HuR Displaces Polypyrimidine Tract Binding Protein To Facilitate La Binding to the 3 ` Untranslated Region and Enhances Hepatitis C Virus Replication

HuR is a ubiquitous, RNA binding protein that influences the stability and translation of several cellular mRNAs. Here, we report a novel role for HuR, as a regulator of proteins assembling at the 3' untranslated region (UTR) of viral RNA in the context of hepatitis C virus (HCV) infection. HuR relocalizes from the nucleus to the cytoplasm upon HCV infection, interacts with the viral polymerase (NS5B), and gets redistributed into compartments of viral RNA synthesis. Depletion in HuR levels leads to a significant reduction in viral RNA synthesis. We further demonstrate that the interaction of HuR with the 3' UTR of the viral RNA affects the interaction of two host proteins, La and polypyrimidine tract binding protein (PTB), at this site. HuR interacts with La and facilitates La binding to the 3' UTR, enhancing La-mediated circularization of the HCV genome and thus viral replication. In addition, it competes with PTB for association with the 3' UTR, which might stimulate viral replication. Results suggest that HuR influences the formation of a cellular/viral ribonucleoprotein complex, which is important for efficient initiation of viral RNA replication. Our study unravels a novel strategy of regulation of HCV replication through an interplay of host and viral proteins, orchestrated by HuR. IMPORTANCE Hepatitis C virus (HCV) is highly dependent on various host factors for efficient replication of the viral RNA. Here, we have shown how a host factor (HuR) migrates from the nucleus to the cytoplasm and gets recruited in the protein complex assembling at the 3' untranslated region (UTR) of HCV RNA. At the 3' UTR, it facilitates circularization of the viral genome through interaction with another host factor, La, which is critical for replication. Also, it competes with the host protein PTB, which is a negative regulator of viral replication. Results demonstrate a unique strategy of regulation of HCV replication by a host protein through alteration of its subcellular localization and interacting partners. The study has advanced our knowledge of the molecular mechanism of HCV replication and unraveled the complex interplay between the host factors and viral RNA that could be targeted for therapeutic interventions.

Probabilistic Models for Forecasting Earthquakes in the Northeast Region of India

Northeast India and its adjoining areas are characterized by very high seismic activity. According to the Indian seismic code, the region falls under seismic zone V, which represents the highest seismic-hazard level in the country. This region has experienced a number of great earthquakes, such as the Assam (1950) and Shillong (1897) earthquakes, that caused huge devastation in the entire northeast and adjacent areas by flooding, landslides, liquefaction, and damage to roads and buildings. In this study, an attempt has been made to find the probability of occurrence of a major earthquake (M-w > 6) in this region using an updated earthquake catalog collected from different sources. Thereafter, dividing the catalog into six different seismic regions based on different tectonic features and seismogenic factors, the probability of occurrences was estimated using three models: the lognormal, Weibull, and gamma distributions. We calculated the logarithmic probability of the likelihood function (ln L) for all six regions and the entire northeast for all three stochastic models. A higher value of ln L suggests a better model, and a lower value shows a worse model. The results show different model suits for different seismic zones, but the majority follows lognormal, which is better for forecasting magnitude size. According to the results, Weibull shows the highest conditional probabilities among the three models for small as well as large elapsed time T and time intervals t, whereas the lognormal model shows the lowest and the gamma model shows intermediate probabilities. Only for elapsed time T = 0, the lognormal model shows the highest conditional probabilities among the three models at a smaller time interval (t = 3-15 yrs). The opposite result is observed at larger time intervals (t = 15-25 yrs), which show the highest probabilities for the Weibull model. However, based on this study, the IndoBurma Range and Eastern Himalaya show a high probability of occurrence in the 5 yr period 2012-2017 with >90% probability.

DETERMINISTIC ALGORITHMS FOR MATCHING AND PACKING PROBLEMS BASED ON REPRESENTATIVE SETS

In this work, we study the well-known r-DIMENSIONAL k-MATCHING ((r, k)-DM), and r-SET k-PACKING ((r, k)-SP) problems. Given a universe U := U-1 ... U-r and an r-uniform family F subset of U-1 x ... x U-r, the (r, k)-DM problem asks if F admits a collection of k mutually disjoint sets. Given a universe U and an r-uniform family F subset of 2(U), the (r, k)-SP problem asks if F admits a collection of k mutually disjoint sets. We employ techniques based on dynamic programming and representative families. This leads to a deterministic algorithm with running time O(2.851((r-1)k) .vertical bar F vertical bar. n log(2)n . logW) for the weighted version of (r, k)-DM, where W is the maximum weight in the input, and a deterministic algorithm with running time O(2.851((r-0.5501)k).vertical bar F vertical bar.n log(2) n . logW) for the weighted version of (r, k)-SP. Thus, we significantly improve the previous best known deterministic running times for (r, k)-DM and (r, k)-SP and the previous best known running times for their weighted versions. We rely on structural properties of (r, k)-DM and (r, k)-SP to develop algorithms that are faster than those that can be obtained by a standard use of representative sets. Incorporating the principles of iterative expansion, we obtain a better algorithm for (3, k)-DM, running in time O(2.004(3k).vertical bar F vertical bar . n log(2)n). We believe that this algorithm demonstrates an interesting application of representative families in conjunction with more traditional techniques. Furthermore, we present kernels of size O(e(r)r(k-1)(r) logW) for the weighted versions of (r, k)-DM and (r, k)-SP, improving the previous best known kernels of size O(r!r(k-1)(r) logW) for these problems.

Investigations of aerosol black carbon from a semi-urban site in the Indo-Gangetic Plain region

Long-term (2009-2012) data from ground-based measurements of aerosol black carbon (BC) from a semi-urban site, Pantnagar (29.0 degrees N, 79.5 degrees E, 231 m amsl), in the Indo-Gangetic Plain (IGP) near the Himalayan foothills are analyzed to study the regional characterization. Large variations are seen in BC at both diurnal and seasonal scales, associated with the mesoscale and synoptic meteorological processes, and local/regional anthropogenic activities. BC diurnal variations show two peaks (morning and evening) arising from the combined effects of the atmospheric boundary layer (ABL) dynamics and local emissions. The diurnal amplitudes as well as the rates of diurnal evolution are the highest in winter season, followed by autumn, and the lowest in summer-monsoon. BC exhibits nearly an inverse relation with mixing layer depth in all seasons; being strongest in winter (R-2 = 0.89) and weakest (R-2 = 0.33) in monsoon (July-August). Unlike BC, co-located aerosol optical depths (AOD) and aerosol absorption are highest in spring over IGP, probably due to the presence of higher abundances of aerosols (including dust) above the ABL (in the free troposphere). AOD (500 nm) showed annual peak (>0.6) in May-June, dominated by coarse mode, while fine mode aerosols dominated in late autumn and early winter. Aerosols profiles from CALIPSO show highest values close to the surface in winter/autumn, similar to the feature seen in surface BC, whereas at altitudes > 2 km, the extinction is maximum in spring/summer. WRF-Chem model is used to simulate BC temporal variations and then compared with observed BC. The model captures most of the important features of the diurnal and seasonal variations but significantly underestimated the observed BC levels, suggesting improvements in diurnal and seasonal varying BC emissions apart from the boundary layer processes. (C) 2015 Elsevier Ltd. All rights reserved.

Inter-comparison and performance evaluation of chemistry transport models over Indian region

Aerosol loading over the South Asian region has the potential to affect the monsoon rainfall, Himalayan glaciers and regional air-quality, with implications for the billions in this region. While field campaigns and network observations provide primary data, they tend to be location/season specific. Numerical models are useful to regionalize such location-specific data. Studies have shown that numerical models underestimate the aerosol scenario over the Indian region, mainly due to shortcomings related to meteorology and the emission inventories used. In this context, we have evaluated the performance of two such chemistry-transport models: WRF-Chem and SPRINTARS over an India-centric domain. The models differ in many aspects including physical domain, horizontal resolution, meteorological forcing and so on etc. Despite these differences, both the models simulated similar spatial patterns of Black Carbon (BC) mass concentration, (with a spatial correlation of 0.9 with each other), and a reasonable estimates of its concentration, though both of them under-estimated vis-a-vis the observations. While the emissions are lower (higher) in SPRINTARS (WRF-Chem), overestimation of wind parameters in WRF-Chem caused the concentration to be similar in both models. Additionally, we quantified the under-estimations of anthropogenic BC emissions in the inventories used these two models and three other widely used emission inventories. Our analysis indicates that all these emission inventories underestimate the emissions of BC over India by a factor that ranges from 1.5 to 2.9. We have also studied the model simulations of aerosol optical depth over the Indian region. The models differ significantly in simulations of AOD, with WRF-Chem having a better agreement with satellite observations of AOD as far as the spatial pattern is concerned. It is important to note that in addition to BC, dust can also contribute significantly to AOD. The models differ in simulations of the spatial pattern of mineral dust over the Indian region. We find that both meteorological forcing and emission formulation contribute to these differences. Since AOD is column integrated parameter, description of vertical profiles in both models, especially since elevated aerosol layers are often observed over Indian region, could be also a contributing factor. Additionally, differences in the prescription of the optical properties of BC between the models appear to affect the AOD simulations. We also compared simulation of sea-salt concentration in the two models and found that WRF-Chem underestimated its concentration vis-a-vis SPRINTARS. The differences in near-surface oceanic wind speeds appear to be the main source of this difference. In-spite of these differences, we note that there are similarities in their simulation of spatial patterns of various aerosol species (with each other and with observations) and hence models could be valuable tools for aerosol-related studies over the Indian region. Better estimation of emission inventories could improve aerosol-related simulations. (C) 2015 Elsevier Ltd. All rights reserved.

Region-of-interest diffuse optical tomography system

Diffuse optical tomography (DOT) using near-infrared light is a promising tool for non-invasive imaging of deep tissue. This technique is capable of quantitative reconstruction of absorption (mu(a)) and scattering coefficient (mu(s)) inhomogeneities in the tissue. The rationale for reconstructing the optical property map is that the absorption coefficient variation provides diagnostic information about metabolic and disease states of the tissue. The aim of DOT is to reconstruct the internal tissue cross section with good spatial resolution and contrast from noisy measurements non-invasively. We develop a region-of-interest scanning system based on DOT principles. Modulated light is injected into the phantom/tissue through one of the four light emitting diode sources. The light traversing through the tissue gets partially absorbed and scattered multiple times. The intensity and phase of the exiting light are measured using a set of photodetectors. The light transport through a tissue is diffusive in nature and is modeled using radiative transfer equation. However, a simplified model based on diffusion equation (DE) can be used if the system satisfies following conditions: (a) the optical parameter of the inhomogeneity is close to the optical property of the background, and (b) mu(s) of the medium is much greater than mu(a) (mu(s) >> mu(a)). The light transport through a highly scattering tissue satisfies both of these conditions. A discrete version of DE based on finite element method is used for solving the inverse problem. The depth of probing light inside the tissue depends on the wavelength of light, absorption, and scattering coefficients of the medium and the separation between the source and detector locations. Extensive simulation studies have been carried out and the results are validated using two sets of experimental measurements. The utility of the system can be further improved by using multiple wavelength light sources. In such a scheme, the spectroscopic variation of absorption coefficient in the tissue can be used to arrive at the oxygenation changes in the tissue. (C) 2016 AIP Publishing LLC.

Fully 3D refraction correction dosimetry system

The irradiation of selective regions in a polymer gel dosimeter results in an increase in optical density and refractive index (RI) at those regions. An optical tomography-based dosimeter depends on rayline path through the dosimeter to estimate and reconstruct the dose distribution. The refraction of light passing through a dose region results in artefacts in the reconstructed images. These refraction errors are dependant on the scanning geometry and collection optics. We developed a fully 3D image reconstruction algorithm, algebraic reconstruction technique-refraction correction (ART-rc) that corrects for the refractive index mismatches present in a gel dosimeter scanner not only at the boundary, but also for any rayline refraction due to multiple dose regions inside the dosimeter. In this study, simulation and experimental studies have been carried out to reconstruct a 3D dose volume using 2D CCD measurements taken for various views. The study also focuses on the effectiveness of using different refractive-index matching media surrounding the gel dosimeter. Since the optical density is assumed to be low for a dosimeter, the filtered backprojection is routinely used for reconstruction. We carry out the reconstructions using conventional algebraic reconstruction (ART) and refractive index corrected ART (ART-rc) algorithms. The reconstructions based on FDK algorithm for cone-beam tomography has also been carried out for comparison. Line scanners and point detectors, are used to obtain reconstructions plane by plane. The rays passing through dose region with a RI mismatch does not reach the detector in the same plane depending on the angle of incidence and RI. In the fully 3D scanning setup using 2D array detectors, light rays that undergo refraction are still collected and hence can still be accounted for in the reconstruction algorithm. It is found that, for the central region of the dosimeter, the usable radius using ART-rc algorithm with water as RI matched medium is 71.8%, an increase of 6.4% compared to that achieved using conventional ART algorithm. Smaller diameter dosimeters are scanned with dry air scanning by using a wide-angle lens that collects refracted light. The images reconstructed using cone beam geometry is seen to deteriorate in some planes as those regions are not scanned. Refraction correction is important and needs to be taken in to consideration to achieve quantitatively accurate dose reconstructions. Refraction modeling is crucial in array based scanners as it is not possible to identify refracted rays in the sinogram space.

Anthropogenic aerosol fraction over the Indian region: model simulations versus multi-satellite data analysis

Anthropogenic aerosols play a crucial role in our environment, climate, and health. Assessment of spatial and temporal variation in anthropogenic aerosols is essential to determine their impact. Aerosols are of natural and anthropogenic origin and together constitute a composite aerosol system. Information about either component needs elimination of the other from the composite aerosol system. In the present work we estimated the anthropogenic aerosol fraction (AF) over the Indian region following two different approaches and inter-compared the estimates. We espouse multi-satellite data analysis and model simulations (using the CHIMERE Chemical transport model) to derive natural aerosol distribution, which was subsequently used to estimate AF over the Indian subcontinent. These two approaches are significantly different from each other. Natural aerosol satellite-derived information was extracted in terms of optical depth while model simulations yielded mass concentration. Anthropogenic aerosol fraction distribution was studied over two periods in 2008: premonsoon (March-May) and winter (November-February) in regard to the known distinct seasonality in aerosol loading and type over the Indian region. Although both techniques have derived the same property, considerable differences were noted in temporal and spatial distribution. Satellite retrieval of AF showed maximum values during the pre-monsoon and summer months while lowest values were observed in winter. On the other hand, model simulations showed the highest concentration of AF in winter and the lowest during pre-monsoon and summer months. Both techniques provided an annual average AF of comparable magnitude (similar to 0.43 +/- 0.06 from the satellite and similar to 0.48 +/- 0.19 from the model). For winter months the model-estimated AF was similar to 0.62 +/- 0.09, significantly higher than that (0.39 +/- 0.05) estimated from the satellite, while during pre-monsoon months satellite-estimated AF was similar to 0.46 +/- 0.06 and the model simulation estimation similar to 0.53 +/- 0.14. Preliminary results from this work indicate that model-simulated results are nearer to the actual variation as compared to satellite estimation in view of general seasonal variation in aerosol concentrations.

Load-Unload Response Ratio and Accelerating Moment/Energy Release Critical Region Scaling and Earthquake Prediction

The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.

Diagnostico de hemoparasitos en equinos en la region del Pacifico de Nicaragua utilizando frotis sanguineo

Con el objetivo de conocer la presencia de agentes Etiológicos causantes de homoparásitosis en equinos se realizó un estudio en la faja del Pacifico de Nicaragua durante los meses de Abril a Noviembre del 2006, en los Departamentos de Carazo, Chinandega, Granada, León, Managua, Masaya y Rivas. Esta zona geográfica del país presenta una temperatura media anual en el rango de 30ºC a 32ºC y una humedad relativa de 76% ± 78 5%; precipitación pluvial media anual en el rango de 1483.9 a 1970.0 mm; la altitud osciló entre 82.97 msnm a 580.13 msnm. Se realizo un muestreo de 150 equinos mayores de dos años, correspondiente al 1.30 % de la población muestradas, en los cuales se tomo 3cc de sangre de la vena yugular, mediante una punción, a las muestras de sangre se les realizo dos frotis sanguíneos, y se obtuvo el hematocrito de la misma , tiñéndose los frotis sanguíneos por el método de Giemsa, posteriormente se observaron los frotis sanguíneos por cada equino muestrado, se utilizo microscopia óptica de inmersión para identificar lo hemoparásitos haciendo uso de los parámetros morfológicos de sus clasificación taxonómica. Se encontraron 58 equinos positivos de Babesia ssp correspondiente al 38.66 % de los 150 equinos muestrados y 92 casos de equinos negativos de Babesia ssp correspondiente al 61.33 % de los 150 equinos muestrados. Además se encontró prevalencia de Babesia de 5.92% en toda la faja del pacifico, encontrando para cada uno de los Departamentos muestrados son: a Managua con un 7.14 %, Masaya 6.43%, Granada 5.71%, Rivas 7.14%, Carazo 3,57%, León 3,57%, Chinandega 7,86% de Babesia ssp.

Caracterizacion del comportamiento de la estomatitis vesicular en animales domesticos de pezuña hendida en la sexta region (Jinotega y Matagalpa) en el periodo 2008

El presente trabajo se realizó con el fin de contribuir al conocimiento dando a conocer la Caracterización del comportamiento de la estomatitis Vesicular en animales domésticos de pezuña hendida en la región VI (Jinotega y Matagalpa) en el periodo 2008, debido a su gran poder de difusión considerando que en Nicaragua no existe un programa de erradicación o control de la estomatitis vesicular, aunque los humanos también pueden contraer estomatitis vesicular. Se hizo necesario realizar un monitoreo de la enfermedad en esta región, determinar el tipo de cepa que es mas prevalente en la especie de pezuña hendida y el lugar anatómico que más afecta , se tomaron muestras en conjunto con técnicos del MAGFOR y fueron enviadas al Laboratorio de Diagnóstico de Enfermedades Vesiculares (LADIVES) ,localizado en Panamá, se llevó a cabo un análisis estadístico descriptivo, para este análisis se utilizó la información que se colectó en los casos atendidos entre el mes de Julio a Diciembre 2008 y la información retrospectiva de Enero a Junio, con apoyo de la base de datos de Enfermedades Vesiculares que lleva la oficina del Convenio Bilateral Antiaftosa (CAB) del MAGFOR Se elaboraron distribuciones de frecuencia, para las variables; diagnóstico, prevalencia, especie animal y región anatómica, lo que nos accedió informarnos sobre los valores concretos que adoptaron las variables a analizar y sobre el número(o porcentaje) de veces que se repite cada uno de esos valores y nos permitió construir los diagramas con los resultados, concluyendo que de un total de 132 muestras enviadas al laboratorio 82 resultaron positivas a Estomatitis Vesicular, 44 de ellas resultaron al serotipo New Jersey en la zona de Matagalpa y 33 en Jinotega, 5 resultaron positivas al serotipo Indian a en Matagalpa y en la región de Jinotega no se presentó ninguna positiva a este serotipo, la especie más afectada fue el bovino, de las 132 muestras enviadas 129 fueron tomadas en esta especie, siendo las pezuñas el lugar anatómico de mayor predilección para el virus, del total de muestras 91 se tomaran esta región, manifestándose con mayor frecuencia en épocas de lluvia sobre todo en los meses de mayo a octubre.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

Temporally adaptive estimation of logistic classifiers on data streams

Modern technology has allowed real-time data collection in a variety of domains, ranging from environmental monitoring to healthcare. Consequently, there is a growing need for algorithms capable of performing inferential tasks in an online manner, continuously revising their estimates to reflect the current status of the underlying process. In particular, we are interested in constructing online and temporally adaptive classifiers capable of handling the possibly drifting decision boundaries arising in streaming environments. We first make a quadratic approximation to the log-likelihood that yields a recursive algorithm for fitting logistic regression online. We then suggest a novel way of equipping this framework with self-tuning forgetting factors. The resulting scheme is capable of tracking changes in the underlying probability distribution, adapting the decision boundary appropriately and hence maintaining high classification accuracy in dynamic or unstable environments. We demonstrate the scheme's effectiveness in both real and simulated streaming environments. © Springer-Verlag 2009.