Beta-blocker usage after malignant melanoma diagnosis and survival: a population-based nested case-control study

Background: Beta-blockers have potential antiangiogenic and antimigratory activity. Studies have demonstrated a survival benefit in patients with malignant melanoma treated with beta-blockers.

Objectives: To investigate the association between postdiagnostic beta-blocker usage and risk of melanoma-specific mortality in a population-based cohort of patients with malignant melanoma.

Methods: Patients with incident malignant melanoma diagnosed between 1998 and 2010 were identified within the U.K. Clinical Practice Research Datalink and confirmed using cancer registry data. Patients with malignant melanoma with a melanoma-specific death (cases) recorded by the Office of National Statistics were matched on year of diagnosis, age and sex to four malignant melanoma controls (who lived at least as long after diagnosis as their matched case). A nested case–control approach was used to investigate the association between postdiagnostic beta-blocker usage and melanoma-specific death and all-cause mortality. Conditional logistic regression was applied to generate odds ratios (ORs) and 95% confidence intervals (CIs) for beta-blocker use determined from general practitioner prescribing.

Results: Beta-blocker medications were prescribed after malignant melanoma diagnosis to 20·2% of 242 patients who died from malignant melanoma (cases) and 20·3% of 886 matched controls. Consequently, there was no association between beta-blocker use postdiagnosis and cancer-specific death (OR 0·99, 95% CI 0·68–1·42), which did not markedly alter after adjustment for confounders including stage (OR 0·87, 95% CI 0·56–1·34). No significant associations were detected for individual beta-blocker types, by defined daily doses of use or for all-cause mortality.

Conclusions: Contrary to some previous studies, beta-blocker use after malignant melanoma diagnosis was not associated with reduced risk of death from melanoma in this U.K. population-based study.

Beta-blocker usage and breast cancer survival: a nested case-control study within a UK clinical practice research datalink cohort.

Background: To investigate the association between post-diagnostic beta-blocker usage and risk of cancer-specific mortality in a large population-based cohort of female breast cancer patients.

Methods: A nested case-control study was conducted within a cohort of breast cancer patients identified from cancer registries in England(using the National Cancer Data repository) and diagnosed between 1998 and 2007. Patients who had a breast cancer-specific death(ascertained from Office of National Statistics death registration data) were each matched to four alive controls by year and age at diagnosis. Prescription data for these patients were available through the Clinical Practice Research Datalink. Conditional logistic regression models were used to investigate the association between breast cancer-specific death and beta-blocker usage.

Results: Post-diagnostic use of beta-blockers was identified in 18.9% of 1435 breast cancer-specific deaths and 19.4% of their 5697 matched controls,indicating little evidence of association between beta-blocker use and breast cancer-specific mortality [odds ratio (OR) = 0.97,95% confidence interval (CI) 0.83, 1.13]. There was also little evidence of an association when analyses were restricted to cardio non-selective beta-blockers (OR = 0.90, 95% CI 0.69, 1.17). Similar results were observed in analyses of drug dosage frequency and duration, and beta-blocker type.

Conclusions: In this large UK population-based cohort of breast cancer patients,there was little evidence of an association between post-diagnostic beta-blocker usage and breast cancer progression. Further studies which include information on tumour receptor status are warranted to determine whether response to beta-blockers varies by tumour subtypes.

Low-dose aspirin and survival in men with prostate cancer: a study using the UK Clinical Practice Research Datalink

Purpose: Aspirin use is associated with reduced risk of, and death from, prostate cancer. Our aim was to determine whether low-dose aspirin use after a prostate cancer diagnosis was associated with reduced prostate cancer-specific mortality.

Methods: A cohort of newly diagnosed prostate cancer patients (1998–2006) was identified in the UK Clinical Practice Research Datalink (confirmed by cancer registry linkage). A nested case–control analysis was conducted using conditional logistic regression to compare aspirin usage in cases (prostate cancer deaths) with up to three controls (matched by age and year of diagnosis).

Results: Post-diagnostic low-dose aspirin use was identified in 52 % of 1,184 prostate cancer-specific deaths and 39 % of 3,531 matched controls (unadjusted OR 1.51, 95 % CI 1.19, 1.90; p < 0.001). After adjustment for confounders including treatment and comorbidities, this association was attenuated (adjusted OR 1.02 95 % CI 0.78, 1.34; p = 0.86). Adjustment for estrogen therapy accounted for the majority of this attenuation. There was also no evidence of dose–response association after adjustments. Compared with no use, patients with 1–11 prescriptions and 12 or more prescriptions had adjusted ORs of 1.07 (95 % CI 0.78, 1.47; p = 0.66) and 0.97 (95 % CI 0.69, 1.37; p = 0.88), respectively. There was no evidence of a protective association between low-dose aspirin use in the year prior to diagnosis and prostate cancer-specific mortality (adjusted OR 1.04 95 % CI 0.89, 1.22; p = 0.60).

Conclusion: We found no evidence of an association between low-dose aspirin use before or after diagnosis and risk of prostate cancer-specific mortality, after potential confounders were accounted for, in UK prostate cancer patients.

Beta-blocker usage and prostate cancer survival:A nested case-control study in the UK Clinical Practice Research Datalink cohort

Background: Recent laboratory and epidemiological evidence suggests that beta-blockers could inhibit prostate cancer progression. Methods: We investigated the effect of beta-blockers on prostate cancer-specific mortality in a cohort of prostate cancer patients. Prostate cancer patients diagnosed between 1998 and 2006 were identified from the UK Clinical Practice Research Database and confirmed by cancer registries. Patients were followed up to 2011 with deaths identified by the Office of National Statistics. A nested case-control analysis compared patients dying from prostate cancer (cases) with up to three controls alive at the time of their death, matched by age and year of diagnosis. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional logistic regression. Results: Post-diagnostic beta-blocker use was identified in 25% of 1184 prostate cancer-specific deaths and 26% of 3531 matched controls. There was little evidence (P=0.40) of a reduction in the risk of cancer-specific death in beta-blocker users compared with non-users (OR=0.94 95% CI 0.81, 1.09). Similar results were observed after adjustments for confounders, in analyses by beta-blocker frequency, duration, type and for all-cause mortality. Conclusions: Beta-blocker usage after diagnosis was not associated with cancer-specific or all-cause mortality in prostate cancer patients in this large UK study.

Nonlocality of two- and three-mode continuous variable systems

We address the nonlocality of fully inseparable three-mode Gaussian states generated either by bilinear three-mode Hamiltonians or by a sequence of bilinear two-mode Hamiltonians. Two different tests revealing nonlocality are considered, in which the dichotomic Bell operator is represented by the displaced parity and by the pseudospin operator respectively. Three-mode states are also considered as a conditional source of two-mode non-Gaussian states, whose nonlocality properties are analysed. We found that the non-Gaussian character of the conditional states allows violation of Bell's inequalities (by parity and pseudospin tests) stronger than with a conventional twin-beam state. However, the non-Gaussian character is not sufficient to reveal nonlocality through a dichotomized quadrature measurement strategy.

Nonlinearity Induced Entanglement Stability in a Qubit-Oscillator System

We consider a system composed of a qubit interacting with a quartic (undriven) nonlinear oscillator (NLO) through a conditional displacement Hamiltonian. We show that even a modest nonlinearity can enhance and stabilize the quantum entanglement dynamically generated between the qubit and the NLO. In contrast to the linear case, in which the entanglement is known to oscillate periodically between zero and its maximal value, the nonlinearity suppresses the dynamical decay of the entanglement once it is established. While the entanglement generation is due to the conditional displacements, as noted in several works before, the suppression of its decay is related to the presence of squeezing and other complex processes induced by two- and four-phonon interactions. Finally, we solve the respective Markovian master equation, showing that the previous features are preserved also when the system is open.

A Burkholderia cenocepacia MurJ (MviN) homolog is essential for cell wall peptidoglycan synthesis and bacterial viability

The cell wall peptidoglycan (PG) of Burkholderia cenocepacia, an opportunistic pathogen, has not yet been characterized. However, the B. cenocepacia genome contains homologs of genes encoding PG biosynthetic functions in other bacteria. PG biosynthesis involves the formation of the undecaprenyl-pyrophosphate-linked N-acetyl glucosamine-N-acetyl muramic acid-pentapeptide, known as lipid II, which is built on the cytosolic face of the cell membrane. Lipid II is then translocated across the membrane and its glycopeptide moiety becomes incorporated into the growing cell wall mesh; this translocation step is critical to PG synthesis. We have investigated candidate flippase homologs of the MurJ family in B. cenocepacia. Our results show that BCAL2764, herein referred to as murJBc, is indispensable for viability. Viable B. cenocepacia could only be obtained through a conditional mutagenesis strategy by placing murJBc under the control of a rhamnose-inducible promoter. Under rhamnose depletion, the conditional strain stopped growing and individual cells displayed morphological abnormalities consistent with a defect in PG synthesis. Bacterial cells unable to express MurJBc underwent cell lysis, while partial MurJBc depletion sensitized the mutant to the action of β-lactam antibiotics. Depletion of MurJBc caused accumulation of PG precursors consistent with the notion that this protein plays a role in lipid II flipping to the periplasmic compartment. Reciprocal complementation experiments of conditional murJ mutants in B. cenocepacia and Escherichia coli with plasmids expressing MurJ from each strain indicated that MurJBc and MurJEc are functional homologs. Together, our results are consistent with the notion that MurJBc is a PG lipid II flippase in B. cenocepacia.

NSUN4 Is a Dual Function Mitochondrial Protein Required for Both Methylation of 12S rRNA and Coordination of Mitoribosomal Assembly

Biogenesis of mammalian mitochondrial ribosomes requires a concerted maturation of both the small (SSU) and large subunit (LSU). We demonstrate here that the m(5)C methyltransferase NSUN4, which forms a complex with MTERF4, is essential in mitochondrial ribosomal biogenesis as mitochondrial translation is abolished in conditional Nsun4 mouse knockouts. Deep sequencing of bisulfite-treated RNA shows that NSUN4 methylates cytosine 911 in 12S rRNA (m5C911) of the SSU. Surprisingly, NSUN4 does not need MTERF4 to generate this modification. Instead, the NSUN4/MTERF4 complex is required to assemble the SSU and LSU to form a monosome. NSUN4 is thus a dual function protein, which on the one hand is needed for 12S rRNA methylation and, on the other hand interacts with MTERF4 to facilitate monosome assembly. The presented data suggest that NSUN4 has a key role in controlling a final step in ribosome biogenesis to ensure that only the mature SSU and LSU are assembled.

Temporal and statistical information in causal structure learning

Three experiments examined children’s and adults’ abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a three-variable mechanical system that operated probabilistically. Participants of all ages preferentially relied on the temporal pattern of events in their inferences, even if this conflicted with statistical information. In Experiments 2 and 3, participants observed a series of interventions on the system, which in these experiments operated deterministically. In Experiment 2, participants found it easier to use temporal pattern information than statistical information provided as a result of interventions. In Experiment 3, in which no temporal pattern information was provided, children from 6-7 years, but not younger children, were able to use intervention information to make causal chain judgments, although they had difficulty when the structure was a common cause. The findings suggest that participants, and children in particular, may find it more difficult to use statistical information than temporal pattern information because of its demands on information processing resources. However, there may also be an inherent preference for temporal information.

Post-diagnostic prescriptions for low-dose aspirin and breast cancer-specific survival: a nested case-control study in a breast cancer cohort from the UK Clinical Practice Research Datalink

INTRODUCTION: Recent observational studies indicate that post-diagnostic use of aspirin in breast cancer patients may protect against cancer progression perhaps by inhibiting cyclooxygenase-2 dependent mechanisms. Evidence also supports a crucial role for interactions between tumour cells and circulating platelets in cancer growth and dissemination, therefore, use of low-dose aspirin may reduce the risk of death from cancer in breast cancer patients.

METHODS: A cohort of newly diagnosed breast cancer patients (1998 to 2006) were identified in the UK Clinical Practice Research Datalink (and confirmed by cancer registry linkage). Cancer-specific deaths were identified up to 2011 from Office for National Statistics mortality data. A nested case-control analysis was conducted using conditional logistic regression to compare post-diagnostic aspirin exposure using General Practice prescription data in 1,435 cases (breast cancer deaths) with 5,697 controls (matched by age and year of diagnosis).

RESULTS: After breast cancer diagnosis, 18.3% of cancer-specific deaths and 18.5% of matched controls received at least one prescription for low-dose aspirin, corresponding to an odds ratio (OR) of 0.98 (95% CI 0.83, 1.15). Adjustment for potential confounders (including stage and grade) had little impact on this estimate. No dose response relationship was observed when the number of tablets was investigated and no associations were seen when analyses were stratified by receipt of prescriptions for aspirin in the pre-diagnostic period, by stage at diagnosis or by receipt of prescriptions for hormone therapy.

CONCLUSIONS: Overall, in this large population-based cohort of breast cancer patients, there was little evidence of an association between receipt of post-diagnostic prescriptions for low-dose aspirin and breast cancer-specific death. However, information was not available on medication compliance or over-the-counter use of aspirin, which may have contributed to the null findings.

Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21 856) and multiple sclerosis (MS) (n=43 879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16 731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.Molecular Psychiatry advance online publication, 28 January 2014; doi:10.1038/mp.2013.195.

Due North? Do American Theories of Legislative Committees Apply to Canada?

Several theories of legislative organisation have been proposed to explain committee selection in American legislatures, but do these theories travel outside the United States? This paper tests whether these theories apply to data from the Canadian House of Commons. It was found that the distributive and partisan models of legislative organisation explain committee composition in Canada. In many cases, committees in the House of Commons are made up of preference outliers. As predicted by partisan models, it was also found that the governing party stacks committees with its members, but this is conditional upon the strength of the governing party.

Civil Society Aid to Post-Communist Countries

A major debate within foreign aid literature is whether civil society can be ‘purchased’ through outside assistance.We test this proposition by exploring the influence of aid provided by the United States Agency for International
Development on post-communist civil rights environments. A review of research critical of international assistance highlights the risk of unsustainability, polarization and dependence among recipient civic organizations.We argue that
a more effective stimulant is socio-economic growth, which stimulates committed constituencies, higher citizen expectations and pressure on the state to protect civil freedoms. Using cross-sectional, time-series data from 27
post-communist countries, we find no evidence that aid independently promotes stronger civil rights environments but that economic growth produces substantial improvements. Further, any aid effectiveness appears to be conditional on economic strength.We conclude that developmental organizations should reassess how and where civil society aid is targeted.

Efficient Marginal Likelihood Computation for Gaussian Process Regression

In a Bayesian learning setting, the posterior distribution of a predictive model arises from a trade-off between its prior distribution and the conditional likelihood of observed data. Such distribution functions usually rely on additional hyperparameters which need to be tuned in order to achieve optimum predictive performance; this operation can be efficiently performed in an Empirical Bayes fashion by maximizing the posterior marginal likelihood of the observed data. Since the score function of this optimization problem is in general characterized by the presence of local optima, it is necessary to resort to global optimization strategies, which require a large number of function evaluations. Given that the evaluation is usually computationally intensive and badly scaled with respect to the dataset size, the maximum number of observations that can be treated simultaneously is quite limited. In this paper, we consider the case of hyperparameter tuning in Gaussian process regression. A straightforward implementation of the posterior log-likelihood for this model requires O(N^3) operations for every iteration of the optimization procedure, where N is the number of examples in the input dataset. We derive a novel set of identities that allow, after an initial overhead of O(N^3), the evaluation of the score function, as well as the Jacobian and Hessian matrices, in O(N) operations. We prove how the proposed identities, that follow from the eigendecomposition of the kernel matrix, yield a reduction of several orders of magnitude in the computation time for the hyperparameter optimization problem. Notably, the proposed solution provides computational advantages even with respect to state of the art approximations that rely on sparse kernel matrices.

Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms

Kuznetsov independence of variables X and Y means that, for any pair of bounded functions f(X) and g(Y), E[f(X)g(Y)]=E[f(X)] *times* E[g(Y)], where E[.] denotes interval-valued expectation and *times* denotes interval multiplication. We present properties of Kuznetsov independence for several variables, and connect it with other concepts of independence in the literature; in particular we show that strong extensions are always included in sets of probability distributions whose lower and upper expectations satisfy Kuznetsov independence. We introduce an algorithm that computes lower expectations subject to judgments of Kuznetsov independence by mixing column generation techniques with nonlinear programming. Finally, we define a concept of conditional Kuznetsov independence, and study its graphoid properties.