Automated DNA extraction using the QIAsymphony platform: Estimation of DNA recovery from simulated forensic stains

The aim of this study was to evaluate the forensic protocol recently developed by Qiagen for the QIAsymphony automated DNA extraction platform. Samples containing low amounts of DNA were specifically considered, since they represent the majority of samples processed in our laboratory. The analysis of simulated blood and saliva traces showed that the highest DNA yields were obtained with the maximal elution volume available for the forensic protocol, that is 200 ml. Resulting DNA extracts were too diluted for successful DNA profiling and required a concentration. This additional step is time consuming and potentially increases inversion and contamination risks. The 200 ml DNA extracts were concentrated to 25 ml, and the DNA recovery estimated with real-time PCR as well as with the percentage of SGM Plus alleles detected. Results using our manual protocol, based on the QIAamp DNA mini kit, and the automated protocol were comparable. Further tests will be conducted to determine more precisely DNA recovery, contamination risk and PCR inhibitors removal, once a definitive procedure, allowing the concentration of DNA extracts from low yield samples, will be available for the QIAsymphony.

Transjugular liver biopsy: prospective evaluation of the angle formed between the hepatic veins and the vena cava main axis and modification of a semi-automated biopsy device in cases of an unfavorable angle.

In cases of transjugular liver biopsies, the venous angle formed between the chosen hepatic vein and the vena cava main axis in a frontal plane can be large, leading to technical difficulties. In a prospective study including 139 consecutive patients who underwent transjugular liver biopsy using the Quick-Core biopsy set, the mean venous angle was equal to 49.6 degrees. For 21.1% of the patients, two attempts at hepatic venous catheterization failed because the venous angle was too large, with a mean of 69.7 degrees. In all of these patients, manual reshaping of the distal curvature of the stiffening metallic cannula, by forming a new mean angle equal to 48 degrees , allowed successful completion of the procedure in less than 10 min.

Molecular investigation of lymph nodes in patients with colon cancer: a new road to better staging

Objective: Small nodal tumor infiltrates are identified by applying multilevel sectioning and immunohistochemistry (IHC) in addition to H&E (hematoxylin and eosin) stains of resected lymph nodes. However, the use of multilevel sectioning and IHC is very time-consuming and costly. The current standard analysis of lymph nodes in colon cancer patients is based on one slide per lymph node stained by H&E. A new molecular diagnostic system called ''One tep Nucleic Acid Amplification'' (OSNA) was designed for a more accurate detection of lymph node metastases. The objective of the present investigation was to compare the performance ofOSNAto current standard histology (H&E). We hypothesize that OSNA provides a better staging than the routine use of one slide H&E per lymph node.Methods: From 22 colon cancer patients 307 frozen lymph nodes were used to compare OSNA with H&E. The lymph nodes were cut into halves. One half of the lymph node was analyzed by OSNA. The semi-automated OSNA uses amplification of reverse-transcribed cytokeratin19 (CK19) mRNA directly from the homogenate. The remaining tissue was dedicated to histology, with 5 levels of H&E and IHC staining (CK19).Results: On routine evaluation of oneH&Eslide 7 patients were nodal positive (macro-metastases). All these patients were recognized by OSNA analysis as being positive (sensitivity 100%). Two of the remaining 15 patients had lymph node micro-metastases and 9 isolated tumor cells. For the patients with micrometastases both H&E and OSNA were positive in 1 of the 2 patients. For patients with isolated tumor cells, H&E was positive in 1/9 cases whereas OSNA was positive in 3/9 patients (IHC as a reference). There was only one case to be described as IHC negative/OSNA positive. On the basis of single lymph nodes the sensitivity of OSNA and the 5 levels of H&E and IHC was 94・5%.Conclusion: OSNA is a novel molecular tool for the detection of lymph node metastases in colon cancer patients which provides better staging compared to the current standard evaluation of one slide H&E stain. Since the use of OSNA allows the analysis of the whole lymph node, sampling bias and undetected tumor deposits due to uninvestigated material will be overcome. OSNA improves staging in colon cancer patients and may replace the current standard of H&E staining in the future.

Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.

An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.

Dynamic social representations of the 2009 H1N1 pandemic: Shifting patterns of sense-making and blame

We investigate dynamics of public perceptions of the 2009 H1N1 influenza pandemic to understand changing patterns of sense-making and blame regarding the outbreak of emerging infectious diseases. We draw on social representation theory combined with a dramaturgical perspective to identify changes in how various collectives are depicted over the course of the pandemic, according to three roles: heroes, villains and victims. Quantitative results based on content analysis of three cross-sectional waves of interviews show a shift from mentions of distant collectives (e.g., far-flung countries) at Wave 1 to local collectives (e.g., risk groups) as the pandemic became of more immediate concern (Wave 2) and declined (Wave 3). Semi-automated content analysis of media coverage shows similar results. Thematic analyses of the discourse associated with collectives revealed that many were consistently perceived as heroes, villains and victims.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

Robust volume-targeted balanced steady-state free-precession coronary magnetic resonance angiography in a breathhold at 3.0 Tesla: a reproducibility study.

BACKGROUND: Transient balanced steady-state free-precession (bSSFP) has shown substantial promise for noninvasive assessment of coronary arteries but its utilization at 3.0 T and above has been hampered by susceptibility to field inhomogeneities that degrade image quality. The purpose of this work was to refine, implement, and test a robust, practical single-breathhold bSSFP coronary MRA sequence at 3.0 T and to test the reproducibility of the technique. METHODS: A 3D, volume-targeted, high-resolution bSSFP sequence was implemented. Localized image-based shimming was performed to minimize inhomogeneities of both the static magnetic field and the radio frequency excitation field. Fifteen healthy volunteers and three patients with coronary artery disease underwent examination with the bSSFP sequence (scan time = 20.5 ± 2.0 seconds), and acquisitions were repeated in nine subjects. The images were quantitatively analyzed using a semi-automated software tool, and the repeatability and reproducibility of measurements were determined using regression analysis and intra-class correlation coefficient (ICC), in a blinded manner. RESULTS: The 3D bSSFP sequence provided uniform, high-quality depiction of coronary arteries (n = 20). The average visible vessel length of 100.5 ± 6.3 mm and sharpness of 55 ± 2% compared favorably with earlier reported navigator-gated bSSFP and gradient echo sequences at 3.0 T. Length measurements demonstrated a highly statistically significant degree of inter-observer (r = 0.994, ICC = 0.993), intra-observer (r = 0.894, ICC = 0.896), and inter-scan concordance (r = 0.980, ICC = 0.974). Furthermore, ICC values demonstrated excellent intra-observer, inter-observer, and inter-scan agreement for vessel diameter measurements (ICC = 0.987, 0.976, and 0.961, respectively), and vessel sharpness values (ICC = 0.989, 0.938, and 0.904, respectively). CONCLUSIONS: The 3D bSSFP acquisition, using a state-of-the-art MR scanner equipped with recently available technologies such as multi-transmit, 32-channel cardiac coil, and localized B0 and B1+ shimming, allows accelerated and reproducible multi-segment assessment of the major coronary arteries at 3.0 T in a single breathhold. This rapid sequence may be especially useful for functional imaging of the coronaries where the acquisition time is limited by the stress duration and in cases where low navigator-gating efficiency prohibits acquisition of a free breathing scan in a reasonable time period.

Reproducibility of 3D free-breathing magnetic resonance coronary vessel wall imaging.

AIMS: Although the coronary artery vessel wall can be imaged non-invasively using magnetic resonance imaging (MRI), the in vivo reproducibility of wall thickness measures has not been previously investigated. Using a refined magnetization preparation scheme, we sought to assess the reproducibility of three-dimensional (3D) free-breathing black-blood coronary MRI in vivo. METHODS AND RESULTS: MRI vessel wall scans parallel to the right coronary artery (RCA) were obtained in 18 healthy individuals (age range 25-43, six women), with no known history of coronary artery disease, using a 3D dual-inversion navigator-gated black-blood spiral imaging sequence. Vessel wall scans were repeated 1 month later in eight subjects. The visible vessel wall segment and the wall thickness were quantitatively assessed using a semi-automatic tool and the intra-observer, inter-observer, and inter-scan reproducibilities were determined. The average imaged length of the RCA vessel wall was 44.5+/-7 mm. The average wall thickness was 1.6+/-0.2 mm. There was a highly significant intra-observer (r=0.97), inter-observer (r=0.94), and inter-scan (r=0.90) correlation for wall thickness (all P<0.001). There was also a significant agreement for intra-observer, inter-observer, and inter-scan measurements on Bland-Altman analysis. The intra-class correlation coefficients for intra-observer (r=0.97), inter-observer (r=0.92), and inter-scan (r=0.86) analyses were also excellent. CONCLUSION: The use of black-blood free-breathing 3D MRI in conjunction with semi-automated analysis software allows for reproducible measurements of right coronary arterial vessel-wall thickness. This technique may be well-suited for non-invasive longitudinal studies of coronary atherosclerosis.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Identification of in vitro HSC fate regulators by differential lipid raft clustering.

Most hematopoietic stem cells (HSC) in the bone marrow reside in a quiescent state and occasionally enter the cell cycle upon cytokine-induced activation. Although the mechanisms regulating HSC quiescence and activation remain poorly defined, recent studies have revealed a role of lipid raft clustering (LRC) in HSC activation. Here, we tested the hypothesis that changes in lipid raft distribution could serve as an indicator of the quiescent and activated state of HSCs in response to putative niche signals. A semi-automated image analysis tool was developed to map the presence or absence of lipid raft clusters in live HSCs cultured for just one hour in serum-free medium supplemented with stem cell factor (SCF). By screening the ability of 19 protein candidates to alter lipid raft dynamics, we identified six factors that induced either a marked decrease (Wnt5a, Wnt3a and Osteopontin) or increase (IL3, IL6 and VEGF) in LRC. Cell cycle kinetics of single HSCs exposed to these factors revealed a correlation of LRC dynamics and proliferation kinetics: factors that decreased LRC slowed down cell cycle kinetics, while factors that increased LRC led to faster and more synchronous cycling. The possibility of identifying, by LRC analysis at very early time points, whether a stem cell is activated and possibly committed upon exposure to a signaling cue of interest could open up new avenues for large-scale screening efforts.

An automated microreactor for semi-continuous biosensor measurements.

Living bacteria or yeast cells are frequently used as bioreporters for the detection of specific chemical analytes or conditions of sample toxicity. In particular, bacteria or yeast equipped with synthetic gene circuitry that allows the production of a reliable non-cognate signal (e.g., fluorescent protein or bioluminescence) in response to a defined target make robust and flexible analytical platforms. We report here how bacterial cells expressing a fluorescence reporter ("bactosensors"), which are mostly used for batch sample analysis, can be deployed for automated semi-continuous target analysis in a single concise biochip. Escherichia coli-based bactosensor cells were continuously grown in a 13 or 50 nanoliter-volume reactor on a two-layered polydimethylsiloxane-on-glass microfluidic chip. Physiologically active cells were directed from the nl-reactor to a dedicated sample exposure area, where they were concentrated and reacted in 40 minutes with the target chemical by localized emission of the fluorescent reporter signal. We demonstrate the functioning of the bactosensor-chip by the automated detection of 50 μgarsenite-As l(-1) in water on consecutive days and after a one-week constant operation. Best induction of the bactosensors of 6-9-fold to 50 μg l(-1) was found at an apparent dilution rate of 0.12 h(-1) in the 50 nl microreactor. The bactosensor chip principle could be widely applicable to construct automated monitoring devices for a variety of targets in different environments.

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis.

Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.