Project sanitarium:playing tuberculosis to its end game

Interdisciplinary and collaborative projects between industry and academia provide exceptional opportunities for learning. Project Sanitarium is a serious game for Windows PC and Tablet which aims to embed learning about tuberculosis (TB) through the player taking on the role of a doctor and solving cases across the globe. The project developed as a collaboration between staff and undergraduate students at the School of Arts, Media and Computer Games at Abertay University working with academics and researchers from the Infection Group at the University of St Andrews. The project also engaged industry partners Microsoft and DeltaDNA. The project aimed to educate students through a workplace simulation pedagogical model, encourage public engagement at events and through news coverage and lastly to prototype whether games could be used to simulate a virtual clinical trial. The project was embedded in the Abertay undergraduate programme where students are presented with real world problems to solve through design and technology. The result was a serious game prototype that utilized game design techniques and technology to demystify and educate players about the diagnosis and treatment of one of the world’s oldest and deadliest diseases, TB. Project Sanitarium aims to not only educate the player, but allows the player to become a part of a simulated drug trial that could potentially help create new treatments in the fight against TB. The game incorporates a mathematical model that is based on data from real-world drug trials. The interdisciplinary pedagogical model provides undergraduates with workplace simulation, wider industry collaboration and access to academic expertise to solve challenging and complex problems

Centrifugation and decontamination procedures selectively impair recovery of important populations in Mycobacterium smegmatis

This work was supported by PreDiCT-TB (SMDO XEU-07).Diagnosis and treatment monitoring of patients with tuberculosis (TB) requires detection of all viable mycobacteria in clinical samples. Quantitation of Mycobacterium tuberculosis (Mtb) in sputum is commonly performed by culture after sample decontamination to prevent overgrowth by contaminant organisms. Exponentially growing cultures have cells that predominately lack non-polar lipid bodies whereas stationary cultures have a predominance of cells with non-polar lipid bodies. This may reflect rapidly growing ‘active’ and non-replicating ‘persister’ sub-populations respectively in sputum from TB patients. We investigated the effect of decontamination on culture-based quantitation of exponential and stationary phase cultures of Mycobacterium smegmatis in an artificial sputum model. Exponentially growing populations were between 89 and 50 times more susceptible to decontamination than stationary phase cultures when quantified by most probable number and colony forming units. These findings suggest that decontamination selectively eliminates the ‘active’ population. This may impair diagnostic sensitivity, treatment monitoring, and compromise clinical trials designed to identify new antibiotic combinations with activity against all mycobacterial cell states.PostprintPeer reviewe

Stochastic simulation and analysis of biomolecular reaction networks

<p>Abstract</p> <p>Background</p> <p>In recent years, several stochastic simulation algorithms have been developed to generate Monte Carlo trajectories that describe the time evolution of the behavior of biomolecular reaction networks. However, the effects of various stochastic simulation and data analysis conditions on the observed dynamics of complex biomolecular reaction networks have not recieved much attention. In order to investigate these issues, we employed a a software package developed in out group, called Biomolecular Network Simulator (BNS), to simulate and analyze the behavior of such systems. The behavior of a hypothetical two gene <it>in vitro </it>transcription-translation reaction network is investigated using the Gillespie exact stochastic algorithm to illustrate some of the factors that influence the analysis and interpretation of these data.</p> <p>Results</p> <p>Specific issues affecting the analysis and interpretation of simulation data are investigated, including: (1) the effect of time interval on data presentation and time-weighted averaging of molecule numbers, (2) effect of time averaging interval on reaction rate analysis, (3) effect of number of simulations on precision of model predictions, and (4) implications of stochastic simulations on optimization procedures.</p> <p>Conclusion</p> <p>The two main factors affecting the analysis of stochastic simulations are: (1) the selection of time intervals to compute or average state variables and (2) the number of simulations generated to evaluate the system behavior.</p

AVIRIS spectral trajectories for forested areas of the Gifford Pinchot National Forest

A simple mixing model employing reference endmembers (green vegetation, non-photosynthetic vegetation, soil and shade), and using 180 AVIRIS bands, was used to establish an interpretive framework for a forested area in the Pacific Northwest. A regrowth trend, based on changes in the endmember proportions, was defined for conifers that extends from clearcuts to mature forest, and by implication to old growth. Deciduous species within replanted forest plots caused the fractions to be displaced from the main coniferous regrowth trend and to move toward the green vegetation fraction. The results indicate that the spectral information in AVIRIS can be inverted to estimate approximate stand age and relative proportion of deciduous species in the context of the area studied. Using AVIRIS we measured a 3 to 5 percent increase in woody material in old-growth forest, as distinct from other mature forest. This result is consistent with a predicted increase in NPV in old-growth forest, based on field observations. Previous application of the mixing analysis to a TM image of the same area separated old growth based solely on the shade fraction; however the approach required successful removal of shade introduced by topography. Our new results suggest that with the high spectral resolution and high signal-to-noise of AVIRIS images it may be possible to characterize and map old-growth forests in the Northwest using both the NPV fraction and shade

The Nondeterministic Waiting Time Algorithm: A Review

We present briefly the Nondeterministic Waiting Time algorithm. Our technique for the simulation of biochemical reaction networks has the ability to mimic the Gillespie Algorithm for some networks and solutions to ordinary differential equations for other networks, depending on the rules of the system, the kinetic rates and numbers of molecules. We provide a full description of the algorithm as well as specifics on its implementation. Some results for two well-known models are reported. We have used the algorithm to explore Fas-mediated apoptosis models in cancerous and HIV-1 infected T cells

Homophily and Contagion Are Generically Confounded in Observational Social Network Studies

We consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual's covariates on their behavior or other measurable responses. We show that, generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular we demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects, and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual's enduring traits and their choices, even when there is no intrinsic affinity between them. We also suggest some possible constructive responses to these results.Comment: 27 pages, 9 figures. V2: Revised in response to referees. V3: Ditt

Molecular bacterial load assay (MBLA) concurs with culture on the NaOH-induced Mycobacterium tuberculosis loss of viability

This work was supported by the commonwealth studentship award for Bariki Mtafya at University of St Andrews in UK and European and Developing Countries Clinical Trials Partnership (EDCTP) through TWENDE and PanACEA II grants.Effective methods to detect viable Mycobacterium tuberculosis (Mtb), the main causative agent of tuberculosis (TB) are urgently needed. To date, cultivation of Mtb is the gold standard which depends on initial sample processing with N-Acetyl-L-Cysteine/Sodium hydroxide (NALC/NaOH), chemicals that compromise Mtb viability and, consequently the performance of downstream tests. We applied culture and the novel Molecular bacterial load assay (MBLA) to measure the loss of Mtb viability following NALC/NaOH treatment of Mtb H37Rv pure culture and clinical sputa from pulmonary TB patients. Compared to untreated controls, NALC/NaOH treatment of Mtb, reduced MBLA detectable bacillary load (estimated colony forming units/milliliter (eCFU/mL) by 0.66±0.21log10- at 23°C (P=0.018) and 0.72±0.08log10- at 30°C (P=0.013). Likewise, NALC/NaOH treatment reduced viable count on solid culture by 0.84±0.02log10- at 23°C (P<0.001) and 0.85±0.01log10- CFU/mL at 30°C (P<0.001) respectively. The reduction in viable count was reflected by a corresponding increase in time to positivity of MGIT liquid culture, 1.2 days at 23°C (P<0.001), and 1.1 days at 30°C (P<0.001). This NaOH-induced Mtb viability loss was replicated in clinical sputum samples, with bacterial load dropping by 0.65±0.17log10 from 5.36±0.24log10- to 4.71±0.16log10- eCFU/mL for untreated and treated sputa respectively. Applying the Bowness et al model, revealed that the treated MGIT time to culture positivity of 142hrs was equivalent to 4.86±0.28log10CFU, consistent with MBLA-measured bacterial load. Our study confirms the contribution of NALC/NaOH treatment to loss of viable bacterial count. Tests that obviate the need of decontamination may offer alternative option for accurate detection of viable Mtb and treatment response monitoring.PostprintPeer reviewe

Results of the combined U.S. multicenter postapproval study of the Nit‐Occlud PDA device for percutaneous closure of patent ductus arteriosus

ObjectivesTo report the results of the Nit‐Occlud PDA prospective postapproval study (PAS) along with a comparison to the results of the pivotal and continued access trials.BackgroundThe Nit‐Occlud PDA (PFM Medical, Cologne, Germany), a nitinol coil patent ductus arteriosus (PDA) occluder, was approved by the Food and Drug Administration in 2013.MethodsThe PAS enrolled a total of 184 subjects greater than 6 months of age, weighing at least 5 kg, with PDAs less than 4 mm by angiography at 11 centers. Patients were followed prospectively at 2 months, 12 months, and 24 months postprocedure. These outcomes were compared to the 357 subjects enrolled in the pivotal and continued access protocols. Efficacy and safety data were reported.ResultsAmong 184 subjects enrolled for the PAS between 2014 and 2017, 180 (97.8%) had successful device implantation. After 12 months, 98.7% (150/152) had trivial or no residual shunt by echocardiography and two subjects had only small residual shunts. There were three device embolizations that were all retrieved by snare without clinical consequence. Together with the pivotal and continued access study, 97.4% (449/461) had complete echocardiographic closure at 12 months in 541 enrolled subjects. The composite success was 94.4%. There were no mortalities and no serious device‐related adverse events.ConclusionsThe Nit‐Occlud PDA is a safe and effective device for closure of a small to moderate sized PDA. There were no serious device‐related adverse events in a large cohort of three clinical trials.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148398/1/ccd27995_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148398/2/ccd27995.pd

Noise-Driven Phenotypic Heterogeneity with Finite Correlation Time in Clonal Populations

There has been increasing awareness in the wider biological community of the role of clonal phenotypic heterogeneity in playing key roles in phenomena such as cellular bet-hedging and decision making, as in the case of the phage-λ lysis/lysogeny and B. Subtilis competence/vegetative pathways. Here, we report on the effect of stochasticity in growth rate, cellular memory/intermittency, and its relation to phenotypic heterogeneity. We first present a linear stochastic differential model with finite auto-correlation time, where a randomly fluctuating growth rate with a negative average is shown to result in exponential growth for sufficiently large fluctuations in growth rate. We then present a non-linear stochastic self-regulation model where the loss of coherent self-regulation and an increase in noise can induce a shift from bounded to unbounded growth. An important consequence of these models is that while the average change in phenotype may not differ for various parameter sets, the variance of the resulting distributions may considerably change. This demonstrates the necessity of understanding the influence of variance and heterogeneity within seemingly identical clonal populations, while providing a mechanism for varying functional consequences of such heterogeneity. Our results highlight the importance of a paradigm shift from a deterministic to a probabilistic view of clonality in understanding selection as an optimization problem on noise-driven processes, resulting in a wide range of biological implications, from robustness to environmental stress to the development of drug resistance