Platelet-derived growth factor-B gene delivery sustains gingival fibroblast signal transduction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65871/1/j.1600-0765.2008.01089.x.pd

A survey on independence-based Markov networks learning

This work reports the most relevant technical aspects in the problem of learning the \emph{Markov network structure} from data. Such problem has become increasingly important in machine learning, and many other application fields of machine learning. Markov networks, together with Bayesian networks, are probabilistic graphical models, a widely used formalism for handling probability distributions in intelligent systems. Learning graphical models from data have been extensively applied for the case of Bayesian networks, but for Markov networks learning it is not tractable in practice. However, this situation is changing with time, given the exponential growth of computers capacity, the plethora of available digital data, and the researching on new learning technologies. This work stresses on a technology called independence-based learning, which allows the learning of the independence structure of those networks from data in an efficient and sound manner, whenever the dataset is sufficiently large, and data is a representative sampling of the target distribution. In the analysis of such technology, this work surveys the current state-of-the-art algorithms for learning Markov networks structure, discussing its current limitations, and proposing a series of open problems where future works may produce some advances in the area in terms of quality and efficiency. The paper concludes by opening a discussion about how to develop a general formalism for improving the quality of the structures learned, when data is scarce.Comment: 35 pages, 1 figur

Biphoton generation in quadratic waveguide arrays: A classical optical simulation

Quantum entanglement, the non-separability of a multipartite wave function, became essential in understanding the non-locality of quantum mechanics. In optics, this non-locality can be demonstrated on impressively large length scales, as photons travel with the speed of light and interact only weakly with their environment. With the discovery of spontaneous parametric down-conversion (SPDC) in nonlinear crystals, an efficient source for entangled photon pairs, so-called biphotons, became available. It has recently been shown that SPDC can also be implemented in nonlinear arrays of evanescently coupled waveguides which allows the generation and the investigation of correlated quantum walks of such biphotons in an integrated device. Here, we analytically and experimentally demonstrate that the biphoton degrees of freedom are entailed in an additional spatial dimension, therefore the SPDC and the subsequent quantum random walk in one-dimensional (1D) arrays can be simulated through classical optical beam propagation in a two-dimensional (2D) photonic lattice. Thereby, the output intensity images directly represent the biphoton correlations and exhibit a clear violation of a Bell-type inequality

Predicting disease-associated substitution of a single amino acid by analyzing residue interactions

<p>Abstract</p> <p>Background</p> <p>The rapid accumulation of data on non-synonymous single nucleotide polymorphisms (nsSNPs, also called SAPs) should allow us to further our understanding of the underlying disease-associated mechanisms. Here, we use complex networks to study the role of an amino acid in both local and global structures and determine the extent to which disease-associated and polymorphic SAPs differ in terms of their interactions to other residues.</p> <p>Results</p> <p>We found that SAPs can be well characterized by network topological features. Mutations are probably disease-associated when they occur at a site with a high centrality value and/or high degree value in a protein structure network. We also discovered that study of the neighboring residues around a mutation site can help to determine whether the mutation is disease-related or not. We compiled a dataset from the Swiss-Prot variant pages and constructed a model to predict disease-associated SAPs based on the random forest algorithm. The values of total accuracy and MCC were 83.0% and 0.64, respectively, as determined by 5-fold cross-validation. With an independent dataset, our model achieved a total accuracy of 80.8% and MCC of 0.59, respectively.</p> <p>Conclusions</p> <p>The satisfactory performance suggests that network topological features can be used as quantification measures to determine the importance of a site on a protein, and this approach can complement existing methods for prediction of disease-associated SAPs. Moreover, the use of this method in SAP studies would help to determine the underlying linkage between SAPs and diseases through extensive investigation of mutual interactions between residues.</p

Up-regulation of bone marrow stromal protein 2 (BST2) in breast cancer with bone metastasis

<p>Abstract</p> <p>Background</p> <p>Bone metastases are frequent complications of breast cancer. Recent literature implicates multiple chemokines in the formation of bone metastases in breast cancer. However, the molecular mechanism of metastatic bone disease in breast cancer remains unknown. We have recently made the novel observation of the BST2 protein expression in human breast cancer cell lines. The purpose of our present study is to investigate the expression and the role of BST2 in bone metastatic breast cancer.</p> <p>Methods</p> <p>cDNA microarray analysis was used to compare the BST2 gene expression between a metastatic to bone human breast cancer cell line (MDA-231BO) and a primary human breast cancer cell line (MDA-231). The BST2 expression in one bone metastatic breast cancer and seven non-bone metastatic breast cancer cell lines were also determined using real-time RT-PCR and Western blot assays. We then employed tissue array to further study the BST2 expression in human breast cancer using array slides containing 20 independent breast cancer tumors that formed metastatic bone lesions, 30 non-metastasis-forming breast cancer tumors, and 8 normal breast tissues. In order to test the feasibility of utilizing BST2 as a serum marker for the presence of bone metastasis in breast cancer, we had measured the BST2 expression levels in human serums by using ELISA on 43 breast cancer patients with bone metastasis, 43 breast cancer patients without bone metastasis, and 14 normal healthy controls. The relationship between cell migration and proliferation and BST2 expression was also studied in a human breast recombinant model system using migration and FACS analysis.</p> <p>Results</p> <p>The microarray demonstrated over expression of the BST2 gene in the bone metastatic breast cancer cell line (MDA-231BO) compared to the primary human breast cancer cell line (MDA-231). The expression of the BST2 gene was significantly increased in the bone metastatic breast cancer cell lines and tumor tissues compared to non-bone metastatic breast cancer cell lines and tumor tissues by real time RT-PCR, Western blot and TMA. Furthermore, serum levels of BST2 measured by ELISA were also significantly higher among patients with breast cancer metastatic to bone compared to breast cancer patients without metastatic to bone (P < .0001). Most importantly, the breast cancer cell line that transfected with BST2 demonstrated increased BST2 expressions, which was associated with increased cancer cell migration and cell proliferation.</p> <p>Conclusion</p> <p>These results provide novel data indicating the BST2 protein expression is associated with the formation of bone metastases in human breast cancer. We believe that BST2 may be a potential biomarker in breast cancer with bone metastasis.</p

Tyrosine kinase signalling in breast cancer: Epidermal growth factor receptor and c-Src interactions in breast cancer

Both the non-receptor tyrosine kinase, c-Src, and members of the epidermal growth factor (EGF) receptor family are overexpressed in high percentages of human breast cancers. Because these molecules are plasma membrane-associated and involved in mitogenesis, it has been speculated that they function in concert with one another to promote breast cancer development and progression. Evidence to date supports a model wherein c-Src potentiates the survival, proliferation and tumorigenesis of EGF receptor family members, in part by associating with them. Phosphorylation of the EGF receptor by c-SRC is also critical for mitogenic signaling initiated by the EGF receptor itself, as well as by several G-protein coupled receptors (GPCRs), a cytokine receptor, and the estrogen receptor. Thus, c-Src appears to have pleiotropic effects on cancer cells by modulating the action of multiple growth-promoting receptors

Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron

We study the underlying event in proton-antiproton collisions by examining the behavior of charged particles (transverse momentum pT > 0.5 GeV/c, pseudorapidity |\eta| < 1) produced in association with large transverse momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan production) or the leading jet (in high-pT jet production) in each event to define three regions of \eta-\phi space; toward, away, and transverse, where \phi is the azimuthal scattering angle. For Drell-Yan production (excluding the leptons) both the toward and transverse regions are very sensitive to the underlying event. In high-pT jet production the transverse region is very sensitive to the underlying event and is separated into a MAX and MIN transverse region, which helps separate the hard component (initial and final-state radiation) from the beam-beam remnant and multiple parton interaction components of the scattering. The data are corrected to the particle level to remove detector effects and are then compared with several QCD Monte-Carlo models. The goal of this analysis is to provide data that can be used to test and improve the QCD Monte-Carlo models of the underlying event that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.

Top Quark Mass Measurement from Dilepton Events at CDF II with the Matrix-Element Method

We describe a measurement of the top quark mass using events with two charged leptons collected by the CDF II detector from $p\bar{p}$ collisions with $\sqrt s = 1.96$ TeV at the Fermilab Tevatron. The likelihood in top mass is calculated for each event by convoluting the leading order matrix element describing $q\bar{q} \to t\bar{t} \to b\ell\nu_{\ell}\bar{b}\ell'\nu_{\ell'}$ with detector resolution functions. The presence of background events in the data sample is modeled using similar calculations involving the matrix elements for major background processes. In a data sample with integrated luminosity of 340 pb$^{-1}$, we observe 33 candidate events and measure $M_{top} = 165.2 \pm 6.1(\textrm{stat.}) \pm 3.4(\textrm{syst.}) \mathrm{~GeV}/c^2.$ This measurement represents the first application of this method to events with two charged leptons and is the most precise single measurement of the top quark mass in this channel.Comment: 21 pages, 14 figure

Search for New Physics in Lepton + Photon + X Events with L=305 pb-1 of ppbar Collisions at roots=1.96 TeV

We present results of a search for anomalous production of events containing a charged lepton (either electron or muon) and a photon, both with high transverse momentum, accompanied by additional signatures, X, including missing transverse energy (MET) and additional leptons and photons. We use the same kinematic selection criteria as in a previous CDF search, but with a substantially larger data set, 305 pb-1, a ppbar collision energy of 1.96 TeV, and the upgraded CDF II detector. We find 42 Lepton+Photon+MET events versus a standard model expectation of 37.3 +- 5.4 events. The level of excess observed in Run I, 16 events with an expectation of 7.6 +- 0.7 events (corresponding to a 2.7 sigma effect), is not supported by the new data. In the signature of Multi-Lepton+Photon+X we observe 31 events versus an expectation of 23.0 +- 2.7 events. In this sample we find no events with an extra photon or MET and so find no events like the one ee+gg+MET event observed in Run I.Comment: 7 pages, 3 figures, 1 table. Accepted to PR

Measurement of the B0 anti-B0 oscillation frequency using l- D*+ pairs and lepton flavor tags

The oscillation frequency Delta-md of B0 anti-B0 mixing is measured using the partially reconstructed semileptonic decay anti-B0 -> l- nubar D*+ X. The data sample was collected with the CDF detector at the Fermilab Tevatron collider during 1992 - 1995 by triggering on the existence of two lepton candidates in an event, and corresponds to about 110 pb-1 of pbar p collisions at sqrt(s) = 1.8 TeV. We estimate the proper decay time of the anti-B0 meson from the measured decay length and reconstructed momentum of the l- D*+ system. The charge of the lepton in the final state identifies the flavor of the anti-B0 meson at its decay. The second lepton in the event is used to infer the flavor of the anti-B0 meson at production. We measure the oscillation frequency to be Delta-md = 0.516 +/- 0.099 +0.029 -0.035 ps-1, where the first uncertainty is statistical and the second is systematic.Comment: 30 pages, 7 figures. Submitted to Physical Review