There is a dire need for infection prevention strategies that do not require the use of antibiotics, which exacerbate the rise of multi-and pan-drug resistant infectious organisms. An important target in this area is the bacterial attachment and subsequent biofilm formation on medical devices (e.g., catheters). Here we describe non-fouling, lubricant-infused slippery polymers as proof-of-concept medical materials that are based on oil-infused polydimethylsiloxane (iPDMS). Planar and tubular geometry silicone substrates can be infused with non-toxic silicone oil to create a stable, extremely slippery interface that exhibits exceptionally low bacterial adhesion and prevents biofilm formation. Analysis of a flow culture of Pseudomonas aeruginosa through untreated PDMS and iPDMS tubing shows at least an order of magnitude reduction of biofilm formation on iPDMS, and almost complete absence of biofilm on iPDMS after a gentle water rinse. The iPDMS materials can be applied as a coating on other polymers or prepared as simply as taking a silicone tubing and immersing it in a silicone oil, and are compatible with traditional sterilization methods. As a demonstration, we show the preparation of silicone-coated polyurethane catheters and significant reduction of Escherichia coli and Staphylococcus epidermidis biofilm formation on the catheter surface. This work represents an important first step towards a simple and effective means of preventing bacterial adhesion on a wide range of materials used for medical devices.
Canada has stockpiles of waste petroleum coke, a high carbon waste product leftover from oil production with little positive market value. A polygeneration process is proposed which implements "power-to-gas" technology, through the use of electrolysis and surplus grid electricity, to use waste petroleum coke and biomass to create a carbon monoxide-rich stream after gasification, which is then converted into a portfolio of value-added products with the addition of hydrogen. A model implementing mixed-integer linear programming integrates power-to-gas technology and AspenPlus simulates the polygeneration process. The downstream production rates are selected using particle swarm optimization. When comparing 100% electrolysis vs. 100% steam reforming as a source of hydrogen production, electrolysis provides a larger net present value due to the carbon pricing introduced in Canada and the cost reduction from removal of the air separation unit by using the oxygen from the electrolysers. The optimal percent of hydrogen produced from electrolysis is about 82% with a hydrogen input of 7600 kg/h. The maximum net present value is $332 M when over 75% production rate is dimethyl ether or $203 M when the dimethyl ether is capped at 50% production. The polygeneration plant is an example of green technology used to environmentally process Canada's petroleum coke.
PURPOSE This study documents the creation of automated, longitudinal, and prospective data and analytics platform for breast cancer at a regional cancer center. This platform combines principles of data warehousing with natural language processing (NLP) to provide the integrated, timely, meaningful, high-quality, and actionable data required to establish a learning health system. METHODS Data from six hospital information systems and one external data source were integrated on a nightly basis by automated extract/transform/load jobs. Free-text clinical documentation was processed using a commercial NLP engine. RESULTS The platform contains 141 data elements of 7,019 patients with newly diagnosed breast cancer who received care at our regional cancer center from January 1, 2014, to June 3, 2022. Daily updating of the database takes an average of 56 minutes. Evaluation of the tuning of NLP jobs found overall high performance, with an F1 of 1.0 for 19 variables, with a further 16 variables with an F1 of > 0.95. CONCLUSION This study describes how data warehousing combined with NLP can be used to create a prospective data and analytics platform to enable a learning health system. Although upfront time investment required to create the platform was considerable, now that it has been developed, daily data processing is completed automatically in less than an hour.
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