Monoacylglycerol, alpha/beta-hydrolase domain-6, and the regulation of insulin secretion and energy metabolism

Le cycle glycérolipides/acides gras libres (GL/FFA) est une voie métabolique clé qui relie le métabolisme du glucose et des acides gras et il est composé de deux processus métaboliques appelés lipogenèse et lipolyse. Le cycle GL/FFA, en particulier la lipolyse des triglycérides, génère diverses molécules de signalisation pour réguler la sécrétion d'insuline dans les cellules bêta pancréatiques et la thermogenèse non-frissonnante dans les adipocytes. Actuellement, les lipides provenant spécifiquement de la lipolyse impliqués dans ce processus sont mal connus. L’hydrolyse des triglycérides dans les cellules β est réalisée par les actions successives de la triglycéride lipase adipocytaire pour produire le diacylglycérol, ensuite par la lipase hormono-sensible pour produire le monoacylglycérol (MAG) et enfin par la MAG lipase (MAGL) qui relâche du glycerol et des acides gras. Dans les cellules bêta, la MAGL classique est très peu exprimée et cette étude a démontré que l’hydrolyse de MAG dans les cellules β est principalement réalisée par l'α/β-Hydrolase Domain-6 (ABHD6) nouvellement identifiée. L’inhibition d’ABHD6 par son inhibiteur spécifique WWL70, conduit à une accumulation des 1-MAG à longues chaines saturées à l'intérieur des cellules, accompagnée d’une augmentation de la sécrétion d'insuline stimulée par le glucose (GSIS). Baisser les niveaux de MAG en surexprimant ABHD6 dans la lignée cellulaire bêta INS832/13 réduit la GSIS, tandis qu’une augmentation des niveaux de MAG par le « knockdown » d’ABHD6 améliore la GSIS. L'exposition aiguë des monoacylglycérols exogènes stimule la sécrétion d'insuline de manière dose-dépendante et restaure la GSIS supprimée par un inhibiteur de lipases appelé orlistat. En outre, les souris avec une inactivation du gène ABHD6 dans tous les tissus (ABHD6-KO) et celles avec une inactivation du gène ABHD6 spécifiquement dans la cellule β présentent une GSIS stimulée, et leurs îlots montrent une augmentation de la production de monoacylglycérol et de la sécrétion d'insuline en réponse au glucose. L’inhibition d’ABHD6 chez les souris diabétiques (modèle induit par de faibles doses de streptozotocine) restaure la GSIS et améliore la tolérance au glucose. De plus, les résultats montrent que les MAGs non seulement améliorent la GSIS, mais potentialisent également la sécrétion d’insuline induite par les acides gras libres ainsi que la sécrétion d’insuline induite par divers agents et hormones, sans altération de l'oxydation et l'utilisation du glucose ainsi que l'oxydation des acides gras. Nous avons démontré que le MAG se lie à la protéine d’amorçage des vésicules appelée Munc13-1 et l’active, induisant ainsi l’exocytose de l'insuline. Sur la base de ces observations, nous proposons que le 1-MAG à chaines saturées agit comme facteur de couplage métabolique pour réguler la sécrétion d'insuline et que ABHD6 est un modulateur négatif de la sécrétion d'insuline. En plus de son rôle dans les cellules bêta, ABHD6 est également fortement exprimé dans les adipocytes et son niveau est augmenté avec l'obésité. Les souris dépourvues globalement d’ABHD6 et nourris avec une diète riche en gras (HFD) montrent une faible diminution de la prise alimentaire, une diminution du gain de poids corporel et de la glycémie à jeun et une amélioration de la tolérance au glucose et de la sensibilité à l'insuline et ont une activité locomotrice accrue. En outre, les souris ABHD6-KO affichent une augmentation de la dépense énergétique et de la thermogenèse induite par le froid. En conformité avec ceci, ces souris présentent des niveaux élevés d’UCP1 dans les adipocytes blancs et bruns, indiquant le brunissement des adipocytes blancs. Le phénotype de brunissement est reproduit dans les souris soit en les traitant de manière chronique avec WWL70 (inhibiteur d’ABHD6) ou des oligonucléotides anti-sense ciblant l’ABHD6. Les tissus adipeux blanc et brun isolés de souris ABHD6-KO montrent des niveaux très élevés de 1-MAG, mais pas de 2-MAG. L'augmentation des niveaux de MAG soit par administration exogène in vitro de 1-MAG ou par inhibition ou délétion génétique d’ABHD6 provoque le brunissement des adipocytes blancs. Une autre évidence indique que les 1-MAGs sont capables de transactiver PPARα et PPARγ et que l'effet de brunissement induit par WWL70 ou le MAG exogène est aboli par les antagonistes de PPARα et PPARγ. L’administration in vivo de l’antagoniste de PPARα GW6471 à des souris ABHD6-KO inverse partiellement les effets causés par l’inactivation du gène ABHD6 sur le gain de poids corporel, et abolit l’augmentation de la thermogenèse, le brunissement du tissu adipeux blanc et l'oxydation des acides gras dans le tissu adipeux brun. L’ensemble de ces observations indique que ABHD6 régule non seulement l’homéostasie de l'insuline et du glucose, mais aussi l'homéostasie énergétique et la fonction des tissus adipeux. Ainsi, 1-MAG agit non seulement comme un facteur de couplage métabolique pour réguler la sécrétion d'insuline en activant Munc13-1 dans les cellules bêta, mais régule aussi le brunissement des adipocytes blancs et améliore la fonction de la graisse brune par l'activation de PPARα et PPARγ. Ces résultats indiquent que ABHD6 est une cible prometteuse pour le développement de thérapies contre l'obésité, le diabète de type 2 et le syndrome métabolique.

Energy Management in Wireless Sensor Networks: A Crosslayer,Channel Adaptive Approach Towards Performance Optimization

The proliferation of wireless sensor networks in a large spectrum of applications had been spurered by the rapid advances in MEMS(micro-electro mechanical systems )based sensor technology coupled with low power,Low cost digital signal processors and radio frequency circuits.A sensor network is composed of thousands of low cost and portable devices bearing large sensing computing and wireless communication capabilities. This large collection of tiny sensors can form a robust data computing and communication distributed system for automated information gathering and distributed sensing.The main attractive feature is that such a sensor network can be deployed in remote areas.Since the sensor node is battery powered,all the sensor nodes should collaborate together to form a fault tolerant network so as toprovide an efficient utilization of precious network resources like wireless channel,memory and battery capacity.The most crucial constraint is the energy consumption which has become the prime challenge for the design of long lived sensor nodes.

Characterization of Wastes from Natural Rubber and Rubber Wood Processing Industries and Their Utilization for Biomethanation

The research work which was carried out to characterization of wastes from natural rubber and rubber wood processing industries and their utilization for biomethanation. Environmental contamination is an inevitable consequence of human activity. The liquid and solid wastes from natural rubber based industries were: characterized and their use for the production of biogas investigated with a view to conserve conventional energy, and to mitigate environmental degradation.Rubber tree (flevea brasiliensis Muell. Arg.), is the most important commercial source of natural rubber and in india. Recently, pollution from the rubber processing factories has become very serious due to the introduction of modern methods and centralized group processing practices.The possibility of the use of spent slurry as organic manure is discussed.l0 percent level of PSD, the activity of cellulolytic, acid producing,proteolytic, lipolytic and methanogenic bacteria were more in the middle stage of methanogenesis.the liquid wastes from rubber processing used as diluents in combination with PSD, SPE promoted more biogas production with high methane content in the gas.The factors that favour methane production like TS, VS, cellulose and hemicellulose degradation were favoured in this treatment which led to higher methane biogenesis.The results further highlight ways and means to use agricultural wastes as alternative sources of energy.

Impact of sward type, cutting date and conditioning temperature on mass and energy flows in the integrated generation of solid fuel and biogas from semi-natural grassland

Energy production from biomass and the conservation of ecologically valuable grassland habitats are two important issues of agriculture today. The combination of a bioenergy production, which minimises environmental impacts and competition with food production for land with a conversion of semi-natural grasslands through new utilization alternatives for the biomass, led to the development of the IFBB process. Its basic principle is the separation of biomass into a liquid fraction (press fluid, PF) for the production of electric and thermal energy after anaerobic digestion to biogas and a solid fraction (press cake, PC) for the production of thermal energy through combustion. This study was undertaken to explore mass and energy flows as well as quality aspects of energy carriers within the IFBB process and determine their dependency on biomass-related and technical parameters. Two experiments were conducted, in which biomass from semi-natural grassland was conserved as silage and subjected to a hydrothermal conditioning and a subsequent mechanical dehydration with a screw press. Methane yield of the PF and the untreated silage was determined in anaerobic digestion experiments in batch fermenters at 37°C with a fermentation time of 13-15 and 27-35 days for the PF and the silage, respectively. Concentrations of dry matter (DM), ash, crude protein (CP), crude fibre (CF), ether extract (EE), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent ligning (ADL) and elements (K, Mg, Ca, Cl, N, S, P, C, H, N) were determined in the untreated biomass and the PC. Higher heating value (HHV) and ash softening temperature (AST) were calculated based on elemental concentration. Chemical composition of the PF and mass flows of all plant compounds into the PF were calculated. In the first experiment, biomass from five different semi-natural grassland swards (Arrhenaterion I and II, Caricion fuscae, Filipendulion ulmariae, Polygono-Trisetion) was harvested at one late sampling (19 July or 31 August) and ensiled. Each silage was subjected to three different temperature treatments (5°C, 60°C, 80°C) during hydrothermal conditioning. Based on observed methane yields and HHV as energy output parameters as well as literature-based and observed energy input parameters, energy and green house gas (GHG) balances were calculated for IFBB and two reference conversion processes, whole-crop digestion of untreated silage (WCD) and combustion of hay (CH). In the second experiment, biomass from one single semi-natural grassland sward (Arrhenaterion) was harvested at eight consecutive dates (27/04, 02/05, 09/05, 16/05, 24/05, 31/05, 11/06, 21/06) and ensiled. Each silage was subjected to six different treatments (no hydrothermal conditioning and hydrothermal conditioning at 10°C, 30°C, 50°C, 70°C, 90°C). Energy balance was calculated for IFBB and WCD. Multiple regression models were developed to predict mass flows, concentrations of elements in the PC, concentration of organic compounds in the PF and energy conversion efficiency of the IFBB process from temperature of hydrothermal conditioning as well as NDF and DM concentration in the silage. Results showed a relative reduction of ash and all elements detrimental for combustion in the PC compared to the untreated biomass of 20-90%. Reduction was highest for K and Cl and lowest for N. HHV of PC and untreated biomass were in a comparable range (17.8-19.5 MJ kg-1 DM), but AST of PC was higher (1156-1254°C). Methane yields of PF were higher compared to those of WCD when the biomass was harvested late (end of May and later) and in a comparable range when the biomass was harvested early and ranged from 332 to 458 LN kg-1 VS. Regarding energy and GHG balances, IFBB, with a net energy yield of 11.9-14.1 MWh ha-1, a conversion efficiency of 0.43-0.51, and GHG mitigation of 3.6-4.4 t CO2eq ha-1, performed better than WCD, but worse than CH. WCD produces thermal and electric energy with low efficiency, CH produces only thermal energy with a low quality solid fuel with high efficiency, IFBB produces thermal and electric energy with a solid fuel of high quality with medium efficiency. Regression models were able to predict target parameters with high accuracy (R2=0.70-0.99). The influence of increasing temperature of hydrothermal conditioning was an increase of mass flows, a decrease of element concentrations in the PC and a differing effect on energy conversion efficiency. The influence of increasing NDF concentration of the silage was a differing effect on mass flows, a decrease of element concentrations in the PC and an increase of energy conversion efficiency. The influence of increasing DM concentration of the silage was a decrease of mass flows, an increase of element concentrations in the PC and an increase of energy conversion efficiency. Based on the models an optimised IFBB process would be obtained with a medium temperature of hydrothermal conditioning (50°C), high NDF concentrations in the silage and medium DM concentrations of the silage.

Apparent digestibility and nitrogen utilization of diets based on maize silage harvested at three stages of maturity and fed to steers

Advancing maize crop maturity is associated with changes in ear-to-stover ratio which may have consequences for the digestibility of the ensiled crop. The apparent digestibility and nitrogen retention of three diets (Early, Mid and Late) containing maize silages made from maize of advancing harvest date [dry matter (DM) contents of the maize silages were 273, 314 and 367 g kg(-1) for the silages in the Early, Mid and Late diets respectively], together with a protein supplement offered in sufficient quantities to make the diets isonitrogenous, were measured in six Holstein-Friesian steers in an incomplete Latin square design with four periods. Dry-matter intake of maize silage tended to be least for the Early diet and greatest for the Medium diet (P=0(.)182). Apparent digestibility of DM and organic matter did not differ between diets. Apparent digestibility of energy was lowest in the Late diet (P = 0(.)057) and the metabolizable energy concentrations of the three silages were calculated as 11(.)0, 11(.)1 and 10(.)6 MJ kg(-1) DM for the Early, Medium and Late diets respectively (P = 0(.)068). No differences were detected between diets in starch digestibility but the number of undamaged grains present in the faeces of animals fed the Late diet was significantly higher than with the Early and Mid diets (P = 0(.)006). The apparent digestibility of neutral-detergent fibre of the diets reduced significantly as silage DM content increased (P = 0(.)012) with a similar trend for the apparent digestibility of acid-detergent fibre (P = 0(.)078). Apparent digestibility of nitrogen (N) was similar for the Early and Mid diets, both being greater than the Late diet (P = 0(.)035). Nitrogen retention did not differ between diets. It was concluded that delaying harvest until the DM content is above 300 g kg(-1) can negatively affect the nutritive value of maize silage in the UK.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (k(l)), 3) growth (k(g)), and the efficiency of utilization of body stores for milk production (k(t)). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate k(g) and k(t). Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for k(g) and k(t) using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for k(g) and 0.82 to 0.84 for k(t). Using the estimated values of k(g) and k(t), the data were corrected to allow for body tissue changes. Based on the definition of k(l) as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and k(l) were determined. Meta-analysis of the pooled data showed that the average k(l) ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.

Energy and protein interactions and their effect on nitrogen excretion in dairy cows

The principal driver of nitrogen (N) losses from the body including excretion and secretion in milk is N intake. However, other covariates may also play a role in modifying the partitioning of N. This study tests the hypothesis that N partitioning in dairy cows is affected by energy and protein interactions. A database containing 470 dairy cow observations was collated from calorimetry experiments. The data include N and energy parameters of the diet and N utilization by the animal. Univariate and multivariate meta-analyses that considered both within and between study effects were conducted to generate prediction equations based on N intake alone or with an energy component. The univariate models showed that there was a strong positive linear relationships between N intake and N excretion in faeces, urine and milk. The slopes were 0.28 faeces N, 0.38 urine N and 0.20 milk N. Multivariate model analysis did not improve the fit. Metabolizable energy intake had a significant positive effect on the amount of milk N in proportion to faeces and urine N, which is also supported by other studies. Another measure of energy considered as a covariate to N intake was diet quality or metabolizability (the concentration of metabolizable energy relative to gross energy of the diet). Diet quality also had a positive linear relationship with the proportion of milk N relative to N excreted in faeces and urine. Metabolizability had the largest effect on faeces N due to lower protein digestibility of low quality diets. Urine N was also affected by diet quality and the magnitude of the effect was higher than for milk N. This research shows that including a measure of diet quality as a covariate with N intake in a model of N execration can enhance our understanding of the effects of diet composition on N losses from dairy cows. The new prediction equations developed in this study could be used to monitor N losses from dairy systems.

Methodology To model the energy and greenhouse gas emissions of electronic software distributions

A new electronic software distribution (ESD) life cycle analysis (LCA)methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative,physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO2e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO2e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.

Prediction of nutrient digestibility and energy concentrations in fresh grass using nutrient composition

Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.

Evaluating nitrogen utilization efficiency of nonpregnant dry cows offered solely fresh cut grass at maintenance levels

The present study aimed to identify key parameters influencing N utilization and develop prediction equations for manure N output (MN), feces N output (FN), and urine N output (UN). Data were obtained under a series of digestibility trials with nonpregnant dry cows fed fresh grass at maintenance level. Grass was cut from 8 different ryegrass swards measured from early to late maturity in 2007 and 2008 (2 primary growth, 3 first regrowth, and 3 second regrowth) and from 2 primary growth early maturity swards in 2009. Each grass was offered to a group of 4 cows and 2 groups were used in each of the 8 swards in 2007 and 2008 for daily measurements over 6 wk; the first group (first 3 wk) and the second group (last 3 wk) assessed early and late maturity grass, respectively. Average values of continuous 3-d data of N intake (NI) and output for individual cows ( = 464) and grass nutrient contents ( = 116) were used in the statistical analysis. Grass N content was positively related to GE and ME contents but negatively related to grass water-soluble carbohydrates (WSC), NDF, and ADF contents ( < 0.01), indicating that accounting for nutrient interrelations is a crucial aspect of N mitigation. Significantly greater ratios of UN:FN, UN:MN, and UN:NI were found with increased grass WSC contents and ratios of N:WSC, N:digestible OM in total DM (DOMD), and N:ME ( < 0.01). Greater NI, animal BW, and grass N contents and lower grass WSC, NDF, ADF, DOMD, and ME concentrations were significantly associated with greater MN, FN, and UN ( < 0.05). The present study highlighted that using grass lower in N and greater in fermentable energy in animals fed solely fresh grass at maintenance level can improve N utilization, reduce N outputs, and shift part of N excretion toward feces rather than urine. These outcomes are highly desirable in mitigation strategies to reduce nitrous oxide emissions from livestock. Equations predicting N output from BW and grass N content explained a similar amount of variability as using NI and grass chemical composition (excluding DOMD and ME), implying that parameters easily measurable in practice could be used for estimating N outputs. In a research environment, where grass DOMD and ME are likely to be available, their use to predict N outputs is highly recommended because they strongly improved of the equations in the current study.

Amylase utilization for the extrusion of dog diets

Effects of amylase addition on extruder parameters, cost of extrusion, kibble quality and digestibility of dog food were measured in two separate experiments. In experiment 1, 120 kilo-novo-alpha-amilase-unit (KNU)/kg of heat stable alpha-amylase produced by Bacillus licheniformis was added in liquid form during a preconditioning period. In experiment 23684 KNU/kg of heat stable alpha-amylase produced by Aspergillus oryzae was mixed with the ingredients before extrusion. The diets were processed in a single screw extruder and submitted to digestibility and on experiment 1 also to palatability tests. Digestibility was tested using 12 dogs, six per diet. Data were submitted to analysis of variance followed by F-test. Amylase addition altered extrusion parameters in both experiments (P<0.05), with higher output (kg of dry matter [DM]/h: 28% and 43% higher in experiments 1 and 2) and less electric energy consumption (kW to produce 100 kg DM: 22% and 29% lower in experiments 1 and 2). Kibble appearance and quality [density (g/L), cutting force (g), and starch gelatinization degree (%)] did not change with enzyme treatment (P>0.05). Likewise, enzyme addition did not change nutrient digestibility, fecal dry matter or food palatability (P<0.05). Taken together our results suggest that amylase promoted the breakdown of amylose chains, thereby reducing the dough viscosity and resistance inside the extruder which allowed for higher product flow and less electricity energy consumption without altering food quality. (C) 2012 Elsevier B.V. All rights reserved.

Influence of chromium supplementation on energy metabolism in horses used in policing activity

O presente trabalho avaliou a influência da suplementação com cromo em algumas variáveis sanguíneas em 11 equinos machos, adultos, usados em atividade de policiamento. Cada animal recebeu 11mg de cromo/400kg de peso corpóreo, via oral, durante 30 dias. Nos dias 0 (antes) e 30 (após), os animais foram avaliados e amostras de sangue foram obtidas antes e após o exercício. Glicose e lactato plasmáticos e cortisol e insulina séricas foram determinados. No dia 0, as concentrações de glicose plasmática foram 68,4±5,6mg/dL e 78,7±6,5mg/dL; de lactato plasmático, 6,2±0,6mg/dL e 13,1±7,6mg/dL; de cortisol sérico, 48,5±7,9ng/mL e 42,6±19,7ng/mL; e de insulina sérica, 3,0±6,4µUI/m L e 1,9±1,7µUI/mL, respectivamente, antes e após o exercício. No dia 30, as concentrações de glicose plasmática foram 73,3±5,7mg/dL e 78,4±6,7mg/dL; de lactato plasmático, 7,3±0,9mg/dL e 7,6±1,2mg/dL; de cortisol sérico, 62,9±21,8ng/mL e 40,3±17,0ng/mL; e de insulina sérica, 1,4±1,3µUI/mL e 1,7±1,4µUI/mL, respectivamente, antes e após o exercício. Como efeito do exercício, foi demonstrado redução na concentração sérica de insulina e aumento no lactato e glicose plasmáticas. A suplementação com cromo resulto u em redução dos valores de lactato após a atividade física, possivelmente indicando que o cromo contribuiu para a melhor utilização da glicose plasmática e melhor adaptação ao exercício físico realizado.