Gene expression profiling reveals different pathways related to Abl and other genes that cooperate with c-Myc in a model of plasma cell neoplasia

<p>Abstract</p> <p>Background</p> <p>To elucidate the genes involved in the neoplastic transformation of B cells, global gene expression profiles were generated using Affymetrix U74Av2 microarrays, containing 12,488 genes, for four different groups of mouse B-cell lymphomas and six subtypes of pristane-induced mouse plasma cell tumors, three of which developed much earlier than the others.</p> <p>Results</p> <p>Unsupervised hierarchical cluster analysis exhibited two main sub-clusters of samples: a B-cell lymphoma cluster and a plasma cell tumor cluster with subclusters reflecting mechanism of induction. This report represents the first step in using global gene expression to investigate molecular signatures related to the role of cooperating oncogenes in a model of Myc-induced carcinogenesis. Within a single subgroup, e.g., ABPCs, plasma cell tumors that contained typical T(12;15) chromosomal translocations did not display gene expression patterns distinct from those with variant T(6;15) translocations, in which the breakpoint was in the <it>Pvt-1 </it>locus, 230 kb 3' of c-<it>Myc</it>, suggesting that c-<it>Myc </it>activation was the initiating factor in both. When integrated with previously published Affymetrix array data from human multiple myelomas, the IL-6-transgenic subset of mouse plasma cell tumors clustered more closely with MM1 subsets of human myelomas, slow-appearing plasma cell tumors clustered together with MM2, while plasma cell tumors accelerated by v-Abl clustered with the more aggressive MM3-MM4 myeloma subsets. Slow-appearing plasma cell tumors expressed <it>Socs1 </it>and <it>Socs2 </it>but v-<it>Abl</it>-accelerated plasma cell tumors expressed 4–5 times as much. Both v-<it>Abl</it>-accelerated and non-v-<it>Ab</it>l-associated tumors exhibited phosphorylated STAT 1 and 3, but only v-Abl-accelerated plasma cell tumors lost viability and STAT 1 and 3 phosphorylation when cultured in the presence of the v-Abl kinase inhibitor, STI-571. These data suggest that the Jak/Stat pathway was critical in the transformation acceleration by v-Abl and that v-Abl activity remained essential throughout the life of the tumors, not just in their acceleration. A different pathway appears to predominate in the more slowly arising plasma cell tumors.</p> <p>Conclusion</p> <p>Gene expression profiling differentiates not only B-cell lymphomas from plasma cell tumors but also distinguishes slow from accelerated plasma cell tumors. These data and those obtained from the sensitivity of v-Abl-accelerated plasma cell tumors and their phosphorylated STAT proteins indicate that these similar tumors utilize different signaling pathways but share a common initiating genetic lesion, a c-<it>Myc</it>-activating chromosome translocation.</p

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models

Evolutionary relationships between Rhynchosporium lolii sp. nov. and other Rhynchosporium species on grass.

Copyright: 2013 King et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedThe fungal genus Rhynchosporium (causative agent of leaf blotch) contains several host-specialised species, including R. commune (colonising barley and brome-grass), R. agropyri (couch-grass), R. secalis (rye and triticale) and the more distantly related R. orthosporum (cocksfoot). This study used molecular fingerprinting, multilocus DNA sequence data, conidial morphology, host range tests and scanning electron microscopy to investigate the relationship between Rhynchosporium species on ryegrasses, both economically important forage grasses and common wild grasses in many cereal growing areas, and other plant species. Two different types of Rhynchosporium were found on ryegrasses in the UK. Firstly, there were isolates of R. commune that were pathogenic to both barley and Italian ryegrass. Secondly, there were isolates of a new species, here named R. lolii, that were pathogenic only to ryegrass species. R. lolii was most closely related to R. orthosporum, but exhibited clear molecular, morphological and host range differences. The species was estimated to have diverged from R. orthosporum ca. 5735 years before the present. The colonisation strategy of all of the different Rhynchosporium species involved extensive hyphal growth in the sub-cuticular regions of the leaves. Finally, new species-specific PCR diagnostic tests were developed that could distinguish between these five closely related Rhynchosporium species.Peer reviewedFinal Published versio

The All-Data-Based Evolutionary Hypothesis of Ciliated Protists with a Revised Classification of the Phylum Ciliophora (Eukaryota, Alveolata)

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The file attached is the published version of the article

Multi-level evidence of an allelic hierarchy of USH2A variants in hearing, auditory processing and speech/language outcomes.

Language development builds upon a complex network of interacting subservient systems. It therefore follows that variations in, and subclinical disruptions of, these systems may have secondary effects on emergent language. In this paper, we consider the relationship between genetic variants, hearing, auditory processing and language development. We employ whole genome sequencing in a discovery family to target association and gene x environment interaction analyses in two large population cohorts; the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK10K. These investigations indicate that USH2A variants are associated with altered low-frequency sound perception which, in turn, increases the risk of developmental language disorder. We further show that Ush2a heterozygote mice have low-level hearing impairments, persistent higher-order acoustic processing deficits and altered vocalizations. These findings provide new insights into the complexity of genetic mechanisms serving language development and disorders and the relationships between developmental auditory and neural systems

Optimal In Silico Target Gene Deletion through Nonlinear Programming for Genetic Engineering

Optimal selection of multiple regulatory genes, known as targets, for deletion to enhance or suppress the activities of downstream genes or metabolites is an important problem in genetic engineering. Such problems become more feasible to address in silico due to the availability of more realistic dynamical system models of gene regulatory and metabolic networks. The goal of the computational problem is to search for a subset of genes to knock out so that the activity of a downstream gene or a metabolite is optimized.Based on discrete dynamical system modeling of gene regulatory networks, an integer programming problem is formulated for the optimal in silico target gene deletion problem. In the first result, the integer programming problem is proved to be NP-hard and equivalent to a nonlinear programming problem. In the second result, a heuristic algorithm, called GKONP, is designed to approximate the optimal solution, involving an approach to prune insignificant terms in the objective function, and the parallel differential evolution algorithm. In the third result, the effectiveness of the GKONP algorithm is demonstrated by applying it to a discrete dynamical system model of the yeast pheromone pathways. The empirical accuracy and time efficiency are assessed in comparison to an optimal, but exhaustive search strategy.Although the in silico target gene deletion problem has enormous potential applications in genetic engineering, one must overcome the computational challenge due to its NP-hardness. The presented solution, which has been demonstrated to approximate the optimal solution in a practical amount of time, is among the few that address the computational challenge. In the experiment on the yeast pheromone pathways, the identified best subset of genes for deletion showed advantage over genes that were selected empirically. Once validated in vivo, the optimal target genes are expected to achieve higher genetic engineering effectiveness than a trial-and-error procedure

Bacterial and fungal microflora in surgically removed lung cancer samples

<p>Abstract</p> <p>Background</p> <p>Clinical and experimental data suggest an association between the presence of bacterial and/or fungal infection and the development of different types of cancer, independently of chemotherapy-induced leukopenia. This has also been postulated for the development of lung cancer, however the prevalence and the exact species of the bacteria and fungi implicated, have not yet been described.</p> <p>Aim</p> <p>To determine the presence of bacterial and fungal microflora in surgically extracted samples of patients with lung cancer.</p> <p>Materials and methods</p> <p>In this single-center prospective, observational study, tissue samples were surgically extracted from 32 consecutive patients with lung cancer, and reverse-transcription polymerase chain reaction (RT-PCR) was used to identify the presence of bacteria and fungi strains.</p> <p>Results</p> <p>The analysis of the electrophoresis data pointed out diversity between the samples and the strains that were identified. Mycoplasma strains were identified in all samples. Strains that appeared more often were Staphylococcus epidermidis, Streptococcus mitis and Bacillus strains, followed in descending frequency by Chlamydia, Candida, Listeria, and Haemophilus influenza. In individual patients Legionella pneumophila and Candida tropicalis were detected.</p> <p>Conclusions</p> <p>A diversity of pathogens could be identified in surgically extracted tissue samples of patients with lung cancer, with mycoplasma strains being present in all samples. These results point to an etiologic role for chronic infection in lung carcinogenesis. Confirmation of these observations and additional studies are needed to further characterize the etiologic role of inflammation in lung carcinogenesis.</p

Comparative Study of SVM Methods Combined with Voxel Selection for Object Category Classification on fMRI Data

BACKGROUND: Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. METHODOLOGY/PRINCIPAL FINDINGS: Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. CONCLUSIONS/SIGNIFICANCE: The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice

Nano-Architecture of nitrogen-doped graphene films synthesized from a solid CN source

New synthesis routes to tailor graphene properties by controlling the concentration and chemical configuration of dopants show great promise. Herein we report the direct reproducible synthesis of 2-3% nitrogen-doped ‘few-layer’ graphene from a solid state nitrogen carbide a-C:N source synthesized by femtosecond pulsed laser ablation. Analytical investigations, including synchrotron facilities, made it possible to identify the configuration and chemistry of the nitrogen-doped graphene films. Auger mapping successfully quantified the 2D distribution of the number of graphene layers over the surface, and hence offers a new original way to probe the architecture of graphene sheets. The films mainly consist in a Bernal ABA stacking three-layer architecture, with a layer number distribution ranging from 2 to 6. Nitrogen doping affects the charge carrier distribution but has no significant effects on the number of lattice defects or disorders, compared to undoped graphene synthetized in similar conditions. Pyridinic, quaternary and pyrrolic nitrogen are the dominant chemical configurations, pyridinic N being preponderant at the scale of the film architecture. This work opens highly promising perspectives for the development of self-organized nitrogen-doped graphene materials, as synthetized from solid carbon nitride, with various functionalities, and for the characterization of 2D materials using a significant new methodology

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration