Diabetes is a disease that involves dysregulation of metabolic processes. Patients with type 1 diabetes (T1D) require insulin injections and measured food intake to maintain clinical stability, manually tracking their results by measuring blood glucose levels. Low blood glucose levels, hypoglycemia, can be extremely dangerous and can result in seizures, coma, or even death. Canines trained as diabetes alert dogs (DADs) have demonstrated the ability to detect hypoglycemia from breath, which led us to hypothesize that hypoglycemia, a metabolic dysregulation leading to low blood glucose levels, could be identified through analyzing volatile organic compounds (VOCs) contained within breath. We hoped to replicate the canines' detection ability and success by analytically using gas chromatography/mass spectrometry of VOCs in 128 breath samples collected from 52 youths with T1D at two different diabetes camps. We used different tests for significance including Ranksum, Student's T-test, and difference between means, and found a subset of 56 traces of potential metabolites. Principle component and linear discriminant analysis (LDA) confirmed a hypoglycemic signature likely resides within this group. Supervised machine learning combined with LDA narrowed the list of likely components to seven. The technique of leave one out cross validation demonstrated the model thus developed has a sensitivity of 91% (95% confidence interval (CI) [57.1, 94.7]) and a specificity of 84% (95% CI [73.0, 92.7]) at identifying hypoglycemia. Confidence intervals were obtained by bootstrapping. These results demonstrate that it is possible to differentiate breath samples obtained during hypoglycemic events from all other breath samples by analytical means and could lead to developing a simple analytical monitoring device as an alternative to using DADs.
Paper-based batteries represent a new frontier in battery technology. However, low-flexibility and poor ionic conductivity of solid electrolytes have been major impediments in achieving practical mechanically flexible batteries. This work discuss new highly ionic conductive polymer gel electrolytes for paper-based battery applications. In this paper, we present a poly(vinylidene fluoride-hexafluoropropylene) (PVDH-HFP) porous membrane electrolyte enhanced with lithium bis(trifluoromethane sulphone)imide (LiTFSI) and lithium aluminum titanium phosphate (LATP), with an ionic conductivity of 2.1 × 10−3 S cm−1. Combining ceramic (LATP) with the gel structure of PVDF-HFP and LiTFSI ionic liquid harnesses benefits of ceramic and gel electrolytes in providing flexible electrolytes with a high ionic conductivity. In a flexibility test experiment, bending the polymer electrolyte at 90° for 20 times resulted in 14% decrease in ionic conductivity. Efforts to further improving the flexibility of the presented electrolyte are ongoing. Using this electrolyte, full-cell batteries with lithium titanium oxide (LTO) and lithium cobalt oxide (LCO) electrodes and (i) standard metallic current collectors and (ii) paper-based current collectors were fabricated and tested. The achieved specific capacities were (i) 123 mAh g−1 for standard metallic current collectors and (ii) 99.5 mAh g−1 for paper-based current collectors. Thus, the presented electrolyte has potential to become a viable candidate in paper-based and flexible battery applications. Fabrication methods, experimental procedures, and test results for the polymer gel electrolyte and batteries are presented and discussed.
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