Patchy layered structure of tropical troposphere as seen by Indian MST radar

The MST radar observations at Gadanki (13.47° N, 79.18° E) show, almost every day throughout the year, stratified layers of intense reflectivity near the tropopause level (17 km) and also at a couple of levels between 4 km and 10 km. Highest individual reflectivity values occur near 17 km, but they occur for a short while. The region between 11 km and 15 km shows the lowest values of reflectivity alongwith vertical downward motion almost on all days of the year. High values of reflectivity are attributed to the existence of visible or sub-visible clouds; the layered structure of clouds is attributed to inertio-gravity waves with vertical wavelength of 2-3 km. It is suggested that each high reflectivity layer consists mainly of thin sheets and patches of visible and sub-visible cloud material. Hydrometeors inside the cloud material go up and down due to gravity, precipitation-loading, Brunt-Vaisala oscillations, and Kelvin-Helmholtz waves. In these small-scale motions, thin air sheets and patches get formed with sharp temperature and humidity discontinuities through contact cooling, melting, evaporation, condensation and freezing. Also, melting and freezing at low temperatures generate electrical charges in these thin sheets and patches. These thin sheets and patches have vertical dimensions ranging from a few centimetres to several metres and horizontal dimensions of the order of 1km. These thin sheets and patches have corresponding vertical and horizontal discontinuities and sharp gradients in refractive index for the MST radar beam. These show up as regions of high values of reflectivity

Spin-orbit density wave induced hidden topological order in URu2Si2

The conventional order parameters in quantum matters are often characterized by 'spontaneous' broken symmetries. However, sometimes the broken symmetries may blend with the invariant symmetries to lead to mysterious emergent phases. The heavy fermion metal URu2Si2 is one such example, where the order parameter responsible for a second-order phase transition at Th = 17.5 K has remained a long-standing mystery. Here we propose via ab-initio calculation and effective model that a novel spin-orbit density wave in the f-states is responsible for the hidden-order phase in URu2Si2. The staggered spin-orbit order 'spontaneous' breaks rotational, and translational symmetries while time-reversal symmetry remains intact. Thus it is immune to pressure, but can be destroyed by magnetic field even at T = 0 K, that means at a quantum critical point. We compute topological index of the order parameter to show that the hidden order is topologically invariant. Finally, some verifiable predictions are presented.Comment: (v2) Substantially modified from v1, more calculation and comparison with experiments are include

Texture analysis-and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction:a preliminary study

We sought to investigate, whether texture analysis of diffusional kurtosis imaging (DKI) enhanced by support vector machine (SVM) analysis may provide biomarkers for gliomas staging and detection of the IDH mutation. First-order statistics and texture feature extraction were performed in 37 patients on both conventional (FLAIR) and mean diffusional kurtosis (MDK) images and recursive feature elimination (RFE) methodology based on SVM was employed to select the most discriminative diagnostic biomarkers. The first-order statistics demonstrated significantly lower MDK values in the IDH-mutant tumors. This resulted in 81.1% accuracy (sensitivity = 0.96, specificity = 0.45, AUC 0.59) for IDH mutation diagnosis. There were non-significant differences in average MDK and skewness among the different tumour grades. When texture analysis and SVM were utilized, the grading accuracy achieved by DKI biomarkers was 78.1% (sensitivity 0.77, specificity 0.79, AUC 0.79); the prediction accuracy for IDH mutation reached 83.8% (sensitivity 0.96, specificity 0.55, AUC 0.87). For the IDH mutation task, DKI outperformed significantly the FLAIR imaging. When using selected biomarkers after RFE, the prediction accuracy achieved 83.8% (sensitivity 0.92, specificity 0.64, AUC 0.88). These findings demonstrate the superiority of DKI enhanced by texture analysis and SVM, compared to conventional imaging, for gliomas staging and prediction of IDH mutational status

Azimuthal anisotropy and correlations at large transverse momenta in p+pp+p and Au+Au collisions at sNN\sqrt{s_{_{NN}}}= 200 GeV

Results on high transverse momentum charged particle emission with respect to the reaction plane are presented for Au+Au collisions at $\sqrt{s_{_{NN}}}$= 200 GeV. Two- and four-particle correlations results are presented as well as a comparison of azimuthal correlations in Au+Au collisions to those in $p+p$ at the same energy. Elliptic anisotropy, $v_2$, is found to reach its maximum at $p_t \sim 3$ GeV/c, then decrease slowly and remain significant up to $p_t\approx 7$ -- 10 GeV/c. Stronger suppression is found in the back-to-back high-$p_t$ particle correlations for particles emitted out-of-plane compared to those emitted in-plane. The centrality dependence of $v_2$ at intermediate $p_t$ is compared to simple models based on jet quenching.Comment: 4 figures. Published version as PRL 93, 252301 (2004

Azimuthal anisotropy in Au+Au collisions at sqrtsNN = 200 GeV

The results from the STAR Collaboration on directed flow (v_1), elliptic flow (v_2), and the fourth harmonic (v_4) in the anisotropic azimuthal distribution of particles from Au+Au collisions at sqrtsNN = 200 GeV are summarized and compared with results from other experiments and theoretical models. Results for identified particles are presented and fit with a Blast Wave model. Different anisotropic flow analysis methods are compared and nonflow effects are extracted from the data. For v_2, scaling with the number of constituent quarks and parton coalescence is discussed. For v_4, scaling with v_2^2 and quark coalescence is discussed.Comment: 26 pages. As accepted by Phys. Rev. C. Text rearranged, figures modified, but data the same. However, in Fig. 35 the hydro calculations are corrected in this version. The data tables are available at http://www.star.bnl.gov/central/publications/ by searching for "flow" and then this pape

Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death

Incorporation of enzyme concentrations into FBA and identification of optimal metabolic pathways

<p>Abstract</p> <p>Background</p> <p>In the present article, we propose a method for determining optimal metabolic pathways in terms of the level of concentration of the enzymes catalyzing various reactions in the entire metabolic network. The method, first of all, generates data on reaction fluxes in a pathway based on steady state condition. A set of constraints is formulated incorporating weighting coefficients corresponding to concentration of enzymes catalyzing reactions in the pathway. Finally, the rate of yield of the target metabolite, starting with a given substrate, is maximized in order to identify an optimal pathway through these weighting coefficients.</p> <p>Results</p> <p>The effectiveness of the present method is demonstrated on two synthetic systems existing in the literature, two pentose phosphate, two glycolytic pathways, core carbon metabolism and a large network of carotenoid biosynthesis pathway of various organisms belonging to different phylogeny. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. Biological relevance and validation of the results are provided. Finally, the impact of the method on metabolic engineering is explained with a few examples.</p> <p>Conclusions</p> <p>The method may be viewed as determining an optimal set of enzymes that is required to get an optimal metabolic pathway. Although it is a simple one, it has been able to identify a carotenoid biosynthesis pathway and the optimal pathway of core carbon metabolic network that is closer to some earlier investigations than that obtained by the extreme pathway analysis. Moreover, the present method has identified correctly optimal pathways for pentose phosphate and glycolytic pathways. It has been mentioned using some examples how the method can suitably be used in the context of metabolic engineering.</p

Phyllanthus spp. Induces Selective Growth Inhibition of PC-3 and MeWo Human Cancer Cells through Modulation of Cell Cycle and Induction of Apoptosis

BACKGROUND: Phyllanthus is a traditional medicinal plant that has been used in the treatment of many diseases including hepatitis and diabetes. The main aim of the present work was to investigate the potential cytotoxic effects of aqueous and methanolic extracts of four Phyllanthus species (P.amarus, P.niruri, P.urinaria and P.watsonii) against skin melanoma and prostate cancer cells. METHODOLOGY/PRINCIPAL FINDINGS: Phyllanthus plant appears to possess cytotoxic properties with half-maximal inhibitory concentration (IC(50)) values of 150-300 µg/ml for aqueous extract and 50-150 µg/ml for methanolic extract that were determined using the MTS reduction assay. In comparison, the plant extracts did not show any significant cytotoxicity on normal human skin (CCD-1127Sk) and prostate (RWPE-1) cells. The extracts appeared to act by causing the formation of a clear "ladder" fragmentation of apoptotic DNA on agarose gel, displayed TUNEL-positive cells with an elevation of caspase-3 and -7 activities. The Lactate Dehydrogenase (LDH) level was lower than 15% in Phyllanthus treated-cancer cells. These indicate that Phyllanthus extracts have the ability to induce apoptosis with minimal necrotic effects. Furthermore, cell cycle analysis revealed that Phyllanthus induced a Go/G1-phase arrest on PC-3 cells and a S-phase arrest on MeWo cells and these were accompanied by accumulation of cells in the Sub-G1 (apoptosis) phase. The cytotoxic properties may be due to the presence of polyphenol compounds such as ellagitannins, gallotannins, flavonoids and phenolic acids found both in the water and methanol extract of the plants. CONCLUSIONS/SIGNIFICANCE: Phyllanthus plant exerts its growth inhibition effect in a selective manner towards cancer cells through the modulation of cell cycle and induction of apoptosis via caspases activation in melanoma and prostate cancer cells. Hence, Phyllanthus may be sourced for the development of a potent apoptosis-inducing anticancer agent

Trends in modeling Biomedical Complex Systems

In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented