Angiopreventive Efficacy of Pure Flavonolignans from Milk Thistle Extract against Prostate Cancer: Targeting VEGF-VEGFR Signaling

The role of neo-angiogenesis in prostate cancer (PCA) growth and metastasis is well established, but the development of effective and non-toxic pharmacological inhibitors of angiogenesis remains an unaccomplished goal. In this regard, targeting aberrant angiogenesis through non-toxic phytochemicals could be an attractive angiopreventive strategy against PCA. The rationale of the present study was to compare the anti-angiogenic potential of four pure diastereoisomeric flavonolignans, namely silybin A, silybin B, isosilybin A and isosilybin B, which we established previously as biologically active constituents in Milk Thistle extract. Results showed that oral feeding of these flavonolignans (50 and 100 mg/kg body weight) effectively inhibit the growth of advanced human PCA DU145 xenografts. Immunohistochemical analyses revealed that these flavonolignans inhibit tumor angiogenesis biomarkers (CD31 and nestin) and signaling molecules regulating angiogenesis (VEGF, VEGFR1, VEGFR2, phospho-Akt and HIF-1α) without adversely affecting the vessel-count in normal tissues (liver, lung, and kidney) of tumor bearing mice. These flavonolignans also inhibited the microvessel sprouting from mouse dorsal aortas ex vivo, and the VEGF-induced cell proliferation, capillary-like tube formation and invasiveness of human umbilical vein endothelial cells (HUVEC) in vitro. Further studies in HUVEC showed that these diastereoisomers target cell cycle, apoptosis and VEGF-induced signaling cascade. Three dimensional growth assay as well as co-culture invasion and in vitro angiogenesis studies (with HUVEC and DU145 cells) suggested the differential effectiveness of the diastereoisomers toward PCA and endothelial cells. Overall, these studies elucidated the comparative anti-angiogenic efficacy of pure flavonolignans from Milk Thistle and suggest their usefulness in PCA angioprevention

Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya

Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling-Narayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75 %) were randomly selected for building landslide susceptibility models, while the remaining 80 (25 %) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16 %. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57 % of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80 % accuracy (i.e. 89.15 % for IOE model, 89.10 % for LR model and 87.21 % for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling-Narayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.ArticleNATURAL HAZARDS. 65(1):135-165 (2013)journal articl

Assessment of safety and efficacy of Karallief® Easy ClimbTM, an herbal extract blend for supporting joint health: a double-blind, placebo-controlled, randomized clinical trial

Background: Osteoarthritis is common among the aging population worldwide. The current techniques to manage osteoarthritis focus on relieving pain and slowing the progression of the disease. Herbal or natural supplements have shown promise in achieving both these treatment goals. Two new proprietary herbal extract blends, Karallief® Easy ClimbTM (KEC) and herbal extracts with glucosamine (HEG), are combinations of several natural products shown to be effective in the treatment of knee osteoarthritis. The current study tested the efficacy and safety of KEC and HEG versus a placebo control.Methods: This is a randomized, double-blind and placebo-controlled study. A total of 120 patients were divided into 3 groups and were given KEC, HEG and Placebo in the ratio 1:1:1. Treatment results were assessed using the 30 second chair stand test, WOMAC test, knee flexion test and joint space measurement using X-rays of the knee joint.Results: The study found that the herbal supplements HEG and KEC significantly reduced osteoarthritis-related knee pain and increased joint mobility and were safe to use during 120 days of treatment. Both supplements resulted in an improvement in the 30 second chair stand test results, WOMAC pain scores, knee flexion, and joint space width as measured by X-ray, as compared to the placebo.Conclusions: Natural supplements such as HEG and KEC improve knee osteoarthritis symptoms and can be a safe and effective treatment option for patients with osteoarthritis

Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya.

Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling–Narayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75 %) were randomly selected for building landslide susceptibility models, while the remaining 80 (25 %) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16 %. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57 % of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80 % accuracy (i.e. 89.15 % for IOE model, 89.10 % for LR model and 87.21 % for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling–Narayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose

Anisotropy dissipation in brane-world inflation

We examine the behavior of an anisotropic brane-world in the presence of inflationary scalar fields. We show that, contrary to naive expectations, a large anisotropy does not adversely affect inflation. On the contrary, a large initial anisotropy introduces more damping into the scalar field equation of motion, resulting in greater inflation. The rapid decay of anisotropy in the brane-world significantly increases the class of initial conditions from which the observed universe could have originated. This generalizes a similar result in general relativity. A unique feature of Bianchi I brane-world cosmology appears to be that for scalar fields with a large kinetic term the initial expansion of the universe is quasi-isotropic. The universe grows more anisotropic during an intermediate transient regime until anisotropy finally disappears during inflationary expansion.Comment: 6 pages, 5 figures; minor typo corrected in Eq. (16); matches version to appear in Phy Rev

The GstLAL Search Analysis Methods for Compact Binary Mergers in Advanced LIGO's Second and Advanced Virgo's First Observing Runs

After their successful first observing run (September 12, 2015 - January 12, 2016), the Advanced LIGO detectors were upgraded to increase their sensitivity for the second observing run (November 30, 2016 - August 26, 2017). The Advanced Virgo detector joined the second observing run on August 1, 2017. We discuss the updates that happened during this period in the GstLAL-based inspiral pipeline, which is used to detect gravitational waves from the coalescence of compact binaries both in low latency and an offline configuration. These updates include deployment of a zero-latency whitening filter to reduce the over-all latency of the pipeline by up to 32 seconds, incorporation of the Virgo data stream in the analysis, introduction of a single-detector search to analyze data from the periods when only one of the detectors is running, addition of new parameters to the likelihood ratio ranking statistic, increase in the parameter space of the search, and introduction of a template mass-dependent glitch-excision thresholding method.Comment: 12 pages, 7 figures, to be submitted to Phys. Rev. D, comments welcom

Accretion of Chaplygin gas upon black holes: Formation of faster outflowing winds

We study the accretion of modified Chaplygin gas upon different types of black hole. Modified Chaplygin gas is one of the best candidates for a combined model of dark matter and dark energy. In addition, from a field theoretical point of view the modified Chaplygin gas model is equivalent to that of a scalar field having a self-interacting potential. We formulate the equations related to both spherical accretion and disc accretion, and respective winds. The corresponding numerical solutions of the flow, particularly of velocity, are presented and are analyzed. We show that the accretion-wind system of modified Chaplygin gas dramatically alters the wind solutions, producing faster winds, upon changes in physical parameters, while accretion solutions qualitatively remain unaffected. This implies that modified Chaplygin gas is more prone to produce outflow which is the natural consequence of the dark energy into the system.Comment: 21 pages including 7 figures; published in Classical and Quantum Gravit

Holistic Cube Analysis: A Query Framework for Data Insights

We present Holistic Cube Analysis (HoCA), a framework that augments the capabilities of relational queries for data insights. We first define AbstractCube, a data type defined as a function from RegionFeatures space to relational tables. AbstractCube provides a logical form of data for HoCA operators and their compositions to operate on to analyze the data. This function-as-data modeling allows us to simultaneously capture a space of non-uniform tables on the co-domain of the function, and region space structure on the domain of the function. We describe two HoCA operators, cube crawling and cube join, which are cube-to-cube transformations (i.e., higher-order functions). Cube crawling explores a region subspace, and outputs a cube mapping regions to signal vectors. Cube join, in turn, allows users to meld information in different cubes, which is critical for composition. The cube crawling interface introduces two novel features: (1) Region Analysis Models (RAMs), which allows one to program and organize analysis on a set of data features into a module. (2) Multi-Model Crawling, which allows one to apply multiple models, potentially on different feature sets, during crawling. These two features, together with cube join and a rich RAM library, allows us to construct succinct HoCA programs to capture a wide variety of data-insight problems in system monitoring, experimentation analysis, and business intelligence. HoCA poses a rich algorithmic design space, such as optimizing crawling performance leveraging region space structure, optimizing cube join performance, and physical designs of cubes. We describe several cube crawling implementations leveraging different foundations (an in-house relational query engine, and Apache Beam), and evaluate their performance characteristics. Finally, we discuss avenues in extending the framework, such as devising more useful HoCA operators.Comment: Establishing core concepts of HoC

Ultra Long Period Cepheids: a primary standard candle out to the Hubble flow

The cosmological distance ladder crucially depends on classical Cepheids (with P=3-80 days), which are primary distance indicators up to 33 Mpc. Within this volume, very few SNe Ia have been calibrated through classical Cepheids, with uncertainty related to the non-linearity and the metallicity dependence of their period-luminosity (PL) relation. Although a general consensus on these effects is still not achieved, classical Cepheids remain the most used primary distance indicators. A possible extension of these standard candles to further distances would be important. In this context, a very promising new tool is represented by the ultra-long period (ULP) Cepheids (P \geq 80 days), recently identified in star-forming galaxies. Only a small number of ULP Cepheids have been discovered so far. Here we present and analyse the properties of an updated sample of 37 ULP Cepheids observed in galaxies within a very large metallicity range of 12+log(O/H) from ~7.2 to 9.2 dex. We find that their location in the colour(V-I)-magnitude diagram as well as their Wesenheit (V-I) index-period (WP) relation suggests that they are the counterparts at high luminosity of the shorter-period (P \leq 80 days) classical Cepheids. However, a complete pulsation and evolutionary theoretical scenario is needed to properly interpret the true nature of these objects. We do not confirm the flattening in the studied WP relation suggested by Bird et al. (2009). Using the whole sample, we find that ULP Cepheids lie around a relation similar to that of the LMC, although with a large spread (~0.4 mag).Comment: 8 pages, 4 figures, accepted for publication in Astrophysics & Space Scienc

The Role of CD44 and ERM Proteins in Expression and Functionality of P-glycoprotein in Breast Cancer Cells

Multidrug resistance (MDR) is often attributed to the over-expression of P-glycoprotein (P-gp), which prevents the accumulation of anticancer drugs within cells by virtue of its active drug efflux capacity. We have previously described the intercellular transfer of P-gp via extracellular vesicles (EVs) and proposed the involvement of a unique protein complex in regulating this process. In this paper, we investigate the role of these mediators in the regulation of P-gp functionality and hence the acquisition of MDR following cell to cell transfer. By sequentially silencing the FERM domain-binding proteins, Ezrin, Radixin and Moesin (ERM), as well as CD44, which we also report a selective packaging in breast cancer derived EVs, we have established a role for these proteins, in particular Radixin and CD44, in influencing the P-gp-mediated MDR in whole cells. We also report for the first time the role of ERM proteins in the vesicular transfer of functional P-gp. Specifically, we demonstrate that intercellular membrane insertion is dependent on Ezrin and Moesin, whilst P-gp functionality is governed by the integrity of all ERM proteins in the recipient cell. This study identifies these candidate proteins as potential new therapeutic targets in circumventing MDR clinically