Research opportunities in muscle atrophy

A trophy of skeletal muscle; muscle a trophy associated with manned space flight; the nature, causes, and mechanisms of muscle atrophy associated with space flight, selected physiological factors, biochemical aspects, and countermeasures are addressed

Research opportunities in muscle atrophy

Muscle atrophy in a weightless environment is studied. Topics of investigation include physiological factors of muscle atrophy in space flight, biochemistry, countermeasures, modelling of atrophied muscle tissue, and various methods of measurement of muscle strength and endurance. A review of the current literature and suggestions for future research are included

Twelve-year follow-up of conservative management of postnatal urinary and faecal incontinence and prolapse outcomes : randomised controlled trial

© 2013 Royal College of Obstetricians and Gynaecologists. Funded by Royal College of Obstetricians and Gynaecologists, London, UK; Health Research Council of New Zealand. Grant Number: RG 819/06 New Zealand Lottery Grant Board Health Services Research Unit, University of Aberdeen Chief Scientist Office of the Scottish Government Health DirectoratesPeer reviewedPostprin

An investigation of the impact of using different methods for network meta-analysis: A protocol for an empirical evaluation

BACKGROUND: Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and contrast-synthesis models, with a range of models that can be fitted within each. There has been recent debate about the validity of the arm-synthesis models, but to date, there has been limited empirical evaluation comparing results using the methods applied to a large number of networks. We aim to address this gap through the re-analysis of a large cohort of published networks of interventions using a range of network meta-analysis methods. METHODS: We will include a subset of networks from a database of network meta-analyses of randomised trials that have been identified and curated from the published literature. The subset of networks will include those where the primary outcome is binary, the number of events and participants are reported for each direct comparison, and there is no evidence of inconsistency in the network. We will re-analyse the networks using three contrast-synthesis methods and two arm-synthesis methods. We will compare the estimated treatment effects, their standard errors, treatment hierarchy based on the surface under the cumulative ranking (SUCRA) curve, the SUCRA value, and the between-trial heterogeneity variance across the network meta-analysis methods. We will investigate whether differences in the results are affected by network characteristics and baseline risk. DISCUSSION: The results of this study will inform whether, in practice, the choice of network meta-analysis method matters, and if it does, in what situations differences in the results between methods might arise. The results from this research might also inform future simulation studies

Establishing comprehensive oral assessments for children with safeguarding concerns.

The dental profession is well placed to contribute important information in child protection cases but no previous research has been reported that assesses the volume or impact of this information. Comprehensive oral assessment clinics were introduced and established as an integral part of comprehensive medical assessments for children with welfare concerns in Greater Glasgow and Clyde. An assessment protocol and standardised paperwork for comprehensive oral assessments were developed to enhance information sharing and patient access to appropriate care. Two cases are presented and discussed to demonstrate the value of dental input

An investigation of the impact of using different methods for network meta-analysis: a protocol for an empirical evaluation.

BACKGROUND: Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and contrast-synthesis models, with a range of models that can be fitted within each. There has been recent debate about the validity of the arm-synthesis models, but to date, there has been limited empirical evaluation comparing results using the methods applied to a large number of networks. We aim to address this gap through the re-analysis of a large cohort of published networks of interventions using a range of network meta-analysis methods. METHODS: We will include a subset of networks from a database of network meta-analyses of randomised trials that have been identified and curated from the published literature. The subset of networks will include those where the primary outcome is binary, the number of events and participants are reported for each direct comparison, and there is no evidence of inconsistency in the network. We will re-analyse the networks using three contrast-synthesis methods and two arm-synthesis methods. We will compare the estimated treatment effects, their standard errors, treatment hierarchy based on the surface under the cumulative ranking (SUCRA) curve, the SUCRA value, and the between-trial heterogeneity variance across the network meta-analysis methods. We will investigate whether differences in the results are affected by network characteristics and baseline risk. DISCUSSION: The results of this study will inform whether, in practice, the choice of network meta-analysis method matters, and if it does, in what situations differences in the results between methods might arise. The results from this research might also inform future simulation studies

Definition of Estrogen Receptor Pathway Critical for Estrogen Positive Feedback to Gonadotropin-Releasing Hormone Neurons and Fertility

SummaryThe mechanisms through which estrogen regulates gonadotropin-releasing hormone (GnRH) neurons to control mammalian ovulation are unknown. We found that estrogen positive feedback to generate the preovulatory gonadotropin surge was normal in estrogen receptor β knockout (ERβ) mutant mice, but absent in ERα mutant mice. An ERα-selective compound was sufficient to generate positive feedback in wild-type mice. As GnRH neurons do not express ERα, estrogen positive feedback upon GnRH neurons must be indirect in nature. To establish the cell type responsible, we generated a neuron-specific ERα mutant mouse line. These mice failed to exhibit estrogen positive feedback, demonstrating that neurons expressing ERα are critical. We then used a GnRH neuron-specific Pseudorabies virus (PRV) tracing approach to show that the ERα-expressing neurons innervating GnRH neurons are located within rostral periventricular regions of the hypothalamus. These studies demonstrate that ovulation is driven by estrogen actions upon ERα-expressing neuronal afferents to GnRH neurons