Temperature Affects the Tripartite Interactions between Bacteriophage WO, Wolbachia, and Cytoplasmic Incompatibility

Wolbachia infections are a model for understanding intracellular, bacterial symbioses. While the symbiosis is often studied from a binary perspective of host and bacteria, it is increasingly apparent that additional trophic levels can influence the symbiosis. For example, Wolbachia in arthropods harbor a widespread temperate bacteriophage, termed WO, that forms virions and rampantly transfers between coinfections. Here we test the hypothesis that temperatures at the extreme edges of an insect's habitable range alter bacteriophage WO inducibility and in turn, Wolbachia densities and the penetrance of cytoplasmic incompatibility. We report four key findings using the model wasp, Nasonia vitripennis: First, both cold treatment at 18 C and heat treatment at 30 C reduce Wolbachia densities by as much as 74% relative to wasps reared at 25 C. Second, in all cases where Wolbachia densities decline due to temperature changes, phage WO densities increase and inversely associate with Wolbachia densities. Heat has a marked effect on phage WO, yielding phage densities that are 552% higher than the room temperature control. Third, there is a significant affect of insect family on phage WO and endoysmbiont densities. Fourth, at extreme temperatures, there was a temperature-mediated adjustment to the density threshold at which Wolbachia cause complete cytoplasmic incompatibility. Taken together, these results demonstrate that temperature simultaneously affects phage WO densities, endosymbiont densities, and the penetrance of cytoplasmic incompatibility. While temperature shock enhances bacteriophage inducibility and the ensuing bacterial mortality in a wide range of medically and industrially-important bacteria, this is the first investigation of the associations in an obligate intracellular bacteria. Implications to a SOS global sensing feedback mechanism in Wolbachia are discussed

Competing risk and heterogeneity of treatment effect in clinical trials

It has been demonstrated that patients enrolled in clinical trials frequently have a large degree of variation in their baseline risk for the outcome of interest. Thus, some have suggested that clinical trial results should routinely be stratified by outcome risk using risk models, since the summary results may otherwise be misleading. However, variation in competing risk is another dimension of risk heterogeneity that may also underlie treatment effect heterogeneity. Understanding the effects of competing risk heterogeneity may be especially important for pragmatic comparative effectiveness trials, which seek to include traditionally excluded patients, such as the elderly or complex patients with multiple comorbidities. Indeed, the observed effect of an intervention is dependent on the ratio of outcome risk to competing risk, and these risks – which may or may not be correlated – may vary considerably in patients enrolled in a trial. Further, the effects of competing risk on treatment effect heterogeneity can be amplified by even a small degree of treatment related harm. Stratification of trial results along both the competing and the outcome risk dimensions may be necessary if pragmatic comparative effectiveness trials are to provide the clinically useful information their advocates intend

Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal

Mounting evidence suggests that there is frequently considerable variation in the risk of the outcome of interest in clinical trial populations. These differences in risk will often cause clinically important heterogeneity in treatment effects (HTE) across the trial population, such that the balance between treatment risks and benefits may differ substantially between large identifiable patient subgroups; the "average" benefit observed in the summary result may even be non-representative of the treatment effect for a typical patient in the trial. Conventional subgroup analyses, which examine whether specific patient characteristics modify the effects of treatment, are usually unable to detect even large variations in treatment benefit (and harm) across risk groups because they do not account for the fact that patients have multiple characteristics simultaneously that affect the likelihood of treatment benefit. Based upon recent evidence on optimal statistical approaches to assessing HTE, we propose a framework that prioritizes the analysis and reporting of multivariate risk-based HTE and suggests that other subgroup analyses should be explicitly labeled either as primary subgroup analyses (well-motivated by prior evidence and intended to produce clinically actionable results) or secondary (exploratory) subgroup analyses (performed to inform future research). A standardized and transparent approach to HTE assessment and reporting could substantially improve clinical trial utility and interpretability

Internet-based search of randomised trials relevant to mental health originating in the Arab world

BACKGROUND: The internet is becoming a widely used source of accessing medical research through various on-line databases. This instant access to information is of benefit to busy clinicians and service users around the world. The population of the Arab World is comparable to that of the United States, yet it is widely believed to have a greatly contrasting output of randomised controlled trials related to mental health. This study was designed to investigate the existence of such research in the Arab World and also to investigate the availability of this research on-line. METHODS: Survey of findings from three internet-based potential sources of randomised trials originating from the Arab world and relevant to mental health care. RESULTS: A manual search of an Arabic online current contents service identified 3 studies, MEDLINE, EMBASE, and PsycINFO searches identified only 1 study, and a manual search of a specifically indexed, study-based mental health database, PsiTri, revealed 27 trials. CONCLUSION: There genuinely seem to be few trials from the Arab world and accessing these on-line was problematic. Replication of some studies that guide psychiatric/psychological practice in the Arab world would seem prudent

"Me's me and you's you": Exploring patients' perspectives of single patient (n-of-1) trials in the UK

BACKGROUND: The n-of-1 trial offers a more methodologically sound approach to determining optimum treatment for an individual patient than "trials of therapy" routinely conducted in clinical practice. However, such methodology is rarely used in the UK. This pilot study explores the acceptability of n-of-1 trials to patients in the UK. METHODS: Patients with osteoarthritis of the knee were recruited to their own 12-week n-of-1 trial comparing either two knee supports or an NSAID with simple analgesic. Patients were interviewed at the start and completion of their trial to explore reasons for participation, understanding of the trial design and experiences of participation. Daily diaries were completed to inform future treatment. RESULTS: Nine patients participated (5 supports, 4 drugs). Patients were keen to participate, believing that the trial may lead to personal gains such as improved symptom control and quality of life. However, recruitment to the pharmacological comparison was more difficult since this could also entail risk. All patients were eager to complete the trial, even when difficulties were encountered. Completing the daily diary provided some patients with greater insight into their condition, which allowed them to improve their self-management. The n-of-1 trial design was viewed as a 'logical' design offering an efficient method of reaching a personalised treatment decision tailored to suit individual needs and preferences. CONCLUSION: This pilot study suggests that patients perceive the n-of-1 trial as an acceptable approach to the individualisation of treatment. In addition, further benefits over and above any gained from the interventions can be derived from involvement in such a study

Cancer somatic mutations cluster in a subset of regulatory sites predicted from the ENCODE data

Background: Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. The ENCODE project has mapped potential regulatory sites across the complete genome in many cell types, and these regions have been shown to harbour many of the somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. The ENCODE data suggests a very large number of regulatory sites, and methods are needed to identify those that are most relevant and to connect them to the genes that they control. Methods: Predictive models of gene expression were developed by integrating the ENCODE data for regulation, including transcription factor binding and DNase1 hypersensitivity, with RNA-seq data for gene expression. A penalized regression method was used to identify the most predictive potential regulatory sites for each transcript. Known cancer somatic mutations from the COSMIC database were mapped to potential regulatory sites, and we examined differences in the mapping frequencies associated with sites chosen in regulatory models and other (rejected) sites. The effects of potential confounders, for example replication timing, were considered. Results: Cancer somatic mutations preferentially occupy those regulatory regions chosen in our models as most predictive of gene expression. Conclusion: Our methods have identified a significantly reduced set of regulatory sites that are enriched in cancer somatic mutations and are more predictive of gene expression. This has significance for the mechanistic interpretation of cancer mutations, and the understanding of genetic regulation

Chronic non-specific low back pain - sub-groups or a single mechanism?

Copyright 2008 Wand and O'Connell; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Low back pain is a substantial health problem and has subsequently attracted a considerable amount of research. Clinical trials evaluating the efficacy of a variety of interventions for chronic non-specific low back pain indicate limited effectiveness for most commonly applied interventions and approaches. Discussion: Many clinicians challenge the results of clinical trials as they feel that this lack of effectiveness is at odds with their clinical experience of managing patients with back pain. A common explanation for this discrepancy is the perceived heterogeneity of patients with chronic non-specific low back pain. It is felt that the effects of treatment may be diluted by the application of a single intervention to a complex, heterogeneous group with diverse treatment needs. This argument presupposes that current treatment is effective when applied to the correct patient. An alternative perspective is that the clinical trials are correct and current treatments have limited efficacy. Preoccupation with sub-grouping may stifle engagement with this view and it is important that the sub-grouping paradigm is closely examined. This paper argues that there are numerous problems with the sub-grouping approach and that it may not be an important reason for the disappointing results of clinical trials. We propose instead that current treatment may be ineffective because it has been misdirected. Recent evidence that demonstrates changes within the brain in chronic low back pain sufferers raises the possibility that persistent back pain may be a problem of cortical reorganisation and degeneration. This perspective offers interesting insights into the chronic low back pain experience and suggests alternative models of intervention. Summary: The disappointing results of clinical research are commonly explained by the failure of researchers to adequately attend to sub-grouping of the chronic non-specific low back pain population. Alternatively, current approaches may be ineffective and clinicians and researchers may need to radically rethink the nature of the problem and how it should best be managed

Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events

Stable Isotope Analysis Can Potentially Identify Completely-Digested Bloodmeals in Mosquitoes

Background: Vertebrate bloodfeeding is a critical component of a mosquito’s ability to transmit pathogens that cause diseases such as malaria, dengue fever and viral encephalitis. Due to degradation by the digestive process, current methods to identify mosquito bloodmeal sources are only useful for approximately 36 hours post-feeding. A critical need exists for technologies to extend this window and gain a more complete picture of mosquito feeding behavior for epidemiological studies. Stable isotopes are useful for investigating organism feeding behavior because the isotopic ratio of an organism’s tissues reflects that of the material it ingests. Methodology/Principal Findings: Proof-of-principle data indicates that after bloodfeeding, Aedes albopictus mosquitoes acquire diagnostic Carbon and Nitrogen stable isotope profiles from their vertebrate hosts that can be accurately identified one week post-feeding, approximately 4 days after the entire bloodmeal has been digested. Total C/N ratio served as a biomarker marker for bloodfeeding (P,0.02), while dN was the most informative variable which could distinguish between unfed, chicken-fed and human-fed mosquitoes (P,0.01). By plotting C/N vs. dN, all feeding treatments could be identified in a double-blind analysis. Conclusions/Significance: These proof-of-principle experiments indicate that analysis of stable isotopes can be used to distinguish bloodfed from unfed mosquitoes, and also distinguish between different vertebrate bloodmeal sources eve

Method for evaluating prediction models that apply the results of randomized trials to individual patients

<p>Abstract</p> <p>Introduction</p> <p>The clinical significance of a treatment effect demonstrated in a randomized trial is typically assessed by reference to differences in event rates at the group level. An alternative is to make individualized predictions for each patient based on a prediction model. This approach is growing in popularity, particularly for cancer. Despite its intuitive advantages, it remains plausible that some prediction models may do more harm than good. Here we present a novel method for determining whether predictions from a model should be used to apply the results of a randomized trial to individual patients, as opposed to using group level results.</p> <p>Methods</p> <p>We propose applying the prediction model to a data set from a randomized trial and examining the results of patients for whom the treatment arm recommended by a prediction model is congruent with allocation. These results are compared with the strategy of treating all patients through use of a net benefit function that incorporates both the number of patients treated and the outcome. We examined models developed using data sets regarding adjuvant chemotherapy for colorectal cancer and Dutasteride for benign prostatic hypertrophy.</p> <p>Results</p> <p>For adjuvant chemotherapy, we found that patients who would opt for chemotherapy even for small risk reductions, and, conversely, those who would require a very large risk reduction, would on average be harmed by using a prediction model; those with intermediate preferences would on average benefit by allowing such information to help their decision making. Use of prediction could, at worst, lead to the equivalent of an additional death or recurrence per 143 patients; at best it could lead to the equivalent of a reduction in the number of treatments of 25% without an increase in event rates. In the Dutasteride case, where the average benefit of treatment is more modest, there is a small benefit of prediction modelling, equivalent to a reduction of one event for every 100 patients given an individualized prediction.</p> <p>Conclusion</p> <p>The size of the benefit associated with appropriate clinical implementation of a good prediction model is sufficient to warrant development of further models. However, care is advised in the implementation of prediction modelling, especially for patients who would opt for treatment even if it was of relatively little benefit.</p