Wednesday, 29 September 2010

Timing of De Novo Mutagenesis — A Twin Study of Sodium-Channel Mutations — NEJM

Timing of De Novo Mutagenesis — A Twin Study of Sodium-Channel Mutations

Lata Vadlamudi, M.B., B.S., Ph.D., Leanne M. Dibbens, Ph.D., Kate M. Lawrence, B.Sc., Xenia Iona, Dip.Biomed.Sci., Jacinta M. McMahon, B.Sc., Wayne Murrell, Ph.D., Alan Mackay-Sim, Ph.D., Ingrid E. Scheffer, M.B., B.S., Ph.D., and Samuel F. Berkovic, M.D.

N Engl J Med 2010; 363:1335-1340September 30, 2010

De novo mutations are a cause of sporadic disease, but little is known about the developmental timing of such mutations. We studied concordant and discordant monozygous twins with de novo mutations in the sodium channel α1 subunit gene (SCN1A) causing Dravet's syndrome, a severe epileptic encephalopathy. On the basis of our findings and the literature on mosaic cases, we conclude that de novo mutations in SCN1A may occur at any time, from the premorula stage of the embryo (causing disease in the subject) to adulthood (with mutations in the germ-line cells of parents causing disease in offspring).

Sunday, 26 September 2010

Eating behaviour in narcolepsy

Abnormal eating behaviour in narcolepsy.

Sleep. 2007 Oct 1;30(10):1267-73.

Eating disorder and metabolism in narcoleptic patients.

Chabas D, Foulon C, Gonzalez J, Nasr M, Lyon-Caen O, Willer JC, Derenne JP, Arnulf I.

Fédération des maladies du système nerveux, Programme AVENIR, Inserm U546, France.

Abstract

STUDY OBJECTIVE: To evaluate eating behavior and energy balance as a cause of increased body mass index (BMI) in narcolepsy.
DESIGN: Case controlled pilot study.
SETTINGS: University hospital.
PARTICIPANTS: 13 patients with narcolepsy (7 "typical" patients, with HLA DQB1*0602 and clear cut cataplexy, with suspected hypocretin deficiency; and 6 "atypical" narcoleptics, i.e., HLA negative or without cataplexy), and 9 healthy controls matched for age, gender, and ethnicity.
INTERVENTION: Energy balance was evaluated by measuring BMI, rest energy expenditure with calorimetry, daily food and water intake, and plasma hormone levels. Eating behavior was evaluated using psychometric tests (EAT-40, EDI2, CIDI-2, MADRS).
RESULTS: Patients with narcolepsy (whether typical or not) tended to be overweight and to have a lower basal metabolism than controls. Only patients with typical narcolepsy tended to eat less than controls. Narcoleptic patients who were overweight ate half as much as others, indicating caloric restriction. Plasma glucose, cortisol, thyroid, and sex hormones levels did not differ between groups, while prolactin levels were twice as high in patients with narcolepsy as in controls. Narcoleptic patients had higher EAT-40 scores and more frequent features of bulimia nervosa (independent of depressive mood) than controls, suggesting a mild eating disorder, classified as "Eating Disorder Not Other Specified."
DISCUSSION: Both lower basal metabolism and subtle changes in eating behavior (rather than in calorie intake) could explain the positive energy balance leading to overweight in narcolepsy. Eating behavior changes may be a strategy to control weight or to avoid daytime sleepiness.

PMID: 17969460 [PubMed - indexed for MEDLINE]PMCID: PMC2266283Free PMC Article

Saturday, 25 September 2010

CADASIL and skin biopsy

Congruence between NOTCH3 mutations and GOM in 131 CADASIL patients — Brain
upper arm biopsies
granular osmophilic bodies in deep dermal arteriole basal lamina

Mixed research methods for qualitative and quantitative research

BMJ 2010; 341:c4587 doi: 10.1136/bmj.c4587 (Published 17 September 2010)

Cite this as: BMJ 2010; 341:c4587

Research Methods & Reporting

Three techniques for integrating data in mixed methods studies

Alicia O’Cathain, professor1,
Elizabeth Murphy, professor2,
Jon Nicholl, professor1

+ Author Affiliations

¹Medical Care Research Unit, School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
²University of Leicester, Leicester, UK

Correspondence to: A O’Cathain a.ocathain@sheffield.ac.uk

Accepted 8 June 2010

Techniques designed to combine the results of qualitative and quantitative studies can provide researchers with more knowledge than separate analysis

Health researchers are increasingly using designs that combine qualitative and quantitative methods, and this is often called mixed methods research.1 Integration—the interaction or conversation between the qualitative and quantitative components of a study—is an important aspect of mixed methods research, and, indeed, is essential to some definitions.2 Recent empirical studies of mixed methods research in health show, however, a lack of integration between components,3 4 which limits the amount of knowledge that these types of studies generate. Without integration, the knowledge yield is equivalent to that from a qualitative study and a quantitative study undertaken independently, rather than achieving a “whole greater than the sum of the parts.”5

Barriers to integration have been identified in both health and social research.6 7 One barrier is the absence of formal education in mixed methods research. Fortunately, literature is rapidly expanding to fill this educational gap, including descriptions of how to integrate data and findings from qualitative and quantitative methods.8 9 In this article we outline three techniques that may help health researchers to integrate data or findings in their mixed methods studies and show how these might enhance knowledge generated from this approach.

Triangulation protocol

Researchers will often use qualitative and quantitative methods to examine different aspects of an overall research question. For example, they might use a randomised controlled trial to assess the effectiveness of a healthcare intervention and semistructured interviews with patients and health professionals to consider the way in which the intervention was used in the real world. Alternatively, they might use a survey of service users to measure satisfaction with a service and focus groups to explore views of care in more depth. Data …

[Full text of this article]

Pregabalin is good for sleep

Check this out, pregabalin is good for sleep:

Sleep. 2005 Feb 1;28(2):187-93.

A double-blind study in healthy volunteers to assess the effects on sleep of pregabalin compared with alprazolam and placebo.

Hindmarch I, Dawson J, Stanley N.

HPRU Medical Research Centre, University of Surrey, School of Biomedical & Molecular Sciences, Egerton Road, Guildford, UK.

Abstract

STUDY OBJECTIVES: To assess the effects of pregabalin compared with alprazolam and placebo on aspects of sleep in healthy volunteers.
DESIGN: Randomized, double-blind, placebo- and active-controlled, 3-way crossover.
SETTING: Single research center.
PARTICIPANTS AND INTERVENTIONS: Healthy adult (12 men) volunteers (N=24) received oral pregabalin 150 mg t.i.d., alprazolam 1 mg t.i.d., and placebo t.i.d. for 3 days.
MEASUREMENTS AND RESULTS: Objective sleep was measured by an 8-channel polysomnograph; subjective sleep was measured using the Leeds Sleep Evaluation Questionnaire. Compared with placebo, pregabalin significantly increased slow-wave sleep both as a proportion of the total sleep period and the duration of stage 4 sleep. Alprazolam significantly reduced slow-wave sleep. Pregabalin and alprazolam produced modest, but significant, reductions in sleep-onset latency compared with placebo. Rapid eye movement sleep latency after pregabalin was no different than placebo but was significantly shorter than that found with alprazolam. Although there were no differences between the active treatments, both pregabalin and alprazolam reduced rapid eye movement sleep as a proportion of the total sleep period compared with placebo. Pregabalin also significantly reduced the number of awakenings of more than 1 minute in duration. Leeds Sleep Evaluation Questionnaire ratings of the ease of getting to sleep and the perceived quality of sleep were significantly improved following both active treatments, and ratings of behavior following awakening were significantly impaired by both drug treatments.
CONCLUSIONS: Pregabalin appears to have an effect on sleep and sleep architecture that distinguishes it from benzodiazepines. Enhancement of slow-wave sleep is intriguing, since reductions in slow-wave sleep have frequently been reported in fibromyalgia and general anxiety disorder.

PMID: 16171242 [PubMed - indexed for MEDLINE]

The SF Community - SF-36® Health Survey Update

sf36

SF-36 Literature
Construction of the SF-36
Version 2.0
Psychometric Considerations
Translations
Discussion

The SF-36 is a multi-purpose, short-form health survey with only 36 questions. It yields an 8-scale profile of functional health and well-being scores as well as psychometrically-based physical and mental health summary measures and a preference-based health utility index. It is a generic measure, as opposed to one that targets a specific age, disease, or treatment group. Accordingly, the SF-36 has proven useful in surveys of general and specific populations, comparing the relative burden of diseases, and in differentiating the health benefits produced by a wide range of different treatments. This book chapter summarizes the steps in the construction of the SF-36; how it led to the development of an even shorter (1-page, 2-minute) survey form -- the SF-12; the improvements reflected in Version 2.0 of the SF-36; psychometric studies of assumptions underlying scale construction and scoring; how they have been translated in more than 50 countries as part of the International Quality of Life Assessment (IQOLA) Project; and studies of reliability and validity.

The Update

Wednesday, 29 September 2010