The antimicrobial polymer PHMB enters cells and selectively condenses bacterial chromosomes

To combat infection and antimicrobial resistance, it is helpful to elucidate drug mechanism(s) of action. Here we examined how the widely used antimicrobial polyhexamethylene biguanide (PHMB) kills bacteria selectively over host cells. Contrary to the accepted model of microbial membrane disruption by PHMB, we observed cell entry into a range of bacterial species, and treated bacteria displayed cell division arrest and chromosome condensation, suggesting DNA binding as an alternative antimicrobial mechanism. A DNA-level mechanism was confirmed by observations that PHMB formed nanoparticles when mixed with isolated bacterial chromosomal DNA and its effects on growth were suppressed by pairwise combination with the DNA binding ligand Hoechst 33258. PHMB also entered mammalian cells, but was trapped within endosomes and excluded from nuclei. Therefore, PHMB displays differential access to bacterial and mammalian cellular DNA and selectively binds and condenses bacterial chromosomes. Because acquired resistance to PHMB has not been reported, selective chromosome condensation provides an unanticipated paradigm for antimicrobial action that may not succumb to resistance

Sample size calculations for cluster randomised controlled trials with a fixed number of clusters

Background\ud Cluster randomised controlled trials (CRCTs) are frequently used in health service evaluation. Assuming an average cluster size, required sample sizes are readily computed for both binary and continuous outcomes, by estimating a design effect or inflation factor. However, where the number of clusters are fixed in advance, but where it is possible to increase the number of individuals within each cluster, as is frequently the case in health service evaluation, sample size formulae have been less well studied. \ud \ud Methods\ud We systematically outline sample size formulae (including required number of randomisation units, detectable difference and power) for CRCTs with a fixed number of clusters, to provide a concise summary for both binary and continuous outcomes. Extensions to the case of unequal cluster sizes are provided. \ud \ud Results\ud For trials with a fixed number of equal sized clusters (k), the trial will be feasible provided the number of clusters is greater than the product of the number of individuals required under individual randomisation ($n_i$) and the estimated intra-cluster correlation ($\rho$). So, a simple rule is that the number of clusters ($\kappa$) will be sufficient provided: \ud \ud $\kappa$ > $n_i$ x $\rho$\ud \ud Where this is not the case, investigators can determine the maximum available power to detect the pre-specified difference, or the minimum detectable difference under the pre-specified value for power. \ud \ud Conclusions\ud Designing a CRCT with a fixed number of clusters might mean that the study will not be feasible, leading to the notion of a minimum detectable difference (or a maximum achievable power), irrespective of how many individuals are included within each cluster. \ud \u

Measurement error in a multi-level analysis of air pollution and health: a simulation study.

BACKGROUND: Spatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health. METHODS: Our study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of "true" site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009-2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and "true" data and the ratio of their variances (model versus "true") and assumed these parameters were the same spatially and temporally. RESULTS: In general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1. CONCLUSION: While our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and "true" data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models

Role of surface nickel content on human cell cytoskeleton formation on Nitinol

Cell activity on an implant surface can be modulated by cues such as topography, chemistry or stiffness(1,2). For Ni-Ti alloy this is achieved mainly by alteration in chemistry. However, high nickel concentrations may be a concern in the use Nitinol on a larger scale. Current reports on Nitinol bring contradictory data(3-5) suggesting that high nickel content is not particularly dangerous and nickel-titanium alloys are safe to be used. On the other hand it was shown that nickel has a toxic effects on cells(6). Nevertheless, shape memory effects and pseudo-elasticity could support different treatments (e.g. scoliosis) and currently, Nitinol is used to produce porous foams and coatings (Actipore™), pins, clamps and intramedullary nails. In this paper authors investigated a role for nickel surface concentration on influencing cell behaviour e.g. cytoskeleton formation and organization in vitro

Costs of Measuring Outcomes of Acute Hospital Care in a Longitudinal Outcomes Measurement System

It is widely acknowledged that the measurement of outcomes of care and the comparison of outcomes over time within health care providers and risk-adjusted comparisons among providers are important parts of improving quality and cost-effectiveness of care. However, few studies have assessed the costs of measuring outcomes of care. We sought to evaluate the personnel and financial resources spent for a prospective assessment of outcomes of acute hospital care by health professionals in internal medicine. The study included 15 primary care hospitals participating in a longitudinal outcomes measurement program and 2005 patients over an assessment period with an average duration of 6 months. Each hospital project manager participated in a previously-tested structured 30-minute telephone interview. Outcome measures include time spent by the individual job titles in implementing and running the outcomes measurement program. Job-title-specific times were used to calculate costs from the hospitals' perspective. One-time costs (C2132 + 1352) and administrative costs (95 97 per week) varied substantially. Costs per patient were fairly stable at around 20. We estimated that the total cost for each hospital to assess outcomes of care for accreditation (10 tracer diagnoses over 6 months) would be 9700 and that continuous monitoring of outcomes (5 tracer diagnoses) would cost 12,400 per year. This study suggests that outcomes of acute hospital care can be assessed with limited resources and that standardized training programs would reduce variability in overall costs. This study should help hospital decision makers to estimate the necessary funding for outcomes measurement initiatives

Ruthenium polypyridyl complexes and their modes of interaction with DNA : is there a correlation between these interactions and the antitumor activity of the compounds?

Various interaction modes between a group of six ruthenium polypyridyl complexes and DNA have been studied using a number of spectroscopic techniques. Five mononuclear species were selected with formula [Ru(tpy) L1L2](2-n)?, and one closely related dinuclear cation of formula [{Ru(apy)(tpy)}2{l-H2N(CH2)6NH2}]4?. The ligand tpy is 2,20:60,200-terpyridine and the ligand L1 is a bidentate ligand, namely, apy (2,20-azobispyridine), 2-phenylazopyridine, or 2-phenylpyridinylmethylene amine. The ligand L2 is a labile monodentate ligand, being Cl-, H2O, or CH3CN. All six species containing a labile L2 were found to be able to coordinate to the DNA model base 9-ethylguanine by 1H NMR and mass spectrometry. The dinuclear cationic species, which has no positions available for coordination to a DNA base, was studied for comparison purposes. The interactions between a selection of four representative complexes and calf-thymus DNA were studied by circular and linear dichroism. To explore a possible relation between DNA-binding ability and toxicity, all compounds were screened for anticancer activity in a variety of cancer cell lines, showing in some cases an activity which is comparable to that of cisplatin. Comparison of the details of the compound structures, their DNA binding, and their toxicity allows the exploration of structure–activity relationships that might be used to guide optimization of the activity of agents of this class of compounds

A mechanistic model of infection: why duration and intensity of contacts should be included in models of disease spread

<p>Abstract</p> <p>Background</p> <p>Mathematical models and simulations of disease spread often assume a constant per-contact transmission probability. This assumption ignores the heterogeneity in transmission probabilities, e.g. due to the varying intensity and duration of potentially contagious contacts. Ignoring such heterogeneities might lead to erroneous conclusions from simulation results. In this paper, we show how a mechanistic model of disease transmission differs from this commonly used assumption of a constant per-contact transmission probability.</p> <p>Methods</p> <p>We present an exposure-based, mechanistic model of disease transmission that reflects heterogeneities in contact duration and intensity. Based on empirical contact data, we calculate the expected number of secondary cases induced by an infector (i) for the mechanistic model and (ii) under the classical assumption of a constant per-contact transmission probability. The results of both approaches are compared for different basic reproduction numbers <it>R</it>₀.</p> <p>Results</p> <p>The outcomes of the mechanistic model differ significantly from those of the assumption of a constant per-contact transmission probability. In particular, cases with many different contacts have much lower expected numbers of secondary cases when using the mechanistic model instead of the common assumption. This is due to the fact that the proportion of long, intensive contacts decreases in the contact dataset with an increasing total number of contacts.</p> <p>Conclusion</p> <p>The importance of highly connected individuals, so-called super-spreaders, for disease spread seems to be overestimated when a constant per-contact transmission probability is assumed. This holds particularly for diseases with low basic reproduction numbers. Simulations of disease spread should weight contacts by duration and intensity.</p

A combinatorial TIR1/AFB–Aux/IAA co-receptor system for differential sensing of auxin

The plant hormone auxin regulates virtually every aspect of plant growth and development. Auxin acts by binding the F-box protein transport inhibitor response 1 (TIR1) and promotes the degradation of the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) transcriptional repressors. Here we show that efficient auxin binding requires assembly of an auxin co-receptor complex consisting of TIR1 and an Aux/IAA protein. Heterologous experiments in yeast and quantitative IAA binding assays using purified proteins showed that different combinations of TIR1 and Aux/IAA proteins form co-receptor complexes with a wide range of auxin-binding affinities. Auxin affinity seems to be largely determined by the Aux/IAA. As there are 6 TIR1/AUXIN SIGNALING F-BOX proteins (AFBs) and 29 Aux/IAA proteins in Arabidopsis thaliana, combinatorial interactions may result in many co-receptors with distinct auxin-sensing properties. We also demonstrate that the AFB5–Aux/IAA co-receptor selectively binds the auxinic herbicide picloram. This co-receptor system broadens the effective concentration range of the hormone and may contribute to the complexity of auxin response

Cancer mortality in 13 to 29-year-olds in England and Wales, 1981–2005

We examined cancer mortality at ages 13–29 years in England and Wales between 1981 and 2005, a total of 20 026 deaths over approximately 303 million person-years (mpy) at risk by sex, age group and time period. Overall, the mortality rate was 65.6 per mpy. Malignant neoplasms of the central nervous system showed the highest rate (8.5), followed by myeloid and monocytic leukaemia (6.6), lymphoid leukaemia (6.4), malignant bone tumours (5.4) and non-Hodgkin's lymphoma (5.2). These groups together accounted for almost 50% of all cancer deaths. The mortality rate for males (72.4) was 23% higher than for females (58.6) (P-value <0.0001). Males showed significantly higher mortality rates than females in almost all diagnostic groups, in general, mortality increasing with age (P-value <0.0001). There were significant decreases in mortality over time, the annual percentage change between 1981 and 2005 being minus 1.86 (95% confidence interval −2.09 to −1.62). Cancer groups with the highest mortality differed from those with the highest incidence

Profound and Sustained Reduction in Chlamydia trachomatis in The Gambia: A Five-Year Longitudinal Study of Trachoma Endemic Communities

Trachoma is the most common infectious cause of blindness worldwide. Mass antibiotic treatment with azithromycin is used to control ocular Chlamydia trachomatis infection. There is uncertainty over how frequently and for how long treatment is needed, particularly in low prevalence settings. This study examines the effect of a single round of treatment on clinical disease and infection in a cluster of trachoma endemic Gambian villages over a five-year period. These villages had good water supplies and sanitation improved part way through the study. We found treatment was followed by a marked decline in infection prevalence (by PCR) to less than 1%. The decline in prevalence of active disease in children was less marked. Several villages had a prevalence of active trachoma in 1 to 9 year old children of greater than 10% during the follow-up period, mostly in the absence of detectable infection. The implication of this study is that a single, high coverage mass treatment may be sufficient to control C. trachomatis infection in a low prevalence setting, particularly when combined with environmental measures to limit transmission. However, relying on clinical signs to guide treatment decisions is likely to lead to significant amounts of over treatment where current guidelines are implemented