85 research outputs found
Multiscale Hy3S: Hybrid stochastic simulation for supercomputers
BACKGROUND: Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. RESULTS: Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users create biological systems and analyze data. We demonstrate the accuracy and efficiency of Hy3S with examples, including a large-scale system benchmark and a complex bistable biochemical network with positive feedback. The software itself is open-sourced under the GPL license and is modular, allowing users to modify it for their own purposes. CONCLUSION: Hy3S is a powerful suite of simulation programs for simulating the stochastic dynamics of networks of biochemical reactions. Its first public version enables computational biologists to more efficiently investigate the dynamics of realistic biological systems
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Short-term and working memory treatments for improving sentence comprehension in aphasia: a review and a replication study
Although the roles of verbal short-term and working memory on spoken sentence comprehension skills in persons with aphasia have been debated for many years, the development of treatments to mitigate verbal short-term and working memory deficits as a way of improving spoken sentence comprehension is a new avenue in treatment research. In this article, we review and critically appraise this emerging evidence base. We also present new data from five persons with aphasia of a replication of a previously reported treatment that had resulted in some improvement of spoken sentence comprehension in a person with aphasia. The replicated treatment did not result in improvements in sentence comprehension. We forward recommendations for future research in this, admittedly weak at present, but important clinical research avenue that would help improve our understanding of the mechanisms of improvement of short-term and working memory training in relation to sentence comprehension
Model-Driven Designs of an Oscillating Gene Network
ABSTRACT The current rapid expansion of biological knowledge offers a great opportunity to rationally engineer biological systems that respond to signals such as light and chemical inducers by producing specific proteins. Turning on and off the production of proteins on demand holds great promise for creating significant biotechnological and biomedical applications. With successful stories already registered, the challenge still lies with rationally engineering gene regulatory networks which, like electronic circuits, sense inputs and generate desired outputs. From the literature, we have found kinetic and thermodynamic information describing the molecular components and interactions of the transcriptionally repressing lac, tet, and ara operons. Connecting these components in a model gene network, we determine how to change the kinetic parameters to make this normally nonperiodic system one which has well-defined oscillations. Simulating the designed lac-tet-ara gene network using a hybrid stochastic-discrete and stochastic-continuous algorithm, we seek to elucidate the relationship between the strength and type of specific connections in the gene network and the oscillatory nature of the protein product. Modeling the molecular components of the gene network allows the simulation to capture the dynamics of the real biological system. Analyzing the effect of modifications at this level provides the ability to predict how changes to experimental systems will alter the network behavior, while saving the time and expense of trial and error experimental modifications
Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria
Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs
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Design of a computerised treatment for short-term memory deficits in aphasia
The treatment of auditory-verbal short-term memory (STM) deficits in aphasia is a growing avenue of research (Martin & Reilly, 2012; Murray, 2012). STM treatment requires time precision, which is suited to computerised delivery. We have designed software, which provides STM treatment for aphasia. The treatment is based on matching listening span tasks (Howard & Franklin, 1990), aiming to improve the temporal maintenance of multi-word sequences (Salis, 2012). The person listens to pairs of word-lists that differ in word-order and decides if the pairs are the same or different. This approach does not require speech output and is suitable for persons with aphasia who have limited or no output. We describe the software and how its review from clinicians shaped its design
A Synthetic Genetic Edge Detection Program
SummaryEdge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks
Key issues in recruitment to randomised controlled trials with very different interventions: a qualitative investigation of recruitment to the SPARE trial (CRUK/07/011)
<p>Abstract</p> <p>Background</p> <p>Recruitment to randomised controlled trials (RCTs) with very different treatment arms is often difficult. The ProtecT (Prostate testing for cancer and Treatment) study successfully used qualitative research methods to improve recruitment and these methods were replicated in five other RCTs facing recruitment difficulties. A similar qualitative recruitment investigation was undertaken in the SPARE (Selective bladder Preservation Against Radical Excision) feasibility study to explore reasons for low recruitment and attempt to improve recruitment rates by implementing changes suggested by qualitative findings.</p> <p>Methods</p> <p>In Phase I of the investigation, reasons for low levels of recruitment were explored through content analysis of RCT documents, thematic analysis of interviews with trial staff and recruiters, and conversation analysis of audio-recordings of recruitment appointments. Findings were presented to the trial management group and a plan of action was agreed. In Phase II, changes to design and conduct were implemented, with training and feedback provided for recruitment staff.</p> <p>Results</p> <p>Five key challenges to trial recruitment were identified in Phase I: (a) Investigators and recruiters had considerable difficulty articulating the trial design in simple terms; (b) The recruitment pathway was complicated, involving staff across different specialties/centres and communication often broke down; (c) Recruiters inadvertently used 'loaded' terminology such as 'gold standard' in study information, leading to unbalanced presentation; (d) Fewer eligible patients were identified than had been anticipated; (e) Strong treatment preferences were expressed by potential participants and trial staff in some centres. In Phase II, study information (patient information sheet and flowchart) was simplified, the recruitment pathway was focused around lead recruiters, and training sessions and 'tips' were provided for recruiters. Issues of patient eligibility were insurmountable, however, and the independent Trial Steering Committee advised closure of the SPARE trial in February 2010.</p> <p>Conclusions</p> <p>The qualitative investigation identified the key aspects of trial design and conduct that were hindering recruitment, and a plan of action that was acceptable to trial investigators and recruiters was implemented. Qualitative investigations can thus be used to elucidate challenges to recruitment in trials with very different treatment arms, but require sufficient time to be undertaken successfully.</p> <p>Trial Registration</p> <p>CRUK/07/011; <a href="http://www.controlled-trials.com/ISRCTN61126465">ISRCTN61126465</a></p
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Conversation therapy with people with aphasia and conversation partners using video feedback: a group and case series investigation of changes in interaction
Conversation therapies employing video for feedback and to facilitate outcome measurement are increasingly used with people with post-stroke aphasia and their conversation partners; however the evidence base for change in everyday interaction remains limited. We investigated the effect of Better Conversations with Aphasia (BCA), an intervention that is freely available online at https://extend.ucl.ac.uk/. Eight people with chronic agrammatic aphasia, and their regular conversation partners participated in the tailored 8 week program involving significant video feedback. We explored changes in: (i) conversation facilitators (such as multi-modal turns by people with aphasia); and (ii) conversation barriers (such as use of test questions by conversation partners). The outcome of intervention was evaluated directly by measuring change in video-recorded everyday conversations. The study employed a pre-post design with multiple 5 minute samples of conversation before and after intervention, scored by trained raters blind to the point of data collection. Group level analysis showed no significant increase in conversation facilitators. There was, however, a significant reduction in the number of conversation barriers. The case series data revealed variability in conversation behaviors across occasions for the same dyad and between different dyads. Specifically, post-intervention there was a significant increase in facilitator behaviors for two dyads, a decrease for one and no significant change for five dyads. There was a significant decrease in barrier behaviors for five dyads and no significant change for three dyads. The reduction in barrier behaviors was considerable; on average change from over eight to fewer than three barrier behaviors in 5 minutes of conversation. The pre-post design has the limitation of no comparison group. However, change occurs in targeted conversational behaviors and in people with chronic aphasia and their partners. The findings suggest change can occur after eight therapy sessions and have implications for clinical practice. A reduction in barrier behaviors may be easier to obtain, although the controlled case series results demonstrate a significant increase in conversation facilitators is also possible. The rehabilitation tool is available online and video technology was central to delivering intervention and evaluating change
Qualitative analysis of feasibility of recruitment and retention in a planned randomised controlled trial of a psychosocial cancer intervention within the NHS
Background: The randomised control trial (RCT) is the most rigorous method of evaluating interventions. Recruitment
is often slower and more challenging than expected. The aim of the current paper is to understand the feasibility of
recruitment within the NHS and the barriers and motivators to recruitment from the perspective of patients and
healthcare professionals (HCPs).
Methods: NHS HCPs were surveyed to establish their willingness to participate. Twenty HCPs were interviewed to
establish barriers and motivators to recruitment. Eleven patients were interviewed to understand their willingness to
participate. Interviews were analysed using thematic analysis.
Results: HCP interviews identified key barriers to recruitment: practical barriers included workload and time; clinical
barriers included terminology and concern that the trial implied criticism of their current practice; and patient barriers
included gender and cultural factors. Motivators to recruitment included: regular communication between research
and clinical teams; feedback on findings; and patient and individual benefits for clinicians. Patient interviews suggested
that participation in a trial of a psychosocial intervention would strengthen existing coping skills and develop
mechanisms for those who were struggling.
Conclusions: Survey results demonstrated that recruitment to an RCT of a psychosocial intervention for people living with
and beyond cancer would be feasible within the NHS if specific barriers are addressed. From a clinician point of view, barriers
should be addressed to improve recruitment, particularly training and education of clinicians and clear communication.
From a patient perspective, interventions and RCT should be tailored to target those not routinely represented in RCTs.National Institute for Health Researc
Targeted sound attenuation capacity of 3D printed noise cancelling waveguides
This is an accepted manuscript of an article published by Elsevier in Applied Acoustics on 08/03/2019, available online: https://doi.org/10.1016/j.apacoust.2019.03.008
The accepted version of the publication may differ from the final published version.The study explores the creation of 3D printed sound cancelling waveguides that can be customised for selected frequencies as a function of geometry. The potential for attenuation in these waveguides is characterised through experimentally measured acoustic-absorption (α) and Transmission Loss (TL). This was done to evaluate the potential of geometry-controlled waveguides in the development of passive sound cancelling structures. Geometrically complex waveguides to exploit the Herschel–Quincke-Arjunan (HQA) waveguide model manufactured in Nylon-12 using Selective Laser Melting (SLM) are presented. The attenuation of the waveguides was compared to the bulk Nylon-12 materials to segregate the material-based influence. The results showed that the performance of HQA waveguides can be controlled as a function of length, diameter and waveguide-tortuosity. Accordingly, under right parameters significant improvement in α (0.96, 0.80, 0.61 and 0.98) and TL (65.59%, 30.15%, 53.36% and 95.28%) can be achieved at the design frequency. The proposed methodology can be used to develop customisable waveguides exploiting the principles of acoustic wave interference for a range of application including building walls, noise barriers and absorptive panels.UK Department for Transpor
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