Statistical modelling of transcript profiles of differentially regulated genes

Background: The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA) and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results: Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Splitline" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t) = A + (B + Ct)Rt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data allowed 11% of the Escherichia coli features to be fitted by an exponential function, and 25% of the Rattus norvegicus features could be described by the critical exponential model, all with statistical significance of p < 0.05. Conclusion: The statistical non-linear regression approaches presented in this study provide detailed biologically oriented descriptions of individual gene expression profiles, using biologically variable data to generate a set of defining parameters. These approaches have application to the modelling and greater interpretation of profiles obtained across a wide range of platforms, such as microarrays. Through careful choice of appropriate model forms, such statistical regression approaches allow an improved comparison of gene expression profiles, and may provide an approach for the greater understanding of common regulatory mechanisms between genes

New approaches to investigating the function of mycelial networks

Fungi play a key role in ecosystem nutrient cycles by scavenging, concentrating, translocating and redistributing nitrogen. To quantify and predict fungal nitrogen redistribution, and assess the importance of the integrity of fungal networks in soil for ecosystem function, we need better understanding of the structures and processes involved. Until recently nitrogen translocation has been experimentally intractable owing to the lack of a suitable radioisotope tracer for nitrogen, and the impossibility of observing nitrogen translocation in real time under realistic conditions. We have developed an imaging method for recording the magnitude and direction of amino acid flow through the whole mycelial network as it captures, assimilates and channels its carbon and nitrogen resources, while growing in realistically heterogeneous soil microcosms. Computer analysis and modeling, based on these digitized video records, can reveal patterns in transport that suggest experimentally testable hypotheses. Experimental approaches that we are developing include genomics and stable isotope NMR to investigate where in the system nitrogen compounds are being acquired and stored, and where they are mobilized for transport or broken down. The results are elucidating the interplay between environment, metabolism, and the development and function of transport networks as mycelium forages in soil. The highly adapted and selected foraging networks of fungi may illuminate fundamental principles applicable to other supply networks

Grizzly Bear Scavenging of Carrion on the Northern Yellowstone Winter Range (1997-2012)

The Northern Yellowstone Winter Range (NYWR) in northwestern Wyoming and southwestern Montana is an important winter migratory destination for ungulates.  The NYWR is within the Greater Yellowstone Ecosystem (GYE), a landscape characterized by a complex ecological system of predators, scavengers, and ungulates.  Grizzly bears (Ursus arctos) are dominant members of the scavenging community throughout the spring.  However, little is known about factors associated with grizzly bear use of carcasses.  Of particular interest to managers is how habitat and anthropogenic factors are associated with carcass use.  Such information, for example, may be useful to manage spring recreation in important bear foraging areas to reduce conflict and support conservation efforts.  We used logistic regression to analyze spring survey data from 23 transects located in Yellowstone National Park and the Gallatin National Forest during 1997–2012, to identify factors associated with grizzly bear scavenging of winter- or predator-killed ungulates.  Multi-model inference was used to evaluate relative support for a set of a priori candidate models containing environmental and temporal correlates. Our preliminary findings showed support for models with distance to forest edge, road density, and elevation. Results indicated negative relationships between these factors and probability of carcass use.  Our results suggest that spatial heterogeneity in landscape-level habitat characteristics and human activity affect grizzly bear use of a valuable spring food source

Linking biodiversity into national economic accounting

Biodiversity underpins the supply of ecosystem services essential for well-being and economic development, yet biodiversity loss continues at a substantial rate. Linking biodiversity indicators with national economic accounts provides a means of mainstreaming biodiversity into economic planning and monitoring processes. Here we examine the various strategies for biodiversity indicators to be linked into national economic accounts, specifically the System of Environmental-Economic Accounts Experimental Ecosystem Accounting (SEEA EEA) framework. We present what has been achieved in practice, using various case studies from across the world. These case studies demonstrate the potential of economic accounting as an integrating, mainstreaming framework that explicitly considers biodiversity. With the right indicators for the different components of biodiversity and scales of biological organisation, this can directly support more holistic economic planning approaches. This will be a significant step forward from relying on the traditional indicators of national economic accounts to guide national planning. It is also essential if society’s objectives for biodiversity and sustainable development are to be met

How was it for you? Experiences of participatory design in the UK health service

Improving co-design methods implies that we need to understand those methods, paying attention to not only the effect of method choices on design outcomes, but also how methods affect the people involved in co-design. In this article, we explore participants' experiences from a year-long participatory health service design project to develop ‘Better Outpatient Services for Older People’. The project followed a defined method called experience-based design (EBD), which represented the state of the art in participatory service design within the UK National Health Service. A sample of participants in the project took part in semi-structured interviews reflecting on their involvement in and their feelings about the project. Our findings suggest that the EBD method that we employed was successful in establishing positive working relationships among the different groups of stakeholders (staff, patients, carers, advocates and design researchers), although conflicts remained throughout the project. Participants' experiences highlighted issues of wider relevance in such participatory design: cost versus benefit, sense of project momentum, locus of control, and assumptions about how change takes place in a complex environment. We propose tactics for dealing with these issues that inform the future development of techniques in user-centred healthcare design

In vitro Evidence That Combination Therapy With CD16-Bearing NK-92 Cells and FDA-Approved Alefacept Can Selectively Target the Latent HIV Reservoir in CD4+ CD2hi Memory T Cells

Elimination of the latent HIV reservoir remains the biggest hurdle to achieve HIV cure. In order to specifically eliminate HIV infected cells they must be distinguishable from uninfected cells. CD2 was recently identified as a potential marker enriched in the HIV-1 reservoir on CD4+ T cells, the largest, longest-lived and best-characterized constituent of the HIV reservoir. We previously proposed to repurpose FDA-approved alefacept, a humanized α-CD2 fusion protein, to reduce the HIV reservoir in CD2hi CD4+ memory T cells. Here, we show the first evidence that alefacept can specifically target and reduce CD2hi HIV infected cells in vitro. We explore a variety of natural killer (NK) cells as mediators of antibody-dependent cell-mediated cytotoxicity (ADCC) including primary NK cells, expanded NK cells as well as the CD16 transduced NK-92 cell line which is currently under study in clinical trials as a treatment for cancer. We demonstrate that CD16.NK-92 has a natural preference to kill CD2hi CD45RA– memory T cells, specifically CD45RA– CD27+ central memory/transitional memory (TCM/TM) subset in both healthy and HIV+ patient samples as well as to reduce HIV DNA from HIV+ samples from donors well controlled on antiretroviral therapy. Lastly, alefacept can combine with CD16.NK-92 to decrease HIV DNA in some patient samples and thus may yield value as part of a strategy toward sustained HIV remission

Dual-microcavity narrow-linewidth Brillouin laser

Ultralow-noise yet tunable lasers are a revolutionary tool in precision spectroscopy, displacement measurements at the standard quantum limit, and the development of advanced optical atomic clocks. Further applications include lidar, coherent communications, frequency synthesis, and precision sensors of strain, motion, and temperature. While all applications benefit from lower frequency noise, many also require a laser that is robust and compact. Here, we introduce a dual-microcavity laser that leverages one chip-integrable silica microresonator to generate tunable 1550 nm laser light via stimulated Brillouin scattering (SBS) and a second microresonator for frequency stabilization of the SBS light. This configuration reduces the fractional frequency noise to 7.8×10^(−14)  1/√Hz at 10 Hz offset, which is a new regime of noise performance for a microresonator-based laser. Our system also features terahertz tunability and the potential for chip-level integration. We demonstrate the utility of our dual-microcavity laser by performing spectral linewidth measurements with hertz-level resolution

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

Improving Access and Mental Health For Youth Using Smart Technologies

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14 and 25 years, with symptoms of anxiety and/or depression. This project includes 122 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using the Smart technology to enhance care. The technology uses mobile questionnaires (QnairesTM) to help promote self-assessment and track changes to support the plan of care. The youth were provided a smartphone and talk/text/data plan, if needed. The majority of participants identified themselves as Caucasian (73.5%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (73.6% and 66.9% respectively). Findings from the qualitative summary established that both staff and youth found having a smartphone and data plan beneficial. Demographic variables such as age, sex, mental health and physical health did not predict which youth were more likely to use the application