The role of accelerator programmes in supporting the adoption of digital health technologies: A qualitative study of the perspectives of small- and medium-sized enterprises

Objective Evidence-based digital health technologies are increasingly important in delivering care to an ageing population with constrained resources. In the United Kingdom, accelerator programmes (APs) have been developed to support the adoption of digital health technologies within the National Health Service. This study aims to explore the perspectives of stakeholders using APs. Methods Stakeholders representing nine small -and medium-sized enterprises (SMEs) that were engaged with three different APs ( n = 9). Semi-structured interviews were conducted with key informants between April and September 2018. Framework analysis of the data was performed to explore their perspectives on APs. Results Four key themes were generated. Informants reported the need to generate evidence before and during the programme, appreciating different types of evidence and their importance. Informants identified several key factors that were a catalyst for success, including involvement in the programme and access to individuals and organisations that were crucial for support. However, several barriers were identified at the programme and system levels. Finally, informants identified key supporting processes that enhanced the adoption of their innovations. Conclusion SMEs that develop digital health technologies report that, while APs are useful in supporting the adoption of these technologies, some issues remain. These relate to the emphasis on traditional research evidence that remains a challenge for SMEs to generate. Also, several system-level barriers to innovation in healthcare persist. As APs and SMEs continue to create an entrepreneurial ecosystem, there is increased potential for the development of supporting processes and infrastructure to accelerate the efficient and timely adoption of new digital health technologies

Triad3a induces the degradation of early necrosome to limit RipK1-dependent cytokine production and necroptosis.

Understanding the molecular signaling in programmed cell death is vital to a practical understanding of inflammation and immune cell function. Here we identify a previously unrecognized mechanism that functions to downregulate the necrosome, a central signaling complex involved in inflammation and necroptosis. We show that RipK1 associates with RipK3 in an early necrosome, independent of RipK3 phosphorylation and MLKL-induced necroptotic death. We find that formation of the early necrosome activates K48-ubiquitin-dependent proteasomal degradation of RipK1, Caspase-8, and other necrosomal proteins. Our results reveal that the E3-ubiquitin ligase Triad3a promotes this negative feedback loop independently of typical RipK1 ubiquitin editing enzymes, cIAPs, A20, or CYLD. Finally, we show that Triad3a-dependent necrosomal degradation limits necroptosis and production of inflammatory cytokines. These results reveal a new mechanism of shutting off necrosome signaling and may pave the way to new strategies for therapeutic manipulation of inflammatory responses

Asteroseismology

Asteroseismology is the determination of the interior structures of stars by using their oscillations as seismic waves. Simple explanations of the astrophysical background and some basic theoretical considerations needed in this rapidly evolving field are followed by introductions to the most important concepts and methods on the basis of example. Previous and potential applications of asteroseismology are reviewed and future trends are attempted to be foreseen.Comment: 38 pages, 13 figures, to appear in: "Planets, Stars and Stellar Systems", eds. T. D. Oswalt et al., Springer Verla

Radio emission from Supernova Remnants

The explosion of a supernova releases almost instantaneously about 10^51 ergs of mechanic energy, changing irreversibly the physical and chemical properties of large regions in the galaxies. The stellar ejecta, the nebula resulting from the powerful shock waves, and sometimes a compact stellar remnant, constitute a supernova remnant (SNR). They can radiate their energy across the whole electromagnetic spectrum, but the great majority are radio sources. Almost 70 years after the first detection of radio emission coming from a SNR, great progress has been achieved in the comprehension of their physical characteristics and evolution. We review the present knowledge of different aspects of radio remnants, focusing on sources of the Milky Way and the Magellanic Clouds, where the SNRs can be spatially resolved. We present a brief overview of theoretical background, analyze morphology and polarization properties, and review and critical discuss different methods applied to determine the radio spectrum and distances. The consequences of the interaction between the SNR shocks and the surrounding medium are examined, including the question of whether SNRs can trigger the formation of new stars. Cases of multispectral comparison are presented. A section is devoted to reviewing recent results of radio SNRs in the Magellanic Clouds, with particular emphasis on the radio properties of SN 1987A, an ideal laboratory to investigate dynamical evolution of an SNR in near real time. The review concludes with a summary of issues on radio SNRs that deserve further study, and analyzing the prospects for future research with the latest generation radio telescopes.Comment: Revised version. 48 pages, 15 figure

Social class and gender patterning of insomnia symptoms and psychiatric distress: a 20-year prospective cohort study

Background: Psychiatric distress and insomnia symptoms exhibit similar patterning by gender and socioeconomic position. Prospective evidence indicates a bi-directional relationship between psychiatric distress and insomnia symptoms so similarities in social patterning may not be coincidental. Treatment for insomnia can also improve distress outcomes. We investigate the extent to which the prospective patterning of distress over 20 years is associated with insomnia symptoms over that period.Methods: 999 respondents to the Twenty-07 Study had been followed for 20 years from approximately ages 36-57 (73.2% of the living baseline sample). Psychiatric distress was measured using the GHQ-12 at baseline and at 20-year follow-up. Gender and social class were ascertained at baseline. Insomnia symptoms were self-reported approximately every five years. Latent class analysis was used to classify patterns of insomnia symptoms over the 20 years. Structural Equation Models were used to assess how much of the social patterning of distress was associated with insomnia symptoms. Missing data was addressed with a combination of multiple-imputation and weighting.Results: Patterns of insomnia symptoms over 20 years were classified as either healthy, episodic, developing or chronic. Respondents from a manual social class were more likely to experience episodic, developing or chronic patterns than those from non-manual occupations but this was mostly explained by baseline psychiatric distress. People in manual occupations experiencing psychiatric distress however were particularly likely to experience chronic patterns of insomnia symptoms. Women were more likely to experience a developing pattern than men, independent of baseline distress. Psychiatric distress was more persistent over the 20 years for those in manual social classes and this effect disappeared when adjusting for insomnia symptoms. Irrespective of baseline symptoms, women, and especially those in a manual social class, were more likely than men to experience distress at age 57. This overall association for gender, but not the interaction with social class, was explained after adjusting for insomnia symptoms. Sensitivity analyses supported these findings.Conclusions: Gender and socioeconomic inequalities in psychiatric distress are strongly associated with inequalities in insomnia symptoms. Treatment of insomnia or measures to promote healthier sleeping may therefore help alleviate inequalities in psychiatric distress. © 2014 Green et al.; licensee BioMed Central Ltd

Epidermal growth factor suppresses induction by progestin of the adhesion protein desmoplakin in T47D breast cancer cells

INTRODUCTION: Although the effects of progesterone on cell cycle progression are well known, its role in spreading and adhesion of breast cancer cells has not attracted much attention until recently. Indeed, by controlling cell adhesion proteins, progesterone may play a direct role in breast cancer invasion and metastasis. Progesterone has also been shown to modulate epidermal growth factor (EGF) effects in neoplasia, although EGF effects on progesterone pathways and targets are less well understood. In the present study we identify an effect of EGF on a progesterone target, namely desmoplakin. METHODS: Initially flow cytometry was used to establish the growing conditions and demonstrate that the T47D breast cancer cell line was responding to progesterone and EGF in a classical manner. Differential display RT-PCR was employed to identify differentially expressed genes affected by progesterone and EGF. Western and Northern blotting were used to verify interactions between EGF and progesterone in three breast cancer cell lines: T47D, MCF-7, and ZR-75. RESULTS: We found the cell adhesion protein desmoplakin to be upregulated by progesterone – a process that was suppressed by EGF. This appears to be a general but not universal effect in breast cancer cell lines. CONCLUSION: Our findings suggest that progesterone and EGF may play opposing roles in metastasis. They also suggest that desmoplakin may be a useful biomarker for mechanistic studies designed to analyze the crosstalk between EGF and progesterone dependent events. Our work may help to bridge the fields of metastasis and differentiation, and the mechanisms of steroid action

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145

<p>Abstract</p> <p>Background</p> <p>Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state.</p> <p>Methods</p> <p>We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain answers to additional specific questions, we have added a new analysis targeted specifically to the detection of breakpoints.</p> <p>Results</p> <p>The reanalysis shows that the performance of our method is comparable to that of the other methods analyzed. In addition, we can provide probabilities of a given spot being a breakpoint, something unique among the methods examined.</p> <p>Conclusion</p> <p>Markov Chain Monte Carlo methods require using a sufficient number of iterations before they can be assumed to yield samples from the distribution of interest. Running our method with too small a number of iterations cannot be representative of its performance. Moreover, our analysis shows how our original approach can be easily adapted to answer specific additional questions (e.g., identify edges).</p

Anticancer Gene Transfer for Cancer Gene Therapy

Gene therapy vectors are among the treatments currently used to treat malignant tumors. Gene therapy vectors use a specific therapeutic transgene that causes death in cancer cells. In early attempts at gene therapy, therapeutic transgenes were driven by non-specific vectors which induced toxicity to normal cells in addition to the cancer cells. Recently, novel cancer specific viral vectors have been developed that target cancer cells leaving normal cells unharmed. Here we review such cancer specific gene therapy systems currently used in the treatment of cancer and discuss the major challenges and future directions in this field