Auditory and visual prompts during cardiopulmonary resuscitation in the emergency department.
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Audiovisual Aids↗
Biomedical subjects
J France
Publications and source records attributed to J France.
A revised model for studying phosphorus and calcium kinetics in growing sheep.
The objective of the study was to revise a model of P kinetics proposed by Vitti et al. (2000) and extend its use to study Ca flows in growing sheep. Twelve Santa Ines male sheep, 8 mo of age, with average BW of 31.6 kg were injected with 32P and 45Ca to trace the movement of P and Ca in the body. The original model had 4 pools representing the gut, plasma, soft tissues, and bone. In the revised model, instantaneous values rather than averages for pool derivatives were incorporated, and the model was extended to represent absorption and excretion of phytate P explicitly. The amendments improved the model, resulting in higher flows between plasma and bone than between plasma and tissue and, therefore, a more accurate representation of P metabolism. Phosphorus and Ca metabolism were then assessed conjointly using the revised model. The results showed that P and Ca metabolism are closely related as evidenced by the ratio of these minerals in the bidirectional flows between plasma and bone and between plasma and tissue. Phytate P digestibility was 47%, and P retention was negative (-1.4 g/d), suggesting that a feed characteristic impaired P utilization and led to P deficiency. The revised model provides an improved prediction of P and Ca metabolism that can be used to assess mineral requirements and to estimate losses to the environment.
Animal Feed↗
Modeling small-scale dairy farms in central Mexico using multi-criteria programming.
Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multi-criteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, ryegrass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.
Animal Feed↗
Evaluation of models to describe ruminal degradation kinetics from in situ ruminal incubation of whole soybeans.
Different mathematical models were evaluated as candidates to describe ruminal dry matter (DM) and crude protein (CP) degradation kinetics of raw and roasted whole soybeans from data obtained using the in situ polyester bag technique. Three models were used: segmented with up to 3 straight lines (model I), negative exponential (model II), and rational function or inverse polynomial (linear over linear; model III). A fourth, a generalized sigmoidal model, was also considered but the data did not exhibit sigmoidicity, so it was dropped from the analysis. Lagged and nonlagged versions of each model were fitted to the DM and CP disappearance curves of 6 different feeds (2 cultivars of raw or differently heat-processed whole soybean). The comparison between lagged and nonlagged versions of each model, based on statistical and behavior characteristics, showed for all models that the discrete lag parameter did not significantly improve the fit to ruminal DM and CP disappearance curves. The comparison between models (using nonlagged equations) showed that models I and II gave better goodness-of-fit than model III. Based on biological characteristics, models II and III underestimated the undegradable DM and CP fractions, but there was no significant difference between models for extent of degradation.
Animal Feed↗
Estimation of the stoichiometry of volatile fatty acid production in the rumen of lactating cows.
The purpose of this study was to improve the prediction of the quantity and type of Volatile Fatty Acids (VFA) produced from fermented substrate in the rumen of lactating cows. A model was formulated that describes the conversion of substrate (soluble carbohydrates, starch, hemi-cellulose, cellulose, and protein) into VFA (acetate, propionate, butyrate, and other VFA). Inputs to the model were observed rates of true rumen digestion of substrates, whereas outputs were observed molar proportions of VFA in rumen fluid. A literature survey generated data of 182 diets (96 roughage and 86 concentrate diets). Coefficient values that define the conversion of a specific substrate into VFA were estimated meta-analytically by regression of the model against observed VFA molar proportions using non-linear regression techniques. Coefficient estimates significantly differed for acetate and propionate production in particular, between different types of substrate and between roughage and concentrate diets. Deviations of fitted from observed VFA molar proportions could be attributed to random error for 100%. In addition to regression against observed data, simulation studies were performed to investigate the potential of the estimation method. Fitted coefficient estimates from simulated data sets appeared accurate, as well as fitted rates of VFA production, although the model accounted for only a small fraction (maximally 45%) of the variation in VFA molar proportions. The simulation results showed that the latter result was merely a consequence of the statistical analysis chosen and should not be interpreted as an indication of inaccuracy of coefficient estimates. Deviations between fitted and observed values corresponded to those obtained in simulations.
Acetates↗
Effects of phosphorus intake on phosphorus flow in growing pigs: application and comparison of two models.
A comparison of the models of Vitti et al. (2000, J. Anim. Sci. 78, 2706-2712) and Fernández (1995c, Livest. Prod. Sci. 41, 255-261) was carried out using two data sets on growing pigs as input. The two models compared were based on similar basic principles, although their aims and calculations differed. The Vitti model employs the rate:state formalism and describes phosphorus (P) flow between four pools representing P content in gut, blood, bone and soft tissue in growing goats. The Fernández model describes flow and fractional recirculation between P pools in gut, blood and bone in growing pigs. The results from both models showed similar trends for P absorption from gut to blood and net retention in bone with increasing P intake, with the exception of the 65 kg results from Date Set 2 calculated using the Fernández model. Endogenous loss from blood back to gut increased faster with increasing P intake in the Fernández than in the Vitti model for Data Set 1. However, for Data Set 2, endogenous loss increased with increasing P intake using the Vitti model, but decreased when calculated using the Fernández model. Incorporation of P into bone was not influenced by intake in the Fernández model, while in the Vitti model there was an increasing trend. The Fernández model produced a pattern of decreasing resorption in bone with increasing P intake, with one of the data sets, which was not observed when using the Vitti model. The pigs maintained their P homeostasis in blood by regulation of P excretion in urine.
Animal Feed↗
Statistical evaluation of mathematical models for microbial growth.
The aim of this study was to evaluate the suitability of several mathematical functions for describing microbial growth curves. The nonlinear functions used were: three-phase linear, logistic, Gompertz, Von Bertalanffy, Richards, Morgan, Weibull, France and Baranyi. Two data sets were used, one comprising 21 growth curves of different bacterial and fungal species in which growth was expressed as optical density units, and one comprising 34 curves of colony forming units counted on plates of Yersinia enterocolitica grown under different conditions of pH, temperature and CO(2) (time-constant conditions for each culture). For both sets, curves were selected to provide a wide variety of shapes with different growth rates and lag times. Statistical criteria used to evaluate model performance were analysis of residuals (residual distribution, bias factor and serial correlation) and goodness-of-fit (residual mean square, accuracy factor, extra residual variance F-test, and Akaike's information criterion). The models showing the best overall performance were the Baranyi, three-phase linear, Richards and Weibull models. The goodness-of-fit attained with other models can be considered acceptable, but not as good as that reached with the best four models. Overall, the Baranyi model showed the best behaviour for the growth curves studied according to a variety of criteria. The Richards model was the best-fitting optical density data, whereas the three-phase linear showed some limitations when fitting these curves, despite its consistent performance when fitting plate counts. Our results indicate that the common use of the Gompertz model to describe microbial growth should be reconsidered critically, as the Baranyi, three-phase linear, Richards and Weibull models showed a significantly superior ability to fit experimental data than the extensively used Gompertz.
Bacteria↗
An integrative model of amino acid metabolism in the liver of the lactating dairy cow.
The objective of this work was to construct a dynamic model of hepatic amino acid metabolism in the lactating dairy cow that could be parameterized using net flow data from in vivo experiments. The model considers 22 amino acids, ammonia, urea, and 13 energetic metabolites, and was parameterized using a steady-state balance model and two in vivo, net flow experiments conducted with mid-lactation dairy cows. Extracellular flows were derived directly from the observed data. An optimization routine was used to derive nine intracellular flows. The resulting dynamic model was found to be stable across a range of inputs suggesting that it can be perturbed and applied to other physiological states. Although nitrogen was generally in balance, leucine was in slight deficit compared to predicted needs for export protein synthesis, suggesting that an alternative source of leucine (e.g. peptides) was utilized. Simulations of varying glucagon concentrations indicated that an additional 5 mol/d of glucose could be synthesized at the reference substrate concentrations and blood flows. The increased glucose production was supported by increased removal from blood of lactate, glutamate, aspartate, alanine, asparagine, and glutamine. As glucose output increased, ketone body and acetate release increased while CO(2) release declined. The pattern of amino acids appearing in hepatic vein blood was affected by changes in amino acid concentration in portal vein blood, portal blood flow rate and glucagon concentration, with methionine and phenylalanine being the most affected of essential amino acids. Experimental evidence is insufficient to determine whether essential amino acids are affected by varying gluconeogenic demands.
Amino Acids↗
Technical note: A proposed method to determine the extent of degradation of a feed in the rumen from the degradation profile obtained with the in vitro gas production technique using feces as the inoculum.
A method is proposed to determine the extent of degradation in the rumen involving a two-stage mathematical modeling process. In the first stage, a statistical model shifts (or maps) the gas accumulation profile obtained using a fecal inoculum to a ruminal gas profile. Then, a kinetic model determines the extent of degradation in the rumen from the shifted profile. The kinetic model is presented as a generalized mathematical function, allowing any one of a number of alternative equation forms to be selected. This method might allow the gas production technique to become an approach for determining extent of degradation in the rumen, decreasing the need for surgically modified animals while still maintaining the link with the animal. Further research is needed before the proposed methodology can be used as a standard method across a range of feeds.
Animals↗
Study of the lactation curve in dairy cattle on farms in central Mexico.
Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines (exponential decay), Wood (gamma equation), Rook (Michaelis-Menten xexponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.
Animals↗
An evaluation of different growth functions for describing the profile of live weight with time (age) in meat and egg strains of chicken.
A total of 86 profiles from meat and egg strains of chickens (male and female) were used in this study. Different flexible growth functions were evaluated with regard to their ability to describe the relationship between live weight and age and were compared with the Gompertz and logistic equations, which have a fixed point of inflection. Six growth functions were used: Gompertz, logistic, Lopez, Richards, France, and von Bertalanffy. A comparative analysis was carried out based on model behavior and statistical performance. The results of this study confirmed the initial concern about the limitation of a fixed point of inflection, such as in the Gompertz equation. Therefore, consideration of flexible growth functions as an alternatives to the simpler equations (with a fixed point of inflection) for describing the relationship between live weight and age are recommended for the following reasons: they are easy to fit, they very often give a closer fit to data points because of their flexibility and therefore a smaller RSS value, than the simpler models, and they encompasses simpler models for the addition of an extra parameter, which is especially important when the behavior of a particular data set is not defined previously.
Aging↗
Effects of volatile fatty acid supply on their absorption and on water kinetics in the rumen of sheep sustained by intragastric infusions.
Three sheep fitted with a ruminal cannula and an abomasal catheter were used to study water kinetics and absorption of VFA infused continuously into the rumen. The effects of changing VFA concentrations in the rumen by shifting VFA infusion rates were investigated in an experiment with a 3 x 3 Latin square design. On experimental days, the animals received the basal infusion rate of VFA (271 mmol/h) during the first 2 h. Each animal then received VFA at a different rate (135, 394, or 511 mmol/h) for the next 7.5 h. Using soluble markers (polyethylene glycol and Cr-EDTA), ruminal volume, liquid outflow, apparent water absorption, and VFA absorption rates were estimated. There were no significant effects of VFA infusion rate on ruminal volume and water kinetics. As the VFA infusion rate was increased, VFA concentration and osmolality in the rumen were increased and pH was decreased. There was a biphasic response of liquid outflow to changes in the total VFA concentration in the rumen, as both variables increased together up to a total VFA concentration of 80.1 mM, whereas, beyond that concentration, liquid outflow remained stable at an average rate of 407 mL/h. There were significant linear (P = 0.003) and quadratic (P = 0.001) effects of VFA infusion rate on the VFA absorption rate, confirming that VFA absorption in the rumen is mainly a concentration-dependent process. The proportion of total VFA supplied that was absorbed in the rumen was 0.845 (0.822, 0.877, and 0.910 for acetate, propionate, and butyrate, respectively). The molar proportions of acetate, propionate, and butyrate absorbed were affected by the level of VFA infusion in the rumen, indicating that this level affected to a different extent the absorption of the different acids.
Animals↗
Alternative approaches to predicting methane emissions from dairy cows.
Previous attempts to apply statistical models, which correlate nutrient intake with methane production, have been of limited value where predictions are obtained for nutrient intakes and diet types outside those used in model construction. Dynamic mechanistic models have proved more suitable for extrapolation, but they remain computationally expensive and are not applied easily in practical situations. The first objective of this research focused on employing conventional techniques to generate statistical models of methane production appropriate to United Kingdom dairy systems. The second objective was to evaluate these models and a model published previously using both United Kingdom and North American data sets. Thirdly, nonlinear models were considered as alternatives to the conventional linear regressions. The United Kingdom calorimetry data used to construct the linear models also were used to develop the three nonlinear alternatives that were all of modified Mitscherlich (monomolecular) form. Of the linear models tested, an equation from the literature proved most reliable across the full range of evaluation data (root mean square prediction error = 21.3%). However, the Mitscherlich models demonstrated the greatest degree of adaptability across diet types and intake level. The most successful model for simulating the independent data was a modified Mitscherlich equation with the steepness parameter set to represent dietary starch-to-ADF ratio (root mean square prediction error = 20.6%). However, when such data were unavailable, simpler Mitscherlich forms relating dry matter or metabolizable energy intake to methane production remained better alternatives relative to their linear counterparts.
Animal Feed↗
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 (kl), 3) growth (kg), and the efficiency of utilization of body stores for milk production (kt). 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 kg and kt. Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for kg and kt 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 kg and 0.82 to 0.84 for kt. Using the estimated values of kg and kt, the data were corrected to allow for body tissue changes. Based on the definition of kl as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and kl were determined. Meta-analysis of the pooled data showed that the average kl 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.
Animal Nutritional Physiological Phenomena↗
Rates of production of acetate, propionate, and butyrate in the rumen of lactating dairy cows given normal and low-roughage diets.
Five lactating dairy cows with a permanent cannula in the rumen were given (kg DM/d) a normal diet (7.8 concentrates, 5.1 hay) or a low-roughage (LR) diet (11.5 concentrates, 1.2 hay) in two meals daily in a two-period crossover design. Milk fat (g/kg) was severely reduced on diet LR. To measure rates of production of individual volatile fatty acids (VFA) in the rumen, 0.5 mCi 1-(14)C-acetic acid, 2-(14)C-propionic acid, or 1-(14)C-n-butyric acid were infused into the rumen for 22 h at intervals of 2 to 6 d; rumen samples were taken over the last 12 h. To measure rumen volume, we infused Cr-EDTA into the rumen continuously, and polyethylene glycol was injected 2 h before the morning feed. Results were very variable, so volumes measured by rumen emptying were used instead. Net production of propionic acid more than doubled on LR, but acetate and butyrate production was only numerically lower. Net production rates pooled across both diets were significantly related to concentrations for each VFA. Molar proportions of net production were only slightly higher than molar proportions of concentrations for acetate and propionate but were lower for butyrate. The net energy value (MJ/d) of production of the three VFA increased from 89.5 on normal to 109.1 on LR, equivalent to 55 and 64% of digestible energy, respectively. Fully interchanging, three-pool models of VFA C fluxes are presented. It is concluded that net production rates of VFA can be measured in non-steady states without the need to measure rumen volumes.
Acetates↗
Modelling mammary metabolism in the dairy cow to predict milk constituent yield, with emphasis on amino acid metabolism and milk protein production: model evaluation.
A model of mammary metabolism has been constructed and parameterized, with milk protein synthesis represented as a function of five essential amino acids (EAA) (Hanigan et al., 2001). Herein the model is evaluated using both the data used to construct the model (reference data) and an independent data set (literature data), and sensitivity to inputs and parameter estimates is assessed. The model predicted metabolite removal well for the reference data with exceptions for glutamate, glucose, and acetate. However, predictions of milk protein synthesis exhibited significant mean positive bias, which apparently was associated with the representation of milk protein synthesis. Adjustment of model parameters removed the mean bias, however, prediction accuracy was still inadequate. Simulation of the single reference experiment containing all critical inputs resulted in predictions of milk protein output that explained 53% of the observed variation, suggesting that the limited accuracy of the model when applied to the entire reference data set was due to assumptions regarding missing inputs. Mammary removal of glutamate, isoleucine, lysine, phenylalanine, tyrosine, valine, glycerol, beta -hydroxybutyrate (BHBA), and acetate were predicted less accurately when simulations of the independent data set were conducted. Twenty-five percent of the observed variation in milk protein yields for the independent data set was explained by the model. Refitting parameters for removal of isoleucine, lysine, phenylalanine, tyrosine, valine, glycerol, BHBA, and acetate raised the variation explained to 43%. Sensitivity analysis indicated that milk protein synthesis was responsive to only the five EAA used in its determination, with sensitivity to any single EAA falling to zero as supply of the EAA exceeded protein synthetic needs. Similarly, milk protein synthesis was readily affected by parameters associated with removal and metabolism of the five EAA. Milk lactose was found to be sensitive to glucose input as well as to similar parameters and inputs as milk protein. It is concluded that representation of the milk protein synthesis process as a function of a single limiting EAA may not be adequate and might be better represented by simultaneous consideration of multiple EAA. Additional work on the description of energy metabolism is also suggested.
Amino Acids↗
A dynamic model of N metabolism in the lactating dairy cow and an assessment of impact of N excretion on the environment.
Improving N utilization in dairy cows and especially reducing N output in excreta is desirable due to global concerns of agricultural contribution of N to environmental pollution, particularly as ammonia. Data from five N balance experiments were used to develop a dynamic model that was evaluated with independent data. Model predictions of feces, urine, and milk outputs were close to observed values. Statistical analysis showed that 96% of mean square prediction error for feces and urine N output predictions was due to random variation. However, the model tends to overpredict milk N output, especially at higher N intake levels. Evaluation of model predictions for independent experimental observations from Agricultural Development Advisory Service at Bridgets (U.K.) showed good agreement between predicted and observed urine N output (95% due to random variation). However, there was a slight underprediction for fecal N output (14% mean square prediction error due to bias) and overprediction of milk N output (22% of mean square prediction error due to bias). The model predictions of N outputs in excreta were sensitive to changes in energy concentration of the diet. Dietary protein degradability had only a small influence on predicted fecal N output. However, the model was sensitive in its predictions of urine N when protein degradability was varied. Application of the model to assess reduction in ammonia emissions from dairy cows showed that increasing the energy concentration could potentially reduce ammonia emissions by up to 25% per cow. Similarly, reducing CP concentration in the diet to about 16% could reduce ammonia production by 20% and lower degradability of CP to match microbial requirement by 19% per cow. The model is a first step toward a mechanistic approach of nutrient modeling, and it is a valuable method for predicting N excretions and estimating N emissions from dairy systems.
Ammonia↗
Modelling mammary metabolism in the dairy cow to predict milk constituent yield, with emphasis on amino acid metabolism and milk protein production: model construction.
Previous efforts to simulate mammary metabolism have focused on energy, mostly considering amino acids (AA) in aggregate. The main objective of this work was to build a model of mammary metabolism, based on data from arterio-venous difference studies, which considered AA in sufficient detail to predict yields of milk solids. The model contains 19 state variables and considers the removal of 37 metabolites from blood, including 22 AA. It is driven by blood flow and arterial concentrations, and outputs include milk protein, milk lactose, and three classes of milk fat (by chain length). The model was parameterized using a balance version of it and the mean observations from four arterio-venous difference experiments, with a limited number of assumptions, and evaluated against these experiments. In assembling the balance model, milk protein output was not predicted satisfactorily, as some essential AA were not present in quantities great enough to support the rates of milk protein synthesis observed experimentally. Tryptophan showed the greatest deficit, followed by tyrosine plus phenylalanine, methionine, and histidine. In addition, significant quantities of pyruvate were needed to synthesize serine, glycine, and alanine. The supply of alpha-ketoglutarate plus glutamate to synthesize proline and glutamine was provided in part by catabolism of arginine; the remainder was derived from catabolism of other AA and energetic substrates.
Algorithms↗