Background Pregnant women with type 1 diabetes strive for tight glucose targets (3.5-7.8 mmol/L) to minimise the risks of obstetric and neonatal complications. Despite using diabetes technologies including continuous glucose monitoring (CGM), insulin pumps and contemporary insulin analogues, most women struggle to achieve and maintain the recommended pregnancy glucose targets. This study aims to evaluate whether the use of automated closed-loop insulin delivery improves antenatal glucose levels in pregnant women with type 1 diabetes. Methods/design A multicentre, open label, randomized, controlled trial of pregnant women with type 1 diabetes and a HbA1c of ≥48 mmol/mol (6.5%) at pregnancy confirmation and ≤ 86 mmol/mol (10%) at randomization. Participants who provide written informed consent before 13 weeks 6 days gestation will be entered into a run-in phase to collect 96 h (24 h overnight) of CGM glucose values. Eligible participants will be randomized on a 1:1 basis to CGM (Dexcom G6) with usual insulin delivery (control) or closed-loop (intervention). The closed-loop system includes a model predictive control algorithm (CamAPS FX application), hosted on an android smartphone that communicates wirelessly with the insulin pump (Dana Diabecare RS) and CGM transmitter. Research visits and device training will be provided virtually or face-to-face in conjunction with 4-weekly antenatal clinic visits where possible. Randomization will stratify for clinic site. One hundred twenty-four participants will be recruited. This takes into account 10% attrition and 10% who experience miscarriage or pregnancy loss. Analyses will be performed according to intention to treat. The primary analysis will evaluate the change in the time spent in the target glucose range (3.5-7.8 mmol/l) between the intervention and control group from 16 weeks gestation until delivery. Secondary outcomes include overnight time in target, time above target (> 7.8 mmol/l), standard CGM metrics, HbA1c and psychosocial functioning and health economic measures. Safety outcomes include the number and severity of ketoacidosis, severe hypoglycaemia and adverse device events. Discussion This will be the largest randomized controlled trial to evaluate the impact of closed-loop insulin delivery during type 1 diabetes pregnancy. Trial registration ISRCTN 56898625 Registration Date: 10 April, 2018.
In many organisms codon usage is biased, with certain synonymous codons preferred over others. It is less well known that within open reading frames codon pairing is also subject to significant bias. In this study we tested the hypothesis that the process of mRNA translation exerts a selective force on codon pair preference. A series of bioinformatic tools was created to analyse codon pair bias within bacterial and eukaryotic genomes. Cluster analysis was used to identify ribosomal P site (5') and A site (3') codons with similar pairing preferences. This revealed that the combined identities of the third P site nucleotide (P3) and the first A site nucleotide (A1) exert a key influence over codon pair bias. Other nucleotide combinations (P3-A2, P3-A3) within the two codons also modulate pairing preferences, indicating that codon-anticodon interactions act as a selective force on codon pair preference. In the genomes of Bacillus subtilis, Saccharomyces cerevisiae, and many of the gamma proteobacteria, there is also strong evidence that translational selection is operating. In these genomes, codons in the ribosomal A site that are decoded by the same tRNA isoacceptor exhibit highly similar codon pairing preferences. This suggests that codon pair selection is influenced by tRNA-mRNA interactions in the ribosomal A-site. Supporting this, multivariate analysis identified individual sequence elements within A-site tRNAs that affect codon pairing. In conclusion, we propose that in some genomes, optimal tRNA juxtaposition within the ribosome drives selection of codon pair preference. Such pairing may be an important factor enhancing translation rate or fidelity.
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