The role of lipids in mechanosensation

Acknowledgements: This work was supported by Wellcome Trust grants WT092552MA (J.H.N. and I.R.B.), Senior Investigator Award WT100209MA (J.H.N.), 093228 (T.K.S.) and 092970 (M.S.P.S.), and Biotechnology and Biological Sciences Research Council grants BB/I019855/1 (M.S.P.S.), BB/H017917/1 (J.H.N. and I.R.B.) and BB/J009784/1 (H.B.). We acknowledge the Diamond Light Source for beam time. I.R.B. is supported as a Leverhulme Emeritus Fellow. J.H.N. is supported as a Royal Society Wolfson Merit Award holder and as a 1000 Talent Scholar at Sichuan University. A.C.E.D. was supported by an Engineering and Physical Sciences Research Council Systems Biology Doctoral Training Centre student fellowship. We thank R. Phillips, A. Lee and S. Conway for helpful discussions.Peer reviewedPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprin

Bringing LTL Model Checking to Biologists

Abstract The BioModelAnalyzer (BMA) is a web based tool for the development of discrete models of biological systems. Through a graphical user interface, it allows rapid development of complex models of gene and protein interaction networks and stability analysis without requiring users to be proficient computer programmers. Whilst stability is a useful specification for testing many systems, testing temporal specifications in BMA presently requires the user to perform simulations. Here we describe the LTL module, which includes a graphical and natural language interfaces to testing LTL queries. The graphical interface allows for graphical construction of the queries and presents results visually in keeping with the current style of BMA. The Natural language interface complements the graphical interface by allowing a gentler introduction to formal logic and exposing educational resources

Bringing LTL Model Checking to Biologists

Abstract The BioModelAnalyzer (BMA) is a web based tool for the development of discrete models of biological systems. Through a graphical user interface, it allows rapid development of complex models of gene and protein interaction networks and stability analysis without requiring users to be proficient computer programmers. Whilst stability is a useful specification for testing many systems, testing temporal specifications in BMA presently requires the user to perform simulations. Here we describe the LTL module, which includes a graphical and natural language interfaces to testing LTL queries. The graphical interface allows for graphical construction of the queries and presents results visually in keeping with the current style of BMA. The Natural language interface complements the graphical interface by allowing a gentler introduction to formal logic and exposing educational resources

Exome-wide analysis of rare coding variation identifies novel associations with COPD and airflow limitation in MOCS3, IFIT3 and SERPINA12.

Several regions of the genome have shown to be associated with COPD in genome-wide association studies of common variants.To determine rare and potentially functional single nucleotide polymorphisms (SNPs) associated with the risk of COPD and severity of airflow limitation.3226 current or former smokers of European ancestry with lung function measures indicative of Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2 COPD or worse were genotyped using an exome array. An analysis of risk of COPD was carried out using ever smoking controls (n=4784). Associations with %predicted FEV1 were tested in cases. We followed-up signals of interest (p<10(-5)) in independent samples from a subset of the UK Biobank population and also undertook a more powerful discovery study by meta-analysing the exome array data and UK Biobank data for variants represented on both arrays.Among the associated variants were two in regions previously unreported for COPD; a low frequency non-synonymous SNP in MOCS3 (rs7269297, pdiscovery=3.08×10(-6), preplication=0.019) and a rare SNP in IFIT3, which emerged in the meta-analysis (rs140549288, pmeta=8.56×10(-6)). In the meta-analysis of % predicted FEV1 in cases, the strongest association was shown for a splice variant in a previously unreported region, SERPINA12 (rs140198372, pmeta=5.72×10(-6)). We also confirmed previously reported associations with COPD risk at MMP12, HHIP, GPR126 and CHRNA5. No associations in novel regions reached a stringent exome-wide significance threshold (p<3.7×10(-7)).This study identified several associations with the risk of COPD and severity of airflow limitation, including novel regions MOCS3, IFIT3 and SERPINA12, which warrant further study

SNW1 Is a Critical Regulator of Spatial BMP Activity, Neural Plate Border Formation, and Neural Crest Specification in Vertebrate Embryos

In frog and fish embryos, SNW1 is a protein required for the spatio-temporal activity of BMP signaling necessary for neural plate border formation and specification of neural crest tissue

Packages of Care for Epilepsy in Low- and Middle-Income Countries

In the second in a series of six articles on packages of care for mental health disorders in low- and middle-income countries, Caroline Mbuba and Charles Newton discuss treatment for epilepsy

Associations among height, body mass index and intelligence from age 11 to age 78 years

BACKGROUND: Intelligence is related to both height and body mass index (BMI) at various stages of life. Several studies have demonstrated longitudinal relationships between these measures, but none has established whether height and intelligence, or BMI and intelligence are linked from childhood through to older age. METHODS: We assessed the relations between these measures over an interval of up to 67 years using data from the 36-Day Sample, an initially-representative sample of Scottish people born in 1936, assessed at age 11 years (N = 6,291) and again at 77-78 years (N = 722). This paper focuses on the 423 participants (6.7 % of the original sample) who provided relevant data in late adulthood. RESULTS: Height and intelligence were significantly positively associated in childhood (β = .23) and late adulthood (β = .21-.29). Longitudinal correlations also showed that childhood intelligence predicted late-adulthood height (β = .20), and childhood height predicted late-adulthood cognitive ability (β = .12-.14). We observed no significant relationship between BMI and intelligence either in childhood or in late adulthood, nor any longitudinal association between the two in this sample. CONCLUSIONS: Our results on height and intelligence are the first to demonstrate that their relationship spans almost seven decades, from childhood through to late adulthood, and they call for further investigation into the mechanisms underlying this lifelong association