Protein dose requirements to maximize skeletal muscle protein synthesis after repeated bouts of resistance exercise in young trained women

Studies examining the effect of protein (PRO) feeding on post resistance exercise (RE) muscle protein synthesis (MPS) have primarily been performed in men, and little evidence is available regarding the quantity of PRO required to maximally stimulate MPS in trained women following repeated bouts of RE. We therefore quantified acute (4 h and 8 h) and extended (24 h) effects of two bouts of resistance exercise, alongside protein-feeding, in women, and the PRO requirement to maximize MPS. Twenty-four RE trained women (26.6 ± 0.7 years, mean ± SEM) performed two bouts of whole-body RE (3 × 8 repetitions/maneuver at 75% 1-repetition maximum) 4 h apart, with post-exercise ingestion of 15 g, 30 g, or 60 g whey PRO (n = 8/group). Saliva, venous blood, and a vastus lateralis muscle biopsy were taken at 0 h, 4 h, 8 h, and 24 h post-exercise. Plasma leucine and branched chain amino acids were quantified using gas chromatography mass spectrometry (GC-MS) after ingestion of D2 O. Fifteen grams PRO did not alter plasma leucine concentration or myofibrillar synthetic rate (MyoFSR). Thirty and sixty grams PRO increased plasma leucine concentration above baseline (105.5 ± 5.3 μM; 120.2 ± 7.4 μM, respectively) at 4 h (151.5 ± 8.2 μM, p < 0.01; 224.8 ± 16.0 μM, p < 0.001, respectively) and 8 h (176.0 ± 7.3 μM, p < 0.001; 281.7 ± 21.6 μM, p < 0.001, respectively). Ingestion of 30 g PRO increased MyoFSR above baseline (0.068 ± 0.005%/h) from 0 to 4 h (0.140 ± 0.021%/h, p < 0.05), 0 to 8 h (0.121 ± 0.012%/h, p < 0.001), and 0 to 24 h (0.099 ± 0.011%/h, p < 0.01). Ingestion of 60 g PRO increased MyoFSR above baseline (0.063 ± 0.003%/h) from 0 to 4 h (0.109 ± 0.011%/h, p < 0.01), 0 to 8 h (0.093 ± 0.008%/h, p < 0.01), and 0 to 24 h (0.086 ± 0.006%/h, p < 0.01). Post-exercise ingestion of 30 g or 60 g PRO, but not 15 g, acutely increased MyoFSR following two consecutive bouts of RE and extended the anabolic window over 24 h. There was no difference between the 30 g and 60 g responses.

Oregano essential oil improves piglet health and performance through maternal feeding and is associated with changes in the gut microbiota

Background

With a growing demand for safe and sustainable alternatives to antimicrobials, functional feed ingredients such as plant essential oils have been evaluated for their potential to improve gut health. Amongst these, oregano essential oil (OEO) with the main active compounds carvacrol and thymol has been reported to have antimicrobial and antioxidative properties resulting in improved intestinal barrier function and growth in pigs and poultry. However, its impact on the gut microbiota still remains unclear. The aim of this study was to examine the effect of an oregano essential oil phytobiotic on sow and piglet performance and faecal microbiota.

Results

Piglets from OEO supplemented sows were significantly heavier at one week of age and showed a trend for improved average daily weight gain from birth to weaning. Post-weaning, maternally supplemented piglets were numerically heavier at 10 weeks post-weaning and at slaughter with a reduced variability in bodyweight. Health records showed that piglets in the OEO supplemented litters had significantly reduced incidence of therapeutic treatment and reduced mortality. In both sows and piglets, the structure and composition of the faecal microbiota varied considerably over time. Sows supplemented with OEO during lactation showed an increase in the relative abundance of Lactobacillaceae family. In addition, there was an increase in the relative abundance of families known to be important in fibre digestion (Fibrobacteriaceae and Akkermansiaceae). Analysis of piglet microbiota at two weeks and four weeks of age revealed a relative decrease in Enterobacteriaceae while butyrate producers (Lachnospiraceae family) were increased at both timepoints.

Conclusion

We hypothesise that the effects observed from this study were exerted through modulation of the gut microbial communities in the sow and her offspring through maternal microbial transfer. Understanding the link between the gut microbiota and dietary factors represents a keystone to improving health and performance for sustainable pig production. Reducing antimicrobial usage can help to reduce the risk of antimicrobial resistance (AMR) which is a global focus for animal production.

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Systems Biology Markup Language (SBML) Level 3 Package: Distributions, Version 1, Release 1

Biological models often contain elements that have inexact numerical values, since they are based on values that are stochastic in nature or data that contains uncertainty. The Systems Biology Markup Language (SBML) Level 3 Core specification does not include an explicit mechanism to include inexact or stochastic values in a model, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactic constructs. The SBML Distributions package for SBML Level 3 adds the necessary features to allow models to encode information about the distribution and uncertainty of values underlying a quantity.

Impacts of rat hindlimb Fndc5/irisin overexpression on muscle and adipose tissue metabolism

Myokines, such as irisin, have been purported to exert physiological effects on skeletal muscle in an autocrine/paracrine fashion. In this study, we aimed to investigate the mechanistic role of in vivo fibronectin type III domain-containing 5 (Fndc5)/irisin upregulation in muscle. Overexpression (OE) of Fndc5 in rat hindlimb muscle was achieved by in vivo electrotransfer, i.e., bilateral injections of Fndc5 harboring vectors for OE rats (n = 8) and empty vector for control rats (n = 8). Seven days later, a bolus of D₂O (7.2 mL/kg) was administered via oral gavage to quantify muscle protein synthesis. After an overnight fast, on day 9, 2-deoxy-d-glucose-6-phosphate (2-DG6P; 6 mg/kg) was provided during an intraperitoneal glucose tolerance test (2 g/kg) to assess glucose handling. Animals were euthanized, musculus tibialis cranialis muscles and subcutaneous fat (inguinal) were harvested, and metabolic and molecular effects were evaluated. Muscle Fndc5 mRNA increased with OE (~2-fold; P = 0.014), leading to increased circulating irisin (1.5 ± 0.9 to 3.5 ± 1.2 ng/mL; P = 0.049). OE had no effect on protein anabolism or mitochondrial biogenesis; however, muscle glycogen was increased, along with glycogen synthase 1 gene expression (P = 0.04 and 0.02, respectively). In addition to an increase in glycogen synthase activation in OE (P = 0.03), there was a tendency toward increased glucose transporter 4 protein (P = 0.09). However, glucose uptake (accumulation of 2-DG6P) was identical. Irisin elicited no endocrine effect on mitochondrial biogenesis or uncoupling proteins in white adipose tissue. Hindlimb overexpression led to physiological increases in Fndc5/irisin. However, our data indicate limited short-term impacts of irisin in relation to muscle anabolism, mitochondrial biogenesis, glucose uptake, or adipose remodeling.

Variations in the management of adolescents with blunt splenic trauma in England and Wales: are we preserving enough?

INTRODUCTION

Management of blunt splenic injury has changed drastically with non-operative management increasingly used in paediatric and adult patients. Studies from America and Australia demonstrate disparities in care of patients treated at paediatric and adult centres. This study assessed management of splenic injuries in UK adolescents.

MATERIALS AND METHODS

Data were acquired from the Trauma Audit and Research Network on isolated blunt splenic injuries reported 2006-2015. Adolescents were divided into age groups of 11-15 years and 16-20 years, and injuries classified as minor (grades 1/2) or major (3+). Primary outcomes were needed for splenectomy and blood transfusion.

RESULTS

A total of 445 adolescents suffered isolated blunt splenic injuries. Road traffic collisions were the most common mechanism. There were no deaths as a result of isolated blunt splenic injuries, but 49 (11%) adolescents needed transfusions and 105 (23.6%) underwent splenectomies. There was no significant difference observed in the management of adolescents with minor trauma. In major trauma, 11-15-year-olds were more likely to have splenectomies when managed at local trauma units compared with major trauma centres (31% vs 4%, odds ratio 11.5; 95% confidence interval 3.82-34.38, p < 0.0001). Within major trauma centres, older adolescents were more likely to have splenectomies than younger adolescents (35.5% vs 3.8%, odds ratio 14; 95% confidence interval 4.55-43.26, p < 0.0001). There were no significant differences in haemodynamic status, transfusion requirement or embolisation rates.

CONCLUSIONS

There appears to be a large variation in the management of isolated blunt splenic injuries in the UK. The reasons for this remain unclear however non-operative management is safe and should be first line management in the haemodynamically stable adolescent, even with major splenic injuries.

EBI Metagenomics in 2017: enriching the analysis of microbial communities, from sequence reads to assemblies

EBI metagenomics (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the analysis and archiving of sequence data derived from the microbial populations found in a particular environment. Over the past two years, EBI metagenomics has increased the number of datasets analysed 10-fold. In addition to increased throughput, the underlying analysis pipeline has been overhauled to include both new or updated tools and reference databases. Of particular note is a new workflow for taxonomic assignments that has been extended to include assignments based on both the large and small subunit RNA marker genes and to encompass all cellular micro-organisms. We also describe the addition of metagenomic assembly as a new analysis service. Our pilot studies have produced over 2400 assemblies from datasets in the public domain. From these assemblies, we have produced a searchable, non-redundant protein database of over 50 million sequences. To provide improved access to the data stored within the resource, we have developed a programmatic interface that provides access to the analysis results and associated sample metadata. Finally, we have integrated the results of a series of statistical analyses that provide estimations of diversity and sample comparisons.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core Release 2

Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Release 2 of Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. Release 2 corrects some errors and clarifies some ambiguities discovered in Release 1. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project website at http://sbml.org/.

Impact of the calcium form of β-hydroxy-β-methylbutyrate upon human skeletal muscle protein metabolism

BACKGROUND & AIMS

β-hydroxy-β-methylbutyrate (HMB) is purported as a key nutritional supplement for the preservation of muscle mass in health, disease and as an ergogenic aid in exercise. Of the two available forms of HMB (calcium (Ca-HMB) salt or free acid (FA-HMB)) - differences in plasma bioavailability have been reported. We previously reported that ∼3 g oral FA-HMB increased muscle protein synthesis (MPS) and reduced muscle protein breakdown (MPB). The objective of the present study was to quantify muscle protein metabolism responses to oral Ca-HMB.

METHODS

Eight healthy young males received a primed constant infusion of 1,2 ¹³C₂ leucine and ²H₅ phenylalanine to assess MPS (by tracer incorporation in myofibrils) and MPB (via arterio-venous (A-V) dilution) at baseline and following provision of ∼3 g of Ca-HMB; muscle anabolic (MPS) and catabolic (MPB) signalling was assessed via immunoblotting.

RESULTS

Ca-HMB led a significant and rapid (<60 min) peak in plasma HMB concentrations (483.6 ± 14.2 μM, p < 0.0001). This rise in plasma HMB was accompanied by increases in MPS (PA: 0.046 ± 0.004%/h, CaHMB: 0.072 ± 0.004%/h, p < 0001) and suppressions in MPB (PA: 7.6 ± 1.2 μmol Phe per leg min^-1, Ca-HMB: 5.2 ± 0.8 μmol Phe per leg min^-1, p < 0.01). Increases in the phosphorylation of mTORc1 substrates i.e. p70S6K1 and RPS6 were also observed, with no changes detected in the MPB targets measured.

CONCLUSIONS

These findings support the pro-anabolic properties of HMB via mTORc1, and show that despite proposed differences in bioavailability, Ca-HMB provides a comparable stimulation to MPS and suppression of MPB, to FA-HMB, further supporting its use as a pharmaconutrient in the modulation of muscle mass.

A double-blind placebo controlled trial into the impacts of HMB supplementation and exercise on free-living muscle protein synthesis, muscle mass and function, in older adults

Age-related sarcopenia and dynapenia are associated with frailty and metabolic diseases. Resistance exercise training (RET) adjuvant to evidence-based nutritional intervention(s) have been shown as mitigating strategies. Given that β-hydroxy-β-methyl-butyrate (HMB) supplementation during RET improves lean body mass in younger humans, and that we have shown that HMB acutely stimulates muscle protein synthesis (MPS) and inhibits breakdown; we hypothesized that chronic supplementation of HMB free acid (HMB-FA) would enhance MPS and muscle mass/function in response to RET in older people.

We recruited 16 healthy older men (Placebo (PLA): 68.5 ± 1.0 y, HMB-FA: 67.8 ± 1.15 y) for a randomised double-blind-placebo controlled trial (HMB-FA 3 × 1 g/day vs. PLA) involving a 6-week unilateral progressive RET regime (6 × 8 repetitions, 75% 1-RM, 3 · wk⁻¹). Deuterium oxide (D₂O) dosing was performed over the first two weeks (0–2 wk) and last two weeks (4–6 wk) with bilateral vastus lateralis (VL) biopsies at 0–2 and 4–6 wk (each time 75 ± 2 min after a single bout of resistance exercise (RE)) for quantification of early and later MPS responses and post-RE myogenic gene expression. Thigh lean mass (TLM) was measured by DXA, VL thickness and architecture (fibre length and pennation angle) by ultrasound at 0/3/6 wk, and strength by knee extensor 1-RM testing and MVC by isokinetic dynamometry (approx. every 10 days).

RET induced strength increases (1-RM) in the exercised leg of both groups (398 ± 22N to 499 ± 30N HMB-FA vs. 396 ± 29N to 510 ± 43N PLA (both P < 0.05)). In addition, maximal voluntary contraction (MVC) also increased (179 ± 12 Nm to 203 ± 12 Nm HMB-FA vs. 185 ± 10 Nm to 217 ± 11 Nm PLA (both P < 0.05); with no group differences. VL muscle thickness increased significantly in the exercised leg in both groups, with no group differences. TLM (by DXA) rose to significance only in the HMB-FA group (by 5.8%–5734 ± 245 g p = 0.015 vs. 3.0% to 5644 ± 323 g P = 0.06 in PLA). MPS remained unchanged in the untrained legs (UT) 0–2 weeks being 1.06 ± 0.08%.d⁻¹ (HMB-FA) and 1.14 ± 0.09%.d⁻¹ (PLA), the trained legs (T) exhibited increased MPS in the HMB-FA group only at 0–2-weeks (1.39 ± 0.10%.d⁻¹, P < 0.05) compared with UT: but was not different at 4–6-weeks: 1.26 ± 0.05%.d⁻¹. However, there were no significant differences in MPS between the HMB-FA and PLA groups at any given time point and no significant treatment interaction observed. We also observed significant inductions of c-Myc gene expression following each acute RE bout, with no group differences. Further, there were no changes in any other muscle atrophy/hypertrophy or myogenic transcription factor genes we measured.

RET with adjuvant HMB-FA supplements in free-living healthy older men did not enhance muscle strength or mass greater than that of RET alone (PLA). That said, only HMB-FA increased TLM, supported by early increases in chronic MPS. As such, chronic HMB-FA supplementation may result in long term benefits in older males, however longer and larger studies may be needed to fully determine the potential effects of HMB-FA supplementation; translating to any functional benefit.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core

Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Release 2 of Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the format of annotations, the correction of errata and the addition of clarifications. Other materials and software are available from the SBML project website at http://sbml.org/.

A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation

We investigate the feasibility of using a surrogate-based method to emulate the deformation and detachment behaviour of a biofilm in response to hydrodynamic shear stress. The influence of shear force, growth rate and viscoelastic parameters on the patterns of growth, structure and resulting shape of microbial biofilms was examined. We develop a statistical modelling approach to this problem, using combination of Bayesian Poisson regression and dynamic linear models for the emulation. We observe that the hydrodynamic shear force affects biofilm deformation in line with some literature. Sensitivity results also showed that the expected number of shear events, shear flow, yield coefficient for heterotrophic bacteria and extracellular polymeric substance (EPS) stiffness per unit EPS mass are the four principal mechanisms governing the bacteria detachment in this study. The sensitivity of the model parameters is temporally dynamic, emphasising the significance of conducting the sensitivity analysis across multiple time points. The surrogate models are shown to perform well, and produced ≈ 480 fold increase in computational efficiency. We conclude that a surrogate-based approach is effective, and resulting biofilm structure is determined primarily by a balance between bacteria growth, viscoelastic parameters and applied shear stress.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core

Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. The design of Version 2 differs from Version 1 principally in allowing new MathML constructs, making more child elements optional, and adding identifiers to all SBML elements instead of only selected elements. Other materials and software are available from the SBML project website at http://sbml.org/.

A novel D2O tracer method to quantify RNA turnover as a biomarker of de novo ribosomal biogenesis, in vitro, in animal models, and in human skeletal muscle

Current methods to quantify in vivo RNA dynamics are limited. Here, we developed a novel stable isotope (D₂O) methodology to quantify RNA synthesis (i.e., ribosomal biogenesis) in cells, animal models, and humans. First, proliferating C2C12 cells were incubated in D₂O-enriched media and myotubes ±50 ng/ml IGF-I. Second, rat quadriceps (untrained, n = 9; 7-wk interval-"like" training, n = 13) were collected after ~3-wk D₂O (70 atom %) administration, with body-water enrichment monitored via blood sampling. Finally, 10 (23 ± 1 yr) men consumed 150-ml D₂O followed by 50 ml/wk and undertook 6-wk resistance exercise (6 × 8 repetitions, 75% 1-repetition maximum 3/wk) with body-water enrichment monitored by saliva sampling and muscle biopsies (for determination of RNA synthesis) at 0, 3, and 6 wk. Ribose mole percent excess (r-MPE) from purine nucleotides was analyzed via GC-MS/MS. Proliferating C2C12 cell r-MPE exhibited a rise to plateau, whereas IGF-I increased myotube RNA from 76 ± 3 to 123 ± 3 ng/μl and r-MPE by 0.39 ± 0.1% (both P < 0.01). After 3 wk, rat quadriceps r-MPE had increased to 0.25 ± 0.01% (P < 0.01) and was greater with running exercise (0.36 ± 0.02%; P < 0.01). Human muscle r-MPE increased to 0.06 ± 0.01 and 0.13 ± 0.02% at 3/6 wk, respectively, equating to synthesis rates of ~0.8%/day, increasing with resistance exercise to 1.7 ± 0.3%/day (P < 0.01) and 1.2 ± 0.1%/day (P < 0.05) at 3/6 wk, respectively. Therefore, we have developed and physiologically validated a novel technique to explore ribosomal biogenesis in a multimodal fashion.

A network epidemic model for online community commissioning data

A statistical model assuming a preferential attachment network, which is generated by adding nodes sequentially according to a few simple rules, usually describes real-life networks better than a model assuming, for example, a Bernoulli random graph, in which any two nodes have the same probability of being connected, does. Therefore, to study the propagation of "infection" across a social network, we propose a network epidemic model by combining a stochastic epidemic model and a preferential attachment model. A simulation study based on the subsequent Markov Chain Monte Carlo algorithm reveals an identifiability issue with the model parameters. Finally, the network epidemic model is applied to a set of online commissioning data.

An overview of technical considerations for Western blotting applications to physiological research

The applications of Western/immunoblotting (WB) techniques have reached multiple layers of the scientific community and are now considered routine procedures in the field of physiology. This is none more so than in relation to skeletal muscle physiology (i.e., resolving the mechanisms underpinning adaptations to exercise). Indeed, the inclusion of WB data is now considered an essential aspect of many such physiological publications to provide mechanistic insight into regulatory processes. Despite this popularity, and due to the ubiquitous and relatively inexpensive availability of WB equipment, the quality of WB in publications and subsequent analysis and interpretation of the data can be variable, perhaps resulting in spurious conclusions. This may be due to poor laboratory technique and/or lack of comprehension of the critical steps involved in WB and what quality control procedures should be in place to ensure robust data generation. The present review aims to provide a detailed description and critique of WB procedures and technicalities, from sample collection through preparation, blotting and detection, to analysis of the data collected. We aim to provide the reader with improved expertise to critically conduct, evaluate, and troubleshoot the WB process, to produce reproducible and reliable blots.

Bayesian inference for Markov jump processes with informative observations

In this paper we consider the problem of parameter inference for Markov jump process (MJP) representations of stochastic kinetic models. Since transition probabilities are intractable for most processes of interest yet forward simulation is straightforward, Bayesian inference typically proceeds through computationally intensive methods such as (particle) MCMC. Such methods ostensibly require the ability to simulate trajectories from the conditioned jump process. When observations are highly informative, use of the forward simulator is likely to be inefficient and may even preclude an exact (simulation based) analysis. We therefore propose three methods for improving the efficiency of simulating conditioned jump processes. A conditioned hazard is derived based on an approximation to the jump process, and used to generate end-point conditioned trajectories for use inside an importance sampling algorithm. We also adapt a recently proposed sequential Monte Carlo scheme to our problem. Essentially, trajectories are reweighted at a set of intermediate time points, with more weight assigned to trajectories that are consistent with the next observation. We consider two implementations of this approach, based on two continuous approximations of the MJP. We compare these constructs for a simple tractable jump process before using them to perform inference for a Lotka-Volterra system. The best performing construct is used to infer the parameters governing a simple model of motility regulation in Bacillus subtilis.

Bayesian hierarchical modelling for inferring genetic interactions in yeast

Quantitative fitness analysis (QFA) is a high throughput experimental and computational methodology for measuring the growth of microbial populations. QFA screens can be used to compare the health of cell populations with and without a mutation in a query gene to infer genetic interaction strengths genomewide, examining thousands of separate genotypes. We introduce Bayesian hierarchical models of population growth rates and genetic interactions that better reflect QFA experimental design than current approaches. Our new approach models population dynamics and genetic interaction simultaneously, thereby avoiding passing information between models via a univariate fitness summary. Matching experimental structure more closely, Bayesian hierarchical approaches use data more efficiently and find new evidence for genes which interact with yeast telomeres within a published data set.

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

Quantitative Fitness Analysis Identifies exo1∆ and Other Suppressors or Enhancers of Telomere Defects in Schizosaccharomyces pombe

Synthetic genetic array (SGA) has been successfully used to identify genetic interactions in S. cerevisiae and S. pombe. In S. pombe, SGA methods use either cycloheximide (C) or heat shock (HS) to select double mutants before measuring colony size as a surrogate for fitness. Quantitative Fitness Analysis (QFA) is a different method for determining fitness of microbial strains. In QFA, liquid cultures are spotted onto solid agar and growth curves determined for each spot by photography and model fitting. Here, we compared the two S. pombe SGA methods and found that the HS method was more reproducible for us. We also developed a QFA procedure for S. pombe. We used QFA to identify genetic interactions affecting two temperature sensitive, telomere associated query mutations (taz1Δ and pot1-1). We identify exo1∆ and other gene deletions as suppressors or enhancers of S. pombe telomere defects. Our study identifies known and novel gene deletions affecting the fitness of strains with telomere defects. The interactions we identify may be relevant in human cells.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

Likelihood free inference for Markov processes: a comparison

Approaches to Bayesian inference for problems with intractable likelihoods have become increasingly important in recent years. Approximate Bayesian computation (ABC) and “likelihood free” Markov chain Monte Carlo techniques are popular methods for tackling inference in these scenarios but such techniques are computationally expensive. In this paper we compare the two approaches to inference, with a particular focus on parameter inference for stochastic kinetic models, widely used in systems biology. Discrete time transition kernels for models of this type are intractable for all but the most trivial systems yet forward simulation is usually straightforward. We discuss the relative merits and drawbacks of each approach whilst considering the computational cost implications and efficiency of these techniques. In order to explore the properties of each approach we examine a range of observation regimes using two example models. We use a Lotka–Volterra predator–prey model to explore the impact of full or partial species observations using various time course observations under the assumption of known and unknown measurement error. Further investigation into the impact of observation error is then made using a Schlögl system, a test case which exhibits bi-modal state stability in some regions of parameter space.

Bayesian identification of protein differential expression in multi-group isobaric labelled mass spectrometry data

In this paper we develop a Bayesian statistical inference approach to the unified analysis of isobaric labelled MS/MS proteomic data across multiple experiments. An explicit probabilistic model of the log-intensity of the isobaric labels' reporter ions across multiple pre-defined groups and experiments is developed. This is then used to develop a full Bayesian statistical methodology for the identification of differentially expressed proteins, with respect to a control group, across multiple groups and experiments. This methodology is implemented and then evaluated on simulated data and on two model experimental datasets (for which the differentially expressed proteins are known) that use a TMT labelling protocol.

Fast Bayesian parameter estimation for stochastic logistic growth models

The transition density of a stochastic, logistic population growth model with multiplicative intrinsic noise is analytically intractable. Inferring model parameter values by fitting such stochastic differential equation (SDE) models to data therefore requires relatively slow numerical simulation. Where such simulation is prohibitively slow, an alternative is to use model approximations which do have an analytically tractable transition density, enabling fast inference. We introduce two such approximations, with either multiplicative or additive intrinsic noise, each derived from the linear noise approximation (LNA) of a logistic growth SDE. After Bayesian inference we find that our fast LNA models, using Kalman filter recursion for computation of marginal likelihoods, give similar posterior distributions to slow, arbitrarily exact models. We also demonstrate that simulations from our LNA models better describe the characteristics of the stochastic logistic growth models than a related approach. Finally, we demonstrate that our LNA model with additive intrinsic noise and measurement error best describes an example set of longitudinal observations of microbial population size taken from a typical, genome-wide screening experiment.

Do simple models lead to generality in ecology?

Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex models can be linked together to produce broad-scale and predictive understanding of biological systems.

Pentose phosphate pathway function affects tolerance to the G-quadruplex binder TMPyP4

G-quadruplexes form in guanine-rich regions of DNA and the presence of these structures at telomeres prevents the activity of telomerase in vitro. Ligands such as the cationic porphyrin TMPyP4 stabilise G-quadruplexes and are therefore under investigation for their potential use as anti-cancer drugs. In order to investigate the mechanism of action of TMPyP4 in vivo, we carried out a genome-wide screen in the budding yeast Saccharomyces cerevisiae. We found that deletion of key pentose phosphate pathway (PPP) genes increased the sensitivity of yeast to the presence of TMPyP4. The PPP plays an important role in the oxidative stress response and sensitivity to TMPyP4 also increased when genes involved in the oxidative stress response, CCS1 and YAP1, were deleted. For comparison we also report genome wide-screens using hydrogen peroxide, which causes oxidative stress, RHPS4, another G-quadruplex binder and hydroxyurea, an S phase poison. We found that a number of TMPyP4-sensitive strains are also sensitive to hydrogen peroxide in a genome-wide screen. Overall our results suggest that treatment with TMPyP4 results in light-dependent oxidative stress response in budding yeast, and that this, rather than G-quadruplex binding, is the major route to cytotoxicity. Our results have implications for the usefulness and mechanism of action of TMPyP4.

Effects of leucine and its metabolite β-hydroxy-β-methylbutyrate on human skeletal muscle protein metabolism

Maintenance of skeletal muscle mass is contingent upon the dynamic equilibrium (fasted losses–fed gains) in protein turnover. Of all nutrients, the single amino acid leucine (Leu) possesses the most marked anabolic characteristics in acting as a trigger element for the initiation of protein synthesis. While the mechanisms by which Leu is ‘sensed’ have been the subject of great scrutiny, as a branched-chain amino acid, Leu can be catabolized within muscle, thus posing the possibility that metabolites of Leu could be involved in mediating the anabolic effect(s) of Leu. Our objective was to measure muscle protein anabolism in response to Leu and its metabolite HMB. Using [1,2-¹³C₂]Leu and [²H₅]phenylalanine tracers, and GC-MS/GC-C-IRMS we studied the effect of HMB or Leu alone on MPS (by tracer incorporation into myofibrils), and for HMB we also measured muscle proteolysis (by arteriovenous (A–V) dilution). Orally consumed 3.42 g free-acid (FA-HMB) HMB (providing 2.42 g of pure HMB) exhibited rapid bioavailability in plasma and muscle and, similarly to 3.42 g Leu, stimulated muscle protein synthesis (MPS; HMB +70%vs. Leu +110%). While HMB and Leu both increased anabolic signalling (mechanistic target of rapamycin; mTOR), this was more pronounced with Leu (i.e. p70S6K1 signalling ≤90 min vs. ≤30 min for HMB). HMB consumption also attenuated muscle protein breakdown (MPB; −57%) in an insulin-independent manner. We conclude that exogenous HMB induces acute muscle anabolism (increased MPS and reduced MPB) albeit perhaps via distinct, and/or additional mechanism(s) to Leu.

A whole-body mathematical model of cholesterol metabolism and its age-associated dysregulation

BACKGROUND

Global demographic changes have stimulated marked interest in the process of aging. There has been, and will continue to be, an unrelenting rise in the number of the oldest old ( >85 years of age). Together with an ageing population there comes an increase in the prevalence of age related disease. Of the diseases of ageing, cardiovascular disease (CVD) has by far the highest prevalence. It is regarded that a finely tuned lipid profile may help to prevent CVD as there is a long established relationship between alterations to lipid metabolism and CVD risk. In fact elevated plasma cholesterol, particularly Low Density Lipoprotein Cholesterol (LDL-C) has consistently stood out as a risk factor for having a cardiovascular event. Moreover it is widely acknowledged that LDL-C may rise with age in both sexes in a wide variety of groups. The aim of this work was to use a whole-body mathematical model to investigate why LDL-C rises with age, and to test the hypothesis that mechanistic changes to cholesterol absorption and LDL-C removal from the plasma are responsible for the rise. The whole-body mechanistic nature of the model differs from previous models of cholesterol metabolism which have either focused on intracellular cholesterol homeostasis or have concentrated on an isolated area of lipoprotein dynamics. The model integrates both current and previously published data relating to molecular biology, physiology, ageing and nutrition in an integrated fashion.

RESULTS

The model was used to test the hypothesis that alterations to the rate of cholesterol absorption and changes to the rate of removal of LDL-C from the plasma are integral to understanding why LDL-C rises with age. The model demonstrates that increasing the rate of intestinal cholesterol absorption from 50% to 80% by age 65 years can result in an increase of LDL-C by as much as 34 mg/dL in a hypothetical male subject. The model also shows that decreasing the rate of hepatic clearance of LDL-C gradually to 50% by age 65 years can result in an increase of LDL-C by as much as 116 mg/dL.

CONCLUSIONS

Our model clearly demonstrates that of the two putative mechanisms that have been implicated in the dysregulation of cholesterol metabolism with age, alterations to the removal rate of plasma LDL-C has the most significant impact on cholesterol metabolism and small changes to the number of hepatic LDL receptors can result in a significant rise in LDL-C. This first whole-body systems based model of cholesterol balance could potentially be used as a tool to further improve our understanding of whole-body cholesterol metabolism and its dysregulation with age. Furthermore, given further fine tuning the model may help to investigate potential dietary and lifestyle regimes that have the potential to mitigate the effects aging has on cholesterol metabolism.

Bayesian integration of networks without gold standards

Motivation: Biological experiments give insight into networks of processes inside a cell, but are subject to error and uncertainty. However, due to the overlap between the large number of experiments reported in public databases it is possible to assess the chances of individual observations being correct. In order to do so, existing methods rely on high-quality ‘gold standard’ reference networks, but such reference networks are not always available.

Results: We present a novel algorithm for computing the probability of network interactions that operates without gold standard reference data. We show that our algorithm outperforms existing gold standard-based methods. Finally, we apply the new algorithm to a large collection of genetic interaction and protein–protein interaction experiments.

Availability: The integrated dataset and a reference implementation of the algorithm as a plug-in for the Ondex data integration framework are available for download at http://bio-nexus.ncl.ac.uk/projects/nogold/

Contact:darren.wilkinson@ncl.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka-Volterra system and a prokaryotic auto-regulatory network.

Controlled vocabularies and semantics in systems biology

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. This Perspective discusses the development and use of ontologies that are designed to add semantic information to computational models and simulations.

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.

Moment closure approximations for stochastic kinetic models with rational rate laws

Stochastic models are often used when modelling chemical species that have low numbers of molecules. However, as these models become large, it can become computationally expensive to simulate even a single realisation of the system since even efficient simulation techniques have a high computational cost. One possible technique to approximate the stochastic system is moment closure. The moment closure approximation is used to provide analytic approximations to non-linear stochastic models. Until now, this approximation has only been applied to models with polynomial rate laws. In this paper we extend the moment closure method to cover models with rational rate laws.

Ethical and practical issues relating to the global use of therapeutic hypothermia for perinatal asphyxial encephalopathy

In intensive care settings in the developed world, therapeutic hypothermia is established as a therapy for term infants with moderate to severe neonatal encephalopathy due to perinatal asphyxia. Several preclinical, pilot and clinical trials conducted in such settings over the last decade have demonstrated that this therapy is safe and effective. The greatest burden of birth asphyxia falls, however, in low- and middle-income countries; it is still unclear whether therapeutic hypothermia is safe and effective in this context. In this paper, the issues around treatments that may be proven safe and effective in the developed world and the caution needed in translating these into different settings and populations are explored. It is argued that there are strong scientific and ethical reasons supporting the conduct of rigorous, randomised controlled trials of therapeutic hypothermia in middle-income settings. There also needs to be substantial and sustainable improvements in all facets of antenatal care and in the basic level of newborn resuscitation in low income countries. This will reduce the burden of disease and allow health workers to determine rapidly which infants are most eligible for potential neuroprotection.

Colonyzer: automated quantification of micro-organism growth characteristics on solid agar

Background

High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after inoculation. Precise estimates can be made by inoculating cultures onto agar and capturing cell density frequently by plate-scanning or photography, especially throughout the exponential growth phase, and summarising growth with a simple dynamic model (e.g. the logistic growth model). In order to parametrize such a model, a robust image analysis tool capable of capturing a wide range of cell densities from plate photographs is required.

Results

Colonyzer is a collection of image analysis algorithms for automatic quantification of the size, granularity, colour and location of micro-organism cultures grown on solid agar. Colonyzer is uniquely sensitive to extremely low cell densities photographed after dilute liquid culture inoculation (spotting) due to image segmentation using a mixed Gaussian model for plate-wide thresholding based on pixel intensity. Colonyzer is robust to slight experimental imperfections and corrects for lighting gradients which would otherwise introduce spatial bias to cell density estimates without the need for imaging dummy plates. Colonyzer is general enough to quantify cultures growing in any rectangular array format, either growing after pinning with a dense inoculum or growing with the irregular morphology characteristic of spotted cultures. Colonyzer was developed using the open source packages: Python, RPy and the Python Imaging Library and its source code and documentation are available on SourceForge under GNU General Public License. Colonyzer is adaptable to suit specific requirements: e.g. automatic detection of cultures at irregular locations on streaked plates for robotic picking, or decreasing analysis time by disabling components such as lighting correction or colour measures.

Conclusion

Colonyzer can automatically quantify culture growth from large batches of captured images of microbial cultures grown during genome-wide scans over the wide range of cell densities observable after highly dilute liquid spot inoculation, as well as after more concentrated pinning inoculation. Colonyzer is open-source, allowing users to assess it, adapt it to particular research requirements and to contribute to its development.

Analysing time course microarray data using Bioconductor: a case study using yeast2 Affymetrix arrays

Background

Large scale microarray experiments are becoming increasingly routine, particularly those which track a number of different cell lines through time. This time-course information provides valuable insight into the dynamic mechanisms underlying the biological processes being observed. However, proper statistical analysis of time-course data requires the use of more sophisticated tools and complex statistical models.

Findings

Using the open source CRAN and Bioconductor repositories for R, we provide example analysis and protocol which illustrate a variety of methods that can be used to analyse time-course microarray data. In particular, we highlight how to construct appropriate contrasts to detect differentially expressed genes and how to generate plausible pathways from the data. A maintained version of the R commands can be found at http://www.mas.ncl.ac.uk/~ncsg3/microarray/.

Conclusions

CRAN and Bioconductor are stable repositories that provide a wide variety of appropriate statistical tools to analyse time course microarray data.

Functional neuroimaging and withdrawal of life-sustaining treatment from vegetative patients

Recent studies using functional magnetic resonance imaging of patients in a vegetative state have raised the possibility that such patients retain some degree of consciousness. In this paper, the ethical implications of such findings are outlined, in particular in relation to decisions about withdrawing life-sustaining treatment. It is sometimes assumed that if there is evidence of consciousness, treatment should not be withdrawn. But, paradoxically, the discovery of consciousness in very severely brain-damaged patients may provide more reason to let them die. Although functional neuroimaging is likely to play an increasing role in the assessment of patients in a vegetative state, caution is needed in the interpretation of neuroimaging findings.

Bayesian calibration of a stochastic kinetic computer model using multiple data sources

In this article, we describe a Bayesian approach to the calibration of a stochastic computer model of chemical kinetics. As with many applications in the biological sciences, the data available to calibrate the model come from different sources. Furthermore, these data appear to provide somewhat conflicting information about the model parameters. We describe a modeling framework that allows us to synthesize this conflicting information and arrive at a consensus inference. In particular, we show how random effects can be incorporated into the model to account for between-individual heterogeneity that may be the source of the apparent conflict.

A mathematical model of aging-related and cortisol induced hippocampal dysfunction

Background

The hippocampus is essential for declarative memory synthesis and is a core pathological substrate for Alzheimer's disease (AD), the most common aging-related dementing disease. Acute increases in plasma cortisol are associated with transient hippocampal inhibition and retrograde amnesia, while chronic cortisol elevation is associated with hippocampal atrophy. Thus, cortisol levels could be monitored and managed in older people, to decrease their risk of AD type hippocampal dysfunction. We generated an in silicomodel of the chronic effects of elevated plasma cortisol on hippocampal activity and atrophy, using the systems biology mark-up language (SBML). We further challenged the model with biologically based interventions to ascertain if cortisol associated hippocampal dysfunction could be abrogated.

Results

The in silicoSBML model reflected the in vivoaging of the hippocampus and increased plasma cortisol and negative feedback to the hypothalamic pituitary axis. Aging induced a 12% decrease in hippocampus activity (HA), increased to 30% by acute and 40% by chronic elevations in cortisol. The biological intervention attenuated the cortisol associated decrease in HA by 2% in the acute cortisol simulation and by 8% in the chronic simulation.

Conclusion

Both acute and chronic elevations in cortisol secretion increased aging-associated hippocampal atrophy and a loss of HA in the model. We suggest that this first SMBL model, in tandem with in vitroand in vivostudies, may provide a backbone to further frame computational cortisol and brain aging models, which may help predict aging-related brain changes in vulnerable older people.

A genome wide analysis of the response to uncapped telomeres in budding yeast reveals a novel role for the NAD+ biosynthetic gene BNA2 in chromosome end protection

BACKGROUND

Telomeres prevent the ends of eukaryotic chromosomes from being recognized as damaged DNA and protect against cancer and ageing. When telomere structure is perturbed, a co-ordinated series of events promote arrest of the cell cycle so that cells carrying damaged telomeres do not divide. In order to better understand the eukaryotic response to telomere damage, budding yeast strains harboring a temperature sensitive allele of an essential telomere capping gene (cdc13-1) were subjected to a transcriptomic study.

RESULTS

The genome-wide response to uncapped telomeres in yeast cdc13-1 strains, which have telomere capping defects at temperatures above approximately 27 degrees C, was determined. Telomere uncapping in cdc13-1 strains is associated with the differential expression of over 600 transcripts. Transcripts affecting responses to DNA damage and diverse environmental stresses were statistically over-represented. BNA2, required for the biosynthesis of NAD+, is highly and significantly up-regulated upon telomere uncapping in cdc13-1 strains. We find that deletion of BNA2 and NPT1, which is also involved in NAD+ synthesis, suppresses the temperature sensitivity of cdc13-1 strains, indicating that NAD+ metabolism may be linked to telomere end protection.

CONCLUSIONS

Our data support the hypothesis that the response to telomere uncapping is related to, but distinct from, the response to non-telomeric double-strand breaks. The induction of environmental stress responses may be a conserved feature of the eukaryotic response to telomere damage. BNA2, which is involved in NAD+ synthesis, plays previously unidentified roles in the cellular response to telomere uncapping.

Evaluation of the performance of different cleaning treatments in reducing microbial contamination of poultry transport crates

1. The present systems for cleaning the plastic crates (drawers) used to transport live poultry to the processing plant are known to be inadequate for removing microbial contamination. 2. To investigate possible improvements, a mobile experimental rig was constructed and operated in the lairage of a poultry processing plant. The cleaning rig could simulate the conditions of commercial cleaning systems and utilise freshly emptied crates from the processing plant. 3. The aim of the study was to improve cleaning by enhancing the removal of adherent organic material on the crates and by reducing microbial contamination by at least 4 log(10) units. 4. Trials showed that the most effective treatments against Campylobacter were either (a) the combination of soaking at 55 degrees C, brushing for 90 s, washing for 15 s at 60 degrees C, followed by the application of disinfectant (Virkon S in this study) or (b) the use of ultrasound (4 kW) at 65 degrees C for 3 to 6 min, with or without mechanical brushing of crates. 5. Both of these treatments also achieved a 4 log(10) reduction or more in the counts of Enterobacteriaceae but were less effective in reducing aerobic plate counts. 6. It was noted that there was little correlation between the visual assessment of crate cleanliness and microbiological counts. 7. It was concluded that the demonstrated enhanced cleaning could contribute significantly to overall hygiene control in poultry meat production.

Pharyngeal pressure with high-flow nasal cannulae in premature infants

OBJECTIVE

The aim of this study was to measure pharyngeal pressures in preterm infants receiving high-flow nasal cannulae.

STUDY DESIGN

A total of 18 infants were studied (median gestational age 34 weeks, weight 1.619 kg). A catheter-tip pressure transducer was introduced into the nasopharynx. Flow was sequentially increased to a maximum of 8 l min(-1) and decreased to a minimum of 2 l min(-1).

RESULT

There was a strong association between pharyngeal pressure and both flow rate and infant weight (P<0.001, r (2)=0.61), but not mouth closure. This relationship could be expressed as pharyngeal pressure (cm H(2)O)=0.7+1.1 F (F=flow per kg in l min(-1) kg(-1)).

CONCLUSION

High-flow nasal cannulae at flow rates of 2 to 8 l min(-1) can lead to clinically significant elevations in pharyngeal pressure in preterm infants. Flow rate and weight but not mouth closure are important determinants of the pressure transmitted.

The SBML discrete stochastic models test suite

MOTIVATION

Stochastic simulation is a very important tool for mathematical modelling. However, it is difficult to check the correctness of a stochastic simulator, since any two realizations from a single model will typically be different.

RESULTS

We have developed a test suite of stochastic models that have been solved either analytically or using numerical methods. This allows the accuracy of stochastic simulators to be tested against known results. The test suite is already being used by a number of stochastic simulator developers.

AVAILABILITY

The latest version of the test suite can be obtained from http://www.calibayes.ncl.ac.uk/Resources/dsmts/ and is licensed under GNU Lesser General Public License.