The Neurosphere Simulator: An educational online tool for modeling neural stem cell behavior and tissue growth.

Until very recently, distance education, including digital science labs, served a rather small portion of postsecondary students in the United States and many other countries. This situation has, however, dramatically changed in 2020 in the wake of the COVID-19 pandemic, which forced colleges to rapidly transit from face-to-face instructions to online classes. Here, we report the development of an interactive simulator that is freely available on the web (http://neurosphere.cos.northeastern.edu/) for teaching lab classes in developmental biology. This simulator is based on cellular automata models of neural-stem-cell-driven tissue growth in the neurosphere assay. By modifying model parameters, users can explore the role in tissue growth of several developmental mechanisms, such as regulation of mitosis or apoptotic cell death by contact inhibition. Besides providing an instantaneous animation of the simulated development of neurospheres, the Neurosphere Simulator tool offers also the possibility to download data for detailed analysis. The simulator function is complemented by a tutorial that introduces students to computational modeling of developmental processes.

Use of a Low-Cost Portable 3D Virtual Reality Gesture-Mediated Simulator for Training and Learning Basic Psychomotor Skills in Minimally Invasive Surgery: Development and Content Validity Study.

BACKGROUND: Simulation in virtual environments has become a new paradigm for surgeon training in minimally invasive surgery (MIS). However, this technology is expensive and difficult to access. OBJECTIVE: This study aims first to describe the development of a new gesture-based simulator for learning skills in MIS and, second, to establish its fidelity to the criterion and sources of content-related validity evidence. METHODS: For the development of the gesture-mediated simulator for MIS using virtual reality (SIMISGEST-VR), a design-based research (DBR) paradigm was adopted. For the second objective, 30 participants completed a questionnaire, with responses scored on a 5-point Likert scale. A literature review on the validity of the MIS training-VR (MIST-VR) was conducted. The study of fidelity to the criterion was rated using a 10-item questionnaire, while the sources of content-related validity evidence were assessed using 10 questions about the simulator training capacity and 6 questions about MIS tasks, and an iterative process of instrument pilot testing was performed. RESULTS: A good enough prototype of a gesture-based simulator was developed with metrics and feedback for learning psychomotor skills in MIS. As per the survey conducted to assess the fidelity to the criterion, all 30 participants felt that most aspects of the simulator were adequately realistic and that it could be used as a tool for teaching basic psychomotor skills in laparoscopic surgery (Likert score: 4.07-4.73). The sources of content-related validity evidence showed that this study's simulator is a reliable training tool and that the exercises enable learning of the basic psychomotor skills required in MIS (Likert score: 4.28-4.67). CONCLUSIONS: The development of gesture-based 3D virtual environments for training and learning basic psychomotor skills in MIS opens up a new approach to low-cost, portable simulation that allows ubiquitous learning and preoperative warm-up. Fidelity to the criterion was duly evaluated, which allowed a good enough prototype to be achieved. Content-related validity evidence for SIMISGEST-VR was also obtained.

Global optimization using Gaussian processes to estimate biological parameters from image data.

Parameter estimation is a major challenge in computational modeling of biological processes. This is especially the case in image-based modeling where the inherently quantitative output of the model is measured against image data, which is typically noisy and non-quantitative. In addition, these models can have a high computational cost, limiting the number of feasible simulations, and therefore rendering most traditional parameter estimation methods unsuitable. In this paper, we present a pipeline that uses Gaussian process learning to estimate biological parameters from noisy, non-quantitative image data when the model has a high computational cost. This approach is first successfully tested on a parametric function with the goal of retrieving the original parameters. We then apply it to estimating parameters in a biological setting by fitting artificial in-situ hybridization (ISH) data of the developing murine limb bud. We expect that this method will be of use in a variety of modeling scenarios where quantitative data is missing and the use of standard parameter estimation approaches in biological modeling is prohibited by the computational cost of the model.

A hidden markov model for identifying differentially methylated sites in bisulfite sequencing data.

DNA methylation studies have enabled researchers to understand methylation patterns and their regulatory roles in biological processes and disease. However, only a limited number of statistical approaches have been developed to provide formal quantitative analysis. Specifically, a few available methods do identify differentially methylated CpG (DMC) sites or regions (DMR), but they suffer from limitations that arise mostly due to challenges inherent in bisulfite sequencing data. These challenges include: (1) that read-depths vary considerably among genomic positions and are often low; (2) both methylation and autocorrelation patterns change as regions change; and (3) CpG sites are distributed unevenly. Furthermore, there are several methodological limitations: almost none of these tools is capable of comparing multiple groups and/or working with missing values, and only a few allow continuous or multiple covariates. The last of these is of great interest among researchers, as the goal is often to find which regions of the genome are associated with several exposures and traits. To tackle these issues, we have developed an efficient DMC identification method based on Hidden Markov Models (HMMs) called "DMCHMM" which is a three-step approach (model selection, prediction, testing) aiming to address the aforementioned drawbacks. Our proposed method is different from other HMM methods since it profiles methylation of each sample separately, hence exploiting inter-CpG autocorrelation within samples, and it is more flexible than previous approaches by allowing multiple hidden states. Using simulations, we show that DMCHMM has the best performance among several competing methods. An analysis of cell-separated blood methylation profiles is also provided.

Broadening the Perspective of Cost-Effectiveness Modeling in Chronic Obstructive Pulmonary Disease: A New Patient-Level Simulation Model Suitable to Evaluate Stratified Medicine.

OBJECTIVES: To develop a health economic model that included a great diversity of patient characteristics and outcomes for chronic obstructive pulmonary disease (COPD), which can be used to inform decisions about stratified medicine in COPD. METHODS: The choice of patient characteristics and outcomes to include in the model was based on 3 literature reviews on multidimensional prognostic COPD indices, COPD phenotypes, and treatment effects in subgroups. A conceptual model was constructed including 14 patient characteristics, 7 intermediate outcomes (lung function, physical activity, exercise capacity, symptoms, disease-specific quality of life, exacerbations, and pneumonias), and 3 final outcomes (mortality, quality-adjusted life-years [QALYs], and costs). Regression equations describing the statistical associations between the patient characteristics and intermediate and final outcomes were estimated using the longitudinal data of 5 large COPD trials (19,378 patients). A patient-level simulation model was developed in which individual patients from the baseline population of the 5 trials are sampled and their outcomes over lifetime are predicted based on the regression equations. RESULTS: The base-case analysis (single-arm simulation representing treatment with tiotropium) showed that patients had a mean lung function decline of 43 mL/year, 0.62 exacerbations/year, a worsening of their physical activity and quality of life with 1.48 and 1.10 points/year, a life expectancy of 11.2 years, 7.25 QALYs, and total lifetime costs of £24,891. Results for a selection of treatment scenarios and subgroups were shown to demonstrate the potential of the model. CONCLUSIONS: We developed a unique patient-level simulation model that can be used to evaluate COPD treatment options for a variety of subgroups.

Process of medical simulator development: An approach based on personal experience.

With increasing demand for simulators from the healthcare community and increasingly sophisticated technology being used in the manufacture of medical simulators, the manufacture of healthcare simulators has become a multifaceted undertaking. Based on our experience in the field and our diverse backgrounds, we explore the processes and issues related to the development of these simulators and suggest ways for the developing teams to collaborate and coordinate with each other to achieve a successful outcome.

Computer-Aided Surgical Simulation in Head and Neck Reconstruction: A Cost Comparison among Traditional, In-House, and Commercial Options.

BACKGROUND: Computer-aided surgical simulation (CASS) has redefined surgery, improved precision and reduced the reliance on intraoperative trial-and-error manipulations. CASS is provided by third-party services; however, it may be cost-effective for some hospitals to develop in-house programs. This study provides the first cost analysis comparison among traditional (no CASS), commercial CASS, and in-house CASS for head and neck reconstruction. METHODS: The costs of three-dimensional (3D) pre-operative planning for mandibular and maxillary reconstructions were obtained from an in-house CASS program at our large tertiary care hospital in Northern Virginia, as well as a commercial provider (Synthes, Paoli, PA). A cost comparison was performed among these modalities and extrapolated in-house CASS costs were derived. The calculations were based on estimated CASS use with cost structures similar to our institution and sunk costs were amortized over 10 years. RESULTS: Average operating room time was estimated at 10 hours, with an average of 2 hours saved with CASS. The hourly cost to the hospital for the operating room (including anesthesia and other ancillary costs) was estimated at $4,614/hour. Per case, traditional cases were $46,140, commercial CASS cases were $40,951, and in-house CASS cases were $38,212. Annual in-house CASS costs were $39,590. CONCLUSIONS: CASS reduced operating room time, likely due to improved efficiency and accuracy. Our data demonstrate that hospitals with similar cost structure as ours, performing greater than 27 cases of 3D head and neck reconstructions per year can see a financial benefit from developing an in-house CASS program.

Ethics of Virtual Reality in Medical Education and Licensure.

The aim of this section is to expand and accelerate advances in curriculum developments and in methods of teaching bioethics.

Advanced Low-Cost Ultrasound-Guided Vascular Access Simulation: The Chicken Breast Model.

There is a growing body of literature that supports the use of ultrasound for vascular access. Advanced simulation has become a widely applied technique for training medical staff in vascular access. Nevertheless, advanced simulators are expensive and of limited usage. We describe both a step-wise systematic approach and an experimental cadaveric model of vascular access using a simple piece of chicken that can be easily used for trainees.

Assessment of Epstein-Barr virus nucleic acids in gastric but not in breast cancer by next-generation sequencing of pooled Mexican samples.

Gastric (GC) and breast (BrC) cancer are two of the most common and deadly tumours. Different lines of evidence suggest a possible causative role of viral infections for both GC and BrC. Wide genome sequencing (WGS) technologies allow searching for viral agents in tissues of patients with cancer. These technologies have already contributed to establish virus-cancer associations as well as to discovery new tumour viruses. The objective of this study was to document possible associations of viral infection with GC and BrC in Mexican patients. In order to gain idea about cost effective conditions of experimental sequencing, we first carried out an in silico simulation of WGS. The next-generation-platform IlluminaGallx was then used to sequence GC and BrC tumour samples. While we did not find viral sequences in tissues from BrC patients, multiple reads matching Epstein-Barr virus (EBV) sequences were found in GC tissues. An end-point polymerase chain reaction confirmed an enrichment of EBV sequences in one of the GC samples sequenced, validating the next-generation sequencing-bioinformatics pipeline.

Applying dynamic simulation modeling methods in health care delivery research-the SIMULATE checklist: report of the ISPOR simulation modeling emerging good practices task force.

Health care delivery systems are inherently complex, consisting of multiple tiers of interdependent subsystems and processes that are adaptive to changes in the environment and behave in a nonlinear fashion. Traditional health technology assessment and modeling methods often neglect the wider health system impacts that can be critical for achieving desired health system goals and are often of limited usefulness when applied to complex health systems. Researchers and health care decision makers can either underestimate or fail to consider the interactions among the people, processes, technology, and facility designs. Health care delivery system interventions need to incorporate the dynamics and complexities of the health care system context in which the intervention is delivered. This report provides an overview of common dynamic simulation modeling methods and examples of health care system interventions in which such methods could be useful. Three dynamic simulation modeling methods are presented to evaluate system interventions for health care delivery: system dynamics, discrete event simulation, and agent-based modeling. In contrast to conventional evaluations, a dynamic systems approach incorporates the complexity of the system and anticipates the upstream and downstream consequences of changes in complex health care delivery systems. This report assists researchers and decision makers in deciding whether these simulation methods are appropriate to address specific health system problems through an eight-point checklist referred to as the SIMULATE (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) tool. It is a primer for researchers and decision makers working in health care delivery and implementation sciences who face complex challenges in delivering effective and efficient care that can be addressed with system interventions. On reviewing this report, the readers should be able to identify whether these simulation modeling methods are appropriate to answer the problem they are addressing and to recognize the differences of these methods from other modeling approaches used typically in health technology assessment applications.

Reducing the cost of evaluating the committor by a fitting procedure.

Correct identification of reaction coordinates in complex systems is essential for understanding the mechanisms of their reaction dynamics. Existing methods for identifying reaction coordinates typically require knowledge of the committor--the probability of a given configuration to reach the product basin. The high computational cost of evaluating committors has limited applications of methods for identifying reaction coordinates. We proposed a fitting procedure that can reduce the cost of evaluating committors by an order of magnitude or more. The method only requires evaluating the committors of a few configurations in a transition path by the standard and costly shooting procedure. The committors of the other configurations are then estimated with great accuracy by a sigmoid function derived from fitting the few numerically evaluated committors. The method has been systematically tested on a model system of a Brownian particle moving in a one-dimensional double-well potential, and a small biomolecular system--the isomerization of alanine dipeptide in vacuum and in explicit water.

Are virtual planning and guided surgery for head and neck reconstruction economically viable?

PURPOSE: Virtual planning and guided surgery with or without prebent or milled plates are becoming more and more common for mandibular reconstruction with fibular free flaps (FFFs). Although this excellent surgical option is being used more widely, the question of the additional cost of planning and cutting-guide production has to be discussed. In capped payment systems such additional costs have to be offset by other savings if there are no special provisions for extra funding. Our study was designed to determine whether using virtual planning and guided surgery resulted in time saved during surgery and whether this time gain resulted in self-funding of such planning through the time saved. MATERIALS AND METHODS: All consecutive cases of FFF surgery were evaluated during a 2-year period. Institutional data were used to determine the price of 1 minute of operative time. The time for fibula molding, plate adaptation, and insetting was recorded. RESULTS: During the defined period, we performed 20 mandibular reconstructions using FFFs, 9 with virtual planning and guided surgery and 11 freehand cases. One minute of operative time was calculated to cost US $47.50. Multiplying this number by the time saved, we found that the additional cost of virtual planning was reduced from US $5,098 to US $1,231.50 with a prebent plate and from US $6,980 to US $3,113.50 for a milled plate. CONCLUSIONS: Even in capped health care systems, virtual planning and guided surgery including prebent or milled plates are financially viable.

Modern Multi-line Slot Machine Games: The Effect of Lines Wagered on Winners, Losers, Bonuses, and Losses Disguised as Wins.

We simulated the commercially available multi-line slot machine game "Money Storm," including its bonus wins. Our results show that after a specified amount of time (such as 1 or 50 h), when players played a single line, there were marked differences between one player and the next-a few won a lot, others lost far more than average. When playing 20 lines there were fewer big winners and fewer players quickly losing a large percentage of their money. We simulated a Gambler's Ruin scenario whereby players arrived with $100 and made $1 wagers until broke. Again we saw a reduction in the variability among player as the number of lines wagered increased, fewer players lost their entire bankroll quickly, and fewer players had big wins. The bonus wins in Money Storm contribute approximately 24% to the payback of the game, and our simulations of bonus wins shows that with 20 lines wagered the players spend approximately 11% of their time in bonus wins. With one line wagered, there are no losses disguised as wins while with 20 lines wagered the majority of hits are losses disguised as wins. Players using multi-line machines can thus tune the characteristics of the machine gambling experience to match their preferred pattern, though most seem in practice to bet on the most possible lines. Our results serve to inform researchers, counsellors, gamblers and others about how slot machines are designed, and the effect that wagering on multiple lines has on short-term and long-term play, bonus wins, and losses disguised as wins.

Optimal insemination and replacement decisions to minimize the cost of pathogen-specific clinical mastitis in dairy cows.

Mastitis is a serious production-limiting disease, with effects on milk yield, milk quality, and conception rate, and an increase in the risk of mortality and culling. The objective of this study was 2-fold: (1) to develop an economic optimization model that incorporates all the different types of pathogens that cause clinical mastitis (CM) categorized into 8 classes of culture results, and account for whether the CM was a first, second, or third case in the current lactation and whether the cow had a previous case or cases of CM in the preceding lactation; and (2) to develop this decision model to be versatile enough to add additional pathogens, diseases, or other cow characteristics as more information becomes available without significant alterations to the basic structure of the model. The model provides economically optimal decisions depending on the individual characteristics of the cow and the specific pathogen causing CM. The net returns for the basic herd scenario (with all CM included) were $507/cow per year, where the incidence of CM (cases per 100 cow-years) was 35.6, of which 91.8% of cases were recommended for treatment under an optimal replacement policy. The cost per case of CM was $216.11. The CM cases comprised (incidences, %) Staphylococcus spp. (1.6), Staphylococcus aureus (1.8), Streptococcus spp. (6.9), Escherichia coli (8.1), Klebsiella spp. (2.2), other treated cases (e.g., Pseudomonas; 1.1), other not treated cases (e.g., Trueperella pyogenes; 1.2), and negative culture cases (12.7). The average cost per case, even under optimal decisions, was greatest for Klebsiella spp. ($477), followed by E. coli ($361), other treated cases ($297), and other not treated cases ($280). This was followed by the gram-positive pathogens; among these, the greatest cost per case was due to Staph. aureus ($266), followed by Streptococcus spp. ($174) and Staphylococcus spp. ($135); negative culture had the lowest cost ($115). The model recommended treatment for most CM cases (>85%); the range was 86.2% (Klebsiella spp.) to 98.5% (Staphylococcus spp.). In general, the optimal recommended time for replacement was up to 5 mo earlier for cows with CM compared with cows without CM. Furthermore, although the parameter estimates implemented in this model are applicable to the dairy farms in this study, the parameters may be altered to be specific to other dairy farms. Cow rankings and values based on disease status, pregnancy status, and milk production can be extracted; these provide guidance when determining which cows to keep or cull.

Is the "in situ" simulation for teaching anesthesia residents a lower cost, feasible and satisfying alternative to simulation center ? A 24 months prospective observational study in a university hospital.

BACKGROUND: The value of simulation in medical education is increasingly obvious. Nevertheless, the high cost of running a simulation center and the time's availability for students to get to simulation center remain a major problem. Technological developments and miniaturization of computer systems now allow handling of simulation manikins. Therefore, "in situ" simulation seems a valuable alternative to center simulation. OBJECTIVE(S): To identify the costs and feasibility of "in situ" simulation. To conduct an evaluation of the sessions by participants in order to adapt the educational objectives. DESIGN: Observational study. SETTING: 118 "in situ" simulation sessions were organized between March 2011 and February 2013 in the university hospital of Université Catholique de Louvain. Sessions took place in OR facilities. At the end of each session, a questionnaire was given to each participant. PARTICIPANTS: 357 of 368 participants completed a questionnaire. For each session, one or two nurses and 2 residents in anesthesia were invited. MAIN OUTCOME MEASURES: Total costs for organizing the sessions. Number of realized sessions. Global satisfaction of participants. RESULTS: Total cost for organizing the sessions is 18 414 Euro. One hundred and one among the 118 scheduled sessions were performed, which corresponds to a rate of 85%. Three hundred and sixty-five people participated in training simulations. During the sessions, 357 questionnaires were completed. The global satisfaction was high with a median Likert scale of 5 (5-5) to the question "I would like to participate in other sessions in the future". CONCLUSION: The "in situ" simulation in anesthesia is feasible in a university hospital using the available facilities of the operating theater during the working hours of both participants and trainers. However, the number of annual sessions may be limited by the availability of the simulation room or staff.