AimsTo estimate the incidence of Type 2 diabetes in children aged <17 years, compare this with similar data 10 years ago, and characterize clinical features at diagnosis in the UK and Republic of Ireland.MethodsUsing the British Paediatric Surveillance Unit reporting framework, cases of Type 2 diabetes diagnosed in children aged <17 years between 1 April 2015 and 30 April 2016 were reported each month.ResultsA total of 106 cases were reported, giving a UK incidence of 0.72/100 000 (95% CI 0.58–0.88). Children from ethnic minorities had significantly higher incidence compared with white children (0.44/100 000) with rates of 2.92/100 000 and 1.67/100 000, in Asian and BACBB (black/African/Caribbean/black British) children respectively. Sixty‐seven percent were girls and 81% had a family history of Type 2 diabetes. The mean BMI sd score at diagnosis was 2.89 (2.88, girls; 2.92, boys); 81% were obese. Children of Asian ethnicity had a significantly lower BMI sd score compared with white children (P<0.001). There was a trend in increased incidence from 2005 to 2015, with a rate ratio of 1.35 (95% CI 0.99–1.84), although this was not statistically significant (P=0.062). There was statistical evidence of increased incidence among girls (P=0.03) and children of South‐Asian ethnicity (P=0.01) when comparing the 2005 and 2015 surveys.ConclusionsType 2 diabetes remains far less common than Type 1 diabetes in childhood in the UK, but the number of cases continues to rise, with significantly increased incidence among girls and South‐Asian children over a decade. Female gender, family history, non‐white ethnicity and obesity were found to be strongly associated with the condition.

Several microorganisms are known for their efficient anaerobic conversion of glycerol to 1,3-propanediol, with Clostridium diolis DSM 15410 as one of the better performers in terms of molar yield and volumetric productivity. However, this performance is still insufficient to compete with established chemical processes. Previous studies have shown that high concentrations of 1,3-propanediol, glycerol, and fermentation side products can limit the productivity of C. diolis DSM 15410. Here, we describe the use of genome shuffling for improved 1,3-propanediol fermentation by the strict anaerobe C. diolis DSM 15410. By using chemical mutagenesis, strains with superior substrate and product tolerance levels were isolated and higher product yields were obtained. These superior strains were then used for genome shuffling and selection for 1,3-propanediol and organic acid tolerance. After four rounds of genome shuffling and selection, significant improvements were observed, with one strain attaining a 1,3-propanediol volumetric yield of 85 g/liter. This result represents an 80% improvement compared to the yield from the parental wild-type strain.

BackgroundMicroarray technology, as well as other functional genomics experiments, allow simultaneous measurements of thousands of genes within each sample. Both the prediction accuracy and interpretability of a classifier could be enhanced by performing the classification based only on selected discriminative genes. We propose a statistical method for selecting genes based on overlapping analysis of expression data across classes. This method results in a novel measure, called proportional overlapping score (POS), of a feature’s relevance to a classification task.ResultsWe apply POS, along‐with four widely used gene selection methods, to several benchmark gene expression datasets. The experimental results of classification error rates computed using the Random Forest, k Nearest Neighbor and Support Vector Machine classifiers show that POS achieves a better performance.ConclusionsA novel gene selection method, POS, is proposed. POS analyzes the expressions overlap across classes taking into account the proportions of overlapping samples. It robustly defines a mask for each gene that allows it to minimize the effect of expression outliers. The constructed masks along‐with a novel gene score are exploited to produce the selected subset of genes.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-274) contains supplementary material, which is available to authorized users.

Within the centralized service there is centre-level variation in secondary speech surgery, intervention and speech outcomes. These findings support the importance of early management of fistulae, effective management of velopharyngeal insufficiency and hearing impairment, and most importantly speech intervention in the preschool years. Parental concern about speech is a good indicator of speech status.

Combining multiple classifiers, known as ensemble methods, can give substantial improvement in prediction performance of learning algorithms especially in the presence of non-informative features in the data sets. We propose an ensemble of subset of kNN classifiers, ESkNN, for classification task in two steps. Firstly, we choose classifiers based upon their individual performance using the out-of-sample accuracy. The selected classifiers are then combined sequentially starting from the best model and assessed for collective performance on a validation data set. We use bench mark data sets with their original and some added non-informative features for the evaluation of our method. The results are compared with usual kNN, bagged kNN, random kNN, multiple feature subset method, random forest and support vector machines. Our experimental comparisons on benchmark classification problems and simulated data sets reveal that the proposed ensemble gives better classification performance than the usual kNN and its ensembles, and performs comparable to random forest and support vector machines.

BackgroundObservational studies on pubertal timing and asthma, mainly performed in females, have provided conflicting results about a possible association of early puberty with higher risk of adult asthma, possibly due to residual confounding. To overcome issues of confounding, we used Mendelian randomisation (MR), i.e., genetic variants were used as instrumental variables to estimate causal effects of early puberty on post-pubertal asthma in both females and males.Methods and findingsMR analyses were performed in UK Biobank on 243,316 women using 254 genetic variants for age at menarche, and on 192,067 men using 46 variants for age at voice breaking. Age at menarche, recorded in years, was categorised as early (<12), normal (12–14), or late (>14); age at voice breaking was recorded and analysed as early (younger than average), normal (about average age), or late (older than average). In females, we found evidence for a causal effect of pubertal timing on asthma, with an 8% increase in asthma risk for early menarche (odds ratio [OR] 1.08; 95% CI 1.04 to 1.12; p = 8.7 × 10−5) and an 8% decrease for late menarche (OR 0.92; 95% CI 0.89 to 0.97; p = 3.4 × 10−4), suggesting a continuous protective effect of increasing age at puberty. In males, we found very similar estimates of causal effects, although with wider confidence intervals (early voice breaking: OR 1.07; 95% CI 1.00 to 1.16; p = 0.06; late voice breaking: OR 0.93; 95% CI 0.87 to 0.99; p = 0.03). We detected only modest pleiotropy, and our findings showed robustness when different methods to account for pleiotropy were applied. BMI may either introduce pleiotropy or lie on the causal pathway; secondary analyses excluding variants associated with BMI yielded similar results to those of the main analyses. Our study relies on self-reported exposures and outcomes, which may have particularly affected the power of the analyses on age at voice breaking.ConclusionsThis large MR study provides evidence for a causal detrimental effect of early puberty on asthma, and does not support previous observational findings of a U-shaped relationship between pubertal timing and asthma. Common biological or psychological mechanisms associated with early puberty might explain the similarity of our results in females and males, but further research is needed to investigate this. Taken together with evidence for other detrimental effects of early puberty on health, our study emphasises the need to further investigate and address the causes of the secular shift towards earlier puberty observed worldwide.

Background Latent class analysis (LCA) has been used extensively to identify (latent) phenotypes of childhood wheezing. However, the number and trajectory of discovered phenotypes differed substantially between studies. Objective We sought to investigate sources of variability affecting the classification of phenotypes, identify key time points for data collection to understand wheeze heterogeneity, and ascertain the association of childhood wheeze phenotypes with asthma and lung function in adulthood. Methods We used LCA to derive wheeze phenotypes among 3167 participants in the ALSPAC cohort who had complete information on current wheeze recorded at 14 time points from birth to age 16½ years. We examined the effects of sample size and data collection age and intervals on the results and identified time points. We examined the associations of derived phenotypes with asthma and lung function at age 23 to 24 years. Results A relatively large sample size (>2000) underestimated the number of phenotypes under some conditions (eg, number of time points <11). Increasing the number of data points resulted in an increase in the optimal number of phenotypes, but an identical number of randomly selected follow-up points led to different solutions. A variable selection algorithm identified 8 informative time points (months 18, 42, 57, 81, 91, 140, 157, and 166). The proportion of asthmatic patients at age 23 to 24 years differed between phenotypes, whereas lung function was lower among persistent wheezers. Conclusions Sample size, frequency, and timing of data collection have a major influence on the number and type of wheeze phenotypes identified by using LCA in longitudinal data.

Structured AbstractObjectivesThe aims of this study were to describe child behavioural and psychosocial outcomes associated with appearance and speech in the Cleft Care UK (CCUK) study. We also wanted to explore centre‐level variation in child outcomes and investigate individual predictors of such outcomes.Setting and sample populationTwo hundred and sixty‐eight five‐year‐old children with non‐syndromic unilateral cleft lip and palate (UCLP) recruited to CCUK.Materials and methodsParents completed the Strengths and Difficulties questionnaire (SDQ) and reported their own perceptions of the child's self‐confidence. Child facial appearance and symmetry were assessed using photographs, and intelligibility of speech was derived from audio‐visual speech recordings. Centre‐level variation in behavioural and psychosocial outcomes was examined using hierarchical models, and associations with clinical outcomes were examined using logit regression models.ResultsChildren with UCLP had a higher hyperactive difficulty score than the general population. For boys, the average score was 4.5 vs 4.1 (P=.03), and for girls, the average score was 3.8 vs 3.1 (P=.008). There was no evidence of centre‐level variation for behaviour or parental perceptions of the child's self‐confidence. There is no evidence of associations between self‐confidence and SDQ scores and either facial appearance or behaviour.ConclusionsChildren born with UCLP have higher levels of behaviour problems than the general population.