Feasibility and Preliminary Safety of Smartphone-Based Automated Insulin Delivery in Adolescents and Children With Type 1 Diabetes

BACKGROUND

A smartphone-based automated insulin delivery (AID) controller device can facilitate use of interoperable components and acceptance in adolescents and children.

METHODS

Pediatric participants (N = 20, 8F) with type 1 diabetes were enrolled in three sequential age-based cohorts: adolescents (12-<18 years, n = 8, 5F), school-age (8-<12 years, n = 7, 2F), and young children (2-<8 years, n = 5, 1F). Participants used the interoperable artificial pancreas system (iAPS) and zone model predictive control (MPC) on an unlocked smartphone for 48 hours, consumed unrestricted meals of their choice, and engaged in various unannounced exercises. Primary outcomes and stopping criteria were defined using fingerstick blood glucose (BG) data; secondary outcomes compared continuous glucose monitoring (CGM) data with preceding sensor augmented pump (SAP) therapy.

RESULTS

During AID, there was no more than one BG <50 mg/dL except in one young child participant; no instance of more than two episodes of BG ≥300 mg/dL lasting longer than 2 hours; and no adverse events. Despite large meals (total of 404.9 grams of carbs) and unannounced exercise (total of 182 minutes), overall CGM percent time in range (TIR) of 70 to 180 mg/dL during AID was statistically similar to SAP (63.5% vs 57.3%, respectively, P = .145). Overnight glucose standard deviation was 43 mg/dL (vs SAP 57.9 mg/dL, P = .009) and coefficient of variation was 25.7% (vs SAP 34.9%, P < .001). The percent time in closed-loop mode and connected to the CGM was 92.7% and 99.6%, respectively. Surveys indicated that participants and parents/guardians were satisfied with the system.

CONCLUSIONS

The smartphone-based AID was feasible and safe in sequentially younger cohorts of adolescents and children.

CLINICALTRIALS.GOV

NCT04255381 (https://clinicaltrials.gov/ct2/show/NCT04255381).

The development and acceptability of an educational and training intervention for recruiters to neonatal trials: the TRAIN project

BACKGROUND

Suboptimal or slow recruitment affects 30-50% of trials. Education and training of trial recruiters has been identified as one strategy for potentially boosting recruitment to randomised controlled trials (hereafter referred to as trials). The Training tRial recruiters, An educational INtervention (TRAIN) project was established to develop and assess the acceptability of an education and training intervention for recruiters to neonatal trials. In this paper, we report the development and acceptability of TRAIN.

METHODS

TRAIN involved three sequential phases, with each phase contributing information to the subsequent phase(s). These phases were 1) evidence synthesis (systematic review of the effectiveness of training interventions and a content analysis of the format, content, and delivery of identified interventions), 2) intervention development using a Partnership (co-design/co-creation) approach, and 3) intervention acceptability assessments with recruiters to neonatal trials.

RESULTS

TRAIN, accompanied by a comprehensive intervention manual, has been designed for online or in-person delivery. TRAIN can be offered to recruiters before trial recruitment begins or as refresher sessions during a trial. The intervention consists of five core learning outcomes which are addressed across three core training units. These units are the trial protocol (Unit 1, 50 min, trial-specific), understanding randomisation (Unit 2, 5 min, trial-generic) and approaching and engaging with parents (Unit 3, 70 min, trial-generic). Eleven recruiters to neonatal trials registered to attend the acceptability assessment training workshops, although only four took part. All four positively valued the training Units and resources for increasing recruiter preparedness, knowledge, and confidence. More flexibility in how the training is facilitated, however, was noted (e.g., training divided across two workshops of shorter duration). Units 2 and 3 were considered beneficial to incorporate into Good Clinical Practice Training or as part of induction training for new staff joining neonatal units.

CONCLUSION

TRAIN offers a comprehensive co-produced training and education intervention for recruiters to neonatal trials. TRAIN was deemed acceptable, with minor modification, to neonatal trial recruiters. The small number of recruiters taking part in the acceptability assessment is a limitation. Scale-up of TRAIN with formal piloting and testing for effectiveness in a large cluster randomised trial is required.

Glucose Rate-of-Change and Insulin-on-Board Jointly Weighted Zone Model Predictive Control

We present design and evaluation of closed-loop insulin delivery using zone model predictive control (MPC) featuring an adaptive weighting scheme to address prolonged hyperglycemia due to changes in insulin sensitivity, underdelivery from profile mismatch, and meal composition. In the MPC cost function, the penalty on predicted glucose deviation from the upper zone boundary is weighted by a joint function of predicted glucose rate-of-change (ROC) and insulin-on-board (IOB). The asymmetric weighting gradually increases when glucose ROC and IOB were jointly low, independent of glucose magnitude, to limit hyperglycemia while aggressively reduces for negative glucose ROC to avoid hypoglycemia. The proposed controller was evaluated using two simulation scenarios: an induced resistance scenario and a nominal scenario to highlight the performance over a reference zone MPC with glucose ROC weighting only. The continuous adaption scheme resulted in consistent improvement for the entire glucose range without incurring additional risk of hypoglycemia. For the induced resistance and no feedforward bolus scenario, the percent time in 70-180 mg/dL was higher (53.5% versus 48.9%, p<0.001) with larger improvement in the overnight percent time in tighter glucose range 70-140 mg/dL (70.9% versus 52.9%, p<0.001). The results from extensive simulations, as well as clinical validation in three different outpatient studies demonstrate the utility and safety of the proposed zone MPC.

A comparative study of rectal volume variation in patients with prostate cancer: A tertiary care center study

INTRODUCTION

Every day variations in rectal filling in prostate cancer radiotherapy can significantly alter the delivered dose distribution from what was intended. The goal of this study was to see if the time of treatment delivery affected the rectal filling.

METHODS

This is a retrospective study which included 50 patients with localized prostate cancer treated with volumetric modulated arc therapy (VMAT) to the primary and regional lymph nodes. Cone Beam Computed Tomography (CBCT) image-sets were done for all patient's daily setup verification. The radiation therapist contoured the rectum on all CBCT image sets. The rectal volumes delineated on CBCT and the planning CT image sets were compared. The change in rectal volumes between morning and afternoon treatments were calculated and compared.

RESULTS

A total of 1000 CBCT image sets were obtained on 50 patients in the morning and afternoon. The percentage variation of the CBCT rectal volumes over the planning CT scan was 16.57% in the AM group and 24.35% in the PM group.

CONCLUSION

The percentage change in rectal volume was significantly lesser in AM group compared to PM group and therefore morning treatments may result in dose distribution that is close to the intended dose distribution.

IMPLICATIONS FOR PRACTICE

In prostate cancer radiotherapy our study suggests that a simple technique of changing the time of treatment from afternoon to morning can help to reduce the rectal volume.

At-Home Use of a Pregnancy-Specific Zone-MPC Closed-Loop System for Pregnancies Complicated by Type 1 Diabetes: A Single-Arm, Observational Multicenter Study

OBJECTIVE

There are no commercially available hybrid closed-loop insulin delivery systems customized to achieve pregnancy-specific glucose targets in the U.S. This study aimed to evaluate the feasibility and performance of at-home use of a zone model predictive controller-based closed-loop insulin delivery system customized for pregnancies complicated by type 1 diabetes (CLC-P).

RESEARCH DESIGN AND METHODS

Pregnant women with type 1 diabetes using insulin pumps were enrolled in the second or early third trimester. After study sensor wear collecting run-in data on personal pump therapy and 2 days of supervised training, participants used CLC-P targeting 80-110 mg/dL during the day and 80-100 mg/dL overnight running on an unlocked smartphone at home. Meals and activities were unrestricted throughout the trial. The primary outcome was the continuous glucose monitoring percentage of time in the target range 63-140 mg/dL versus run-in.

RESULTS

Ten participants (HbA1c 5.8 ± 0.6%) used the system from mean gestational age of 23.7 ± 3.5 weeks. Mean percentage time in range increased 14.1 percentage points, equivalent to 3.4 h per day, compared with run-in (run-in: 64.5 ± 16.3% versus CLC-P: 78.6 ± 9.2%; P = 0.002). During CLC-P use, there was significant decrease in both time over 140 mg/dL (P = 0.033) and the hypoglycemic ranges of less than 63 mg/dL and 54 mg/dL (P = 0.037 for both). Nine participants exceeded consensus goals of above 70% time in range during CLC-P use.

CONCLUSIONS

The results show that the extended use of CLC-P at home until delivery is feasible. Larger, randomized studies are needed to further evaluate system efficacy and pregnancy outcomes.

Comparative in vitro evaluation of remaining dentine thickness following instrumentation with hand and rotary endodontic files during pulpectomy in primary molars: a systematic review

PURPOSE

The aim was to compare the remaining dentine thickness (RDT) following instrumentation with hand and rotary endodontic files during pulpectomy in primary molars. Research question was 'Is there any difference between the remaining dentine thickness following instrumentation with hand and rotary endodontic files during pulpectomy in primary molars?'.

METHODS

Electronic Databases like MEDLINE PubMed, Cochrane Library, EBSCOhost, Google scholar and grey literature were searched between January 1, 2006 and August 31, 2022 for in vitro and ex vivo studies that compared hand and rotary endodontic instrumentation to evaluate the RDT in primary molars. Articles published in English or which could be translated into English were searched. Two reviewers independently selected studies, extracted data, assessed risk of bias using the Revised, validated version of MINORS criteria.

RESULTS

Twelve studies were included in qualitative analysis. All included studies showed low risk of bias. Six studies showed more RDT with rotary instrumentation compared to manual instrumentation. Whereas, five studies showed variable results for RDT with manual and rotary instrumentation at different levels of root canals. One study showed no significant difference between manual and rotary instrumentation. In view of methodological heterogeneity of the findings, a meta-analysis was not conducted.

CONCLUSION

High quality of evidence based on low risk of bias was found in all the included studies. Statistically, rotary instrumentation showed more RDT than manual instrumentation according to majority of studies. Despite the shortcomings of this systematic review, it is possible to infer that the use of rotary instrumentation provides more RDT and thus there is considerable conservation of tooth structure.

Inflammation begets isolated atrioventricular conduction disturbances in young an observation from indian registry data

Background

High grade AV block is less commonly encountered in patients &lt;60 years. The aetiological role of inflammatory conditions is not well studied in this group of patients.

Purpose

To determine the prevalence of myocardial inflammation in young patients presenting with High grade AV block and assess its response to immunosuppression.

Methodology

This is a prospective, registry based, observational study conducted at two centers from Jan 2020 to Dec 2021. Myocardial inflammation was detected using Cardiac PET, and/or histopathological examination. Those with evidence of inflammation were started on graded immunosuppression.

Results

318 patients were enrolled. Mean EF was 55.2±7.0%. Cardiac PET was performed in 87/318 (27.3%). Myocardial inflammation was seen in 57/87 (65%). LV basal septum was most commonly involved. 44/57 (77%) were started on immunosuppressive therapy after excluding indolent tuberculosis.8 patients died during follow-up with all deaths being sudden in nature. 5/44 (11.3%) had reversal of CHB with resolution of cPET findings.

Conclusion

Significant proportion of young patients with High grade AV block have segmental myocardial inflammation. Immunosuppression helps restore AV conduction in some of these patients. Long-term studies are required to assess adverse impact of inflammation on cardiac contractile function.

Funding Acknowledgement

Type of funding sources: None.

Outpatient Randomized Crossover Comparison of Zone Model Predictive Control Automated Insulin Delivery with Weekly Data Driven Adaptation Versus Sensor-Augmented Pump: Results from the International Diabetes Closed-Loop Trial 4

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70-180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70-180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: -1% to +6%], P = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (-1.5% [-2.4% to -0.5%], P = 0.002). The adaptation system decreased initial basal rates by a median of 4% (-8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

Feasibility of Closed-Loop Insulin Delivery with a Pregnancy-Specific Zone Model Predictive Control Algorithm

Objective: Evaluating the feasibility of closed-loop insulin delivery with a zone model predictive control (zone-MPC) algorithm designed for pregnancy complicated by type 1 diabetes (T1D). Research Design and Methods: Pregnant women with T1D from 14 to 32 weeks gestation already using continuous glucose monitor (CGM) augmented pump therapy were enrolled in a 2-day multicenter supervised outpatient study evaluating pregnancy-specific zone-MPC based closed-loop control (CLC) with the interoperable artificial pancreas system (iAPS) running on an unlocked smartphone. Meals and activities were unrestricted. The primary outcome was the CGM percentage of time between 63 and 140 mg/dL compared with participants' 1-week run-in period. Early (2-h) postprandial glucose control was also evaluated. Results: Eleven participants completed the study (age: 30.6 ± 4.1 years; gestational age: 20.7 ± 3.5 weeks; weight: 76.5 ± 15.3 kg; hemoglobin A1c: 5.6% ± 0.5% at enrollment). No serious adverse events occurred. Compared with the 1-week run-in, there was an increased percentage of time in 63-140 mg/dL during supervised CLC (CLC: 81.5%, run-in: 64%, P = 0.007) with less time >140 mg/dL (CLC: 16.5%, run-in: 30.8%, P = 0.029) and time <63 mg/dL (CLC: 2.0%, run-in:5.2%, P = 0.039). There was also less time <54 mg/dL (CLC: 0.7%, run-in:1.6%, P = 0.030) and >180 mg/dL (CLC: 4.9%, run-in: 13.1%, P = 0.032). Overnight glucose control was comparable, except for less time >250 mg/dL (CLC: 0%, run-in:3.9%, P = 0.030) and lower glucose standard deviation (CLC: 23.8 mg/dL, run-in:42.8 mg/dL, P = 0.007) during CLC. Conclusion: In this pilot study, use of the pregnancy-specific zone-MPC was feasible in pregnant women with T1D. Although the duration of our study was short and the number of participants was small, our findings add to the limited data available on the use of CLC systems during pregnancy (NCT04492566).

Outpatient Randomized Crossover Automated Insulin Delivery Versus Conventional Therapy with Induced Stress Challenges

Background: Automated insulin delivery (AID) systems have not been evaluated in the context of psychological and pharmacological stress in type 1 diabetes. Our objective was to determine glycemic control and insulin use with Zone Model Predictive Control (zone-MPC) AID system enhanced for states of persistent hyperglycemia versus sensor-augmented pump (SAP) during outpatient use, including in-clinic induced stress. Materials and Methods: Randomized, crossover, 2-week trial of zone-MPC AID versus SAP in 14 adults with type 1 diabetes. In each arm, each participant was studied in-clinic with psychological stress induction (Trier Social Stress Test [TSST] and Socially Evaluated Cold Pressor Test [SECPT]), followed by pharmacological stress induction with oral hydrocortisone (total four sessions per participant). The main outcomes were 2-week continuous glucose monitor percent time in range (TIR) 70-180 mg/dL, and glucose and insulin outcomes during and overnight following stress induction. Results: During psychological stress, AID decreased glycemic variability percentage by 13.4% (P = 0.009). During pharmacological stress, including the following overnight, there were no differences in glucose outcomes and total insulin between AID and physician-assisted SAP. However, with AID total user-requested insulin was lower by 6.9 U (P = 0.01) for pharmacological stress. Stress induction was validated by changes in heart rate and salivary cortisol levels. During the 2-week AID use, TIR was 74.4% (vs. SAP 63.1%, P = 0.001) and overnight TIR was 78.3% (vs. SAP 63.1%, P = 0.004). There were no adverse events. Conclusions: Zone-MPC AID can reduce glycemic variability and the need for user-requested insulin during pharmacological stress and can improve overall glycemic outcomes. Clinical Trial Identifier NCT04142229.

Optimizing behavioral interventions to regulate gestational weight gain with sequential decision policies using hybrid model predictive control

Excessive gestational weight gain is a significant public health concern that has been the recent focus of control systems-based interventions. Healthy Mom Zone (HMZ) is an intervention study that aims to develop and validate an individually-tailored and "intensively adaptive" intervention to manage weight gain for pregnant women with overweight or obesity using control engineering approaches. This paper presents how Hybrid Model Predictive Control (HMPC) can be used to assign intervention dosages and consequently generate a prescribed intervention with dosages unique to each individuals needs. A Mixed Logical Dynamical (MLD) model enforces the requirements for categorical (discrete-level) doses of intervention components and their sequential assignment into mixed-integer linear constraints. A comprehensive system model that integrates energy balance and behavior change theory, using data from one HMZ participant, is used to illustrate the workings of the HMPC-based control system for the HMZ intervention. Simulations demonstrate the utility of HMPC as a means for enabling optimized complex interventions in behavioral medicine, and the benefits of a HMPC framework in contrast to conventional interventions relying on "IF-THEN" decision rules.

Zone-MPC Automated Insulin Delivery Algorithm Tuned for Pregnancy Complicated by Type 1 Diabetes

Type 1 diabetes (T1D) increases the risk for pregnancy complications. Increased time in the pregnancy glucose target range (63-140 mg/dL as suggested by clinical guidelines) is associated with improved pregnancy outcomes that underscores the need for tight glycemic control. While closed-loop control is highly effective in regulating blood glucose levels in individuals with T1D, its use during pregnancy requires adjustments to meet the tight glycemic control and changing insulin requirements with advancing gestation. In this paper, we tailor a zone model predictive controller (zone-MPC), an optimization-based control strategy that uses model predictions, for use during pregnancy and verify its robustness in-silico through a broad range of scenarios. We customize the existing zone-MPC to satisfy pregnancy-specific glucose control objectives by having (i) lower target glycemic zones (i.e., 80-110 mg/dL daytime and 80-100 mg/dL overnight), (ii) more assertive correction bolus for hyperglycemia, and (iii) a control strategy that results in more aggressive postprandial insulin delivery to keep glucose within the target zone. The emphasis is on leveraging the flexible design of zone-MPC to obtain a controller that satisfies glycemic outcomes recommended for pregnancy based on clinical insight. To verify this pregnancy-specific zone-MPC design, we use the UVA/Padova simulator and conduct in-silico experiments on 10 subjects over 13 scenarios ranging from scenarios with ideal metabolic and treatment parameters for pregnancy to extreme scenarios with such parameters that are highly deviant from the ideal. All scenarios had three meals per day and each meal had 40 grams of carbohydrates. Across 13 scenarios, pregnancy-specific zone-MPC led to a 10.3 ± 5.3% increase in the time in pregnancy target range (baseline zone-MPC: 70.6 ± 15.0%, pregnancy-specific zone-MPC: 80.8 ± 11.3%, p < 0.001) and a 10.7 ± 4.8% reduction in the time above the target range (baseline zone-MPC: 29.0 ± 15.4%, pregnancy-specific zone-MPC: 18.3 ± 12.0, p < 0.001). There was no significant difference in the time below range between the controllers (baseline zone-MPC: 0.5 ± 1.2%, pregnancy-specific zone-MPC: 3.5 ± 1.9%, p = 0.1). The extensive simulation results show improved performance in the pregnancy target range with pregnancy-specific zone MPC, suggest robustness of the zone-MPC in tight glucose control scenarios, and emphasize the need for customized glucose control systems for pregnancy.

Review of Automated Insulin Delivery Systems for Individuals with Type 1 Diabetes: Tailored Solutions for Subpopulations

Automated insulin delivery (AID) systems have proven safe and effective in improving glycemic outcomes in individuals with type 1 diabetes (T1D). Clinical evaluation of this technology has progressed to large randomized, controlled outpatient studies and recent commercial approval of AID systems for children and adults. However, several challenges remain in improving these systems for different subpopulations (e.g., young children, athletes, pregnant women, seniors and those with hypoglycemia unawareness). In this review, we highlight the requirements and challenges in AID design for selected subpopulations, and discuss current advances from recent clinical studies.

AB0610 NORMOCALCAEMIC HYPERPARATHYROIDISM AND BONE HEALTH – WORSE THAN ANTICIPATED?

Background:

Since the formal recognition of normocalcaemic hyperparathyroidism (nHPT) as a distinct entity in 2008, several studies have been published describing the characteristics of these individuals. Controversy exists regarding diagnostics and the role of parathyroidectomy in such cases. A chief reason for lack of consensus is the disagreement among experts regarding the potential complications and a bias towards perhaps benign nature of this condition.

Objectives:

In order to understand the challenges posed by this cohort, we aim to characterise these patients at presentation to our metabolic bone diseases unit with a focus on bone health.

Methods:

We interrogated our departmental database and undertook retrospective analysis of all patients presenting to metabolic bone service at our large university teaching hospital with a catchment population of 350,000. Individuals were included in the survey based on criteria of Vit D >70 nmol/L, normal calcium (2.20-2.60 mmol/L), eGFR>60ml/min and PTH >6.9 pmol/L measured twice at least three months apart.

Results:

Over six months review period, of 134 referrals, 42 (31%) were identified with nHPT. Follow up duration was two years. Mean age was 60 years (25-86). 38 (90%) were women with 31 (81%) post menopause. 34 (80%) were of Caucasian descent. All had comorbidities with median of five (1-14). Polypharmacy (>4 prescribed medicines) was common (36/42, 85%) with mean of seven prescribed medications (0-22). Mean Vit D was 88 (70.4-133.6), calcium 2.43 (2.26-2.58), creatinine 69.8 (48-115) and PTH 8.8 (7.2-14.2). Ten (24%) had already had fragility fractures with mean of two (0-4). 21 had DXA scan with mean T score of -3.78 (-2.1 - -6.0). 13/21(31%) had osteoporosis. Oral and IV bisphosphonates, denosumab and teriparatide were prescribed to 12 (28.5%), 14 (33%), 4 (10%) and one patient respectively.

Conclusion:

Our study suggests high prevalence of nHPT among patients referred to metabolic bone service with confirmed bone health issues. Nearly a third of patients have nHPT in this secondary care setting and a quarter have already suffered fragility fractures. These patients carry high comorbidity, polypharmacy and osteoporosis burden. Management of such patients is challenging owing to complex interplay of various ailments. Bone active agents are required for nearly two-thirds of this group. Though the natural course of nHPT is an area of active research, our data adds to the growing body of evidence that this is not a benign condition with particularly high fracture burden and poor bone quality. nHPT is perhaps responsible for the onset and progression of the similar osseous complications as described in classical PHPT. Further longitudinal studies are required to help devise best management plan to mitigate against the skeletal encumbrance of nHPT.

Disclosure of Interests:

None declared.

Exogenous β-cyclocitral treatment primes tomato plants against drought by inducing tolerance traits, independent of abscisic acid

Drought is the most devastating stress for crops. Intensity and duration of drought determine the magnitude of plant damage; similarly, plant ability to counteract drought determines its tolerance capacity. Recent studies revealed that exogenous apocarotenoid treatment confers abiotic stress tolerance to plants. However, much less is known about the role of β-cyclocitral (βCC), the major apocarotenoid, in drought tolerance. Here, we demonstrate βCC's role in improving plants' tolerance against drought stress. Tomato (Solanum lycopersicum L.) plants were independently treated with water and βCC and grown under either water-limited or irrigated conditions. The βCC-treated drought-exposed (BD) and βCC-treated irrigated (BH) plants were analysed for the major drought tolerance associated traits; water-treated drought-exposed (CD) and water-treated irrigated plants (CH) were used as controls. On exposure to drought, unlike controls, βCC-treated plants showed no wilting, higher RWC and stomatal conductance, unchanged ABA levels and stomatal closure. The BD plants had increased photosynthesis, chlorophyll content and enhanced root, but not shoot, growth. In addition, βCC treatment enhanced proline accumulation and activity of SOD in both drought-exposed and well irrigated plants. Taken together, βCC was identified as a potential candidate that improves tomato osmolyte accumulation and superoxide elimination, independent of ABA, and prepares the plant for upcoming drought stress. Our results suggest that βCC can be used to prime crops against drought stress.

Using Iterative Learning for Insulin Dosage Optimization in Multiple-Daily-Injections Therapy for People With Type 1 Diabetes

OBJECTIVE

In this work, we design iterative algorithms for the delivery of long-acting (basal) and rapid-acting (bolus) insulin, respectively, for people with type 1 diabetes (T1D) on multiple-daily-injections (MDIs) therapy using feedback from self-monitoring of blood glucose (SMBG) measurements.

METHODS

Iterative learning control (ILC) updates basal therapy consisting of one long-acting insulin injection per day, while run-to-run (R2R) adapts meal bolus therapy via the update of the mealtime-specific insulin-to-carbohydrate ratio (CR). Updates are due weekly and are based upon sparse SMBG measurements.

RESULTS

Upon termination of the 20 weeks long in-silico trial, in a scenario characterized by meal carbohydrate (CHO) normally distributed with mean μ = [50, 75, 75] grams and standard deviation σ = [5, 7, 7] grams, our strategy produced statistically significant improvements in time in range (70--180) [mg/dl], from 66.9(33.1) % to 93.6(6.7) %, p = 0.02.

CONCLUSIONS

Iterative learning shows potential to improve glycemic regulation over time by driving blood glucose closer to the recommended glycemic targets.

SIGNIFICANCE

Decision support systems (DSSs) and automated therapy advisors such as the one proposed here are expected to improve glycemic outcomes reducing the burden on patients on MDI therapy.

Randomized Crossover Comparison of Automated Insulin Delivery Versus Conventional Therapy Using an Unlocked Smartphone with Scheduled Pasta and Rice Meal Challenges in the Outpatient Setting

Background: Automated Insulin Delivery (AID) hybrid closed-loop systems have not been well studied in the context of prescribed meals. We evaluated performance of our interoperable artificial pancreas system (iAPS) in the at-home setting, running on an unlocked smartphone, with scheduled meal challenges in a randomized crossover trial. Methods: Ten adults with type 1 diabetes completed 2 weeks of AID-based control and 2 weeks of conventional therapy in random order where they consumed regular pasta or extra-long grain white rice as part of a complete dinner meal on six different occasions in both arms (each meal thrice in random order). Surveys assessed satisfaction with AID use. Results: Postprandial differences in conventional therapy were 10,919.0 mg/dL × min (95% confidence interval [CI] 3190.5-18,648.0, P = 0.009) for glucose area under the curve (AUC) and 40.9 mg/dL (95% CI 4.6-77.3, P = 0.03) for peak continuous glucose monitor glucose, with rice showing greater increases than pasta. White rice resulted in a lower estimate over pasta by a factor of 0.22 (95% CI 0.08-0.63, P = 0.004) for AUC under 70 mg/dL. These glycemic differences in both meal types were reduced under AID-based control and were not statistically significant, where 0-2 h insulin delivery decreased by 0.45 U for pasta (P = 0.001) and by 0.27 U for white rice (P = 0.01). Subjects reported high overall satisfaction with the iAPS. Conclusions: The AID system running on an unlocked smartphone improved postprandial glucose control over conventional therapy in the setting of challenging meals in the outpatient setting. Clinical Trial Registry: clinicaltrials.gov NCT03767790.

The Effect of Two Types of Pasta Versus White Rice on Postprandial Blood Glucose Levels in Adults with Type 1 Diabetes: A Randomized Crossover Trial

Background: Food choices are essential to successful glycemic control for people with diabetes. We compared the impact of three carbohydrate-rich meals on the postprandial glycemic response in adults with type 1 diabetes (T1D). Methods: We performed a randomized crossover study in 12 adults with T1D (age 58.7 ± 14.2 years, baseline hemoglobin A1c 7.5% ± 1.3%) comparing the postprandial glycemic response to three meals using continuous glucose monitoring: (1) "higher protein" pasta containing 10 g protein/serving, (2) regular pasta with 7 g protein/serving, and (3) extra-long grain white rice. All meals contained 42 g carbohydrate; were served with homemade tomato sauce, green salad, and balsamic dressing; and were repeated twice in random order. After their insulin bolus, subjects were observed in clinic for 5 h. Linear mixed effects models were used to assess the glycemic response. Results: Compared with white rice, peak glucose levels were significantly lower for higher protein pasta (-32.6 mg/dL; 95% CI -48.4 to -17.2; P < 0.001) and regular pasta (-43.2 mg/dL, 95% CI -58.7 to -27.7; P < 0.001). The difference between the two types of pastas did not reach statistical significance (-11 mg/dL; 95% CI -24.1 to 3.4; P = 0.17). Total glucose area under the curve was also significantly higher for white rice compared with both pastas (P < 0.001 for both comparisons). Conclusions: This exploratory study concluded that different food types of similar macronutrient content (e.g., rice and pasta) generate significantly different postprandial glycemic responses in persons with T1D. These results provide useful insights into the impact of food choices on and optimization of glucose control. Clinical Trial Registry: clinicaltrials.gov NCT03362151.

OR22-3 Closed-Loop Glucagon Pump: A Novel and Effective Strategy for Post-Bariatric Hypoglycemia

Current therapies for post-bariatric hypoglycemia (PBH) are incompletely effective. We previously reported feasibility of an open-loop glucagon system for this challenging syndrome. In this study, patients with PBH were enrolled in a double-masked, placebo-controlled, crossover trial to determine the efficacy of a closed-loop mini-dose glucagon delivery system to reduce severe hypoglycemia after a mixed meal. A novel hypoglycemia detection & mitigation algorithm was embedded in the Artificial Pancreas System connected to a continuous glucose monitor (CGM, Dexcom) driving a patch infusion pump (Insulet) filled with study drug (Xeris liquid glucagon or vehicle). After screening and enrollment, CGM were placed; participants returned after an overnight fast for the 1^st of 2 study visits. A liquid mixed meal (Ensure Compact: 64 g CHO, 18 g protein, 236 mL) was consumed, and sensor/plasma glucose were measured serially. The system autonomously delivered up to 2 doses of study drug (300/150 mcg of glucagon or equal volume vehicle) if triggered by the hypoglycemia mitigation algorithm. If plasma glucose fell to <55 mg/dL or neuroglycopenia occurred, rescue IV dextrose was given per protocol. During a 2^nd study visit, the protocol was repeated, with pump filled with the other study drug. Twelve participants (11F/1M, age 52+2, postoperative duration 8+1 years, mean+SEM) completed all study visits. In an additional 3 participants, the mixed meal did not trigger either alarm or hypoglycemia, so study drug was not administered, and a second visit was not conducted. For the 12 participants receiving glucagon vs. vehicle during 2 study visits, predictive hypoglycemia alerts prompted automated drug delivery at mean 94+6 vs. 89+5 (p=0.41) minutes post meal, when sensor glucose was 114+7 vs. 121+5 mg/dL (p=0.39). Four participants did not require rescue during either visit; 1 participant required rescue during both visits. Seven participants required rescue glucose after vehicle but not after glucagon (p=0.0082). Similarly, 5 participants had severe hypoglycemia (plasma glucose <55 mg/dL) after vehicle but not after glucagon (p=0.03). Nadir plasma glucose was higher in study visits with glucagon vs. vehicle delivery (67.4±2.7 vs. 58.5±1.9 mg/dL, p=0.004). Glucagon levels were not elevated at time of alert (14.6±1.4 pg/mL) but rose after glucagon delivery (1231±187 vs. vehicle 16 ±1.4 pg/mL at 30 minutes, p = 0.001). No rebound hyperglycemia occurred. Emesis occurred before study drug delivery in 2 visits. Transient pain at infusion site was reported during both glucagon (n=11 of 12) and vehicle (n=10 of 12) study visits. No other adverse advents were observed. Our data demonstrate that a CGM-guided glucagon closed-loop system can detect imminent hypoglycemia and deliver mini-dose glucagon, yielding improvements in post-meal glucose and reducing severe hypoglycemia in patients with PBH.

Lung nodules are reliably detectable on ultra-low-dose CT utilising model-based iterative reconstruction with radiation equivalent to plain radiography

AIM

To determine if ultra-low-dose (ULD) computed tomography (CT) utilising model-based iterative reconstruction (MBIR) with radiation equivalent to plain radiography allows the detection of lung nodules.

MATERIALS AND METHODS

Ninety-nine individuals undergoing surveillance of solid pulmonary nodules undertook a low-dose (LD) and ULD CT during the same sitting. Image pairs were read blinded, in random order, and independently by two experienced thoracic radiologists. With LD-CT as the reference standard, the number, size, and location of nodules was compared, and inter-rater agreement was established.

RESULTS

There was very good inter-rater agreement with regards nodules ≥4mm for both the LD- (k=0.931) and ULD-CT (k=0.869). One hundred and ninety-nine nodules were reported on the LD-CT by both radiologists and 196 reported on the ULD-CT, with no nodules reported only on the ULD-CT. This gives a sensitivity of 98.5% and specificity of 100% for ULD-CT with MBIR. The effective dose of radiation was significantly different between the two scans (p<0.0001), 1.67 mSv for the LD-CT and 0.13 mSv for the ULD-CT.

CONCLUSION

ULD-CT utilising MBIR and delivering radiation equivalent to plain radiography, allows detection of lung nodules with high sensitivity. The attendant 10-fold reduction in radiation may allow for dramatic reductions in cumulative radiation exposure.

A microfluidic platform for the characterisation of membrane active antimicrobials

The spread of bacterial resistance against conventional antibiotics generates a great need for the discovery of novel antimicrobials. Polypeptide antibiotics constitute a promising class of antimicrobial agents that favour attack on bacterial membranes. However, efficient measurement platforms for evaluating their mechanisms of action in a systematic manner are lacking. Here we report an integrated lab-on-a-chip multilayer microfluidic platform to quantify the membranolytic efficacy of such antibiotics. The platform is a biomimetic vesicle-based screening assay, which generates giant unilamellar vesicles (GUVs) in physiologically relevant buffers on demand. Hundreds of these GUVs are individually immobilised downstream in physical traps connected to separate perfusion inlets that facilitate controlled antibiotic delivery. Antibiotic efficacy is expressed as a function of the time needed for an encapsulated dye to leak out of the GUVs as a result of antibiotic treatment. This proof-of-principle study probes the dose response of an archetypal polypeptide antibiotic cecropin B on GUVs mimicking bacterial membranes. The results of the study provide a foundation for engineering quantitative, high-throughput microfluidics devices for screening antibiotics.

Design and Clinical Evaluation of the Interoperable Artificial Pancreas System (iAPS) Smartphone App: Interoperable Components with Modular Design for Progressive Artificial Pancreas Research and Development

BACKGROUND

There is an unmet need for a modular artificial pancreas (AP) system for clinical trials within the existing regulatory framework to further AP research projects from both academia and industry. We designed, developed, and tested the interoperable artificial pancreas system (iAPS) smartphone app that can interface wirelessly with leading continuous glucose monitors (CGM), insulin pump devices, and decision-making algorithms while running on an unlocked smartphone.

METHODS

After algorithm verification, hazard and mitigation analysis, and complete system verification of iAPS, six adults with type 1 diabetes completed 1 week of sensor-augmented pump (SAP) use followed by 48 h of AP use with the iAPS, a Dexcom G5 CGM, and either a Tandem or Insulet insulin pump in an investigational device exemption study. The AP system was challenged by participants performing extensive walking without exercise announcement to the controller, multiple large meals eaten out at restaurants, two overnight periods, and multiple intentional connectivity interruptions.

RESULTS

Even with these intentional challenges, comparison of the SAP phase with the AP study showed a trend toward improved time in target glucose range 70-180 mg/dL (78.8% vs. 83.1%; P = 0.31), and a statistically significant reduction in time below 70 mg/dL (6.1% vs. 2.2%; P = 0.03). The iAPS system performed reliably and showed robust connectivity with the peripheral devices (99.8% time connected to CGM and 94.3% time in closed loop) while requiring limited user intervention.

CONCLUSIONS

The iAPS system was safe and effective in regulating glucose levels under challenging conditions and is suitable for use in unconstrained environments.

Real-Time Detection of Infusion Site Failures in a Closed-Loop Artificial Pancreas

BACKGROUND

As evidence emerges that artificial pancreas systems improve clinical outcomes for patients with type 1 diabetes, the burden of this disease will hopefully begin to be alleviated for many patients and caregivers. However, reliance on automated insulin delivery potentially means patients will be slower to act when devices stop functioning appropriately. One such scenario involves an insulin infusion site failure, where the insulin that is recorded as delivered fails to affect the patient's glucose as expected. Alerting patients to these events in real time would potentially reduce hyperglycemia and ketosis associated with infusion site failures.

METHODS

An infusion site failure detection algorithm was deployed in a randomized crossover study with artificial pancreas and sensor-augmented pump arms in an outpatient setting. Each arm lasted two weeks. Nineteen participants wore infusion sets for up to 7 days. Clinicians contacted patients to confirm infusion site failures detected by the algorithm and instructed on set replacement if failure was confirmed.

RESULTS

In real time and under zone model predictive control, the infusion site failure detection algorithm achieved a sensitivity of 88.0% (n = 25) while issuing only 0.22 false positives per day, compared with a sensitivity of 73.3% (n = 15) and 0.27 false positives per day in the SAP arm (as indicated by retrospective analysis). No association between intervention strategy and duration of infusion sets was observed ( P = .58).

CONCLUSIONS

As patient burden is reduced by each generation of advanced diabetes technology, fault detection algorithms will help ensure that patients are alerted when they need to manually intervene. Clinical Trial Identifier: www.clinicaltrials.gov,NCT02773875.

Design and Clinical Evaluation of a Novel Low-Glucose Prediction Algorithm with Mini-Dose Stable Glucagon Delivery in Post-Bariatric Hypoglycemia

BACKGROUND

Postbariatric hypoglycemia (PBH) is a complication of bariatric surgery with limited therapeutic options. We developed an event-based system to predict and detect hypoglycemia based on continuous glucose monitor (CGM) data and recommend delivery of minidose liquid glucagon.

METHODS

We performed an iterative development clinical study employing a novel glucagon delivery system: a Dexcom CGM connected to a Windows tablet running a hypoglycemia prediction algorithm and an Omnipod pump filled with an investigational stable liquid glucagon formulation. Meal tolerance testing was performed in seven participants with PBH and history of neuroglycopenia. Glucagon was administered when hypoglycemia was predicted. Primary outcome measures included the safety and feasibility of this system to predict and prevent severe hypoglycemia. Secondary outcomes included hypoglycemia prediction by the prediction algorithm, minimization of time below hypoglycemia threshold using glucagon, and prevention of rebound hyperglycemia.

RESULTS

The hypoglycemia prediction algorithm alerted for impending hypoglycemia in the postmeal state, prompting delivery of glucagon (150 μg). After observations of initial incomplete efficacy to prevent hypoglycemia in the first two participants, system modifications were implemented: addition of PBH-specific detection algorithm, increased glucagon dose (300 μg), and a second glucagon dose if needed. These modifications, together with rescue carbohydrates provided to some participants, contributed to progressive improvements in glucose time above the hypoglycemia threshold (75 mg/dL).

CONCLUSIONS

Preliminary results indicate that our event-based automatic monitoring algorithm successfully predicted likely hypoglycemia. Minidose glucagon therapy was well tolerated, without prolonged or severe hypoglycemia, and without rebound hyperglycemia.