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Abstract Background Human T cell lymphotropic virus type 1 (HTLV-1) infection remains a largely neglected public health problem, particularly in resource-poor areas with high burden of communicable and non-communicable diseases, such as some remote populations in Central Australia where an estimated 37% of adults are infected with HTLV-1. Most of our understanding of HTLV-1 infection comes from studies of the globally spread subtype-A (HTLV-1a), with few molecular studies reported with the Austral-Melanesian subtype-C (HTLV-1c) predominant in the Indo-Pacific and Oceania regions. Results Using a primer walking strategy and direct sequencing, we constructed HTLV-1c genomic consensus sequences from 22 First Nations participants living with HTLV-1c in Central Australia. Phylogenetic and pairwise analysis of this subtype-C proviral gDNA showed higher levels of genomic divergence in comparison to previously published HTLV-1a genomes. While the overall genomic homology between subtypes was 92.5%, the lowest nucleotide and amino acid sequence identity occurred near the 3′ end of the proviral genome coding regulatory genes, especially overlapping hbz (85.37%, 77.46%, respectively) and orf-I product p12 (82.00%, 70.30%, respectively). Strikingly, the HTLV-1c genomic consensus sequences uniformly showed a defective translation start codon for the immune regulatory proteins p12/p8 encoded by the HTLV-1A orf-I. Deletions in the proviral genome were detected in many subjects, particularly in the structural gag, pol and env genes. Similarly, using a droplet digital PCR assay measuring the copies of gag and tax per reference host genome, we quantitatively confirmed that provirus retains the tax gene region at higher levels than gag. Conclusions Our genomic analysis of HTLV-1c in Central Australia in conjunction with earlier Melanesian HTLV-1c sequences, elucidate substantial differences with respect to the globally spread HTLV-1a. Future studies should address the impact these genomic differences have on infection and the regionally distinctive frequency of associated pulmonary disease. Understanding the host and virus subtype factors which contribute to the differential morbidity observed, is crucial for the development of much needed therapeutics and vaccine strategies against this highly endemic infection in remote First Nations communities in Central Australia.

Abstract Background HIV-1 infects a wide range of CD4+ T cells with different phenotypic properties and differing expression levels of entry coreceptors. We sought to determine the viral tropism of subtype C (C-HIV) Envelope (Env) clones for different CD4+ T cell subsets and whether tropism changes during acute to chronic disease progression. HIV-1 envs were amplified from the plasma of five C-HIV infected women from three untreated time points; less than 2 months, 1-year and 3-years post-infection. Pseudoviruses were generated from Env clones, phenotyped for coreceptor usage and CD4+ T cell subset tropism was measured by flow cytometry. Results A total of 50 C-HIV envs were cloned and screened for functionality in pseudovirus infection assays. Phylogenetic and variable region characteristic analysis demonstrated evolution in envs between time points. We found 45 pseudoviruses were functional and all used CCR5 to mediate entry into NP2/CD4/CCR5 cells. In vitro infection assays showed transitional memory (TM) and effector memory (EM) CD4+ T cells were more frequently infected (median: 46% and 25% of total infected CD4+ T cells respectively) than naïve, stem cell memory, central memory and terminally differentiated cells. This was not due to these subsets contributing a higher proportion of the CD4+ T cell pool, rather these subsets were more susceptible to infection (median: 5.38% EM and 2.15% TM cells infected), consistent with heightened CCR5 expression on EM and TM cells. No inter- or intra-participant changes in CD4+ T cell subset tropism were observed across the three-time points. Conclusions CD4+ T cell subsets that express more CCR5 were more susceptible to infection with C-HIV Envs, suggesting that these may be the major cellular targets during the first 3 years of infection. Moreover, we found that viral tropism for different CD4+ T cell subsets in vitro did not change between Envs cloned from acute to chronic disease stages. Finally, central memory, naïve and stem cell memory CD4+ T cell subsets were susceptible to infection, albeit inefficiently by Envs from all time-points, suggesting that direct infection of these cells may help establish the latent reservoir early in infection.

Abstract Background We wished to compare the nuisance parameters of pediatric vs. adult randomized-trials (RCTs) and determine if the latter can be used in sample size computations of the former. Methods In this meta-epidemiologic empirical evaluation we examined meta-analyses from the Cochrane Database of Systematic-Reviews, with at least one pediatric-RCT and at least one adult-RCT. Within each meta-analysis of binary efficacy-outcomes, we calculated the pooled-control-group event-rate (CER) across separately all pediatric and adult-trials, using random-effect models and subsequently calculated the control-group event-rate risk-ratio (CER-RR) of the pooled-pediatric-CERs vs. adult-CERs. Within each meta-analysis with continuous outcomes we calculated the pooled-control-group effect standard deviation (CE-SD) across separately all pediatric and adult-trials and subsequently calculated the CE-SD-ratio of the pooled-pediatric-CE-SDs vs. adult-CE-SDs. We then calculated across all meta-analyses the pooled-CER-RRs and pooled-CE-SD-ratios (primary endpoints) and the pooled-magnitude of effect-sizes of CER-RRs and CE-SD-ratios using REMs. A ratio

Abstract Background Pragmatic clinical trials embedded in routine delivery of clinical care can lead to improvements in quality of care, but often have design features that raise ethical concerns. Methods We performed a discrete choice experiment and used conjoint analysis to assess how specific attributes of pragmatic dialysis trials influenced patients’ and physicians’ willingness to have their dialysis facility participate in a hypothetical trial of hypertension management. Electronic survey data were collected from 200 patients enrolled from 11 outpatient hemodialysis units and from 203 nephrologists. The three attributes studied were physicians’ treatment autonomy, participants’ research burden, and the approach to consent. The influence of each attribute was quantified using mixed-effects logistic regression. Results Similar proportions of patients were willing to have their facilities participate in a trial with high vs. low physician autonomy (77% vs. 79%; p = 0.13) and research burden (76% vs. 80%; p = 0.06). Opt-in, opt-out, and notification-only consent approaches were acceptable to most patients (84%, 82%, and 81%, respectively), but compared to each of these consent approaches, fewer patients (66%) were willing to have their facility participate in a trial that used no notification (p

Abstract Background To identify safety signals by manual review of individual report in large surveillance databases is time consuming; such an approach is very unlikely to reveal complex relationships between medications and adverse events. Since the late 1990s, efforts have been made to develop data mining tools to systematically and automatically search for safety signals in surveillance databases. Influenza vaccines present special challenges to safety surveillance because the vaccine changes every year in response to the influenza strains predicted to be prevalent that year. Therefore, it may be expected that reporting rates of adverse events following flu vaccines (number of reports for a specific vaccine-event combination/number of reports for all vaccine-event combinations) may vary substantially across reporting years. Current surveillance methods seldom consider these variations in signal detection, and reports from different years are typically collapsed together to conduct safety analyses. However, merging reports from different years ignores the potential heterogeneity of reporting rates across years and may miss important safety signals. Method Reports of adverse events between years 1990 to 2013 were extracted from the Vaccine Adverse Event Reporting System (VAERS) database and formatted into a three-dimensional data array with types of vaccine, groups of adverse events and reporting time as the three dimensions. We propose a random effects model to test the heterogeneity of reporting rates for a given vaccine-event combination across reporting years. The proposed method provides a rigorous statistical procedure to detect differences of reporting rates among years. We also introduce a new visualization tool to summarize the result of the proposed method when applied to multiple vaccine-adverse event combinations. Result We applied the proposed method to detect safety signals of FLU3, an influenza vaccine containing three flu strains, in the VAERS database. We showed that it had high statistical power to detect the variation in reporting rates across years. The identified vaccine-event combinations with significant different reporting rates over years suggested potential safety issues due to changes in vaccines which require further investigation. Conclusion We developed a statistical model to detect safety signals arising from heterogeneity of reporting rates of a given vaccine-event combinations across reporting years. This method detects variation in reporting rates over years with high power. The temporal trend of reporting rate across years may reveal the impact of vaccine update on occurrence of adverse events and provide evidence for further investigations.

Between 1999 and 2003 we collected information on the breeding distribution and abundance of 12 seabird species occurring on nine islands off the coasts of north and central Chile (27°-33°S). The Peruvian booby Sula variegata was the most abundant seabird with a breeding population of ca. 18,000 pairs concentrated in two islands, followed by the Humboldt penguin Spheniscus humboldti with ca. 9,000 pairs, the largest colony being at Chañaral Island with ca. 7,000 pairs. Kelp gulls Larus dominicanus bred at all the surveyed sites in colonies of variable size, ranging from 40 to 2,000 pairs. Peruvian diving-petrels Pelecanoides garnotii and Peruvian pelicans Pelecanus occidentalis bred at restricted sites, but generally in large colonies. Magellanic penguins Spheniscus magellanicus, wedge-rumped storm-petrels Oceanodroma tethys, Neotropical cormorants Hypoleucos brasiliensis, guanay cormorants Leucocarbo bougainvillii, red-legged cormorants Stictocarbo gairmardi, band-tailed gulls Larus belcheri and Inca terns Larosterna inca nested at few sites forming small colonies (from a few to 150 pairs). Two new breeding sites are reported for the Peruvian diving-petrel and nesting of the wedge-rumped storm-petrel is confirmed on the Chilean coast for the first time. Despite protective status, most of the islands showed human disturbance, derived mainly from guano harvesting, egging and tourism. On at least five of these islands we were able to confirm introduced mammals including rats, rabbits and cats. These factors are likely to be detrimental to seabirds and thus demand detailed assessment. Further comprehensive ornithological surveys in other areas are needed so as to improve the scarce knowledge that we currently have on the seabird populations along the Chilean coast

Abstract Background SOLAR II is the 2nd follow-up of a population-based cohort study that follows the participants of ISAAC Phase Two recruited in Munich and Dresden in 1995/6. A first follow-up study was conducted 2002 and 2003 (SOLAR I). The aims of SOLAR II were to investigate the course of atopic diseases over puberty taking environmental and occupational risk factors into account. This paper describes the methods of the 2nd follow-up carried out from 2007 to 2009 and the challenges we faced while studying a population-based cohort of young adults. Methods Wherever possible, the same questionnaire instruments were used throughout the studies. They included questions on respiratory and allergic diseases, domestic and occupational exposure and work related stress. Furthermore, clinical examinations including skin prick tests, spirometry and bronchial challenge with methacholine, exhaled nitric oxide (FeNO) and blood samples were employed at baseline and 2nd follow-up. As information from three studies was available, multiple imputation could be used to handle missing data. Results Of the 3053 SOLAR I study participants who had agreed to be contacted again, about 50% had moved in the meantime and had to be traced using phone directories and the German population registries. Overall, 2904 of these participants could be contacted on average five years after the first follow-up. From this group, 2051 subjects (71%) completed the questionnaire they received via mail. Of these, 57% participated at least in some parts of the clinical examinations. Challenges faced included the high mobility of this age group. Time constraints and limited interest in the study were substantial. Analysing the results, selection bias had to be considered as questionnaire responders (54%) and those participating in the clinical part of the study (63%) were more likely to have a high parental level of education compared to non-participants (42%). Similarly, a higher prevalence of parental atopy (e.g. allergic rhinitis) at baseline was found for participants in the questionnaire part (22%) and those participating in the clinical part of the study (27%) compared to non-participants (11%). Conclusions In conclusion, a 12-year follow-up from childhood to adulthood is feasible resulting in a response of 32% of the baseline population. However, our experience shows that researchers need to allocate more time to the field work when studying young adults compared to other populations.

Abstract Background There is currently much interest in pharmacogenetics: determining variation in genes that regulate drug effects, with a particular emphasis on improving drug safety and efficacy. The ability to determine such variation motivates the application of personalized drug therapies that utilize a patient's genetic makeup to determine a safe and effective drug at the correct dose. To ascertain whether a genotype-guided drug therapy improves patient care, a personalized medicine intervention may be evaluated within the framework of a randomized controlled trial. The statistical design of this type of personalized medicine intervention requires special considerations: the distribution of relevant allelic variants in the study population; and whether the pharmacogenetic intervention is equally effective across subpopulations defined by allelic variants. Methods The statistical design of the Clarification of Optimal Anticoagulation through Genetics (COAG) trial serves as an illustrative example of a personalized medicine intervention that uses each subject's genotype information. The COAG trial is a multicenter, double blind, randomized clinical trial that will compare two approaches to initiation of warfarin therapy: genotype-guided dosing, the initiation of warfarin therapy based on algorithms using clinical information and genotypes for polymorphisms in CYP2C9 and VKORC1; and clinical-guided dosing, the initiation of warfarin therapy based on algorithms using only clinical information. Results We determine an absolute minimum detectable difference of 5.49% based on an assumed 60% population prevalence of zero or multiple genetic variants in either CYP2C9 or VKORC1 and an assumed 15% relative effectiveness of genotype-guided warfarin initiation for those with zero or multiple genetic variants. Thus we calculate a sample size of 1238 to achieve a power level of 80% for the primary outcome. We show that reasonable departures from these assumptions may decrease statistical power to 65%. Conclusions In a personalized medicine intervention, the minimum detectable difference used in sample size calculations is not a known quantity, but rather an unknown quantity that depends on the genetic makeup of the subjects enrolled. Given the possible sensitivity of sample size and power calculations to these key assumptions, we recommend that they be monitored during the conduct of a personalized medicine intervention. Trial Registration clinicaltrials.gov: NCT00839657

Abstract There is increasing concern among many in the medical arena about the extent to which the effects of treatment, either good or bad, apply to specific subgroups of individuals. Women comprise one of the most frequently considered 'subgroups' of patients. In the 1980s, much political attention was focused on concerns about equity in the research enterprise. In this paper, we briefly describe the statutory approaches to achieving equity in research, beginning with The NIH Revitalization Act of 1993. We go on to describe clinical, methodological and political factors affecting these discussions. We conclude that the controversy over the inclusion of women in clinical trials probably stems, in part, from theoretical concerns about gender differences in treatment effects and, in part, by legitimate fears of exposing fetuses to investigational drugs. However, we believe that the broader issue centres on biological factors, possibly defined by genes or gene expression, that may directly or indirectly modify the effect of specific treatments on specific individuals. A growing concern of physicians, regulators, healthcare policy makers and patients is the extent to which the effects of treatment, both good and bad, apply to specific subgroups. Do results of clinical trials apply consistently and equally across all clinically meaningful subclasses of patients enrolled in the studies? Can the results of those studies be extrapolated to patients or types of patients who did not participate in the original research? Reliable data on these issues are rarely available at the time of drug approval and are more difficult to generate once the drug is on the market and readily available.