People living with type 1 diabetes (T1D) have an increased risk of cardiovascular disease (CVD), and it is the leading cause of morbidity and mortality in this population. CVD risk increases with each uncontrolled risk factor, even in individuals with good glycaemic control. Recommendations for assessing CVD risk in the T1D population are extended from those for type 2 diabetes (T2D) even though the physiopathology and underlying mechanisms of atherosclerosis in T1D are poorly understood and differ from those in T2D. Unlike the assessment of microvascular complications, which is well established in T1D, this is far from being the case for the comorbidities and risk associated with CVD. Aside from classical cardiovascular comorbidities, carotid ultrasound can be useful to stratify CVD risk. The utilization of specific risk scales such as the Steno Type 1 Risk Engine can help to more accurately classify cardiovascular risk in these individuals. The cornerstones of the management of cardiovascular risk in T1D are the promotion of the Mediterranean diet, tight glycaemic control (glycated haemoglobin (HbA1c) < 7%), blood pressure < 130/80 mmHg in most patients, and low-density lipoprotein (LDL) cholesterol < 100 mg/dL in moderate-risk individuals, < 70 mg/dL in high-risk individuals, and < 55 mg/dL in very high-risk individuals. Conventional medical follow-up of patients with T1D should be individualized (approximately 2-3 visits per year), and a carotid ultrasound evaluation is recommended every 5 years in the absence of significant preclinical atherosclerosis or more often in those with severe preclinical atherosclerosis. Antithrombotic therapy is recommended in those receiving secondary prevention, those with stenosis > 50% in any arterial bed, and those with an impaired ankle-brachial index. This document is a proposal of a practical approach for the evaluation, classification, and management of CVD risk in individuals living with T1D.

Type 1 diabetes (T1D) arises from autoimmune-mediated destruction of insulin-producing pancreatic beta cells. Recent advancements in the technology of generating pancreatic beta cells from human pluripotent stem cells (SC-beta cells) have facilitated the exploration of cell replacement therapies for treating T1D. However, the persistent threat of autoimmunity poses a significant challenge to the survival of transplanted SC-beta cells. Genetic engineering is a promising approach to enhance immune resistance of beta cells as we previously showed by inactivating the Renalase (Rnls) gene. Here, we demonstrate that Rnls loss of function in beta cells shapes autoimmunity by mediating a regulatory natural killer (NK) cell phenotype important for the induction of tolerogenic antigen-presenting cells. Rnls-deficient beta cells mediate cell-cell contact-independent induction of hallmark anti-inflammatory cytokine Tgfβ1 in NK cells. In addition, surface expression of regulatory NK immune checkpoints CD47 and Ceacam1 is markedly elevated on beta cells deficient for Rnls. Altered glucose metabolism in Rnls mutant beta cells is involved in the upregulation of CD47 surface expression. These findings are crucial to better understand how genetically engineered beta cells shape autoimmunity, giving valuable insights for future therapeutic advancements to treat and cure T1D.

BACKGROUND: Evidence suggests that glucose levels in menstruating females with type 1 diabetes change throughout the menstrual cycle, reaching a peak during the luteal phase. The Type 1 Diabetes Exercise Initiative (T1DEXI) study provided the opportunity to assess glycemic metrics between early and late phases of the menstrual cycle, and whether differences could be explained by exercise, insulin, and carbohydrate intake.
METHODS: One hundred and sixty two adult females were included in the analysis. Glycemic metrics, carbohydrate intake, insulin requirements, and exercise habits during the early vs. late phases of the menstrual cycles (i.e. 2-4 days after vs. 2-4 days before reported menstruation start date) were compared.
RESULTS: Mean glucose increased from 8.2±1.5 mmol/L (148±27 mg/dL) during the early follicular phase to 8.6±1.6 mmol/L (155±29 mg/dL) during the late luteal phase (p<0.001). Mean percent time-in-range (3.9-10.0 mmol/L [70-180 mg/dL] ) decreased from 73±17% to 70±18% (p=0.002), and median percent time >10.0 mmol/L (>180 mg/dL) increased from 21% to 23% (p<0.001). Median total daily insulin requirements increased from 37.4 units during the early follicular to 38.5 units during the late luteal phase (p=0.02) and mean daily carbohydrate consumption increased slightly from 127±47 g to 133±47 g (p=0.05), but the difference in mean glucose during early follicular vs. late luteal phase was not explained by differences in exercise duration, total daily insulin units, or reported carbohydrate intake.
CONCLUSIONS: Glucose levels during the late luteal phase were higher than the early follicular phase of the menstrual cycle. These glycemic changes suggest that glucose management for females with type 1 diabetes may need to be fine-tuned within the context of their menstrual cycles.

OBJECTIVE: To investigate fear of hypoglycemia (FoH) in parents of children with type 1 diabetes (T1D) before and after undergoing training to learn intranasal (IN) glucagon administration.
METHODS: In this pre-test/post-test uncontrolled study 364 caregivers of patients with T1D (6-18 years) completed questionnaires measuring sociodemographic characteristics, diabetes-related factors (e.g., type of insulin therapy, glycemic control), and parents\' trait anxiety. Parents\' FoH was assessed at baseline (T0, training) and after nine months (T1). Two repeated-measure mixed analyses of covariance (ANCOVA) compared the FoH at T0 and at T1 and analyzed the moderating roles of anxiety proneness and type of insulin therapy, as well as of anxiety proneness and use of sensor. Age, T1D duration, HbA1c values, and SES were included as covariates.
RESULTS: Parental FoH at T1 (M = 1.72; SE = 0.06/M = 1.57; SE = 0.09) was significantly lower than parental FoH at T0 (M = 1.89; SE = 0.06/M = 1.77; SE = 0.09). The group with high trait-anxiety had a higher level of FoH (M = 2.05; SE = 0.08/M = 1.89; SE = 0.12) than the group with low trait-anxiety (M = 1.57; SE = 0.08/M = 1.46; SE = 0.09) at both time points. SES was negatively associated with FoH at T0 (t = -2.87; p = .004/t = -2.87; p = .005). No other significant effects were found.
CONCLUSIONS: Training and educating parents on IN glucagon use can help them effectively manage hypoglycemic episodes and alleviate the fear that generally accompany such events.

The development of closed-loop systems for glycemia control in type I diabetes relies heavily on simulated patients. Improving the performances and adaptability of these close-loops raises the risk of over-fitting the simulator. This may have dire consequences, especially in unusual cases which were not faithfully - if at all - captured by the simulator. To address this, we propose to use model-free offline RL agents, trained on real patient data, to perform the glycemia control. To further improve the performances, we propose an end-to-end personalization pipeline, which leverages offline-policy evaluation methods to remove altogether the need of a simulator, while still enabling an estimation of clinically relevant metrics for diabetes.

BACKGROUND: Youth with diabetes should transition from paediatric to adult diabetes services in a deliberate, organized and cooperative way. We sought to identify healthcare professionals\' (HCPs) experiences and perceptions around transition readiness planning, policies and procedures, and the actual transfer to adult services.
METHODS: Data were collected via an online global survey (seven language options), broadly advertised by the International Society for Pediatric and Adolescent Diabetes (ISPAD), and European Association for the Study of Diabetes (EASD)., team members and partners, via newsletters, websites, e-mails and social media.
RESULTS: Respondents (n = 372) were mainly physicians (74.5 %), practicing in government funded (59.4 %), pediatric (54.0 %), metropolitan settings (85.8 %) in Europe (44.9 %); 37.1 % in low and middle-income countries (LMICs). Few centers used a transition readiness checklist (32.8 %), provided written transition information (29.6 %), or had a dedicated staff member (23.7 %). Similarly, few involved a psychologist (25.8 %), had combined (35.2 %) or transition/young person-only clinics (34.9 %), or a structured transition education program (22.6 %); 49.8 % advised youth to use technology to assist the transfer. Most (91.9 %) respondents reported barriers in offering a good transition experience. Proportionally, more respondents from LMICs prioritised more funding (p = 0.01), a structured protocol (p < 0.001) and education (p < 0.001).
CONCLUSIONS: HCPs\' experiences and perceptions related to transition vary widely. There is a pressing need for an international consensus transition guideline.

OBJECTIVE: Evaluate the association between cumulative tobacco consumption (CTC; packs-year) and atherosclerosis in type 1 diabetes (T1D), and study whether the inclusion of CTC in the Steno T1 Risk Engine (ST1RE) equation improves the identification of plaques.
METHODS: Cross-sectional study in T1D patients without cardiovascular disease (CVD), with ≥ 1 of the following: ≥40 years-old, diabetic kidney disease, and/or T1D duration ≥ 10 years + cardiovascular risk factors.Preclinical atherosclerosis was evaluated by carotid ultrasonography.
RESULTS: N = 584 patients were included (46.1 % women, age 48.7 ± 10.5 years, T1D duration 27.3 ± 10.8 years, 26.2 % active smokers). The overall plaque prevalence was 40.9 %. In models adjusted for age, sex, lipids, blood pressure, kidney function, statin use, microvascular complications and HbA1c, CTC was dose-dependently associated with the number of plaques (none, 1-2, ≥3) overall and in both active and former smokers (p < 0.001). This association remained after adjusting for ST1RE (OR 1.11 [1.02-1.19]). Although the inclusion of CTC in the ST1RE did not improve plaque identification overall (p = 0.180), it did so when analyzing active smokers separately (AUC 0.738 vs. 0.768; p < 0.01).
CONCLUSIONS: In T1D patients, CTC is dose-dependently associated with atherosclerosis. Further prospective studies are needed to determine if CTC could identify T1D individuals more prone to accelerated atherosclerosis.

OBJECTIVE: Exercise is a recommended part of type 1 diabetes (T1D) treatment, as high physical activity levels improve health outcomes. However, many people with T1D do not meet physical activity recommendations. The aim of this study was to identify factors influencing physical activity levels in people with T1D.
METHODS: This questionnaire-based study included adults with T1D from 1 outpatient clinic in the UK and 2 in Denmark. Exercise characteristics, motivators and barriers was assessed. Physical activity level was measured using Saltin-Grimby Physical Activity Level Scale. Respondents were categorized into three activity groups: inactive, light active and moderate-to-vigourous active.
RESULTS: Out of 332 respondents, 8.4% rated themselves as inactive, 48% light active and 43% moderate-to-vigorous active. 78% of inactive and light active repondents expressed a desire to become more physically active. 53% of respondents had received guidance concerning exercise/physical activity from their diabetes team. Being male and having received guidance, was associated with higher physical activity level. Important motivators for exercising/being physically active were improved mental and physical health and glycaemic control, while most frequent barriers were busyness with work/private life and lack of motivation. Worries about glucose excursions, costs, lack of knowledge, and health related reasons were more prevalent barriers in the least active groups.
CONCLUSIONS: This study found that 78% of inactive and light active respondents reported wishing to become more physically active. Receiving guidance about exercise/physical activity was associated with higher physical activity level, but only 53% of respondents had received support from their diabetes team.

OBJECTIVE: The aim of this work was to investigate the association between macronutrient intakes and continuous glucose monitoring (CGM) metrics in individuals with type 1 diabetes.
METHODS: In 470 individuals with type 1 diabetes of the GUTDM1 cohort (65% female, median age 40 [IQR 28-53] years, median diabetes duration 15 [IQR 6-29] years), we used logistic regression to establish associations between macronutrient intakes and the CGM metrics time in range (TIR, time spent between 3.9-10.0 mmol/l blood glucose, optimally set at ≥70%) and time below range (TBR, <3.9 mmol/l blood glucose, optimally set at <4%). ORs were expressed per 1 SD intake of nutrient and were adjusted for other macronutrient intakes, age, sex, socioeconomic status, BMI, duration of type 1 diabetes, pump use, insulin dose and alcohol intake.
RESULTS: The median (IQR) TIR was 67 (51-80)% and TBR was 2 (1-4)%; the mean ± SD energy intake was 6879±2001 kJ, fat intake 75±31 g, carbohydrate intake 162±63 g, fibre intake 20±9 g and protein intake 70±24 g. A higher fibre intake and a lower carbohydrate intake were associated with higher odds of having a TIR≥70% (OR [95% CI] 1.64 [1.22, 2.24] and 0.67 [0.51, 0.87], respectively), whereas solely a higher carbohydrate intake was associated with TBR<4% (OR 1.34 [95% CI 1.02, 1.78]).
CONCLUSIONS: A higher fibre intake is independently associated with a higher TIR. A higher carbohydrate intake is associated with less time spent in hypoglycaemia, a lower TIR and a higher time above range. These findings warrant confirmatory (interventional) investigations and may impact current nutritional guidelines for type 1 diabetes.

This review outlines some of the extraordinary recent advances in diabetes technology, which are transforming the management of type 1 diabetes before, during and after pregnancy. It highlights recent improvements associated with use of continuous glucose monitoring (CGM) but acknowledges that neither CGM nor insulin pump therapy are adequate for achieving the pregnancy glucose targets. Furthermore, even hybrid closed-loop (HCL) systems that are clinically effective outside of pregnancy may not confer additional benefits throughout pregnancy. To date, there is only one HCL system, the CamAPS FX, with a strong evidence base for use during pregnancy, suggesting that the pregnancy benefits are HCL system specific. This is in stark contrast to HCL system use outside of pregnancy, where benefits are HCL category specific. The CamAPS FX HCL system has a rapidly adaptive algorithm and lower glucose targets with benefits across all maternal glucose categories, meaning that it is applicable for all women with type 1 diabetes, before and during pregnancy. For women of reproductive years living with type 2 diabetes, the relative merits of using non-insulin pharmacotherapies vs diabetes technology (dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter 2 inhibitors) are unknown. Despite the urgent unmet need and potential benefits, studies of pharmacotherapy and technology use are extremely limited in pregnant women with type 2 diabetes.