Use of antihypertensive medications in pregnancy and the risk of adverse perinatal outcomes: McMaster Outcome Study of Hypertension In Pregnancy 2 (MOS HIP 2)

BACKGROUND: Uncertainty remains about the potential harmful effects of antihypertensive therapy on the developing fetus, especially for beta-blockers (βb). METHODS: We prospectively enrolled all singleton women with a blood pressure ≥ 140/90 mm Hg during pregnancy. The main analysis included 1948 women with all forms of hypertension and compared the use of βb drugs, non-βb drugs or a combination of both, to no treatment. The primary study outcome was a composite of the diseases of prematurity, need for assisted ventilation for greater than 1 day, or perinatal death. A sub-group analysis evaluated the four treatment options among 583 singleton women with chronic hypertension before 20 weeks gestation. RESULTS: In the main analysis, no association was observed between βb use and the primary composite outcome [adjusted odds ratio (OR) 1.4, 95% CI 0.9–2.2], while an association was seen with non-βb therapy (OR 5.0, 95% CI 2.6–9.6) and combination therapy (OR 2.9, 95% CI 1.8–4.7). In the sub-group of 583 women with hypertension before 20 weeks, use of a non-βb drug (OR 4.9, 95% CI 1.7–14.2) or combination therapy (OR 2.9. 95% CI 1.1–7.7) was significantly associated with the primary composite outcome, while βb monotherapy was not (OR 1.4, 95% CI 0.6–3.4). CONCLUSIONS: Maternal use of antihypertensive medications other than βbs was associated with both major perinatal morbidity and mortality, while βb monotherapy was not. The combined use of βb and non-βb medications demonstrated the strongest association. Before definitive conclusions can be drawn, a large multicentre randomized controlled trial is needed to address the issues of both maternal efficacy and fetal safety with the use of one or more antihypertensive agents in pregnancy

The Cost-Effectiveness of Early Access to HIV Services and Starting cART in the UK 1996–2008

To calculate use, cost and cost-effectiveness of people living with HIV (PLHIV) starting routine treatment and care before starting combination antiretroviral therapy (cART) and PLHIV starting first-line 2NRTIs+NNRTI or 2NRTIs+PI(boosted), comparing PLHIV with CD4≤200 cells/mm3 and CD4>200 cells/mm3. Few studies have calculated the use, cost and cost-effectiveness of routine treatment and care before starting cART and starting cART above and below CD4 200 cells/mm3.Use, costs and cost-effectiveness were calculated for PLHIV in routine pre-cART and starting first-line cART, comparing CD4≤200 cells/mm3 with CD4>200 cells/mm3 (2008 UK prices).cART naïve patients CD4≤200 cells/mm3 had an annual cost of £6,407 (95%CI £6,382 to £6,425) PPY compared with £2,758 (95%CI £2,752 to £2,761) PPY for those with CD4>200 cells/mm3; cost per life year gained of pre-cART treatment and care for those with CD4>200 cells/mm3 was £1,776 (cost-saving to £2,752). Annual cost for starting 2NRTIs+NNRTI or 2NRTIs+PI(boosted) with CD4≤200 cells/mm3 was £12,812 (95%CI £12,685-£12,937) compared with £10,478 (95%CI £10,376-£10,581) for PLHIV with CD4>200 cells/mm3. Cost per additional life-year gained on first-line therapy for those with CD4>200 cells/mm3 was £4639 (£3,967 to £2,960).PLHIV starting to use HIV services before CD4≤200 cells/mm3 is cost-effective and enables them to be monitored so they start cART with a CD4>200 cells/mm3, which results in better outcomes and is cost-effective. However, 25% of PLHIV accessing services continue to present with CD4≤200 cells/mm3. This highlights the need to investigate the cost-effectiveness of testing and early treatment programs for key populations in the UK

The effect of statin therapy on heart failure events: a collaborative meta-analysis of unpublished data from major randomized trials

The effect of statins on risk of heart failure (HF) hospitalization and HF death remains uncertain. We aimed to establish whether statins reduce major HF events.We searched Medline, EMBASE, and the Cochrane Central Register of Controlled Trials for randomized controlled endpoint statin trials from 1994 to 2014. Collaborating trialists provided unpublished data from adverse event reports. We included primary- and secondary-prevention statin trials with >1000 participants followed for >1 year. Outcomes consisted of first non-fatal HF hospitalization, HF death and a composite of first non-fatal HF hospitalization or HF death. HF events occurring <30 days after within-trial myocardial infarction (MI) were excluded. We calculated risk ratios (RR) with fixed-effects meta-analyses. In up to 17 trials with 132 538 participants conducted over 4.3 [weighted standard deviation (SD) 1.4] years, statin therapy reduced LDL-cholesterol by 0.97 mmol/L (weighted SD 0.38 mmol/L). Statins reduced the numbers of patients experiencing non-fatal HF hospitalization (1344/66 238 vs. 1498/66 330; RR 0.90, 95% confidence interval, CI 0.84-0.97) and the composite HF outcome (1234/57 734 vs. 1344/57 836; RR 0.92, 95% CI 0.85-0.99) but not HF death (213/57 734 vs. 220/57 836; RR 0.97, 95% CI 0.80-1.17). The effect of statins on first non-fatal HF hospitalization was similar whether this was preceded by MI (RR 0.87, 95% CI 0.68-1.11) or not (RR 0.91, 95% CI 0.84-0.98).In primary- and secondary-prevention trials, statins modestly reduced the risks of non-fatal HF hospitalization and a composite of non-fatal HF hospitalization and HF death with no demonstrable difference in risk reduction between those who suffered an MI or not

The effect of statin therapy on heart failure events: a collaborative meta-analysis of unpublished data from major randomized trials

The effect of statins on risk of heart failure (HF) hospitalization and HF death remains uncertain. We aimed to establish whether statins reduce major HF events.We searched Medline, EMBASE, and the Cochrane Central Register of Controlled Trials for randomized controlled endpoint statin trials from 1994 to 2014. Collaborating trialists provided unpublished data from adverse event reports. We included primary- and secondary-prevention statin trials with >1000 participants followed for >1 year. Outcomes consisted of first non-fatal HF hospitalization, HF death and a composite of first non-fatal HF hospitalization or HF death. HF events occurring <30 days after within-trial myocardial infarction (MI) were excluded. We calculated risk ratios (RR) with fixed-effects meta-analyses. In up to 17 trials with 132 538 participants conducted over 4.3 [weighted standard deviation (SD) 1.4] years, statin therapy reduced LDL-cholesterol by 0.97 mmol/L (weighted SD 0.38 mmol/L). Statins reduced the numbers of patients experiencing non-fatal HF hospitalization (1344/66 238 vs. 1498/66 330; RR 0.90, 95% confidence interval, CI 0.84-0.97) and the composite HF outcome (1234/57 734 vs. 1344/57 836; RR 0.92, 95% CI 0.85-0.99) but not HF death (213/57 734 vs. 220/57 836; RR 0.97, 95% CI 0.80-1.17). The effect of statins on first non-fatal HF hospitalization was similar whether this was preceded by MI (RR 0.87, 95% CI 0.68-1.11) or not (RR 0.91, 95% CI 0.84-0.98).In primary- and secondary-prevention trials, statins modestly reduced the risks of non-fatal HF hospitalization and a composite of non-fatal HF hospitalization and HF death with no demonstrable difference in risk reduction between those who suffered an MI or not

Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction

&lt;b&gt;Background&lt;/b&gt; The widely used k top scoring pair (k-TSP) algorithm is a simple yet powerful parameter-free classifier. It owes its success in many cancer microarray datasets to an effective feature selection algorithm that is based on relative expression ordering of gene pairs. However, its general robustness does not extend to some difficult datasets, such as those involving cancer outcome prediction, which may be due to the relatively simple voting scheme used by the classifier. We believe that the performance can be enhanced by separating its effective feature selection component and combining it with a powerful classifier such as the support vector machine (SVM). More generally the top scoring pairs generated by the k-TSP ranking algorithm can be used as a dimensionally reduced subspace for other machine learning classifiers.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; We developed an approach integrating the k-TSP ranking algorithm (TSP) with other machine learning methods, allowing combination of the computationally efficient, multivariate feature ranking of k-TSP with multivariate classifiers such as SVM. We evaluated this hybrid scheme (k-TSP+SVM) in a range of simulated datasets with known data structures. As compared with other feature selection methods, such as a univariate method similar to Fisher's discriminant criterion (Fisher), or a recursive feature elimination embedded in SVM (RFE), TSP is increasingly more effective than the other two methods as the informative genes become progressively more correlated, which is demonstrated both in terms of the classification performance and the ability to recover true informative genes. We also applied this hybrid scheme to four cancer prognosis datasets, in which k-TSP+SVM outperforms k-TSP classifier in all datasets, and achieves either comparable or superior performance to that using SVM alone. In concurrence with what is observed in simulation, TSP appears to be a better feature selector than Fisher and RFE in some of the cancer datasets.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt; The k-TSP ranking algorithm can be used as a computationally efficient, multivariate filter method for feature selection in machine learning. SVM in combination with k-TSP ranking algorithm outperforms k-TSP and SVM alone in simulated datasets and in some cancer prognosis datasets. Simulation studies suggest that as a feature selector, it is better tuned to certain data characteristics, i.e. correlations among informative genes, which is potentially interesting as an alternative feature ranking method in pathway analysis

Genome-wide enhancer maps link risk variants to disease genes

Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complextraits, each of which could reveal insights into the mechanisms of disease(1). Many ofthe underlying causal variants may affect enhancers(2,3), but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types(4). Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577genesthat appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.Peer reviewe

Binary and Millisecond Pulsars at the New Millennium

We review the properties and applications of binary and millisecond pulsars. Our knowledge of these exciting objects has greatly increased in recent years, mainly due to successful surveys which have brought the known pulsar population to over 1300. There are now 56 binary and millisecond pulsars in the Galactic disk and a further 47 in globular clusters. This review is concerned primarily with the results and spin-offs from these surveys which are of particular interest to the relativity community.Comment: 59 pages, 26 figures, 5 tables. Accepted for publication in Living Reviews in Relativity (http://www.livingreviews.org

RNA interference as a key to knockdown overexpressed cyclooxygenase-2 gene in tumour cells

Silencing those genes that are overexpressed in cancer and contribute to the survival and progression of tumour cells is the aim of several researches. Cyclooxygenase-2 (COX-2) is one of the most intensively studied genes since it is overexpressed in most tumours, mainly in colon cancer. The use of specific COX-2 inhibitors to treat colon cancer has generated great enthusiasm. Yet, the side effects of some inhibitors emerging during long-term treatment have caused much concern. Genes silencing by RNA interference (RNAi) has led to new directions in the field of experimental oncology. In this study, we detected sequences directed against COX-2 mRNA, that potently downregulate COX-2 gene expression and inhibit phorbol 12-myristate 13-acetate-induced angiogenesis in vitro in a specific, nontoxic manner. Moreover, we found that the insertion of a specific cassette carrying anti-COX-2 short hairpin RNA sequence into a viral vector (pSUPER.retro) greatly increased silencing potency in a colon cancer cell line (HT29) without activating any interferon response. Phenotypically, COX-2 deficient HT29 cells showed a significant impairment of their in vitro malignant behaviour. Thus, the retroviral approach enhancing COX-2 knockdown, mediated by RNAi, proved to be an useful tool to better understand the role of COX-2 in colon cancer. Furthermore, the higher infection efficiency we observed in tumour cells, if compared to normal endothelial cells, may disclose the possibility to specifically treat tumour cells without impairing endothelial COX-2 activity

Clone-specific expression, transcriptional regulation, and action of interleukin-6 in human colon carcinoma cells

<p>Abstract</p> <p>Background</p> <p>Many cancer cells produce interleukin-6 (IL-6), a cytokine that plays a role in growth stimulation, metastasis, and angiogenesis of secondary tumours in a variety of malignancies, including colorectal cancer. Effectiveness of IL-6 in this respect may depend on the quantity of basal and inducible IL-6 expressed as the tumour progresses through stages of malignancy. We therefore have evaluated the effect of <it>IL-6 </it>modulators, i.e. IL-1β, prostaglandin E₂, 17β-estradiol, and 1,25-dihydroxyvitamin D₃, on expression and synthesis of the cytokine at different stages of tumour progression.</p> <p>Methods</p> <p>We utilized cultures of the human colon carcinoma cell clones Caco-2/AQ, COGA-1A and COGA-13, all of which expressed differentiation and proliferation markers typical of distinct stages of tumour progression. IL-6 mRNA and protein levels were assayed by RT-PCR and ELISA, respectively. DNA sequencing was utilized to detect polymorphisms in the <it>IL-6 </it>gene promoter.</p> <p>Results</p> <p><it>IL-6 </it>mRNA and protein concentrations were low in well and moderately differentiated Caco-2/AQ and COGA-1A cells, but were high in poorly differentiated COGA-13 cells. Addition of IL-1β (5 ng/ml) to a COGA-13 culture raised IL-6 production approximately thousandfold via a prostaglandin-independent mechanism. Addition of 17β-estradiol (10^-7M) reduced basal IL-6 production by one-third, but IL-1β-inducible IL-6 was unaffected. Search for polymorphisms in the <it>IL-6 </it>promoter revealed the presence of a single haplotype, i.e., -597A/-572G/-174C, in COGA-13 cells, which is associated with a high degree of transcriptional activity of the <it>IL-6 </it>gene. IL-6 blocked differentiation only in Caco-2/AQ cells and stimulated mitosis through up-regulation of c-<it>myc </it>proto-oncogene expression. These effects were inhibited by 10^-8M 1,25-dihydroxyvitamin D₃.</p> <p>Conclusion</p> <p>In human colon carcinoma cells derived from well and moderately differentiated tumours, IL-6 expression is low and only marginally affected, if at all, by PGE₂, 1,25-dihydroxyvitamin D₃, and 17β-estradiol. However, IL-6 is highly abundant in undifferentiated tumour cells and is effectively stimulated by IL-1β. In case of overexpression of an <it>IL-6 </it>gene variant with extreme sensitivity to IL-1β, massive release of the cytokine from undifferentiated tumour cells may accelerate progression towards malignancy by paracrine action on more differentiated tumour cells with a still functioning proliferative IL-6 signalling pathway.</p

Transcriptome-Based Differentiation of Closely-Related Miscanthus Lines

BACKGROUND: Distinguishing between individuals is critical to those conducting animal/plant breeding, food safety/quality research, diagnostic and clinical testing, and evolutionary biology studies. Classical genetic identification studies are based on marker polymorphisms, but polymorphism-based techniques are time and labor intensive and often cannot distinguish between closely related individuals. Illumina sequencing technologies provide the detailed sequence data required for rapid and efficient differentiation of related species, lines/cultivars, and individuals in a cost-effective manner. Here we describe the use of Illumina high-throughput exome sequencing, coupled with SNP mapping, as a rapid means of distinguishing between related cultivars of the lignocellulosic bioenergy crop giant miscanthus (Miscanthus × giganteus). We provide the first exome sequence database for Miscanthus species complete with Gene Ontology (GO) functional annotations. RESULTS: A SNP comparative analysis of rhizome-derived cDNA sequences was successfully utilized to distinguish three Miscanthus × giganteus cultivars from each other and from other Miscanthus species. Moreover, the resulting phylogenetic tree generated from SNP frequency data parallels the known breeding history of the plants examined. Some of the giant miscanthus plants exhibit considerable sequence divergence. CONCLUSIONS: Here we describe an analysis of Miscanthus in which high-throughput exome sequencing was utilized to differentiate between closely related genotypes despite the current lack of a reference genome sequence. We functionally annotated the exome sequences and provide resources to support Miscanthus systems biology. In addition, we demonstrate the use of the commercial high-performance cloud computing to do computational GO annotation