Cancer and systemic inflammation: treat the tumour and treat the host

Determinants of cancer progression and survival are multifactorial and host responses are increasingly appreciated to have a major role. Indeed, the development and maintenance of a systemic inflammatory response has been consistently observed to confer poorer outcome, in both early and advanced stage disease. For patients, cancer-associated symptoms are of particular importance resulting in a marked impact on day-to-day quality of life and are also associated with poorer outcome. These symptoms are now recognised to cluster with one another with anorexia, weight loss and physical function forming a recognised cluster whereas fatigue, pain and depression forming another. Importantly, it has become apparent that these symptom clusters are associated with presence of a systemic inflammatory response in the patient with cancer. Given the understanding of the above, there is now a need to intervene to moderate systemic inflammatory responses, where present. In this context the rationale for therapeutic intervention using nonselective anti-inflammatory agents is clear and compelling and likely to become a part of routine clinical practice in the near future. The published literature on therapeutic intervention using anti-inflammatory agents for cancer-associated symptoms was reviewed. There are important parallels with the development of useful treatments for the systemic inflammatory response in patients with rheumatological disease and cardiovascular disease

Valley-spin blockade and spin resonance in carbon nanotubes

Manipulation and readout of spin qubits in quantum dots made in III-V materials successfully rely on Pauli blockade that forbids transitions between spin-triplet and spin-singlet states. Quantum dots in group IV materials have the advantage of avoiding decoherence from the hyperfine interaction by purifying them with only zero-spin nuclei. Complications of group IV materials arise from the valley degeneracies in the electronic bandstructure. These lead to complicated multiplet states even for two-electron quantum dots thereby significantly weakening the selection rules for Pauli blockade. Only recently have spin qubits been realized in silicon devices where the valley degeneracy is lifted by strain and spatial confinement. In carbon nanotubes Pauli blockade can be observed by lifting valley degeneracy through disorder. In clean nanotubes, quantum dots have to be made ultra-small to obtain a large energy difference between the relevant multiplet states. Here we report on low-disorder nanotubes and demonstrate Pauli blockade based on both valley and spin selection rules. We exploit the bandgap of the nanotube to obtain a large level spacing and thereby a robust blockade. Single-electron spin resonance is detected using the blockade.Comment: 31 pages including supplementary informatio

A valley-spin qubit in a carbon nanotube

Although electron spins in III-V semiconductor quantum dots have shown great promise as qubits, a major challenge is the unavoidable hyperfine decoherence in these materials. In group IV semiconductors, the dominant nuclear species are spinless, allowing for qubit coherence times that have been extended up to seconds in diamond and silicon. Carbon nanotubes are a particularly attractive host material, because the spin-orbit interaction with the valley degree of freedom allows for electrical manipulation of the qubit. In this work, we realise such a qubit in a nanotube double quantum dot. The qubit is encoded in two valley-spin states, with coherent manipulation via electrically driven spin resonance (EDSR) mediated by a bend in the nanotube. Readout is performed by measuring the current in Pauli blockade. Arbitrary qubit rotations are demonstrated, and the coherence time is measured via Hahn echo. Although the measured decoherence time is only 65 ns in our current device, this work offers the possibility of creating a qubit for which hyperfine interaction can be virtually eliminated

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

Pretense and Imagination

Issues of pretense and imagination are of central interest to philosophers, psychologists, and researchers in allied fields. In this entry, we provide a roadmap of some of the central themes around which discussion has been focused. We begin with an overview of pretense, imagination, and the relationship between them. We then shift our attention to the four specific topics where the disciplines' research programs have intersected or where additional interactions could prove mutually beneficial: the psychological underpinnings of performing pretense and of recognizing pretense, the cognitive capacities involved in imaginative engagement with fictions, and the real-world impact of make-believe. In the final section, we discuss more briefly a number of other mental activities that arguably involve imagining, including counterfactual reasoning, delusions, and dreaming

Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma

Therapy development for adult diffuse glioma is hindered by incomplete knowledge of somatic glioma driving alterations and suboptimal disease classification. We defined the complete set of genes associated with 1,122 diffuse grade II-III-IV gliomas from The Cancer Genome Atlas and used molecular profiles to improve disease classification, identify molecular correlations, and provide insights into the progression from low- to high-grade disease. Whole-genome sequencing data analysis determined that ATRX but not TERT promoter mutations are associated with increased telomere length. Recent advances in glioma classification based on IDH mutation and 1p/19q co-deletion status were recapitulated through analysis of DNA methylation profiles, which identified clinically relevant molecular subsets. A subtype of IDH mutant glioma was associated with DNA demethylation and poor outcome; a group of IDH-wild-type diffuse glioma showed molecular similarity to pilocytic astrocytoma and relatively favorable survival. Understanding of cohesive disease groups may aid improved clinical outcomes

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Azimuthal anisotropy of charged particles at high transverse momenta in PbPb collisions at sqrt(s[NN]) = 2.76 TeV

The azimuthal anisotropy of charged particles in PbPb collisions at nucleon-nucleon center-of-mass energy of 2.76 TeV is measured with the CMS detector at the LHC over an extended transverse momentum (pt) range up to approximately 60 GeV. The data cover both the low-pt region associated with hydrodynamic flow phenomena and the high-pt region where the anisotropies may reflect the path-length dependence of parton energy loss in the created medium. The anisotropy parameter (v2) of the particles is extracted by correlating charged tracks with respect to the event-plane reconstructed by using the energy deposited in forward-angle calorimeters. For the six bins of collision centrality studied, spanning the range of 0-60% most-central events, the observed v2 values are found to first increase with pt, reaching a maximum around pt = 3 GeV, and then to gradually decrease to almost zero, with the decline persisting up to at least pt = 40 GeV over the full centrality range measured.Comment: Replaced with published version. Added journal reference and DO

Hypermethylation of Tumor Suppressor Genes Involved in Critical Regulatory Pathways for Developing a Blood-Based Test in Breast Cancer

Aberrant DNA methylation patterns might be used as a biomarker for diagnosis and management of cancer patients