Temporal trends in hepatitis B and C infection in family blood donors from interior Sindh, Pakistan

<p>Abstract</p> <p>Background</p> <p>Hepatitis B (HBV) and C (HCV) infections are a serious global and national public health problem. Earlier studies have reported increasing rates of hepatitis infection in Pakistan, particularly in rural areas. Pakistan has no active surveillance program to monitor trends of these infections. The objective of this study was to verify this trend in blood donors from the rural Sindh area of the country.</p> <p>Methods</p> <p>The study analysed the data of blood donors of interior Sindh who donated blood at JPMC blood bank from January 1, 2004 to September 15, 2007. HBsAg status was determined by using HBsAg Serodia kit and antibodies to HCV using the Detect HCV ™ V.3 Kit. Samples repeatedly reactive for HBsAg or anti-HCV were considered positive for HBV or HCV infection respectively.</p> <p>Results</p> <p>The overall seroprevalence of HBV infection among donors was 6.2 % (95% CI 5.5%–6.9%) and did not change significantly over the study period. Overall seroprevalence of HBV infection in literate blood donors was 5.7 %(95% CI 4.7%–6.8%). Prevalence decreased significantly in this group over the study period (p = 0.05). No other significant trends in seroprevalence of HBV infection were seen in the stratified analyses.</p> <p>The overall seroprevalence of HCV among donors was 7.5% (95% CI 6.8%–8.3%) and increased significantly over the study period from 7.2% (95% CI 5.8%–8.7%) in 2004 to 8.9% (95% CI 7.4%–10.6%) in 2007 (p = 0.02). Significant increase in seroprevalence was particularly seen in literate (p = 0.03), non–first time (p = 0.01) and Sindhi speaking (p = 0.01) donors.</p> <p>Conclusion</p> <p>Our study finds a steady increase in the prevalence of HCV infection in blood donors from interior Sindh between 2004 and 2007. On the contrary, decreasing prevalence of HBV was found, particularly in literate blood donors. There may be a need to have rural community-based epidemiological studies to identify the determinants of the spread of HCV infection and also those that are limiting the spread of HBV infection particularly in the literate blood donor population.</p

Imputation strategies for missing binary outcomes in cluster randomized trials

<p>Abstract</p> <p>Background</p> <p>Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate dependent missing, we compared six MI strategies which account for the intra-cluster correlation for missing binary outcomes in CRTs with the standard imputation strategies and complete case analysis approach using a simulation study.</p> <p>Method</p> <p>We considered three within-cluster and three across-cluster MI strategies for missing binary outcomes in CRTs. The three within-cluster MI strategies are logistic regression method, propensity score method, and Markov chain Monte Carlo (MCMC) method, which apply standard MI strategies within each cluster. The three across-cluster MI strategies are propensity score method, random-effects (RE) logistic regression approach, and logistic regression with cluster as a fixed effect. Based on the community hypertension assessment trial (CHAT) which has complete data, we designed a simulation study to investigate the performance of above MI strategies.</p> <p>Results</p> <p>The estimated treatment effect and its 95% confidence interval (CI) from generalized estimating equations (GEE) model based on the CHAT complete dataset are 1.14 (0.76 1.70). When 30% of binary outcome are missing completely at random, a simulation study shows that the estimated treatment effects and the corresponding 95% CIs from GEE model are 1.15 (0.76 1.75) if complete case analysis is used, 1.12 (0.72 1.73) if within-cluster MCMC method is used, 1.21 (0.80 1.81) if across-cluster RE logistic regression is used, and 1.16 (0.82 1.64) if standard logistic regression which does not account for clustering is used.</p> <p>Conclusion</p> <p>When the percentage of missing data is low or intra-cluster correlation coefficient is small, different approaches for handling missing binary outcome data generate quite similar results. When the percentage of missing data is large, standard MI strategies, which do not take into account the intra-cluster correlation, underestimate the variance of the treatment effect. Within-cluster and across-cluster MI strategies (except for random-effects logistic regression MI strategy), which take the intra-cluster correlation into account, seem to be more appropriate to handle the missing outcome from CRTs. Under the same imputation strategy and percentage of missingness, the estimates of the treatment effect from GEE and RE logistic regression models are similar.</p

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors

Climate change adaptation and cross-sectoral policy coherence in southern Africa

To be effective, climate change adaptation needs to be mainstreamed across multiple sectors and greater policy coherence is essential. Using the cases of Malawi, Tanzania and Zambia, this paper investigates the extent of coherence in national policies across the water and agriculture sectors and to climate change adaptation goals outlined in national development plans. A two-pronged qualitative approach is applied using Qualitative Document Analysis of relevant policies and plans, combined with expert interviews from non-government actors in each country. Findings show that sector policies have differing degrees of coherence on climate change adaptation, currently being strongest in Zambia and weakest in Tanzania. We also identify that sectoral policies remain more coherent in addressing immediate-term disaster management issues of floods and droughts rather than longer-term strategies for climate adaptation. Coherence between sector and climate policies and strategies is strongest when the latter has been more recently developed. However to date, this has largely been achieved by repackaging of existing sectoral policy statements into climate policies drafted by external consultants to meet international reporting needs and not by the establishment of new connections between national sectoral planning processes. For more effective mainstreaming of climate change adaptation, governments need to actively embrace longer-term cross-sectoral planning through cross-Ministerial structures, such as initiated through Zambia’s Interim Climate Change Secretariat, to foster greater policy coherence and integrated adaptation planning

LINT, a Novel dL(3)mbt-Containing Complex, Represses Malignant Brain Tumour Signature Genes

Mutations in the l(3)mbt tumour suppressor result in overproliferation of Drosophila larval brains. Recently, the derepression of different gene classes in l(3)mbt mutants was shown to be causal for transformation. However, the molecular mechanisms of dL(3)mbt-mediated gene repression are not understood. Here, we identify LINT, the major dL(3)mbt complex of Drosophila. LINT has three core subunits—dL(3)mbt, dCoREST, and dLint-1—and is expressed in cell lines, embryos, and larval brain. Using genome-wide ChIP–Seq analysis, we show that dLint-1 binds close to the TSS of tumour-relevant target genes. Depletion of the LINT core subunits results in derepression of these genes. By contrast, histone deacetylase, histone methylase, and histone demethylase activities are not required to maintain repression. Our results support a direct role of LINT in the repression of brain tumour-relevant target genes by restricting promoter access

Association of dialysis facility-level hemoglobin measurement and erythropoiesis-stimulating agent dose adjustment frequencies with dialysis facility-level hemoglobin variation: a retrospective analysis

<p>Abstract</p> <p>Background</p> <p>A key goal of anemia management in dialysis patients is to maintain patients' hemoglobin (Hb) levels consistently within a target range. Our aim in this study was to assess the association of facility-level practice patterns representing Hb measurement and erythropoiesis-stimulating agent (ESA) dose adjustment frequencies with facility-level Hb variation.</p> <p>Methods</p> <p>This was a retrospective observational database analysis of patients in dialysis facilities affiliated with large dialysis organizations as of July 01, 2006, covering a follow-up period from July 01, 2006 to June 30, 2009. A total of 2,763 facilities representing 436,442 unique patients were included. The predictors evaluated were facility-level Hb measurement and ESA dose adjustment frequencies, and the outcome measured was facility-level Hb variation.</p> <p>Results</p> <p>First to 99th percentile ranges for facility-level Hb measurement and ESA dose adjustment frequencies were approximately once per month to once per week and approximately once per 3 months to once per 3 weeks, respectively. Facility-level Hb measurement and ESA dose adjustment frequencies were inversely associated with Hb variation. Modeling results suggested that a more frequent Hb measurement (once per week rather than once per month) was associated with approximately 7% to 9% and 6% to 8% gains in the proportion of patients with Hb levels within a ±1 and ±2 g/dL range around the mean, respectively. Similarly, more frequent ESA dose adjustment (once per 2 weeks rather than once per 3 months) was associated with approximately 6% to 9% and 5% to 7% gains in the proportion of patients in these respective Hb ranges.</p> <p>Conclusions</p> <p>Frequent Hb measurements and timely ESA dose adjustments in dialysis patients are associated with lower facility-level Hb variation and an increase in proportion of patients within ±1 and ±2 g/dL ranges around the facility-level Hb mean.</p

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Epigenome Microarray Platform for Proteome-Wide Dissection of Chromatin-Signaling Networks

Knowledge of protein domains that function as the biological effectors for diverse post-translational modifications of histones is critical for understanding how nuclear and epigenetic programs are established. Indeed, mutations of chromatin effector domains found within several proteins are associated with multiple human pathologies, including cancer and immunodeficiency syndromes. To date, relatively few effector domains have been identified in comparison to the number of modifications present on histone and non-histone proteins. Here we describe the generation and application of human modified peptide microarrays as a platform for high-throughput discovery of chromatin effectors and for epitope-specificity analysis of antibodies commonly utilized in chromatin research. Screening with a library containing a majority of the Royal Family domains present in the human proteome led to the discovery of TDRD7, JMJ2C, and MPP8 as three new modified histone-binding proteins. Thus, we propose that peptide microarray methodologies are a powerful new tool for elucidating molecular interactions at chromatin

Relation between body mass index and depression: a structural equation modeling approach

<p>Abstract</p> <p>Background</p> <p>Obesity and depression are two major diseases which are associated with many other health problems such as hypertension, dyslipidemia, diabetes mellitus, coronary heart disease, stroke, myocardial infarction, heart failure in patients with systolic hypertension, low bone mineral density and increased mortality. Both diseases share common health complications but there are inconsistent findings concerning the relationship between obesity and depression. In this work we used the <it>structural equation modeling </it>(SEM) technique to examine the relation between body mass index (BMI), as a proxy for obesity, and depression using the Canadian Community Health Survey, Cycle 1.2.</p> <p>Methods</p> <p>In this SEM model we postulate that 1) BMI and depression are directly related, 2) BMI is directly affected by the physical activity and, 3)depression is directly influenced by stress. SEM was also used to assess the relation between BMI and depression separately for males and females.</p> <p>Results</p> <p>The results indicate that higher BMI is associated with more severe form of depression. On the other hand, the more severe form of depression may result in less weight gain. However, the association between depression and BMI is gender dependent. In males, the higher BMI may result in a more severe form of depression while in females the relation may not be the same. Also, there was a negative relationship between physical activity and BMI.</p> <p>Conclusion</p> <p>In general, use of SEM method showed that the two major diseases, obesity and depression, are associated but the form of the relation is different among males and females. More research is necessary to further understand the complexity of the relationship between obesity and depression. It also demonstrated that SEM is a feasible technique for modeling the relation between obesity and depression.</p