Are you IDDSI ready?

The International Dysphagia Diet Standardisation Initiative (IDDSI) global framework was launched in November 2015. It was subsequently adopted by the Royal College of Speech and Language Therapists and the British Dietetic Association following expert review and professional membership consultation. In the UK, NHS England established an External IDDSI Reference Group comprising of stakeholders including professional, catering, industry and manufacturing representatives. The IDDSI External reference Group have endorsed a UK Aware, Prepare, Adopt model of implementation and all manufacturers and all healthcare settings are anticipated to be fully IDDSI compliant by April 2019. This requires whole system change with a comprehensive training programme. Those providing and delivering food and drink to individuals with swallowing difficulties need to familiarise themselves with food and drink consistencies and their testing methods. Resources are available to assist local healthcare institutions with implementation of the framework at www.rcslt.org / www.bda.org / www.iddsi.org

Glucokinase (GCK) Mutations and Their Characterization in MODY2 Children of Southern Italy

Type 2 Maturity Onset Diabetes of the Young (MODY2) is a monogenic autosomal disease characterized by a primary defect in insulin secretion and hyperglycemia. It results from GCK gene mutations that impair enzyme activity. Between 2006 and 2010, we investigated GCK mutations in 66 diabetic children from southern Italy with suspected MODY2. Denaturing High Performance Liquid Chromatography (DHPLC) and sequence analysis revealed 19 GCK mutations in 28 children, six of which were novel: p.Glu40Asp, p.Val154Leu, p.Arg447Glyfs, p.Lys458_Cys461del, p.Glu395_Arg397del and c.580-2A>T. We evaluated the effect of these 19 mutations using bioinformatic tools such as Polymorphism Phenotyping (Polyphen), Sorting Intolerant From Tolerant (SIFT) and in silico modelling. We also conducted a functional study to evaluate the pathogenic significance of seven mutations that are among the most severe mutations found in our population, and have never been characterized: p.Glu70Asp, p.His137Asp, p.Phe150Tyr, p.Val154Leu, p.Gly162Asp, p.Arg303Trp and p.Arg392Ser. These seven mutations, by altering one or more kinetic parameters, reduced enzyme catalytic activity by >40%. All mutations except p.Glu70Asp displayed thermal-instability, indeed >50% of enzyme activity was lost at 50°C/30 min. Thus, these seven mutations play a pathogenic role in MODY2 insurgence. In conclusion, this report revealed six novel GCK mutations and sheds some light on the structure-function relationship of human GCK mutations and MODY2

Denoising swallowing sound to improve the evaluator's qualitative analysis

Swallowing dynamics involves the coordination and interaction of several muscles and nerves which allow correct food transport from mouth to stomach without laryngotracheal penetration or aspiration. Clinical swallowing assessment depends on the evaluator's knowledge of anatomic structures and of neurophysiological processes involved in swallowing. Any alteration in those steps is denominated oropharyngeal dysphagia, which may have many causes, such as neurological or mechanical disorders. Videofluoroscopy of swallowing is presently considered to be the best exam to objectively assess the dynamics of swallowing, but the exam needs to be conducted under certain restrictions, due to patient's exposure to radiation, which limits periodical repetition for monitoring swallowing therapy. Another method, called cervical auscultation, is a promising new diagnostic tool for the assessment of swallowing disorders. The potential to diagnose dysphagia in a noninvasive manner by assessing the sounds of swallowing is a highly attractive option for the dysphagia clinician. Even so, the captured sound has an amount of noise, which can hamper the evaluator's decision. In that way, the present paper proposes the use of a filter to improve the quality of audible sound and facilitate the perception of examination. The wavelet denoising approach is used to decompose the noisy signal. The signal to noise ratio was evaluated to demonstrate the quantitative results of the proposed methodology. (C) 2007 Elsevier Ltd. All rights reserved.34214815