Association of the Epstein-Barr virus latent membrane protein 1 with lipid rafts is mediated through its N-terminal region.

The latent membrane protein 1 (LMP1) encoded by the Epstein-Barr virus acts like a constitutively activated receptor of the tumor necrosis factor receptor (TNFR) family and is enriched in lipid rafts. We showed that LMP1 is targeted to lipid rafts in transfected HEK 293 cells, and that the endogenous TNFR-associated factor 3 binds LMP1 and is recruited to lipid rafts upon LMP1 expression. An LMP1 mutant lacking the C-terminal 55 amino acids (Cdelta55) behaves like the wild-type (WT) LMP1 with respect to membrane localization. In contrast, a mutant with a deletion of the 25 N-terminal residues (Ndelta25) does not concentrate in lipid rafts but still binds TRAF3, demonstrating that cell localization of LMP1 was not crucial for TRAF3 localization. Moreover, Ndelta25 inhibited WT LMP1-mediated induction of the transcription factors NF-kappaB and AP-1. Morphological data indicate that Ndelta25 hampers WT LMP1 plasma membrane localization, thus blocking LMP1 function.

Latent tuberculosis: which test in which situation?

Detection of latent tuberculosis infection (LTBI) is a cost-effective procedure in patients at high risk of developing tuberculosis later and who could benefit from preventive treatment. The commonest situation where screening is indicated is the search for infected contacts of an index case with pulmonary tuberculosis. As a screening procedure the current tendency is to replace the time-honoured tuberculin skin test by one of the new blood tests measuring the release of interferon gamma by sensitised T lymphocytes after stimulation by specific peptides from M. tuberculosis. The main advantage of the new tests is the absence of interference with BCG and non-tuberculous mycobacteria, which confers high specificity on the test. This allows a more selective choice of persons for whom preventive treatment is indicated. Some controversial issues remain, such as sensitivity in children and immunocompromised subjects, the predictive value of the blood test and interpretation of possible changes in test results over time. The technical aspects required for performance of the tests must be considered.

Preliminary epidemiological study of latent tuberculosis in Mexican agricultural workers in the Niagara region, Canada

It is well documented that the majority of Tuberculosis (TB) cases diagnosed in Canada are related to foreign-bom persons from TB high-burden countries. The Canadian seasonal agricultural workers program (SAWP) operating with Mexico allows migrant workers to enter the country with a temporary work permit for up to 8 months. Preiimnigration screening of these workers by both clinical examination and chest X-ray (CXR) reduces the risk of introducing cases of active pulmonary TB to Canada, but screening for latent TB (LTBI) is not routinely done. Studies carried out in industrialized nations with high immigration from TBendemic countries provide data of lifetime LTBI reactivation of around 10% but little is known about reactivation rates within TB-endemic countries where new infections (or reinfections) may be impossible to distinguish from reactivation. Migrant populations like the SAWP workers who spend considerable amounts of time in both Canada and TBendemic rural areas in Mexico are a unique population in terms of TB epidemiology. However, to our knowledge no studies have been undertaken to explore either the existence of LTBI among Mexican workers, the probability of reactivation or the workers' exposure to TB cases while back in their communities before returning the following season. Being aware of their LTBI status may help workers to exercise healthy behaviours to avoid TB reactivation and therefore continue to access the SAWP. In order to assess the prevalence of LTBI and associated risk factors among Mexican migrant workers a preliminary cross sectional study was designed to involve a convenience sample of the Niagara Region's Mexican workers in 2007. Research ethics clearance was granted by Brock University. Individual questionnaires were administered to collect socio-demographic and TB-related epidemiological data as well as TB knowledge and awareness levels. Cellular immunity to M tuberculosis was assessed by both an Interferon-y release assay (lGRA), QuantiFERON -TB Gold In-Tube (QFf™) and by the tuberculin skin test (TSn using Mantoux. A total of 82 Mexican workers (out of 125 invited) completed the study. Most participants were male (80%) and their age ranged from 22 to 65 years (mean 38.5). The prevalence of LTBI was 34% using TST and 18% using QFTTM. As previously reported, TST (using ~lOmm cut-off) showed a sensitivity of 93.3% and a specificity of 79.1 %. These findings at the moment cannot predict the probability of progression to active TB; only longitudinal cohort studies of this population can ascertain this outcome. However, based on recent publications, lORA positive individuals may have up to 14% probability of reactivation within the next two years. Although according to the SA WP guidelines, all workers undergo TB screening before entering or re-entering Canada, CXR examination requirements showed to be inconsistent for this population: whereas 100% of the workers coming to Canada for the first time reported having the procedure done, only 31 % of returning participants reported having had a CXR in the past year. None of the participants reported ever having a CXR compatible with TB which was consistent with the fact that none had ever been diagnosed with active pulmonary TB and with only 3.6% reporting close contact with a person with active TB in their lifetime. Although Mexico reports that 99% of popUlation is fully immunized against TB within the first year of age, only 85.3% of participants reported receiving BOC vaccine in childhood. Conversely, even when TST is not part of the routine TB screening in endemic countries, a suqDrisingly high 25.6% reported receiving a TST in the past. In regards to TB knowledge and awareness, 74% of the studied population had previous knowledge about (active) TB, 42% correctly identified active TB symptomatology, 4.8% identified the correct route of transmission, 4.8% knew about the existence of LTBI, 3.6% knew that latent TB could reactivate and 48% recognized TB as treatable and curable. Of all variables explored as potential risk factors for LTBI, age was the only one which showed statistical significance. Significant associations could not be proven for other known variables (such as sex, TB contact, history of TB) probably because of the small sample size and the homogeneity of the sample. Screening for LTBI by TST (high sensitivity) followed by confirmation with QFT''"'^ (high specificity) suggests to be a good strategy especially for immigrants from TB high-burden countries. After educational sessions, workers positive for LTBI gained greater knowledge about the signs and symptoms of TB reactivation as well as the risk factors commonly associated with reactivation. Additionally, they were more likely to attend their annual health check up and request a CXR exam to monitor for TB reactivation.

Vitamin D status and latent tuberculosis infection : a preliminary study in a group of healthy Mexican agricultural workers

Vitamin D metabolites are important in the regulation of bone and calcium homeostasis, but also have a more ubiquitous role in the regulation of cell differentiation and immune function. Severely low circulating 25-dihydroxyvitamin D [25(OH)D] concentrations have been associated with the onset of active tuberculosis (TB) in immigrant populations, although the association with latent TB infection (LTBI) has not received much attention. A previous study identified the prevalence of LTBI among a sample of Mexican migrant workers enrolled in Canada's Seasonal Agricultural Workers Program (SA WP) in the Niagara Region of Ontario. The aim of the present study was to determine the vitamin D status of the same sample, and identify if a relationship existed with LTBI. Studies of vitamin D deficiency and active TB are most commonly carried out among immigrant populations to non-endemic regions, in which reactivation of LTBI has occurred. Currently, there is limited knowledge of the association between vitamin D deficiency and LTBI. Entry into Canada ensured that these individuals did not have active TB, and L TBI status was established previously by an interferon-gamma release assay (IGRA) (QuantiFERON-TB Gold In-Tube®, Cellestis Ltd., Australia). Awareness of vitamin D status may enable individuals at risk of deficiency to improve their nutritional health, and those with LTBI to be aware of this risk factor for disease. Prevalence of vitamin D insufficiency among the Mexican migrant workers was determined from serum samples collected in the summer of 2007 as part of the cross sectional LTBI study. Samples were measured for concentrations of the main circulating vitamin D metabolite, 25(OH)D, with a widely used 1251 250HD RIA (DiaSorin Inc.®, Stillwater, MN), and were categorized as deficient «37.5 nmoI/L), insufficient (>37.5 nmollL, < 80 nmol/L) or sufficient (2::80 nmoI/L). Fisher's exact tests and t tests were used to determine if vitamin D status (sufficiency or insufficiency) or 25(OH)D concentrations significantly differed by sex or age categories. Predictors of vitamin D insufficiency and 25(OH)D concentrations were taken from questionnaires carried out during the previous study, and analyzed in the present study using multiple regression prediction models. Fisher's exact test and t test was used to determine if vitamin D status or 25(OH)D concentration differed by LTBI status. Strength of the relationship between interferongamma (IFN-y) concentration (released by peripheral T cells in response to TB antigens) and 25(OH)D concentration was analyzed using a Spearman correlation. Out of 87 participants included in the study (78% male; mean age 38 years), 14 were identified as LTBI positive but none had any signs or symptoms of TB reactivation. Only 30% of the participants were vitamin D sufficient, whereas 68% were insufficient and 2% were deficient. Significant independent predictors of lower 25(OH)D concentrations were sex, number of years enrolled in the SA WP and length of stay in Canada. No significant differences were found between 25(OH)D concentrations and LTBI status. There was a significant moderate correlation between IFN-y and 25(OH)D concentrations ofLTBI-positive individuals. The majority of participants presented with Vitamin D insufficiency but none were severely deficient, indicating that 25(OH)D concentrations do not decrease dramatically in populations who temporarily reside in Canada but go back to their countries of origin during the Canadian winter. This study did not find a statistical relationship between low levels of vitamin D and LTBI which suggests that in the presence of overall good health, lower than ideal levels of 2S(OH)D, may still be exerting a protective immunological effect against LTBI reactivation. The challenge remains to determine a critical 2S(OH)D concentration at which reactivation is more likely to occur.

Impact of considering the effects of latent heat on caldera-hosted hydrothermal systems

To investigate the thennal effects of latent heat in hydrothennal settings, an extension was made to the existing finite-element numerical modelling software, Aquarius. The latent heat algorithm was validated using a series of column models, which analysed the effects of penneability (flow rate), thennal gradient, and position along the two-phase curve (pressure). Increasing the flow rate and pressure increases displacement of the liquid-steam boundary from an initial position detennined without accounting for latent heat while increasing the thennal gradient decreases that displacement. Application to a regional scale model of a caldera-hosted hydrothennal system based on a representative suite of calderas (e.g., Yellowstone, Creede, Valles Grande) led to oscillations in the model solution. Oscillations can be reduced or eliminated by mesh refinement, which requires greater computation effort. Results indicate that latent heat should be accounted for to accurately model phase change conditions in hydrothennal settings.

Nonsuicidal Self-Injury and Suicidal Behavior: A Latent Class Analysis among Young Adults

Although there is a general consensus among researchers that engagement in nonsuicidal self-injury (NSSI) is associated with increased risk for suicidal behavior, little attention has been given to whether suicidal risk varies among individuals engaging in NSSI. To identify individuals with a history of NSSI who are most at risk for suicidal behavior, we examined individual variability in both NSSI and suicidal behavior among a sample of young adults with a history of NSSI (N = 439, Mage = 19.1). Participants completed self-report measures assessing NSSI, suicidal behavior, and psychosocial adjustment (e.g., depressive symptoms, daily hassles). We conducted a latent class analysis using several characteristics of NSSI and suicidal behaviors as class indicators. Three subgroups of individuals were identified: 1) an infrequent NSSI/not high risk for suicidal behavior group, 2) a frequent NSSI/not high risk for suicidal behavior group, and 3) a frequent NSSI/high risk for suicidal behavior group. Follow-up analyses indicated that individuals in the ‘frequent NSSI/high risk for suicidal behavior’ group met the clinical-cut off score for high suicidal risk and reported significantly greater levels of suicidal ideation, attempts, and risk for future suicidal behavior as compared to the other two classes. Thus, this study is the first to identity variability in suicidal risk among individuals engaging in frequent and multiple methods of NSSI. Class 3 was also differentiated by higher levels of psychosocial impairment relative to the other two classes, as well as a comparison group of non-injuring young adults. Results underscore the importance of assessing individual differences in NSSI characteristics, as well as psychosocial impairment, when assessing risk for suicidal behavior.

Latent Variable Models for Stochastic Discount Factors.

Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.

Empirical Assessment of an Intertemporal Option Pricing Model with Latent variables

This paper assesses the empirical performance of an intertemporal option pricing model with latent variables which generalizes the Hull-White stochastic volatility formula. Using this generalized formula in an ad-hoc fashion to extract two implicit parameters and forecast next day S&P 500 option prices, we obtain similar pricing errors than with implied volatility alone as in the Hull-White case. When we specialize this model to an equilibrium recursive utility model, we show through simulations that option prices are more informative than stock prices about the structural parameters of the model. We also show that a simple method of moments with a panel of option prices provides good estimates of the parameters of the model. This lays the ground for an empirical assessment of this equilibrium model with S&P 500 option prices in terms of pricing errors.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

An Improved Technique for Evolving Wavelet Coefficients for Fingerprint Image Compression

In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16:1. These evolved coefficients perform well for other compression ratios also.

Faster techniques to evolve wavelet coefficients for better fingerprint image compression

In this article, techniques have been presented for faster evolution of wavelet lifting coefficients for fingerprint image compression (FIC). In addition to increasing the computational speed by 81.35%, the coefficients performed much better than the reported coefficients in literature. Generally, full-size images are used for evolving wavelet coefficients, which is time consuming. To overcome this, in this work, wavelets were evolved with resized, cropped, resized-average and cropped-average images. On comparing the peak- signal-to-noise-ratios (PSNR) offered by the evolved wavelets, it was found that the cropped images excelled the resized images and is in par with the results reported till date. Wavelet lifting coefficients evolved from an average of four 256 256 centre-cropped images took less than 1/5th the evolution time reported in literature. It produced an improvement of 1.009 dB in average PSNR. Improvement in average PSNR was observed for other compression ratios (CR) and degraded images as well. The proposed technique gave better PSNR for various bit rates, with set partitioning in hierarchical trees (SPIHT) coder. These coefficients performed well with other fingerprint databases as well.

Evolution of Better Wavelet Coefficients for Fingerprint Image Compression using cropped images

This paper explains the Genetic Algorithm (GA) evolution of optimized wavelet that surpass the cdf9/7 wavelet for fingerprint compression and reconstruction. Optimized wavelets have already been evolved in previous works in the literature, but they are highly computationally complex and time consuming. Therefore, in this work, a simple approach is made to reduce the computational complexity of the evolution algorithm. A training image set comprised of three 32x32 size cropped images performed much better than the reported coefficients in literature. An average improvement of 1.0059 dB in PSNR above the classical cdf9/7 wavelet over the 80 fingerprint images was achieved. In addition, the computational speed was increased by 90.18 %. The evolved coefficients for compression ratio (CR) 16:1 yielded better average PSNR for other CRs also. Improvement in average PSNR was experienced for degraded and noisy images as well

Multifinger Feature Level Fusion Based Fingerprint Identification

Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images are taken, global singularities are located using directional field strength and their local orientation vector is formulated with respect to the base line of the finger. Feature level fusion is carried out and a 32 element feature template is obtained. A matching score is formulated for the identification and 100% accuracy was obtained for a database of 300 persons. The polygonal feature vector helps to reduce the size of the feature database from the present 70-100 minutiae features to just 32 features and also a lower matching threshold can be fixed compared to single finger based identification