Leeno: Type 1 diabetes management training environment using smart algorithms.

A growing number of Type-1 Diabetes (T1D) patients globally use insulin pump technologies to monitor and manage their glucose levels. Although recent advances in closed-loop systems promise automated pump control in the near future, most patients worldwide still use open-loop continuous subcutaneous insulin infusion (CSII) devices which require close monitoring and continuous regulation. Apart from specialized diabetes units, hospital physicians and nurses generally lack necessary training to support the growing number of patients on insulin pumps. Most hospital staff and providers worldwide have never seen or operated an insulin pump device. T1D patients at nurseries, schools, in hospital emergency rooms, surgery theatres, and in-patient units all require close monitoring and active management. The lack of knowledge and necessary training to support T1D patients on pumps puts them at life-threatening risks. In this work, we develop a training simulation software for hospitals to educate and train their physicians and nurses on how to effectively operate a T1D pump and reduce hypoglycemia events. The software includes clinically validated T1D virtual patients that users can monitor and adjust their pump settings to improve glycemic outcomes. We develop a Fuzzy-Logic learning algorithm that helps guide users learn how to improve pump parameters for these patients. We recruited and trained 13 nurses on the software and report their improvement in pump administration, basal rates adjustments, and ICR modulation.

Unraveling the stability landscape of mutations in the SARS-CoV-2 receptor-binding domain.

The interaction between the receptor-binding domain (RBD) of the SARS-CoV-2 spike glycoprotein and the ACE2 enzyme is believed to be the entry point of the virus into various cells in the body, including the lungs, heart, liver, and kidneys. The current focus of several therapeutic design efforts explores attempts at affecting the binding potential between the two proteins to limit the activity of the virus and disease progression. In this work, we analyze the stability of the spike protein under all possible single-point mutations in the RBD and computationally explore mutations that can affect the binding with the ACE2 enzyme. We unravel the mutation landscape of the receptor region and assess the toxicity potential of single and multi-point mutations, generating insights for future vaccine efforts on mutations that might further stabilize the spike protein and increase its infectivity. We developed a tool, called SpikeMutator, to construct full atomic protein structures of the mutant spike proteins and shared a database of 3800 single-point mutant structures. We analyzed the recent 65,000 reported spike sequences across the globe and observed the emergence of stable multi-point mutant structures. Using the landscape, we searched through 7.5 million possible 2-point mutation combinations and report that the (R355D K424E) mutation produces one of the strongest spike proteins that therapeutic efforts should investigate for the sake of developing effective vaccines.

Development platform for artificial pancreas algorithms.

BACKGROUND AND AIMS: Assessing algorithms of artificial pancreas systems is critical in developing automated and fault-tolerant solutions that work outside clinical settings. The development and evaluation of algorithms can be facilitated with a platform that conducts virtual clinical trials. We present in this paper a clinically validated cloud-based distributed platform that supports the development and comprehensive testing of single and dual-hormone algorithms for type 1 diabetes mellitus (T1DM). METHODS: The platform is built on principles of object-oriented design and runs user algorithms in real-time virtual clinical trials utilizing a multi-threaded environment enabled by concurrent execution over a cloud infrastructure. The platform architecture isolates user algorithms located on personal machines from proprietary patient data running on the cloud. Users import a plugin into their algorithms (Matlab, Python, or Java) to connect to the platform. Once connected, users interact with a graphical interface to design experimental protocols for their trials. Protocols include trial duration in days, mealtimes and amounts, variability in mealtimes and amounts, carbohydrate counting errors, snacks, and onboard insulin levels. RESULTS: The platform facilitates development by solving the ODE model in the cloud on large CPU-optimized machines, providing a 62% improvement in memory, speed and CPU utilization. Users can easily debug & modify code, test multiple strategies, and generate detailed clinical performance reports. We validated and integrated into the platform a glucoregulatory system of ordinary differential equations (ODEs) parameterized with clinical data to mimic the inter and intra-day variability of glucose responses of 15 T1DM patients. CONCLUSION: The platform utilizes the validated patient model to conduct virtual clinical trials for the rapid development and testing of closed-loop algorithms for T1DM.

Impact of macronutrient content of meals on postprandial glucose control in the context of closed-loop insulin delivery: A randomized cross-over study.

The aim of this randomized four-way cross-over study was to examine the effect of added protein and/or fat in standard meals with a fixed carbohydrate content on postprandial glucose control with closed-loop insulin delivery in adults with type 1 diabetes. Participants (n = 15) consumed breakfast meals with a fixed carbohydrate content (75 ± 1 g) and added protein and/or fat (35 ± 2 g): (1) carbohydrate-only (standard), (2) high protein (HP), (3) high fat (HF) and (4) high fat + protein (HFHP). The closed-loop insulin delivery algorithm generated insulin bolus and infusion rates. The addition of fat, protein or both did not impact 5-hour post-meal sensor glucose area under the curve (AUC) (main outcome), mean sensor glucose or glycaemic peak as compared with a standard meal (P > 0.05). However, time to glycaemic peak was delayed by 40 minutes (P = 0.03) and 5-hour post-meal basal insulin requirements were 39% higher (P = 0.04) with an HFHP meal compared with a standard meal. In conclusion, in the context of closed-loop insulin delivery, protein and/or fat meal content affects the timing of postprandial glycaemic peak, insulin requirements and late glycaemic excursion, without impacting overall 5-hour AUC.

Impact of erroneous meal insulin bolus with dual-hormone artificial pancreas using a simplified bolus strategy - A randomized controlled trial.

Postprandial glucose control remains challenging for patients with type 1 diabetes (T1D). A simplified meal bolus approach with a dual-hormone (insulin and glucagon) closed-loop system (DH-CLS) has been tested; yet, the impact of categorization errors with this strategy is unknown. The objective was to compare, in a randomized controlled inpatient trial, DH-CLS with the simplified meal bolus approach for two different meals properly categorized or overestimated. We tested, in patients with T1D, the simplified strategy with two standardized breakfasts (n = 10 per meal) adequately categorized or overestimated: (1) 75 g and (2) 45 g of carbohydrate. No difference was observed for percentage of time <4.0 mmol/L over a 4-hour post-meal period (primary outcome; median [IQR]: 0[0-0] vs. 0[0-0] for both comparisons, p = 0.47 and 0.31 for the 75 g and 45 g meals, respectively). Despite higher meal insulin boluses with overestimation for both meals (9.2 [8.2-9.6] vs. 8.1 [7.3-9.1] U and 8.4 [7.2-10.4] vs. 4.8 [3.7-5.6] U; p < 0.05), mean glycemia, percentage of time in target range and glucagon infusion did not differ. Additional scenarios were tested in silico with comparable results. These results suggest that the DH-CLS with a simplified meal bolus calculation is probably able to avoid hypoglycemia in the event of meal size misclassification.

Treatment of mild-to-moderate hypoglycemia in patients with type 1 diabetes treated with insulin pump therapy: are current recommendations effective?

AIMS: Mild-to-moderate hypoglycemia (blood glucose < 4.0 mmol/L) is recommended to be treated with 15 g of carbohydrates and to repeat the treatment if hypoglycemia persists after 15 min. This recommendation was established before intensive insulin therapy and based on studies using insulin with different pharmacokinetic profiles from actual insulin analogs showing that 15 g of glucose increases blood glucose by ~ 1.5 mmol/L in 15 min. We aimed to explore the effect of current recommended treatment of mild-to-moderate hypoglycemia in type 1 diabetes (T1D) participants and factors associated with treatment effectiveness. METHODS: This is a secondary analysis from three observational inpatient studies with a standardized and supervised treatment (16 g carbohydrates) of hypoglycemia (< 3.3 mmol/L with symptoms or < 3.0 mmol/L without symptom) in participants (47 adults-10 adolescents) with T1D using continuous subcutaneous insulin infusion ("insulin pumps"; CSII)). RESULTS: Twenty-seven participants presented a total of 48 hypoglycemia episodes treated by a single intake of 16 g of carbohydrates. Time required for normoglycemia recovery was 19.5 ± 12.0 min. The rise in plasma glucose following treatment was 0.85 ± 0.66 mmol/L in 15 min. Eighteen episodes (38%) were resolved (> 4.0 mmol/L) 15-min post-treatment. Glycemia at the time of treatment (< 3.2 mmol/L; p < 0.001) and a higher proportion of total daily insulin from basal doses (p = 0.03) were associated with a slower post-treatment plasma glucose rise. CONCLUSIONS: These results raise the possibility that sixteen grams of carbohydrates could be insufficient to treat a large proportion of hypoglycemia episodes in T1D patients treated with CSII. Factors affecting treatment effectiveness need to be investigated.

Postoperative analgesia in children when using clonidine in addition to fentanyl with bupivacaine given caudally.

The aim of the study was to evaluate the efficacy of clonidine in association with fentanyl as an additive to bupivacaine 0.25% given via single shot caudal epidural in pediatric patients for postoperative pain relief. In the present prospective randomized double blind study, 40 children of ASA-I-II aged 1-5 years scheduled for infraumblical surgical procedures were randomly allocated to two groups to receive either bupivacaine 0.25% (1 ml/kg) with fentanyl 1 µg/kg and clonidine 1µg/kg (group I) or bupivacaine 0.25% (1 ml/kg) with fentanyl 1 µg/kg (group II). Caudal block was performed after the induction of general anesthesia. Postoperatively patients were observed for analgesia, sedation, hemodynamic parameters, and side effects or complications. Both the groups were similar with respect to patient and various block characteristics. Heart rate and blood pressure were not different in 2 groups. Significantly prolonged duration of post-operative analgesia was observed in group I (P<0.05). Side effects such as respiratory depression, vomiting and bradycardia were similar in both groups. The adjunction of clonidine to fentanyl as additives to bupivacaine in single shot caudal epidural in children may provide better and longer analgesia after infraumblical surgical procedures.

Subarachnoid morphine versus TAP blocks for enhanced recovery after caesarean section delivery: A randomized controlled trial.

INTRODUCTION: Subarachnoid morphine is widely used for pain relief in enhanced recovery program after cesarean section in spite of its side effects. However, the role of TAP block is still controversial. The aim of our study was to compare the impact of these analgesic techniques (subarachnoid morphine and TAP block) on enhanced recovery after cesarean section. MATERIALS AND METHODS: In this randomized controlled trial, we included patients scheduled for cesarean delivery under spinal anesthesia. Patients were randomized in two groups. Group I: received spinal anesthesia with 100µg of subarachnoid morphine. Group II: received spinal anesthesia without subarachnoid morphine followed by an ultrasound-guided TAP block. We assessed the time required for mobilization, for re-establishment of gastrointestinal transit and for breast-feeding. RESULTS: TAP block allowed earlier postoperative mobilization. Time required for getting up was significantly lower in group II (9.4h versus 6.9h; P=0.024) as well as time required for walking (12.4h versus 7.4h; P=0.001). TAP block allowed earlier re-establishment of gastrointestinal transit (11.2h in group I versus 8.1h in group II; P<0.001). CONCLUSIONS: TAP block seems to be suitable with enhanced recovery programs.

Investigating Mutations to Reduce Huntingtin Aggregation by Increasing Htt-N-Terminal Stability and Weakening Interactions with PolyQ Domain.

Huntington's disease is a fatal autosomal genetic disorder characterized by an expanded glutamine-coding CAG repeat sequence in the huntingtin (Htt) exon 1 gene. The Htt protein associated with the disease misfolds into toxic oligomers and aggregate fibril structures. Competing models for the misfolding and aggregation phenomena have suggested the role of the Htt-N-terminal region and the CAG trinucleotide repeats (polyQ domain) in affecting aggregation propensities and misfolding. In particular, one model suggests a correlation between structural stability and the emergence of toxic oligomers, whereas a second model proposes that molecular interactions with the extended polyQ domain increase aggregation propensity. In this paper, we computationally explore the potential to reduce Htt aggregation by addressing the aggregation causes outlined in both models. We investigate the mutation landscape of the Htt-N-terminal region and explore amino acid residue mutations that affect its structural stability and hydrophobic interactions with the polyQ domain. Out of the millions of 3-point mutation combinations that we explored, the (L4K E12K K15E) was the most promising mutation combination that addressed aggregation causes in both models. The mutant structure exhibited extreme alpha-helical stability, low amyloidogenicity potential, a hydrophobic residue replacement, and removal of a solvent-inaccessible intermolecular side chain that assists oligomerization.

[Bernard-Soulier syndrome and pregnancy: a case report]. / Syndrome de Bernard-Soulier et grossesse : à propos d'un cas.

Bernard-Soulier syndrome is an inherited bleeding disorder. Due to the rarity of the combination of this syndrome and pregnancy, data on the clinical course and outcome of pregnancy in women with Bernard-Soulier syndrome is scattered in individual case reports and there is no consensus in the management of SBS. In some patients, the pregnancy course was uneventful while in others post partum hemorrhage was the most common complication. We report our experience about the perioperative management of a pregnant woman with Bernard-Soulier syndrome.

Computational re-engineering of Amylin sequence with reduced amyloidogenic potential.

BACKGROUND: The aggregation of amyloid proteins into fibrils is associated with neurodegenerative diseases such as Alzheimer's and Type II Diabetes. Different methods have explored ways to impede and inhibit amyloid aggregation. Most attempts in the literature involve applying stress to the environment around amyloids. Varying pH levels, modifying temperature, applying pressure through protein crowding and ligand docking are classical examples of these methods. However, environmental stress usually affects molecular pathways and protein functions in the cell and is challenging to construct in vivo. In this paper, we explore destabilizing amyloid proteins through the manipulation of genetic code to create beneficial substitute molecules for patients with certain deficiencies. RESULTS: To unravel sequence mutations that destabilize amyloid fibrils yet simultaneously conserve native fold, we analyze the structural landscape of amyloid proteins and search for potential areas that could be exploited to weaken aggregation. Our tool, FibrilMutant, analyzes these regions and studies the effect of amino acid point mutations on nucleation and aggregation. This multiple objective approach impedes aggregation without stressing the cellular environment. We identified six main regions in amyloid proteins that contribute to structural stability and generated amino acid mutations to destabilize those regions. Full length fibrils were built from the mutated amyloid monomers and a dipolar-solvent model capturing the effect of dipole-dipole interactions between water and very large molecular systems to assess their aqueous stability was used to generate energy plots. CONCLUSION: Our results are in agreement with experimental studies and suggest novel targeted single point mutations in the Amylin protein, potentially creating a better therapeutic agent than the currently administered Pramlintide drug for diabetes patients.

Probing the binding affinity of amyloids to reduce toxicity of oligomers in diabetes.

MOTIVATION: Amyloids play a role in the degradation of ß-cells in diabetes patients. In particular, short amyloid oligomers inject themselves into the membranes of these cells and create pores that disrupt the strictly controlled flow of ions through the membranes. This leads to cell death. Getting rid of the short oligomers either by a deconstruction process or by elongating them into longer fibrils will reduce this toxicity and allow the ß-cells to live longer. RESULTS: We develop a computational method to probe the binding affinity of amyloid structures and produce an amylin analog that binds to oligomers and extends their length. The binding and extension lower toxicity and ß-cell death. The amylin analog is designed through a parsimonious selection of mutations and is to be administered with the pramlintide drug, but not to interact with it. The mutations (T9K L12K S28H T30K) produce a stable native structure, strong binding affinity to oligomers, and long fibrils. We present an extended mathematical model for the insulin-glucose relationship and demonstrate how affecting the concentration of oligomers with such analog is strictly coupled with insulin release and ß-cell fitness. AVAILABILITY AND IMPLEMENTATION: SEMBA, the tool to probe the binding affinity of amyloid proteins and generate the binding affinity scoring matrices and R-scores is available at: http://amyloid.cs.mcgill.ca

Complete characterization of the mutation landscape reveals the effect on amylin stability and amyloidogenicity.

Type-II diabetes is believed to be partially aggravated by the emergence of toxic amylin protein deposits in the extracellular space of the pancreas ß-cells. Amylin, the regulatory hormone that is co-secreted with insulin, has been observed to misfold into toxic structures. Pramlintide, an FDA approved injectable amylin analog mutated at positions 25, 28, and 29 was therefore developed to create a more stable, soluble, less-aggregating, and equipotent peptide that is used as an adjunctive therapy for diabetes. However, because Pramlintide is not ideal, researchers have been exploring other amylin analogs as therapeutic replacements. In this work, we assist the finding of optimal analogs by computationally revealing the mutational landscape of amylin. We computed the structure energies of all possible single-point mutations and studied the effect they have on amylin stability and amyloidogenicity. Each of the 37 amylin residues was mutated in silico into the 19 canonical amino acids and an energy function computing the Lennard-Jones, Coulomb and solvation energy was used to analyze changes in stability. The mutation landscape identified amylin's conserved stable regions, residues that can be tweaked to further stabilize structure, regions that are susceptible to mutations, and mutations that are amyloidogenic. We used the single-point mutational landscape data to generate estimations for higher-order multiple-point mutational landscapes and discovered millions of three-point mutations that are more stable and less amyloidogenic than Pramlintide. The landscapes provided an explanation for the effect of the S20G and Q10R mutations on the onset of diabetes of the Chinese and Maori populations, respectively.

Percutaneous closure of Ostium secundum atrial septal defect using amplatzer occlusion device.

AIM: To report our clinical experience with transcatheter closure of ostium secundum atrial septal defects (OS ASDs) using Amplatzer septal occluder. METHODS: It's a retrospective study conducted between October 2005 and April 2010 and involving 34 patients. The procedures were conducted in the hemodynamic laboratory under general anesthesia with transthoracic (TTE) and transoesophageal echocardiographic (TEE) monitoring. Clinical and echocardiography assessments of the patients were conducted within 24 hours post procedure and several months after the procedure. RESULTS: From the 34 patients, 28 (82%) were females. The middle age was 27.5 years. The mean ASD diameter was 19.4 mm by TTE; 18.1 mm [12-38] by TEE, and 23.4 by angiography. The average size of the implanted devices was 23.2 mm ranging from 10 to 34 mm.The final success rate of the procedure was 90.9% (30/33). One patient was excluded from transcatheter occlusion and three patients (8,6%) had complications including two prosthesis migrations and one large residual shunting. A total of 4 patients (11,7%) underwent surgery. No major complication (thromboembolic events, obstruction of intracardiac structures, cardiac perforation, device embolization and endocarditis) or death has occurred during follow-up and all devices were securely anchored without any persistent residual shunts. CONCLUSION: Compared to previous data of the literature, percutaneous closure of OS ASDs using Amplatzer device appears safe and effective according to our experience of the cardiology department of Hedi Chaker Hospital.

Computational assembly of polymorphic amyloid fibrils reveals stable aggregates.

Amyloid proteins aggregate into polymorphic fibrils that damage tissues of the brain, nerves, and heart. Experimental and computational studies have examined the structural basis and the nucleation of short fibrils, but the ability to predict and precisely quantify the stability of larger aggregates has remained elusive. We established a complete classification of fibril shapes and developed a tool called CreateFibril to build such complex, polymorphic, modular structures automatically. We applied stability landscapes, a technique we developed to reveal reliable fibril structural parameters, to assess fibril stability. CreateFibril constructed HET-s, Aß, and amylin fibrils up to 17 nm in length, and utilized a novel dipolar solvent model that captured the effect of dipole-dipole interactions between water and very large molecular systems to assess their aqueous stability. Our results validate experimental data for HET-s and Aß, and suggest novel (to our knowledge) findings for amylin. In particular, we predicted the correct structural parameters (rotation angles, packing distances, hydrogen bond lengths, and helical pitches) for the one and three predominant HET-s protofilaments. We reveal and structurally characterize all known Aß polymorphic fibrils, including structures recently classified as wrapped fibrils. Finally, we elucidate the predominant amylin fibrils and assert that native amylin is more stable than its amyloid form. CreateFibril and a database of all stable polymorphic fibril models we tested, along with their structural energy landscapes, are available at http://amyloid.cs.mcgill.ca.