Non-Invasive Imaging of Cysteine Cathepsin Activity in Solid Tumors Using a 64Cu-Labeled Activity-Based Probe

The papain family of cysteine cathepsins are actively involved in multiple stages of tumorigenesis. Because elevated cathepsin activity can be found in many types of human cancers, they are promising biomarkers that can be used to target radiological contrast agents for tumor detection. However, currently there are no radiological imaging agents available for these important molecular targets. We report here the development of positron emission tomography (PET) radionuclide-labeled probes that target the cysteine cathepsins by formation of an enzyme activity-dependent bond with the active site cysteine. These probes contain an acyloxymethyl ketone (AOMK) functional group that irreversibly labels the active site cysteine of papain family proteases attached to a 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) tag for labeling with 64Cu for PET imaging studies. We performed biodistribution and microPET imaging studies in nude mice bearing subcutaneous tumors expressing various levels of cysteine cathepsin activity and found that the extent of probe uptake by tumors correlated with overall protease activity as measured by biochemical methods. Furthermore, probe signals could be reduced by pre-treatment with a general cathepsin inhibitor. We also found that inclusion of a Cy5 tag on the probe increased tumor uptake relative to probes lacking this fluorogenic dye. Overall, these results demonstrate that small molecule activity-based probes carrying radio-tracers can be used to image protease activity in living subjects

Prospective randomized trial of iliohypogastric-ilioinguinal nerve block on post-operative morphine use after inpatient surgery of the female reproductive tract

<p>Abstract</p> <p>Objective</p> <p>To determine the impact of pre-operative and intra-operative ilioinguinal and iliohypogastric nerve block on post-operative analgesic utilization and length of stay (LOS).</p> <p>Methods</p> <p>We conducted a prospective randomized double-blind placebo controlled trial to assess effectiveness of ilioinguinal-iliohypogastric nerve block (IINB) on post-operative morphine consumption in female study patients (<it>n </it>= 60). Patients undergoing laparotomy via Pfannenstiel incision received injection of either 0.5% bupivacaine + 5 mcg/ml epinephrine for IINB (Group I, <it>n </it>= 28) or saline of equivalent volume given to the same site (Group II, <it>n </it>= 32). All injections were placed before the skin incision and after closure of rectus fascia via direct infiltration. Measured outcomes were post-operative morphine consumption (and associated side-effects), visual analogue pain scores, and hospital length of stay (LOS).</p> <p>Results</p> <p>No difference in morphine use was observed between the two groups (47.3 mg in Group I vs. 45.9 mg in Group II; <it>p </it>= 0.85). There was a trend toward lower pain scores after surgery in Group I, but this was not statistically significant. The mean time to initiate oral narcotics was also similar, 23.3 h in Group I and 22.8 h in Group II (<it>p </it>= 0.7). LOS was somewhat shorter in Group I compared to Group II, but this difference was not statistically significant (<it>p </it>= 0.8). Side-effects occurred with similar frequency in both study groups.</p> <p>Conclusion</p> <p>In this population of patients undergoing inpatient surgery of the female reproductive tract, utilization of post-operative narcotics was not significantly influenced by IINB. Pain scores and LOS were also apparently unaffected by IINB, indicating a need for additional properly controlled prospective studies to identify alternative methods to optimize post-surgical pain management and reduce LOS.</p

When One Size Does Not Fit All: A Simple Statistical Method to Deal with Across-Individual Variations of Effects

In science, it is a common experience to discover that although the investigated effect is very clear in some individuals, statistical tests are not significant because the effect is null or even opposite in other individuals. Indeed, t-tests, Anovas and linear regressions compare the average effect with respect to its inter-individual variability, so that they can fail to evidence a factor that has a high effect in many individuals (with respect to the intra-individual variability). In such paradoxical situations, statistical tools are at odds with the researcher’s aim to uncover any factor that affects individual behavior, and not only those with stereotypical effects. In order to go beyond the reductive and sometimes illusory description of the average behavior, we propose a simple statistical method: applying a Kolmogorov-Smirnov test to assess whether the distribution of p-values provided by individual tests is significantly biased towards zero. Using Monte-Carlo studies, we assess the power of this two-step procedure with respect to RM Anova and multilevel mixed-effect analyses, and probe its robustness when individual data violate the assumption of normality and homoscedasticity. We find that the method is powerful and robust even with small sample sizes for which multilevel methods reach their limits. In contrast to existing methods for combining p-values, the Kolmogorov-Smirnov test has unique resistance to outlier individuals: it cannot yield significance based on a high effect in one or two exceptional individuals, which allows drawing valid population inferences. The simplicity and ease of use of our method facilitates the identification of factors that would otherwise be overlooked because they affect individual behavior in significant but variable ways, and its power and reliability with small sample sizes (<30–50 individuals) suggest it as a tool of choice in exploratory studies

Generalized shrinkage F-like statistics for testing an interaction term in gene expression analysis in the presence of heteroscedasticity

<p>Abstract</p> <p>Background</p> <p>Many analyses of gene expression data involve hypothesis tests of an interaction term between two fixed effects, typically tested using a residual variance. In expression studies, the issue of variance heteroscedasticity has received much attention, and previous work has focused on either between-gene or within-gene heteroscedasticity. However, in a single experiment, heteroscedasticity may exist both within and between genes. Here we develop flexible shrinkage error estimators considering both between-gene and within-gene heteroscedasticity and use them to construct <it>F</it>-like test statistics for testing interactions, with cutoff values obtained by permutation. These permutation tests are complicated, and several permutation tests are investigated here.</p> <p>Results</p> <p>Our proposed test statistics are compared with other existing shrinkage-type test statistics through extensive simulation studies and a real data example. The results show that the choice of permutation procedures has dramatically more influence on detection power than the choice of <it>F </it>or <it>F</it>-like test statistics. When both types of gene heteroscedasticity exist, our proposed test statistics can control preselected type-I errors and are more powerful. Raw data permutation is not valid in this setting. Whether unrestricted or restricted residual permutation should be used depends on the specific type of test statistic.</p> <p>Conclusions</p> <p>The <it>F</it>-like test statistic that uses the proposed flexible shrinkage error estimator considering both types of gene heteroscedasticity and unrestricted residual permutation can provide a statistically valid and powerful test. Therefore, we recommended that it should always applied in the analysis of real gene expression data analysis to test an interaction term.</p

Potential Associations between Severity of Infection and the Presence of Virulence-Associated Genes in Clinical Strains of Staphylococcus aureus

BACKGROUND: The clinical spectrum of Staphylococcus aureus infection ranges from asymptomatic nasal carriage to osteomyelitis, infective endocarditis (IE) and death. In this study, we evaluate potential association between the presence of specific genes in a collection of prospectively characterized S. aureus clinical isolates and clinical outcome. METHODOLOGY/PRINCIPAL FINDINGS: Two hundred thirty-nine S. aureus isolates (121 methicillin-resistant S. aureus [MRSA] and 118 methicillin-susceptible S. aureus [MSSA]) were screened by array comparative genomic hybridization (aCGH) to identify genes implicated in complicated infections. After adjustment for multiple tests, 226 genes were significantly associated with severity of infection. Of these 226 genes, 185 were not in the SCCmec element. Within the 185 non-SCCmec genes, 171 were less common and 14 more common in the complicated infection group. Among the 41 genes in the SCCmec element, 37 were more common and 4 were less common in the complicated group. A total of 51 of the 2014 sequences evaluated, 14 non-SCCmec and 37 SCCmec, were identified as genes of interest. CONCLUSIONS/SIGNIFICANCE: Of the 171 genes less common in complicated infections, 152 are of unknown function and may contribute to attenuation of virulence. The 14 non-SCCmec genes more common in complicated infections include bacteriophage-encoded genes such as regulatory factors and autolysins with potential roles in tissue adhesion or biofilm formation

Haplotype association analyses in resources of mixed structure using Monte Carlo testing

<p>Abstract</p> <p>Background</p> <p>Genomewide association studies have resulted in a great many genomic regions that are likely to harbor disease genes. Thorough interrogation of these specific regions is the logical next step, including regional haplotype studies to identify risk haplotypes upon which the underlying critical variants lie. Pedigrees ascertained for disease can be powerful for genetic analysis due to the cases being enriched for genetic disease. Here we present a Monte Carlo based method to perform haplotype association analysis. Our method, hapMC, allows for the analysis of full-length and sub-haplotypes, including imputation of missing data, in resources of nuclear families, general pedigrees, case-control data or mixtures thereof. Both traditional association statistics and transmission/disequilibrium statistics can be performed. The method includes a phasing algorithm that can be used in large pedigrees and optional use of pseudocontrols.</p> <p>Results</p> <p>Our new phasing algorithm substantially outperformed the standard expectation-maximization algorithm that is ignorant of pedigree structure, and hence is preferable for resources that include pedigree structure. Through simulation we show that our Monte Carlo procedure maintains the correct type 1 error rates for all resource types. Power comparisons suggest that transmission-disequilibrium statistics are superior for performing association in resources of only nuclear families. For mixed structure resources, however, the newly implemented pseudocontrol approach appears to be the best choice. Results also indicated the value of large high-risk pedigrees for association analysis, which, in the simulations considered, were comparable in power to case-control resources of the same sample size.</p> <p>Conclusions</p> <p>We propose hapMC as a valuable new tool to perform haplotype association analyses, particularly for resources of mixed structure. The availability of meta-association and haplotype-mining modules in our suite of Monte Carlo haplotype procedures adds further value to the approach.</p

Testing Simulation Theory with Cross-Modal Multivariate Classification of fMRI Data

The discovery of mirror neurons has suggested a potential neural basis for simulation and common coding theories of action perception, theories which propose that we understand other people's actions because perceiving their actions activates some of our neurons in much the same way as when we perform the actions. We propose testing this model directly in humans with functional magnetic resonance imaging (fMRI) by means of cross-modal classification. Cross-modal classification evaluates whether a classifier that has learned to separate stimuli in the sensory domain can also separate the stimuli in the motor domain. Successful classification provides support for simulation theories because it means that the fMRI signal, and presumably brain activity, is similar when perceiving and performing actions. In this paper we demonstrate the feasibility of the technique by showing that classifiers which have learned to discriminate whether a participant heard a hand or a mouth action, based on the activity patterns in the premotor cortex, can also determine, without additional training, whether the participant executed a hand or mouth action. This provides direct evidence that, while perceiving others' actions, (1) the pattern of activity in premotor voxels with sensory properties is a significant source of information regarding the nature of these actions, and (2) that this information shares a common code with motor execution

Distinct colonization patterns and cDNA-AFLP transcriptome profiles in compatible and incompatible interactions between melon and different races of Fusarium oxysporum f. sp. melonis

Background: Fusarium oxysporum f. sp. melonis Snyd. & Hans. (FOM) causes Fusarium wilt, the most important infectious disease of melon (Cucumis melo L.). The four known races of this pathogen can be distinguished only by infection on appropriate cultivars. No molecular tools are available that can discriminate among the races, and the molecular basis of compatibility and disease progression are poorly understood. Resistance to races 1 and 2 is controlled by a single dominant gene, whereas only partial polygenic resistance to race 1,2 has been described. We carried out a large-scale cDNA-AFLP analysis to identify host genes potentially related to resistance and susceptibility as well as fungal genes associated with the infection process. At the same time, a systematic reisolation procedure on infected stems allowed us to monitor fungal colonization in compatible and incompatible host-pathogen combinations. Results: Melon plants (cv. Charentais Fom-2), which are susceptible to race 1,2 and resistant to race 1, were artificially infected with a race 1 strain of FOM or one of two race 1,2 w strains. Host colonization of stems was assessed at 1, 2, 4, 8, 14, 16, 18 and 21 days post inoculation (dpi), and the fungus was reisolated from infected plants. Markedly different colonization patterns were observed in compatible and incompatible host-pathogen combinations. Five time points from the symptomless early stage (2 dpi) to obvious wilting symptoms (21 dpi) were considered for cDNA-AFLP analysis. After successful sequencing of 627 transcript-derived fragments (TDFs) differentially expressed in infected plants, homology searching retrieved 305 melon transcripts, 195 FOM transcripts expressed in planta and 127 orphan TDFs. RNA samples from FOM colonies of the three strains grown in vitro were also included in the analysis to facilitate the detection of in planta-specific transcripts and to identify TDFs differentially expressed among races/strains. Conclusion: Our data suggest that resistance against FOM in melon involves only limited transcriptional changes, and that wilting symptoms could derive, at least partially, from an active plant response. We discuss the pathogen-derived transcripts expressed in planta during the infection process and potentially related to virulence functions, as well as transcripts that are differentially expressed between the two FOM races grown in vitro. These transcripts provide candidate sequences that can be further tested for their ability to distinguish between races. Sequence data from this article have been deposited in GenBank, Accession Numbers: HO867279-HO867981