Reports from different populations show variable associations of TB susceptibility and severity with cytokine gene polymorphisms. Tuberculosis clinical severity is multi-factorial and cytokines play a pivotal role in the modulation of disease severity. We have recently reported that the ratio of two key cytokines (IFNγ and IL10) show significant correlation with the severity spectrum of tuberculosis. The objective of the current study was to analyze the frequency of cytokine gene polymorphisms linked to high and low responder phenotypes (IFNγ +874 Thi→Alo and IL10 −1082 Glo→Ahi) in tuberculosis patients.Pakistan ranks 7TT genotype and T allele was overrepresented in PMN (p = 0.01) and PMD (p = 0.02). IFNγ +874 TT in combination with IL10 GGlo genotypes showed the highest association . IFNγ AAlo on the other hand in combination with IL10 GGlo increased the risk of PAD  and DTB .Study groups were stratified according to disease site as well as disease severity: Pulmonary N = 111 ; Extra-pulmonary N = 67  and compared with healthy controls (TBNA = 188). Genotype analyses were carried out using amplification refractory mutation system-PCR (ARMS-PCR) and stimulated whole blood (WB) culture assay was used for assessing cytokine profiles. Our results suggest that the IFNγ +874 These findings are consistent with the role of IL10 in reducing collateral tissue damage and the protective role of IFNγ in limiting disease in the lung. Several reports from different countries have shown that household contacts of active pulmonary tuberculosis are at much higher risk of latent infection that range from 30–80% depending on the intensity of tuberculosis disease transmission Thi→Alo) polymorphism is located within a putative NF-kb binding site and shows preferential binding to the T allele and correlates with high IFNγ producer phenotype in situ, depending on the disease site. IL10 is particularly important in reducing collateral tissue damage, particularly in the lung by dampening macrophage activation and by indirectly antagonizing IFNγ function Thi→Alo and IL10 −1082 Glo→Ahi) to analyze the relationship of these SNPs with clinical severity of tuberculosis. Our results show that SNPs in IFNγ are significantly related to site of TB disease (Pulmonary vs. Extrapulmonary) while combinations of SNPs in IFNγ and IL10 genes are important determinants of TB disease severity. Our results therefore substantiate our aim of the study.Pakistan ranks 7p<0.05) in TBA compared to TBNA. However, no significant association of genotype with age or sex was observed in both TBA and TBNA (>0.05) using multiple logistic regression analysis (data not shown).There were no significant differences in age in TBNA and TBA groups . The rathiT→Alo) and IL10 (−1082 Glo→Ahi).We found IFNγ TT and IL10 AA to be the high producer phenotype in response to mycobacterial antigens. We next looked at the frequency of these genotypes in association with disease severity.T→A genotype distribution was in Hardy-Weinberg equilibrium for both patients and controls . On the other hand, IL-10 −1082G→A polymorphism showed deviation from HWE due to excess of heterozygosity . Cases and controls were compared using χ2, odds ratios (OR) and their confidence intervals, (95% CI). A p value of <0.05 was considered significant. Different cytokine genotypes and alleles showed distinct associations with different disease types as described below.Cytokine genotypes and alleles frequencies in all patient groups were compared with healthy controls  & 4. IFNTT genotype showed significant association with PTB  (vs. LTB). When we compared healthy controls with latent infection (TST+) similar and much more marked effect of IFNγ +874 TT genotype was observed (vs. ETB) but there was a distinct difference between severity within a disease site (PMD vs. PAD). These results therefore suggest that it is inappropriate to pool tuberculosis patient with differing sites and even severity within individual sites.IFNγ +874 = 0.034) . This as= 0.034) . In termobserved . Therefop values were similar when patients were compared with TST+ controls . The results were similar when cases were compared with TST+ controls.We have previously shown that IFNγ/IL10 ratio is a critical determinant of disease severity AAhi may play a critical role in limiting tissue damage in PTB. Because of careful characterization of disease in each of the group, we are able to show significant differences between groups and among groups. In addition, differences seen in both cytokines SNPs can be reconciled with their biological function. We feel that this is a very important issue despite small numbers in the stratified groups. When pulmonary patients are not stratified the sample size is sufficient for power of statistics. We have therefore given results for both pooled and stratified groups. There are very few studies, which relate genotype to phenotype. This is the strength of the current study.Although the effect of cytokine gene polymorphisms (SNPs) on tuberculosis disease sites or disease severity have been reported in different populations, our results for the first time show differential association of cytokine genotype combinations with either pulmonary or extra-pulmonary disease. We also report that in the lung compartment the high responder IL10 −1082 Thi→Alo) is the most studied polymorphism in terms of association with tuberculosis disease sites and severity. However, the reports are conflicting in that A allele is more common in patients with TB and T alleles, more common in controls in Italian A allele A allele was found only in microscopy and culture positive vs. negative TB patients. On the other hand, no association has been reported in Caucasians in Houston, Texas T allele with the more localized pleural disease has been observed. Our results are in agreement with the latter study. We show that the effect of IFNγ T allele in TB affected patients is restricted to pulmonary patients with minimal/ moderate disease increasing the risk by 2–3 folds (AAhi may limit lung tissue damage when associated with IFNγ TThi. Turner has reported AA to be a low producer phenotype in response to mitogenic (ConA) stimulus There are considerable variations in allelic frequencies of cytokine gene polymorphisms in different populations –3 folds . Both ouGlo→Ahi) where no associations were reported in Gambian A allele was observed in Italian (Sicilian) GA heterozygosity was associated with pulmonary TB in Cambodia GGlo increases the risk of DTB when it is associated with IFNγ +874 AAlo phenotype . This is consistent with the low levels of mycobacterial stimulated IFNγ and IL10 from DTB GA heterozygous genotype in our study groups and may increase the risk of PMN when associated with IFNγ AAlo . The control group consisted of healthy donors (TBNA = 188) with no signs, symptoms or history of previous tuberculosis. Tuberculin skin tests (TST) positivity was assessed by administering five tuberculin units intracutaneously on the volar surface of the right arm. An induration of ≥10 mm was used as a cut for positive responses (TST+) which is considered to be indicative of latent infection. The Aga Khan University Ethical Review Committee (ERC) approved the project. Written consent was obtained, for each participant or his or her guardians in case of minors after explaining the purpose of the study.Five ml blood were collected in ACD  tubes and kept frozen until use. Genomic DNA was extracted from frozen whole blood using Promega Wizard Genomic DNA Purification Kit  according to the manufacturer's instructions. After extraction, DNA was quantified by spectrophotometery, checked for purity and stored at −35°C until further analyses.IFNγ and IL10 genotype analyses were carried out using amplification refractory mutation system-PCR (ARMS-PCR) 5′-TAT GAT TCT GGC TAA GGA-3′), IFNγ Reverse (5′-CCC CAA TGG TAC AGG TTT CT-3′) and IL-10 Forward (5′-TGT GGA AGG GGA AGG TG-3′), IL-10 Reverse (5′-TAA AAG ATG GGG TGG AAG AA-3′). These primers were designed using software Lasergene version 7.0  and amplify a part of the gene that covers IFNγ (+874T→A) or IL10 (−1082G→A) SNPs to yield products size of 318 and 329 bp respectively. PCR products were purified with the QIAquick PCR purification kit  according to the manufacturer's instructions. Purified products were then sent to Macrogen for sequencing  with both forward and reverse primers. Sequencing results were analyzed by BLAST search of the GenBank database and EMBOSS pairwise alignment of the EMBL-EBI database. There was complete concordance between PCR based and sequence based analyses for homozygous as well as heterozygous genotypes .Sequencing methodology was used as a second confirmatory method on a subset of samples to verify that correct alleles were being identified by ARMS-PCR. The primers used for sequencing analyses were IFNγ Forward (Stimulated whole blood (WB) culture assay for assessing cytokine profiles have been described in detail previously Cytokine (IFNγ and IL10) in supernatants were assessed using pairs of monoclonal antibodies as described in detail previously p<0.05 were considered significant for both Pearson and linear-by-linear χ2 test. Hardy-Weinberg proportions were determined by applying the equation (p2+2pq+q2).Allelic and genotypic frequencies and multi loci analysis were compared for all groups together and for individual patient and control groups. Computer software SPSS version 16.0 and Epi Info 2000 applications were used to carry out statistical analyses. Frequencies were compared between groups by Pearson chi-squared tests or Fisher's exact tests, when analyzing allelic frequencies lower than five to determine statistical significance differences between groups. Odds ratios (OR) with respective confidence intervals (95% CI) for disease susceptibly were also calculated. Linear-by-linear test were used to determine the significance  of genotypes between TB groups and healthy controls. Multiple logistic regression analysis was applied, to determine the effect of age and sex with genotypes. Values of


Individuals homozygous for α+-thalassaemia have microcytosis and an increased erythrocyte count. α+-Thalassaemia homozygosity confers considerable protection against severe malaria, including severe malarial anaemia (SMA) (Hb concentration < 50 g/l), but does not influence parasite count. We tested the hypothesis that the erythrocyte indices associated with α+-thalassaemia homozygosity provide a haematological benefit during acute malaria.The heritable haemoglobinopathy α+-thalassaemia against severe malaria were reanalysed to assess the genotype-specific reduction in erythrocyte count and Hb levels associated with acute malarial disease. We observed a reduction in median erythrocyte count of ∼1.5 × 1012/l in all children with acute falciparum malaria relative to values in community children (p < 0.001). We developed a simple mathematical model of the linear relationship between Hb concentration and erythrocyte count. This model predicted that children homozygous for α+-thalassaemia lose less Hb than children of normal genotype for a reduction in erythrocyte count of >1.1 × 1012/l as a result of the reduced mean cell Hb in homozygous α+-thalassaemia. In addition, children homozygous for α+-thalassaemia require a 10% greater reduction in erythrocyte count than children of normal genotype (p = 0.02) for Hb concentration to fall to 50 g/l, the cutoff for SMA. We estimated that the haematological profile in children homozygous for α+-thalassaemia reduces the risk of SMA during acute malaria compared to children of normal genotype .Data from children living on the north coast of Papua New Guinea who had participated in a case-control study of the protection afforded by α+-thalassaemia may contribute substantially to their protection against SMA. A lower concentration of Hb per erythrocyte and a larger population of erythrocytes may be a biologically advantageous strategy against the significant reduction in erythrocyte count that occurs during acute infection with the malaria parasite Plasmodium falciparum. This haematological profile may reduce the risk of anaemia by other Plasmodium species, as well as other causes of anaemia. Other host polymorphisms that induce an increased erythrocyte count and microcytosis may confer a similar advantage.The increased erythrocyte count and microcytosis in children homozygous for α +-thalassaemia-homozygous children against severe malaria anaemia.Karen Day and colleagues show that increased microcytic erythrocyte count may contribute substantially to the protection of α +-thalassemia, which is common in Africa and Southeast Asia, provides protection against malaria, a parasitic disease that occurs in tropical and subtropical parts of the world. α+-Thalassemia is caused by the loss of one or more of the genes that encode the α chains of hemoglobin, the red blood cell (erythrocyte) protein that carries oxygen around the body. These α chains are normally encoded by four genes, two on each Chromosome 16 . People with heterozygous α+-thalassemia lack one copy of the α chain gene and have a –α/αα genotype (genetic makeup). People with homozygous α+-thalassemia lack one copy of the gene on each chromosome (they have a –α/–α genotype) and have mild “microcytic anemia,” a condition characterized by increased numbers of abnormally small erythrocytes (microcytosis) that contain reduced amounts of hemoglobin.Mutations (changes in the DNA that encodes proteins) continually arise within human populations. Harmful mutations that affect an individual's ability to reproduce usually disappear, but most other mutations persist at a low frequency. Some mutations, however, protect their human carriers against specific disease-causing organisms, and consequently occur at high frequencies in human populations that live in places where these organisms are common. For example, the inherited blood disorder α+-thalassemia causes mild anemia, it provides protection against severe malarial anemia, a potentially fatal complication of malaria. Malaria parasites cause anemia because they multiply inside erythrocytes and rupture them. Scientists originally thought that α+-thalassemia protects against malaria by interfering with the parasite's ability to infect erythrocytes, but the evidence collected so far does not support this hypothesis. In this study, therefore, the researchers have investigated whether the microcytosis and increased erythrocyte count associated with α+-thalassemia might be responsible for the protection that this blood disorder provides against severe malarial anemia. Specifically, they asked whether this hematological (blood) profile protects against severe malarial anemia because people with the –α/–α genotype lose less hemoglobin for a given degree of malaria-induced erythrocyte loss than do those with the normal genotype.Paradoxically, although homozygous α+-thalassemia) showed that homozygous α+-thalassemia protects against severe malaria. To investigate why, the researchers re-analyzed the genotype-specific reduction in erythrocyte counts and hemoglobin levels associated with acute malarial disease in these children and developed a simple mathematical model to predict hemoglobin levels after malaria infection. They found that when malarial infection reduced the number of erythrocytes per liter of blood by more than 1.1 × 1012 , children with homozygous α+-thalassemia lost less hemoglobin than did those with the normal genotype. Furthermore, children with homozygous α+-thalassemia needed a 10% greater reduction in their red blood cell count than children with the normal genotype for their hemoglobin levels to fall below the value that defines severe malarial anemia.A study done in the mid 1990s in children living on the north coast of Papua New Guinea , but speculate that the hematological profile associated with α+-thalassemia might also prevent other Plasmodium species causing anemia. Futhermore, they suggest, other mutations that increase the erythrocyte count and cause microcytosis might protect against severe malaria anemia in a similar fashion.These findings suggest that the increased number of abnormally small erythrocytes associated with homozygous αhttp://dx.doi.org/10.1371/journal.pmed.0050056.Please access these Web sites via the online version of this summary at thalassemia and on malaria (in English and Spanish)The MedlinePlus encyclopedia contains pages on US National Heart Lung and Blood Institute, from the US National Human Genome Research Institute, from the Cooley's Anemia Foundation, and from MedlinePlusDetailed information is available on thalassemia (including useful links to other resources) from the malaria (in English and Spanish)The US Centers for Disease Control and Prevention provide information on malaria Information is also available from the World Health Organization on  In other words, children homozygous for α+-thalassaemia would require 10% greater reduction in erythrocyte count than children of normal genotype, for Hb concentration to fall to 50 g/l. This result should be considered in relation to our observation that similar degrees of reduction in erythrocyte count were found among α+-thalassaemia genotypes in acute disease, relative to community controls  erythrocyte loss was higher in homozygous α+-thalassaemia homozygotes, we applied the reduction of 2.35 × 1012/l erythrocytes  to all children living in the community. The proportion of community children predicted to develop SMA, defined by the genotype-specific erythrocyte count definitions for SMA, was lower in children who were homozygous for α+-thalassaemia  than in heterozygous children , and those of normal genotype . Compared with normal children, the risk of a community child being defined as having SMA was 0.52  in α+-thalassaemia homozygotes and 0.74  in heterozygotes for this degree of reduction in erythrocyte count. This simple model based on observed haematological data predicted that children who were homozygous for α+-thalassaemia would be 48% less likely to develop SMA than children of normal genotype.To determine whether microcytosis and increased erythrocyte count could explain the protection observed against SMA in α+-thalassaemia may be a haematological advantage in the face of the estimated >30% reduction in erythrocyte count, which we observed in PNG children with acute malaria.The reasons for the microcytosis and relatively high erythrocyte count in carriers for alpha or beta thalassaemia are not understood. It has been proposed that it reflects an increased number of terminal cell divisions during erythropoiesis, due to the combination of defective haemoglobinisation of the erythrocytes and a highly proliferative bone marrow . We inve12/l) at which microcytosis and an increased erythrocyte count becomes an advantage to the host. This erythrocyte cutoff is considerably lower than the median erythrocyte reduction we estimated to be associated with acute malaria (∼1.5 × 1012/l). This result would account for the reversal of Hb concentrations in children with acute malaria , a phenomenon that has been noted previously , 3.27 × 1012/l [2.11–4.44]; mild malaria, 90 g/l [67–103], 4.03 × 1012/l [3.12–4.84]; community children, 100 g/l [88–109], 4.78 × 1012/l [4.24–5.24].Hb is positively associated with erythrocyte count, (158 KB JPG)Click here for additional data file.


Apoptosis was associated with cleavage of p22 BID protein to p15, p13 and p11 fragments and activation of JNK and tyrosine phosphorylation (18 kDa and 45 kDa proteins). All these effects and apoptosis were prevented by exogenous glutathione (15 mM). Protein tyrosine phosphatase activity was unchanged. The general caspase inhibitor Z-VAD-fmk prevented apoptosis but not JNK activation – excluding a role for caspases in JNK activation, whereas curcumin prevented JNK activation but only delayed apoptosis. This suggests that in isothiocyanate-induced apoptosis, the caspase pathway has an essential role, the JNK pathway a supporting role, and inhibition of protein tyrosine phosphatases is not involved. © 2001 Cancer Research Campaign


P. falciparum genome that take advantage of post-PCR ligation detection reaction and fluorescent microsphere labeling strategies. Data from these assays produce a spectrum of outcomes showing that infections result from single to multiple strains. Traditional methods for distinguishing true positive signal from background can cause false positive diagnoses leading to incorrect interpretation of outcomes associated with disease treatment.Diagnosis of infectious diseases now benefits from advancing technology to perform multiplex analysis of a growing number of variables. These advances enable simultaneous surveillance of markers characterizing species and strain complexity, mutations associated with drug susceptibility, and antigen-based polymorphisms in relation to evaluation of vaccine effectiveness. We have recently developed assays detecting single nucleotide polymorphisms (SNPs) in the Plasmodium falciparum dihydrofolate reductase SNPs associated with resistance to a commonly used antimalarial drug, Fansidar (Sulfadoxine/pyrimethamine), and presumably neutral SNPs for parasite strain differentiation, we first evaluated our data after setting a background signal based on the mean plus three standard deviations for known negative control samples. Our analysis of single allelic controls suggested that background for the absent allele increased as the concentration of the target allele increased. To address this problem, we introduced a simple change of variables from customary  (Cartesian) coordinates to planar polar coordinates (X = rcos(θ), Y = rsin(θ)). Classification of multidimensional fluorescence signals based on histograms of angular and radial data distributions proved more effective than classification based on Cartesian thresholds. Comparison with known diallelic dilution controls suggests that histogram-based classification is effective for major:minor allele concentration ratios as high as 10:1.Following analysis of P. falciparum mutations is more accurately diagnosed when a simple polar transform of the  data into  is used. The development of high through-put methods for genotyping P. falciparum SNPs and the refinement of analytical approaches for evaluating these molecular diagnostic results significantly advance the evaluation of parasite population diversity and antimalarial drug resistance.We have observed that the diallelic SNP data resulting from analysis of  Evaluating genotype data of pathogens isolated from a single human host presents an important challenge for molecular diagnostic assays as each human sample can contain varying numbers of parasite strains . GenotypPlasmodium falciparum (Pf) [We have recently developed a post-PCR, ligase detection reaction - fluorescent microsphere assay (LDR-FMA) to evaluate single nucleotide polymorphisms (SNPs) associated with drug resistance in the notorious malaria parasite, rum (Pf) . This asrum (Pf) .x,y) coordinates into polar  coordinates as described below. In the standard Cartesian representation, the x-axis represents the fluorescence signal in an individual sample associated with allele X  and the y-axis represents the fluorescence signal associated with allele Y . This polar transformation takes into account the apparently linear crosstalk interaction responsible for the background signal. A similar kind of bivariate transformation has been applied to genotyping of diploid systems [We approach the problem of accurate genotype identification by transforming bivariate fluorescence data from standard Cartesian , X-/Y+ (infected by mutant parasites only), X+/Y+ (infected by both wild-type and mutant parasites), or X-/Y- (no infection). Three of these states  cannot be distinguished using standard blood smear microscopy because the SNP does not confer observable changes in parasite morphology. The goals of the present study were to distinguish the infection states of individuals in an endemic population and to establish levels of confidence in the diagnostic assessment.When diallelic SNPs occur in a population of haploid P. falciparum cover a continuous and varying range as a human infection can consist of multiple parasite strains with wide ranging parasitemia levels for each strain. The LDR-FMA procedure produces fluorescence measurements associated with the presence of varying levels of one or two site-specific alleles in a blood sample. Some low-level background signal is observed in control samples containing no DNA. The standard method for establishing the presence of a given allele in a sample is to impose a threshold based on the background signals obtained from a number of blank controls; background signals for alleles of the Pf dihydrofolate reductase gene (dhfr) when evaluated in uninfected North American controls ranged from 154 to 322 Median Fluorescence Intensity (MFI) units [dhfr SNP occurring at amino acid 164 . PCR amplification was performed on a dilution series of the Pf laboratory-adapted strain, 3D7 (dhfr 164I). The average background signal when no 3D7 genomic DNA was added to the initial PCR was 95.5 MFI units (3xSD = 156.6 MFI units). At higher concentrations of 3D7 genomic DNA the dhfr 164L signal was consistently above the conventional background value (> 200 MFI units).Unlike genotyping results on single-copy loci from diploid organisms, where allele-specific signals are based on discrete template quantities , allele-specific signals for dhfr 59 (C/R) locus. This locus was chosen as both alleles are found in the PNG parasite population, in contrast to the dhfr 164 locus. Using the threshold determined as three standard deviations above the mean calculated from known negative samples, these results suggest that 68 individuals (25.8%) were infected with mixtures of 59 C and R  fluorescence data that is compatible with this natural multiplicative structure in the distribution of the data. We introduce polar coordinates  such that r represents the distance in the plane from the point at  to the point at , and provides a measure of the overall level of infection. The quantity θ represents the angle between the x-axis and ray extending from the point at  to the point at . The angle θ depends only on the ratio y/x of the two fluorescence signals. If the background signal were truly linear, samples with single strain infections would appear in the Cartesian plane along lines with y/x ratios equal to a constant. Consequently we sought to determine diagnosis thresholds in terms of the angle θ  rather than in terms of x or y alone.Because the two sequences differ at only a single base pair, it was not surprising that a small fraction of LDR products representing the 164L allele (not present in 3D7) formed despite sequence mismatch when the concentration of the 164I template increased through PCR amplification. This is particularly true since the mismatched base pairs occur at the end of the oligonucleotide probe sequences and not in middle positions found to be more destabilizing to probe hybridization . In our ividuals 5.8% wereividuals 5.8% wereX,Y) plane. Results for individuals with monoallelic infections lie near either the x- or y-axis, whereas results for mixed strain infections lie somewhere in the upper right region of the plane. Uninfected individuals cluster together near the origin. The classification problem amounts to drawing boundaries between these groups and providing confidence level assessments of the locations of the boundaries. In the  plane, the transformed fluorescence data again occupy four regions , and finishing with the maximum magnitude, r+ = max(r). We chose the number of bins as r- ≤ r ≤ r- + 100. Heuristically, the density of points along the r-axis should peak near r = r- and decrease smoothly as we move to successive bins, leaving the uninfected population; the density should reach a minimum before climbing again as one enters the various infected populations. Practically, this method has worked well for data sets ranging in population size from 44 to 667. For very small data sets (n ≤ 40) this histogram-based method should be used with caution. For further details on implementing the algorithm, see Methods. Sample code written in MATLAB is available from the authors upon request.Our histogram-segmentation analysis of the diallelic population fluorescence data proceeded in two steps. First, we constructed histograms corresponding to the number of data points in the population with magnitudes θ of the remaining, infected individuals . We set the threshold for the X-/Y+ population (wild-type infection only) to be the first minimum in the histogram as θ increases past the local maximum near θ ≈ 0. The threshold for the X-/Y+ population (mutant infection only) is the first minimum below the local maximum near θ that is positive  plane) but close to zero. Individuals with infections carrying only the mutant allele lie scattered around a vertical line at an angle close to but less than θ. Once thresholds for distinguishing the four classes of infection/no infection in the polar coordinate plane were established, an inverse polar coordinate transformation returned the data and the diagnosis thresholds to the Cartesian  plane  percentile confidence intervals that were placed at the α1 <α2 <...<αn. Each pair of confidence parameters αj <αj + 1 encloses a region of the  plane  plane). A hypothetical point lying in such a region would have a classification confidence between αj and 1-αj + 1. For example, the pair αj = .05 <αj + 1 = .10 would determine a region of the plane corresponding to points with diagnosis confidence exceeding 90%, but not higher than 95%. Table error)). This upper bound on the probability of error in turn gives us a lower bound on the overall confidence of our classifications (as 1-Pr (error)), shown in Table In order to estimate the probability of classification error following polar transformation of the data, we used bootstrap resampling with replacement to establish percentage confidence interval distributions for the three thresholds  . With eaet cetera. The last two rows of Table The first column of Table In order to assess the sensitivity of the histogram segmentation based diagnostic method we used mixtures of laboratory clones  with known genotypes to perform control LDR-FMA assays on the chr1SNP  and breaks down once the ratio between major and minor allele concentrations becomes too large. Samples with major:minor allele ratios ranging from 1:1 to 5:1 were called correctly (as mixed infections) 100% of the time (18 out of 18 samples); samples with ratios of 9:1 or 10:1 were called correctly 67% of the time (4 out of 6 samples); both pure samples were called correctly. Mixed samples with ratios of 15:1 were called correctly 50% of the time (1 out of 2 samples) and samples with ratios of 29:1 or higher were always miscalled (as single rather than mixed infections). This performance is expected because of the mismatch binding effect described earlier: when the lower concentration allele is present in too small an amount relative to the major allele, the minor allele disappears below the advancing background signal. Fortunately the method is nevertheless robust over a wide range. In particular, all of the 21 samples called as "mixed" with nominal confidence exceeding 95%, were in fact called correctly. By taking the natural two-dimensional geometry of the data into account, the polar coordinate/histogram segmentation method greatly reduces the risk of false positive diagnoses of mixed infection, without increasing the risk of false negative diagnoses of overall infection. In practice diagnostic assays should therefore include dilutions of allele-specific controls to evaluate potential for misclassification of samples on any given 96-well plate.dhfr 59 and 5 additional SNPs listed in Additional File Primers and PCR amplification conditions for additional SNPs) from field samples collected in PNG. Due to a range of factors the angle thresholds (θ) for distinguishing mixed from single strain infections varied significantly between SNPs. The X+/Y- versus X+/Y+ threshold (wild-type only versus mixed) ranged from 0.12 to 0.40 radians (7° to 23°) with a mean ± s.d. of 0.22 ± 0.07 radians (12 ± 4)°. The X-/Y+ versus X+/Y+ threshold (mutant only versus mixed) ranged from 1.34 to 1.48 radians (77° to 85°) with a mean ± s.d. of 1.42 ± 0.04 radians (83 ± 2)°. This variability in the natural breakpoint between single and mixed infections may result from SNP-to-SNP variability of practical peak fluorescence, differences in population structure such as relative prevalence of particular SNPs, sequence specific differences in the likelihood of mismatch binding in the LDR assay, among other effects. Because of this variability we cannot fix a single diagnosis threshold in the angle θ  that will work equally well for all populations and SNPs.We applied the histogram segmentation based diagnostic algorithm to data for six diallelic SNPs  [P. falciparum, P. vivax, P. malariae and P. ovale are observed. Informed consent was obtained from all study participants. This study was approved by the Medical Research Advisory Committee of PNG and by the Institutional Review Board for Human Investigation at University Hospitals of Cleveland, Ohio.Samples evaluated in this study were part of on-going efforts to monitor ea (PNG) ,23. Thisea (PNG) -26) for In vitro growth of Pf was performed as described previously [Pf laboratory-adapted strains obtained from the Malaria Research and Reference Reagent Resource  included 3D7 (MRA-102), HB3 (MRA-155), K1 (MRA-159) and VS/1 (MR4-176). eviously . Thin blDNA was extracted from whole blood field samples (200 μL) using the QIAamp 96 DNA Blood Kit . Genomic DNA was extracted from cultures (200 μL) of laboratory adapted Pf strains using the QIAamp DNA blood mini kit .4, 16.6 mM (NH4)2 SO4, 10 mM 2-mercaptoethanol, 100 μ M dATP, dGTP, dCTP, and dTTP, and 2.5 units of thermostable DNA polymerase. Amplification reactions were performed in a Peltier Thermal Cycler, PTC-225 . Specific primers and thermocycling conditions used to amplify the Pf dihydrofolate reductase (dhfr) target sequence for evaluating polymorphisms associated with pyrimethamine resistance were described in Carnevale et al [Primers and PCR amplification conditions for additional SNPs. Following PCR amplification, products were loaded on 2% Agarose gels , and electrophoresis was performed in 1× TBE buffer . The gels were stained for 30 min with SYBR Gold , diluted 1:10,000 in 1× TBE buffer, and DNA products were visualized on a Storm 860 using ImageQuant software .All reactions (25 μl) were performed in a buffer containing 3 pmoles of the appropriate upstream and downstream primers, 67 mM Tris-HCl, pH 8.8, 6.7 mM MgSOdhfr gene have been previously described in detail [Ligase detection reaction primers for genotyping additional SNPs. The following brief description and summary in Figure The methods and strategies used to perform the LDR-FMA evaluation of Pf mutations in the n detail . Primers5 beads/mL/US$25) are available from Luminex Corporation .Following PCR amplification of the gene-specific target sequences carrying the locus of interest, products were combined into a multiplex LDR (Step #1) where allele-specific upstream primers ligate to conserved sequence downstream primers. Upstream, allele-specific primers include 5' extensions of unique "TAG" sequences. Downstream, conserved sequence primers are modified by 5' phosphorylation and 3' biotinylation. The 5' ends of the LDR products receive "classification" labeling in a second multiplex (Step #2) reaction where hybridization occurs between the TAG sequences added to the allele-specific primers and anti-TAG (complementary sequence) oligonucleotide probes bound to fluorescent microspheres. Following this hybridization reaction, products are incubated (Step #3) in a solution containing streptavidin-R-phycoerythrin (SA-PE) to allow "reporter" labeling through binding to the 3'-biotin on the conserved sequence primers. Detection of doubly labeled ligation products occurs through dual fluorescence flow cytometry in the BioPlex array reader  and leads to collection of "reporter" signal in unique allele-specific bins. Anti-TAG oligonucleotide probes bound to fluorescent microspheres  LDR-FMA signals from these samples were normally distributed. From these results, conventional methods (3× standard deviations above the mean) for establishing thresholds between negative and positive fluorescence were deemed appropriate for comparison against our polar transformation method Table .N bivariate  fluorescence values into polar  coordinates and forming the histogram as described above, the "first minimum after the initial maximum" in the magnitude variable was found by applying three criteria. Let n(r) denote the number of counts in the histogram centered at magnitude r and let Δr denote the bin width. (1) The histogram count at the minimum should be less than the counts on either side, or possibly equal to the number on the right, i.e. n(r-Δr) >n(r) ≤ n(r + Δr). (2) The location of the minimum should exceed the location of the first maximum. The first maximum is required to be a local maximum and to exceed a minimum count requirement, to avoid finding spurious local max/min combinations before the true first population maximum. We used bins of size Δr = 100 MFI units, approximately equal to a single standard deviation of the MFI distribution for uninfected blank samples. We find the following heuristic to be robust in practice: assuming at least 10% of the population falls in the "uninfected" class, we expect approximately 50% of that number to fall within one standard deviation of the uninfected population mean. Therefore we use a threshold for the bin count at the "first maximum" of max. (3) We impose a minimum value for the relevant "first minimum after the initial maximum." Assuming bin widths and standard deviation of MFI blank signals of 100 each, we set the bin occupancy threshold equal to twice the number of counts expected to fall between two and three standard deviations from the blank mean, if all N samples were actually uninfected. That is, we requireAll statistical analyses were performed using MATLAB version 7.7 (R2008a or b) . After transforming a set of erf denotes the standard error function.where r*) for distinguishing infected from uninfected samples, we produce a histogram of the angles θ for all Ninf ≤ N "infected" samples, i.e. those with (r >r*), in 45 bins with a width of 2 degrees ranging from zero to π/2 (ninety degrees). Here let n(θ) denote the number of counts in the histogram centered at angle θ and let Δθ denote the bin width for the angle histogram. Again we apply three criteria to find the wild-type/mixed cutoff  and the mutant/mixed cutoff . First we find the largest count in the range 0 to π/4 (45 degrees) or π/4 to π/2 (45 to 90 degrees), respectively. (1) Given maximum counts at θ = θ0  and θ = θ90  we require θ0 <θlo and θhi <θ90. (2) We require that the diagnosis thresholds be placed at local minima of the histogram, i.e. n(θlo - Δθ) >n(θlo) ≤ n(θlo + Δθ) and n(θhi - Δθ) ≥ n(θhi) <n(θhi + Δθ). (3) In order to be an appropriate local minimum, the count at θlo or θhi should not exceed the expected number of counts for the uniform distribution of Ninf samples over 45 bins, or Ninf/45.After obtaining a magnitude cutoff  [α) percentile confidence intervals that were placed at the ρ denote the density of signal throughout the polar plane, and let f denote the classification confidence associated with any given point on the polar plane. We would like to approximate the following integral in order to bound the total probability of error by our thresholds :As described in the Results section, we estimated the probability of classification error . X+/Y+) . With eas Figure . We usedθ- = min(θ) and θ+ = max(θ) (respectively for r- and r+). We can rewrite this integral as:for xi =  and N is our total sample size. If we choose a subset of confidences, such as {α1,α2,...αn} for αj ∈  then we can obtain an upper bound on the probability of error as the sum of the desired confidences, αj, multiplied by the fraction of the total sample size that lies inside those αj confidence intervals.  From these estimates, we obtain a lower bound on the overall confidence in our classifications  were genotyped at Chr1SNP using the LDR-FMA method. Allele calls were then made using both the conventional methods (3× standard deviations above the mean of known negative samples) and by the polar coordinate histogram method. Conventional thresholds are indicated by the red dotted line, and the polar thresholds are indicated by the black solid line with the black dotted line showing the 95% confidence intervals.Click here for filePlot of chr9SNP fluorescence data with conventional Cartesian thresholds and thresholds generated by the polar coordinate histogram method. Samples (n = 357) were genotyped at Chr9SNP using the LDR-FMA method. Allele calls were then made using both the conventional methods (3× standard deviations above the mean of known negative samples) and by the polar coordinate histogram method. Conventional thresholds are indicated by the red dotted line, and the polar thresholds are indicated by the black solid line with the black dotted line showing the 95% confidence intervals.Click here for fileLigation detection reaction primers for genotyping additional SNPs. Primers for the LDR-FMA diagnosis of additional SNPs utilized in assessing the sensitivity of the histogram segmentation analysis and for examining the diagnostic threshold variability.Click here for file


Previous work has not definitively established the general relationship between liposomes' configuration and composition, and their in vivo kinetics. Also, no straightforward method exists to calculate optimal liposome high-throughput production conditions for specific liposome compositions. This work presents first-principles quantitative correlations describing liposomes' in vivo drug leakage and vascular mass transfer kinetics. This work further presents a simple quantitative model relating specific liposome compositions to ideal high-throughput production parameters. The results have implications for the identification of promising liposome compositions via high-throughput screening methodologies, as well as the design and optimization of high-throughput reactors for liposome production.In developing liposomes for  Many drugs are attendant with significant systemic risks and side effects. To allow these drugs to achieve the treatment ideality of maximal efficacy and maximal specificity, it is necessary to use a targeted drug carrier to deliver and release the drugs specifically at the right time and at the right location in vivo characteristics including intrinsic destabilization, drug leakage, immunogenicity, and short plasma half-life Closed phospholipid vesicles  are widely used as targeted drug carriers to deliver and release drugs in appropriate amounts at specific times and specific locations in the body. Existing liposomes exhibit undesirable in vivo characteristics can be developed with knowledge of potential liposome compositions' in vivo kinetics. The in vivo kinetics of some liposome compositions have been characterized by experimental studies in vivo kinetics for many different liposome compositions.Liposomes with optimal Also, it is important to identify optimal high-throughput industrial liposome production conditions for liposome compositions of interest. While efficient industrial production conditions have been experimentally identified  for some liposome compositions in vivo drug leakage and vascular mass transfer kinetics for many liposome compositions.This work presents generally valid quantitative models describing liposomes' high-throughput production and predicting liposomes' Drug leakage from a widely used type of liposome, multilamellar liposomes (MLVs), is inherently minimized relative to drug leakage from one-layer, or unilamellar, liposomes due to MLVs' basic configuration  concentration of the drug in the MLVD = diffusivity of the drug in the MLVCk = mass transfer coefficient of the drugR = radius of the MLVt = elapsed timeHere, the term “homogeneous” is used to refer to the drug particles being evenly mixed with the lipid molecules throughout the MLV.A critically important issue associated with using liposomes in biological systems is the question of how the liposomes migrate in the bloodstream . From thbC = bulk liposome concentration in a vesseloC = initial (inlet) liposome concentrationck = mass transfer coefficient of the liposomes in the bloodstreammk = mass transfer coefficient of the liposomes in the vessel walltk = mass transfer coefficient of the liposomes in the tissue spaceR = radius of the blood vesselμ = dynamic viscosity of the bloodU = mean velocity of fluid flow in the vesselA highly efficient method for producing large quantities of drug-encapsulating liposomes rapidly comprises using a continuous flow reactor that can be run indefinitely as long as adequate quantities of reagents are supplied d = CTR diameterk = reaction rate coefficientu = feed flow rate in the CTRin vivo kinetics of (drug-encapsulating) liposomes. Specifically, the models describe liposomes' encapsulated drug leakage kinetics, vascular mass transfer kinetics and high-throughput production kinetics.This work presents first principles quantitative correlations characterizing the core rate processes associated with the high-throughput production and The models can be used to facilitate the high-throughput screening of drug-encapsulating liposome compositions, configurations, and/or synthesis methods, with modeling data output employed as a preliminary rapid and low-cost filter in evaluating many different drug-encapsulating liposome compositions, configurations, and synthesis procedures. For example, the models could be used to screen different drugs to see which drugs, based on known biophysical properties, could potentially be carried and delivered effectively by a MLV. Also, the models could be used to screen different lipid modifications to see what kinds of modifications  might minimize undesired leakage of a particular drug. Other applications are also possible.Compositions, configurations, or synthesis methods deemed to be promising based on the modeling output could then be further tested and characterized experimentally. Such a screening methodology is particularly important because past efforts to identify effective novel compositions, configurations, or synthesis methods have been limited due to an almost exclusive reliance on direct experimental testing. High-throughput screening using these models hence provides a way to test many more compositions, configurations, and synthesis methods (and identify more promising candidates) than experimental testing alone.Further work may be performed to test and adapt these models for specific experimental conditions in practice. Also, future studies could extend these models to cover additional classes of liposomes and to other biologically relevant micro- and nanoparticles.iC = molar concentration of species iNi = molar flux of species i (using fixed coordinates)iR = net rate of formation of species i per unit volumei is a minor component in a pseudobinary, constant density, constant diffusivity liquid solution. Then:i, and no flow:Assume C = concentration of the drug within the MLVD = diffusivity of the drug within the MLVt = elapsed timeBoundary conditions are:Ck = mass transfer coefficient of the drug within the MLVScale and nondimensionalize:r = 0:r = R (R = vessel radius):Assume fully developed unidirectional flow. Then:C = liposome concentration within the vesselr:Integrate over rN = liposome fluxAlso:A = cross-sectional area of the vesselApply the following correlations:tC = liposome concentration in the tissue at the surface of the outer vessel wallThen:jC = concentration of species jL = position in reactoru = feed flow rateAssume constant reactor radius and constant flow. Then:A = area of reactord = diameter of reactorjN = number of moles of species jr = radius of reactorV = volume of reactorAssume pseudo-second order kinetics with large excess of deposited lipid. Use:l)+10000 Drug (DRG) (l)+80000 Lipid (LIP) (s)→Liposome (DEL) (l)100 Targeting Receptors (TR) (Then:d = CTR diameterk = reaction rate coefficientu = feed flow rate in the CTR


Sections of human and porcine ureter were cultured as explants and irradiated on day 7 when the urothelial outgrowth formed a halo around the tissue fragment. The Gray Cancer Institute charge particle microbeam facility allowed the irradiation of individual cells within the explant outgrowth with a predetermined exact number of 3He2+ ions . A total of 10 individual cell nuclei were irradiated with 10 3He2+ ions either on the periphery, where proliferating cells are located, or at the centre of the explant outgrowth, which consisted of terminally differentiated cells. Samples were fixed 3 days after irradiation, stained and scored. The fraction of apoptotic and micronucleated cells was measured and a significant bystander-induced damage was observed. Approximately 2000–6000 cells could be damaged by the irradiation of a few cells initially, suggesting a cascade mechanism of cell damage induction. However, the fraction of micronucleated and apoptotic cells did not exceed 1–2% of the total number of the cells within the explant outgrowth. It is concluded that the bystander-induced damage depends on the proliferation status of the cells and can be observed in an in vitro explant model.The aim of this study was to test whether radiation-induced bystander effects are involved in the response of multicellular systems to targeted irradiation. A primary explant technique was used that reconstructed the  Until recently, it has been commonly accepted that the biological consequences following radiation exposure are attributable to direct DNA damage. According to this paradigm, DNA damage occurs during or very shortly after irradiation of the nuclei in targeted cells, and the potential for biological consequences can be expressed within one or two cell generations . SeveralThe radiation-induced bystander effect is a phenomenon whereby cellular damage  was found to be lower than when they were irradiated as single cells . Samples were placed in sterile physiological saline immediately on removal from the patient and shipped on ice to the laboratory. Explants were normally established within 24 h.L-glutamine  containing 20 mM HEPES, 10% (v v−1) foetal calf serum  and 20 IU ml−1 of aprotinin  with additions of penicillin (100 IU ml−1) and streptomycin (100 μg ml−1), (50 μg ml−1) fungisone  and nystatin . Explants were normally established within 24 h.Dr Mohi Rezvani and Neil Hubbard  generously provided porcine ureter samples. They were obtained from 10 to 72-week-old farm pigs during post-mortem examination. These animals were maintained in compliance with the Animal (Scientific Procedures) Act 1986  trypsin solution  containing 10 mg ml−1 collagenase IV  in Hank's balanced solution  and incubated for 30 min at 37°C. Ureter fragments were then plated into specially designed dishes  for microbeam experiments or in T25 tissue culture flasks  for cell growth measurements and BUdR cell proliferation measurements. The dishes contained 2 ml of serum rich ‘start-up’ medium for initial outgrowth formation. This was based on RPMI 1640 with L-glutamine , containing 13% (v v−1) foetal calf serum and 7% (v v−1) horse serum  with additions of 100 mIU insulin , 1 mg ml−1 hydrocortisone , 30 ng ml−1 human recombinant EGF , penicillin (100 IU ml−1) and streptomycin (100 μg ml−1), (50 μg ml−1) fungisone  and nystatin .An explant approach  was used2) the medium was replaced with serum-free Keratinocyte Growth Medium  or Keratinocyte-SFM  and incubated for a further 4–5 days. A typical 7-day-old, human ureter urothelium outgrowth was a few millimetres in diameter , which have almost identical track structure to that of α-particles. The explant outgrowth was irradiated through the base of the microbeam dish.The Gray Cancer Institute charged particle microbeam  allowed μM Hoechst 33258  in KGM medium for 1 h before irradiation. During the irradiation, the ureter explant outgrowth was incubated with 20 μM HEPES KGM-based medium at room temperature. A total of 10 individual cell nuclei were irradiated each with 10 3He2+ particles in a 7-day-old explant outgrowth. Cell nuclei to be irradiated were randomly selected at the periphery  and the number of delivered particles was counted with a particle detector  acridine orange , destained in PBS for 1 h, air-dried and scored using a fluorescent microscope. Typical normal urothelial cells are shown in . Fractions of micronucleated and apoptotic cells were calculated per field of view from one side of the explant to the other.On day 3 after irradiation the samples were washed in phosphate-buffered saline (PBS), fixed in 100% methanol and stained for 20 min with 0.5%  in culture medium for 3 days, to assess the total number of cells undergoing division after irradiation and before fixing 3 days later. Samples were stained with anti-BUdR (mouse IgG1) antibodies  and visualised with FITC mouse IgG (whole molecule) conjugated antibodies . A few explants were examined using antibodies to Uroplakin III, a specific marker of terminal urothelial differentiation on day 7. Explants were fixed and stained with Uroplakin III antibodies  and visualised with FITC conjugated antibodies . Scoring of the cells was performed by scanning a straight line across the explant in 0.1 mm steps under low magnification. The fractions of BUdR or Uroplakin III-positive cells were calculated per field of view.Cell proliferation was measured by adding 10 t-test.Cell damage data represent the mean and standard deviation for between two and four individual explants for each sample. In the case of cell kinetics, 10 individual explants were measured from each sample, with the mean and the standard error calculated. Individual explants were all number-coded and were scored blind. Significance tests were made using the Student's in vitro cultivation conditions is about 56±5.6 h . The explant outgrowth doubled in size within 2–3 days. The doubling time for primary urothelial cell under stimulated in vivo . However, control mean values for human samples are not statistically different from the porcine ones (P<0.05). Porcine samples irradiated at the centre demonstrated considerably higher variation in response than those irradiated at the periphery.There was considerable interindividual variations of bystander response in human and porcine samples  under in vivo conditions might be highly individual and tissue specific. In vitro cell systems are unlikely to exactly mimic the in vivo system response in terms of carcinogenesis. To date, the only other data, where cells within multicellular systems have been targeted with radiation demonstrating bystander responses, have utilised models containing one cell type (Our findings contribute to continuing debate regarding the relevance of ell type . OverallIn summary, we have demonstrated evidence of a radiation-induced bystander effect within human and porcine urothelium explant outgrowths where dividing and differentiated cells were present. The bystander response was observed when the actively proliferating region within an explant outgrowth was targeted and the distribution of additional micronucleated and apoptotic cells was nonuniform. This evidence strongly suggests that the expression of bystander damage and proliferation/differentiation state of the cells involved is linked. Further studies will test the underlying mechanisms that lead to signal transduction under these conditions.


Following a single injection of MNU into “intact” mice, a high incidence of leukaemia (90%) is obtained, with a 50% induction time of 200 days. Immunological studies indicate that the θ antigen is expressed on the leukaemic cells. Thymectomized MNU treated mice had a 50% induction time of 500 days, and the incidence was somewhat lower. Leukaemias failed to develop in MNU treated T lymphocyte deficient animals and in lethally irradiated, or thymectomized lethally irradiated mice reconstituted with MNU treated bone marrow. It is suggested that the T lymphocytes rather than the haemopoietic stem cells or pre-T cells are the “target cells” in MNU leukaemogenesis.


To evaluate whether cytokines are altered in peripheral blood of rats transgenic for the human Huntington´s disease mutation we investigated serum levels of GRO/KC, IL-1β, IL-13 and TNF-α at a symptomatic stage at 12 months of age. Overall serum levels of these cytokines were not significantly changed between transgenic HD rats and controls. Moreover, we observed a high interindividual variability. Our results indicate that these cytokines will be difficult to pursue as biomarkers in at least this rat model of HD. Huntington's disease (HD) is an autosomal dominantly inherited neurodegenerative disease that is characterized by motor, psychiatric, and cognitive symptoms leading to progressive disability and eventually early death. Despite the underlying genetic defect being known for more than 15 years Transgenic HD rats carrying a truncated huntingtin cDNA fragment with 51 CAG repeats under the control of the native rat huntingtin promoter, and their wildtype littermates were used. The expressed gene product was about 75 kDa, corresponding to 22% of the full-length huntingtin , which are under the control of 886 bp of the rat huntingtin promoter (position 900 to 15). A colony of tg rats derived from a Sprague Dawley founder rat was established at the central animal facilities at Hannover Medical School, and the line was maintained by persistent inbreeding. For the experiments, fully inbred animals derived from generation F12 were used.Genotyping was carried out as previously described A set of 12 months old rats consisting of 20 homozygous transgenicHD rats  and 20 wildtype littermates  was used in this study.  Rats were deeply anesthetized with an isofluran-inhalation-anesthesia, and subsequently, the retrobulbar venous plexus was punctured with a glass capillary and approximately 1 ml blood taken. Blood drawing and handling was performed by two experimenters (F.B. and M.S.) on one day between 8 am and 11 am. All samples were immediately cooled to 4°C and centrifuged at 400 rpm for 20 min  and the supernatant was taken. Afterwards, all samples were stored at -80°C until measurement. Serum cytokine levels  were quantified using Meso Scale Discovery  electrochemoluminescence multiplex assay using a modification of the manufacturer’s protocol. 20 ul was used as the sample volume and a 10-point standard curve was used, ranging from 2500 pg/ml to 0 pg/ml. The sample and calibrator were incubated on the MSD plate for 3 h (instead of 2 h), followed by a wash (as per manufacturer’s recommendation). The MSD plate was then incubated with detection antibody solution for 3 h (instead of 2h) before wash and read as per manufacturer’s recommendation).  Results were analyzed on a SECTOR™ 2400 instrument (MSD)..  Since gender differences have been reported for transgenic HD rats , we analyzed whether this also applies to the cytokine levels that we had investigated. One-way ANOVA for the factor sex as well as two-way ANOVA for the factors genotype and sex did not reveal any significant differences. Therefore, we had combined the results from both males and females for further statistical analyses. Data were then subjected to unpaired two-tailed t tests to identify significantly different serum levels for each cytokine. A critical value for significance of p < 0.05 was used throughout the study. All data represent means ± SEM.Clear outliers that have values more than two standard deviations above the mean value were excluded from statistical analysesTable 1 summarizes the results ofMultiplex ELISA quantification of cytokine levels in serum from transgenic HD rats  compared with control animals. Notably, we observed that in a significant number of rats (both transgenic and wildtypes) serum levels of TNF-α, IL-13 and Il-1b were below the detection limit and a value of zero was recorded. Although a zero value (lack of evidence) cannot be considered as evidence for a lack of the cytokines investigated, this poses a statistical problem. Here we present data both including and excluding zero values (see table 1).  Nevertheless a large variability of cytokine levels in HD rats and controls was observed (Table 1) and no significant differences in absolute values between groups were found for any of the four cytokines investigated., IL-1β and GRO/KC in HD rats at the age of 12 months. NS: non significant, excl.: zero values excluded, incl.: zero values included Table 1: Serum levels of TNF-α, IL-13Figure 1 illustrates the level of the various cytokines in transgenic HD rats in comparison to control levels . There was no significant difference between transgenic HD rats and controls regarding serum levels of TNF-α or IL-1β, and although there was a trend towards higher serum levels of GRO/KC and IL-13 in transgenic animals compared to wildtype animals, this observation did not reach significance. This might be due to technical limitations or due to the large biological variability of these cytokines and it is in agreement with observations in mice and humans Taken together, the investigated pro-inflammatory cytokines were not significantly changed between transgenic HD rats and their wildtype littermate controls at the age of 12 months where motor deficits, cognitive impairment and neuropathological abnormalities are readily detectable. Our results indicate that there is a significant biological variance in serum levels of these cytokines and that these cytokines will be difficult to pursue as biomarkers in at least this rat model of HD. However, we only investigated a subset of cytokines, and notably, IL-6 was not measured.  European Community ‘RATstream STREP project’ (037846 to H. Nguyen and S. von Hörsten)The authors have declared that no competing interests exist.


Glial tumours are a devastating, poorly understood condition carrying a gloomy prognosis for which clinicians sorely lack reliable predictive parameters facilitating a sound treatment strategy. Tp73, a p53 family member, expresses two main classes of isoforms – transactivatory activity (TA)p73 and ΔTAp73 – exhibiting tumour suppressor gene and oncogene properties, respectively. The authors examined their expression status in high- and low-grade adult gliomas. Isoform-specific real-time reverse transcription-polymerase chain reaction was used for the analysis of Tp73 isoform transcript expression in a series of 51 adult patients harbouring glial tumours, in order to compare tumour grades with each other, and with non-tumoural samples obtained from epileptic patients as well. Our data demonstrate increase of TAp73 and ΔTAp73 transcript levels at onset and early stage of the disease. We also show that ΔEx2–3 isoform expression in low-grade tumours anticipates clinical and imaging progression to higher grades, and correlates to the patients’ survival. Expression levels of P1 promoter generated Tp73 isoforms – and particularly ΔEx2–3 – indeed allow for prediction of the clinical progression of low-grade gliomas in adults. Our data are the first such molecular biology report regarding low-grade tumours and as such should be of help for sound decision-making. Although our knowledge of the molecular mechanisms involved in tumorigenesis and progression has significantly improved over fairly recent years, this has yet to result in an improved therapeutic strategy. To date, no reliable parameter has allowed for anticipation of clinical progression from lower to higher grades. Such criteria would be of paramount importance in therapeutic management of these patients.Glioblastomas are divided into primary or in vitro and in inducing MEF-derived fibrosarcomas in vivo in nude mice  in compliance with the ethics committee. For each patient a sample was collected at the presumed higher-grade region and named the ‘central’ sample. Whenever deemed reasonable – that is without significant additional functional risk – a second sample was harvested in the vicinity of the tumour and called ‘peripheral’.All patients were treated between January 2002 and May 2003. Distribution of patients in groups according to the WHO pathology classification appears in samples obtained either from open-sky surgery or stereotactic biopsies. Each tumour sample was divided into two parts: one was dedicated to smears, the second was immediately frozen in liquid nitrogen in the operating room, and stored at –80°C until usage.Per operative pathology exam allowed to check glial tumour diagnosis with Total RNA was extracted from tumour tissues using the RNAeasy® Mini Kit  according to the manufacturer's instructions with minor modifications, for exclusion of contaminated genomic DNA. The spin-column membranes were treated with DNase (Qiagen) for 15 min at room temperature before elution. Ten microliters of DNAse-treated total RNA was transcribed into cDNA using Superscript™ II RnaseH - and random hexamers .We assessed levels of Tp73 isoform mRNA transcripts by real-time quantitative PCR in the ABI PRISM 7000 sequence detection system . Primer sequences are listed in μl reaction volumes consisting of 1 × Taqman Universal PCR Master-Mix or SyberGreen Universal PCR Master-Mix (Applera), one out of 20 of the reverse transcription reaction, 300 nm of each primer and 200 nm of probe when Taqman chemistry was used. The samples were submitted to amplification as follows: heating at 50°C for 2 min, 95°C for 10 min followed by 40 cycles at 95°C × 15 s, 60°C × 1 min. Each RNA sample was tested in duplicate and a negative control was included in every plate. The computed tomography value was defined as the cycle number (Ct) at which the fluorescence crossed the threshold. Range of threshold cycles was Ct: 25–37.6 for P1–TAp73, Ct: 26.9–39.8 for ΔNp73 Ct: 22.89–39.43 for TAp73, Ct: 26.73–37.33 for ΔEx2p73, Ct: 23.24–38.75 for ΔEx2–3p73 and Ct:30.32–36.36 for ΔN’p73. Results were normalised using the endogenous reference GAPDH. The threshold cycle differences is given in Ct−ΔΔ formula where ΔΔCt=ΔCtTumoural−ΔCtNonTumoural.The reactions were carried out first by using the Taqman® chemistry for the global screening of P1-generated p73 transcripts (P1–p73) and P2-generated transcripts (ΔNp73). We then used SyberGreen chemistry assessing of discriminant Tp73 isoform expression. Briefly, the PCR reactions were performed in 25 The data distribution of expression levels being non-Gaussian, non-parametric tests were used for data analyses. Increase in transcript levels of each Tp73 isoform was analysed by signed tests, whereas differences between tumour tissues were tested by the Wilcoxon rank sum test. Each isoform was dichotomised according to its median value. Survival was estimated according to the Kaplan–Meier method and compared between groups by means of the log-rank test. For correlations among the various isoforms and patient age, the threshold cycle differences were used and the Spearman correlation test was applied. Multivariate analyses were performed with the Cox proportional hazard model. Models were fitted for the threshold cycle differences and for the dichotomised variable. All tests were two-sided and the type I error was set at 5%. Statistical analyses were performed with use of SAS Statistical Software (Release 8.02).P<10−3) when compared to epileptic tissue samples taken as non-tumoural controls (P<10−3). Because no significant difference was found in P1–p73 transcript expression between high- and low-grade tumours, deregulation of the P1 promoter that generates the TAp73 and ΔTAp73 isoforms was likely to occur early in the tumorigenic process. This upregulation of the P1–p73 transcripts was observed in the centre of the tumours whatever their grade. In contrast, although the high-grade tumour periphery still displayed high levels of the transcript, this expression was significantly (P=0.031) lower on the periphery of low-grade tumours  and P2 – (ΔNp73) generated transcript expression levels conducted in 11 patients shows that P1–p73 transcript levels are increased in low-grade gliomas  as compared to the expression spectrum displayed by non-tumoural, control tissue (P<10−2) and TAp73 and ΔEx2–3p73 levels (P<10−3). These data led to the conclusion that, with the exception of the ΔN’ isoform, all P1 transcripts were upregulated in the tumours. Again, these findings argued in favour of the early deregulation of the P1 promoter in tumours.Analysis of P1-p73 transcripts  shows that TAp73, ΔEx2p73 and ΔEx2-3p73 transcripts levels were increased . A similar observation was reported by P=0.007, In order to determine the clinical relevance of these findings with regards to low-grade glioma outcome, survival analysis was performed as regards overall survival rates. Taking as references the median values of mRNA levels of different transcripts – above and below the 50th percentile of the range of the latter – two groups were defined. This approach was dictated by the impossibility of estimating the absolute copy numbers of transcripts. Group 1 included patients in whom the expression levels for each transcript species were higher than their respective median values. Group 2 included patients whose expression levels were lower or equal to the median values. Among the isoforms, expression levels of the ΔEx2–3p73 transcript proved to be a strong prognostic marker for overall survival in our low-grade glioma cohort P=0.007, . AlthougP=0.017) and a trend is observed for ΔEx2–3p73 (P=0.070). However, when ΔEx2–3 expression is classified in low and high groups, the only factor that remains significant, even when age is taken into account, is ΔEx2–3p73 (P=0.025).In multivariate analysis including age and ΔEx2–3p7 expression, age is a significant prognostic factor . The expression of some transcripts could be restricted to particular areas of the tumour suggesting differential splicing in this area. Addressing this question would require to perform RNA status analysis of at the individual tumour cells level.The selective patterns of expression of the transdominantTp73 gene isoforms observed in a variety of tumours   but they only accompany, and fail to anticipate clinical tumour progression. New criteria allowing for earlier detection of tumour grade progression and correspondingly more expeditious therapeutic adaptation would be of heightened value as regards optimal treatment of these patients. Nevertheless, the use of ΔEx2–3p73 as such an indicator has one limitation, which is inherent to our methodology: as there exists no absolute quantification of this increase in transcript levels, it has got to be compared with a non-tumoural control group.In conclusion, to the best of our knowledge this is the first report of a single molecular prognostic marker criterion for low-grade glioma survival in adults. This could lead to early treatment of the newly diagnosed adult patients harbouring low-grade gliomas and exhibiting increase in transcript levels of ΔEx 2–3p73.


Escherichia coli curved DNA-binding protein A (CbpA) is a nucleoid-associated DNA-binding factor and chaperone that is expressed at high levels as cells enter stationary phase. Using a combination of genetics, biochemistry, structural modelling and single-molecule atomic force microscopy we have examined dimerization of, and DNA binding by, CbpA. Our data show that CbpA dimerization is driven by a hydrophobic surface comprising amino acid side chains W287 and L290 located on the same side of an α helix close to the C-terminus of CbpA. Derivatives of CbpA that are unable to dimerize are also unable to bind DNA. Free in solution, CbpA can exist as either a monomer or dimer. However, when bound to DNA, CbpA forms large aggregates that can protect DNA from degradation by nucleases. These CbpA–DNA aggregates are similar in morphology to protein–DNA complexes formed by the DNA-binding protein from starved cells (Dps), the only other stationary phase-specific nucleoid protein. Conversely, protein–DNA complexes formed by Fis, the major growth phase nucleoid protein, have a markedly different appearance.The  Escherichia coli, a particularly striking change in nucleoid structure occurs as cells enter stationary phase; the nucleoid adopts a super compact conformation and it is believed that this is a mechanism via which the cell can protect its DNA in harsh conditions  assay system, which relies on the fact that the E. coli cyaA- strain BTH101 is unable to produce cAMP and thus has a lac- phenotype  phenotype while cells containing pKT25-ZIP and pUT18-ZIP (encoding T25 and T18 proteins fused to a leucine zipper) have a lac+ (red) phenotype. A lac+ phenotype was also observed for BTH101 cells transformed with pKT25CbpA in combination with either pUT18CbpA or pUT18CCbpM. Thus, both CbpA–CbpA and CbpA–CbpM interactions are detected by the BACTH assay.Biochemical studies with purified proteins have shown that CbpA can dimerize and can form a complex with CbpM . Note that CbpA already has alanine residues at positions 291 and 293 and these positions were therefore not altered. The pUT18CbpAΔ10 derivatives were then used to transform BTH101 cells harbouring pKT25CbpA and β-galactosidase activities were measured in overnight cultures of the transformants. The data are shown in The data in cbpA alleles were transferred to pKT25). We therefore assume that the WA287 and LA290 substitutions must induce mild perturbations in the CbpAΔ10 structure that reduce the ability of CbpAΔ10 to interact with CbpM. We reasoned that it may be possible to ‘repair’ the CbpAΔ10–CbpM interaction by introducing amino acid side chains other than alanine at positions 287 and 290. Moreover, these CbpAΔ10 derivatives should remain unable to dimerize if W287 and L290 truly form the dimerization surface of the protein. Thus, we randomly mutagenized codons 287 and 290 of cbpAΔ10 and selected 114 cbpAΔ10 derivatives for further study. Because there is redundancy in the genetic code, we isolated many amino acid substitutions numerous times. Most of these changes resulted in misfolded proteins unable to dimerize or interact with CbpM (data not shown). However, we identified five dimerization defective CbpAΔ10 derivatives  that were able to interact with CbpM . This region corresponds to amino acids 201–303 of E. coli CbpA, essentially comprising an isolated CTD II domain. From an alignment of the two homologues  prior to beginning the assay.We determined β-Galactosidase levels in overnight cultures of BTH101 carrying derivatives of pKT25 and pUT18 by the cbpA alleles were generated using the primers listed in 650 of ∼0.5 at 37°C. Protein overexpression was then induced with 1 mM IPTG for a 1 h. Cells were harvested by centrifugation, resuspended in buffer FB  gel electrophoresis and ethidium bromide staining.DNA fragments for EMSA experiments were generated by PCR amplification using the appropriate DNA primers  and E. cWe followed the protocols of Purified plasmid DNA (77 ng) was pre-incubated with CbpA or BSA, at 37°C, in DNase I reaction buffer (NEB) in a final volume of 10 µl. After 10 min 1 µl of a freshly prepared 1:200 dilution of DNase I was added. Reactions were then returned to 37°C for a further 5 min. The reactions were stopped by adding 2 µl of 10% SDS and by incubation at 75°C for 5 min. Gel-loading dye was then added and reactions were analysed by electrophoresis on 1% agarose gels.E. coli JCB387 using a Qiagen maxiprep kit and was resuspended in water. The CbpA protein was purified as described above and Fis was purified as described previously  20 µl of the reaction was applied to a freshly cleaved mica surface. Images were then acquired in liquid using a SNL (silicon-tip on nitride lever) AFM probe  and a Veeco Multimode AFM with a Nanoscope IIIa controller operated in tapping mode at scan rates between 1.5 and 2.0 Hz to help minimize tip-sample interactions. The scan size was 1.5 µm2 at a resolution of 512 × 512 pixels. Raw data were selected with the Nanoscope software. NanoScope v5.30r3 software was used to ‘flatten’ AFM images with 3rd order polynomial fitting. AFM images were analysed further with WSxM 4.0 software . The height of particles was rounded to the nearest 0.2 nm. We note that buffer conditions for AFM analysis and bulk in vitro DNA-binding assays do, by necessity, differ substantially. Most notably, it is a prerequisite of AFM analysis to ensure that DNA molecules adhere properly to the mica surface. This is most frequently achieved by adding NiCl2 to reactions. We tested numerous DNA-binding proteins and found that, without exception, all had a higher affinity for DNA in standard AFM buffers. However, the properties of the protein–DNA complexes (with respect to their electrophoretic mobility) were unchanged (The pSR plasmid DNA for AFM analysis was isolated from cultures of nchanged .