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    Use of an Advanced Hybrid Closed Loop System During Marathon Running: Case Examples and Clinical Implications
    (Wiley, 2025-02-28)
    María T. Onetto
    ;
    Denise Montt‐Blanchard
    ;
    Cari Berget
    ;
    Kristel Strodhoff
    ;
    Bruno Grassi
    Maintaining glucose levels in the target range during aerobic training and athletic competition is especially difficult. The use of Automated Insulin Delivery (AID) technology is increasing, but exercise continues to be a challenge for persons with type 1 diabetes (T1D). In this case report series, we present 3 cases (C1, C2 and C3) of persons with T1D who used the MiniMed 780G during marathon races. We describe the strategies they used before, during and after the race to manage their glycaemia as well as the results of these strategies on their glycaemic control during the race.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The Medtronic CareLink platform was employed to remotely access insulin pump settings and glycaemic outcomes. Race parameters were obtained from sport watches. Supplemental data were obtained through interviews.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Carelink data for Cases 1, 2, and 3 before the race were downloaded: Time in range (TIR) 70–180 mg/dL 89%, 76%, 82%; time above range (TAR) &gt; 180 mg/dL, 9%, 20%, 16%; time below range (TBR) &lt; 70 mg/dL, 1%, 4%, 1%, respectively. The breakfast insulin reduction percentages were −25%, 0%, and 0% for C1, C2, and C3, respectively. In all three cases, insulin dose reduction was applied to the pre‐race snack at percentages of −50%, −100% and −83%. The consumption of carbohydrates during the race was 0.39 g/kg/hour, 0.42 g/kg/hour, and 0.5 g/kg/hour, respectively. The total amount of carbohydrates consumed was 101 g, 120 g, and 115 g, respectively. Throughout the race, a temporary target was used for all cases.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>These cases provide insights for healthcare professionals who assist athletes with T1D using AID systems during prolonged physical activities. Highlighting the significance of specialised education, planning, and personalised approaches.</jats:p></jats:sec>
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    Sensory neuron cultures derived from adult db/db mice as a simplified model to study type-2 diabetes-associated axonal regeneration defects
    (2021)
    DE GREGORIO CONCHA, CRISTIAN ALEJANDRO  
    ;
    EZQUER, EDUARDO FERNANDO  
    <jats:title>ABSTRACT</jats:title> <jats:p>Diabetic neuropathy (DN) is an early common complication of diabetes mellitus (DM), leading to chronic pain, sensory loss and muscle atrophy. Owing to its multifactorial etiology, neuron in vitro cultures have been proposed as simplified systems for DN studies. However, the most used models currently available do not recreate the chronic and systemic damage suffered by peripheral neurons of type-2 DM (T2DM) individuals. Here, we cultured neurons derived from dorsal root ganglia from 6-month-old diabetic db/db-mice, and evaluated their morphology by the Sholl method as an easy-to-analyze readout of neuronal function. We showed that neurons obtained from diabetic mice exhibited neuritic regeneration defects in basal culture conditions, compared to neurons from non-diabetic mice. Next, we evaluated the morphological response to common neuritogenic factors, including nerve growth factor NGF and Laminin-1 (also called Laminin-111). Neurons derived from diabetic mice exhibited reduced regenerative responses to these factors compared to neurons from non-diabetic mice. Finally, we analyzed the neuronal response to a putative DN therapy based on the secretome of mesenchymal stem cells (MSC). Neurons from diabetic mice treated with the MSC secretome displayed a significant improvement in neuritic regeneration, but still reduced when compared to neurons derived from non-diabetic mice. This in vitro model recapitulates many alterations observed in sensory neurons of T2DM individuals, suggesting the possibility of studying neuronal functions without the need of adding additional toxic factors to culture plates. This model may be useful for evaluating intrinsic neuronal responses in a cell-autonomous manner, and as a throughput screening for the pre-evaluation of new therapies for DN.</jats:p>
      2  1Scopus© Citations 3
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    Hypoglycemia and glycemic variability of people with type 1 diabetes with lower and higher physical activity loads in free-living conditions using continuous subcutaneous insulin infusion with predictive low-glucose suspend system
    (2023)
    Denise Montt-Blanchard
    ;
    Raimundo Sánchez
    ;
    Karen Dubois-Camacho
    ;
    LEPPE ZAMORA, JAIME ESTEBAN  
    ;
    María Teresa Onetto
    <jats:sec><jats:title>Introduction</jats:title><jats:p>Maintaining glycemic control during and after physical activity (PA) is a major challenge in type 1 diabetes (T1D). This study compared the glycemic variability and exercise-related diabetic management strategies of adults with T1D achieving higher and lower PA loads in nighttime–daytime and active– sedentary behavior hours in free-living conditions.</jats:p></jats:sec><jats:sec><jats:title>Research design and methods</jats:title><jats:p>Active adults (n=28) with T1D (ages: 35±10 years; diabetes duration: 21±11 years; body mass index: 24.8±3.4 kg/m<jats:sup>2</jats:sup>; glycated hemoglobin A1c: 6.9±0.6%) on continuous subcutaneous insulin delivery system with predictive low glucose suspend system and glucose monitoring, performed different types, duration and intensity of PA under free-living conditions, tracked by accelerometer over 14 days. Participants were equally divided into lower load (LL) and higher load (HL) by median of daily counts per minute (61122). Glycemic variability was studied monitoring predefined time in glycemic ranges (time in range (TIR), time above range (TAR) and time below range (TBR)), coefficient of variation (CV) and mean amplitude of glycemic excursions (MAGE). Parameters were studied in defined hours timeframes (nighttime–daytime and active–sedentary behavior). Self-reported diabetes management strategies were analysed during and post-PA.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Higher glycemic variability (CV) was observed in sedentary hours compared with active hours in the LL group (p≤0.05). HL group showed an increment in glycemic variability (MAGE) during nighttime versus daytime (p≤0.05). There were no differences in TIR and TAR across all timeframes between HL and LL groups. The HL group had significantly more TBR during night hours than the LL group (p≤0.05). Both groups showed TBR above recommended values. All participants used fewer post-PA management strategies than during PA (p≤0.05).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Active people with T1D are able to maintain glycemic variability, TIR and TAR within recommended values regardless of PA loads. However, the high prevalence of TBR and the less use of post-PA management strategies highlights the potential need to increase awareness on actions to avoid glycemic excursions and hypoglycemia after exercise completion.</jats:p></jats:sec>
      2Scopus© Citations 6