No abstract available

We report a web-based tool for analysis of experiments using indirect calorimetry to measure physiological energy balance. CalR simplifies the process to import raw data files, generate plots, and determine the most appropriate statistical tests for interpretation. Analysis using the generalized linear model (which includes ANOVA and ANCOVA) allows for flexibility in interpreting diverse experimental designs, including those of obesity and thermogenesis. Users also may produce standardized output files for an experiment that can be shared and subsequently re-evaluated using CalR. This framework will provide the transparency necessary to enhance consistency, rigor, and reproducibility. The CalR analysis software will greatly increase the speed and efficiency with which metabolic experiments can be organized, analyzed per accepted norms, and reproduced and will likely become a standard tool for the field. CalR is accessible at https://CalRapp.org/.

The ability to characterize the development of metabolic function in neonatal rodents has been limited due to technological constraints. Low respiratory volumes and flows at rest pose unique problems, making it difficult to reliably measure O(2) consumption, CO(2) production, respiratory quotient (RQ), and energy expenditure (EE). Our aim was to develop and validate a commercial-grade indirect calorimetry system capable of characterizing the metabolic phenotype of individual neonatal rodents.

Nutritional assessment can be challenging in patients with traumatic brain injury (TBI), and indirect calorimetry may be a more suitable method than predictive equations. We compared the Penn State equation versus the gold standard of indirect calorimetry for the nutritional assessment of patients with TBI, and quantified the difference between nutritional requirements and actual patient intake.

The use of indirect calorimetry (IC) is increasing due to its precision in resting energy expenditure (REE) measurement in critically ill patients. Thus, we aimed to evaluate the clinical outcomes of an IC-guided nutrition therapy compared to predictive equations strategy in such a patient population.

Respiratory quotient (RQ) provides an indication of the relative balance of carbohydrate and fat oxidation. RQ could serve as an early biomarker of negative energy balance during weight loss. Restriction of energy intake relative to total daily energy requirements produces a negative energy balance which can lead to a fall in RQ, accompanied by a decrease in resting energy expenditure (REE). However, the net change in body weight does not usually match predicted weight change due to intraindividual metabolic adaptations. Our aim is to determine the effectiveness of utilising EE information from indirect calorimetry during weight loss intervention.

Energy expenditure (EE) evaluation in Intensive Care Unit (ICU) patients can be very challenging. Critical illness is characterized by great variability in EE, which is influenced by the disease itself and the effects of treatment. Indirect calorimetry (IC) is currently the gold standard to measure EE in Intensive Care Unit (ICU) patients. However, calorimeters are not widely available, and predictive formulas (PF) are still commonly used, leading to under or overfeeding and deleterious consequences.Important metabolic changes occur and catabolism becomes prominent in critically ill patients.Both hyper and hypometabolism can be observed, but hypermetabolic patients appear to have higher mortality rates compared to metabolically normal patients. This study aimed to assess hypermetabolism incidence and compare clinical outcomes between hypermetabolic and normometabolic patients in ICU.

Physical activity (PA) is a main determinant of total energy expenditure (TEE) and has been suggested to play a key role in body weight regulation. However, thus far it has been challenging to determine what part of the expended energy is due to activity in freely moving subjects. We developed a computational method to estimate activity related energy expenditure (AEE) and resting metabolic rate (RMR) in mice from activity and indirect calorimetry data. The method is based on penalised spline regression and takes the time dependency of the RMR into account. In addition, estimates of AEE and RMR are corrected for the regression dilution bias that results from inaccurate PA measurements. We evaluated the performance of our method based on 500 simulated metabolic chamber datasets and compared it to that of conventional methods. It was found that for a sample time of 10 minutes the penalised spline model estimated the time-dependent RMR with 1.7 times higher accuracy than the Kalman filter and with 2.7 times higher accuracy than linear regression. We assessed the applicability of our method on experimental data in a case study involving high fat diet fed male and female C57Bl/6J mice. We found that TEE in male mice was higher due to a difference in RMR while AEE levels were similar in both groups, even though female mice were more active. Interestingly, the higher activity did not result in a difference in AEE because female mice had a lower caloric cost of activity, which was likely due to their lower body weight. In conclusion, TEE decomposition by means of penalised spline regression provides robust estimates of the time-dependent AEE and RMR and can be applied to data generated with generic metabolic chamber and indirect calorimetry set-ups.

Fasting is a simple metabolic strategy that is used to estimate the maintenance energy requirement where the energy supply for basic physiological functions is provided by the mobilization of body reserves. However, the underlying metabolic components of maintenance energy expenditure are not clear. This study investigated the differences in heat production (HP), respiratory quotient (RQ) and plasma metabolites in pigs in the fed and fasted state, using the techniques of indirect calorimetry and metabolomics.

Actual energy needs after a stay in intensive care units (ICUs) are unknown. The aims of this observational study were to measure the energy expenditure (mEE) of ICU survivors during their post-ICU hospitalization period, and to compare this to the estimations of predictive equations (eEE). Survivors of an ICU stay ≥ 7 days were enrolled in the general ward during the first 7 days after ICU discharge. EE was measured using the Q-NRG calorimeter in canopy mode. This measure was compared to the estimated EE using the Harris−Benedict (HB) equation multiplied by a 1.3 stress factor, the Penn−State (PS) equation or the 30 kcal weight-based (WB) equation. A total of 55 adults were included (67.3% male, age 60 (52−67) y, body mass index 26.1 (22.2−29.7) kg/m2). Indirect calorimetry was performed 4 (3−6) d after an ICU stay of 12 (7−16) d. The mEE was 1682 (1328−1975) kcal/d, corresponding to 22.9 (19.1−24.2) kcal/kg/day. The eEE values derived using HB and WB equations were significantly higher than mEE: 3048 (1805−3332) and 2220 (1890−2640) kcal/d, respectively (both p < 0.001). There was no significant difference between mEE and eEE using the PS equation: 1589 (1443−1809) kcal/d (p = 0.145). The PS equation tended to underestimate mEE with a bias of −61.88 kcal and a wide 95% limit of agreement (−717.8 to 594 kcal). Using the PS equation, agreement within 15% of the mEE was found in 32/55 (58.2%) of the patients. In the present cohort of patients who survived a prolonged ICU stay, mEE was around 22−23 kcal/kg/day. In this post-ICU hospitalization context, none of the tested equations were accurate in predicting the EE measured by indirect calorimetry.

Methane (CH4) is a natural by-product of microbial fermentation in the rumen and is a powerful greenhouse gas. An open-circuit indirect calorimetry system for continuous determination of CH4 and CO2 production and O2 consumption and, thereafter, heat production (HP) calculation for small ruminants was described and validated. The system consisted of a computerized control, data acquisition and recording system for gases and air flux. The average value ± standard deviation for the calibration factors in the system were 1.005 ± 0.0007 (n = 6), 1.013 ± 0.0012 (n = 6) and 0.988 ± 0.0035 (n = 6) for O2, CO2 and CH4, respectively. Calibration factors close to 1 confirmed the absence of leaks in the indirect calorimetry system. In addition, an experimental test with 8 goats at mid lactation was conducted to validate the system. The repeatability for CH4 and heat production measured with the open-circuit indirect calorimetry system was 79% and 61%, respectively. Daily average HP measured by indirect calorimetry (Respiration Quotient method) was close to the average HP determined from Carbon-Nitrogen balance (CN method), accounting for 685 and 667 kJ per kg metabolic body weight, respectively. Therefore, discrepancies averaged 1.92%, a rather satisfactory value considering the substantial amount of technical and analytical work involved. The close agreement found between both methods can be considered as being indicative of the absence of systematic error. Two diets with different forage were tested: 40% was either alfalfa hay (HAY) or alfalfa silage (SIL), and the proportion of concentrate was the same in both groups (60%). The experimental trial shown that HP and CH4 were higher in HAY than SIL diet (differences between treatments of 28 kJ of HP per kg of metabolic body weight and 7.1 L CH4/day were found). The data acquisition and recording device developed improved the accuracy of the indirect calorimetry system by reducing the work involved in managing output data and refining the functionality for measuring gas exchange and energy metabolism in small ruminants.

The accurate assessment of resting energy expenditure (REE) is essential for personalized nutrition, particularly in critically ill children. Indirect calorimetry (IC) is the gold standard for measuring REE. This methodology is based on the measurement of oxygen consumption (VO2) and carbon dioxide production (VCO2). These parameters are integrated into the Weir equation to calculate REE. Additionally, IC facilitates the determination of the respiratory quotient (RQ), offering valuable insights into a patient's carbohydrate and lipid consumption. IC validation is limited to spontaneously breathing and mechanically ventilated patients, but it is not validated in patients undergoing non-invasive ventilation (NIV). This study investigates the application of IC during NIV-CPAP (continuous positive airway pressure) and NIV-PS (pressure support).

Changes in total energy expenditure (TEE) and substrate metabolism may help explain the metabolic actions of testosterone (T). This study measured respiratory quotient (RQ), TEE, ghrelin, insulin, and key lipolysis enzyme concentrations in relation to body weight (wt) and food intake (FI) in both normal and bilaterally orchiectomized rats with/without T treatment.

Intestinal failure is defined as the inability to absorb the minimum of macro and micronutrients, minerals and vitamins due to a reduction in gut function. In a subpopulation of patients with a dysfunctional gastrointestinal system, treatment with total or supplemental parenteral nutrition is required. The golden standard for the determination of energy expenditure is indirect calorimetry. This method enables an individualized nutritional treatment based on measurements instead of equations or body weight calculations. The possible use and advantages of this technology in a home PN setting need critical evaluation. For this narrative review, a bibliographic search is performed in PubMed and Web of Science using the following terms: 'indirect calorimetry', 'home parenteral nutrition', 'intestinal failure', 'parenteral nutrition', 'resting energy expenditure', 'energy expenditure' and 'science implementation'. The use of IC is widely embedded in the hospital setting but more research is necessary to investigate the role of IC in a home setting and especially in IF patients. It is important that scientific output is generated in order to improve patients' outcome and develop nutritional care paths.

Indirect calorimetry (InCa) estimates whole-body energy expenditure and total substrate oxidation based on O2 consumption and CO2 production, but does not allow for the quantification of oxidation of exogenous substrates with time. To achieve this, we incorporated 13CO2 and 12CO2 gas sensors into a commercial InCa system and aimed to demonstrate their performance and added value. As a performance indicator, we showed the discriminative oscillations in 13CO2 enrichment associated with food intake in mice fed diets containing naturally low (wheat) vs high (maize) 13C enrichment. To demonstrate the physiological value, we quantified exogenous vs total carbohydrate and fat oxidation continuously, in real time in mice varying in fat mass. Diet-induced obese mice were fed a single liquid mixed meal containing 13C-isotopic tracers of glucose or palmitate. Over 13 h, ~70% glucose and ~48% palmitate ingested were oxidised. Exogenous palmitate oxidation depended on body fat mass, which was not the case for exogenous glucose oxidation. We conclude that extending an InCa system with 13CO2 and 12CO2 sensors provides an accessible and powerful technique for real-time continuous quantification of exogenous and whole-body substrate oxidation in mouse models of human metabolic physiology.

Background : Nutritional management is crucial for severely ill patients. Measuring metabolism is believed to be necessary for the acute sepsis phase to accurately estimate nutrition. Indirect calorimetry (IDC) is assumed to be useful for acute intensive care; however, there are few studies on long-term IDC measurement in patients with systemic inflammation. Methods : Rats were categorized into the LPS received or control groups; LPS rats were categorized into underfeeding (UF), adjusted feeding (AF), and overfeeding (OF) groups. Indirect calorimetry measurement was performed until 72 or 144 h. Body composition was measured at -24 and 72 or 144 h, and tissue weight was measured at 72 or 144 h. Results : Low energy consumption and loss of diurnal variation of resting energy expenditure were observed in the LPS group compared with the control group until 72 h, after which the LPS group recovered. The resting energy expenditure in the OF group was higher than that in the UF and AF groups. In the first phase, low energy consumption was observed in all groups. In the second and third phases, higher energy consumption occurred in the OF group than in the UF and AF groups. In the third phase, diurnal variation recovered in all groups. Muscle atrophy caused body weight loss, but fat tissue loss did not occur. Conclusions : We observed metabolic changes with IDC during the acute systemic inflammation phase owing to differences in calorie intake. This is the first report of long-term IDC measurement using the LPS-induced systemic inflammation rat model.

We propose a novel method for assessing metabolic flexibility (MF) through indirect calorimetry. A total of twenty healthy volunteers (10 females; 10 males) aged 45-65 were categorized into a Low-Intensity activity group (LI, 0-1 session of 1 h per week) and a High-Intensity activity group (HI, 5-6 sessions of 2 h per week). Volunteers underwent a stepwise exercise test on a cycle ergometer, connected to a calorimeter, to examine respiratory gas exchange to evaluate peak fatty acid Oxidation (PFO) and peak carbohydrate oxidation (PCO). Circulating peroxisome proliferator-activated receptor α (PPARα) biomarkers, docosahexaenoic acid/eicosapentaenoic acid (DHA/EPA) ratio and N-oleoylethanolamine (OEA), and the endocannabinoid- 2-arachidonoylglycerol (2-AG), were evaluated. We developed two MF parameters: the MF index (MFI), calculated by the product of PFO normalized per kg of fat-free mass (FFM) and the percentage of VO2max at PFO, and the peak energy substrates' oxidation (PESO), computed by summing the kilocalories from the PFO and PCO, normalized per kg FFM. The MFI and PESO were significantly different between the HI and LI groups, showing strong correlations with the circulating bioactive substances. Higher DHA/EPA ratio (p ≤ 0.05) and OEA (p ≤ 0.01), but lower 2-AG levels (p ≤ 0.01) were found in the HI group. These new parameters successfully established a functional link between MF and the balance of PPARα/endocannabinoid systems.

Resting metabolic rate (RMR) studies frequently involve genetically-manipulated mice and high fat diets (HFD). We hypothesize that the use of inadequate methods impedes the identification of novel regulators of RMR. This idea was tested by simultaneously measuring RMR by direct calorimetry and respirometry in C57BL/6J mice fed chow, 45% HFD, and then returned to chow. Comparing results during chow feeding uncovered an underestimation of RMR by respirometry (0.010 ± 0.001 kcal/h, P < 0.05), which is equivalent in magnitude to ∼2% of total daily caloric turnover. RMR during 45% HFD feeding was increased by respirometry (+0.013 ± 0.003 kcal/h, P < 0.05), but not direct calorimetry (+0.001 ± 0.002 kcal/h). Both methods indicated that return to chow reduced RMR compared to HFD, though direct calorimetry indicated a reduction below the initial chow fed state (-0.019 ± 0.004 kcal/h versus baseline, P < 0.05) that was not detected by respirometry (-0.003 ± 0.002 kcal/h versus baseline). These results highlight method-specific interpretations of the effects of dietary interventions upon RMR in mice, and prompt the reevaluation of preclinical screening methods used to identify novel RMR modulators.

The purpose of this study was to examine agreement in energy expenditure between the Apple Series 1 Watch, LifeTrak Core C200, and Fitbit Charge HR with indirect calorimetry during various treadmill speeds in young adults. Participants were a sample of college-aged students (mean age = 20.1 (1.7) years; 13 females, 17 males). Participants completed six structured 10-minute exercise sessions on a treadmill with speeds ranging from 53.6 m·min-1 to 187.7 m·min-1. Indirect calorimetry was used as the criterion. Participants wore the Apple Watch, LifeTrak, and Fitbit activity monitors on their wrists. Group-level agreement was examined using equivalence testing, relative agreement was examined using Spearman's rho, and individual-level agreement was examined using Mean Absolute Percent Error (MAPE) and Bland-Altman Plots. Activity monitor agreement with indirect calorimetry was supported using the Apple Watch at 160.9 m·min-1 (Mean difference = -2.7 kcals, 90% C.I.: -8.3 kcals, 2.8 kcals; MAPE = 11.9%; rs = 0.64) and 187.7 m·min-1 (Mean difference = 3.7 kcals, 90% C.I.: -2.2 kcals, 9.7 kcals; MAPE = 10.7%; rs = 0.72) and the Fitbit at 187.7 m·min-1 (Mean difference = -0.2 kcals, 90% C.I.: -8.8 kcals, 8.5 kcals; MAPE = 20.1%; rs = 0.44). No evidence for statistical equivalence was seen for the LifeTrak at any speed. Bland-Altman Plot Limits of Agreement were narrower for the Apple Series 1 Watch compared to other monitors, especially at slower treadmill speeds. The results support the utility of the Apple Series 1 Watch and Fitbit Charge HR for assessing energy expenditure during specific treadmill running speeds in young adults.

Indirect calorimetry (IC) is recommended to guide energy delivery over predictive equations in critical illness due to its precision. However, the impact of using IC to measure energy expenditure on clinical outcomes is uncertain.