Antiproton Production in p+Ap+A Collisions at AGS Energies

Inclusive and semi-inclusive measurements are presented for antiproton ($\bar{p}$) production in proton-nucleus collisions at the AGS. The inclusive yields per event increase strongly with increasing beam energy and decrease slightly with increasing target mass. The $\bar{p}$ yield in 17.5 GeV/c p+Au collisions decreases with grey track multiplicity, $N_g$, for $N_g>0$, consistent with annihilation within the target nucleus. The relationship between $N_g$ and the number of scatterings of the proton in the nucleus is used to estimate the $\bar{p}$ annihilation cross section in the nuclear medium. The resulting cross section is at least a factor of five smaller than the free $\bar{p}-p$ annihilation cross section when assuming a small or negligible formation time. Only with a long formation time can the data be described with the free $\bar{p}-p$ annihilation cross section.Comment: 8 pages, 6 figure

Semi-Inclusive Lambda and Kshort Production in p-Au Collisions at 17.5 GeV/c

The first detailed measurements of the centrality dependence of strangeness production in p-A collisions are presented. Lambda and Kshort dn/dy distributions from 17.5 GeV/c p-Au collisions are shown as a function of "grey" track multiplicity and the estimated number of collisions, nu, made by the proton. The nu dependence of the Lambda yield deviates from a scaling of p-p data by the number of participants, increasing faster than this scaling for nu<=5 and saturating for larger nu. A slower growth in Kshort multiplicity with nu is observed, consistent with a weaker nu dependence of K-Kbar production than Y-K production.Comment: 5 pages, 3 figures, formatted with RevTex, current version has enlarged figure catpion

The Effects of Interactions on the Structure and Morphology of Elliptical/Lenticular galaxies in Pairs

We present a photometric and structural analysis of 42 E/S0 galaxies in (E/S0 + S) pairs observed in the BVRI color bands. We empirically determine the effects of interactions on their morphology, structure and stellar populations as seen from the light concentration (C), asymmetry (A), and clumpiness (S) parameters. We further compare these values to a control sample of 67 mostly isolated, non-interacting E/S0 galaxies. The paired E/S0 galaxies occupy a more scattered loci in CAS space than non-interacting E/S0's, and the structural effects of interactions on E/S0's are minor, in contrast to disk galaxies involved in interactions. This suggests that observational methods for recognizing interactions at high z, such the CAS methodology, would hardly detect E/S0's involved in interactions (related to early phases of the so called `dry-mergers'). We however find statistical differences in A when comparing isolated and interacting E/S0s. In the mean, paired E/S0 galaxies have A values 2.96+-0.72 times larger than the ones of non-interacting E/S0's. For the subset of presumably strongly interacting E/S0's, A and S can be several times larger than the typical values of the isolated E/S0's. We show that the asymmetries are consistent with several internal and external morphological distortions. We conclude that the interacting E/S0s in pairs should be dense, gas poor galaxies in systems spaning a wide range of interaction stages, with typical merging timescales >~ 0.1-0.5 Gyr. We use the observed phenomenology of these galaxies to predict the approximate loci of `dry pre-mergers' in the CAS space.(Abridged)Comment: 23 pages, 9 figures included. To appear in The Astronomical Journa

Strangeness Enhancement in p+Ap+A and S+AS+A Interactions at SPS Energies

The systematics of strangeness enhancement is calculated using the HIJING and VENUS models and compared to recent data on $\,pp\,$, $\,pA\,$ and $\,AA\,$ collisions at CERN/SPS energies ($200A\,\, GeV\,$). The HIJING model is used to perform a {\em linear} extrapolation from $pp$ to $AA$. VENUS is used to estimate the effects of final state cascading and possible non-conventional production mechanisms. This comparison shows that the large enhancement of strangeness observed in $S+Au$ collisions, interpreted previously as possible evidence for quark-gluon plasma formation, has its origins in non-equilibrium dynamics of few nucleon systems. % Strangeness enhancement %is therefore traced back to the change in the production dynamics %from $pp$ to minimum bias $pS$ and central $SS$ collisions. A factor of two enhancement of $\Lambda^{0}$ at mid-rapidity is indicated by recent $pS$ data, where on the average {\em one} projectile nucleon interacts with only {\em two} target nucleons. There appears to be another factor of two enhancement in the light ion reaction $SS$ relative to $pS$, when on the average only two projectile nucleons interact with two target ones.Comment: 29 pages, 8 figures in uuencoded postscript fil

Au+Au Reactions at the AGS: Experiments E866 and E917

Particle production and correlation functions from Au+Au reactions have been measured as a function of both beam energy (2-10.7AGeV) and impact parameter. These results are used to probe the dynamics of heavy-ion reactions, confront hadronic models over a wide range of conditions and to search for the onset of new phenomena.Comment: 12 pages, 14 figures, Talk presented at Quark Matter '9

High fat diet modifies the association of lipoprotein lipase gene polymorphism with high density lipoprotein cholesterol in an Asian Indian population

Background Single nucleotide polymorphisms (SNPs) in lipoprotein lipase gene (LPL) have been shown to influence metabolism related to lipid phenotypes. Dietary factors have been shown to modify the association between LPL SNPs and lipids; however, to date, there are no studies in South Asians. Hence, we tested for the association of four common LPL SNPs with plasma lipids and examined the interactions between the SNPs and dietary factors on lipids in 1,845 Asian Indians. Methods The analysis was performed in 788 Type 2 diabetes cases and 1,057 controls randomly chosen from the cross-sectional Chennai Urban Rural Epidemiological Study. Serum triacylglycerol (TAG), serum total cholesterol, and high-density lipoprotein cholesterol (HDL-C) were measured using a Hitachi-912 autoanalyzer (Roche Diagnostics GmbH, Mannheim, Germany). Dietary intake was assessed using a semi-quantitative food frequency questionnaire. The SNPs (rs1121923, rs328, rs4922115 and rs285) were genotyped by polymerase chain reaction followed by restriction enzyme digestion and 20% of samples were sequenced to validate the genotypes obtained. Statistical Package for Social Sciences for Windows version 22.0 (SPSS, Chicago, IL) was used for statistical analysis. Results After correction for multiple testing and adjusting for potential confounders, SNPs rs328 and rs285 showed association with HDL-C (P = 0.0004) and serum TAG (P = 1×10−5), respectively. The interaction between SNP rs1121923 and fat intake (energy %) on HDL-C (P = 0.003) was also significant, where, among those who consumed a high fat diet (28.4 ± 2.5%), the T allele carriers (TT + XT) had significantly higher HDL-C concentrations (P = 0.0002) and 30% reduced risk of low HDL-C levels compared to the CC homozygotes. None of the interactions on other lipid traits were statistically significant. Conclusion Our findings suggest that individuals carrying T allele of the SNP rs1121923 have increased HDL-C levels when consuming a high fat diet compared to CC homozygotes. Our finding warrants confirmation in prospective studies and randomized controlled trials

Analyzing multitarget activity landscapes using protein-ligand interaction fingerprints: interaction cliffs.

This is the original submitted version, before peer review. The final peer-reviewed version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/ci500721x.Activity landscape modeling is mostly a descriptive technique that allows rationalizing continuous and discontinuous SARs. Nevertheless, the interpretation of some landscape features, especially of activity cliffs, is not straightforward. As the nature of activity cliffs depends on the ligand and the target, information regarding both should be included in the analysis. A specific way to include this information is using protein-ligand interaction fingerprints (IFPs). In this paper we report the activity landscape modeling of 507 ligand-kinase complexes (from the KLIFS database) including IFP, which facilitates the analysis and interpretation of activity cliffs. Here we introduce the structure-activity-interaction similarity (SAIS) maps that incorporate information on ligand-target contact similarity. We also introduce the concept of interaction cliffs defined as ligand-target complexes with high structural and interaction similarity but have a large potency difference of the ligands. Moreover, the information retrieved regarding the specific interaction allowed the identification of activity cliff hot spots, which help to rationalize activity cliffs from the target point of view. In general, the information provided by IFPs provides a structure-based understanding of some activity landscape features. This paper shows examples of analyses that can be carried out when IFPs are added to the activity landscape model.M-L is very grateful to CONACyT (No. 217442/312933) and the Cambridge Overseas Trust for funding. AB thanks Unilever for funding and the European Research Council for a Starting Grant (ERC-2013- StG-336159 MIXTURE). J.L.M-F. is grateful to the School of Chemistry, Department of Pharmacy of the National Autonomous University of Mexico (UNAM) for support. This work was supported by a scholarship from the Secretariat of Public Education and the Mexican government

Prefrontal cortex output circuits guide reward seeking through divergent cue encoding

The prefrontal cortex is a critical neuroanatomical hub for controlling motivated behaviours across mammalian species. In addition to intra-cortical connectivity, prefrontal projection neurons innervate subcortical structures that contribute to reward-seeking behaviours, such as the ventral striatum and midline thalamus. While connectivity among these structures contributes to appetitive behaviours, how projection-specific prefrontal neurons encode reward-relevant information to guide reward seeking is unknown. Here we use in vivo two-photon calcium imaging to monitor the activity of dorsomedial prefrontal neurons in mice during an appetitive Pavlovian conditioning task. At the population level, these neurons display diverse activity patterns during the presentation of reward-predictive cues. However, recordings from prefrontal neurons with resolved projection targets reveal that individual corticostriatal neurons show response tuning to reward-predictive cues, such that excitatory cue responses are amplified across learning. By contrast, corticothalamic neurons gradually develop new, primarily inhibitory responses to reward-predictive cues across learning. Furthermore, bidirectional optogenetic manipulation of these neurons reveals that stimulation of corticostriatal neurons promotes conditioned reward-seeking behaviour after learning, while activity in corticothalamic neurons suppresses both the acquisition and expression of conditioned reward seeking. These data show how prefrontal circuitry can dynamically control reward-seeking behaviour through the opposing activities of projection-specific cell populations

Identification of Metabolites in the Normal Ovary and Their Transformation in Primary and Metastatic Ovarian Cancer

In this study, we characterized the metabolome of the human ovary and identified metabolic alternations that coincide with primary epithelial ovarian cancer (EOC) and metastatic tumors resulting from primary ovarian cancer (MOC) using three analytical platforms: gas chromatography mass spectrometry (GC/MS) and liquid chromatography tandem mass spectrometry (LC/MS/MS) using buffer systems and instrument settings to catalog positive or negative ions. The human ovarian metabolome was found to contain 364 biochemicals and upon transformation of the ovary caused changes in energy utilization, altering metabolites associated with glycolysis and β-oxidation of fatty acids—such as carnitine (1.79 fold in EOC, p<0.001; 1.88 fold in MOC, p<0.001), acetylcarnitine (1.75 fold in EOC, p<0.001; 2.39 fold in MOC, p<0.001), and butyrylcarnitine (3.62 fold, p<0.0094 in EOC; 7.88 fold, p<0.001 in MOC). There were also significant changes in phenylalanine catabolism marked by increases in phenylpyruvate (4.21 fold; p = 0.0098) and phenyllactate (195.45 fold; p<0.0023) in EOC. Ovarian cancer also displayed an enhanced oxidative stress response as indicated by increases in 2-aminobutyrate in EOC (1.46 fold, p = 0.0316) and in MOC (2.25 fold, p<0.001) and several isoforms of tocopherols. We have also identified novel metabolites in the ovary, specifically N-acetylasparate and N-acetyl-aspartyl-glutamate, whose role in ovarian physiology has yet to be determined. These data enhance our understanding of the diverse biochemistry of the human ovary and demonstrate metabolic alterations upon transformation. Furthermore, metabolites with significant changes between groups provide insight into biochemical consequences of transformation and are candidate biomarkers of ovarian oncogenesis. Validation studies are warranted to determine whether these compounds have clinical utility in the diagnosis or clinical management of ovarian cancer patients