Effect of plasma insulin and branched-chain amino acids on skeletal muscle protein synthesis in fasted lambs

The increase in fractional rate of protein synthesis (K-s) in the skeletal muscle of growing rats during the transition from fasted to fed state has been explained by the synergistic action of a rise in plasma insulin and branched-chain amino acids (BCAA). Since growing lambs Also exhibit an increase in K-s with level of feed intake, the objective of the present study was to determine if this synergistic relationship between insulin and BCAA also occurs in ruminant animals. Six 30 kg fasted (72 h) lambs (8 months of age) received each of four treatments, which were based on continuous infusion into the jugular vein for 6 h of: (1) saline (155 mmol NaCl/l); (2) a mixture of BCAA (0.778 mumol leucine, 0.640 mumol isoleucine and 0.693 mumol valine/min.kg); (3) 18.7 mumol glucose/min.kg (to induce endogenous insulin secretion): (4) co-infusion of BCAA and glucose. Within each period all animals received the same isotope of phenylalanine, (Phe) as follows: (1) L-[1-C-13]Phe; (2) L-phenyl-[ring H-2(5)]-alanine; (3) L-[N-15]Phe; (4) L-[ring 2,6-H-3]Phe. Blood was sampled serially during infusions to measure plasma concentrations of insulin, glucose and amino acids, and plasma free Phe isotopic activity; biopsies were taken 6 h after the beginning of infusions to determine K-s in in. longissimus dorsi and vastus muscle. Compared with control (saline-infused) lambs, K-s was increased by an average of 40% at the end of glucose infusion, but this effect was not statistically significant in either of the muscles sampled. BCAA infusion, alone or in combination with glucose, also had no significant effect on K-s compared with control sheep. K-s was approximately 60% greater for vastus muscle than for m. longissimus dorsi (P<0.01), regardless of treatment. It is concluded that there are signals other than insulin and BCAA that are responsible for the feed-induced increase in K-s in muscle of growing ruminant animals.

General systems perspective on achieving continuous synergy in a project organisation

Studies of construction labour productivity have revealed that limited predictability and multi-agent social complexity make long-range planning of construction projects extremely inaccurate. Fire-fighting, a cultural feature of construction project management, social and structural diversity of involved permanent organizations, and structural temporality all contribute towards relational failures and frequent changes. The main purpose of this paper is therefore to demonstrate that appropriate construction planning may have a profound synergistic effect on structural integration of a project organization. Using the general systems theory perspective it is further a specific objective to investigate and evaluate organizational effects of changes in planning and potentials for achieving continuous project-organizational synergy. The newly developed methodology recognises that planning should also represent a continuous, improvement-leading driving force throughout a project. The synergistic effect of the process planning membership duality fostered project-wide integration, eliminated internal boundaries, and created a pool of constantly upgrading knowledge. It maintained a creative environment that resulted in a number of process-related improvements from all parts of the organization. As a result labour productivity has seen increases of more than 30%, profits have risen from an average of 12% to more than 18%, and project durations have been reduced by several days.

Dithioacetalisation of PEEK: a general technique for the solubilisation and characterisation of semi-crystalline aromatic polyketones

The family of semi-crystalline, aromatic, high-temperature thermoplastics known as poly(ether-ketone)s are insoluble in conventional organic solvents, but undergo completely general and quantitatively reversible reactions with alkanedithiols in strong acid media, to give soluble poly(dithioacetal)s, which are readily characterisable by GPC and light scattering techniques.

Understanding the transition to seizure by modeling the epileptiform activity of general anesthetic agents

A central difficulty in modeling epileptogenesis using biologically plausible computational and mathematical models is not the production of activity characteristic of a seizure, but rather producing it in response to specific and quantifiable physiologic change or pathologic abnormality. This is particularly problematic when it is considered that the pathophysiological genesis of most epilepsies is largely unknown. However, several volatile general anesthetic agents, whose principle targets of action are quantifiably well characterized, are also known to be proconvulsant. The authors describe recent approaches to theoretically describing the electroencephalographic effects of volatile general anesthetic agents that may be able to provide important insights into the physiologic mechanisms that underpin seizure initiation.

A general-method for tracking analysis and its application to meteorological data

Recent interest in the validation of general circulation models (GCMs) has been devoted to objective methods. A small number of authors have used the direct synoptic identification of phenomena together with a statistical analysis to perform the objective comparison between various datasets. This paper describes a general method for performing the synoptic identification of phenomena that can be used for an objective analysis of atmospheric, or oceanographic, datasets obtained from numerical models and remote sensing. Methods usually associated with image processing have been used to segment the scene and to identify suitable feature points to represent the phenomena of interest. This is performed for each time level. A technique from dynamic scene analysis is then used to link the feature points to form trajectories. The method is fully automatic and should be applicable to a wide range of geophysical fields. An example will be shown of results obtained from this method using data obtained from a run of the Universities Global Atmospheric Modelling Project GCM.

Determination of the impact of continuous defoliation of Lolium perenne and Trifolium repens on bacterial and fungal community structure in rhizosphere soil

To determine the effects of defoliation on microbial community structure, rhizosphere soil samples were taken pre-, and post-defoliation from the root tip and mature root regions of Trifolium repens L. and Lolium perenne L. Microbial DNA isolated from samples was used to generate polymerase chain reaction-denaturing gradient gel electrophoresis molecular profiles of bacterial and fungal communities. Bacterial plate counts were also obtained. Neither plant species nor defoliation affected the bacterial and fungal community structures in both the root tip and mature root regions, but there were significant differences in the bacterial and fungal community profiles between the two root regions for each plant. Prior to defoliation, there was no difference between plants for bacterial plate counts of soils from the root tip regions; however, counts were greater in the mature root region of L. perenne than T. repens. Bacterial plate counts for T. repens were higher in the root tip than the mature root region. After defoliation, there was no effect of plant type, position along the root or defoliation status on bacterial plate counts, although there were significant increases in bacterial plate counts with time. The results indicate that a general effect existed during maturation in the root regions of each plant, which had a greater impact on microbial community structure than either plant type or the effect of defoliation. In addition there were no generic consequences with regard to microbial populations in the rhizosphere as a response to plant defoliation.

A novel technique for differentiation of proteins in the development of acid gel structure from control and heat treated milk using confocal scanning laser microscopy

The incorporation of caseins and whey proteins into acid gels produced from unheated and heat treated skimmed milk was studied by confocal scanning laser microscopy (CSLM) using fluorescent labelled proteins. Bovine casein micelles were labelled using Alexa Fluor 594, while whey proteins were labelled using Alexa Fluor 488. Samples of the labelled protein solutions were introduced into aliquots of pasteurised skim milk, and skim milk heated to 90 degrees C for 2 min and 95 degrees C for 8 min. The milk was acidified at 40 degrees C to a final pH of 4.4 using 20 g gluconodelta-lactone/l (GDL). The formation of gels was observed with CSLM at two wavelengths (488 nm and 594 nm), and also by visual and rheological methods. In the control milk, as pH decreased distinct casein aggregates appeared, and as further pH reduction occurred, the whey proteins could be seen to coat the casein aggregates. With the heated milks, the gel structure was formed of continuous strands consisting of both casein and whey protein. The formation of the gel network was correlated with an increase in the elastic modulus for all three treatments, in relation to the severity of heat treatment. This model system allows the separate observation of the caseins and whey proteins, and the study of the interactions between the two protein fractions during the formation of the acid gel structure, on a real-time basis. The system could therefore be a valuable tool in the study of structure formation in yoghurt and other dairy protein systems.

Empirical mode decomposition: a novel technique for the study of tremor time series

Tremor is a clinical feature characterized by oscillations of a part of the body. The detection and study of tremor is an important step in investigations seeking to explain underlying control strategies of the central nervous system under natural (or physiological) and pathological conditions. It is well established that tremorous activity is composed of deterministic and stochastic components. For this reason, the use of digital signal processing techniques (DSP) which take into account the nonlinearity and nonstationarity of such signals may bring new information into the signal analysis which is often obscured by traditional linear techniques (e.g. Fourier analysis). In this context, this paper introduces the application of the empirical mode decomposition (EMD) and Hilbert spectrum (HS), which are relatively new DSP techniques for the analysis of nonlinear and nonstationary time-series, for the study of tremor. Our results, obtained from the analysis of experimental signals collected from 31 patients with different neurological conditions, showed that the EMD could automatically decompose acquired signals into basic components, called intrinsic mode functions (IMFs), representing tremorous and voluntary activity. The identification of a physical meaning for IMFs in the context of tremor analysis suggests an alternative and new way of detecting tremorous activity. These results may be relevant for those applications requiring automatic detection of tremor. Furthermore, the energy of IMFs was visualized as a function of time and frequency by means of the HS. This analysis showed that the variation of energy of tremorous and voluntary activity could be distinguished and characterized on the HS. Such results may be relevant for those applications aiming to identify neurological disorders. In general, both the HS and EMD demonstrated to be very useful to perform objective analysis of any kind of tremor and can therefore be potentially used to perform functional assessment.

Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

Effect of abomasal glucose infusion on plasma concentrations of gut peptides in periparturient dairy cows

Six Holstein cows fitted with ruminal cannulas and permanent indwelling catheters in the portal vein, hepatic vein, mesenteric vein, and an artery were used to study the effects of abomasal glucose infusion on splanchnic plasma concentrations of gut peptides. The experimental design was a randomized block design with repeated measurements. Cows were assigned to one of 2 treatments: control or infusion of 1,500 g of glucose/d into the abomasum from the day of parturition to 29 d in milk. Cows were sampled 12 ± 6 d prepartum and at 4, 15, and 29 d in milk. Concentrations of glucose-dependent insulinotropic polypeptide, glucagon-like peptide 1(7–36) amide, and oxyntomodulin were measured in pooled samples within cow and sampling day, whereas active ghrelin was measured in samples obtained 30 min before and after feeding at 0800 h. Postpartum, dry matter intake increased at a lower rate with infusion compared with the control. Arterial, portal venous, and hepatic venous plasma concentrations of the measured gut peptides were unaffected by abomasal glucose infusion. The arterial, portal venous, and hepatic venous plasma concentrations of glucose-dependent insulinotropic polypeptide and glucagon-like peptide 1(7–36) amide increased linearly from 12 d prepartum to 29 d postpartum. Plasma concentrations of oxyntomodulin were unaffected by day relative to parturition. Arterial and portal venous plasma concentrations of ghrelin were lower postfeeding compared with prefeeding concentrations. Arterial plasma concentrations of ghrelin were greatest prepartum and lowest at 4 d postpartum, giving a quadratic pattern of change over the transition period. Positive portal venous-arterial and hepatic venous–arterial concentration differences were observed for glucagon-like peptide 1(7–36) amide. A negative portal venous–arterial concentration difference was observed for ghrelin pre-feeding. The remaining portal venous–arterial and hepatic venous–arterial concentration differences of gut peptides did not differ from zero. In conclusion, increased postruminal glucose supply to postpartum transition dairy cows reduced feed intake relative to control cows, but did not affect arterial, portal venous, or hepatic venous plasma concentrations of gut peptide hormones. Instead, gut peptide plasma concentrations increased as lactation progressed. Thus, the lower feed intake of postpartum dairy cows receiving abomasal glucose infusion was not attributable to changes in gut peptide concentrations.

Low-order dynamical behavior in the martian atmosphere: Diagnosis of general circulation model results

The hypothesis of a low dimensional martian climate attractor is investigated by the application of the proper orthogonal decomposition (POD) to a simulation of martian atmospheric circulation using the UK Mars general circulation model (UK-MGCM). In this article we focus on a time series of the interval between autumn and winter in the northern hemisphere, when baroclinic activity is intense. The POD is a statistical technique that allows the attribution of total energy (TE) to particular structures embedded in the UK-MGCM time-evolving circulation. These structures are called empirical orthogonal functions (EOFs). Ordering the EOFs according to their associated energy content, we were able to determine the necessary number to account for a chosen amount of atmospheric TE. We show that for Mars a large fraction of TE is explained by just a few EOFs (with 90% TE in 23 EOFs), which apparently support the initial hypothesis. We also show that the resulting EOFs represent classical types of atmospheric motion, such as thermal tides and transient waves. Thus, POD is shown to be an efficient method for the identification of different classes of atmospheric modes. It also provides insight into the non-linear interaction of these modes.

Model predictive control using dynamic integrated system optimisation and parameter estimation (DISOPE)

DISOPE is a technique for solving optimal control problems where there are differences in structure and parameter values between reality and the model employed in the computations. The model reality differences can also allow for deliberate simplification of model characteristics and performance indices in order to facilitate the solution of the optimal control problem. The technique was developed originally in continuous time and later extended to discrete time. The main property of the procedure is that by iterating on appropriately modified model based problems the correct optimal solution is achieved in spite of the model-reality differences. Algorithms have been developed in both continuous and discrete time for a general nonlinear optimal control problem with terminal weighting, bounded controls and terminal constraints. The aim of this paper is to show how the DISOPE technique can aid receding horizon optimal control computation in nonlinear model predictive control.

DHA-rich fish oil reverses the detrimental effects of saturated fatty acids on postprandial vascular reactivity

Background: Experimental elevation of nonesterified fatty acids (NEFAs) impairs endothelial function, but the effect of NEFA composition is unknown. Objective: The objective was to test the effect of acute elevation of NEFAs enriched with either saturated fatty acids (SFAs) or SFAs with long-chain (LC) n−3 (omega-3) PUFAs on vascular function measured via flow-mediated dilatation (FMD), laser Doppler iontophoresis (LDI), and digital volume pulse (DVP). Design: In 59 subjects (30 men and 29 women), repeated oral fat feeding of either palm stearin (SFA) or palm stearin with DHA-rich fish oil (SFA + LC n−3 PUFA) was performed on 2 separate occasions with continuous heparin infusion to elevate NEFAs for a duration of 60 to 240 min. Vascular function was measured at baseline and at the end of NEFA elevation; venous blood was collected for measurement of lipids and circulating markers of endothelial function. Results: NEFA elevation during consumption of the SFA-rich drinks was associated with a marked impairment of FMD, whereas consumption of SFAs + LC n−3 PUFAs improved FMD response, with a mean (±SEM) difference of 2.06 ± 0.29% (P < 0.001). Positive correlations were found with percentage weight of LC n−3 PUFAs in circulating NEFAs and change in FMD response [Spearman's rho (rs) = 0.460, P < 0.001]. LDI measures increased during both treatments (P ≤ 0.026), and there was no change in DVP indexes. Conclusions: The composition of NEFAs can acutely affect FMD. The beneficial effect of LC n−3 PUFAs on postprandial vascular function warrants further investigation but may be mediated by nitric oxide–independent mechanisms. This trial is registered at clinicaltrials.gov as NCT01351324.

Evaluating mid-infrared spectroscopy as a new technique for predicting sensory texture attributes of processed cheese

The objective of this study was to investigate the potential application of mid-infrared spectroscopy for determination of selected sensory attributes in a range of experimentally manufactured processed cheese samples. This study also evaluates mid-infrared spectroscopy against other recently proposed techniques for predicting sensory texture attributes. Processed cheeses (n = 32) of varying compositions were manufactured on a pilot scale. After 2 and 4 wk of storage at 4 degrees C, mid-infrared spectra ( 640 to 4,000 cm(-1)) were recorded and samples were scored on a scale of 0 to 100 for 9 attributes using descriptive sensory analysis. Models were developed by partial least squares regression using raw and pretreated spectra. The mouth-coating and mass-forming models were improved by using a reduced spectral range ( 930 to 1,767 cm(-1)). The remaining attributes were most successfully modeled using a combined range ( 930 to 1,767 cm(-1) and 2,839 to 4,000 cm(-1)). The root mean square errors of cross-validation for the models were 7.4(firmness; range 65.3), 4.6 ( rubbery; range 41.7), 7.1 ( creamy; range 60.9), 5.1(chewy; range 43.3), 5.2(mouth-coating; range 37.4), 5.3 (fragmentable; range 51.0), 7.4 ( melting; range 69.3), and 3.1 (mass-forming; range 23.6). These models had a good practical utility. Model accuracy ranged from approximate quantitative predictions to excellent predictions ( range error ratio = 9.6). In general, the models compared favorably with previously reported instrumental texture models and near-infrared models, although the creamy, chewy, and melting models were slightly weaker than the previously reported near-infrared models. We concluded that mid-infrared spectroscopy could be successfully used for the nondestructive and objective assessment of processed cheese sensory quality..

On variational data assimilation in continuous time

Variational data assimilation in continuous time is revisited. The central techniques applied in this paper are in part adopted from the theory of optimal nonlinear control. Alternatively, the investigated approach can be considered as a continuous time generalization of what is known as weakly constrained four-dimensional variational assimilation (4D-Var) in the geosciences. The technique allows to assimilate trajectories in the case of partial observations and in the presence of model error. Several mathematical aspects of the approach are studied. Computationally, it amounts to solving a two-point boundary value problem. For imperfect models, the trade-off between small dynamical error (i.e. the trajectory obeys the model dynamics) and small observational error (i.e. the trajectory closely follows the observations) is investigated. This trade-off turns out to be trivial if the model is perfect. However, even in this situation, allowing for minute deviations from the perfect model is shown to have positive effects, namely to regularize the problem. The presented formalism is dynamical in character. No statistical assumptions on dynamical or observational noise are imposed.