Detection of recently discovered human polyomaviruses in a longitudinal kidney transplant cohort

A large number of human polyomaviruses have been discovered in the last 7 years. However, little is known about the clinical impact on vulnerable immunosuppressed patient populations. Blood, urine, and respiratory swabs collected from a prospective, longitudinal adult kidney transplant cohort (n = 167) generally pre-operatively, at day 4, months 1, 3, and 6 posttransplant, and at BK viremic episodes within the first year were screened for 12 human polyomaviruses using real-time polymerase chain reaction. Newly discovered polyomaviruses were most commonly detected in the respiratory tract, with persistent shedding seen for up to 6 months posttransplant. Merkel cell polyomavirus was the most common detection, but was not associated with clinical symptoms or subsequent development of skin cancer or other skin abnormalities. In contrast, KI polyomavirus was associated with respiratory disease in a subset of patients. Human polyomavirus 9, Malawi polyomavirus, and human polyomavirus 12 were not detected in any patient samples.

Selection of intrusion detection system threshold bounds for effective sensor fusion

The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

Detection,amplification and sequence homology of sodC in clinical isolates of Salmonella sp

Background & objectives: Periplasmic copper and zinc superoxide dismutase (Cu,Zn-SOD or SodC) is an important component of the antioxidant shield which protects bacteria from the phagocytic oxidative burst. Cu,Zn-SODs protect Gram-negative bacteria against oxygen damage which have also been shown to contribute to the pathogenicity of these bacterial species. We report the presence of SodC in drug resistant Salmonella sp. isolated from patients suffering from enteric fever. Further sodC was amplified, cloned into Escherichia coli and the nucleotide sequence and amino acid sequence homology were compared with the standard strain Salmonella Typhimurium 14028. Methods: Salmonella enterica serovar Typhi (S. Typhi) and Salmonellaenterica serovar Paratyphi (S. Paratyphi) were isolated and identified from blood samples of the patients. The isolates were screened for the presence of Cu, Zn-SOD by PAGE using KCN as inhibitor of Cu,Zn-SOD. The gene (sodC) was amplified by PCR, cloned and sequenced. The nucleotide and amino acid sequences of sodC were compared using CLUSTAL X.Results: SodC was detected in 35 per cent of the Salmonella isolates. Amplification of the genomic DNA of S. Typhi and S. Paratyphi with sodC specific primers resulted in 519 and 515 bp amplicons respectively. Single mutational difference at position 489 was observed between thesodC of S. Typhi and S. Paratyphi while they differed at 6 positions with the sodC of S. Typhimurium 14028. The SodC amino acid sequences of the two isolates were homologous but 3 amino acid difference was observed with that of standard strain S. Typhimurium 14028.Interpretation & conclusions: The presence of SodC in pathogenic bacteria could be a novel candidate as phylogenetic marker.

Detection of multiple source locations using a glowworm metaphor with applications to collective robotics

This paper presents a glowworm swarm based algorithm that finds solutions to optimization of multiple optima continuous functions. The algorithm is a variant of a well known ant-colony optimization (ACO) technique, but with several significant modifications. Similar to how each moving region in the ACO technique is associated with a pheromone value, the agents in our algorithm carry a luminescence quantity along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luminescence and have a circular sensor range. The glowworms depend on a local-decision domain to compute their movements. Simulations demonstrate the efficacy of the proposed glowworm based algorithm in capturing multiple optima of a multimodal function. The above optimization scenario solves problems where a collection of autonomous robots is used to form a mobile sensor network. In particular, we address the problem of detecting multiple sources of a general nutrient profile that is distributed spatially on a two dimensional workspace using multiple robots.

Oncolytic Adenoviruses with Radiation Therapy for Treatment of Prostate Cancer

Prostate cancer is the most common cancer in males. Although many patients with localized disease can be cured with surgery and radiotherapy, advanced disease and especially castration resistant metastatic disease remains incurable, with a median life expectancy of less than 18 months. Oncolytic adenoviruses (Ads) are a new promising treatment against cancer due to their innate capacity to kill cancer cells. Viral replication in tumor cells leads to oncolysis and production of a multiplicity of new virions that are capable of further destroying cancerous tissue. Oncolytic Ads can be modified for tumor targeted infection and replication and be armed with therapeutic transgenes to maximize the oncolytic effect. Worldwide, clinical trials with oncolytic Ads have demonstrated good safety while the antitumor efficacy remains to be improved. Importantly, the best responses have been reported when oncolytic adenoviruses have been combined with standard cancer treatments, such as chemotherapy and radiation. Further, a challenge in many virotherapy approaches has been the monitoring of virus replication in vivo. Reporter genes have been extensively used as transgenes to evaluate the biodistribution of the virus and activity of specific promoters. However, these techniques are often limited to preclinical evaluation and not amenable to human use. The aim of the thesis was to find and develop new oncolytic Ads with maximum efficacy against metastatic, castration resistant prostate cancer and study them in vitro and in vivo combined to different forms of radiation therapy. Using combination therapy, we were aiming for better antitumor efficacy with reduced side effects. Capsid modified Ads for enhanced transduction were studied. Serotype 3 targeted chimera, Ad5/3, was found to have enhanced infectivity for prostate cancer and was used for developing new viruses for the study. Correlation between Ad-encoded marker peptide secretion and simultaneous viral replication was evaluated and the effects of radiotherapy on viral replication were studied in detail. We found that the repair of double strand breaks caused by ionizing radiation was inhibited by adenoviral proteins and led to autophagic cell death. Both subcutaneous models and intrapulmonary tumor models mimicking metastatic, aggressive disease were used in vivo. Virus efficacy was evaluated by intratumoral injections. Also, intravenous administration was evaluated to study the effectiveness in metastatic disease. Oncolytic adenovirus treatment led to significant tumor growth control and increased the survival rate of the mice. These results were further improved when oncolytic Ads were combined with radiation therapy. Oncolytic Ads expressing human sodium/iodide transporter (hNIS) as a transgene were evaluated for their oncolytic potency and for the functionality of hNIS in vitro and in vivo. Monitoring of viral replication was also assessed using different imaging modalities relative to clinical use. SPECT imaging of tumor-bearing mice was evaluated and combined with simultaneous CT-scanning to obtain important anatomical information on biodistribution, also in a three-dimensional form. It was shown that hNIS-expressing adenoviruses could harbour a bi-functional transgene allowing for localization and imaging of viral replication. Targeted radiotherapy was applied by systemic radioiodide administration and resulted in iodide accumulation into Ad-infected tumor. The combination treatment showed significantly enhanced antitumor efficacy in mice bearing prostate cancer tumors. In summary, the results presented above aim to provide new treatment modalities for castration resistant prostate cancer. Molecular insights were provided for better understanding of the benefits of combined radiation therapy and oncolytic adenoviruses, which will hopefully facilitate the translation of the approach into clinical use for humans.

Detection of a periodic structure hidden in random background: the role of signal amplitude in the matched filter detection method

The matched filter method for detecting a periodic structure on a surface hidden behind randomness is known to detect up to (r(0)/Lambda) gt;= 0.11, where r(0) is the coherence length of light on scattering from the rough part and 3 is the wavelength of the periodic part of the surface-the above limit being much lower than what is allowed by conventional detection methods. The primary goal of this technique is the detection and characterization of the periodic structure hidden behind randomness without the use of any complicated experimental or computational procedures. This paper examines this detection procedure for various values of the amplitude a of the periodic part beginning from a = 0 to small finite values of a. We thus address the importance of the following quantities: `(a)lambda) `, which scales the amplitude of the periodic part with the wavelength of light, and (r(0))Lambda),in determining the detectability of the intensity peaks.

An exact similarity solution in radiation-gas-dynamics

We have found an exact similarity solution of the point explosion problem in the case when the total energy of the shock wave that is produced is not constant but decreases with time and when the loss due to radiation escape is significant. We have compared the results of our exact solution with those of exact numerical solutions of Elliot and Wang and have explained the cause why our solution differs from theirs in certain aspects.

A class of one-dimensional steady-state flows in radiation-gas-dynamics

The study of steady-state flows in radiation-gas-dynamics, when radiation pressure is negligible in comparison with gas pressure, can be reduced to the study of a single first-order ordinary differential equation in particle velocity and radiation pressure. The class of steady flows, determined by the fact that the velocities in two uniform states are real, i.e. the Rankine-Hugoniot points are real, has been discussed in detail in a previous paper by one of us, when the Mach number M of the flow in one of the uniform states (at x=+∞) is greater than one and the flow direction is in the negative direction of the x-axis. In this paper we have discussed the case when M is less than or equal to one and the flow direction is still in the negative direction of the x-axis. We have drawn the various phase planes and the integral curves in each phase plane give various steady flows. We have also discussed the appearance of discontinuities in these flows.

Strong shock with radiation near the surface of a star

The propagation of a shock wave, originating in a stellar interior, is considered when it approaches the surface of the star and assumes a self-similar character, "forgetting" its initial conditions. The flow behind the shock is assumed to be spatially isothermal rather than adiabatic to simulate the conditions of large radiative transfer near the stellar surface. The adiabatic and isothermal flows behind such a shock are compared. The exact shock-propagation laws, obtained by solving the equations in similarity variables, for different values of the parameter δ in the undisturbed density law, ρ0 ∝ xδ, and γ, the ratio of specific heats, are compared with the approximate values calculated by Whitham's characteristic rule and the two show a generally good agreement.

Possible use of self-calibration to reduce systematic uncertainties in determining distance-redshift relation via gravitational radiation from merging binaries

By observing mergers of compact objects, future gravity wave experiments would measure the luminosity distance to a large number of sources to a high precision but not their redshifts. Given the directional sensitivity of an experiment, a fraction of such sources (gold plated) can be identified optically as single objects in the direction of the source. We show that if an approximate distance-redshift relation is known then it is possible to statistically resolve those sources that have multiple galaxies in the beam. We study the feasibility of using gold plated sources to iteratively resolve the unresolved sources, obtain the self-calibrated best possible distance-redshift relation and provide an analytical expression for the accuracy achievable. We derive the lower limit on the total number of sources that is needed to achieve this accuracy through self-calibration. We show that this limit depends exponentially on the beam width and give estimates for various experimental parameters representative of future gravitational wave experiments DECIGO and BBO.

A Wavelet based Teager Energy Operator for Spike Detection in Microelectrode Array Recordings

Spike detection in neural recordings is the initial step in the creation of brain machine interfaces. The Teager energy operator (TEO) treats a spike as an increase in the `local' energy and detects this increase. The performance of TEO in detecting action potential spikes suffers due to its sensitivity to the frequency of spikes in the presence of noise which is present in microelectrode array (MEA) recordings. The multiresolution TEO (mTEO) method overcomes this shortcoming of the TEO by tuning the parameter k to an optimal value m so as to match to frequency of the spike. In this paper, we present an algorithm for the mTEO using the multiresolution structure of wavelets along with inbuilt lowpass filtering of the subband signals. The algorithm is efficient and can be implemented for real-time processing of neural signals for spike detection. The performance of the algorithm is tested on a simulated neural signal with 10 spike templates obtained from [14]. The background noise is modeled as a colored Gaussian random process. Using the noise standard deviation and autocorrelation functions obtained from recorded data, background noise was simulated by an autoregressive (AR(5)) filter. The simulations show a spike detection accuracy of 90%and above with less than 5% false positives at an SNR of 2.35 dB as compared to 80% accuracy and 10% false positives reported [6] on simulated neural signals.

On resampling detection and its application to detect image tampering

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.

Transient signal detection using wigner-ville distribution and wavelet denoising

The problem of detecting an unknown transient signal in noise is considered. The SNR of the observed data is first enhanced using wavelet domain filter The output of the wavelet domain filter is then transformed using a Wigner-Ville transform,which separates the spectrum of the observed signal into narrow frequency bands. Each subband signal at the output of the Wigner-ville block is subjected kto wavelet based level dependent denoising (WBLDD)to supress colored noise A weighted sum of the absolute value of outputs of WBLDD is passed through an energy detector, whose output is used as test statistic to take the final decision. By assigning weights proportional to the energy of the corresponding subband signals, the proposed detector approximates a frequency domain matched filter Simulation results are presented to show that the performance of the proposed detector is better than that of the wavelet packet transform based detector.