Development of fast methods to conduct in silico experiments using computational models of cellular signaling is a promising approach toward advances in personalized medicine. However, software-based cellular network simulation has runtimes plagued by wasted CPU cycles and unnecessary processes. Hardware-based simulation affords substantial speedup, but prior attempts at hardware-based biological simulation have been limited in scope and have suffered from inaccuracies due to poor random number generation. In this work, we propose several hardware-based simulation schemes utilizing novel random update index generation techniques for step-based and roundbased stochastic simulations of cellular networks. Our results show improved runtimes while maintaining simulation accuracy compared to software implementations.
Background: It is well established that stethoscopes harbor pathogenic bacteria species. Within hospital settings, these pathogens can be rapidly transmitted from room to room and can cause harm in vulnerable populations. The current literature demonstrates that disinfecting stethoscopes with isopropanol kills 99% of all bacteria. However, in practice this rarely occurs and disinfection is subject to user error. We assessed the efficacy of ultraviolet germicidal irradiation (UV-C) at decontaminating stethoscopes used at our rural healthcare system along with the cleaning habits of their users. Methods: Stethoscopes were randomly selected from the clinical staff of our hospital’s largest nursing unit. The stethoscopes were each swabbed for culture then exposed to UV-C for 20 seconds and sampled again. Users were asked to complete a survey during this process. Samples were then cultivated on tryptone soya broth (TSB) agar, and all growth was sent for identification via matrix-assisted laser desorption/ionization (MALDI-TOF). Later, the protocol was repeated to assess cleaning efficacy of the isopropanol wipes commonly used in our hospital. We collected pre- and postintervention samples after cleaning vigorously for 3 minutes according to the manufacturer’s guidelines. The samples were classified as follows: “cleaner” if the number of colonies decreased after sanitation, “sterilized” if the number of colonies decreased to zero, “no change” if the number of colonies stayed the same, and “no assessment” if there was no preintervention growth. Several samples “increased” in CFU count after the intervention, likely due to incomplete sampling, contamination, or incomplete penetration of UV-C. The Fisher exact test was used to analyze the effectiveness of the stethoscope sanitation techniques. Results: In total, 60 samples (33 used for analysis) were obtained from stethoscopes cleaned with UV-C (Fig. 1). Moreover, 34 samples (28 used for analysis) were obtained from stethoscopes cleaned with isopropanol (Fig. 2). Both UV-C (93.9% vs 6.1%; P < .01) and isopropanol (100% vs 0%; P < .01) resulted in a significant decrease in bacterial colonization on stethoscopes. UV-C was not more effective at sanitizing stethoscopes than isopropanol (93.9% vs 100%; P = .50). Conclusions: Both UV-C and isopropanol were effective at cleaning hospital stethoscopes. Given that UV-C is not subject to user error and that it takes less time to clean a stethoscope than isopropanol, it may be the superior option in a clinical setting.Funding: NoneDisclosures: None
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.