ρ(770)0\rho(770)^0, K∗(892)0^*(892)^0 and f0(980)_{0}(980) Production in Au-Au and pp Collisions at sNN\sqrt{s_{NN}} = 200 GeV

Preliminary results on $\rho(770)^0 \to \pi^{+}\pi^{-}$, K$^{*}(892)^{0} \to \pi$K and $f_{0}(980) \to \pi^{+}\pi^{-}$ production using the mixed-event technique are presented. The measurements are performed at mid-rapidity by the STAR detector in $\sqrt{s_{NN}}$= 200 GeV Au-Au and pp interactions at RHIC. The results are compared to different measurements at various energies.Comment: 4 pages, 6 figures. Talk presented at Quark Matter 2002, Nantes, France, July 18-24, 2002. To appear in the proceedings (Nucl. Phys. A

Resonance Production

Recent results on rho(770)^0, K(892)^*0, f_0(980), phi(1020), Delta(1232)^++, and Lambda(1520) production in A+A and p+p collisions at SPS and RHIC energies are presented. These resonances are measured via their hadronic decay channels and used as a sensitive tool to examine the collision dynamics in the hadronic medium through their decay and regeneration. The modification of resonance mass, width, and shape due to phase space and dynamical effects are discussed.Comment: 8 pages, 10 figures, proceedings of the Quark Matter 2004, in Oakland, California, to be published in Journal of Physics G: Nuclear and Particle Physic

Lambda Polarization in Polarized Proton-Proton Collisions at RHIC

We discuss Lambda polarization in semi-inclusive proton-proton collisions, with one of the protons longitudinally polarized. The hyperfine interaction responsible for the $\Delta$-$N$ and $\Sigma$-$\Lambda$ mass splittings gives rise to flavor asymmetric fragmentation functions and to sizable polarized non-strange fragmentation functions. We predict large positive Lambda polarization in polarized proton-proton collisions at large rapidities of the produced Lambda, while other models, based on SU(3) flavor symmetric fragmentation functions, predict zero or negative Lambda polarization. The effect of $\Sigma^0$ and $\Sigma^*$ decays is also discussed. Forthcoming experiments at RHIC will be able to differentiate between these predictions.Comment: 18 pages, 5 figure

Understanding uncertainty in temperature effects on vector-borne disease: A Bayesian approach

Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases, like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number $R_0$. However, understanding the mechanisms linking $R_0$ and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this we show how a Bayesian approach can help identify critical uncertainties in components of $R_0$ and how this uncertainty is propagated into the estimate of $R_0$. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15-25$^\circ$ C; fecundity across all temperatures, but especially $\sim$25-32$^\circ$ C; mortality from 20-30$^\circ$ C; parasite development rate at $\sim$15-16$^\circ$C and again at $\sim$33-35$^\circ$C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of $R_0$. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.Comment: 27 pages, including 1 table and 3 figure

Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability

Habitat of endangered white abalone, Haliotis sorenseni.

Abstract Surveys with a submersible at offshore islands and banks in southern California found that white abalone were most abundant at depths between 43 and 60 m. This is deeper than estimates taken when white abalone were more abundant. Densities were highest at sites far from fishing ports. Controlling for depth and site found that white abalone were significantly more abundant in areas with Laminaria farlowii (an alga) but abalone were not associated with areas high in the cover of other algae (Pelagophycus porra or Eisenia arborea) or the amount of sand in the habitat (except that abalone always occurred on rock). Within an area with abalone, the particular rock they occurred on was significantly larger than unoccupied neighboring rocks. Occupied rocks were not significantly different in algal cover or in sea urchin density than unoccupied neighboring rocks. The position of abalone on a rock was nearer to the rock-sand interface than would be expected based on a random distribution. More white abalone were feeding when in association with red urchins, perhaps because both grazers capture drift algae to eat. These data may aid future efforts to locate white abalone brood stock and identify locations for outplanting.

Inference algorithms for gene networks: a statistical mechanics analysis

The inference of gene regulatory networks from high throughput gene expression data is one of the major challenges in systems biology. This paper aims at analysing and comparing two different algorithmic approaches. The first approach uses pairwise correlations between regulated and regulating genes; the second one uses message-passing techniques for inferring activating and inhibiting regulatory interactions. The performance of these two algorithms can be analysed theoretically on well-defined test sets, using tools from the statistical physics of disordered systems like the replica method. We find that the second algorithm outperforms the first one since it takes into account collective effects of multiple regulators

Evaluation of MPA designs that protect highly mobile megafauna now and under climate change scenarios

Marine protected area (MPA) designs, including large-scale MPAs (LSMPAs; \u3e150,000 km2), mobile MPAs (fluid spatiotemporal boundaries), and MPA networks, may offer different benefits to species and could enhance protection by encompassing spatiotemporal scales of animal movement. We sought to understand how well LSMPAs could benefit nine highly-mobile marine species in the tropics now and into the future by: 1) evaluating current range overlap within a LSMPA; 2) evaluating range overlap under climate change projections; and 3) evaluating how well theoretical MPA designs benefit these nine species. We focused on Palmyra Atoll and Kingman Reef, a 2000 km2 area within the 1.2 million km2 U.S. Pacific Remote Islands Marine National Monument (PRIMNM) that contains marine megafauna (reef and pelagic fishes; sea turtles; seabirds; cetaceans) reflecting different behaviors and habitat use. Our approach is useful for evaluating the effectiveness of the Palmyra-Kingman MPA and PRIMNM in protecting these species, and tropical LSMPAs in general, and for informing future MPA design. Stationary MPAs provided protection at varying scales. Reef manta rays (Mobula alfredi), grey reef sharks (Carcharhinus amblyrhynchos), green sea turtles (Chelonia mydas), and bottlenose dolphins (Tursiops truncatus) had overall small ranges (\u3c100 km from Palmyra-Kingman) and could benefit from stationary MPAs that contained heterogenous reef habitats. Yellowfin tuna (Thunnus albacares), sooty terns (Onychoprion fuscatus), red-footed boobies (Sula sula), great frigatebirds (Fregata minor), and melon-headed whales (Peponocephala electra) navigated complex oceanographic processes and may benefit most from mobile MPAs that shift with features including thermal fronts, cyclic regions of elevated productivity, and eddies, if relationships with these features are established and predictable. All species had capacity to travel to nearby reef systems, illustrating potential benefits of MPA networks and protected corridors. Suitable habitats will likely contract for all species as warm water expands under climate change scenarios (species habitats were predicted to decrease by 4–49% at Palmyra-Kingman) and MPAs may not protect suitable habitats into the future. Species habitat requirements and movement ecologies are critical aspects of marine spatial planning, especially with respect to dynamic ocean processes and a changing climate