Resting energy expenditure in non-ventilated, non-sedated patients recovering from serious traumatic brain injury: Comparison of prediction equations with indirect calorimetry values

Background & aims: Little is known about energy requirements in brain injured (TBI) patients, despite evidence suggesting adequate nutritional support can improve clinical outcomes. The study aim was to compare predicted energy requirements with measured resting energy expenditure (REE) values, in patients recovering from TBI.

Methods: Indirect calorimetry (IC) was used to measure REE in 45 patients with TBI. Predicted energy requirements were determined using FAO/WHO/UNU and Harris–Benedict (HB) equations. Bland– Altman and regression analysis were used for analysis.

Results: One-hundred and sixty-seven successful measurements were recorded in patients with TBI. At an individual level, both equations predicted REE poorly. The mean of the differences of standardised areas of measured REE and FAO/WHO/UNU was near zero (9 kcal) but the variation in both directions was substantial (range 591 to þ573 kcal). Similarly, the differences of areas of measured REE and HB demonstrated a mean of 1.9 kcal and range 568 to þ571 kcal. Glasgow coma score, patient status, weight and body temperature were signi?cant predictors of measured REE (p < 0.001; R²⁼ 0.47).

Conclusions: Clinical equations are poor predictors of measured REE in patients with TBI. The variability in REE is substantial. Clinicians should be aware of the limitations of prediction equations when estimating energy requirements in TBI patients.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Macronutrients and energy balance in obesity.

Energy balance is the difference between metabolizable energy intake and total energy expenditure. Energy intake is difficult to measure accurately; changes in body weight, for example, are not a good measure of the adequacy of energy intake, because fluctuations in body weight are common even if the overall trend is toward weight loss. It is now customary to assess energy requirements indirectly from total energy expenditure. Total energy expenditure consists of basal metabolism, postprandial thermogenesis, and physical activity. Energy expenditure is related to both body weight and body composition. A reduction in total energy expenditure accompanies weight loss, because basal metabolic rate decreases with the loss of lean tissue mass. Similarly, with weight gain, there is an increase in basal metabolic rate, because lean tissue mass grows to support the increase in fat tissue mass. Excess energy intake over energy expenditure causes weight gain and an accompanying increase in total energy expenditure. Following a period of adaptation, total energy expenditure will match energy intake and body weight will stabilize at a higher level. This same relationship holds for weight loss. Respiratory quotient (measured in steady state) is an indication of the proportion of energy expenditure derived from fat and carbohydrate oxidation. Over long periods of time, fat balance is equivalent to energy balance, as an excess of fat intake over fat oxidation causes fat storage.

Energy Aware Cluster-based Multihop Routing Protocol for Sensor Networks

Clustering combined with multihop communication is a promising solution to cope with the energy requirements of large scale Wireless Sensor Networks. In this work, a new cluster based routing protocol referred to as Energy Aware Cluster-based Multihop (EACM) Routing Protocol is introduced, with multihop communication between cluster heads for transmitting messages to the base station and direct communication within clusters. We propose EACM with both static and dynamic clustering. The network is partitioned into near optimal load balanced clusters by using a voting technique, which ensures that the suitability of a node to become a cluster head is determined by all its neighbors. Results show that the new protocol performs better than LEACH on network lifetime and energy dissipation

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.

Wild bird feeding in a large UK urban area: characteristics and estimates of energy input and individuals supported

Wild bird feeding is popular in domestic gardens across the world. Nevertheless, there is surprisingly little empirical information on certain aspects of the activity and no year-round quantitative records of the amounts and nature of the different foods provided in individual gardens. We sought to characterise garden bird feeding in a large UK urban area in two ways. First, we conducted face-to-face questionnaires with a representative cross-section of residents. Just over half fed birds, the majority doing so year round and at least weekly. Second, a two-year study recorded all foodstuffs put out by households on every provisioning occasion. A median of 628 kcal/garden/day was given. Provisioning level was not significantly influenced by weather or season. Comparisons between the data sets revealed significantly less frequent feeding amongst these ‘keen’ feeders than the face-to-face questionnaire respondents, suggesting that one-off questionnaires may overestimate provisioning frequency. Assuming 100% uptake, the median provisioning level equates to sufficient supplementary resources across the UK to support 196 million individuals of a hypothetical average garden-feeding bird species (based on 10 common UK garden-feeding birds’ energy requirements). Taking the lowest provisioning level recorded (101 kcal/day) as a conservative measure, 31 million of these average individuals could theoretically be supported.

Use of L-Proline and ATP Production by Trypanosoma cruzi Metacyclic Forms as Requirements for Host Cell Invasion

The process of host cell invasion by Trypanosoma cruzi depends on parasite energy. What source of energy is used for that event is not known. To address this and other questions related to T. cruzi energy requirements and cell invasion, we analyzed metacyclic trypomastigote forms of the phylogenetically distant CL and G strains. For both strains, the nutritional stress experienced by cells starved for 24, 36, or 48 h in phosphate-buffered saline reduced the ATP content and the ability of the parasite to invade HeLa cells proportionally to the starvation time. Inhibition of ATP production by treating parasites with rotenone plus antimycin A also diminished the infectivity. Nutrient depletion did not alter the expression of gp82, the surface molecule that mediates CL strain internalization, but increased the expression of gp90, the negative regulator of cell invasion, in the G strain. When L-proline was given to metacyclic forms starved for 36 h, the ATP levels were restored to those of nonstarved controls for both strains. Glucose had no such effect, although this carbohydrate and L-proline were transported in similar fashions. Recovery of infectivity promoted by L-proline treatment of starved parasites was restricted to the CL strain. The profile of restoration of ATP content and gp82-mediated invasion capacity by L-proline treatment of starved Y-strain parasites was similar to that of the CL strain, whereas the Dm28 and Dm30 strains, whose infectivity is downregulated by gp90, behaved like the G strain. L-Proline was also found to increase the ability of the CL strain to traverse a gastric mucin layer, a property important for the establishment of T. cruzi infection by the oral route. Efficient translocation of parasites through gastric mucin toward the target epithelial cells in the stomach mucosa is an essential requirement for subsequent cell invasion. By relying on these closely associated ATP-driven processes, the metacyclic trypomastigotes effectively accomplish their internalization.

Modelling energy utilisation in broiler breeder hens

1. The objective of this study was to determine a metabolisable energy ( ME) requirement model for broiler breeder hens. The influence of temperature on ME requirements for maintenance was determined in experiments conducted in three environmental rooms with temperatures kept constant at 13, 21 and 30 degrees C using a comparative slaughter technique. The energy requirements for weight gain were determined based upon body energy content and efficiency of energy utilisation for weight gain. The energy requirements for egg production were determined on the basis of egg energy content and efficiency of energy deposition in the eggs.2. The following model was developed using these results: ME = kgW(0.75)(806.53 - 26.45T + 0.50T(2)) + 31.90G + 10.04EM, where kgW(0.75) is body weight (kg) raised to the power 0.75, T is temperature (degrees C), G is weight gain (g) and EM is egg mass (g).3. A feeding trial was conducted using 400 Hubbard Hi-Yield broiler breeder hens and 40 Peterson males from 31 to 46 weeks of age in order to compare use of the model with a recommended feeding programme for this strain of bird. The application of the model in breeder hens provided good productive and reproductive performance and better results in feed and energy conversion than in hens fed according to strain recommendation. In conclusion, the model evaluated predicted an ME intake which matched breeder hens' requirements.

Modeling energy utilization in broiler breeders, laying hens and broilers

The factorial approach has been used to partition the energy requirements into maintenance, growth, and production. The coefficients determined for these purposes can be used to elaborate energy requirement models. These models consider the body weight, weight gain, egg production, and environmental temperature to determine the energy requirements for poultry. Predicting daily energy requirement models can help to establish better and more profitable feeding programs for poultry. Studies were conducted at UNESP-Jaboticabal to determine metabolizable energy (ME) requirement models for broiler breeders, laying hens, and broilers. These models were evaluated in performance trials and provided good adjustments. Therefore, they could be used to establish nutritional programs. This review aims to outline the results found at UNESP studies and to show the application of models in nutritional programs for broiler breeders, laying hens, and broilers.

Modelling energy utilization for laying type Pullets

Three trials were carried out to determine energy metabolized (EM) requirement model for starting and growing pullets from different strains, at five ambient temperatures and different percentage feather coverage. In Trial I, metabolizable energy requirements for maintenance (MEm) and efficiency of energy utilization were estimated using 64 birds of two different strains, Hy-Line W36 (HLW36) and Hy-Line Semi-heavy (HLSH), from 9 to 13 weeks of age. The effects of ambient temperature (12, 18, 24, 30 and 36ºC) and percentage feather coverage (0, 50 and 100%) on MEm were assessed in the second trial, using 48 birds per temperature per strain (HLSH and HLW36) from 9 to 13 weeks of age. Trial III evaluated ME requirements for weight gain (MEg) using 1,200 birds from two light strains (HLW36 and Hisex Light, HL) and two semi-heavy strains (HLSH and Hisex Semi-heavy, HSH) reared until 18 weeks of age. According to the prediction models, MEm changed as a function of temperature and feather coverage, whereas MEg changed as a function of age and bird strain. Thus, two models were developed for birds aged 1 to 6 weeks, one model for the light strain and one for the semi-heavy strain. Energy requirements (ER) were different among strains from 7 to 12 weeks, and therefore 4 models were elaborated. From 13 to 18 weeks, one single model was produced for semi-heavy birds, since ER between semi-heavy strains were not different, whereas two different models were elaborated for the light layers. MEg of light birds was higher than MEg of semi-heavy birds, independent of age.

Modeling metabolizable energy utilization in broiler breeder pullets

The objective of this study was to determine models for ME requirements for broiler breeder pullets using the factorial method. The influence of the temperature on maintenance ME requirements was determined by experiments conducted in three environmental rooms with temperature kept constant at 15, 22, and 30°C, using the comparative slaughter technique. The energy requirements for weight gain were determined based on the body energy content and efficiency of energy utilization for weight gain. Two ME requirement models for each age were developed using the coefficients for maintenance and weight gain. The models for 3 to 8 wk were ME = W 0.75 (186.52 - 1.94T) + 2.47WG, and ME = W 0.75 (174 - 1.88T) + 2.83WG; for 9 to 14 wk, ME = W 0.75 (186.52 - 1.94T) + 2.69WG, and ME = W 0.75 (174 - 1.88T) + 2.50WG; and 15 to 20 wk, ME = W 0.75 (186.52 - 1.94T) + 2.76WG, and ME = W 0.75 (174 - 1.88T) + 3.24WG. In these equations, W is BW (kg), T is temperature (°C), and WG is daily weight gain (g). These models were compared to the breeder's recommendations in a feeding trial from 5 to 20 wk of age. Models 1 and 2 provided energy intakes that promoted BW smaller than the breeder's recommendation. However, all breeder pullets had weights above the standard recommendation. Model 2 gave the smallest ME intake and BW close to the standard recommendation and provided the best prediction of ME requirements.

Modeling energy utilization and growth parameter description for broiler chickens

Two experiments were conducted to develop and evaluate a model to estimate ME requirements and determine Gompertz growth parameters for broilers. The first experiment was conducted to determine maintenance energy requirements and the efficiencies of energy utilization for fat and protein deposition. Maintenance ME (ME m) requirements were estimated to be 157.8, 112.1, and 127.2 kcal of ME/kg 0.75 per day for broilers at 13, 23, and 32°C, respectively. Environmental temperature (T) had a quadratic effect on maintenance requirements (ME m = 307.87 - 15.63T + 0.3105T 2; r 2= 0.93). Energy requirements for fat and protein deposition were estimated to be 13.52 and 12.59 kcal of ME/g, respectively. Based on these coefficients, a model was developed to calculate daily ME requirements: ME = BW 0.75 (307.87 - 15.63T + 0.3105 T 2) + 13.52 G f + 12.59 G p. This model considers live BW, the effects of environmental temperature, and fractional fat (G f) and protein (G p) deposition. The second experiment was carried out to estimate the growth parameters of Ross broilers and to collect data to evaluate the ME requirement model proposed. Live BW, empty feather-free carcass, weight of the feathers, and carcass chemical compositions were analyzed until 16 wk of age. Parameters of Gompertz curves for each component were estimated. Males had higher growth potential and higher capacity to deposit nutrients than females, except for fat deposition. Data of BW and body composition collected in this experiment were fitted into the energy model proposed herein and the equations described by Emmans (1989) and Chwalibog (1991). The daily ME requirements estimated by the model determined in this study were closer to the ME intake observed in this trial compared with other models. ©2005 Poultry Science Association, Inc.

Modelling energy utilization in poultry

Models of daily energy requirement can help to establish better and more profitable feeding programs for poultry. Studies have been conducted at UNESP-Jaboticabal-Brazil with the aim of studying energy utilization in broiler breeders, laying hens, and broilers, and to establish metabolisable energy requirement models. The factorial approach was used to partition the energy requirements into maintenance, growth, and production components. The resulting models consider body weight, weight gain, egg production, and environmental temperature for the determination of the energy requirements of poultry. These models were evaluated in performance trials and provided good estimates. Therefore, they can be used to establish nutritional programs. The aim of this chapter is to describe the development of these models and to outline the results of our studies at UNESP.

Energy balance for ethyl alcohol production from crops

Energy requirements to produce ethyl alcohol from three different crops in Brazil (sugarcane, cassava, and sweet sorghum) were calculated. Figures are presented for the agricultural and industrial phases. The industrial phase is always more energy-intensive, consuming from 60 to 75 percent of the total energy. Sugarcane is the more efficient crop for ethyl alcohol production, followed by sweet sorghum and cassava from a net energy viewpoint. The utilization of sweet sorghum stems might increase the total energy gain from this crop to almost the same level as sugarcane. Cassava has a lower energy gain at the present state of agriculture in Brazil. Copyright © 1978 AAAS.