Embedding physical activity in the heart of the NHS: the need for a whole-system approach

Solutions to the global challenge of physical inactivity have tended to focus on interventions at an individual level, when evidence shows that wider factors, including the social and physical environment, play a major part in influencing health-related behaviour. A multidisciplinary perspective is needed to rewrite the research agenda on physical activity if population-level public health benefits are to be demonstrated. This article explores the questions that this raises regarding the particular role that the UK National Health Service (NHS) plays in the system. The National Centre for Sport and Exercise Medicine in Sheffield is put forward as a case study to discuss some of the ways in which health systems can work in collaboration with other partners to develop environments and systems that promote active lives for patients and staff

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Mapping of Charcot-Marie-Tooth Disease Type 1C to Chromosome 16p Identifies a Novel Locus for Demyelinating Neuropathies

Charcot-Marie-Tooth (CMT) neuropathy represents a genetically heterogeneous group of diseases affecting the peripheral nervous system. We report genetic mapping of the disease to chromosome 16p13.1-p12.3, in two families with autosomal dominant CMT type 1C (CMT1C). Affected individuals in these families manifest characteristic CMT symptoms, including high-arched feet, distal muscle weakness and atrophy, depressed deep-tendon reflexes, sensory impairment, slow nerve conduction velocities, and nerve demyelination. A maximal combined LOD score of 14.25 was obtained with marker D16S500. The combined haplotype analysis in these two families localizes the CMT1C gene within a 9-cM interval flanked by markers D16S519 and D16S764. The disease-linked haplotypes in these two pedigrees are not conserved, suggesting that the gene mutation underlying the disease in each family arose independently. The epithelial membrane protein 2 gene (EMP2), which maps to chromosome 16p13.2, was evaluated as a candidate gene for CMT1C

mTOR cascade activation distinguishes tubers from focal cortical dysplasia

Balloon cells (BCs) in focal cortical dysplasia (FCD) and giant cells (GCs) in tubers of the tuberous sclerosis complex (TSC) share phenotypic similarities. TSC1 or TSC2 gene mutations in TSC lead to mTOR pathway activation and p70S6kinase (phospho-S6K) and ribosomal S6 (phospho-S6) protein phosphorylation. Phospho-S6K, phospho-S6, and phospho-S6K-activated proteins phospho-STAT3 and phospho-4EBP1 were detected immunohistochemically in GCs, whereas only phospho-S6 was observed in BCs. Expression of four candidate gene families (cell signaling, cell adhesion, growth factor/receptor, and transcription factor mRNAs) was assayed in single, microdissected phospho-S6-immunolabeled BCs and GCs as a strategy to define whether BCs and GCs exhibit differential transcriptional profiles. Among 60 genes, differential expression of 24 mRNAs distinguished BCs from GCs and only 4 genes showed similar expression profiles between BCs and GCs. Tuberin mRNA levels were reduced in GCs from TSC patients with TSC2 gene mutations but were unchanged in BCs. Phospho-S6K, -S6, -STAT3, and -4EBP1 expression in GCs reflects loss of hamartin-tuberin-mediated mTOR pathway inhibition. Phospho-S6 expression alone in BCs does not support mTOR cascade activation in FCD. Differential gene expression profiles in BCs and GCs supports the hypothesis that these cell types derive by distinct pathogenic mechanism

A Microfluidic Platform for Long-Term Monitoring of Algae in a Dynamic Environment

Culturing cells in microfluidic “lab-on-a-chip” devices for time lapse microscopy has become a valuable tool for studying the dynamics of biological systems. Although microfluidic technology has been applied to culturing and monitoring a diverse range of bacterial and eukaryotic species, cyanobacteria and eukaryotic microalgae present several challenges that have made them difficult to culture in a microfluidic setting. Here, we present a customizable device for the long-term culturing and imaging of three well characterized strains of cyanobacteria and microalgae. This platform has several advantages over agarose pads and demonstrates great potential for obtaining high quality, single-cell gene expression data of cyanobacteria and algae in precisely controlled, dynamic environments over long time periods

Brood size variability.

The table shows the average brood size under normal husbandry (control) or re-fed animals following 5 or 10 days in ARD. A high degree of variability was observed between and within experimental replicates for the average brood size (SEM). These brood sizes did not correlate to fate adoption of each strain nor with influence on any of stages of ARD. Red indicates a decrease compared to wildtype whereas green indicates an increase vs wildtype. (PDF)</p

DAPI staining of spermatheca during ARD reveal changes in number of sperm nuclei during ARD.

(A) DAPI staining of worms after 15 days in ARD reveals fewer sperm in the spermatheca of ogt-1(1474), and nhr-49(nr2041) compared to wild-type N2 worms. In the oga-1(ok1207) worms, more sperm were observed. White arrows indicate examples of sperm nuclei. (B) Whereas most of the strains analyzed saw a decrease in the number of sperm nuclei present at day 30 of ARD, oga-1(ok1207) had an overall increase compared to wildtype. However, these dynamics did not correlate with changes in brood size among selfed individuals. Green arrows indicate increased brood numbers vs wildtype and red arrows indicate decreased brood vs wildtype. (TIF)</p

Lifespan of mutant strains in recovery after 30 days of ARD and summary model.

Lifespan of wild-type and mutant strains in control husbandry conditions (blue bars) compared to those recovered after 30 days of ARD (gray bars). Lifespan after recovery from ARD was significantly defective in aak-2(ok524), daf-16(mu86), and rsks-1(ok1255). The mutant skn-1(zj15) also had a significantly reduced lifespan post-ARD but not as strongly as the others. A minimum of 8 worms from independent experiments were analyzed for lifespan and statistics were performed in Graph Pad Prism using one-way ANOVA. P-value **** = nhr-49, oga-1, ogt-1, and sir-2.1 play a role in ARD initiation, daf-16, rsks-1, and skn-1 function primarily in recovery from ARD, with aak-2 playing a role in the regulation of both states. Conversely, none of the alleles that we explored significantly impacted maintenance of the ARD.</p