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Determining the nutritional requirements of lambs is necessary to formulate balanced rations and contribute to sustainable sheep production systems. However, limited information is available regarding the nutritional requirements of growing lambs in the Colombian highlands. Twenty-two Romney Marsh males were used. Initially, four lambs were slaughtered at 20 kg body weight (BW). The remaining 18 lambs were distributed into two groups, according to BW (light: 20 BW and heavy: 30 kg BW). Lambs were randomly allocated into one of three different nutritional schemes, according to voluntary intake (no restriction, and 25 and 50% restriction). All the animals received a totally mixed ration. When a voluntary-fed lamb gained 10 kg BW, the two other lambs restricted to 25 and 50% were slaughtered and dissected into components to determine protein and gross energy concentration. Energy and protein accumulation were analyzed through regression analysis. The net energy for maintenance was 82.3 kcal/kg BW0.75, while the energy efficiencies for maintenance and gain were 0.72 and 0.29, respectively. Crude protein for maintenance was 1.78 g/kg BW0.75, and the nitrogen efficiencies for maintenance and gain were 0.41 and 0.27, respectively. The maintenance requirement of energy was greater, while protein was similarly related to values reported in the literature; however, the efficiency of energy and protein use was lower in growing lambs. These results suggested that estimating energy and nitrogen requirements for growing lambs must be adjusted in Colombian highland conditions.

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Prader-Willi syndrome (PWS) is a rare disorder characterised by varying nutritional phases that occur throughout the lifespan, ranging from failure to thrive to hyperphagia. If uncontrolled, the imbalance between energy intake and expenditure results in obesity development and increased morbidity and mortality risk. Although measures of energy requirements for accurate nutrition assessment are vital, the evidence appears sparse and heterogeneous; hence, the aim of this review was to examine the available literature on energy expenditure predicted or measured using various methods in individuals with PWS. Studies were sought that presented methods and results on resting energy expenditure or basal metabolic rate. A narrative synthesis was completed to present the study characteristics and results. Methods of determining energy requirements included predictive equations and indirect calorimetry. Differences amongst ages, growth hormone therapy, fasting status, and measures in which results were presented were limitations to appropriately summarising and identifying trends in energy expenditure. Indirect calorimetry was identified as the most accurate method; however, it is not widely available in all settings. Further research is encouraged to support the development of valid and reliable predictive equations that will better inform and improve the efficiency of clinical practice in supporting people with PWS.

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The two existing clades of Galloanseres, orders Galliformes (landfowl) and Anseriformes (waterfowl), exhibit dramatically different evolutionary trends. Mitochondria serve as primary sites for energy production in organisms, and numerous studies have revealed their role in biological evolution and ecological adaptation. We assembled the complete mitogenome sequences of two species of the genus Aythya within Anseriformes: Aythya baeri and Aythya marila. A phylogenetic tree was constructed for 142 species within Galloanseres, and their divergence times were inferred. The divergence between Galliformes and Anseriformes occurred ~79.62 million years ago (Mya), followed by rapid evolution and diversification after the Middle Miocene (~13.82 Mya). The analysis of selective pressure indicated that the mitochondrial protein-coding genes (PCGs) of Galloanseres species have predominantly undergone purifying selection. The free-ratio model revealed that the evolutionary rates of COX1 and COX3 were lower than those of the other PCGs, whereas ND2 and ND6 had faster evolutionary rates. The CmC model also indicated that most PCGs in Anseriformes exhibited stronger selective constraints. Our study suggests that the distinct evolutionary trends and energy requirements of Galliformes and Anseriformes drive different evolutionary patterns in the mitogenome.

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Elucidating the underlying mechanisms behind variations of animal space and resource use is crucial to pinpoint relevant ecological phenomena. Organism's traits related to its energy requirements might be central in explaining behavioral variation, as the ultimate goal of a forager is to fulfill its energy requirements. However, it has remained poorly understood how energy requirements and behavioral patterns are functionally connected. Here we aimed to assess how body mass and standard metabolic rate (SMR) influence behavioral patterns in terms of cumulative space use and time spent in an experimental patchy environment, both within species and among individuals irrespective of species identity. We measured the behavioral patterns and SMR of two invertebrate species, that is, amphipod Gammarus insensibilis, and isopod Lekanesphaera monodi, individually across a range of body masses. We found that species of G. insensibilis have higher SMR level, in addition to cumulatively exploring a larger space than L. monodi. Cumulative space use scaled allometrically with body mass, and it scaled isometrically with SMR in both species. While time spent similarly in both species was characterized by negative body mass and SMR dependence, it was observed that L. monodi individuals tended to stay longer in resource patches compared to G. insensibilis individuals. Our results further showed that within species, body mass and metabolic rate explained a similar amount of variation in behavior modes. However, among individuals, regardless of species identity, SMR had stronger predictive power for behavioral modes compared to body mass. This suggests that SMR might offer a more generalized and holistic description of behavioral patterns that extend beyond species identity. Our study on the metabolic and body mass scaling of space and resource use behavior sheds light on higher-order ecological processes such as species' competitive coexistence along the spatial and trophic dimensions.

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BACKGROUND & AIMS: Track and field sprinters must obtain an optimal body composition to improve sprint performance. To successfully change body composition, it is important to evaluate the estimated energy requirements (EER) and fluctuations in total energy expenditure (TEE). However, methods to accurately evaluate the EER and TEE in sprinters have not been fully investigated. The aim of this study was to compare currently used methods with the doubly labeled water (DLW) method, which is currently the gold standard for evaluating EER and TEE. METHODS: Ten male collegiate sprinters participated in the study. We evaluated TEEDLW and compared it with the EER calculated using two equations used by the National Institute of Health and Nutrition (NIHN) and the Japan Institute of Sports Sciences (JISS). In addition, we evaluated the TEE from the activity record (AR) and triaxial accelerometer (ACC). RESULTS: TEEDLW (3172 ± 415 kcal/day) was not significantly different from EERNIHN (p = 0.076) or EERJISS (p = 0.967). In addition, there were no significant differences between TEEDLW and TEEAR (p = 0.218). However, two accelerometer-derived equations used to evaluate TEE were found to have underestimated (2783 ± 377 kcal/day, p < 0.001) and overestimated (3405 ± 369 kcal/day, p = 0.009) the TEE. CONCLUSION: Our results suggest that EERNIHN and EERJISS may be useful in evaluating the EER of collegiate male sprinters on a group basis, and AR may be more accurate than ACC in evaluating the TEE. These results may be helpful when considering nutritional support for male collegiate sprinters.

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In chronic spinal cord injury (SCI), individuals experience dietary inadequacies complicated by an understudied research area. Our objectives were to assess (1) the agreement between methods of estimating energy requirement (EER) and estimated energy intake (EEI) and (2) whether dietary protein intake met SCI-specific protein guidelines. Persons with chronic SCI (n = 43) completed 3-day food records to assess EEI and dietary protein intake. EER was determined with the Long and Institute of Medicine (IOM) methods and the SCI-specific Farkas method. Protein requirements were calculated as 0·8-1·0 g/kg of body weight (BW)/d. Reporting accuracy and bias were calculated and correlated to body composition. Compared with IOM and Long methods (P < 0·05), the SCI-specific method did not overestimate the EEI (P = 0·200). Reporting accuracy and bias were best for SCI-specific (98·9 %, -1·12 %) compared with Long (94·8 %, -5·24 %) and IOM (64·1 %, -35·4 %) methods. BW (r = -0·403), BMI (r = -0·323) and total fat mass (r = -0·346) correlated with the IOM reporting bias (all, P < 0·05). BW correlated with the SCI-specific and Long reporting bias (r = -0·313, P = 0·041). Seven (16 %) participants met BW-specific protein guidelines. The regression of dietary protein intake on BW demonstrated no association between the variables (ß = 0·067, P = 0·730). In contrast, for every 1 kg increase in BW, the delta between total and required protein intake decreased by 0·833 g (P = 0·0001). The SCI-specific method for EER had the best agreement with the EEI. Protein intake decreased with increasing BW, contrary to protein requirements for chronic SCI.

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We need energy intake to provide energy and nutrients to our cells. The amount of daily energy intake should aim for energy balance, which results in good health. Under- or overconsumption of total daily energy over a longer period leads to increased risk of diseases. In this scoping review, the components of daily energy requirement are defined. Several methods to estimate energy requirements and the amount of total daily energy intake (kJ) related to health are also discussed. Reference values for energy intake in children, adults and pregnant and postpartum women, and older adults are evaluated. Results show that it is challenging to set reference values for energy intake since existing methods are not accurate and precise, and there are several factors that influence the estimated amount of energy. Energy requirement is increased during growth as in childhood, pregnancy and lactation. We conclude that more research in this area is needed, and that new high-quality studies in both Nordic and Baltic countries are needed to obtain new recommendation numbers for energy intake.

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Climate change is expected to increase the number of heat wave events, leading to prolonged exposures to severe heat stress (HS) and the corresponding adverse effects on dairy cattle productivity. Modelling dairy cattle productivity under HS conditions is complicated because it requires comprehending the complexity, non-linearity, dynamicity, and delays in animal response. In this paper, we applied the System Dynamics methodology to understand the dynamics of animal response and system delays of observed milk yield (MY) in dairy cows under HS. Data on MY and temperature-humidity index were collected from a dairy cattle farm. Model development involved: (i) articulation of the problem, identification of the feedback mechanisms, and development of the dynamic hypothesis through a causal loop diagram; (ii) formulation of the quantitative model through a stock-and-flow structure; (iii) calibration of the model parameters; and (iv) analysis of results for individual cows. The model was successively evaluated with 20 cows in the case study farm, and the relevant parameters of their HS response were quantified with calibration. According to the evaluation of the results, the proposed model structure was able to capture the effect of HS for 11 cows with high accuracy with mean absolute percent error <5%, concordance correlation coefficient >0.6, and R2 > 0.6, except for two cows (ID #13 and #20) with R2 less than 0.6, implying that the rest of the nine animals do not exhibit heat-sensitive behaviour for the defined parameter space. The presented HS model considered non-linear feedback mechanisms as an attempt to help farmers and decision makers quantify the animal response to HS, predict MY under HS conditions, and distinguish the heat-sensitive cows from heat-tolerant cows at the farm level.

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Malnutrition is ubiquitous in cirrhotic patients presenting for liver transplant (LT). Providing an appropriate energy prescription is fundamental to effective nutrition therapy. We aimed to compare measured energy expenditure (mEE) with predicted energy expenditure (pEE) in patients awaiting LT and determine clinical factors associated with mEE. In this prospective observational study, energy expenditure was measured by indirect calorimetry in 110 adult patients referred for LT and predicted by commonly utilized equations (Harris-Benedict, Schofield, and EASL guidelines). Nutritional status, anthropometry, muscle function, biochemical and clinical data were also collected. The median model for end-stage liver disease (MELD) was 19 (IQR 13, 25), and the majority were Child-Pugh B (51%) or C (37%). Malnutrition was evident in 85%. Median mEE by calorimetry was 1756 (1531, 2104) kcal/d and significantly higher than pEE as per Harris-Benedict 1480 (1322, 1722) kcal/d and Schofield 1474 (1349, 1723) kcal/d (both p < 0.001), but lower than EASL guidelines (35 kcal/kg) when an activity factor was applied to mEE; 2283 (1990, 2735) kcal/d versus 2590 (2178, 3010) kcal/d (p < 0.001). Hypermetabolism (mEE:pEE > 1.2) was evident in 48% of the cohort. Multivariate analysis found MELD, Child-Pugh class, diuretic use, and severe malnutrition to be independent predictors of hypermetabolism. A new liver-specific predictive model has been developed, showing superior agreement with mEE than common predictive equations. In conclusion, there is a poor correlation between mEE and pEE in patients awaiting LTs, and hypermetabolism is common. Relying on historical predictive equations in this patient population may result in significant under or over-feeding. A tailored energy prescription based on indirect calorimetry or a liver-specific predictive model is recommended for LT candidates.

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Tomato drying implies high energy consumption due to the high moisture content, and limiting drying temperatures is necessary to avoid carotenoid degradation. To explain the mechanism of moisture transport through the material and to scale up the drying process, drying experiments are needed and supported by mathematical modeling. For the Rila tomato peel drying process, ten thin-layer mathematical models were formulated based on experimental data for six temperatures (50-75 °C) and validated by statistical analysis. Considering the slab geometry of the peels sample and Fick's second law of diffusion model, the calculated effective moisture diffusivity coefficient values Deff varied between 1.01 × 10-9-1.53 × 10-9 m2/s with R2 higher than 0.9432. From the semi-theoretical models, Two-term presents the best prediction of moisture ratio with the highest R2 and lowest χ2 and RMSE values. Using the experimental data on extract quality (carotenoid content), two degradation models were formulated. Increasing the drying temperature from 50 °C to 110 °C, a degradation of 94% for lycopene and 83% for ß-carotene were predicted. From the energy analysis, a specific energy consumption of 56.60 ± 0.51 kWh is necessary for hot-air drying of 1 kg of Rila tomato peel at 50 °C to avoid carotenoid degradation.

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BACKGROUND: Literature on optimal energy provision via parenteral nutrition (PN) is limited and the evidence quality is low. The purpose of this study is to determine if there is a difference in outcomes in adult critically ill patients when receiving lower vs higher calorie provision via PN early in intensive care unit (ICU) stay. METHODS: Adult patients initiated on PN within the first 10 days of ICU stay from May 2014 to June 2021 were included in this retrospective study. The primary outcome was to determine the impact of lower (<20 kcal/kg/day) vs higher (>25 kcal/kg/day) calorie provision on all-cause, in-hospital mortality. Secondary outcomes were to determine the impact of calorie provision on hospital or ICU length of stay and incidence of complications. RESULTS: This study included 133 patients: a lower calorie provision group (n = 77) and a higher calorie provision group (n = 56). There was a significant difference in all-cause, in-hospital mortality between the lower and the higher calorie provision groups (36.36% and 17.86%, respectively; P = 0.02). However, upon a multivariate analysis of death at discharge, the specific calorie provision group did not affect the probability of death at hospital discharge. The secondary outcomes were not significantly different between groups. CONCLUSION: When comparing lower calorie provision with higher calorie provision in adult critically ill patients receiving PN early within their ICU stay, there were no differences in outcomes after controlling for significant confounders. Future larger prospective studies should further evaluate optimal caloric provision via PN in this population.

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Malnutrition and need for nutritive support are both very common in exotic animals requiring critical care. Assessment and monitoring of body condition, weight, protein absorption, and catabolic loss is recommended to help guide restorative therapy. Several critical care diets are available based on digestive strategy. Fluid requirements and evaporative water loss can vary based on taxa; ectoderms suffer evaporative losses at a greater magnitude than endotherms. Enteral and parenteral nutrition strategies can be appropriate for patients, with natural history and anatomic and physiologic differences considered as much as possible.

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BACKGROUND: Total energy expenditure (TEE) determines energy requirements, but objective data in patients with cancer are limited. OBJECTIVES: We aimed to characterize TEE, investigate its predictors, and compare TEE with cancer-specific predicted energy requirements. METHODS: This cross-sectional analysis included patients with stages II-IV colorectal cancer from the Protein Recommendation to Increase Muscle (PRIMe) trial. TEE was assessed by 24-h stay in a whole-room indirect calorimeter before dietary intervention and compared with cancer-specific predicted energy requirements (25-30 kcal/kg). Generalized linear models, paired-samples t tests, and Pearson correlation were applied. RESULTS: Thirty-one patients (56 ± 10 y; body mass index [BMI]: 27.9 ± 5.5 kg/m2; 68% male) were included. Absolute TEE was higher in males (mean difference: 391 kcal/d; 95% CI: 167, 616 kcal/d; P < 0.001), patients with colon cancer (mean difference: 279 kcal/d; 95% CI: 73, 485 kcal/d; P = 0.010), and patients with obesity (mean difference: 393 kcal/d; 95% CI: 182, 604 kcal/d; P < 0.001). Appendicular lean soft tissue (ß: 46.72; 95% CI: 34.27, 59.17; P < 0.001) and tumor location (colon-ß: 139.69; 95% CI: 19.44, 259.95; P = 0.023) independently predicted TEE when adjusted for sex. Error between measured TEE and energy requirements predicted by 25 kcal/kg (mean difference: 241 kcal/d; 95% CI: 76, 405 kcal/d; P = 0.010) or 30 kcal/kg (mean difference: 367 kcal/d; 95% CI: 163, 571 kcal/d; P < 0.001) was higher for patients with obesity, and proportional error was observed (25 kcal/kg: r = -0.587; P < 0.001; and 30 kcal/kg: r = -0.751; P < 0.001). TEE (mean difference: 25 kcal/kg; 95% CI: 24, 27 kcal/kg) was below predicted requirements using 30 kcal/kg (-430 ± 322 kcal/d; P < 0.001). CONCLUSIONS: This is the largest study to assess TEE of patients with cancer using whole-room indirect calorimeter and highlights the need for improved assessment of energy requirements in this population. Energy requirements predicted using 30 kcal/kg overestimated TEE by 1.44 times in a controlled sedentary environment and TEE was outside of the predicted requirement range for most. Special considerations are warranted when determining TEE of patients with colorectal cancer, such as BMI, body composition, and tumor location. This is a baseline cross-sectional analysis from a clinical trial registered at clinicaltrials.gov as NCT02788955 (https://clinicaltrials.gov/ct2/show/NCT02788955).

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BACKGROUND: Nutrition support professionals are tasked with estimating energy requirements for critically ill patients. Estimating energy leads to suboptimal feeding practices and adverse outcomes. Indirect calorimetry (IC) is the gold standard for determining energy expenditure. However, access is limited, so clinicians must rely on predictive equations. METHODS: A retrospective chart review of critically ill patients who underwent IC in 2019 was conducted. The Mifflin-St Jeor equation (MSJ), Penn State University equation (PSU), and weight-based nomograms were calculated using admission weights. Demographic, anthropometric, and IC data were extracted from the medical record. Data were stratified by body mass index (BMI) classifications, and relationships between estimated energy requirements and IC were compared. RESULTS: Participants (N = 326) were included. Median age was 59.2 years, and BMI was 30.1. The MSJ and PSU were positively correlated with IC in all BMI classes (all P < 0.001). Median measured energy expenditure was 2004 kcal/day, which was 1.1-fold greater than PSU, 1.2-fold greater than MSJ, and 1.3-fold greater than weight-based nomograms (all P < 0.001). CONCLUSION: Despite the significant relationships between measured and estimated energy requirements, the significant fold-differences suggest that using predictive equations leads to significant underfeeding, which may result in poor clinical outcomes. Clinicians should rely on IC when available, and increased training in the interpretation of IC is warranted. In the absence of IC, the use of admission weight in weight-based nomograms could serve as a surrogate, as these calculations provided the closest estimate to IC in participants with normal weight and overweight, but not obesity.

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The birth process is a crucial event for piglet survival. Along with increasing litter sizes, not only has the duration of parturition increased, but placental blood flow per piglet has reduced and placental area per piglet has become smaller, making these piglets more susceptible for hypoxia. Diminishing the risk of piglet hypoxia by either reducing the total duration of parturition or increasing fetal oxygenation may reduce the incidence of stillbirth and early post-partum mortality. This review discusses options to do so by nutritionally supporting the sow in the final pre-partum period, after discussing the role of uterine contractions and placental blood flow. Providing sufficient energy seems to be a logical first step, but also other nutrients needed for uterine contractions, such as calcium, or enhancing uterine blood flow by using nitrate seem promising. These nutrient requirements may depend on litter size.

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Microbial growth requires energy for maintaining the existing cells and producing components for the new ones. Microbes therefore invest a considerable amount of their resources into proteins needed for energy harvesting. Growth in different environments is associated with different energy demands for growth of yeast Saccharomyces cerevisiae, although the cross-condition differences remain poorly characterized. Furthermore, a direct comparison of the energy costs for the biosynthesis of the new biomass across conditions is not feasible experimentally; computational models, on the contrary, allow comparing the optimal metabolic strategies and quantify the respective costs of energy and nutrients. Thus in this study, we used a resource allocation model of S. cerevisiae to compare the optimal metabolic strategies between different conditions. We found that S. cerevisiae with respiratory-impaired mitochondria required additional energetic investments for growth, while growth on amino acid-rich media was not affected. Amino acid supplementation in anaerobic conditions also was predicted to rescue the growth reduction in mitochondrial respiratory shuttle-deficient mutants of S. cerevisiae. Collectively, these results point to elevated costs of resolving the redox imbalance caused by de novo biosynthesis of amino acids in mitochondria. To sum up, our study provides an example of how resource allocation modeling can be used to address and suggest explanations to open questions in microbial physiology.

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BACKGROUND: To investigate the accuracy of ten different predictive equations to estimate resting energy expenditure (REE) in a sample of Brazilian older adults and develop a predictive equation for estimating REE based on body composition data. METHODS: A cross-sectional study with thirty-eight Brazilian older adults aged 60-84 years, who had their REE measured by indirect calorimetry (IC) and BC assessed by dual-energy x-ray absorptiometry (DXA). REE was compared to the estimation of ten predictive equations, and the differences between BC and anthropometric-based equations were investigated using Bland-Altman plots and Lin's concordance correlation. Accuracy was evaluated considering ±10% of the ratio between estimated and measured REE. RESULTS: The sample was composed of 57.9% men, with a mean age of 68.1 (5.8) years, and a mean REE by IC of 1528 (451) kcal. The highest accuracy was 47.4% obtained by Luhrmann and Fredrix equations, and the lowest accuracy was 13.2% reached by Weigle equation. In general, the proportion of underestimation was higher than overestimation. All anthropometric-based equations presented a good agreement with REE from IC. For those equations derived from BC, however, three of them reached only a moderate agreement. In terms of accuracy, all equations presented lower than 50% of accurate prediction of REE. CONCLUSIONS: In this sample of older adults, previous predictive equations to estimate REE did not show good accuracy, and those based on BC presented even worse results, showing that changes in BC related to aging could impact the accuracy of these equations.

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Predictive resting metabolic rate (RMR) equations are widely used to determine total daily energy expenditure (TDEE). However, it remains unclear whether these predictive RMR equations accurately predict TDEE in the athletic populations. The purpose of this study was to examine the accuracy of 10 commonly used RMR prediction equations (Cunningham, De Lorenzo, Freire, Harris-Benedict, Mifflin St. Jeor, Nelson, Owen, Tinsley, Watson, Schofield) in collegiate men and women athletes. One-hundred eighty-seven National Collegiate Athletic Association Division III men (n = 97) and women (n = 90) athletes were recruited to participate in one day of metabolic testing. RMR was measured using indirect calorimetry and body composition was analyzed using air displacement plethysmography. A repeated measures ANOVA with Bonferroni post hoc analyses was selected to determine mean differences between measured and predicted RMR. Linear regression analysis was used to assess the accuracy of each RMR prediction method (p<0.05). All prediction equations significantly underestimated RMR (p<0.001), although there was no difference between the De Lorenzo and Watson equations and measured RMR (p = 1.00) for women, only. In men, the Tinsley and Freire equations were the most agreeable formulas with the lowest root-mean-square prediction error value of 404 and 412 kcals, respectively. In women, the De Lorenzo and Watson equations were the most agreeable equations with the lowest root-mean-squared error value of 171 and 211 kcals, respectively. The results demonstrate that such RMR equations may underestimate actual energy requirements of athletes and thus, practitioners should interpret such values with caution.Highlights All prediction equations significantly underestimated RMR in men athletes.All prediction equations, except for the De Lorenzo and Watson equations, significantly underestimated RMR in women athletes.Although a significant underestimation of RMR in men athletes, the Freire and Tinsley equations were the most agreeable prediction equations.In women athletes, the De Lorenzo and Watson equations were the most agreeable prediction equations.

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Room temperature and individual behavior may influence the energy requirements of gestating sows. These factors are not yet integrated on a daily and individual basis in the calculation of these requirements. The objective of this study was to quantify the effect of temperatures on the sows' behaviors, especially on the level of physical activity, and on the energy requirements of gestating sows. Over four consecutive weeks, the temperature of two gestation rooms was maintained at medium temperatures (16.7 °C and 18.5 °C, respectively, for room 1 and room 2) for the first and third week, at low temperatures (14.4 °C and 15.3 °C) for the second week, and at high temperatures (31.6 °C and 31.9 °C) for the fourth week. Individual behavior was manually recorded based on videos and the data used to estimate the physical activity and social interactions of 37 gestating sows separated into two groups. The videos were analyzed over two periods of 5 h ("Feeding period" from 2300 to 0400 hours, "Resting period" from 1330 to 1830 hours). The energy requirements were calculated by the InraPorc model, modified for gestating sows, on the basis of a thermo-neutral situation and an average activity of 4 h standing per day for all the sows. The sows of one group were less active in high than low temperatures (83 vs. 103 min standing or walking over 5 h, P < 0.001). Isolation for high temperatures or huddling for low temperatures could be observed when sows were lying down. The sows spent more time lying laterally with high temperatures than low temperatures (66% vs. 52% of time spent lying, respectively, P < 0.001). Both groups reacted differently to high temperatures, in one the sows changed their activity (lying more) whereas in the other they drank more water compared to medium temperatures (11 vs. 8.5 L/d, P = 0.01). In one group, with high temperatures the sows were fed above their requirements (they should have received 110 g of feed per day per sow less, P < 0.001) and with low temperatures the same group should have received 50 g/d per sow more to fulfill their requirements. For the second group of sows, the temperatures did not significantly affect the feed requirements. In conclusion, daily ambient temperature and individual physical activity seem to be relevant information to add in nutritional models to improve precision feeding.

Ambient temperature may influence the energy requirement of gestating sows, but this factor is not yet integrated daily in the calculation of this requirement. The objective of this study was to quantify the effect of temperatures on sow's behavior, physical activity, and energy requirements on gestating sows. The 37 gestating sows were housed in two groups for which the temperature of each room was maintained at different temperatures during four consecutive weeks: the first and third weeks at 18 °C on average (medium temperature), the second week at 15.5 °C (low temperature), and the last one at 32 °C (high temperature). The sows modified their behavior regarding the room temperature even though these changes differed regarding the group of sows. Compared to medium temperature, high temperatures may induce an increase of water consumption or of the time spent lying, and of the rectal temperature of some sows. Low temperatures may induce huddling and/or an increase in aggressiveness. Low and high temperatures seem to impact energy costs even though it depends on the group of sows. Therefore, ambient temperature and individual activity are relevant information to add into nutritional models to improve their accuracy of energy requirement prediction.

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Average temperatures in the Midwest, USA are predicted to increase 2-9°C by the end of the century; resulting in muddy pastures for spring calving beef heifers as they enter late gestation. The objective of this study was to evaluate the effects of muddy conditions on heifer body weight (BW), body condition score (BCS), conceptus free live weight (CFLW), and fetal growth when heifers were energy restricted during late gestation. Eighteen Angus heifers (n = 9/treatment) were paired based on initial BW. One heifer from each BW pair was randomly allocated to either the mud (MUD) or control (CON) treatment on day 196 of gestation. Pens in the CON treatment were bedded with wood chips, while pens in the MUD treatment were filled with mud (average depth of 19.5 ±â€…7.9 cm). Heifers were housed individually and fed the same diet that consisted of a limit-fed total mixed ration from day 196 to 266 of gestation that was formulated to meet 66% of the net energy for maintenance, growth, and gestation requirements. Requirements and the amount of the diet offered were adjusted weekly, and heifers were weighed and sampled for blood metabolites weekly. Data were analyzed as a randomized complete block design with repeated measurements. There was a treatment × day of gestation interaction, such that heifers had similar BW, BCS, and CFLW on day 196 of gestation. By day 266 of gestation; however, heifers in the MUD treatment weighed 43.5 kg less (P < 0.01) and were 1.8 BCS units less (P < 0.01) than heifers in the CON treatment. This is further supported by the treatment × day effects we observed for back fat (BF) and rump fat (RF) thickness, such that the MUD heifers had less BF (P = 0.02) and RF (P < 0.01) by day 266 of gestation. There was a marginally significant difference for gestation length (P = 0.06), such that heifers in the MUD treatment calved approximately 3.1 days before the heifers in the CON treatment. Though heifers in the MUD treatment decreased their BW and CFLW during the treatment period, we did not observe a difference in calf birth weight (P = 0.34), calf plasma IgG concentration (P = 0.37), or calf weaning weight (P = 0.63). Despite heifers in the MUD treatment having greater BW, CFLW, and BCS losses compared with the heifers in the CON treatment, the heifers in the MUD treatment seemed to prioritize fetal growth, as they mobilized their body tissues to meet the energetic demands of pregnancy.