Comparison of PCR, nested PCR, and random amplified polymorphic DNA PCR for detection and typing of Ureaplasma urealyticum in specimens from pregnant women

A PCR assay, using three primer pairs, was developed for the detection of Ureaplasma urealyticum, parvo biovar, mba types 1, 3, and 6, in cultured clinical specimens. The primer pairs were designed by using the polymorphic base positions within a 310- to 311-bp fragment of the 5* end and upstream control region of the mba gene. The specificity of the assay was confirmed with reference serovars 1, 3, 6, and 14 and by the amplified-fragment sizes (81 bp for mba 1, 262 bp for mba 3, and 193 bp for mba 6). A more sensitive nested PCR was also developed. This involved a first-step PCR, using the primers UMS-125 and UMA226, followed by the nested mba-type PCR described above. This nested PCR enabled the detection and typing of small numbers of U. urealyticum cells, including mixtures, directly in original clinical specimens. By using random amplified polymorphic DNA (RAPD) PCR with seven arbitrary primers, we were also able to differentiate the two biovars of U. urealyticum and to identify 13 RAPD-PCR subtypes. By applying these subtyping techniques to clinical samples collected from pregnant women, we established that (i) U. urealyticum is often a persistent colonizer of the lower genital tract from early midtrimester until the third trimester of pregnancy, (ii) mba type 6 was isolated significantly more often (P 5 0.048) from women who delivered preterm than from women who delivered at term, (iii) no particular ureaplasma subtype(s) was associated with placental infections and/or adverse pregnancy outcomes, and (iv) the ureaplasma subtypes most frequently isolated from women were the same subtypes most often isolated from infected placentas.

Damage detection in slab-on-girder bridges using vibration characteristics

This paper develops and applies a multi-criteria procedure, incorporating changes in natural frequencies, modal flexibility and the modal strain energy, for damage detection in slab-on-girder bridges. The proposed procedure is first validated through experimental testing of a model bridge. Numerically simulated modal data obtained through finite element analyses are then used to evaluate the vibration parameters before and after damage and used as the indices for assessment of the state of structural health. The procedure is illustrated by its application to full scale slab-on-girder bridges under different damage scenarios involving single and multiple damages on the deck and girders.

Cytokine synthesis by intestinal intraepithelial lymphocytes. Both gamma/delta T cell receptor-positive and alpha/beta T cell receptor-positive T cells in the G1 phase of cell cycle produce IFN-gamma and IL-5

Murine intestinal intraepithelial lymphocytes (IEL) have been shown to contain subsets of alpha/beta TCR+ and gamma/delta TCR+ T cells that spontaneously produce cytokines such as IFN-gamma and IL-5. We have now determined the nature and cell cycle stage of these cytokine-producing T lymphocytes in EIL by using IFN-gamma- and IL-5-specific ELISPOT assay, cytokine-specific mRNA-cDNA dot-blot hybridization and polymerase chain reaction, and flow cytometry (FACS) for DNA analysis. When CD3+ T cells from IEL of normal C3H/HeN mice were separated into low and high density fractions by discontinuous Percoll gradients, IFN-gamma and IL-5 spot-forming cells were only found in the former population. Analysis of mRNA for these cytokines by both IFN-gamma- and IL-5-specific dot-blot hybridization and polymerase chain reaction revealed that higher levels of message for IFN-gamma and IL-5 were also seen in the low density fraction. However, cell cycle analysis of these two fractions by FACS using propidium iodide showed a similar pattern of cell cycle stages in both low and high density populations (G0 + G1 approximately 96 to 98% and S/G2 + M approximately 2 to 4%). Finally, mRNA from gamma/delta TCR+ and alpha/beta TCR+ T cells in both low and high density fractions of IEL were analyzed for IFN-gamma and IL-5 message by polymerase chain reaction. After 35 cycles of amplification, both gamma/delta TCR+ and alpha/beta TCR+ T cells in the low density fraction expressed higher levels of message for these two cytokines when compared with the high density population. These results have now shown that both gamma/delta and alpha/beta TCR+ IEL can be separated into low and high density subsets and both fractions possess a similar stage of cell cycle. However, only the low density cells (in G1 phase) of both gamma/delta and alpha/beta TCR types possess increased cytokine-specific mRNA and produce the cytokines IFN-gamma and IL-5. Our results suggest that alpha/beta TCR+ and gamma/delta TCR+ IEL can produce cytokines without cell proliferation.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Comparison of antigen detection and quantitative PCR in the detection of chlamydial infection in koalas (Phascolarctos cinereus)

The gold standard method for detecting chlamydial infection in domestic and wild animals is PCR, but the technique is not suited to testing animals in the field when a rapid diagnosis is frequently required. The objective of this study was to compare the results of a commercially available enzyme immunoassay test for Chlamydia against a quantitative Chlamydia pecorum-specific PCR performed on swabs collected from the conjunctival sac, nasal cavity and urogenital sinuses of naturally infected koalas (Phascolarctos cinereus). The level of agreement for positive results between the two assays was low (43.2%). The immunoassay detection cut-off was determined as approximately 400 C. pecorum copies, indicating that the test was sufficiently sensitive to be used for the rapid diagnosis of active chlamydial infections.

FOXC2 expression links epithelial-mesenchymal transition and stem cell properties in breast cancer

Resistance to chemotherapy and metastases are the major causes of breast cancer-related mortality. Moreover, cancer stem cells (CSC) play critical roles in cancer progression and treatment resistance. Previously, it was found that CSC-like cells can be generated by aberrant activation of epithelial–mesenchymal transition (EMT), thereby making anti-EMT strategies a novel therapeutic option for treatment of aggressive breast cancers. Here, we report that the transcription factor FOXC2 induced in response to multiple EMT signaling pathways as well as elevated in stem cell-enriched factions is a critical determinant of mesenchymal and stem cell properties, in cells induced to undergo EMT- and CSC-enriched breast cancer cell lines. More specifically, attenuation of FOXC2 expression using lentiviral short hairpin RNA led to inhibition of the mesenchymal phenotype and associated invasive and stem cell properties, which included reduced mammosphere-forming ability and tumor initiation. Whereas, overexpression of FOXC2 was sufficient to induce CSC properties and spontaneous metastasis in transformed human mammary epithelial cells. Furthermore, a FOXC2-induced gene expression signature was enriched in the claudin-low/basal B breast tumor subtype that contains EMT and CSC features. Having identified PDGFR-β to be regulated by FOXC2, we show that the U.S. Food and Drug Administration-approved PDGFR inhibitor, sunitinib, targets FOXC2-expressing tumor cells leading to reduced CSC and metastatic properties. Thus, FOXC2 or its associated gene expression program may provide an effective target for anti-EMT-based therapies for the treatment of claudin-low/basal B breast tumors or other EMT-/CSC-enriched tumors.

Organotypic culture of normal, dysplastic and squamous cell carcinoma-derived oral cell lines reveals loss of spatial regulation of CD44 and p75(NTR) in malignancy

Oral squamous cell carcinomas (OSCC) often arise from dysplastic lesions. The role of cancer stem cells in tumour initiation is widely accepted, yet the potential existence of pre-cancerous stem cells in dysplastic tissue has received little attention. Cell lines from oral diseases ranging in severity from dysplasia to malignancy provide opportunity to investigate the involvement of stem cells in malignant progression from dysplasia. Stem cells are functionally defined by their ability to generate hierarchical tissue structures in consortium with spatial regulation. Organotypic cultures readily display tissue hierarchy in vitro; hence, in this study, we compared hierarchical expression of stem cell-associated markers in dermis-based organotypic cultures of oral epithelial cells from normal tissue (OKF6-TERT2), mild dysplasia (DOK), severe dysplasia (POE-9n) and OSCC (PE/CA P J15). Expression of CD44, p75NTR, CD24 and ALDH was studied in monolayers by flow cytometry and in organotypic cultures by immunohistochemistry. Spatial regulation of CD44 and p75NTR was evident for organotypic cultures of normal (OKF6-TERT2) and dysplasia (DOK and POE-9n) but was lacking for OSCC (PE/CA PJ15)-derived cells. Spatial regulation of CD24 was not evident. All monolayer cultures exhibited CD44, p75NTR, CD24 antigens and ALDH activity (ALDEFLUOR® assay), with a trend towards loss of population heterogeneity that mirrored disease severity. In monolayer, increased FOXA1 and decreased FOXA2 expression correlated with disease severity, but OCT3/4, Sox2 and NANOG did not. We conclude that dermis-based organotypic cultures give opportunity to investigate the mechanisms that underlie loss of spatial regulation of stem cell markers seen with OSCC-derived cells.

Markers of cutaneous human papillomavirus infection in individuals with tumor-free skin, actinic keratoses, and squamous cell carcinoma

Separately, actinic keratosis (AK) and cutaneous squamous cell carcinoma (SCC) have been associated with cutaneous human papillomavirus (HPV) infections. To further explore the association between HPV infection and SCC development, we determined markers of cutaneous HPV infection within a single population in persons with precursor lesions (AK), cancerous lesions (SCC), and without. Serum and plucked eyebrow hairs were collected from 57 tumor-free controls, 126 AK, and 64 SCC cases. Presence of HPV L1 and E6 seroreactivity and viral DNA were determined for HPV types 5, 8, 15, 16, 20, 24, and 38. Significant positive associations with increasing severity of the lesions (controls, AK, and SCC, respectively) were observed for overall HPV L1 seropositivity (13%, 26%, and 37%) and for HPV8 (4%, 17%, and 30%). In parallel, the proportion of L1 seropositive individuals against multiple HPV types increased from 14% to 39% and 45%. The overall E6 seroreactivity, however, tended to decline with AK and SCC, especially for HPV8 (21%, 11%, and 2%). HPV DNA positivity was most prevalent in the AK cases (54%) compared with the SCC cases (44%) and the tumor-free controls (40%). Among all participants, there was a positive trend between overall HPV DNA positivity and L1 seropositivity, but not E6 seropositivity. Taken together, our data suggest that cutaneous HPV infections accompanied by detectable HPV DNA in eyebrow hairs and HPV L1 seropositivity, but not E6 seropositivity, are associated with an increased risk of AK and SCC.

Re: Human papillomavirus infection and incidence of squamous cell and basal cell carcinomas of the skin

Human papillomaviruses (HPVs) cause cervical cancer and some other types of epithelial cancers. HPV types from the phylogenic beta genus (beta-PVs), formerly known as epidermodysplasia verruciformis–associated HPV types, are frequently detected in nonmelanoma skin cancers, especially in squamous cell carcinomas (SCCs). An etiologic relationship with beta-PV infection is suspected...

Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

Monitoring smartphones for anomaly detection

In this paper we demonstrate how to monitor a smartphone running Symbian operating system and Windows Mobile in order to extract features for anomaly detection. These features are sent to a remote server because running a complex intrusion detection system on this kind of mobile device still is not feasible due to capability and hardware limitations. We give examples on how to compute relevant features and introduce the top ten applications used by mobile phone users based on a study in 2005. The usage of these applications is recorded by a monitoring client and visualized. Additionally, monitoring results of public and self-written malwares are shown. For improving monitoring client performance, Principal Component Analysis was applied which lead to a decrease of about 80 of the amount of monitored features.

Improved foreground detection via block-based classifier cascade with probabilistic decision integration

Background subtraction is a fundamental low-level processing task in numerous computer vision applications. The vast majority of algorithms process images on a pixel-by-pixel basis, where an independent decision is made for each pixel. A general limitation of such processing is that rich contextual information is not taken into account. We propose a block-based method capable of dealing with noise, illumination variations, and dynamic backgrounds, while still obtaining smooth contours of foreground objects. Specifically, image sequences are analyzed on an overlapping block-by-block basis. A low-dimensional texture descriptor obtained from each block is passed through an adaptive classifier cascade, where each stage handles a distinct problem. A probabilistic foreground mask generation approach then exploits block overlaps to integrate interim block-level decisions into final pixel-level foreground segmentation. Unlike many pixel-based methods, ad-hoc postprocessing of foreground masks is not required. Experiments on the difficult Wallflower and I2R datasets show that the proposed approach obtains on average better results (both qualitatively and quantitatively) than several prominent methods. We furthermore propose the use of tracking performance as an unbiased approach for assessing the practical usefulness of foreground segmentation methods, and show that the proposed approach leads to considerable improvements in tracking accuracy on the CAVIAR dataset.

Quantifying the roles of cell motility and cell proliferation in a circular barrier assay

Moving fronts of cells are essential features of embryonic development, wound repair and cancer metastasis. This paper describes a set of experiments to investigate the roles of random motility and proliferation in driving the spread of an initially confined cell population. The experiments include an analysis of cell spreading when proliferation was inhibited. Our data have been analysed using two mathematical models: a lattice-based discrete model and a related continuum partial differential equation model. We obtain independent estimates of the random motility parameter, D, and the intrinsic proliferation rate, λ, and we confirm that these estimates lead to accurate modelling predictions of the position of the leading edge of the moving front as well as the evolution of the cell density profiles. Previous work suggests that systems with a high λ/D ratio will be characterized by steep fronts, whereas systems with a low λ/D ratio will lead to shallow diffuse fronts and this is confirmed in the present study. Our results provide evidence that continuum models, based on the Fisher–Kolmogorov equation, are a reliable platform upon which we can interpret and predict such experimental observations.

Modeling and detection of complex attacks

A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required. This paper presents a formal methodology for modeling and detection of complex attacks in three phases: (1) we extend basic attack tree (AT) approach to capture temporal dependencies between components and expiration of an attack, (2) using enhanced AT we build a tree automaton which accepts a sequence of actions from input message streams from various sources if there is a traversal of an AT from leaves to root, and (3) we show how to construct an enhanced parallel automaton that has each tree automaton as a subroutine. We use simulation to test our methods, and provide a case study of representing attacks in WLANs.