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.

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.

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).

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.

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.

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 β-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.

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

Motivation: Amyloids play a role in the degradation of β-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.

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.