Examination of hydrogen cross-feeders using a colonic microbiota model.

BACKGROUND: Hydrogen cross-feeding microbes form a functionally important subset of the human colonic microbiota. The three major hydrogenotrophic functional groups of the colon: sulphate-reducing bacteria (SRB), methanogens and reductive acetogens, have been linked to wide ranging impacts on host physiology, health and wellbeing. RESULTS: An existing mathematical model for microbial community growth and metabolism was combined with models for each of the three hydrogenotrophic functional groups. The model was further developed for application to the colonic environment via inclusion of responsive pH, host metabolite absorption and the inclusion of host mucins. Predictions of the model, using two existing metabolic parameter sets, were compared to experimental faecal culture datasets. Model accuracy varied between experiments and measured variables and was most successful in predicting the growth of high relative abundance functional groups, such as the Bacteroides, and short chain fatty acid (SCFA) production. Two versions of the colonic model were developed: one representing the colon with sequential compartments and one utilising a continuous spatial representation. When applied to the colonic environment, the model predicted pH dynamics within the ranges measured in vivo and SCFA ratios comparable to those in the literature. The continuous version of the model simulated relative abundances of microbial functional groups comparable to measured values, but predictions were sensitive to the metabolic parameter values used for each functional group. Sulphate availability was found to strongly influence hydrogenotroph activity in the continuous version of the model, correlating positively with SRB and sulphide concentration and negatively with methanogen concentration, but had no effect in the compartmentalised model version. CONCLUSIONS: Although the model predictions compared well to only some experimental measurements, the important features of the colon environment included make it a novel and useful contribution to modelling the colonic microbiota.

Mathematical modelling supports the existence of a threshold hydrogen concentration and media-dependent yields in the growth of a reductive acetogen.

The bacterial production of acetate via reductive acetogenesis along the Wood-Ljungdahl metabolic pathway is an important source of this molecule in several environments, ranging from industrial bioreactors to the human gastrointestinal tract. Here, we contributed to the study of reductive acetogens by considering mathematical modelling techniques for the prediction of bacterial growth and acetate production. We found that the incorporation of a hydrogen uptake concentration threshold into the models improves their predictions and we calculated this threshold as 86.2 mM (95% confidence interval 6.1-132.6 mM). Monod kinetics and first-order kinetics models, with the inclusion of two candidate threshold terms or reversible Michaelis-Menten kinetics, were compared to experimental data and the optimal formulation for predicting both growth and metabolism was found. The models were then used to compare the efficacy of two growth media for acetogens. We found that the recently described general acetogen medium was superior to the DSMZ medium in terms of unbiased estimation of acetogen growth and investigated the contribution of yeast extract concentration to acetate production and bacterial growth in culture. The models and their predictions will be useful to those studying both industrially and environmentally relevant reductive acetogenesis and allow for straightforward adaptation to similar cases with different organisms.

A mathematical model of the interaction between bovine blastocyst developmental stage and progesterone-stimulated uterine factors on differential embryonic development observed on Day 15 of gestation.

A complex interaction between the developing bovine embryo and the growth potential of the uterine milieu it inhabits results in an embryo capable of developing past the maternal recognition stage and on to a successful pregnancy. Previously, we observed variation in the lengths of embryos recovered 8 d after bulk transfer of Day 7 in vitro-produced (IVP) blastocysts into the same uterus. Potential causes of the differential embryonic growth were examined and modeled using 2 rounds of bulk (n = 4-6) IVP transfers and recovery of these embryos 8 d later. Morphological and gene expression measurements of the embryos were determined and the progesterone concentration of the cows was measured throughout the reproductive cycle as a reflection of the status of the uterine environment. These data were used to develop and evaluate a model that describes the interaction between the uterine environment and the growth rate of the developing embryo. Expression of 6 trophectoderm genes (IFNT, TKDP1, PAG11, PTGS2, DKK1, and PDPN) was correlated with conceptus length. The model determined that if the embryo develops to blastocyst stage, the uterine environment, driven by progesterone, is a more important component than blastocyst size in the stimulation of embryonic growth rate to ensure adequate interferon tau (IFNT) for pregnancy recognition. We detected an effect of Day 7 progesterone on the expression of all 6 genes, embryonic disc size, and trophectoderm length on Day 15. We also found effects of embryo transfer size on trophectoderm length and expression of IFNT and PAG11 on Day 15. Lower energy balance over the period from transfer to recovery was associated with reduced embryo growth to Day 15, and this effect was independent of progesterone. Energy balance also affected expression of PDPN and TKDP1 on Day 15. We observed an effect of energy balance from transfer to recovery on embryo survival in cows with partial embryo losses, where embryo factors dominate embryo survival, with cows with greater energy balance having lower embryo losses. This effect was independent of energy balance 40 d before transfer and suggests that energy balance has direct, immediate effects on the embryo and maternal environment during this period. Furthermore, energy balance effects on embryo survival in cows with partial embryo losses were largely mediated by expression of TKDP1, PAG11, and PDPN. These results provide candidate signaling pathways for the effect of progesterone and energy balance on embryo growth and survival.

The role of enzyme compartmentalization on the regulation of steroid synthesis.

Steroidogenic enzymes can be compartmentalized at different levels, some by virtue of being membrane bound in specific intra-cellular compartments. Although both 3ß-hydroxysteroid dehydrogenase/Δ(5)-Δ(4) isomerase (3ß-HSD) and 17α-hydroxylase/17,20-lyase cytochrome P450 (P450c17) are expressed in the endoplasmic reticulum (ER) membrane, these proteins may still be spatially separated within this membrane system. Side chain cleavage cytochrome P450 (P450scc) is anchored to the inner mitochondrial membrane and this organelle is the major source of pregnenolone (P5) feeding steroidogenesis. Furthermore, steroidogenic enzymes can also be partitioned in different cells. Although well recognized, the effect of enzyme compartmentalization on the rate of steroid production and the balance of different steroids is unclear. This study uses mathematical modeling to investigate the effect of enzyme compartmentalization on steroid synthesis in a human-ovine-bovine model of steroid synthesis. The study shows that the spatial separation of steroidogenic enzymes within the ER has a minimal effect on the rate of steroid synthesis. The compartmentalization of the enzymes into different organelles of a cell creates cellular steroid gradients and can affect the balance of the different steroid products. The partitioning of steroidogenic enzymes in different cells reduces the rate of steroid synthesis. The greater is the distance between the cells that contain different enzymes, the more the rate of steroid synthesis is reduced. Additionally, when 3ß-HSD is not in the same cell with P450scc (the P5 source) and P450c17, the ratio of the Δ(5)-pathway products' concentrations to the Δ(4)-pathway products' concentrations is increased. However, none of these levels of compartmentalization of steroidogenic enzymes alter the qualitative behaviors of steroid synthesis in response to variation in an enzyme activity or P5 supply.

Ewes with higher embryo survival rear lambs that grow faster.

A key economic driver of a meat producing sheep flock is the total kilograms of lamb liveweight at weaning per ewe exposed to the ram. Optimization of key reproductive steps is required to achieve peak performance of a sheep flock. The goal of this paper was to use more than 56,000 records from a commercial flock to investigate the key reproductive steps affecting flock reproductive performance. We also applied a maximum-likelihood based technique to predict the embryo survival and ovulation rate for daughters of individual sires based on measurements of the number of fetuses at midpregnancy (detected by ultrasound-scanning). The model was used to determine how changes in premating liveweight, age, predicted ovulation rate, embryo survival, number of fetuses at midpregnancy, lamb survival, and lamb growth rate affect the total lamb liveweight at weaning per ewe exposed to the ram in the flock. The data from the commercial flock was also used to investigate the role of ewe age and premating liveweight on each reproductive step. Sensitivity analyses were performed to identify the key reproductive steps affecting flock reproductive performance. The elasticity for embryo survival was 80% of that for lamb survival. There was also significant between sire variance in the estimates of ovulation rate and embryo survival. The reproductive performance of daughters of sires with high (top 50%) and low (bottom 50%) embryo survival was investigated. Embryo survival was 0.88 in the high group and 0.82 in the low group (a 6% reduction in embryo survival). The expected total weight of lambs weaned per ewe exposed to the ram was 42 kg in the high embryo survival group and 37 kg in the low embryo survival group (a 12% reduction in the total weight of lambs weaned per ewe exposed to the ram). The proportion of twin litters was 70% in the high group and 60% in the low group, highlighting the potential importance of embryo survival for the rate of twinning in flocks with ovulation rates greater than two ova. Although lamb survival was similar between the high and low embryo survival groups, lamb growth was reduced by 10% in the low embryo survival group for the same litter size (P < 0.001). This novel positive phenotypic association between embryo survival and lamb growth rate can potentially be exploited to improve flock performance.

Post-term birth is associated with greater risk of obesity in adolescent males.

OBJECTIVE: To test the hypothesise that post-term birth (>42 weeks gestation) adversely affects longitudinal growth and weight gain throughout childhood. STUDY DESIGN: A total of 525 children (including 17 boys and 20 girls born post-term) were followed from birth to age 16 years. Weight and height were recorded prospectively throughout childhood, and respective velocities from birth to end of puberty were calculated using a mathematical model. RESULTS: At birth, post-term girls were slimmer than term girls (ponderal index, 27.7 ± 2.6 kg/m(3) vs 26.3 ± 2.8 kg/m(3); P<.05). At age 16 years, post-term boys were 11.8 kg heavier than term subjects (body mass index [BMI], 25.4 ± 5.5 kg/m(2) vs 21.7 ± 3.1 kg/m(2); P<.01). The rate of obesity was 29% in post-term boys and 7% in term boys (P<.01), and the combined rate of overweight and obesity was 47% in post-term boys and 13% in term boys (P<.01). Weight velocity, but not height velocity, was higher in post-term boys at age 1.5-7 years (P<.05) and again at age 11.5-16 years (P<.05). BMI was higher in post-term boys at age 3 years, with the difference increasing thereafter. BMI and growth were similar in post-term and term girls. CONCLUSION: In this post-term birth cohort, boys, but not girls, demonstrated accelerated weight gain during childhood, leading to greater risk of obesity in adolescence.

The role of reproductive loss on flock performance: a comparison of nine industry flocks.

The reproductive performance of a sheep flock is dependent on a multitude of complex interacting factors. Attaining optimal flock performance requires information about how the reproductive steps are linked and relate to readily available measurements of the state of the flock. The goal was to use data from nine commercial flocks (greater than 300,000 records) to investigate and model the key reproductive steps affecting flock reproductive performance. We also developed a maximum-likelihood based methodology to predict flock ovulation rate based on measurements of the number of fetuses at mid-pregnancy (detected by ultrasound-scanning). The model was used to determine how changes in premating liveweight, age, predicted ovulation rate, number of fetuses at mid-pregnancy, lamb survival and lamb growth rate affect the total lamb liveweight at weaning per ewe exposed to the ram in each flock. The data from the commercial flocks were also used to investigate the role of ewe age and premating liveweight on each reproductive step. Sensitivity analyses were conducted to identify the key reproductive steps affecting flock reproductive performance, with a focus on understanding how these steps vary between flocks. The elasticity for embryo survival was 60% of that for lamb survival for these flocks and the elasticities for ovulation rate were highly variable between flocks (0.16 to 0.50 for mature ewes). This indicates that ovulation rate was near-optimal for some flocks, whereas there was potential to significantly improve flock performance in suboptimal flocks. The elasticity for ewe premating liveweight was highly variable between flocks (-0.03 to 0.84 for mature ewes and -0.18 to 1.39 for ewe lambs), indicating that premating liveweight ranged from optimal to suboptimal between flocks. For these suboptimal farms, the opportunity exists to increase flock performance through improved management of ewe premating liveweight. Reproductive loss was significantly greater in ewe lambs than mature ewes, although the difference is dependent on the stage of reproduction and flock. Predicted ovulation rate was 25% lower for ewe lambs and there was a 30% relative decrease in the predicted embryo survival probability from ovulation to scanning for ewe lambs. There was a 10% relative decrease in lamb survival probability from birth to weaning for ewe lambs and lamb growth rate was 25% lower for ewe lambs.

Algorithms predicting gestational stage from the maternal steroid metabolome of mares.

Hormone secretion by the maternal ovaries, trophoblast/placenta and fetus occurs sequentially, creating distinct steroid metabolomic 'signatures' in systemic blood of pregnant mares that vary with gestational stage. Algorithms were developed to predict the gestational day (GD) from the maternal steroid metabolome (nine steroids; pregnenolone (P5), progesterone (P4), 5α-dihydroprogesterone (DHP), 17α-hydroxyprogesterone, allopregnanolone, 20α-hydroxy-DHP, 3ß,20α-dihydroxy-DHP, DHEA and androstenedione) determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) of eight thoroughbred mares sampled longitudinally throughout pregnancy. A physiologically based model was developed to infer rates of steroid secretion during chorionic gonadotropin secretion, the luteo-placental shift and by the equine feto-placenta unit, demonstrating more variability in P5 and DHP than P4. The average of four empirical models, using nine steroids to predict GD, was calibrated (five mares, R2 = 0.94, RMSE = 20 days) and validated (three mares, R2 = 0.84, RMSE = 32 days). Validation performance was improved using paired samples taken 14 or 30 days apart (RMSE = 29 and 19 days, respectively). A second validation used an independent dataset (single serum samples from 56 mixed breed mares, RMSE = 79 days) and an additional longitudinal subset from the same population sampled monthly throughout gestation (seven mares, RMSE = 42 days). Again, using paired samples improved model performance (RMSE = 32.5 days). Despite less predictive performance of the mixed breed than the thoroughbred datasets, these models demonstrate the feasibility and potential for using maternal steroid metabolomic algorithms to estimate the stage of gestation in pregnant mares and perhaps monitor fetal development.

The autocrine regulation of insulin-like growth factor-1 in human brain of Alzheimer's disease.

BACKGROUND: Insulin-like growth factor (IGF) binding protein (IGFBP)-3 and cyclic Glycine-Proline (cGP) regulate circulating IGF-1 function that is associated with cognition. The association between IGF-1 function and Alzheimer's disease (AD) remains inconclusive. This study evaluated the changes of IGFBPs and cGP, and their effects on the bioavailability and function of IGF-1 in human brain of AD cases. METHODS: Using biological and mathematic analysis we measured the concentrations of total, bound and unbound forms of IGF-1, IGFBPs and cGP in the inferior-frontal gyrus and middle-frontal gyrus of human AD (n = 15) and control cases (n = 15). The association between the changes of total concentration of these peptides and total protein concentration in brain tissues were also analyzed. RESULTS: The unbound bioavailable IGF-1 was lower whereas the bound cGP and IGFBP-3 were higher in AD than the control cases. Total protein that was lower in AD than control cases, was negatively associated with cGP concentration of control cases and with IGFBP-3 concentration of AD cases. CONCLUSIONS: The results provide direct evidence for IGF-1 deficiency in AD brain due to lower bioavailable IGF-1. The increase of bound IGFBP-3 impaired autocrine regulation. The increase of bound cGP is an autocrine response to improve the bioavailability and function of IGF-1 in AD brain. AVAILABILITY OF DATA AND MATERIAL: All data generated or analysed during this study are included in this published article. Additional datasets analysed during the current study available from the corresponding author on reasonable request.

The effect of reproductive loss on the performance of a research flock.

The reproductive performance of a sheep flock is dependent on a multitude of complex interacting factors. Achieving optimal flock performance requires knowledge of the reproductive steps and how these are linked and related to available measurements of the state and performance of the flock. The goal was to use previously collected data from a research flock that had undergone selection for fecundity (11,369 lambing records), to model the key reproductive steps affecting flock reproductive performance. The model was used to investigate how changes in liveweight, age, ovulation rate, number of fetuses at midpregnancy, number of lambs born, and birthweight affect the number of lambs weaned and the weaning weight of each lamb in this flock. The data available from the research flock were used to parameterize models of each reproductive step and assess the role of ewe age and premating liveweight on each reproductive step. These models were then linked together as a simulation tool to assess the role of different parameters on flock reproductive performance, which was defined as the total weight of lambs weaned per ewe exposed to the ram. Flock elasticities were calculated that characterize the relative importance of the effect of average premating ewe liveweight (0.81), average ovulation rate (0.33), variance in ovulation rate (-0.095), embryo survival (0.72), lamb survival (1.03), conception failure (0.35), and average ewe age (0.056) on the total kilograms of lamb liveweight at weaning per ewe exposed to the ram. The largest elasticity for lamb survival indicated that a 1% increase in lamb survival is expected to have a 1.03% increase in the total kilograms of lamb liveweight at weaning per ewe exposed to the ram in this flock. Assuming similar costs, interventions to increase lamb survival for this flock will provide the largest increase in the total kilograms of lamb liveweight at weaning per ewe exposed to the ram, which is a key metric of flock performance.

Competition for Hydrogen Prevents Coexistence of Human Gastrointestinal Hydrogenotrophs in Continuous Culture.

Understanding the metabolic dynamics of the human gastrointestinal tract (GIT) microbiota is of growing importance as research continues to link the microbiome to host health status. Microbial strains that metabolize hydrogen have been associated with a variety of both positive and negative host nutritional and health outcomes, but limited data exists for their competition in the GIT. To enable greater insight into the behaviour of these microbes, a mathematical model was developed for the metabolism and growth of the three major hydrogenotrophic groups: sulphate-reducing bacteria (SRB), methanogens and reductive acetogens. In batch culture simulations with abundant sulphate and hydrogen, the SRB outcompeted the methanogen for hydrogen due to having a half-saturation constant 106 times lower than that of the methanogen. The acetogen, with a high model threshold for hydrogen uptake of around 70 mM, was the least competitive. Under high lactate and zero sulphate conditions, hydrogen exchange between the SRB and the methanogen was the dominant interaction. The methanogen grew at 70% the rate of the SRB, with negligible acetogen growth. In continuous culture simulations, both the SRB and the methanogen were washed out at dilution rates above 0.15 h-1 regardless of substrate availability, whereas the acetogen could survive under abundant hydrogen conditions. Specific combinations of conditions were required for survival of more than one hydrogenotroph in continuous culture, and survival of all three was not possible. The stringency of these requirements and the inability of the model to simulate survival of all three hydrogenotrophs in continuous culture demonstrates that factors outside of those modelled are vital to allow hydrogenotroph coexistence in the GIT.

Predicting the quality of ryegrass using hyperspectral imaging.

BACKGROUND: The quality of forage plants is a crucial component of animal performance and a limiting factor in pasture based production systems. Key forage attributes that may require improvement include the sugar, lipid, protein and energy contents of the vegetative parts of these plants. The aim of this study was to evaluate the potential capacity of hyperspectral imaging (HSI) for non-invasive assessment of forage chemical composition. Hyperspectral image data within the visible near-infrared range into the extended near-infrared covering 550-1700 nm wavelengths were obtained from 185 accessions of ryegrass (Lolium perenne), which were also analysed for 13 forage quality attributes. RESULTS: Medium to high predictive power was observed for the HSI models of total sugars (R2 validation of 0.58), high molecular weight sugars (R2 validation of 0.63), %Ash (R2 validation of 0.50) and %Nitrogen (R2 validation of 0.70). Significant HSI models with low R2 validation of 0.1-0.5 were also obtained for low molecular weight sugars, NDF (%), ADF (%), DOMD (% DM), ME (MJ/kg DM), DM (%), Ca (mg/g) and OM (%). We also observed significant differences in the chemical composition between the pseudostems and leaves of the plants for each accession. The power of HSI for prediction of these differences within plants was also demonstrated. CONCLUSION: This study paves the way for the HSI technology to be used for in-field estimation of forage composition attributes in perennial ryegrass. This will allow more rapid genetic-based selection and breeding for a trait that is normally expensive to measure providing a cheaper, non-destructive and high throughput screening tool.

A Mathematical Model for the Hydrogenotrophic Metabolism of Sulphate-Reducing Bacteria.

Sulphate-reducing bacteria (SRB) are studied across a range of scientific fields due to their characteristic ability to metabolise sulphate and produce hydrogen sulphide, which can lead to significant consequences for human activities. Importantly, they are members of the human gastrointestinal microbial population, contributing to the metabolism of dietary and host secreted molecules found in this environment. The role of the microbiota in host digestion is well studied, but the full role of SRB in this process has not been established. Moreover, from a human health perspective, SRB have been implicated in a number of functional gastrointestinal disorders such as Irritable Bowel Syndrome and the development of colorectal cancer. To assist with the study of SRB, we present a mathematical model for the growth and metabolism of the well-studied SRB, Desulfovibrio vulgaris in a closed system. Previous attempts to model SRB have resulted in complex or highly specific models that are not easily adapted to the study of SRB in different environments, such as the gastrointestinal tract. We propose a simpler, Monod-based model that allows for easy alteration of both key parameter values and the governing equations to enable model adaptation. To prevent any incorrect assumptions about the nature of SRB metabolic pathways, we structure the model to consider only the concentrations of initial and final metabolites in a pathway, which circumvents the current uncertainty around hydrogen cycling by SRB. We parameterise our model using experiments with varied initial substrate conditions, obtaining parameter values that compare well with experimental estimates in the literature. We then validate our model against four independent experiments involving D. vulgaris with further variations to substrate availability. Further use of the model will be possible in a number of settings, notably as part of larger models studying the metabolic interactions between SRB and other hydrogenotrophic microbes in the human gastrointestinal tract and how this relates to functional disorders.

Hydrogen cross-feeders of the human gastrointestinal tract.

Hydrogen plays a key role in many microbial metabolic pathways in the human gastrointestinal tract (GIT) that have an impact on human nutrition, health and wellbeing. Hydrogen is produced by many members of the GIT microbiota, and may be subsequently utilized by cross-feeding microbes for growth and in the production of larger molecules. Hydrogenotrophic microbes fall into three functional groups: sulfate-reducing bacteria, methanogenic archaea and acetogenic bacteria, which can convert hydrogen into hydrogen sulfide, methane and acetate, respectively. Despite different energy yields per molecule of hydrogen used between the functional groups, all three can coexist in the human GIT. The factors affecting the numerical balance of hydrogenotrophs in the GIT remain unconfirmed. There is increasing evidence linking both hydrogen sulfide and methane to GIT diseases such as irritable bowel syndrome, and strategies for the mitigation of such health problems through targeting of hydrogenotrophs constitute an important field for further investigation.

Anomalous ion diffusion within skeletal muscle transverse tubule networks.

BACKGROUND: Skeletal muscle fibres contain transverse tubular (t-tubule) networks that allow electrical signals to rapidly propagate into the fibre. These electrical signals are generated by the transport of ions across the t-tubule membranes and this can result in significant changes in ion concentrations within the t-tubules during muscle excitation. During periods of repeated high-frequency activation of skeletal muscle the t-tubule K+ concentration is believed to increase significantly and diffusive K+ transport from the t-tubules into the interstitial space provides a mechanism for alleviating muscle membrane depolarization. However, the tortuous nature of the highly branched space-filling t-tubule network impedes the diffusion of material through the network. The effective diffusion coefficient for ions in the t-tubules has been measured to be approximately five times lower than in free solution, which is significantly different from existing theoretical values of the effective diffusion coefficient that range from 2-3 times lower than in free solution. To resolve this discrepancy, in this paper we study the process of diffusion within electron microscope scanned sections of the skeletal muscle t-tubule network using mathematical modelling and computer simulation techniques. Our model includes t-tubule geometry, tautness, hydrodynamic and non-planar network factors. RESULTS: Using our model we found that the t-tubule network geometry reduced the K+ diffusion coefficient to 19-27% of its value in free solution, which is consistent with the experimentally observed value of 21% and is significantly smaller than existing theoretical values that range from 32-50%. We also found that diffusion in the t-tubules is anomalous for skeletal muscle fibres with a diameter of less than approximately 10-20 microm as a result of obstructed diffusion. We also observed that the [K+] within the interior of the t-tubule network during high-frequency activation is greater for fibres with a larger diameter. Smaller skeletal muscle fibres are therefore more resistant to membrane depolarization. Because the t-tubule network is anisotropic and inhomogeneous, we also found that the [K+] distribution generated within the network was irregular for fibres of small diameter. CONCLUSION: Our model explains the measured effective diffusion coefficient for ions in skeletal muscle t-tubules.

Modeling the effect of insulin-like growth factor-1 on human cell growth.

Insulin-like growth factor-1 (IGF-1) plays a key role in human growth and development. The interactions of IGF-1 with IGF-1 receptors and IGF-1 binding proteins (IGFBPs) regulate IGF-1 function. Recent research suggests that a metabolite of IGF-1, cyclo-glycyl-proline (cGP), has a role in regulating IGF-1 homeostasis. A component of this interaction is believed to be the competitive binding of IGF-1 and cGP to IGFBPs. In this paper we describe a mathematical model of the interaction between IGF-1 and cGP on human cell growth. The model can be used to understand the interaction between IGF-1, IGFBPs, cGP and IGF-1 receptors along with the kinetics of cell growth. An explicit model of the known interactions between IGF-1, cGP, IGFBPs, IGF-1 receptors explained a large portion of the variance in cell growth (R(2) = 0.83). An implicit model of the interactions between IGF-1, cGP, IGFBPs, IGF-1 receptors that included a hypothesized feedback of cGP on IGF-1 receptors explained nonlinear features of interaction between IGF-1 and cGP not described by the explicit model (R(2) = 0.84). The model also explained the effect of IGFBP antibody on the interaction between cGP and IGF-1 (R(2) = 0.78). This demonstrates that the competitive binding of IGF-1 and cGP to IGFBPs plays a large role in the interaction between IGF-1 and cGP, but that other factors potentially play a role in the interaction between cGP and IGF-1. These models can be used to predict the complex interaction between IGF-1 and cGP on human cell growth and form a basis for further research in this field.

Development of a formula for estimating plasma free cortisol concentration from a measured total cortisol concentration when elastase-cleaved and intact corticosteroid binding globulin coexist.

Cortisol bound to corticosteroid binding globulin (CBG) contributes up to 90% of the total cortisol concentration in circulation. Therefore, changes in the binding kinetics of cortisol to CBG can potentially impact on the concentration of free cortisol, the only form that is responsible for the physiological function of the hormone. When CBG is cleaved into elastase-cleaved CBG (eCBG) by the activity of neutrophil elastase, its affinity for cortisol is reduced. Therefore, when eCBG coexists with intact CBG (iCBG) in plasma, the calculation of free cortisol concentration based on the formulae that considers only one CBG pool with the same affinity for cortisol may be inappropriate. In this study, we developed in vivo and in vitro models of cortisol partitioning which considers two CBG pools, iCBG and eCBG, with different affinities for cortisol, and deduce a new formula for calculating plasma free cortisol concentration. The formula provides better estimates of free cortisol concentration than previously used formulae when measurements of the concentrations of the two CBG forms are available. The model can also be used to estimate the affinity of CBG and albumin for cortisol in different clinical groups. We found no significant difference in the estimated affinity of CBG and albumin for cortisol in normal, sepsis and septic shock groups, although free cortisol was higher in sepsis and septic shock groups. The in vivo model also demonstrated that the concentration of interstitial free cortisol is increased locally at a site of inflammation where iCBG is cleaved to form eCBG by the activity of elastase released by neutrophils. This supports the argument that the cleavage of iCBG at sites of inflammation leads to more lower-affinity eCBG and may be a mechanism that permits the local concentration of free cortisol to increase at these sites, while allowing basal free cortisol concentrations at other sites to remain unaffected.

Cyclic glycine-proline regulates IGF-1 homeostasis by altering the binding of IGFBP-3 to IGF-1.

The homeostasis of insulin-like growth factor-1 (IGF-1) is essential for metabolism, development and survival. Insufficient IGF-1 is associated with poor recovery from wounds whereas excessive IGF-1 contributes to growth of tumours. We have shown that cyclic glycine-proline (cGP), a metabolite of IGF-1, can normalise IGF-1 function by showing its efficacy in improving the recovery from ischemic brain injury in rats and inhibiting the growth of lymphomic tumours in mice. Further investigation in cell culture suggested that cGP promoted the activity of IGF-1 when it was insufficient, but inhibited the activity of IGF-1 when it was excessive. Mathematical modelling revealed that the efficacy of cGP was a modulated IGF-1 effect via changing the binding of IGF-1 to its binding proteins, which dynamically regulates the balance between bioavailable and non-bioavailable IGF-1. Our data reveal a novel mechanism of auto-regulation of IGF-1, which has physiological and pathophysiological consequences and potential pharmacological utility.

Bacterial biofilms associated with food particles in the human large bowel.

Bacteria within the gastro-intestinal tract affect host function via production of short-chain fatty acids and synthesis of vitamins. Additionally, the commensal enteric bacteria modulate the immune system and provide protection from potentially pathogenic bacteria. Only recently heterogeneous bacterial biofilms were found to be associated with food particles within the intestinal tract. There are a number of studies investigating the formation and function of pathogenic and single-species biofilms, though few studies have investigated the dynamics of multispecies biofilms, especially with regard to food/microbial/host interactions. The scope of this review is to discuss the current knowledge of bacterial biofilms associated with food particles in the human large bowel, examine the established mathematical models depicting bacterial attachment, and elucidate key areas for further research.

A mathematical model of fatigue in skeletal muscle force contraction.

The ability for muscle to repeatedly generate force is limited by fatigue. The cellular mechanisms behind muscle fatigue are complex and potentially include breakdown at many points along the excitation-contraction pathway. In this paper we construct a mathematical model of the skeletal muscle excitation-contraction pathway based on the cellular biochemical events that link excitation to contraction. The model includes descriptions of membrane voltage, calcium cycling and crossbridge dynamics and was parameterised and validated using the response characteristics of mouse skeletal muscle to a range of electrical stimuli. This model was used to uncover the complexities of skeletal muscle fatigue. We also parameterised our model to describe force kinetics in fast and slow twitch fibre types, which have a number of biochemical and biophysical differences. How these differences interact to generate different force/fatigue responses in fast- and slow- twitch fibres is not well understood and we used our modelling approach to bring new insights to this relationship.