The ISCIP Analyst, Volume VIII, Issue 1

This repository item contains a single issue of The ISCIP Analyst, an analytical review journal published from 1996 to 2010 by the Boston University Institute for the Study of Conflict, Ideology, and Policy

The ISCIP Analyst, Volume VII, Issue 20

This repository item contains a single issue of The ISCIP Analyst, an analytical review journal published from 1996 to 2010 by the Boston University Institute for the Study of Conflict, Ideology, and Policy

The ISCIP Analyst, Volume VIII, Issue 4

This repository item contains a single issue of The ISCIP Analyst, an analytical review journal published from 1996 to 2010 by the Boston University Institute for the Study of Conflict, Ideology, and Policy

Inhibition of Voltage-Gated Hv1 Channel by Guanidine Derivatives

This repository item contains a single issue of The ISCIP Analyst, an analytical review journal published from 1996 to 2010 by the Boston University Institute for the Study of Conflict, Ideology, and Policy

On subsumption and semiunification in feature algebras

AbstractWe consider a generalization of term subsumption, or matching, to a class of mathematical structures which we call feature algebras. We show how these generalize both first-order terms and the feature structures used in computational linguistics. The notion of term subsumption generalizes to a natural notion of algebra homomorphism. In the setting of feature algebras, unification, corresponds naturally to solving constraints involving equalities between strings of unary function symbols, and semiunification also allows inequalities representing subsumption constraints. Our generalization allows us to show that the semiunification problem for finite feature algebras is undecidable. This implies that the corresponding problem for rational trees (cyclic terms) is also undecidable

A Predictive Model of the Oxygen and Heme Regulatory Network in Yeast

Deciphering gene regulatory mechanisms through the analysis of high-throughput expression data is a challenging computational problem. Previous computational studies have used large expression datasets in order to resolve fine patterns of coexpression, producing clusters or modules of potentially coregulated genes. These methods typically examine promoter sequence information, such as DNA motifs or transcription factor occupancy data, in a separate step after clustering. We needed an alternative and more integrative approach to study the oxygen regulatory network in Saccharomyces cerevisiae using a small dataset of perturbation experiments. Mechanisms of oxygen sensing and regulation underlie many physiological and pathological processes, and only a handful of oxygen regulators have been identified in previous studies. We used a new machine learning algorithm called MEDUSA to uncover detailed information about the oxygen regulatory network using genome-wide expression changes in response to perturbations in the levels of oxygen, heme, Hap1, and Co2+. MEDUSA integrates mRNA expression, promoter sequence, and ChIP-chip occupancy data to learn a model that accurately predicts the differential expression of target genes in held-out data. We used a novel margin-based score to extract significant condition-specific regulators and assemble a global map of the oxygen sensing and regulatory network. This network includes both known oxygen and heme regulators, such as Hap1, Mga2, Hap4, and Upc2, as well as many new candidate regulators. MEDUSA also identified many DNA motifs that are consistent with previous experimentally identified transcription factor binding sites. Because MEDUSA's regulatory program associates regulators to target genes through their promoter sequences, we directly tested the predicted regulators for OLE1, a gene specifically induced under hypoxia, by experimental analysis of the activity of its promoter. In each case, deletion of the candidate regulator resulted in the predicted effect on promoter activity, confirming that several novel regulators identified by MEDUSA are indeed involved in oxygen regulation. MEDUSA can reveal important information from a small dataset and generate testable hypotheses for further experimental analysis. Supplemental data are included

A systematic review of randomised controlled trials of radiotherapy for localised prostate cancer

Background: Prostate cancer is the second most frequently diagnosed cancer and the sixth leading cause of cancer death in males. A systematic review of randomised controlled trials (RCTs) of radiotherapy and other non-pharmacological management options for localised prostate cancer was undertaken. Methods: A search of thirteen databases was carried out until March 2014.RCTs comparing radiotherapy (brachytherapy (BT) or external beam radiotherapy (EBRT)) to other management options i.e. radical prostatectomy (RP), active surveillance, watchful waiting, high intensity focused ultrasound (HIFU), or cryotherapy; each alone or in combination, e.g. with adjuvant hormone therapy (HT), were included. Methods followed guidance by the Centre for Reviews and Dissemination and the Cochrane Collaboration. Indirect comparisons were calculated using the Butcher method. Results: Thirty-six randomised controlled trials (RCTs, 134 references) were included. EBRT, BT and RP were found to be effective in the management of localised prostate cancer. While higher doses of EBRT seem to be related to favourable survival-related outcomes they might, depending on technique, involve more adverse events, e.g. gastrointestinal and genitourinary toxicity. Combining EBRT with hormone therapy shows a statistically significant advantage regarding overall survival when compared to EBRT alone (Relative risk 1.21, 95% confidence interval 1.12-1.30). Aside from mixed findings regarding urinary function, BT and radical prostatectomy were comparable in terms of quality of life and biochemical progression-free survival while favouring BT regarding patient satisfaction and sexual function. There might be advantages of EBRT (with/without HT) compared to cryoablation (with/without HT). No studies on HIFU were identified. Conclusions: Based on this systematic review, there is no strong evidence to support one therapy over another as EBRT, BT and RP can all be considered as effective mono therapies for localised disease with EBRT also effective for post-operative management. All treatments have unique adverse events profiles. Further large, robust RCTs which report treatment-specific and treatment combination-specific outcomes in defined prostate cancer risk groups following established reporting standards are needed. These will strengthen the evidence base for newer technologies, help reinforce current consensus guidelines and establish greater standardisation across practices

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe