A TIAM1-TRIM28 complex mediates epigenetic silencing of protocadherins to promote migration of lung cancer cells.

Lung cancer is the leading cause of cancer deaths. Its high mortality is associated with high metastatic potential. Here, we show that the RAC1-selective guanine nucleotide exchange factor T cell invasion and metastasis-inducing protein 1 (TIAM1) promotes cell migration and invasion in the most common subtype of lung cancer, non-small-cell lung cancer (NSCLC), through an unexpected nuclear function. We show that TIAM1 interacts with TRIM28, a master regulator of gene expression, in the nucleus of NSCLC cells. We reveal that a TIAM1-TRIM28 complex promotes epithelial-to-mesenchymal transition, a phenotypic switch implicated in cell migration and invasion. This occurs through H3K9me3-induced silencing of protocadherins and by decreasing E-cadherin expression, thereby antagonizing cell-cell adhesion. Consistently, TIAM1 or TRIM28 depletion suppresses the migration of NSCLC cells, while migration is restored by the simultaneous depletion of protocadherins. Importantly, high nuclear TIAM1 in clinical specimens is associated with advanced-stage lung adenocarcinoma, decreased patient survival, and inversely correlates with E-cadherin expression.

Quantifying insulin-mediated and noninsulin-mediated changes in glucose dynamics during resistance exercise in type 1 diabetes.

Exercise can cause dangerous fluctuations in blood glucose in people living with type 1 diabetes (T1D). Aerobic exercise, for example, can cause acute hypoglycemia secondary to increased insulin-mediated and noninsulin-mediated glucose utilization. Less is known about how resistance exercise (RE) impacts glucose dynamics. Twenty-five people with T1D underwent three sessions of either moderate or high-intensity RE at three insulin infusion rates during a glucose tracer clamp. We calculated time-varying rates of endogenous glucose production (EGP) and glucose disposal (Rd) across all sessions and used linear regression and extrapolation to estimate insulin- and noninsulin-mediated components of glucose utilization. Blood glucose did not change on average during exercise. The area under the curve (AUC) for EGP increased by 1.04 mM during RE (95% CI: 0.65-1.43, P < 0.001) and decreased proportionally to insulin infusion rate (0.003 mM per percent above basal rate, 95% CI: 0.001-0.006, P = 0.003). The AUC for Rd rose by 1.26 mM during RE (95% CI: 0.41-2.10, P = 0.004) and increased proportionally with insulin infusion rate (0.04 mM per percent above basal rate, CI: 0.03-0.04, P < 0.001). No differences were observed between the moderate and high resistance groups. Noninsulin-mediated glucose utilization rose significantly during exercise before returning to baseline roughly 30-min postexercise. Insulin-mediated glucose utilization remained unchanged during exercise sessions. Circulating catecholamines and lactate rose during exercise despite relatively small changes observed in Rd. Results provide an explanation of why RE may pose a lower overall risk for hypoglycemia.NEW & NOTEWORTHY Aerobic exercise is known to cause decreases in blood glucose secondary to increased glucose utilization in people living with type 1 diabetes (T1D). However, less is known about how resistance-type exercise impacts glucose dynamics. Twenty-five participants with T1D performed in-clinic weight-bearing exercises under a glucose clamp. Mathematical modeling of infused glucose tracer allowed for quantification of the rate of hepatic glucose production as well as rates of insulin-mediated and noninsulin-mediated glucose uptake experienced during resistance exercise.

Separating insulin-mediated and non-insulin-mediated glucose uptake during and after aerobic exercise in type 1 diabetes.

Aerobic exercise in type 1 diabetes (T1D) causes rapid increase in glucose utilization due to muscle work during exercise, followed by increased insulin sensitivity after exercise. Better understanding of these changes is necessary for models of exercise in T1D. Twenty-six individuals with T1D underwent three sessions at three insulin rates (100%, 150%, 300% of basal). After 3-h run-in, participants performed 45 min aerobic exercise (moderate or intense). We determined area under the curve for endogenous glucose production (AUCEGP) and rate of glucose disappearance (AUCRd) over 45 min from exercise start. A novel application of linear regression of Rd across the three insulin sessions allowed separation of insulin-mediated from non-insulin-mediated glucose uptake before, during, and after exercise. AUCRd increased 12.45 mmol/L (CI = 10.33-14.58, P < 0.001) and 13.13 mmol/L (CI = 11.01-15.26, P < 0.001) whereas AUCEGP increased 1.66 mmol/L (CI = 1.01-2.31, P < 0.001) and 3.46 mmol/L (CI = 2.81-4.11, P < 0.001) above baseline during moderate and intense exercise, respectively. AUCEGP increased during intense exercise by 2.14 mmol/L (CI = 0.91-3.37, P < 0.001) compared with moderate exercise. There was significant effect of insulin infusion rate on AUCRd equal to 0.06 mmol/L per % above basal rate (CI = 0.05-0.07, P < 0.001). Insulin-mediated glucose uptake rose during exercise and persisted hours afterward, whereas non-insulin-mediated effect was limited to the exercise period. To our knowledge, this method of isolating dynamic insulin- and non-insulin-mediated uptake has not been previously employed during exercise. These results will be useful in informing glucoregulatory models of T1D. The study has been registered at www.clinicaltrials.gov as NCT03090451.NEW & NOTEWORTHY Separating insulin and non-insulin glucose uptake dynamically during exercise in type 1 diabetes has not been done before. We use a multistep process, including a previously described linear regression method, over three insulin infusion sessions, to perform this separation and can graph these components before, during, and after exercise for the first time.

From infection niche to therapeutic target: the intracellular lifestyle of Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) is an obligate human pathogen killing millions of people annually. Treatment for tuberculosis is lengthy and complicated, involving multiple drugs and often resulting in serious side effects and non-compliance. Mtb has developed numerous complex mechanisms enabling it to not only survive but replicate inside professional phagocytes. These mechanisms include, among others, overcoming the phagosome maturation process, inhibiting the acidification of the phagosome and inhibiting apoptosis. Within the past decade, technologies have been developed that enable a more accurate understanding of Mtb physiology within its intracellular niche, paving the way for more clinically relevant drug-development programmes. Here we review the molecular biology of Mtb pathogenesis offering a unique perspective on the use and development of therapies that target Mtb during its intracellular life stage.

Aggression: Perspectives from social and systems neuroscience.

Exhibiting behavioral plasticity in order to mount appropriate responses to dynamic and novel social environments is crucial to the survival of all animals. Thus, how animals regulate flexibility in the timing, duration, and intensity of specific behaviors is of great interest to biologists. In this review, we discuss how animals rapidly respond to social challenges, with a particular focus on aggression. We utilize a conceptual framework to understand the neural mechanisms of aggression that is grounded in Wingfield and colleagues' Challenge Hypothesis, which has profoundly influenced how scientists think about aggression and the mechanisms that allow animals to exhibit flexible responses to social instability. Because aggressive behavior is rooted in social interactions, we propose that mechanisms modulating prosocial behavior may be intricately tied to mechanisms of aggression. Therefore, in order to better understand how aggressive behavior is mediated, we draw on perspectives from social neuroscience and discuss how social context, species-typical behavioral phenotype, and neural systems commonly studied in relation to prosocial behavior (i.e., neuropeptides) contribute to organizing rapid responses to social challenges. Because complex behaviors are not the result of one mechanism or a single neural system, we consider how multiple neural systems important for prosocial and aggressive behavior (i.e., neuropeptides and neurosteroids) interact in the brain to produce behavior in a rapid, context-appropriate manner. Applying a systems neuroscience perspective and seeking to understand how multiple systems functionally integrate to rapidly modulate behavior holds great promise for expanding our knowledge of the mechanisms underlying social behavioral plasticity.

A Probabilistic Approach for Predicting Methane Occurrence in Groundwater.

Aqueous geochemistry datasets from regional groundwater monitoring programs can be a major asset for environmental baseline assessment (EBA) in regions with development of natural gases from unconventional hydrocarbon resources. However, they usually do not include crucial parameters for EBA in areas of shale gas development such as methane concentrations. A logistic regression (LR) model was developed to predict the probability of methane occurrence in aquifers in Alberta (Canada). The model was calibrated and tested using geochemistry data including methane concentrations from two groundwater monitoring programs. The LR model correctly predicts methane occurrence in 89.8% (n = 234 samples) and 88.1% (n = 532 samples) of groundwater samples from each monitoring program. Methane concentrations strongly depend on the occurrence of electron donors such as sulfate and to a lesser extent on well depth and the total dissolved solids of groundwater. The model was then applied to a province-wide public health groundwater monitoring program (n = 52,849 samples) providing aqueous geochemistry data but no methane concentrations. This approach allowed the prediction of methane occurrence in regions where no groundwater gas data are available, thereby increasing the resolution of EBA in areas of shale gas development by using basic hydrochemical parameters measured in high-density groundwater monitoring programs.

Expression quantitative trait locus mapping across water availability environments reveals contrasting associations with genomic features in Arabidopsis.

The regulation of gene expression is crucial for an organism's development and response to stress, and an understanding of the evolution of gene expression is of fundamental importance to basic and applied biology. To improve this understanding, we conducted expression quantitative trait locus (eQTL) mapping in the Tsu-1 (Tsushima, Japan) × Kas-1 (Kashmir, India) recombinant inbred line population of Arabidopsis thaliana across soil drying treatments. We then used genome resequencing data to evaluate whether genomic features (promoter polymorphism, recombination rate, gene length, and gene density) are associated with genes responding to the environment (E) or with genes with genetic variation (G) in gene expression in the form of eQTLs. We identified thousands of genes that responded to soil drying and hundreds of main-effect eQTLs. However, we identified very few statistically significant eQTLs that interacted with the soil drying treatment (GxE eQTL). Analysis of genome resequencing data revealed associations of several genomic features with G and E genes. In general, E genes had lower promoter diversity and local recombination rates. By contrast, genes with eQTLs (G) had significantly greater promoter diversity and were located in genomic regions with higher recombination. These results suggest that genomic architecture may play an important a role in the evolution of gene expression.

Seasonal Variation in Group Size Is Related to Seasonal Variation in Neuropeptide Receptor Density.

In many species, seasonal variation in grouping behavior is widespread, with shifts towards territoriality in the breeding season and grouping in the winter. Compared to the hormonal and neural mechanisms of seasonal territorial aggression, the mechanisms that promote seasonal grouping have received little attention. We collected brains in spring and winter from wild-caught males of two species of emberizid sparrows that seasonally flock (the field sparrow, Spizella pusilla, and the dark-eyed junco, Junco hyemalis) and two species that do not seasonally flock (the song sparrow, Melospiza melodia, and the eastern towhee, Pipilo erythrophthalmus). We used receptor autoradiography to quantify seasonal plasticity in available binding sites for three neuropeptides known to influence social behavior. We examined binding sites for 125I-vasoactive intestinal polypeptide (VIP), 125I-sauvagine (SG, a ligand for corticotropin-releasing hormone receptors) and 125I-ornithine vasotocin analog (OVTA, a ligand for the VT3 nonapeptide). For all species and ligands, brain areas that exhibited a seasonal pattern in binding density were characterized by a winter increase. Compared to nonflocking species, seasonally flocking species showed different binding patterns in multiple brain areas. Furthermore, we found that winter flocking was associated with elevated winter 125I-VIP binding density in the medial amygdala, as well as 125I-VIP and 125I-OVTA binding density in the rostral arcopallium. While the functional significance of the avian rostral arcopallium is unclear, it may incorporate parts of the pallial amygdala. Our results point to this previously undescribed area as a likely hot spot of social modulation.

To flock or fight: neurochemical signatures of divergent life histories in sparrows.

Many bird species exhibit dramatic seasonal switches between territoriality and flocking, but whereas neuroendocrine mechanisms of territorial aggression have been extensively studied, those of seasonal flocking are unknown. We collected brains in spring and winter from male field sparrows (Spizella pusilla), which seasonally flock, and male song sparrows (Melospiza melodia), which are territorial year-round in much of their range. Spring collections were preceded by field-based assessments of aggression. Tissue series were immunofluorescently multilabeled for vasotocin, mesotocin (MT), corticotropin-releasing hormone (CRH), vasoactive intestinal polypeptide, tyrosine hydroxylase, and aromatase, and labeling densities were measured in many socially relevant brain areas. Extensive seasonal differences are shared by both species. Many measures correlate significantly with both individual and species differences in aggression, likely reflecting evolved mechanisms that differentiate the less aggressive field sparrow from the more aggressive song sparrow. Winter-specific species differences include a substantial increase of MT and CRH immunoreactivity in the dorsal lateral septum (LS) and medial amygdala of field sparrows but not song sparrows. These species differences likely relate to flocking rather than the suppression of winter aggression in field sparrows, because similar winter differences were found for two other emberizids that are not territorial in winter--dark-eyed juncos (Junco hyemalis), which seasonally flock, and eastern towhees (Pipilo erythropthalmus), which do not flock. MT signaling in the dorsal LS is also associated with year-round species differences in grouping in estrildid finches, suggesting that common mechanisms are targeted during the evolution of different life histories.

Social Participation and Loneliness in Older Adults in a Rural Australian Context: Individual and Organizational Perspectives.

A rise in aging populations globally calls attention to factors that influence the well-being and health of older adults, including social participation. In Australia, rural older adults face cultural, social, and physical challenges that place them at risk for isolation. Thus, research surrounding social participation and healthy aging is increasingly relevant, especially in rural areas. This qualitative study in a remote town in Western Australia explores barriers and facilitators to older adults' social participation. To investigate multiple perspectives, 23 adults aged 50+ and 19 organizations from a rural town were interviewed. A stakeholder reference group was engaged to refine the research design and validate the findings. Feedback from early interviews was used to refine the data collection process, thus enhancing the validity of the findings. Thematic analysis showed that health and mobility issues, inadequate infrastructure, poor sustainability, and cultural tensions commonly impacted social participation. Themes of rural town culture, cultural power dynamics, and rural stoicism were identified as cultural aspects that inhibited participation. Based on results of this study and the supporting literature, recommendations for inclusive activities include supporting community-designed programs, utilizing culturally sensitive language and personnel, expanding services using existing community resources, and diversifying older adults' roles in existing groups.

Heart and shoal: Social cues and oxytocin receptors impact stress recovery in the zebrafish.

In many species, social interactions decrease behavioral, hormonal, and neural responses to environmental stressors. While "social buffering" and its mechanisms have received considerable attention in mammals, we know less about the phenomenon in fish. The nonapeptide oxytocin regulates social behavior across vertebrates and plays an important role in social buffering in mammals. We investigated social buffering in the zebrafish by evaluating how the social environment and oxytocin receptors impact recovery from an acute stressor. Male and female fish were briefly exposed to alarm substance and recovered either in isolation or within view of a stimulus shoal. Alarm substance did not increase social approach, but social stimuli improved behavioral stress recovery. Oxytocin receptor antagonism decreased social approach during stress recovery and impaired stress recovery exclusively in individuals with access to visual social stimuli. Our findings contribute to the growing body of evidence that social stimuli buffer stress responses in fish and suggest that oxytocin receptors may play a role in socially-buffered stress recovery across taxa.

Design and In Silico Evaluation of an Exercise Decision Support System Using Digital Twin Models.

BACKGROUND: Managing glucose levels during exercise is challenging for individuals with type 1 diabetes (T1D) since multiple factors including activity type, duration, intensity and other factors must be considered. Current decision support tools lack personalized recommendations and fail to distinguish between aerobic and resistance exercise. We propose an exercise-aware decision support system (exDSS) that uses digital twins to deliver personalized recommendations to help people with T1D maintain safe glucose levels (70-180 mg/dL) and avoid low glucose (<70 mg/dL) during and after exercise. METHODS: We evaluated exDSS using various exercise and meal scenarios recorded from a large, free-living study of aerobic and resistance exercise. The model inputs were heart rate, insulin, and meal data. Glucose responses were simulated during and after 30-minute exercise sessions (676 aerobic, 631 resistance) from 247 participants. Glucose outcomes were compared when participants followed exDSS recommendations, clinical guidelines, or did not modify behavior (no intervention). RESULTS: exDSS significantly improved mean time in range for aerobic (80.2% to 92.3%, P < .0001) and resistance (72.3% to 87.3%, P < .0001) exercises compared with no intervention, and versus clinical guidelines (aerobic: 82.2%, P < .0001; resistance: 80.3%, P < .0001). exDSS reduced time spent in low glucose for both exercise types compared with no intervention (aerobic: 15.1% to 5.1%, P < .0001; resistance: 18.2% to 6.6%, P < .0001) and was comparable with following clinical guidelines (aerobic: 4.5%, resistance: 8.1%, P = N.S.). CONCLUSIONS: The exDSS tool significantly improved glucose outcomes during and after exercise versus following clinical guidelines and no intervention providing motivation for clinical evaluation of the exDSS system.

Scalable intracellular delivery via microfluidic vortex shedding enhances the function of chimeric antigen receptor T-cells.

Adoptive chimeric antigen receptor T-cell (CAR-T) therapy is transformative and approved for hematologic malignancies. It is also being developed for the treatment of solid tumors, autoimmune disorders, heart disease, and aging. Despite unprecedented clinical outcomes, CAR-T and other engineered cell therapies face a variety of manufacturing and safety challenges. Traditional methods, such as lentivirus transduction and electroporation, result in random integration or cause significant cellular damage, which can limit the safety and efficacy of engineered cell therapies. We present hydroporation as a gentle and effective alternative for intracellular delivery. Hydroporation resulted in 1.7- to 2-fold higher CAR-T yields compared to electroporation with superior cell viability and recovery. Hydroporated cells exhibited rapid proliferation, robust target cell lysis, and increased pro-inflammatory and regulatory cytokine secretion in addition to improved CAR-T yield by day 5 post-transfection. We demonstrate that scaled-up hydroporation can process 5 x 108 cells in less than 10 s, showcasing the platform as a viable solution for high-yield CAR-T manufacturing with the potential for improved therapeutic outcomes.

Lessons learned: drive-through COVID-19 clinic testing during an adaptive epidemic response and a point-of-care test assessment of a computer-read rapid lateral flow immunoassay with fluorescence-based detection.

Background. The COVID-19 pandemic demonstrated a need for robust SARS-CoV-2 test evaluation infrastructure to underpin biosecurity and protect the population during a pandemic health emergency.Gap statement. The first generation of rapid antigen tests was less accurate than molecular methods due to their inherent sensitivity and specificity shortfalls, compounded by the consequences of self-testing. This created a need for more accurate point-of-care SARS-CoV-2 detection methods.Aim. Here we present the lessons-learned during the COVID-19 emergency response in Western Australia including the detailed set-up, evaluation and operation of rapid antigen test in a state-run drive-through sample collection service during the COVID-19 pandemic after the strict border shutdown ended.Methods. We report a conformity assessment of a novel, second-generation rapid antigen test (Virulizer) comprising a technician-operated rapid lateral flow immunoassay with fluorescence-based detection.Results. The Virulizer rapid antigen test demonstrated up to 100% sensitivity (95% CI: 61.0-100%), 91.94% specificity (95% CI: 82.5-96.5%) and 92.65% accuracy when compared to a commercial PCR assay method. Wide confidence intervals in our series reflect the limits of small sample size. Nevertheless, the Virulizer assay performance was well-suited to point-of-care screening for SARS-CoV-2 in a drive-through clinic setting.Conclusion. The adaptive evaluation process necessary under changing pandemic conditions enabled assessment of a simple sample collection and point-of-care testing process, and showed how this system could be rapidly deployed for SARS-CoV-2 testing, including to regional and remote settings.

Scalable intracellular delivery via microfluidic vortex shedding enhances the function of chimeric antigen receptor T-cells.

Adoptive chimeric antigen receptor T-cell (CAR-T) therapy is transformative and approved for hematologic malignancies. It is also being developed for the treatment of solid tumors, autoimmune disorders, heart disease, and aging. Despite unprecedented clinical outcomes, CAR-T and other engineered cell therapies face a variety of manufacturing and safety challenges. Traditional methods, such as lentivirus transduction and electroporation, result in random integration or cause significant cellular damage, which can limit the safety and efficacy of engineered cell therapies. We present hydroporation as a gentle and effective alternative for intracellular delivery. Hydroporation resulted in 1.7- to 2-fold higher CAR-T yields compared to electroporation with superior cell viability and recovery. Hydroporated cells exhibited rapid proliferation, robust target cell lysis, and increased pro-inflammatory and regulatory cytokine secretion in addition to improved CAR-T yield by day 5 post-transfection. We demonstrate that scaled-up hydroporation can process 5 x 108 cells in less than 10 s, showcasing the platform as a viable solution for high-yield CAR-T manufacturing with the potential for improved therapeutic outcomes.

The diversity of clinical Mycobacterium abscessus isolates in morphology, glycopeptidolipids and infection rates in a macrophage model.

Introduction. Mycobacterium abscessus (MABS) is a pathogenic bacterium that can cause severe lung infections, particularly in individuals with cystic fibrosis. MABS colonies can exhibit either a smooth (S) or rough (R) morphotype, influenced by the presence or absence of glycopeptidolipids (GPLs) on their surface, respectively. Despite the clinical significance of these morphotypes, the relationship between GPL levels, morphotype and the pathogenesis of MABS infections remains poorly understood.Gap statement. The mechanisms and implications of GPL production and morphotypes in clinical MABS infections are unclear. There is a gap in understanding their correlation with infectivity and pathogenicity, particularly in patients with underlying lung disease.Aim. This study aimed to investigate the correlation between MABS morphology, GPL and infectivity by analysing strains from cystic fibrosis patients' sputum samples.Methodology. MABS was isolated from patient sputum samples and categorized by morphotype, GPL profile and replication rate in macrophages. A high-content ex vivo infection model using THP-1 cells assessed the infectivity of both clinical and laboratory strains.Results. Our findings revealed that around 50 % of isolates displayed mixed morphologies. GPL analysis confirmed a consistent relationship between GPL content and morphotype that was only found in smooth isolates. Across morphotype groups, no differences were observed in vitro, yet clinical R strains were observed to replicate at higher levels in the THP-1 infection model. Moreover, the proportion of infected macrophages was notably higher among clinical R strains compared to their S counterparts at 72 h post-infection. Clinical variants also infected THP-1 cells at significantly higher rates compared to laboratory strains, highlighting the limited translatability of lab strain infection data to clinical contexts.Conclusion. Our study confirmed the general correlation between morphotype and GPL levels in smooth strains yet unveiled more variability within morphotype groups than previously recognized, particularly during intracellular infection. As the R morphotype is the highest clinical concern, these findings contribute to the expanding knowledge base surrounding MABS infections, offering insights that can steer diagnostic methodologies and treatment approaches.

Integrating metabolic expenditure information from wearable fitness sensors into an AI-augmented automated insulin delivery system: a randomised clinical trial.

BACKGROUND: Exercise can rapidly drop glucose in people with type 1 diabetes. Ubiquitous wearable fitness sensors are not integrated into automated insulin delivery (AID) systems. We hypothesised that an AID can automate insulin adjustments using real-time wearable fitness data to reduce hypoglycaemia during exercise and free-living conditions compared with an AID not automating use of fitness data. METHODS: Our study population comprised of individuals (aged 21-50 years) with type 1 diabetes from from the Harold Schnitzer Diabetes Health Center clinic at Oregon Health and Science University, OR, USA, who were enrolled into a 76 h single-centre, two-arm randomised (4-block randomisation), non-blinded crossover study to use (1) an AID that detects exercise, prompts the user, and shuts off insulin during exercise using an exercise-aware adaptive proportional derivative (exAPD) algorithm or (2) an AID that automates insulin adjustments using fitness data in real-time through an exercise-aware model predictive control (exMPC) algorithm. Both algorithms ran on iPancreas comprising commercial glucose sensors, insulin pumps, and smartwatches. Participants executed 1 week run-in on usual therapy followed by exAPD or exMPC for one 12 h primary in-clinic session involving meals, exercise, and activities of daily living, and 2 free-living out-patient days. Primary outcome was time below range (<3·9 mmol/L) during the primary in-clinic session. Secondary outcome measures included mean glucose and time in range (3·9-10 mmol/L). This trial is registered with ClinicalTrials.gov, NCT04771403. FINDINGS: Between April 13, 2021, and Oct 3, 2022, 27 participants (18 females) were enrolled into the study. There was no significant difference between exMPC (n=24) versus exAPD (n=22) in time below range (mean [SD] 1·3% [2·9] vs 2·5% [7·0]) or time in range (63·2% [23·9] vs 59·4% [23·1]) during the primary in-clinic session. In the 2 h period after start of in-clinic exercise, exMPC had significantly lower mean glucose (7·3 [1·6] vs 8·0 [1·7] mmol/L, p=0·023) and comparable time below range (1·4% [4·2] vs 4·9% [14·4]). Across the 76 h study, both algorithms achieved clinical time in range targets (71·2% [16] and 75·5% [11]) and time below range (1·0% [1·2] and 1·3% [2·2]), significantly lower than run-in period (2·4% [2·4], p=0·0004 vs exMPC; p=0·012 vs exAPD). No adverse events occurred. INTERPRETATION: AIDs can integrate exercise data from smartwatches to inform insulin dosing and limit hypoglycaemia while improving glucose outcomes. Future AID systems that integrate exercise metrics from wearable fitness sensors may help people living with type 1 diabetes exercise safely by limiting hypoglycaemia. FUNDING: JDRF Foundation and the Leona M and Harry B Helmsley Charitable Trust, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases.

Combining uncertainty-aware predictive modeling and a bedtime Smart Snack intervention to prevent nocturnal hypoglycemia in people with type 1 diabetes on multiple daily injections.

OBJECTIVE: Nocturnal hypoglycemia is a known challenge for people with type 1 diabetes, especially for physically active individuals or those on multiple daily injections. We developed an evidential neural network (ENN) to predict at bedtime the probability and timing of nocturnal hypoglycemia (0-4 vs 4-8 h after bedtime) based on several glucose metrics and physical activity patterns. We utilized these predictions in silico to prescribe bedtime carbohydrates with a Smart Snack intervention specific to the predicted minimum nocturnal glucose and timing of nocturnal hypoglycemia. MATERIALS AND METHODS: We leveraged free-living datasets collected from 366 individuals from the T1DEXI Study and Glooko. Inputs to the ENN used to model nocturnal hypoglycemia were derived from demographic information, continuous glucose monitoring, and physical activity data. We assessed the accuracy of the ENN using area under the receiver operating curve, and the clinical impact of the Smart Snack intervention through simulations. RESULTS: The ENN achieved an area under the receiver operating curve of 0.80 and 0.71 to predict nocturnal hypoglycemic events during 0-4 and 4-8 h after bedtime, respectively, outperforming all evaluated baseline methods. Use of the Smart Snack intervention reduced probability of nocturnal hypoglycemia from 23.9 ± 14.1% to 14.0 ± 13.3% and duration from 7.4 ± 7.0% to 2.4 ± 3.3% in silico. DISCUSSION: Our findings indicate that the ENN-based Smart Snack intervention has the potential to significantly reduce the frequency and duration of nocturnal hypoglycemic events. CONCLUSION: A decision support system that combines prediction of minimum nocturnal glucose and proactive recommendations for bedtime carbohydrate intake might effectively prevent nocturnal hypoglycemia and reduce the burden of glycemic self-management.

Enabling fully automated insulin delivery through meal detection and size estimation using Artificial Intelligence.

We present a robust insulin delivery system that includes automated meal detection and carbohydrate content estimation using machine learning for meal insulin dosing called robust artificial pancreas (RAP). We conducted a randomized, single-center crossover trial to compare postprandial glucose control in the four hours following unannounced meals using a hybrid model predictive control (MPC) algorithm and the RAP system. The RAP system includes a neural network model to automatically detect meals and deliver a recommended meal insulin dose. The meal detection algorithm has a sensitivity of 83.3%, false discovery rate of 16.6%, and mean detection time of 25.9 minutes. While there is no significant difference in incremental area under the curve of glucose, RAP significantly reduces time above range (glucose >180 mg/dL) by 10.8% (P = 0.04) and trends toward increasing time in range (70-180 mg/dL) by 9.1% compared with MPC. Time below range (glucose <70 mg/dL) is not significantly different between RAP and MPC.

New Developments in Glucagon Treatment for Hypoglycemia.

Glucagon is essential for endogenous glucose regulation along with the paired hormone, insulin. Unlike insulin, pharmaceutical use of glucagon has been limited due to the unstable nature of the peptide. Glucagon has the potential to address hypoglycemia as a major limiting factor in the treatment of diabetes, which remains very common in the type 1 and type 2 diabetes. Recent developments are poised to change this paradigm and expand the use of glucagon for people with diabetes. Glucagon emergency kits have major limitations for their use in treating severe hypoglycemia. A complicated reconstitution and injection process often results in incomplete or aborted administration. New preparations include intranasal glucagon with an easy-to-use and needle-free nasal applicator as well as two stable liquid formulations in pre-filled injection devices. These may ease the burden of severe hypoglycemia treatment. The liquid preparations may also have a role in the treatment of non-severe hypoglycemia. Despite potential benefits of expanded use of glucagon, undesirable side effects (nausea, vomiting), cost, and complexity of adding another medication may limit real-world use. Additionally, more long-term safety and outcome data are needed before widespread, frequent use of glucagon is recommended by providers.