [2 incubator. The inocula were removed and the cells washed, and incubated with fresh media for up to 8 days. Culture supernatant fluids were then collected on days 2, 4, 6, and 8 and tested for p24 antigen using the Coulter assay . Cultures treated with HIV-negative sera were used as controls. All maternal and infant plasma samples were tested at three 10-fold dilutions; 69% of samples were tested up through six 10-fold dilutions. Two independent assays were conducted for each maternal or infant plasma sample and each sample was run in duplicate on each assay (4 replicates).A neutralization/enhancement assay was conducted using maternal or infant samples and HIV-1BaL. Maternal plasma samples collected during the third trimester of pregnancy were used in these assays since most prenatal HIV infections occur in the third trimester . Brieflyeviously  in 8 welDescriptive statistics such as mean, median, range were calculated to summarize maternal characteristics such as viral load, CD4+ T cell count and p24 antigen levels. The number of HIV vertical transmission among infants was summarized and the univariate association of maternal characteristics, such as, treatment , stage of disease based on the 1993 CDC classification , method Correlation between maternal versus infant p24 antigen levels and between maternal viral load and maternal or infant p24 antigen levels was evaluated using the Spearman's correlation coefficient. Enhancement, decrease , or no change in p24 levels compared to seronegative control was assessed for mother-infant pairs. The distribution of virus p24 antigen was compared between transmitting vs. non-transmitting mothers and between HIV V3+ infants and HIV V3- infants using Fisher's exact test.The author(s) declare that they have no competing interests.LMG and PEJ were involved in conception and design of the study, collection of the samples, interpretation of the data and drafting and critical review of the manuscript. PK and MA were involved in performing the laboratory experiments that resulted in the acquisition of the data, in data entry, and in drafting and revising the manuscript with LMG and PEJ. HLW was responsible for data analysis and interpretation along with PEJ, LMG and PK. All authors have read and approved the final manuscript.


Fluoxetine and olanzapine combination therapy is rapidly becoming an effective strategy for managing symptoms of treatment-resistant depression. Determining drug-drug interactions, drug metabolism and pharmacokinetics is of particular interest for revealing potential liabilities associated with drug augmentation in special patient populations. In the current studies, we chronically administered fluoxetine and olanzapine in non-stressed rats to extend our previous findings regarding body weight dynamics.Chronic fluoxetine (10 mg/kg) and olanzapine (5 mg/kg and 0.5 mg/kg) treatment decreased weight gain irrespective of olanzapine dosing. At the 10 mg/kg and 5 mg/kg dose, respectively, fluoxetine and olanzapine also significantly reduced food and water consumption. This pharmacodynamic event-related effect, however, was not observed at the 10 mg/kg and 0.5 mg/kg dosing paradigm suggesting differences in tolerability rates as a function of olanzapine dose. The decrease in weight gain was not associated with apparent changes in glucose metabolism as vehicle- and drug-treated rats showed undistinguishable serum glucose levels. The combination of fluoxetine and olanzapine in rats yielded drug plasma concentrations that fell within an expected therapeutic range for these drugs in psychiatric patients.These data suggest that fluoxetine and olanzapine treatment decreases weight gain in rats; a pharmacodynamic event-related effect that differs considerably from what is observed in the clinical condition. The possibility of mismatched models regarding body weight changes during drug augmentation therapy should be seriously considered. Treatment-resistant depression is a serious issue in psychiatry as a significant number of affected individuals show an inadequate response to single antidepressant therapy. An emerging strategy to achieve maximum mood stabilization for treatment-resistant depression, bipolar illness and depression with psychotic features is the augmentation of fluoxetine (Prozac) with novel anti-psychotic agents such as olanzapine (Zyprexa). Indeed, a number of clinical trials have suggested that such an augmentation strategy offers superior efficacy for treating resistant major depression when compared with either fluoxetine or olanzapine alone -3. Despi2A), dopamine , acetylcholine muscarinic  and histamine (H1) receptors distributed widely in limbic neural circuits may somehow account for the pharmacological basis of olanzapine-induced weight gain [We have previously shown that sub-chronic  administration of fluoxetine plus olanzapine results in a significant reduction of weight gain in rats . This fight gain . Needlesght gain . In thisnecrotising vasculitis within the site of injection. The necrotic properties of the above antidepressant have previously been reported [All rats tolerated the fluoxetine plus olanzapine regimen well. There were no mortalities as a result of 18 days of drug administration in any of the rat groups tested. The only apparent untoward side effect was tissue necrosis in the peritoneum of rats injected with fluoxetine plus 5 or 0.5 mg/kg olanzapine  when compared with the vehicle-treated group Fig. . This we10 = 5.5, P ≤ 0.001) than vehicle-treated animals  when compared with cyclodextrin-treated animals  or water  consumption during the dark cycle when compared with cyclodextrin-treated rats  or the lower 0.5 mg/kg olanzapine dose . Thus, changes in glucose metabolism are not the proximate cause affecting the differential body weight dynamics, nor the differential consumption of food and water among vehicle- and drug-treated rats. Along the same lines, levels of the hormone leptin did not differ between cyclodextrin- and drug-treated animals (data not shown), thus suggesting that chronic fluoxetine and olanzapine drug therapy does not affect leptin messages under fasted conditions in male rats.In contrast to the above findings, animals injected first with fluoxetine and then 15 min later with 0.5 mg/kg olanzapine did not show differences in food . For the chronic drug regimen, rats were injected intraperitoneally (IP) first with fluoxetine (10 mg/kg) followed 15 min later by olanzapine (5 or 0.5 mg/kg) to decrease potential pharmacokinetic interactions. Fluoxetine was dissolved in 5% γ-cyclodextrin, whereas olanzapine was dissolved in 12% γ-cyclodextrin (cyclodextrin was used to improve the stability and bioavailability of poorly soluble drugs). Dosages of the two drugs were chosen according to each drug's in vivo potencies for affecting 5-HT, DA, ACh and H systems [Guide for the Care and Use of Laboratory Animals and with approval from the NYIT IACUC.Adult male Long-Evans rats  were used in all experiments described herein. Prior to any drug treatment, all rats were handled for 5 days to minimize non-specific stress. Rats were then randomly assigned to the various experimental groups and cage mates received the same drug treatment. Animals were group-housed, 2–3 per cage under a 12 hr light:dark cycle (light on 0700) and allowed  systems ,34, and  systems ,11,35,36Rats were injected with fluoxetine plus olanzapine or their respective vehicle-solutions for 18 consecutive days and body weights recorded before (day 0) and after (day 18) drug treatment. In addition, body weights were also recorded 7 and 14 days after drug treatment to adjust for dosage. To determine average food intake over a 12 hr period, control-vehicle and experimental rats were given pre-measured food pellets (25 g/rat) on day 10 and subsequent consumption was recorded on the next day. To keep track of food spillage, cage bedding was randomly separated to assess degree of unconsumed food. A similar procedure was instituted to assess average water intake over a 12 hr period: both groups were given pre-measured tap water (100 mL/rat) on day 12 and subsequent consumption was recorded on the next day. On the last day of injections (day 18), rats were either decapitated or perfused under deep chemical anesthesia  with 4% paraformaldehyde. Trunk blood or blood collected from cardiac puncture was collected in centrifuge tubes containing either no EDTA or a 0.3 M EDTA (pH 7.4) solution. Blood samples with 0.3 M EDTA were centrifuged at 10,000 RPM for 10 min and the collected serum frozen at -80°C until determination of glucose levels. Blood collected without EDTA was also frozen at -80°C until determination of drug plasma concentrations by GC-MS.To determine relative glucose levels, all animals were fasted for 12 hr on the last day of injections . Glucose serum levels were determined using the Life-Scan One Touch Basic Meter . In brief, 10 μl of serum was pipetted as a free-flowing drop onto each One Touch Test Strip and read in the glucose meter for 45 sec. Fasting glucose levels are presented as means ± SEM in mg/dL.All solvents used for drug analyses were HPLC grade. Chloroform and 1-chlorobutane were obtained from Burdick & Jackson . Ethyl Acetate and acetonitrile were obtained from EMD . Ammonium Hydroxide, ACS certified, was obtained from Fisher . Ascorbic acid was obtained from Sigma , whereas trifluoroacetic anhydride was obtained from Pierce .Working solutions containing olanzapine, fluoxetine and norfluoxetine at 10 ng/μL, 1.0 ng/μL, and 0.1 ng/μL, respectively were prepared in methanol. The working solutions used to prepare the calibration standards and controls were derived from different sources of reference material  or different weighing of the same reference material . Calibration standards and controls were prepared by adding appropriate amounts of working solutions to clean, separate silanized 16 × 100 mm culture tubes that contained 1 mL of blank bovine blood and 0.2 mL of 2.5% ascorbic acid. The calibration standards ranged from 1 ng/mL to 1000 ng/mL. The controls were prepared at 35 ng/mL, 100 ng/mL, and 650 ng/mL.2O was added to each tube. The samples were therefore a 4-fold dilution compared with the standards and controls. A 0.2 mL volume of 2.5% ascorbic acid was added to each sample in a preparation tube. Sample, standards, and controls were extracted by a liquid/liquid procedure. Eighty ng of fluoxetine-d6 (80 μL of 1 ng/μL fluoxetine-d6 in Milli Q H2O) and 80 ng of clozapine (80 μL of 1 ng/μL clozapine in methanol) were added to each tube and the tubes were then briefly vortexed. A 0.1 mL volume of the concentrated ammonium hydroxide and a 4 mL volume of 1-chlorobutane: acetonitrile (4:1) was then added to each tube. A clean teflon-lined screw cap was placed on each tube. The tubes were mixed 20 min using a reciprocating shaker and centrifuged at 2000 rpm for 10 min using an IEC centrifuge . Using clean, separate glass Pasteur pipettes, the upper organic layer from each tube was transferred to clean, separate 13 × 100 mm culture tubes. The organic layer was evaporated to dryness under a stream of air at 40°C using a Turbo Vap evaporator .A 0.25 mL volume of each blood sample was transferred to clean silanized 16 × 100 mm culture tubes. To bring the sample preparation to a volume of 1 mL, a 0.75 mL volume of Milli Q HFor derivatization, a 0.1 mL volume of chloroform and a 0.1 mL volume of trifluoroacetic anhydride were added to each tube. Clean teflon-lined screw caps were then placed on each tube. The tubes were heated for 20 min at 70°C using a dry block heater. After heating, the tubes were removed from the heater and allowed to cool at room temperature. The caps were then removed and the tubes evaporated using the same conditions as described above. Derivatized extracts were reconstituted with 100 μL of ethyl acetate and were then transferred to clean, separate auto-sampler vials.6: 429, olanzapine: 409, clozapine: 423. For fluoxetine, norfluoxetine, and fluoxetine-d6, the protonated ammonia adducts of the molecule ions were monitored. For olanzapine and clozapine, the protonated molecule ions were also monitored. Fluoxetine-d6 was used as the internal standard for fluoxetine and norfluoxetine. Clozapine was used as the internal standard for olanzapine. The limit of quantification for fluoxetine, norfluoxetine and olanzapine was 5 ng/mL. Data are presented as the means ± SEM.The GC-MS system consisted of an Agilent 6890 gas chromatograph and an Agilent 5973 MSD mass spectrometer . The data system consisted of a Hewlett-Packard X A 6/400 computer and Agilent Chemstation software. For chromatographic separation, a ZB-5, 30 meter × 0.25 mm id, 0.25 μm capillary column  was used. The carrier gas was ultra high purity helium at a flow rate of 1.0 mL/min. The injection port temperature was 260°C and the transfer line temperature was 300°C. The column oven temperature program was 125°C, held at this temperature for 0.2 min, and then increased to 300°C. Positive chemical ionization was used for the mass spectrometry analysis. The ion source temperature was 200°C and ammonia was used as a reagent gas. Selected ion monitoring was used and the following ions (m/z) were analyzed: norfluoxetine: 409, fluoxetine: 423, fluoxetine-dt tests where appropriate. Plasma levels of fluoxetine and olanzapine were analyzed by a Student's t-test. The probability level interpreted as significant was P ≤ 0.05.Statistical comparisons in body weight and glucose levels were carried out using one-way ANOVA or two-tailed JAP and JMC participated in the in vivo studies and in the biochemical assays. BHH and JMH participated in the design of the studies and performed the statistical analysis. GT drafted the manuscript, conceived the study and participated in its design and coordination. All authors read and approved the final manuscript.