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.

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.

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.