Device Design Modifications Informed by In Vitro Testing of Bacterial Attachment Reduce Infection Rates of Cochlear Implants in Clinical Practice.

Recalcitrant chronic infections of implanted medical devices are often linked to the presence of biofilms. The prevention and treatment of medical device-associated infections is a major source of antibiotic use and driver of antimicrobial resistance globally. Lowering the incidence of infection in patients that receive implanted medical devices could therefore significantly improve antibiotic stewardship and reduce patient morbidity. Here we determined if modifying the design of an implantable medical device to reduce bacterial attachment, impacted the incidence of device-associated infections in clinical practice. Since the 1980s cochlear implants have provided long-term treatment of sensorineural hearing deficiency in hundreds of thousands of patients world-wide. Nonetheless, a relatively small number of devices are surgically explanted each year due to unresolvable infections. Features associated with the accumulation of bacteria on the Cochlear™ Nucleus® CI24RE™ model of cochlear implant devices were identified using both in vitro bacterial attachment assays and examination of explanted devices. Macro-scale design modifications that reduced bacterial attachment in vitro were incorporated into the design of the CI500™ and Profile™ series of Nucleus implant. Analyses of mandatory post-market vigilance data of 198,757 CI24RE and 123,084 CI500/Profile series implantation surgeries revealed that these design modifications correlated with significantly reduced infection rates. This study demonstrates that a design-centric approach aimed at mitigating bacterial attachment was a simple, and effective means of reducing infections associated with Cochlear Nucleus devices. This approach is likely to be applicable to improving the designs of other implantable medical devices to reduce device-associated infections

Influence of short and long term processes on SAR11 communities in open ocean and coastal systems

SAR11 bacteria dominate the surface ocean and are major players in converting fixed carbon back to atmospheric carbon dioxide. The SAR11 clade is comprised of niche-specialized ecotypes that display distinctive spatiotemporal transitions. We analyzed SAR11 ecotype seasonality in two long-term 16S rRNA amplicon time series representing different North Atlantic regimes: the Sargasso Sea (subtropical ocean-gyre; BATS) and the temperate coastal Western English Channel (WEC). Using phylogenetically resolved amplicon sequence variants (ASVs), we evaluated seasonal environmental constraints on SAR11 ecotype periodicity. Despite large differences in temperature and nutrient availability between the two sites, at both SAR11 succession was defined by summer and winter clusters of ASVs. The summer cluster was dominated by ecotype Ia.3 in both sites. Winter clusters were dominated by ecotypes Ib and IIa.A at BATS and Ia.1 and IIa.B at WEC. A 2-year weekly analysis within the WEC time series showed that the response of SAR11 communities to short-term environmental fluctuations was variable. In 2016, community shifts were abrupt and synchronized to environmental shifts. However, in 2015, changes were gradual and decoupled from environmental fluctuations, likely due to increased mixing from strong winds. We demonstrate that interannual weather variability disturb the pace of SAR11 seasonal progression

Pre-processing Agilent microarray data

<p>Abstract</p> <p>Background</p> <p>Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to quantify some of the sources of error that affect measurement of expression using Agilent arrays and to compare Agilent's Feature Extraction software with pre-processing methods that have become the standard for normalization of cDNA arrays. These include log transformation followed by loess normalization with or without background subtraction and often a between array scale normalization procedure. The larger goal is to define best study design and pre-processing practices for Agilent arrays, and we offer some suggestions.</p> <p>Results</p> <p>Simple loess normalization without background subtraction produced the lowest variability. However, without background subtraction, fold changes were biased towards zero, particularly at low intensities. ROC analysis of a spike-in experiment showed that differentially expressed genes are most reliably detected when background is not subtracted. Loess normalization and no background subtraction yielded an AUC of 99.7% compared with 88.8% for Agilent processed fold changes. All methods performed well when error was taken into account by t- or z-statistics, AUCs ≥ 99.8%. A substantial proportion of genes showed dye effects, 43% (99%<it>CI </it>: 39%, 47%). However, these effects were generally small regardless of the pre-processing method.</p> <p>Conclusion</p> <p>Simple loess normalization without background subtraction resulted in low variance fold changes that more reliably ranked gene expression than the other methods. While t-statistics and other measures that take variation into account, including Agilent's z-statistic, can also be used to reliably select differentially expressed genes, fold changes are a standard measure of differential expression for exploratory work, cross platform comparison, and biological interpretation and can not be entirely replaced. Although dye effects are small for most genes, many array features are affected. Therefore, an experimental design that incorporates dye swaps or a common reference could be valuable.</p

A nurse-led, preventive, psychological intervention to reduce PTSD symptom severity in critically ill patients: the POPPI feasibility study and cluster RCT

BACKGROUND: High numbers of patients experience severe acute stress in critical care units. Acute stress has been linked to post-critical care psychological morbidity, including post-traumatic stress disorder (PTSD). Previously, a preventive, complex psychological intervention [Psychological Outcomes following a nurse-led Preventative Psychological Intervention for critically ill patients (POPPI)] was developed by this research team, to be led by nurses, to reduce the development of PTSD symptom severity at 6 months. OBJECTIVES: The objectives were to (1) standardise and refine the POPPI intervention, and, if feasible, (2) evaluate it in a cluster randomised clinical trial (RCT). DESIGN: Two designs were used – (1) two feasibility studies to test the delivery and acceptability (to patients and staff) of the intervention, education package and support tools, and to test the trial procedures (i.e. recruitment and retention), and (2) a multicentre, parallel-group, cluster RCT with a baseline period and staggered roll-out of the intervention. SETTING: This study was set in NHS adult, general critical care units. PARTICIPANTS: The participants were adult patients who were > 48 hours in a critical care unit, receiving level 3 care and able to consent. INTERVENTIONS: The intervention comprised three elements – (1) creating a therapeutic environment in critical care, (2) three stress support sessions for patients identified as acutely stressed and (3) a relaxation and recovery programme for patients identified as acutely stressed. MAIN OUTCOMES MEASURES: Primary outcome – patient-reported symptom severity using the PTSD Symptom Scale – Self Report (PSS-SR) questionnaire (to measure clinical effectiveness) and incremental costs, quality-adjusted life-years (QALYs) and net monetary benefit at 6 months (to measure cost-effectiveness). Secondary outcomes – days alive and free from sedation to day 30; duration of critical care unit stay; PSS-SR score of > 18 points; depression, anxiety and health-related quality of life at 6 months; and lifetime cost-effectiveness. RESULTS: (1) A total of 127 participants were recruited to the intervention feasibility study from two sites and 86 were recruited to the RCT procedures feasibility study from another two sites. The education package, support tools and intervention were refined. (2) A total of 24 sites were randomised to the intervention or control arms. A total of 1458 participants were recruited. Twelve sites delivered the intervention during the intervention period: > 80% of patients received two or more stress support sessions and all 12 sites achieved the target of > 80% of clinical staff completing the POPPI online training. There was, however, variation in delivery across sites. There was little difference between baseline and intervention periods in the development of PTSD symptom severity (measured by mean PSS-SR score) at 6 months for surviving patients in either the intervention or the control group: treatment effect estimate −0.03, 95% confidence interval (CI) −2.58 to 2.52; p = 0.98. On average, the intervention decreased costs and slightly improved QALYs, leading to a positive incremental net benefit at 6 months (£835, 95% CI −£4322 to £5992), but with considerable statistical uncertainty surrounding these results. There were no significant differences between the groups in any of the secondary outcomes or in the prespecified subgroup analyses. LIMITATIONS: There was a risk of bias because different consent processes were used and as a result of the lack of blinding, which was mitigated as far as possible within the study design. The intervention started later than anticipated. Patients were not routinely monitored for delirium. CONCLUSIONS: Among level 3 patients who stayed > 48 hours in critical care, the delivery of a preventive, complex psychological intervention, led by nurses, did not reduce the development of PTSD symptom severity at 6 months, when compared with usual care. FUTURE WORK: Prior to development and evaluation of subsequent psychological interventions, there is much to learn from post hoc analyses of the cluster RCT rich quantitative and qualitative data. TRIAL REGISTRATION: This trial is registered as ISRCTN61088114 and ISRCTN53448131. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 23, No. 30. See the NIHR Journals Library website for further project information

puma: a Bioconductor package for propagating uncertainty in microarray analysis

BACKGROUND: Most analyses of microarray data are based on point estimates of expression levels and ignore the uncertainty of such estimates. By determining uncertainties from Affymetrix GeneChip data and propagating these uncertainties to downstream analyses it has been shown that we can improve results of differential expression detection, principal component analysis and clustering. Previously, implementations of these uncertainty propagation methods have only been available as separate packages, written in different languages. Previous implementations have also suffered from being very costly to compute, and in the case of differential expression detection, have been limited in the experimental designs to which they can be applied. RESULTS: puma is a Bioconductor package incorporating a suite of analysis methods for use on Affymetrix GeneChip data. puma extends the differential expression detection methods of previous work from the 2-class case to the multi-factorial case. puma can be used to automatically create design and contrast matrices for typical experimental designs, which can be used both within the package itself but also in other Bioconductor packages. The implementation of differential expression detection methods has been parallelised leading to significant decreases in processing time on a range of computer architectures. puma incorporates the first R implementation of an uncertainty propagation version of principal component analysis, and an implementation of a clustering method based on uncertainty propagation. All of these techniques are brought together in a single, easy-to-use package with clear, task-based documentation. CONCLUSION: For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. These methods can be used to improve results from more traditional analyses of microarray data. puma also offers improvements in terms of scope and speed of execution over previously available methods. puma is recommended for anyone working with the Affymetrix GeneChip platform for gene expression analysis and can also be applied more generally

A comprehensive re-analysis of the Golden Spike data: Towards a benchmark for differential expression methods

<p>Abstract</p> <p>Background</p> <p>The Golden Spike data set has been used to validate a number of methods for summarizing Affymetrix data sets, sometimes with seemingly contradictory results. Much less use has been made of this data set to evaluate differential expression methods. It has been suggested that this data set should not be used for method comparison due to a number of inherent flaws.</p> <p>Results</p> <p>We have used this data set in a comparison of methods which is far more extensive than any previous study. We outline six stages in the analysis pipeline where decisions need to be made, and show how the results of these decisions can lead to the apparently contradictory results previously found. We also show that, while flawed, this data set is still a useful tool for method comparison, particularly for identifying combinations of summarization and differential expression methods that are unlikely to perform well on real data sets. We describe a new benchmark, AffyDEComp, that can be used for such a comparison.</p> <p>Conclusion</p> <p>We conclude with recommendations for preferred Affymetrix analysis tools, and for the development of future spike-in data sets.</p

Evaluation of expressive writing for postpartum health: A randomized controlled trial

Pregnancy, birth and adjusting to a new baby is a potentially stressful time that can negatively affect the health of women. There is some evidence that expressive writing can have positive effects on psychological and physical health, particularly during stressful periods. The current study aimed to evaluate whether expressive writing would improve women’s postpartum health. A randomized controlled trial was conducted with three conditions: expressive writing (n=188), a control writing task (n=213), or normal care (n=163). Measures of psychological health, physical health and quality of life were measured at baseline (6-12 weeks postpartum), 1 month and 6 months later. Ratings of stress were taken before and after the expressive writing task. Intent-to-treat analyses showed no significant differences between women in the expressive writing, control writing and normal care groups on measures of physical health, anxiety, depression, mood or quality of life at 1 and 6 months. Uptake and adherence to the writing tasks was low. However, women in the expressive writing group rated their stress as significantly reduced after completing the task. Cost analysis suggest women who did expressive writing had the lowest costs in terms of healthcare service use and lowest cost per unit of improvement in quality of life. Results suggest expressive writing is not effective as a universal intervention for all women 6-12 weeks postpartum. Future research should examine expressive writing as a targeted intervention for women in high-risk groups, such as those with mild or moderate depression, and further examine cost-effectiveness

Difference-based clustering of short time-course microarray data with replicates

<p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p

Capivasertib, an AKT Kinase Inhibitor, as Monotherapy or in Combination With Fulvestrant in Patients With AKT1 E17K-Mutant, ER-Positive Metastatic Breast Cancer.

PURPOSE:The activating mutation AKT1 E17K occurs in ~7% of ER+ metastatic breast cancer (MBC). We report, from a multipart, first-in-human, Phase I study (NCT01226316), tolerability and activity of capivasertib, an oral AKT inhibitor, as monotherapy or combined with fulvestrant in expansion cohorts of AKT1 E17K-mutant ER+ MBC patients. PATIENTS AND METHODS:Patients with an AKT1 E17K mutation, detected by local (NGS) or central (plasma-based BEAMing) testing, received capivasertib 480 mg bid, 4 days on, 3 days off, weekly or 400 mg bid combined with fulvestrant at the labeled dose. Study endpoints included safety, objective response rate (ORR; RECIST v1.1), progression-free survival (PFS) and clinical benefit rate at 24 weeks (CBR24). Biomarker analyses were conducted in the combination cohort. RESULTS:From October 2013 to August 2018, 63 heavily pretreated patients received capivasertib (20 monotherapy, 43 combination). ORR was 20% with monotherapy, and within the combination cohort was 36% in fulvestrant-pretreated and 20% in fulvestrant-naïve patients, although this latter group may have had more aggressive disease at baseline. AKT1 E17K mutations were detectable in plasma by BEAMing (95%, 41/43), ddPCR (80%, 33/41) and NGS (76%, 31/41). A 50% decrease in AKT1 E17K at cycle 2 day 1 was associated with improved PFS. Combination therapy appeared more tolerable than monotherapy (most frequent grade ≥3 adverse events: rash [9% vs 20%], hyperglycemia [5% vs 30%], diarrhea [5% vs 10%]). CONCLUSIONS:Capivasertib demonstrated clinically meaningful activity in heavily pretreated AKT1 E17K-mutant ER+ MBC patients, including those with prior disease progression on fulvestrant. Tolerability and activity appeared improved by the combination