Improved insulin sensitivity and body composition, irrespective of macronutrient intake, after a 12 month intervention in adolescents with pre-diabetes; RESIST a randomised control trial

© 2014 Garnett et al..Background: A higher protein to carbohydrate ratio in the diet may potentiate weight loss, improve body composition and cardiometabolic risk, including glucose homeostasis in adults. The aim of this randomised control trial was to determine the efficacy of two structured lifestyle interventions, differing in dietary macronutrient content, on insulin sensitivity and body composition in adolescents. We hypothesised that a moderate-carbohydrate (40-45% of energy), increased-protein (25-30%) diet would be more effective than a high-carbohydrate diet (55-60%), moderate-protein (15%) diet in improving outcomes in obese, insulin resistant adolescents. Methods: Obese 10-17 year olds with either pre-diabetes and/or clinical features of insulin resistance were recruited at two hospitals in Sydney, Australia. At baseline adolescents were prescribed metformin and randomised to one of two energy restricted diets. The intervention included regular contact with the dietician and a supervised physical activity program. Outcomes included insulin sensitivity index measured by an oral glucose tolerance test and body composition measured by dual-energy x-ray absorptiometry at 12 months. Results: Of the 111 adolescents recruited, 85 (77%) completed the intervention. BMI expressed as a percentage of the 95th percentile decreased by 6.8% [95% CI: -8.8 to -4.9], ISI increased by 0.2 [95% CI: 0.06 to 0.39] and percent body fat decreased by 2.4% [95% CI: -3.4 to -1.3]. There were no significant differences in outcomes between diet groups at any time. Conclusion: When treated with metformin and an exercise program, a structured, reduced energy diet, which is either high-carbohydrate or moderate-carbohydrate with increased-protein, can achieve clinically significant improvements in obese adolescents at risk of type 2 diabetes.Link_to_subscribed_fulltex

Disorders of sex development : insights from targeted gene sequencing of a large international patient cohort

Background: Disorders of sex development (DSD) are congenital conditions in which chromosomal, gonadal, or phenotypic sex is atypical. Clinical management of DSD is often difficult and currently only 13% of patients receive an accurate clinical genetic diagnosis. To address this we have developed a massively parallel sequencing targeted DSD gene panel which allows us to sequence all 64 known diagnostic DSD genes and candidate genes simultaneously. Results: We analyzed DNA from the largest reported international cohort of patients with DSD (278 patients with 46, XY DSD and 48 with 46, XX DSD). Our targeted gene panel compares favorably with other sequencing platforms. We found a total of 28 diagnostic genes that are implicated in DSD, highlighting the genetic spectrum of this disorder. Sequencing revealed 93 previously unreported DSD gene variants. Overall, we identified a likely genetic diagnosis in 43% of patients with 46, XY DSD. In patients with 46, XY disorders of androgen synthesis and action the genetic diagnosis rate reached 60%. Surprisingly, little difference in diagnostic rate was observed between singletons and trios. In many cases our findings are informative as to the likely cause of the DSD, which will facilitate clinical management. Conclusions: Our massively parallel sequencing targeted DSD gene panel represents an economical means of improving the genetic diagnostic capability for patients affected by DSD. Implementation of this panel in a large cohort of patients has expanded our understanding of the underlying genetic etiology of DSD. The inclusion of research candidate genes also provides an invaluable resource for future identification of novel genes

Text Independent Speaker Identification System Based on Adaptive Wavelets

In this paper, we describe a text independent, phoneme based speaker identification system which uses adaptive wavelets to model the phonemes. This system identifies a speaker by modeling a very short segment of phonemes and then by clustering all the phonemes belonging to the same speaker into one class. The classification is achieved by using a two layer feed forward neural network classifier. The performance of this speaker identification system is demonstrated by considering the phonemes that were extracted from various sentences spoken by three speakers in the TIMIT acoustic-phonetic speech corpus. 1. INTRODUCTION Speaker identification systems are mainly used (a) for verifying a person's identity prior to admitting him/her into a secured place or to a telephone transaction and (b) for associating a person with a voice in police work [1]. A linguistic unit is called a phoneme (speech sound). The acoustic characteristics of each phoneme vary based on the manner of articulation (sou..

A low bit rate speech coder based on Gaussian adaptive wavelets

A low bit rate speech coder based on Gaussian adaptive wavelets is described. This speech coder ameliorates the problem of using two different mother wavelets to model voiced and unvoiced sounds as mentioned in. 1 In addition, it has been demonstrated in this paper, that Gaussian adaptive wavelets are better suited to model both voiced and unvoiced sounds as compared to Morlet and Daubechies' wavelets which are used in 1 and, 2 respectively. The bit rate and speech quality of this speech coder is compared with the speech coder based on Morlet wavelet. 1 Experimental results using TIMIT speech database are discussed with examples. Key words: Adaptive wavelets, speech coding, Gaussian, Morlet, bit rate, scalar and vector quantization 1 INTRODUCTION Low bit rate, high quality speech coders are in continuous demand to maximally utilize the channel capacity of a transmission medium especially in the case of cellular phone, since the number of subscribers is increasing every day. Mo..