Cancer risk among users of neuroleptic medication: a population-based cohort study

It has been suggested that neuroleptic medication may decrease cancer risk. We compared cancer risks in a population-based cohort study of 25 264 users (⩾2 prescriptions) of neuroleptic medications in the county of North Jutland, Denmark, during 1989–2002, with that of county residents who did not receive such prescriptions. Statistical analyses were based on age-standardisation and Poisson regression analysis, adjusting for age, calendar period, COPD, liver cirrhosis or alcoholism, use of NSAID, and, for breast cancer, additionally for use of hormone therapy, age at first birth, and number of children. Use of neuroleptic medications was associated with a decreased risk for rectal cancer in both women and men (adjusted IRRs of 0.61 (95% confidence interval, 0.41–0.91) and 0.82 (0.56–1.19), respectively) and for colon cancer in female users (0.78; 0.62–0.98). Some risk reduction was seen for prostate cancer (0.87; 0.69–1.08), but breast cancer risk was close to unity (0.93; 0.74–1.17). Overall, treatment with neuroleptic medications was not related to a reduced risk of cancer, but for cancers of the rectum, colon and prostate there were suggestive decreases in risk

IgA in the horse: cloning of equine polymeric Ig receptor and J chain and characterization of recombinant forms of equine IgA

As in other mammals, immunoglobulin A (IgA) in the horse has a key role in immune defense. To better dissect equine IgA function, we isolated complementary DNA (cDNA) clones for equine J chain and polymeric Ig receptor (pIgR). When coexpressed with equine IgA, equine J chain promoted efficient IgA polymerization. A truncated version of equine pIgR, equivalent to secretory component, bound with nanomolar affinity to recombinant equine and human dimeric IgA but not with monomeric IgA from either species. Searches of the equine genome localized equine J chain and pIgR to chromosomes 3 and 5, respectively, with J chain and pIgR coding sequence distributed across 4 and 11 exons, respectively. Comparisons of transcriptional regulatory sequences suggest that horse and human pIgR expression is controlled through common regulatory mechanisms that are less conserved in rodents. These studies pave the way for full dissection of equine IgA function and open up possibilities for immune-based treatment of equine diseases

TIMP-1 gene deficiency increases tumour cell sensitivity to chemotherapy-induced apoptosis

Tissue inhibitor of metalloproteinases-1 (TIMP-1) is one of four inhibitors of the matrix metalloproteinases, which are capable of degrading most components of the extracellular matrix. However, in recent years, TIMP-1 has been recognised as a multifunctional protein, playing a complex role in cancer. In this regard, several studies have demonstrated an antiapoptotic effect of TIMP-1 in a number of different cell types. Since chemotherapy works by inducing apoptosis in cancer cells, we raised the hypothesis that TIMP-1 promotes resistance against chemotherapeutic drugs. In order to investigate this hypothesis, we have established TIMP-1 gene-deficient and TIMP-1 wild-type fibrosarcoma cells from mouse lung tissue. We have characterised these cells with regard to TIMP-1 genotype, TIMP-1 expression, malignant transformation and sensitivity to chemotherapy-induced apoptosis. We show that TIMP-1 gene deficiency increases the response to chemotherapy considerably, confirming that TIMP-1 protects the cells from apoptosis. This is to our knowledge the first study investigating TIMP-1 and chemotherapy-induced apoptosis employing a powerful model system comprising TIMP-1 gene-deficient cells and their genetically identical wild-type controls. For future studies, this cell system can be used to uncover the mechanisms and signalling pathways involved in the TIMP-1-mediated inhibition of apoptosis as well as to investigate the possibility of using TIMP-1 inhibitors to optimise the effect of conventional chemotherapy

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Metabolic profiling of human brain metastases using in vivo proton MR spectroscopy at 3T

<p>Abstract</p> <p>Background</p> <p>Metastases to the central nervous system from different primary cancers are an oncologic challenge as the overall prognosis for these patients is generally poor. The incidence of brain metastases varies with type of primary cancer and is probably increasing due to improved therapies of extracranial metastases prolonging patient's overall survival and thereby time for brain metastases to develop. In addition, the greater access to improved neuroimaging techniques can provide earlier diagnosis. The aim of this study was to investigate the feasibility of using proton magnetic resonance spectroscopy (MRS) and multivariate analyses to characterize brain metastases originating from different primary cancers, to assess changes in spectra during radiation treatment and to correlate the spectra to clinical outcome after treatment.</p> <p>Methods</p> <p>Patients (n = 26) with brain metastases were examined using single voxel MRS at a 3T clinical MR system. Five patients were excluded due to poor spectral quality. The spectra were obtained before start (n = 21 patients), immediately after (n = 6 patients) and two months after end of treatment (n = 4 patients). Principal component analysis (PCA) and partial least square regression analysis (PLS) were applied in order to identify clustering of spectra due to origin of metastases and to relate clinical outcome (survival) of the patients to spectral data from the first MR examination.</p> <p>Results</p> <p>The PCA results indicated that brain metastases from primary lung and breast cancer were separated into two clusters, while the metastases from malignant melanomas showed no uniformity. The PLS analysis showed a significant correlation between MR spectral data and survival five months after MRS before start of treatment.</p> <p>Conclusion</p> <p>MRS determined metabolic profiles analysed by PCA and PLS might give valuable clinical information when planning and evaluating the treatment of brain metastases, and also when deciding to terminate further therapies.</p

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

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT