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Aims/hypothesisWomen with diabetes remain at increased risk of adverse pregnancy outcomes associated with poor pregnancy preparation. However, women with type 2 diabetes are less aware of and less likely to access pre-pregnancy care (PPC) compared with women with type 1 diabetes. We developed and evaluated a community-based PPC programme with the aim of improving pregnancy preparation in all women with pregestational diabetes.MethodsThis was a prospective cohort study comparing pregnancy preparation measures before and during/after the PPC intervention in women with pre-existing diabetes from 1 June 2013 to 28 February 2017. The setting was 422 primary care practices and ten National Health Service specialist antenatal diabetes clinics. A multifaceted approach was taken to engage women with diabetes and community healthcare teams. This included identifying and sending PPC information leaflets to all eligible women, electronic preconception care templates, online education modules and resources, and regional meetings and educational events. Key outcomes were preconception folic acid supplementation, maternal HbA1c level, use of potentially harmful medications at conception and gestational age at first presentation, before and during/after the PPC programme.ResultsA total of 306 (73%) primary care practices actively participated in the PPC programme. Primary care databases were used to identify 5075 women with diabetes aged 18–45 years. PPC leaflets were provided to 4558 (89.8%) eligible women. There were 842 consecutive pregnancies in women with diabetes: 502 before and 340 during/after the PPC intervention. During/after the PPC intervention, pregnant women with type 2 diabetes were more likely to achieve target HbA1c levels ≤48 mmol/mol (6.5%) (44.4% of women before vs 58.5% of women during/after PPC intervention; p = 0.016) and to take 5 mg folic acid daily (23.5% and 41.8%; p = 0.001). There was an almost threefold improvement in ‘optimal’ pregnancy preparation in women with type 2 diabetes (5.8% and 15.1%; p = 0.021). Women with type 1 diabetes presented for earlier antenatal care during/after PPC (54.0% vs 67.3% before 8 weeks’ gestation; p = 0.003) with no other changes.Conclusions/interpretationA pragmatic community-based PPC programme was associated with clinically relevant improvements in pregnancy preparation in women with type 2 diabetes. To our knowledge, this is the first community-based PPC intervention to improve pregnancy preparation for women with type 2 diabetes.Data availabilityFurther details of the data collection methodology, individual clinic data and the full audit reports for healthcare professionals and service users are available from https://digital.nhs.uk/data-and-information/clinical-audits-and-registries/our-clinical-audits-and-registries/national-pregnancy-in-diabetes-audit.

Ewan Pearson and colleagues report a genome-wide association study for glycemic response to metformin in individuals with type 2 diabetes. They identify variants near ATM associated with treatment success. Metformin is the most commonly used pharmacological therapy for type 2 diabetes. We report a genome-wide association study for glycemic response to metformin in 1,024 Scottish individuals with type 2 diabetes with replication in two cohorts including 1,783 Scottish individuals and 1,113 individuals from the UK Prospective Diabetes Study. In a combined meta-analysis, we identified a SNP, rs11212617, associated with treatment success ( n = 3,920, P = 2.9 × 10 −9 , odds ratio = 1.35, 95% CI 1.22–1.49) at a locus containing ATM , the ataxia telangiectasia mutated gene. In a rat hepatoma cell line, inhibition of ATM with KU-55933 attenuated the phosphorylation and activation of AMP-activated protein kinase in response to metformin. We conclude that ATM , a gene known to be involved in DNA repair and cell cycle control, plays a role in the effect of metformin upstream of AMP-activated protein kinase, and variation in this gene alters glycemic response to metformin.

The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes.

We present near and mid-infrared interferometric observations made with the Keck Interferometer Nuller and near-contemporaneous spectro-photometry from the IRTF of 11 well known young stellar objects, several observed for the first time in these spectral and spatial resolution regimes. With AU-level spatial resolution, we first establish characteristic sizes of the infrared emission using a simple geometrical model consisting of a hot inner rim and mid-infrared disk emission. We find a high degree of correlation between the stellar luminosity and the mid-infrared disk sizes after using near-infrared data to remove the contribution from the inner rim. We then use a semi-analytical physical model to also find that the very widely used \"star + inner dust rim + flared disk\" class of models strongly fails to reproduce the SED and spatially-resolved mid-infrared data simultaneously; specifically a more compact source of mid-infrared emission is required than results from the standard flared disk model. We explore the viability of a modification to the model whereby a second dust rim containing smaller dust grains is added, and find that the two-rim model leads to significantly improved fits in most cases. This complexity is largely missed when carrying out SED modelling alone, although detailed silicate feature fitting by McClure et al. 2013 recently came to a similar conclusion. As has been suggested recently by Menu et al. 2015, the difficulty in predicting mid-infrared sizes from the SED alone might hint at \"transition disk\"-like gaps in the inner AU; however, the relatively high correlation found in our mid-infrared disk size vs. stellar luminosity relation favors layered disk morphologies and points to missing disk model ingredients instead.