Can cells solve mazes? Understanding cells responses to wound healing

Wound healing is a complex process that occurs after the body\u27s tissue has been damaged or impaled by a foreign object. Cells must travel from all over the body to the site of injury. The goal of this project is to understand what affects the migration of fibroblast cells in order to develop more effective wound treatments. Our research has aimed to develop a way to map the decision-making processes of fibroblasts that drive their migration to a wound site. We have addressed this by asking the question: can cells solve mazes? Our team has developed several methodologies by which we have been able to study the responsiveness of fibroblasts to certain cues. Specifically the migration of the cells has been tracked relative to physical barriers created by the walls of the maze and chemical concentration gradients. Preliminary results have demonstrated the feasibility of this apparatus for a mode of studying cell proliferation and migration

Neutron recognition in the LAND detector for large neutron multiplicity

The performance of the LAND neutron detector is studied. Using an event-mixing technique based on one-neutron data obtained in the S107 experiment at the GSI laboratory, we test the efficiency of various analytic tools used to determine the multiplicity and kinematic properties of detected neutrons. A new algorithm developed recently for recognizing neutron showers from spectator decays in the ALADIN experiment S254 is described in detail. Its performance is assessed in comparison with other methods. The properties of the observed neutron events are used to estimate the detection efficiency of LAND in this experiment.Comment: 16 pages, 8 figure

The Λp\bf{\Lambda p} interaction studied via femtoscopy in p + Nb reactions at sNN=3.18 GeV\mathbf{\sqrt{s_{NN}}=3.18} ~\mathrm{\bf{GeV}}

We report on the first measurement of $p\Lambda$ and $pp$ correlations via the femtoscopy method in p+Nb reactions at $\mathrm{\sqrt{s_{NN}}=3.18} ~\mathrm{GeV}$, studied with the High Acceptance Di-Electron Spectrometer (HADES). By comparing the experimental correlation function to model calculations, a source size for $pp$ pairs of $r_{0,pp}=2.02 \pm 0.01(\mathrm{stat})^{+0.11}_{-0.12} (\mathrm{sys}) ~\mathrm{fm}$ and a slightly smaller value for $p\Lambda$ of $r_{0,\Lambda p}=1.62 \pm 0.02(\mathrm{stat})^{+0.19}_{-0.08}(\mathrm{sys}) ~\mathrm{fm}$ is extracted. Using the geometrical extent of the particle emitting region, determined experimentally with $pp$ correlations as reference together with a source function from a transport model, it is possible to study different sets of scattering parameters. The $p\Lambda$ correlation is proven sensitive to predicted scattering length values from chiral effective field theory. We demonstrate that the femtoscopy technique can be used as valid alternative to the analysis of scattering data to study the hyperon-nucleon interaction.Comment: 12 pages, 11 figure

The High-Acceptance Dielectron Spectrometer HADES

HADES is a versatile magnetic spectrometer aimed at studying dielectron production in pion, proton and heavy-ion induced collisions. Its main features include a ring imaging gas Cherenkov detector for electron-hadron discrimination, a tracking system consisting of a set of 6 superconducting coils producing a toroidal field and drift chambers and a multiplicity and electron trigger array for additional electron-hadron discrimination and event characterization. A two-stage trigger system enhances events containing electrons. The physics program is focused on the investigation of hadron properties in nuclei and in the hot and dense hadronic matter. The detector system is characterized by an 85% azimuthal coverage over a polar angle interval from 18 to 85 degree, a single electron efficiency of 50% and a vector meson mass resolution of 2.5%. Identification of pions, kaons and protons is achieved combining time-of-flight and energy loss measurements over a large momentum range. This paper describes the main features and the performance of the detector system

Strange hadron production at SIS energies: an update from HADES

We present and discuss recent experimental activities of the HADES collaboration on open and hidden strangeness production close or below the elementary NN threshold. Special emphasis is put on the feed-down from ϕ mesons to antikaons, the presence of the Ξ(-) excess in cold nuclear matter and the comparison of statistical model rates to elementary p+p data. The implications for the interpretation of heavy-ion data are discussed as well

Impact of the Coulomb field on charged-pion spectra in few-GeV heavy-ion collisions

In nuclear collisions the incident protons generate a Coulomb field which acts on produced charged particles. The impact of these interactions on charged-pion transverse-mass and rapidity spectra, as well as on pion–pion momentum correlations is investigated in Au + Au collisions at $\sqrt{^{S}NN}$ = 2.4 GeV. We show that the low-m$_{t}$ region (m$_{t}$ < 0.2 GeV / c$^{2}$) can be well described with a Coulomb-modified Boltzmann distribution that also takes changes of the Coulomb field during the expansion of the fireball into account. The observed centrality dependence of the fitted mean Coulomb potential energy deviates strongly from a $A_{part}^{2/3}$ scaling, indicating that, next to the fireball, the non-interacting charged spectators have to be taken into account. For the most central collisions, the Coulomb modifications of the HBT source radii are found to be consistent with the potential extracted from the single-pion transverse-mass distributions. This finding suggests that the region of homogeneity obtained from two-pion correlations coincides with the region in which the pions freeze-out. Using the inferred mean-square radius of the charge distribution at freeze-out, we have deduced a baryon density, in fair agreement with values obtained from statistical hadronization model fits to the particle yields

Study of e+,e− production in elementary and nuclear collisions near the production threshold with HADES

HADES is a second generation experiment designed to study dielectron production in proton, pion, and heavy ion induced reactions at the GSI accelerator facility in Darmstadt. The physics programme of HADES is focused on in-medium properties of the light vector mesons. In this contribution we present status of the HADES experiment, demonstrate its capability to identify rare dielectron signal, show first experimental results obtained from C+C reactions at 2 A GeV and shortly discuss physics programme of up-coming experimental runs. © 2004 Elsevier B.V. All rights reserved. 53 1 49 58 Cited By :1

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10−8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10−7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10−6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10−5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.</p

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10−8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10−7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10−6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10−5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.</p