Prior conscious experience modulates the impact of audiovisual temporal correspondence on unconscious visual processing.

Conscious visual experiences are enriched by concurrent auditory information, implying audiovisual interactions. In the present study, we investigated how prior conscious experience of auditory and visual information influences the subsequent audiovisual temporal integration under the surface of awareness. We used continuous flash suppression (CFS) to render perceptually invisible a ball-shaped object constantly moving and bouncing inside a square frame window. To examine whether audiovisual temporal correspondence facilitates the ball stimulus to enter awareness, the visual motion was accompanied by click sounds temporally congruent or incongruent with the bounces of the ball. In Experiment 1, where no prior experience of the audiovisual events was given, we found no significant impact of audiovisual correspondence on visual detection time. However, when the temporally congruent or incongruent bounce-sound relations were consciously experienced prior to CFS in Experiment 2, congruent sounds yielded faster detection time compared to incongruent sounds during CFS. In addition, in Experiment 3, explicit processing of the incongruent bounce-sound relation prior to CFS slowed down detection time when the ball bounces became later congruent with sounds during CFS. These findings suggest that audiovisual temporal integration may take place outside of visual awareness though its potency is modulated by previous conscious experiences of the audiovisual events. The results are discussed in light of the framework of multisensory causal inference.

Plasmonic Cyclic Au Nanosphere Hexamers.

Rational design of plasmonic colloidal assemblies via bottom-up synthesis is challenging but would show unprecedented optical properties that strongly relate to the assembly's shape and spatial arrangement. Herein, the synthesis of plasmonic cyclic Au nanosphere hexamers (PCHs) is reported, wherein six Au nanospheres (Au NSs) are connected via thin metal ligaments. By tuning Au reduction, six dangling Au NSs are interconnected with a core hexagon nanoplate (NPL). Then, Pt atoms are selectively deposited on the edges of the spheres. After etching of the core, necklace-like nanostructures of Pt framework are obtained. Deposition of Au is followed, leading to PCHs in high yield (≈90%). Notably, PCHs exhibit the combinatorial plasmonic characteristics of individual Au NSs and the in-plane coupling of the six linked Au NSs. They yield highly uniform, reproducible, and polarization-independent single-particle surface-enhanced Raman scattering signals, which are attributed to the 2-dimensional isotropic alignment of the Au NSs. Those are applied to a SERS-based immunoassay as quantitative and qualitative single particle SERS nanoprobes. This assay shows a low limit-of-detection, down to 100 pm, which is orders of magnitude lower than those based on Au NSs, and one order of magnitude lower than an assay using analogous particles of smooth Au nanorings.

Longitudinal analysis of annual national hemovigilance data to assess pathogen reduced platelet transfusion trends during conversion to routine universal clinical use and 7-day storage.

BACKGROUND: France converted to universal pathogen reduced (PR; amotosalen/UVA) platelets in 2017 and extended platelet component (PC) shelf-life from 5- to 7-days in 2018 and 2019. Annual national hemovigilance (HV) reports characterized longitudinal PC utilization and safety over 11 years, including several years prior to PR adoption as the national standard of care. METHODS: Data were extracted from published annual HV reports. Apheresis and pooled buffy coat [BC] PC use was compared. Transfusion reactions (TRs) were stratified by type, severity, and causality. Trends were assessed for three periods: Baseline (2010-14; ~7% PR), Period 1 ([P1] 2015-17; 8%-21% PR), and Period 2 ([P2] 2018-20; 100% PR). RESULTS: PC use increased by 19.1% between 2010 and 2020. Pooled BC PC production increased from 38.8% to 68.2% of total PCs. Annual changes in PCs issued averaged 2.4% per year at baseline, -0.02% (P1) and 2.8% (P2). The increase in P2 coincided with a reduction in the target platelet dose and extension to 7-day storage. Allergic reactions, alloimmunization, febrile non-hemolytic TRs, immunologic incompatibility, and ineffective transfusions accounted for >90% of TRs. Overall, TR incidence per 100,000 PCs issued declined from 527.9 (2010) to 345.7 (2020). Severe TR rates declined 34.8% between P1-P2. Forty-six transfusion-transmitted bacterial infections (TTBI) were associated with conventional PCs during baseline and P1. No TTBI were associated with amotosalen/UVA PCs. Infections with Hepatitis E (HEV) a non-enveloped virus resistant to PR, were reported in all periods. DISCUSSION: Longitudinal HV analysis demonstrated stable PC utilization trends with reduced patient risk during conversion to universal 7-day amotosalen/UVA PCs.

Ring-in-a-Triangle Nanoframes: Integrating with Intra- and Interhotspots for Highly Amplified Near-Field Focusing.

The development of a stepwise synthetic strategy for Au ring-in-a-triangle nanoframes with a high degree of structural solidity is essential to the advancement of highly amplified near-field focusing. This strategy leads to the formation of an inscribed nanoring in a triangular metal frame with stability to withstand elevated temperatures and an oxidizing environment, which is critical for successful single-particle surface-enhanced Raman scattering (SERS). The existence of inscribed nanorings plays an important role in enhancing the so-called "lightning rod effect," whereby the electromagnetic near-field enhancement occurs on the highly curved curvature of a metallic interface. We evaluated the corresponding single-particle SERS as a function of the thickness of the rims and then constructed two-dimensional (2D) bulk SERS substrates, wherein an ensemble of hotspots exists. The synergic contribution from both inter- and intrahotspots allowed the outstanding linearity of the calibration curve and the lowest limit of detection, ∼10-18 M for the analyte concentration.

Sleep quality and glycaemic variability in a real-life setting in adults with type 1 diabetes.

AIMS/HYPOTHESIS: Suboptimal subjective sleep quality is very common in adults with type 1 diabetes. Reducing glycaemic variability is a key objective in this population. To date, no prior studies have examined the associations between objectively measured sleep quality and overnight glycaemic variability in adults with type 1 diabetes. We aimed to test the hypothesis that poor sleep quality would be associated with greater overnight glycaemic variability. METHODS: Data were collected in the home setting from 20 adults (ten male and ten female participants) with type 1 diabetes who were current insulin pump users. Simultaneous assessments of objective sleep quality (Zmachine Insight+) and continuous glucose monitoring (CGM) were performed over multiple nights (up to 15 nights) in each participant. Due to the real-life nature of this study, the participants kept their usual CGM alerts for out-of-range glucose values. Sleep quality was categorised as 'good' or 'poor' using a composite of objective sleep features (i.e. sleep efficiency, wake after sleep onset and number of awakenings) based on the National Sleep Foundation's consensus criteria. Glycaemic variability was quantified using SD and CV of overnight glucose values based on overnight CGM profiles. RESULTS: A total of 170 nights were analysed. Overall, 86 (51%) nights were categorised as good sleep quality, and 84 (49%) nights were categorised as poor sleep quality. Using linear mixed-effects models, poor sleep quality was significantly associated with greater glycaemic variability as quantified by SD (coefficient: 0.39 [95% CI 0.10, 0.67], p = 0.009) and CV (coefficient: 4.35 [95% CI 0.8, 7.9], p = 0.02) of overnight glucose values, after accounting for age, sex, BMI and overnight insulin dose. There was large inter- and intra-individual variability in sleep and glycaemic characteristics. Both pooled and individual-level data revealed that the nights with poor sleep quality had larger SDs and CVs, and, conversely, the nights with good sleep quality had smaller SDs and CVs. No associations were found between sleep quality and time spent in the target glucose range, or above or below the target glucose range, where CGM alarms are most likely to occur. CONCLUSIONS/INTERPRETATION: Objectively measured sleep quality is associated with overnight glycaemic variability in adults with type 1 diabetes. These findings highlight an important role of sleep quality in overnight glycaemic control in type 1 diabetes. They also provide a strong incentive to both patients and healthcare providers for considering sleep quality in personalised type 1 diabetes glycaemic management plans. Future studies should investigate the mechanisms linking sleep quality to glycaemic variability.

Suppression of Osteoarthritis progression by post-natal Induction of Nkx3.2.

Osteoarthritis (OA) is an incurable joint disease affecting 240 million elderly population, and major unmet medical needs exist for better therapeutic options for OA. During skeletal development, Nkx3.2 has been shown to promote chondrocyte differentiation and survival, but to suppress cartilage hypertrophy and blood vessel invasion. Here we show that Nkx3.2 plays a key role in osteoarthritis (OA) pathogenesis. Marked reduction of Nkx3.2 expression was observed in three different murine OA models. Consistent with these findings, analyses of surgery-induced and age-driven OA models revealed that cartilage-specific post-natal induction of Nkx3.2 can suppress OA progression in mice. These results suggest that Nkx3.2 may serve as a promising target for OA drug development.

Determining Physical Activity Characteristics from Wristband Data for Use in Automated Insulin Delivery Systems.

Algorithms that can determine the type of physical activity (PA) and quantify the intensity can allow precision medicine approaches, such as automated insulin delivery systems that modulate insulin administration in response to PA. In this work, data from a multi-sensor wristband is used to design classifiers to distinguish among five different physical states (PS) (resting, activities of daily living, running, biking, and resistance training), and to develop models to estimate the energy expenditure (EE) of the PA for diabetes therapy. The data collected are filtered, features are extracted from the reconciled signals, and the extracted features are used by machine learning algorithms, including deep-learning techniques, to obtain accurate PS classification and EE estimation. The various machine learning techniques have different success rates ranging from 75.7% to 94.8% in classifying the five different PS. The deep neural network model with long short-term memory has 94.8% classification accuracy. We achieved 0.5 MET (Metabolic Equivalent of Task) root-mean-square error for EE estimation accuracy, relative to indirect calorimetry with randomly selected testing data (10% of collected data). We also demonstrate a 5% improvement in PS classification accuracy and a 0.34 MET decrease in the mean absolute error when using multi-sensor approach relative to using only accelerometer data.

Correction: DNA breakpoint assay reveals a majority of gross duplications occur in tandem reducing VUS classifications in breast cancer predisposition genes.

The PDF and HTML versions of the article have been updated to include the Creative Commons Attribution 4.0 International License information.

DNA breakpoint assay reveals a majority of gross duplications occur in tandem reducing VUS classifications in breast cancer predisposition genes.

PURPOSE: Gross duplications are ambiguous in terms of clinical interpretation due to the limitations of the detection methods that cannot infer their context, namely, whether they occur in tandem or are duplicated and inserted elsewhere in the genome. We investigated the proportion of gross duplications occurring in tandem in breast cancer predisposition genes with the intent of informing their classifications. METHODS: The DNA breakpoint assay (DBA) is a custom, paired-end, next-generation sequencing (NGS) method designed to capture and detect deep-intronic DNA breakpoints in gross duplications in BRCA1, BRCA2, ATM, CDH1, PALB2, and CHEK2. RESULTS: DBA allowed us to ascertain breakpoints for 44 unique gross duplications from 147 probands. We determined that the duplications occurred in tandem in 114 (78%) carriers from this cohort, while the remainder have unknown tandem status. Among the tandem gross duplications that were eligible for reclassification, 95% of them were upgraded to pathogenic. CONCLUSION: DBA is a novel, high-throughput, NGS-based method that informs the tandem status, and thereby the classification of, gross duplications. This method revealed that most gross duplications in the investigated genes occurred in tandem and resulted in a pathogenic classification, which helps to secure the necessary treatment options for their carriers.

Simulation Software for Assessment of Nonlinear and Adaptive Multivariable Control Algorithms: Glucose - Insulin Dynamics in Type 1 Diabetes.

A simulator for testing automatic control algorithms for nonlinear systems with time-varying parameters, variable time delays, and uncertainties is developed. It is based on simulation of virtual patients with Type 1 diabetes (T1D). Nonlinear models are developed to describe glucose concentration (GC) variations based on user-defined scenarios for meal consumption, insulin administration, and physical activity. They compute GC values and physiological variables, such as heart rate, skin temperature, accelerometer, and energy expenditure, that are indicative of physical activities affecting GC dynamics. This is the first simulator designed for assessment of multivariable controllers that consider supplemental physiological variables in addition to GC measurements to improve glycemic control. Virtual patients are generated from distributions of identified model parameters using clinical data. The simulator will enable testing and evaluation of new control algorithms proposed for automated insulin delivery as well as various control algorithms for nonlinear systems with uncertainties, time-varying parameters and delays.

Pathways of the relationships among eating behavior, stress, and coping in adults with type 2 diabetes: A cross-sectional study.

Stress is related to eating behavior, and eating behavior is important in diabetes treatment. The aim of this study was to examine the relationships among perceived stress, diabetes-related stress, coping strategies, and eating behaviors in adults living with type 2 diabetes (T2DM). Adults with type 2 diabetes (n = 183) were recruited from a large metropolitan area in the Midwest United States. Stress factors and coping strategies associated with eating behaviors were measured using validated questionnaires. Structural equation modeling was used to investigate the relationships among perceived stress, diabetes-related stress, coping strategies, and eating behaviors. The final model showed that emotion-oriented coping partially mediated the effect of stress on eating behaviors. Specifically, emotion-oriented coping partially mediated the effect of diabetes-related stress on restrained eating behavior (r = 0.318, p < .001) and emotional eating behavior (r = 0.399, p < .001); emotion-oriented coping partially mediated the effect of perceived stress on external eating behavior (r = 0.276, p < .001). Emotion-oriented coping was found to be a partial mediator in the path model between stress and eating behaviors in people with type 2 diabetes. Knowledge of the association of stress with eating behaviors may prove important for health care providers in treatment and care of people with type 2 diabetes.

Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System.

An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration.

Common genetic variants associated with telomere length confer risk for neuroblastoma and other childhood cancers.

Aberrant telomere lengthening is an important feature of cancer cells in adults and children. In addition to somatic mutations, germline polymorphisms in telomere maintenance genes impact telomere length. Whether these telomere-associated polymorphisms affect risk of childhood malignancies remains largely unexplored. We collected genome-wide data from three groups with pediatric malignancies [neuroblastoma (N = 1516), acute lymphoblastic leukemia (ALL) (N = 958) and osteosarcoma (N = 660)] and three control populations (N = 6892). Using case-control comparisons, we analyzed eight single nucleotide polymorphisms (SNPs) in genes definitively associated with interindividual variation in leukocyte telomere length (LTL) in prior genome-wide association studies: ACYP2, TERC, NAF1, TERT, OBFC1, CTC1, ZNF208 and RTEL1 Six of these SNPs were associated (P < 0.05) with neuroblastoma risk, one with leukemia risk and one with osteosarcoma risk. The allele associated with longer LTL increased cancer risk for all these significantly associated SNPs. Using a weighted linear combination of the eight LTL-associated SNPs, we observed that neuroblastoma patients were predisposed to longer LTL than controls, with each standard deviation increase in genotypically estimated LTL associated with a 1.15-fold increased odds of neuroblastoma (95%CI = 1.09-1.22; P = 7.9×10(-7)). This effect was more pronounced in adolescent-onset neuroblastoma patients (OR = 1.46; 95%CI = 1.03-2.08). A one standard deviation increase in genotypically estimated LTL was more weakly associated with osteosarcoma risk (OR = 1.10; 95%CI = 1.01-1.19; P = 0.017) and leukemia risk (OR = 1.07; 95%CI = 1.00-1.14; P = 0.044), specifically for leukemia patients who relapsed (OR = 1.19; 95%CI = 1.01-1.40; P = 0.043). These results indicate that genetic predisposition to longer LTL is a newly identified risk factor for neuroblastoma and potentially for other cancers of childhood.

Cholinesterase Inhibitor Donepezil Increases Mitochondrial Biogenesis through AMP-Activated Protein Kinase in the Hippocampus.

OBJECTIVE: Donepezil, a widely prescribed drug for Alzheimer's disease (AD), is now considered to have multimodal actions beyond cholinesterase inhibition. We aimed to see whether donepezil enhances mitochondrial biogenesis and relevant signaling pathways since mitochondrial dysfunction is a key feature of the hypometabolic AD brain. METHODS: As a metabolic gauge, AMP-activated protein kinase (AMPK) was investigated as a tentative mediator of neurometabolic action of donepezil. Changes in phospho-AMPK levels, mitochondrial biogenesis, and ATP levels were measured upon donepezil treatment using neuroblastoma cells, primary cultured neurons and ex vivo hippocampal tissue of adult mice. RESULTS: Donepezil dose-dependently increased mitochondrial biogenesis and ATP levels as well as expression of PGC-1α and NRF-1 in neuroblastoma cells. Donepezil dose-dependently activated AMPK; however, inhibition of AMPK abolished the observed effects of donepezil, indicating that AMPK is a key mediator of donepezil's action. Notably, mitochondrial biogenesis upon donepezil treatment was mainly observed within dendritic regions of primary cultured hippocampal neurons. Levels of synaptic markers were also increased by donepezil. Finally, AMPK- dependent mitochondrial biogenesis by donepezil was confirmed in organotypic hippocampal tissue. CONCLUSIONS: Our findings indicate that AMPK/PGC-1α signaling is involved in beneficial actions of donepezil on neurometabolism. Pharmacological activation of AMPK might be a promising approach to counteract AD pathogenesis associated with brain hypometabolism.

Constitutive RelA activation mediated by Nkx3.2 controls chondrocyte viability.

During endochondral ossification, a process that accounts for the majority of bone formation in vertebrates, hypertrophic chondrocytes display a greater susceptibility to apoptosis when compared to proliferating chondrocytes. However, the molecular mechanisms underlying this phenomenon remain unclear. Nkx3.2, a member of the NK class of homeoproteins, is initially expressed in chondrogenic precursor cells, and later, during cartilage maturation, its expression is restricted to proliferating chondrocytes. Here, we show that the nuclear factor kappa B (NF-kappaB) pathway is required for chondrocyte viability and that Nkx3.2 supports chondrocyte survival by constitutively activating RelA. Although signal-dependent NF-kappaB activation has been intensively studied, ligand-independent NF-kappaB activation is poorly understood. The data presented here support a novel ligand-independent mechanism of NF-kappaB activation, whereby Nkx3.2 recruits the RelA-IkappaBalpha heteromeric complex into the nucleus by direct protein-protein interactions and activates RelA through proteasome-dependent IkappaBalpha degradation in the nucleus. Furthermore, we demonstrate that stage-specific NF-kappaB activation, mediated by Nkx3.2, regulates chondrocyte viability during cartilage maturation.

Audiovisual interactions outside of visual awareness during motion adaptation.

Motion aftereffects (MAEs), illusory motion experienced in a direction opposed to real motion experienced during prior adaptation, have been used to assess audiovisual interactions. In a previous study from our laboratory, we demonstrated that a congruent direction of auditory motion presented concurrently with visual motion during adaptation strengthened the consequent visual MAE, compared to when auditory motion was incongruent in direction. Those judgments of MAE strength, however, could have been influenced by expectations or response bias from mere knowledge of the state of audiovisual congruity during adaptation. To prevent such knowledge, we now employed continuous flash suppression to render visual motion perceptually invisible during adaptation, ensuring that observers were completely unaware of visual adapting motion and only aware of the motion direction of the sound they were hearing. We found a small but statistically significant congruence effect of sound on adaptation strength produced by invisible adaptation motion. After considering alternative explanations for this finding, we conclude that auditory motion can impact the strength of visual processing produced by translational visual motion even when that motion transpires outside of awareness.

FREE: A randomized controlled feasibility trial of a cognitive behavioral therapy and technology-assisted intervention to reduce fear of hypoglycemia in young adults with type 1 diabetes.

OBJECTIVE: The purpose of this study was to test the preliminary effectiveness of a cognitive behavioral therapy intervention (Fear Reduction Efficacy Evaluation [FREE]) designed to reduce fear of hypoglycemia in young adults with type 1 diabetes. The primary outcome was fear of hypoglycemia, secondary outcomes were A1C, and glycemic variability. METHODS: A randomized clinical trial was used to test an 8-week intervention (FREE) compared to an attention control (diabetes education) in 50 young adults with type 1 diabetes who experienced fear of hypoglycemia at baseline. All participants wore a continuous glucose monitor for the 8-week study period. Self-reported fear of hypoglycemia point-of-care A1C testing, continuous glucose monitor-derived glucose variability were measured at baseline, Week 8, and Week 12 (post-program). RESULTS: Compared to controls, those participating in the FREE intervention experienced a reduction in fear of hypoglycemia (SMD B = -8.52, p = 0.021), change in A1C (SMD B = 0.04, p = 0.841) and glycemic variability (glucose standard deviation SMD B = -2.5, p = 0.545) by the end of the intervention. This represented an 8.52% greater reduction in fear of hypoglycemia. CONCLUSION: A cognitive behavioral therapy intervention (FREE) resulted in improvements in fear of hypoglycemia. CLINICALTRIALS: govNCT03549104.

NMR analysis of G-protein betagamma subunit complexes reveals a dynamic G(alpha)-Gbetagamma subunit interface and multiple protein recognition modes.

G-protein betagamma (Gbetagamma) subunits interact with a wide range of molecular partners including: G(alpha) subunits, effectors, peptides, and small molecule inhibitors. The molecular mechanisms underlying the ability to accommodate this wide range of structurally distinct binding partners are not well understood. To uncover the role of protein flexibility and alterations in protein conformation in molecular recognition by Gbetagamma, a method for site-specific (15)N-labeling of Gbeta-Trp residue backbone and indole amines in insect cells was developed. Transverse Relaxation Optimized Spectroscopy-Heteronuclear Single-Quantum Coherence Nuclear Magnetic Resonance (TROSY-HSQC NMR) analysis of (15)N-Trp Gbetagamma identified well-dispersed signals for the individual Trp residue side chain and amide positions. Surprisingly, a wide range of signal intensities was observed in the spectrum, likely representing a range of backbone and side chain mobilities. The signal for GbetaW99 indole was very intense, suggesting a high level of mobility on the protein surface and molecular dynamics simulations indicate that GbetaW99 is highly mobile on the nanosecond timescale in comparison with other Gbeta tryptophans. Binding of peptides and phosducin dramatically altered the mobility of GbetaW99 and GbetaW332 in the binding site and the chemical shifts at sites distant from the direct binding surface in distinct ways. In contrast, binding of G(alpha)(i1)-GDP to Gbetagamma had relatively little effect on the spectrum and, most surprisingly, did not significantly alter Trp mobility at the subunit interface. This suggests the inactive heterotrimer in solution adopts a conformation with an open subunit interface a large percentage of the time. Overall, these data show that Gbetagamma subunits explore a range of conformations that can be exploited during molecular recognition by diverse binding partners.

Multivariable Automated Insulin Delivery System for Handling Planned and Spontaneous Physical Activities.

BACKGROUND: Hybrid closed-loop control of glucose levels in people with type 1 diabetes mellitus (T1D) is limited by the requirements on users to manually announce physical activity (PA) and meals to the artificial pancreas system. Multivariable automated insulin delivery (mvAID) systems that can handle unannounced PAs and meals without any manual announcements by the user can improve glycemic control by modulating insulin dosing in response to the occurrence and intensity of spontaneous physical activities. METHODS: An mvAID system is developed to supplement the glucose measurements with additional physiological signals from a wristband device, with the signals analyzed using artificial intelligence algorithms to automatically detect the occurrence of PA and estimate its intensity. This additional information gained from the physiological signals enables more proactive insulin dosing adjustments in response to both planned exercise and spontaneous unanticipated physical activities. RESULTS: In silico studies of the mvAID illustrate the safety and efficacy of the system. The mvAID is translated to pilot clinical studies to assess its performance, and the clinical experiments demonstrate an increased time in range and reduced risk of hypoglycemia following unannounced PA and meals. CONCLUSIONS: The mvAID systems can increase the safety and efficacy of insulin delivery in the presence of unannounced physical activities and meals, leading to improved lives and less burden on people with T1D.