The use of telomerase activity for the detection of prostatic cancer cells after prostatic massage.

PURPOSE: Prostate cancer is the most commonly diagnosed cancer in the United States. The diagnosis or followup of prostate cancer in men older than 50 years is based on digital rectal examination, measurement of the free-to-total prostatic specific antigen ratio and transrectal ultrasound assisted needle biopsy of the prostate. We developed and evaluated a noninvasive method for diagnosing prostate cancer based on the measurement of telomerase activity after prostatic massage in fresh voided urine or after urethral washing. MATERIALS AND METHODS: We obtained 36 specimens of cells after prostatic massage in the fresh voided urine of 16 patients who subsequently underwent radical prostatectomy and after urethral washing in 20 who underwent prostate needle biopsies. Ethylenediaminetetraacetic acid was immediately added to the collected urine or washing to a final concentration of 20 mM. After protein extraction by CHAPS buffer each specimen was tested for telomerase activity in a 2-step modified telomeric repeat amplification protocol assay. The 2 prostate cancer cell lines PC-3 and LNCaP with high telomerase activity were used as a positive control. RESULTS: Telomerase activity was detected in 14 of 24 samples with known prostate cancer (sensitivity 58%). In contrast, no telomerase activity was found in the 12 cases without histological evidence of prostate tumor (specificity 100%). Eight of 9 poorly differentiated cancers expressed telomerase activity (89%), while only 6 of 15 well and moderately differentiated cancers showed telomerase activity (40%). CONCLUSIONS: Our data illustrate that telomerase activity may be detected in voided urine or washing after prostatic massage in patients with prostate cancer. Sensitivity was higher for poorly differentiated tumors. This approach is not currently available for detecting prostate cancer in clinical practice. However, these results are promising and further studies are ongoing.

L'immunoscintigraphie par les anticorps monoclonaux radiomarqués. Evolution d'une méthode de diagnostic du cancer et espoir d'une nouvelle forme de thérapie [Immunoscintigraphy using radio-labeled monoclonal antibodies. Development of a method of cancer diagnosis and hopes for a new form of therapy].

Personal results are presented to illustrate the development of immunoscintigraphy for the detection of cancer over the last 12 years, from the early experimental results in nude mice grafted with human colon carcinoma to the most modern form of immunoscintigraphy applied to patients, using I123 labeled Fab fragments from monoclonal anti-CEA antibodies detected by single photon emission computerized tomography (SPECT). The first generation of immunoscintigraphy used I131 labeled, immunoadsorbent purified, polyclonal anti-CEA antibodies and planar scintigraphy, as the detection system. The second generation used I131 labeled monoclonal anti-CEA antibodies and SPECT, while the third generation employed I123 labeled fragments of monoclonal antibodies and SPECT. The improvement in the precision of tumor images with the most recent forms of immunoscintigraphy is obvious. However, we think the usefulness of immunoscintigraphy for routine cancer management has not yet been entirely demonstrated. Further prospective trials are still necessary to determine the precise clinical role of immunoscintigraphy. A case report is presented on a patient with two liver metastases from a sigmoid carcinoma, who received through the hepatic artery a therapeutic dose (100 mCi) of I131 coupled to 40 mg of a mixture of two high affinity anti-CEA monoclonal antibodies. Excellent localisation in the metastases of the I131 labeled antibodies was demonstrated by SPECT and the treatment was well tolerated. The irradiation dose to the tumor, however, was too low at 4300 rads (with 1075 rads to the normal liver and 88 rads to the bone marrow), and no evidence of tumor regression was obtained. Different approaches for increasing the irradiation dose delivered to the tumor by the antibodies are considered.

Discovery of a 29-gene panel in peripheral blood mononuclear cells for the detection of colorectal cancer and adenomas using high throughput real-time PCR.

Colorectal cancer (CRC) is the second leading cause of cancer-related death in developed countries. Early detection of CRC leads to decreased CRC mortality. A blood-based CRC screening test is highly desirable due to limited invasiveness and high acceptance rate among patients compared to currently used fecal occult blood testing and colonoscopy. Here we describe the discovery and validation of a 29-gene panel in peripheral blood mononuclear cells (PBMC) for the detection of CRC and adenomatous polyps (AP). Blood samples were prospectively collected from a multicenter, case-control clinical study. First, we profiled 93 samples with 667 candidate and 3 reference genes by high throughput real-time PCR (OpenArray system). After analysis, 160 genes were retained and tested again on 51 additional samples. Low expressed and unstable genes were discarded resulting in a final dataset of 144 samples profiled with 140 genes. To define which genes, alone or in combinations had the highest potential to discriminate AP and/or CRC from controls, data were analyzed by a combination of univariate and multivariate methods. A list of 29 potentially discriminant genes was compiled and evaluated for its predictive accuracy by penalized logistic regression and bootstrap. This method discriminated AP >1cm and CRC from controls with a sensitivity of 59% and 75%, respectively, with 91% specificity. The behavior of the 29-gene panel was validated with a LightCycler 480 real-time PCR platform, commonly adopted by clinical laboratories. In this work we identified a 29-gene panel expressed in PBMC that can be used for developing a novel minimally-invasive test for accurate detection of AP and CRC using a standard real-time PCR platform.

The development of decision limits for the GH-2000 detection methodology using additional insulin-like growth factor-I and amino-terminal pro-peptide of type III collagen assays.

The GH-2000 and GH-2004 projects have developed a method for detecting GH misuse based on measuring insulin-like growth factor-I (IGF-I) and the amino-terminal pro-peptide of type III collagen (P-III-NP). The objectives were to analyze more samples from elite athletes to improve the reliability of the decision limit estimates, to evaluate whether the existing decision limits needed revision, and to validate further non-radioisotopic assays for these markers. The study included 998 male and 931 female elite athletes. Blood samples were collected according to World Anti-Doping Agency (WADA) guidelines at various sporting events including the 2011 International Association of Athletics Federations (IAAF) World Athletics Championships in Daegu, South Korea. IGF-I was measured by the Immunotech A15729 IGF-I IRMA, the Immunodiagnostic Systems iSYS IGF-I assay and a recently developed mass spectrometry (LC-MS/MS) method. P-III-NP was measured by the Cisbio RIA-gnost P-III-P, Orion UniQ? PIIINP RIA and Siemens ADVIA Centaur P-III-NP assays. The GH-2000 score decision limits were developed using existing statistical techniques. Decision limits were determined using a specificity of 99.99% and an allowance for uncertainty because of the finite sample size. The revised Immunotech IGF-I - Orion P-III-NP assay combination decision limit did not change significantly following the addition of the new samples. The new decision limits are applied to currently available non-radioisotopic assays to measure IGF-I and P-III-NP in elite athletes, which should allow wider flexibility to implement the GH-2000 marker test for GH misuse while providing some resilience against manufacturer withdrawal or change of assays. Copyright © 2015 John Wiley & Sons, Ltd.

Eye-tracking of nodule detection in lung CT volumetric data.

PURPOSE: Signal detection on 3D medical images depends on many factors, such as foveal and peripheral vision, the type of signal, and background complexity, and the speed at which the frames are displayed. In this paper, the authors focus on the speed with which radiologists and naïve observers search through medical images. Prior to the study, the authors asked the radiologists to estimate the speed at which they scrolled through CT sets. They gave a subjective estimate of 5 frames per second (fps). The aim of this paper is to measure and analyze the speed with which humans scroll through image stacks, showing a method to visually display the behavior of observers as the search is made as well as measuring the accuracy of the decisions. This information will be useful in the development of model observers, mathematical algorithms that can be used to evaluate diagnostic imaging systems. METHODS: The authors performed a series of 3D 4-alternative forced-choice lung nodule detection tasks on volumetric stacks of chest CT images iteratively reconstructed in lung algorithm. The strategy used by three radiologists and three naïve observers was assessed using an eye-tracker in order to establish where their gaze was fixed during the experiment and to verify that when a decision was made, a correct answer was not due only to chance. In a first set of experiments, the observers were restricted to read the images at three fixed speeds of image scrolling and were allowed to see each alternative once. In the second set of experiments, the subjects were allowed to scroll through the image stacks at will with no time or gaze limits. In both static-speed and free-scrolling conditions, the four image stacks were displayed simultaneously. All trials were shown at two different image contrasts. RESULTS: The authors were able to determine a histogram of scrolling speeds in frames per second. The scrolling speed of the naïve observers and the radiologists at the moment the signal was detected was measured at 25-30 fps. For the task chosen, the performance of the observers was not affected by the contrast or experience of the observer. However, the naïve observers exhibited a different pattern of scrolling than the radiologists, which included a tendency toward higher number of direction changes and number of slices viewed. CONCLUSIONS: The authors have determined a distribution of speeds for volumetric detection tasks. The speed at detection was higher than that subjectively estimated by the radiologists before the experiment. The speed information that was measured will be useful in the development of 3D model observers, especially anthropomorphic model observers which try to mimic human behavior.

Genome-wide DNA methylation detection by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison.

Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). Objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples, i.e. 65 glioblastoma and 5 non-tumoral tissues. As MethylCap-seq coverages were limited, we focused on the inherent capacity of the methodology to detect methylated loci rather than a quantitative analysis. MethylCap-seq and HM450 data were dichotomized and performances were compared using a gold standard free Bayesian modelling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. In addition, genome-wide characteristics were compared, revealing that HM450 probes identified substantially fewer regions compared to MethylCap-seq. Although results indicated that the latter method can detect more potentially relevant DNA-methylation, this did not translate into the discovery of more differentially methylated loci between tumours and controls compared to HM450. Our results therefore indicate that both methodologies are complementary, with a higher sensitivity for HM450 and a far larger genome-wide coverage for MethylCap-seq, but also that a more comprehensive character does not automatically imply more significant results in biomarker studies.

RNA enrichment method for quantitative transcriptional analysis of pathogens in vivo applied to the fungus Candida albicans.

UNLABELLED: In vivo transcriptional analyses of microbial pathogens are often hampered by low proportions of pathogen biomass in host organs, hindering the coverage of full pathogen transcriptome. We aimed to address the transcriptome profiles of Candida albicans, the most prevalent fungal pathogen in systemically infected immunocompromised patients, during systemic infection in different hosts. We developed a strategy for high-resolution quantitative analysis of the C. albicans transcriptome directly from early and late stages of systemic infection in two different host models, mouse and the insect Galleria mellonella. Our results show that transcriptome sequencing (RNA-seq) libraries were enriched for fungal transcripts up to 1,600-fold using biotinylated bait probes to capture C. albicans sequences. This enrichment biased the read counts of only ~3% of the genes, which can be identified and removed based on a priori criteria. This allowed an unprecedented resolution of C. albicans transcriptome in vivo, with detection of over 86% of its genes. The transcriptional response of the fungus was surprisingly similar during infection of the two hosts and at the two time points, although some host- and time point-specific genes could be identified. Genes that were highly induced during infection were involved, for instance, in stress response, adhesion, iron acquisition, and biofilm formation. Of the in vivo-regulated genes, 10% are still of unknown function, and their future study will be of great interest. The fungal RNA enrichment procedure used here will help a better characterization of the C. albicans response in infected hosts and may be applied to other microbial pathogens. IMPORTANCE: Understanding the mechanisms utilized by pathogens to infect and cause disease in their hosts is crucial for rational drug development. Transcriptomic studies may help investigations of these mechanisms by determining which genes are expressed specifically during infection. This task has been difficult so far, since the proportion of microbial biomass in infected tissues is often extremely low, thus limiting the depth of sequencing and comprehensive transcriptome analysis. Here, we adapted a technology to capture and enrich C. albicans RNA, which was next used for deep RNA sequencing directly from infected tissues from two different host organisms. The high-resolution transcriptome revealed a large number of genes that were so far unknown to participate in infection, which will likely constitute a focus of study in the future. More importantly, this method may be adapted to perform transcript profiling of any other microbes during host infection or colonization.

Rockfall detection from LIDAR point clouds: A clustering approach using R

The analysis of rockfall characteristics and spatial distribution is fundamental to understand and model the main factors that predispose to failure. In our study we analysed LiDAR point clouds aiming to: (1) detect and characterise single rockfalls; (2) investigate their spatial distribution. To this end, different cluster algorithms were applied: 1a) Nearest Neighbour Clutter Removal (NNCR) in combination with the Expectation?Maximization (EM) in order to separate feature points from clutter; 1b) a density based algorithm (DBSCAN) was applied to isolate the single clusters (i.e. the rockfall events); 2) finally we computed the Ripley's K-function to investigate the global spatial pattern of the extracted rockfalls. The method allowed proper identification and characterization of more than 600 rockfalls occurred on a cliff located in Puigcercos (Catalonia, Spain) during a time span of six months. The spatial distribution of these events proved that rockfall were clustered distributed at a welldefined distance-range. Computations were carried out using R free software for statistical computing and graphics. The understanding of the spatial distribution of precursory rockfalls may shed light on the forecasting of future failures.

Evaluation of a new serological test for the detection of anti-Coxiella and anti-Rickettsia antibodies.

Coxiella burnetii and members of the genus Rickettsia are obligate intracellular bacteria. Since cultivation of these organisms requires dedicated techniques, their diagnosis usually relies on serological or molecular biology methods. Immunofluorescence is considered the gold standard to detect antibody-reactivity towards these organisms. Here, we assessed the performance of a new automated epifluorescence immunoassay (InoDiag) to detect IgM and IgG against C. burnetii, Rickettsia typhi and Rickettsia conorii. Samples were tested with the InoDiag assay. A total of 213 sera were tested, of which 63 samples from Q fever, 20 from spotted fever rickettsiosis, 6 from murine typhus and 124 controls. InoDiag results were compared to micro-immunofluorescence. For acute Q fever, the sensitivity of phase 2 IgG was only of 30% with a cutoff of 1 arbitrary unit (AU). In patients with acute Q fever with positive IF IgM, sensitivity reached 83% with the same cutoff. Sensitivity for chronic Q fever was 100% whereas sensitivity for past Q fever was 65%. Sensitivity for spotted Mediterranean fever and murine typhus were 91% and 100%, respectively. Both assays exhibited a good specificity in control groups, ranging from 79% in sera from patients with unrelated diseases or EBV positivity to 100% in sera from healthy patients. In conclusion, the InoDiag assay exhibits an excellent performance for the diagnosis of chronic Q fever but a very low IgG sensitivity for acute Q fever likely due to low reactivity of phase 2 antigens present on the glass slide. This defect is partially compensated by the detection of IgM. Because it exhibits a good negative predictive value, the InoDiag assay is valuable to rule out a chronic Q fever. For the diagnosis of rickettsial diseases, the sensitivity of the InoDiag method is similar to conventional immunofluorescence.

Adaptation of a Gaussia princeps Luciferase reporter system in Candida albicans for in vivo detection in the Galleria mellonella infection model.

For the past 10 years, mini-host models and in particular the greater wax moth Galleria mellonella have tended to become a surrogate for murine models of fungal infection mainly due to cost, ethical constraints and ease of use. Thus, methods to better assess the fungal pathogenesis in G. mellonella need to be developed. In this study, we implemented the detection of Candida albicans cells expressing the Gaussia princeps luciferase in its cell wall in infected larvae of G. mellonella. We demonstrated that detection and quantification of luminescence in the pulp of infected larvae is a reliable method to perform drug efficacy and C. albicans virulence assays as compared to fungal burden assay. Since the linearity of the bioluminescent signal, as compared to the CFU counts, has a correlation of R(2) = 0.62 and that this method is twice faster and less labor intensive than classical fungal burden assays, it could be applied to large scale studies. We next visualized and followed C. albicans infection in living G. mellonella larvae using a non-toxic and water-soluble coelenterazine formulation and a CCD camera that is commonly used for chemoluminescence signal detection. This work allowed us to follow for the first time C. albicans course of infection in G. mellonella during 4 days.

Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography.

X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

Fast and sensitive supercritical fluid chromatography - tandem mass spectrometry multi-class screening method for the determination of doping agents in urine.

This study shows the possibility offered by modern ultra-high performance supercritical fluid chromatography combined with tandem mass spectrometry in doping control analysis. A high throughput screening method was developed for 100 substances belonging to the challenging classes of anabolic agents, hormones and metabolic modulators, synthetic cannabinoids and glucocorticoids, which should be detected at low concentrations in urine. To selectively extract these doping agents from urine, a supported liquid extraction procedure was implemented in a 48-well plate format. At the tested concentration levels ranging from 0.5 to 5 ng/mL, the recoveries were better than 70% for 48-68% of the compounds and higher than 50% for 83-87% of the tested substances. Due to the numerous interferences related to isomers of steroids and ions produced by the loss of water in the electrospray source, the choice of SFC separation conditions was very challenging. After careful optimization, a Diol stationary phase was employed. The total analysis time for the screening assay was only 8 min, and interferences as well as susceptibility to matrix effect (ME) were minimized. With the developed method, about 70% of the compounds had relative ME within the range ±20%, at a concentration of 1 and 5 ng/mL. Finally, limits of detection achieved with the above-described strategy including 5-fold preconcentration were below 0.1 ng/mL for the majority of the tested compounds. Therefore, LODs were systematically better than the minimum required performance levels established by the World anti-doping agency, except for very few metabolites.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.