176 research outputs found
A comparative study of Gaussian Graphical Model approaches for genomic data
The inference of networks of dependencies by Gaussian Graphical models on
high-throughput data is an open issue in modern molecular biology. In this
paper we provide a comparative study of three methods to obtain small sample
and high dimension estimates of partial correlation coefficients: the
Moore-Penrose pseudoinverse (PINV), residual correlation (RCM) and
covariance-regularized method . We first compare them on simulated
datasets and we find that PINV is less stable in terms of AUC performance when
the number of variables changes. The two regularized methods have comparable
performances but is much faster than RCM. Finally, we present the
results of an application of for the inference of a gene network
for isoprenoid biosynthesis pathways in Arabidopsis thaliana.Comment: 7 pages, 1 figure, RevTex4, version to appear in the proceedings of
1st International Workshop on Pattern Recognition, Proteomics, Structural
Biology and Bioinformatics: PR PS BB 2011, Ravenna, Italy, 13 September 201
Caspase-independent programmed cell death triggers Ca2PO4 deposition in an in vitro model of nephrocalcinosis
We provide evidence of caspase-independent cell death triggering the calcification process in GDNF-silenced HK-2 cells
Cooling of a Compact Star with a LOFF Matter Core
Specific heat and neutrino emissivity due to direct URCA processes for quark
matter in the color superconductive Larkin-Ovchinnikov-Fulde-Ferrell (LOFF)
phase of Quantum-Chromodynamics have been evaluated. The cooling rate of
simplified models of compact stars with a LOFF matter core is estimated.Comment: 3 pages, 1 figure, to appear in the proceedings of the Helmoltz
International Summer School of Theoretical Physics on Dense Matter in Heavy
Ion Collisions and Astrophysics, JINR, Dubna, Russia, 21 Aug - 1 Sep 200
An Experimental Validation of Phase-Based Motion Magnification for Structures with Developing Cracks and Time-Varying Configurations
In this study, Computer Vision and Phase-Based Motion Magnification (PBMM) are validated for continuous Structural Health Monitoring (SHM) purposes. The aim is to identify the exact instant of occurrence for damage or abrupt structural changes from video-extracted, very low amplitude (barely visible) vibrations. The study presents three experimental datasets: a box beam with multiple saw cuts of different lengths and angles, a beam with a full rectangular cross section and a mass added at the tip, and the spar of a prototype High-Aspect-Ratio wing. Both mode-shape- and frequency-based approaches are considered, showing the potential to identify the severity and position of the damage as well A high-definition, high-speed camera and a low-cost commercial alternative have been successfully utilised for these video acquisitions. Finally, the technique is also preliminarily tested for outdoor applications with smartphone cameras
Chiral crossover, deconfinement and quarkyonic matter within a Nambu-Jona Lasinio model with the Polyakov loop
We study the interplay between the chiral and the deconfinement transitions,
both at high temperature and high quark chemical potential, by a non local
Nambu-Jona Lasinio model with the Polyakov loop in the mean field approximation
and requiring neutrality of the ground state. We consider three forms of the
effective potential of the Polyakov loop: two of them with a fixed
deconfinement scale, cases I and II, and the third one with a dependent
scale, case III. In the cases I and II, at high chemical potential and
low temperature the main contribution to the free energy is due to the
Z(3)-neutral three-quark states, mimicking the quarkyonic phase of the large
phase diagram. On the other hand in the case III the quarkyonic window is
shrunk to a small region. Finally we comment on the relations of these results
to lattice studies and on possible common prospects. We also briefly comment on
the coexistence of quarkyonic and color superconductive phases.Comment: 16 pages, 7 figures, RevTeX4. Some typos corrected, references adde
A comparative study of covariance selection models for the inference of gene regulatory networks
Display Omitted Three different models for inferring gene networks from microarray data are proposed.The most sensitive approach is selected by an exhaustive simulation study.The method reveals a cross-talk between the isoprenoid biosynthesis pathways in Arabidopsis thaliana.The method highlights 9 genes in HRAS signature regulated by the transcription factor RREB1. MotivationThe inference, or 'reverse-engineering', of gene regulatory networks from expression data and the description of the complex dependency structures among genes are open issues in modern molecular biology. ResultsIn this paper we compared three regularized methods of covariance selection for the inference of gene regulatory networks, developed to circumvent the problems raising when the number of observations n is smaller than the number of genes p. The examined approaches provided three alternative estimates of the inverse covariance matrix: (a) the 'PINV' method is based on the Moore-Penrose pseudoinverse, (b) the 'RCM' method performs correlation between regression residuals and (c) '?2C' method maximizes a properly regularized log-likelihood function. Our extensive simulation studies showed that ?2C outperformed the other two methods having the most predictive partial correlation estimates and the highest values of sensitivity to infer conditional dependencies between genes even when a few number of observations was available. The application of this method for inferring gene networks of the isoprenoid biosynthesis pathways in Arabidopsis thaliana allowed to enlighten a negative partial correlation coefficient between the two hubs in the two isoprenoid pathways and, more importantly, provided an evidence of cross-talk between genes in the plastidial and the cytosolic pathways. When applied to gene expression data relative to a signature of HRAS oncogene in human cell cultures, the method revealed 9 genes (p-value<0.0005) directly interacting with HRAS, sharing the same Ras-responsive binding site for the transcription factor RREB1. This result suggests that the transcriptional activation of these genes is mediated by a common transcription factor downstream of Ras signaling. AvailabilitySoftware implementing the methods in the form of Matlab scripts are available at: http://users.ba.cnr.it/issia/iesina18/CovSelModelsCodes.zip
Bulk viscosity in 2SC quark matter
The bulk viscosity of three-flavor color-superconducting quark matter
originating from the nonleptonic process u+s u+d is computed. It is assumed
that up and down quarks form Cooper pairs while the strange quark remains
unpaired (2SC phase). A general derivation of the rate of strangeness
production is presented, involving contributions from a multitude of different
subprocesses, including subprocesses that involve different numbers of gapped
quarks as well as creation and annihilation of particles in the condensate. The
rate is then used to compute the bulk viscosity as a function of the
temperature, for an external oscillation frequency typical of a compact star
r-mode. We find that, for temperatures far below the critical temperature T_c
for 2SC pairing, the bulk viscosity of color-superconducting quark matter is
suppressed relative to that of unpaired quark matter, but for T >~ 10^(-3) T_c
the color-superconducting quark matter has a higher bulk viscosity. This is
potentially relevant for the suppression of r-mode instabilities early in the
life of a compact star.Comment: 18 pages + appendices (28 pages total), 8 figures; v3: corrected
numerical error in the plots; 2SC bulk viscosity is now larger than unpaired
bulk viscosity in a wider temperature rang
PET/MR in recurrent glioblastoma patients treated with regorafenib: [18F]FET and DWI-ADC for response assessment and survival prediction
Objective: The use of regorafenib in recurrent glioblastoma patients has been recently approved by the Italian Medicines Agency (AIFA) and added to the National Comprehensive Cancer Network (NCCN) 2020 guidelines as a preferred regimen. Given its complex effects at the molecular level, the most appropriate imaging tools to assess early response to treatment is still a matter of debate. Diffusion-weighted imaging and O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography ([18F]FET PET) are promising methodologies providing additional information to the currently used RANO criteria. The aim of this study was to evaluate the variations in diffusion-weighted imaging/apparent diffusion coefficient (ADC) and [18F]FET PET-derived parameters in patients who underwent PET/MR at both baseline and after starting regorafenib. Methods: We retrospectively reviewed 16 consecutive GBM patients who underwent [18F]FET PET/MR before and after two cycles of regorafenib. Patients were sorted into stable (SD) or progressive disease (PD) categories in accordance with RANO criteria. We were also able to analyze four SD patients who underwent a third PET/MR after another four cycles of regorafenib. [18F]FET uptake greater than 1.6 times the mean background activity was used to define an area to be superimposed on an ADC map at baseline and after treatment. Several metrics were then derived and compared. Log-rank test was applied for overall survival analysis. Results: Percentage difference in FET volumes correlates with the corresponding percentage difference in ADC (R = 0.54). Patients with a twofold increase in FET after regorafenib showed a significantly higher increase in ADC pathological volume than the remaining subjects (p = 0.0023). Kaplan-Meier analysis, performed to compare the performance in overall survival prediction, revealed that the percentage variations of FET- and ADC-derived metrics performed at least as well as RANO criteria (p = 0.02, p = 0.024 and p = 0.04 respectively) and in some cases even better. TBR Max and TBR mean are not able to accurately predict overall survival. Conclusion In recurrent glioblastoma patients treated with regorafenib, [18F]FET and ADC metrics, are able to predict overall survival and being obtained from completely different measures as compared to RANO, could serve as semi-quantitative independent biomarkers of response to treatment. Advances in knowledge Simultaneous evaluation of [18F]FET and ADC metrics using PET/MR allows an early and reliable identification of response to treatment and predict overall survival
Addressing the need for standardization of test methods for self-healing concrete: an inter-laboratory study on concrete with macrocapsules.
Development and commercialization of self-healing concrete is hampered due to a lack of standardized test methods. Six inter-laboratory testing programs are being executed by the EU COST action SARCOS, each focusing on test methods for a specific self-healing technique. This paper reports on the comparison of tests for mortar and concrete specimens with polyurethane encapsulated in glass macrocapsules. First, the pre-cracking method was analysed: mortar specimens were cracked in a three-point bending test followed by an active crack width control technique to restrain the crack width up to a predefined value, while the concrete specimens were cracked in a three-point bending setup with a displacement-controlled loading system. Microscopic measurements showed that with the application of the active control technique almost all crack widths were within a narrow predefined range. Conversely, for the concrete specimens the variation on the crack width was higher. After pre-cracking, the self-healing effect was characterized via durability tests: the mortar specimens were tested in a water permeability test and the spread of the healing agent on the crack surfaces was determined, while the concrete specimens were subjected to two capillary water absorption tests, executed with a different type of waterproofing applied on the zone around the crack. The quality of the waterproofing was found to be important, as different results were obtained in each absorption test. For the permeability test, 4 out of 6 labs obtained a comparable flow rate for the reference specimens, yet all 6 labs obtained comparable sealing efficiencies, highlighting the potential for further standardization
Strongly Correlated Quantum Fluids: Ultracold Quantum Gases, Quantum Chromodynamic Plasmas, and Holographic Duality
Strongly correlated quantum fluids are phases of matter that are
intrinsically quantum mechanical, and that do not have a simple description in
terms of weakly interacting quasi-particles. Two systems that have recently
attracted a great deal of interest are the quark-gluon plasma, a plasma of
strongly interacting quarks and gluons produced in relativistic heavy ion
collisions, and ultracold atomic Fermi gases, very dilute clouds of atomic
gases confined in optical or magnetic traps. These systems differ by more than
20 orders of magnitude in temperature, but they were shown to exhibit very
similar hydrodynamic flow. In particular, both fluids exhibit a robustly low
shear viscosity to entropy density ratio which is characteristic of quantum
fluids described by holographic duality, a mapping from strongly correlated
quantum field theories to weakly curved higher dimensional classical gravity.
This review explores the connection between these fields, and it also serves as
an introduction to the Focus Issue of New Journal of Physics on Strongly
Correlated Quantum Fluids: from Ultracold Quantum Gases to QCD Plasmas. The
presentation is made accessible to the general physics reader and includes
discussions of the latest research developments in all three areas.Comment: 138 pages, 25 figures, review associated with New Journal of Physics
special issue "Focus on Strongly Correlated Quantum Fluids: from Ultracold
Quantum Gases to QCD Plasmas"
(http://iopscience.iop.org/1367-2630/focus/Focus%20on%20Strongly%20Correlated%20Quantum%20Fluids%20-%20from%20Ultracold%20Quantum%20Gases%20to%20QCD%20Plasmas
- …