Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra- day variability

[EN] Background and Objective: Current prototypes of closed-loop systems for glucose control in type 1 diabetes mellitus, also referred to as artificial pancreas systems, require a pre-meal insulin bolus to compensate for delays in subcutaneous insulin absorption in order to avoid initial post-prandial hyperglycemia. Computing such a meal bolus is a challenging task due to the high intra-subject variability of insulin requirements. Most closed-loop systems compute this pre-meal insulin dose by a standard bolus calculation, as is commonly found in insulin pumps. However, the performance of these calculators is limited due to a lack of adaptiveness in front of dynamic changes in insulin requirements. Despite some initial attempts to include adaptation within these calculators, challenges remain. Methods: In this paper we present a new technique to automatically adapt the meal-priming bolus within an artificial pancreas. The technique consists of using a novel adaptive bolus calculator based on Case-Based Reasoning and Run-To-Run control, within a closed-loop controller. Coordination between the adaptive bolus calculator and the controller was required to achieve the desired performance. For testing purposes, the clinically validated Imperial College Artificial Pancreas controller was employed. The proposed system was evaluated against itself but without bolus adaptation. The UVa-Padova T1DM v3.2 system was used to carry out a three-month in silico study on 11 adult and 11 adolescent virtual subjects taking into account inter-and intra-subject variability of insulin requirements and uncertainty on carbohydrate intake. Results: Overall, the closed-loop controller enhanced by an adaptive bolus calculator improves glycemic control when compared to its non-adaptive counterpart. In particular, the following statistically significant improvements were found (non-adaptive vs. adaptive). Adults: mean glucose 142.2 ± 9.4 vs. 131.8 ± 4.2 mg/dl; percentage time in target [70, 180] mg/dl, 82.0 ± 7.0 vs. 89.5 ± 4.2; percentage time above target 17.7 ± 7.0 vs. 10.2 ± 4.1. Adolescents: mean glucose 158.2 ± 21.4 vs. 140.5 ± 13.0 mg/dl; percentage time in target, 65.9 ± 12.9 vs. 77.5 ± 12.2; percentage time above target, 31.7 ± 13.1 vs. 19.8 ± 10.2. Note that no increase in percentage time in hypoglycemia was observed.This project has been funded by the Welcome Trust.Herrero, P.; Bondía Company, J.; Adewuji, O.; Pesl, P.; El-Sharkawy, M.; Reddy, M.; Toumazou, C.... (2017). Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra- day variability. Computer Methods and Programs in Biomedicine. 146:125-131. https://doi.org/10.1016/j.cmpb.2017.05.010S12513114

Advanced and Rationalized Atomic Force Microscopy Analysis Unveils Specific Properties of Controlled Cell Mechanics

The cell biomechanical properties play a key role in the determination of the changes during the essential cellular functions, such as contraction, growth, and migration. Recent advances in nano-technologies have enabled the development of new experimental and modeling approaches to study cell biomechanics, with a level of insights and reliability that were not possible in the past. The use of atomic force microscopy (AFM) for force spectroscopy allows nanoscale mapping of the cell topography and mechanical properties under, nearly physiological conditions. A proper evaluation process of such data is an essential factor to obtain accurate values of the cell elastic properties (primarily Young's modulus). Several numerical models were published in the literature, describing the depth sensing indentation as interaction process between the elastic surface and indenting probe. However, many studies are still relying on the nowadays outdated Hertzian model from the nineteenth century, or its modification by Sneddon. The lack of comparison between the Hertz/Sneddon model with their modern modifications blocks the development of advanced analysis software and further progress of AFM promising technology into biological sciences. In this work, we applied a rationalized use of mechanical models for advanced postprocessing and interpretation of AFM data. We investigated the effect of the mechanical model choice on the final evaluation of cellular elasticity. We then selected samples subjected to different physicochemical modulators, to show how a critical use of AFM data handling can provide more information than simple elastic modulus estimation. Our contribution is intended as a methodological discussion of the limitations and benefits of AFM-based advanced mechanical analysis, to refine the quantification of cellular elastic properties and its correlation to undergoing cellular processes in vitro

Improved molecular constants for the X

Improved molecular constants for the $X^1 \Sigma ^+$ and $A^1 \Sigma ^+$ states of the NaH molecule are presented. NaH molecules are produced by reactive scattering of H and Na2 in a crossed beam experiment. High vibrational levels (6 $\le v'' \le$ 9) of the NaH molecules are predominantly populated. Their excitation spectrum in the range $630 {\rm nm }\le \lambda \le 670 {\rm nm}$ has been measured using a new variant of Doppler spectroscopy. The transition frequencies involving the vibrational levels 2 $\le v' \le$ 8 in the $A^1 \Sigma ^+$ and 6 $\le v'' \le$ 9 in the $X^1 \Sigma ^+$ state have been determined with an accuracy of better than $0.01 {\rm cm}^{-1}$. Using also previously published data a new set of molecular constants for the $X^1 \Sigma ^+$ and $A^1 \Sigma ^+$ state is derived. In particular, the vibrational dependence of the rotational constants B, D and H as well as some of v''-v' band origins for $0 \le v'' \le 9$ and $0 \le v' \le 25$ is determined. The transition frequencies measured here or published previously are reproduced by these new coefficients with an accuracy of ≤ 0.1 cm-1 [rms value] with a maximum deviation of 0.4 cm-1. New RKR potential energy curves have been calculated up to the turning points of the levels v'' = 9 in the $X^1\Sigma^+$ state and v' = 25 in the $A^1\Sigma^+$ state

Atomatic adjustment of Basal insulin infusion rates in type 1 diabetes using run-to-run control and case-based reasoning

People with type 1 diabetes mellitus rely on a basal-bolus insulin regimen to roughly emulate how a non-diabetic person’s body delivers insulin. Adjusting such regime is a challenging process usually conducted by an expert clinical. Despite several guidelines exist for such purpose, they are usually impractical and fall short in achieving optimal glycemic outcomes. Therefore, there is a need for more automated and efficient strategies to adjust such regime. This paper presents, and in silico validates, a novel technique to automatically adapt the basal insulin profile of a person with person with type 1 diabetes. The presented technique, which is based on Run-to-Run control and Case-Based Reasoning, overcomes some of the limitations of previously proposed approaches and has been proved to be robust in front of realistic intra-day variability. Over a period of 5 weeks on 10 virtual adult subjects, a significant reduction on the percentage of time in hyperglycemia (180mg/dl) (from 10.2±5.9 to 1.6±1.7, p=0.1), was achieved

Clinical Safety and Feasibility of the Advanced Bolus Calculator for Type 1 Diabetes Based on Case-Based Reasoning: A 6-Week Nonrandomized Single-Arm Pilot Study

Background: The Advanced Bolus Calculator for Diabetes (ABC4D) is an insulin bolus dose decision support system based on case-based reasoning (CBR). The system is implemented in a smartphone application to provide personalized and adaptive insulin bolus advice for people with type 1 diabetes. We aimed to assess proof of concept, safety, and feasibility of ABC4D in a free-living environment over 6 weeks. Methods: Prospective nonrandomized single-arm pilot study. Participants used the ABC4D smartphone application for 6 weeks in their home environment, attending the clinical research facility weekly for data upload, revision, and adaptation of the CBR case base. The primary outcome was postprandial hypoglycemia. Results: Ten adults with type 1 diabetes, on multiple daily injections of insulin, mean (standard deviation) age 47 (17), diabetes duration 25 (16), and HbA1c 68 (16) mmol/mol (8.4 (1.5) %) participated. A total of 182 and 150 meals, in week 1 and week 6, respectively, were included in the analysis of postprandial outcomes. The median (interquartile range) number of postprandial hypoglycemia episodes within 6-h after the meal was 4.5 (2.0–8.2) in week 1 versus 2.0 (0.5–6.5) in week 6 (P = 0.1). No episodes of severe hypoglycemia occurred during the study. Conclusion: The ABC4D is safe for use as a decision support tool for insulin bolus dosing in self-management of type 1 diabetes. A trend suggesting a reduction in postprandial hypoglycemia was observed in the final week compared with week 1