4,312 research outputs found
Inference of epidemiological parameters from household stratified data
We consider a continuous-time Markov chain model of SIR disease dynamics with
two levels of mixing. For this so-called stochastic households model, we
provide two methods for inferring the model parameters---governing
within-household transmission, recovery, and between-household
transmission---from data of the day upon which each individual became
infectious and the household in which each infection occurred, as would be
available from first few hundred studies. Each method is a form of Bayesian
Markov Chain Monte Carlo that allows us to calculate a joint posterior
distribution for all parameters and hence the household reproduction number and
the early growth rate of the epidemic. The first method performs exact Bayesian
inference using a standard data-augmentation approach; the second performs
approximate Bayesian inference based on a likelihood approximation derived from
branching processes. These methods are compared for computational efficiency
and posteriors from each are compared. The branching process is shown to be an
excellent approximation and remains computationally efficient as the amount of
data is increased
Dietary Uncoupling of Gut Microbiota and Energy Harvesting from Obesity and Glucose Tolerance in Mice
The authors gratefully acknowledge Doctoral Training Partnership funding from the BBSRC (M.J.D.) and funding from the Scottish Government (P.J.M., A.W.R., and A.W.W.). We also thank the Centre for Genome-Enabled Biology and Medicine for help with next-generation sequencing and Karen Garden and the Rowett’s Analytical Services for SCFA analysis. SUPPLEMENTAL INFORMATION Supplemental Information includes four figures and two tables and can be found with this article online at https://doi.org/10.1016/j.celrep.2017.10.056.Peer reviewedPublisher PD
Racing with a purpose:Sustainability in Formula E
This study examined the seasonal sustainability reporting of Formula E for its content, variation, and linearity. Formula E was chosen since it was built as a sustainable sport enterprise rather than one which integrated sustainability into existing operations and for the accessibility of its annual sustainability reports. Using an exploratory approach for content and variation, and the Green Waves of sport sustainability for linearity, eight seasons of sustainability reports from Formula E were collected and examined via content analysis. Findings revealed the major content areas for Formula E concerned event management, car design, and community engagement with these initiatives classified as internal or external efforts. Reports were inconsistent in their structure, language, scope, and focus. The Green Waves suggest that while some efforts progress, others may regress according to strategy or the initiative’s life cycle. Formula E is progressing overall in their sustainability efforts, but exemplifies the lack of an end point to sustainability efforts. It is suggested that better coordination could yield higher strategic success and recognition
Presenilin complexes in Arabidopsis: Novel plant cell-signalling components?
Intercellular signalling is essential for multicellular organisms to coordinate growth
and development, and is mediated by a huge variety of proteins. Some signalling
pathways rely on the proteolytic cleavage of membrane proteins by a relatively
newly discovered process of regulated intramembrane proteolysis (RIP), the cleavage
of proteins within a transmembrane domain. There are four classes of
intramembrane cleaving proteases (ICliPs) – Rhomboids, Site-2-proteases, Signal
peptide peptidases and γ-secretase. Of all the ICliPs studied to date, γ-secretase is
unique, as it is comprised of a four-protein complex, and is only found in
multicellular organisms. A vast amount of research is carried out on the γ-secretase
complex, not just because of its role in developmentally important pathways, such as
NOTCH signalling, but also due to its role in Alzheimer’s disease. The β-amyloid
precursor protein (APP) is cleaved by γ-secretase, and defects in this process result in
the release of abnormal peptides that form the senile plaques in the brains of
Alzheimer’s disease patients. Homologues of the four components of γ-secretase
(PRESENILIN (PS), NICASTRIN (NCT), ANTERIOR PHARYNX DEFECTIVE-1
(APH-1) and PRESENILIN ENHANCER-2 (PEN-2)) are found in plants. The aim
of this thesis was to characterise the potential γ-secretase components in Arabidopsis
thaliana, to determine whether they form a complex, and to analyse what role, if any,
they play in plant signalling. The members of the putative Arabidopsis γ-secretase
complex (AtPS1 and 2, AtNCT, AtAPH1 and AtPEN2) were identified through
BLAST searches, and found to be uniformly expressed. Analysis of T-DNA
insertion mutants in each of these genes, and combinations there of, revealed no
gross morphological differences to wild type under normal growth conditions and
when subjected to a range of stresses. Protein fusions to GFP under the control of
the 35S promoter were constructed and stably transformed into plants. AtPEN2:GFP
is expressed throughout the plant, and accumulates in BFA sensitive Golgi bodies in
roots. AtPS1:GFP, only accumulates strongly in developing seeds. Native blue
PAGE was used to look for high molecular weight complexes (HMW) containing
AtPEN2:GFP and AtPS1:GFP. Both fusion proteins were found in similar sized
HMW complexes. A variety of methods were used to look for substrates of the
iv
putative γ-secretase complex in Arabidopsis, and although no specific substrates
were identified, a potential role in seed development has been established
Inference of epidemiological parameters from household stratified data
We consider a continuous-time Markov chain model of SIR disease dynamics with two levels of mixing. For this so-called stochastic households model, we provide two methods for inferring the model parameters-governing within-household transmission, recovery, and between-household transmission-from data of the day upon which each individual became infectious and the household in which each infection occurred, as might be available from First Few Hundred studies. Each method is a form of Bayesian Markov Chain Monte Carlo that allows us to calculate a joint posterior distribution for all parameters and hence the household reproduction number and the early growth rate of the epidemic. The first method performs exact Bayesian inference using a standard data-augmentation approach; the second performs approximate Bayesian inference based on a likelihood approximation derived from branching processes. These methods are compared for computational efficiency and posteriors from each are compared. The branching process is shown to be a good approximation and remains computationally efficient as the amount of data is increased.James N. Walker, Joshua V. Ross, Andrew J. Blac
Resident gut microbiota community determines the efficacy of soluble fiber in reducing adiposity
The authors also thank Lynn Thomson and the Rowett’s Analytical Services for SCFA analysis and CGEBM for sequence analysisPeer reviewe
Changes in the capacity of visual working memory in 5- to 10-year-olds
Using the Luck and Vogel change detection paradigm, we sought to investigate the capacity of visual working memory in 5-, 7-, and 10-year-olds. We found that performance on the task improved significantly with age and also obtained evidence that the capacity of visual working memory approximately doubles between 5 and 10 years of age, where it reaches adult levels of approximately three to four items
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