Resting energy metabolism and sweet taste preference during the menstrual cycle in healthy women.

Differences in blood concentration of sex hormones in the follicular (FP) and luteal (LP) phases may influence energy metabolism in women. We compared fasting energy metabolism and sweet taste preference on a representative day of the FP and LP in twenty healthy women (25·3 (sd 5·1) years, BMI: 22·2 (sd 2·2) kg/m2) with regular self-reported menses and without the use of hormonal contraceptives. From the self-reported duration of the three prior menstrual cycles, the predicted FP and LP visits were scheduled for days 5-12 and 20-25 after menses, respectively. The order of the FP and LP visits was randomly assigned. On each visit, RMR and RQ by indirect calorimetry, sweet taste preference by the Monell two-series forced-choice tracking procedure, serum fibroblast growth factor 21 by a commercial ELISA (FGF21, a liver-derived protein with action in energy balance, fuel oxidation and sugar preference) and dietary food intake by a 24-h dietary recall were determined. Serum progesterone and oestradiol concentrations displayed the expected differences between phases. RMR was lower in the FP v. LP (5042 (sd 460) v. 5197 (sd 490) kJ/d, respectively; P = 0·04; Cohen effect size, d rm = 0·33), while RQ showed borderline significant higher values (0·84 (sd 0·05) v. 0·81 (sd 0·05), respectively; P = 0·07; d rm = 0·62). Also, in the FP v. LP, sweet taste preference was lower (12 (sd 8) v. 16 (sd 9) %; P = 0·04; d rm = 0·47) concomitant with higher serum FGF21 concentration (294 (sd 164) v. 197 (sd 104) pg/ml; P < 0·01; d rm = 0·66). The menstrual cycle is associated with changes in energy expenditure, sweet taste preference and oxidative fuel partitioning.

Effect of an acute long-duration exercise bout on skeletal muscle lipid droplet morphology, GLUT 4 protein, and perilipin protein expression.

PURPOSE: Smaller lipid droplet morphology and GLUT 4 protein expression have been associated with greater muscle oxidative capacity and glucose uptake, respectively. The main purpose of this study was to determine the effect of an acute long-duration exercise bout on skeletal muscle lipid droplet morphology, GLUT4, perilipin 3, and perilipin 5 expressions. METHODS: Twenty healthy men (age 24.0 ± 1.0 years, BMI 23.6 ± 0.4 kg/m2) were recruited for the study. The participants were subjected to an acute bout of exercise on a cycle ergometer at 50% VO2max until they reached a total energy expenditure of 650 kcal. The study was conducted after an overnight fast. Vastus lateralis muscle biopsies were obtained before and immediately after exercise for immunohistochemical analysis to determine lipid, perilipin 3, perilipin 5, and GLUT4 protein contents while GLUT 4 mRNA was quantified using RT-qPCR. RESULTS: Lipid droplet size decreased whereas total intramyocellular lipid content tended to reduce (p = 0.07) after an acute bout of endurance exercise. The density of smaller lipid droplets in the peripheral sarcoplasmic region significantly increased (0.584 ± 0.04 to 0.638 ± 0.08 AU; p = 0.01) while larger lipid droplets significantly decreased (p < 0.05). GLUT4 mRNA tended to increase (p = 0.05). There were no significant changes in GLUT 4, perilipin 3, and perilipin 5 protein levels. CONCLUSION: The study demonstrates that exercise may impact metabolism by enhancing the quantity of smaller lipid droplets over larger lipid droplets.

Liver PDFF estimation using a multi-decoder water-fat separation neural network with a reduced number of echoes.

OBJECTIVE: To accurately estimate liver PDFF from chemical shift-encoded (CSE) MRI using a deep learning (DL)-based Multi-Decoder Water-Fat separation Network (MDWF-Net), that operates over complex-valued CSE-MR images with only 3 echoes. METHODS: The proposed MDWF-Net and a U-Net model were independently trained using the first 3 echoes of MRI data from 134 subjects, acquired with conventional 6-echoes abdomen protocol at 1.5 T. Resulting models were then evaluated using unseen CSE-MR images obtained from 14 subjects that were acquired with a 3-echoes CSE-MR pulse sequence with a shorter duration compared to the standard protocol. Resulting PDFF maps were qualitatively assessed by two radiologists, and quantitatively assessed at two corresponding liver ROIs, using Bland Altman and regression analysis for mean values, and ANOVA testing for standard deviation (STD) (significance level: .05). A 6-echo graph cut was considered ground truth. RESULTS: Assessment of radiologists demonstrated that, unlike U-Net, MDWF-Net had a similar quality to the ground truth, despite it considered half of the information. Regarding PDFF mean values at ROIs, MDWF-Net showed a better agreement with ground truth (regression slope = 0.94, R2 = 0.97) than U-Net (regression slope = 0.86, R2 = 0.93). Moreover, ANOVA post hoc analysis of STDs showed a statistical difference between graph cuts and U-Net (p < .05), unlike MDWF-Net (p = .53). CONCLUSION: MDWF-Net showed a liver PDFF accuracy comparable to the reference graph cut method, using only 3 echoes and thus allowing a reduction in the acquisition times. CLINICAL RELEVANCE STATEMENT: We have prospectively validated that the use of a multi-decoder convolutional neural network to estimate liver proton density fat fraction allows a significant reduction in MR scan time by reducing the number of echoes required by 50%. KEY POINTS: • Novel water-fat separation neural network allows for liver PDFF estimation by using multi-echo MR images with a reduced number of echoes. • Prospective single-center validation demonstrated that echo reduction leads to a significant shortening of the scan time, compared to standard 6-echo acquisition. • Qualitative and quantitative performance of the proposed method showed no significant differences in PDFF estimation with respect to the reference technique.

Time reallocation of physical behaviours induced by endurance exercise in physically active individuals.

Increasing moderate-vigorous physical activity (MVPA) through exercise requires reallocating time from other physical behaviour(s). We aimed to determine the reallocations induced by endurance exercise in physically active individuals. We also searched for behavioural compensatory responses, and explored the effect of exercise on daily energy expenditure. Fourteen participants (8 women; median age 37.8 [IQR 29.9-48.5] yr) exercised on Monday, Wednesday, and Friday mornings (cycling MVPA, 65 min/session; "exercise days"), and avoided exercising on Tuesday and Thursday ("rest days"). Time spent on sleep, sedentary behaviour, light-intensity physical activity, and MVPA was determined each day by accelerometers and logs. An energy expenditure index was computed considering minutes spent on each behaviour and fixed metabolic equivalents. We found that all participants had lower sleep and higher total (including exercise) MVPA on exercise days compared to rest days. Thus, on exercise vs. rest days, sleep was lower (490 [453-553] vs. 553 [497-599] min/day, respectively, P < 0.001), and total MVPA was higher (86 [80-101] vs. 23 [15-45] min/day, respectively; P < 0.001). No differences in other physical behaviours were detected. Notably, exercise not only induced reallocations (i.e. less time in other behaviours) but also behavioural compensatory responses in some participants (e.g. increased sedentary behaviour). This rearrangement of physical behaviours manifested in exercise-induced increases in energy expenditure from 96 to 232 MET × min/day. In conclusion, active individuals reallocated time from sleep to accommodate morning exercise. Yet exercise induced variable rearrangements of behaviours, with some individuals manifesting compensatory responses. Understanding individual rearrangements may help improve exercise interventions.

Adults are recommended to engage in moderate-vigorous physical activity (MVPA) to maintain health. But including exercise sessions within a day inevitably requires reallocating time from other physical behaviour(s): sleep, sedentary behaviour, or physical activity.We studied the time reallocations induced by 65 min/day of morning exercise (cycling MVPA) in physically active participants.Participants spent less time sleeping and higher time on total (including exercise) MVPA on days that included exercise compared to days without exercise. Thus, participants reallocated sleep time to accommodate morning exercise sessions.Some participants also spent higher time on sedentary behaviour during days that included exercise compared to days without exercise. This probably represents a behavioural compensatory response to exercise-induced fatigue.Together, time reallocations and behavioural compensatory responses led to a rearrangement of daily time spent on physical behaviours. This rearrangement was estimated to produce large interindividual variability in the increase in energy expenditure induced by exercise.

Reproducibility of the energy metabolism response to an oral glucose tolerance test: influence of a postcalorimetric correction procedure.

PURPOSE: Metabolic flexibility (MetF), which is a surrogate of metabolic health, can be assessed by the change in the respiratory exchange ratio (RER) in response to an oral glucose tolerance test (OGTT). We aimed to determine the day-to-day reproducibility of the energy expenditure (EE) and RER response to an OGTT, and whether a simulation-based postcalorimetric correction of metabolic cart readouts improves day-to-day reproducibility. METHODS: The EE was assessed (12 young adults, 6 women, 27 ± 2 years old) using an Omnical metabolic cart (Maastricht Instruments, Maastricht, The Netherlands) after an overnight fast (12 h) and after a 75-g oral glucose dose on 2 separate days (48 h). On both days, we assessed EE in 7 periods (one 30-min baseline and six 15-min postprandial). The ICcE was performed immediately after each recording period, and capillary glucose concentration (using a digital glucometer) was determined. RESULTS: We observed a high day-to-day reproducibility for the assessed RER (coefficients of variation [CV] < 4%) and EE (CVs < 9%) in the 7 different periods. In contrast, the RER and EE areas under the curve showed a low day-to-day reproducibility (CV = 22% and 56%, respectively). Contrary to our expectations, the postcalorimetric correction procedure did not influence the day-to-day reproducibility of the energy metabolism response, possibly because the Omnical's accuracy was ~ 100%. CONCLUSION: Our study demonstrates that the energy metabolism response to an OGTT is poorly reproducible (CVs > 20%) even using a very accurate metabolic cart. Furthermore, the postcalorimetric correction procedure did not influence the day-to-day reproducibility. Trial registration NCT04320433; March 25, 2020.

Exploring the sequential accumulation of metabolic syndrome components in adults.

The metabolic syndrome (MetS) is diagnosed upon the manifestation of ≥ 3 out of 5 specific components, regardless of their combination. The sequence through which these components accumulate may serve to identify underlying pathophysiological mechanisms and improve MetS treatment. We aimed to explore whether there is a more frequent sequence of accumulation of components in adults. The cross-sectional data of the National Health Survey of Chile 2016-2017 was analyzed. Subjects aged 18 to < 65 years, with body mass index ≥ 18.5 kg/m2, having all MetS components measured, and not under drug treatment were included (n = 1944, 60% women). MetS components were operationalized based on harmonized criteria: elevated waist circumference (≥ 91 cm for men, ≥ 83 cm for women), reduced high-density lipoprotein cholesterol (HDL-C; < 40 mg/dL for men, < 50 mg/dL for women), elevated triglycerides (≥ 150 mg/dL), elevated blood pressure (≥ 130 mmHg for systolic, or ≥ 85 mmHg for diastolic), and elevated glycemia (≥ 100 mg/dL). Subjects were grouped according to the number of components. Then, the prevalence of the observed combinations was determined. In subjects with one component, the most prevalent was waist circumference (56.7%). In subjects with two, the most prevalent combination was waist circumference and HDL-C (50.8%), while in subjects with three components was waist circumference, HDL-C, and triglycerides (54.0%). Finally, in subjects with four, the most prevalent combination was waist circumference, HDL-C, triglycerides, and blood pressure (40.8%). This pattern suggests that the most frequent accumulation sequence starts with abdominal obesity, followed by dyslipidemia, elevated blood pressure, and ultimately, dysglycemia. The factors that determine the sequence remain to be determined.

Predictive equations for energy expenditure in adult humans: From resting to free-living conditions.

Humans acquire energy from the environment for survival. A central question for nutritional sciences is how much energy is required to sustain cellular work while maintaining an adequate body mass. Because human energy balance is not exempt from thermodynamic principles, the energy requirement can be approached from the energy expenditure. Conceptual and technological advances have allowed understanding of the physiological determinants of energy expenditure. Body mass, sex, and age are the main factors determining energy expenditure. These factors constitute the basis for predictive equations for resting (REE) and total (TEE) energy expenditure in healthy adults. These equations yield predictions that differ up to ~400 kcal/d for REE and ~550 kcal/d for TEE. Identifying additional factors accounting for such variability and the most valid equations appears relevant. This review used novel approaches based on mathematical modeling of REE and analyses of the data from which REE predictive equations were generated. As for TEE, R2 and SE were considered because only a few predictive equations are available. From these analyses, Oxford's and Plucker's equations appear valid for predicting REE and TEE in adults, respectively.

Eating contexts determine the efficacy of nutrient warning labels to promote healthy food choices.

Introduction: Unhealthy food choices increase the risk of obesity and its co-morbidities. Nutrition labels are a public health policy that aims to drive individuals toward healthier food choices. Chile has been an example of this policy, where mandatory nutrient warning labels (NWL) identify processed foods high in calories and critical nutrients. Eating contexts influence individual food choices, but whether eating contexts also influence how NWL alter the decision process and selection during food choice is unknown. Methods: In an online mouse-tracking study, participants prompted to health, typical, or unrestricted eating contexts were instructed to choose between pairs of foods in the presence or absence of NWL. Conflict during choices was analyzed using mouse paths and reaction times. Results: NWL increased conflict during unhealthy food choices and reduced conflict during healthy choices in all contexts. However, the probability that NWL reversed an unhealthy choice was 80% in a healthy, 37% in a typical, and 19% in an unrestricted context. A drift-diffusion model analysis showed the effects of NWL on choice were associated with an increased bias toward healthier foods in the healthy and typical but not in the unrestricted context. Discussion: These data suggest that the efficacy of NWL to drive healthy food choices increases in a healthy eating context, whereas NWL are less effective in typical or unrestricted eating contexts.

Association Between Adipose Tissue Characteristics and Metabolic Flexibility in Humans: A Systematic Review.

Adipose tissue total amount, distribution, and phenotype influence metabolic health. This may be partially mediated by the metabolic effects that these adipose tissue characteristics exert on the nearby and distant tissues. Thus, adipose tissue may influence the capacity of cells, tissues, and the organism to adapt fuel oxidation to fuel availability, i.e., their metabolic flexibility (MetF). Our aim was to systematically review the evidence for an association between adipose tissue characteristics and MetF in response to metabolic challenges in human adults. We searched in PubMed (last search on September 4, 2021) for reports that measured adipose tissue characteristics (total amount, distribution, and phenotype) and MetF in response to metabolic challenges (as a change in respiratory quotient) in humans aged 18 to <65 years. Any study design was considered, and the risk of bias was assessed with a checklist for randomized and non-randomized studies. From 880 records identified, 22 remained for the analysis, 10 of them measured MetF in response to glucose plus insulin stimulation, nine in response to dietary challenges, and four in response to other challenges. Our main findings were that: (a) MetF to glucose plus insulin stimulation seems inversely associated with adipose tissue total amount, waist circumference, and visceral adipose tissue; and (b) MetF to dietary challenges does not seem associated with adipose tissue total amount or distribution. In conclusion, evidence suggests that adipose tissue may directly or indirectly influence MetF to glucose plus insulin stimulation, an effect probably explained by skeletal muscle insulin sensitivity. Systematic Review Registration: PROSPERO [CRD42020167810].

Similar Metabolic Health in Overweight/Obese Individuals With Contrasting Metabolic Flexibility to an Oral Glucose Tolerance Test.

Background: Low metabolic flexibility (MetF) may be an underlying factor for metabolic health impairment. Individuals with low MetF are thus expected to have worse metabolic health than subjects with high MetF. Therefore, we aimed to compare metabolic health in individuals with contrasting MetF to an oral glucose tolerance test (OGTT). Methods: In individuals with excess body weight, we measured MetF as the change in respiratory quotient (RQ) from fasting to 1 h after ingestion of a 75-g glucose load (i.e., OGTT). Individuals were then grouped into low and high MetF (Low-MetF n = 12; High-MetF n = 13). The groups had similar body mass index, body fat, sex, age, and maximum oxygen uptake. Metabolic health markers (clinical markers, insulin sensitivity/resistance, abdominal fat, and intrahepatic fat) were compared between groups. Results: Fasting glucose, triglycerides (TG), and high-density lipoprotein (HDL) were similar between groups. So were insulin sensitivity/resistance, visceral, and intrahepatic fat. Nevertheless, High-MetF individuals had higher diastolic blood pressure, a larger drop in TG concentration during the OGTT, and a borderline significant (P = 0.05) higher Subcutaneous Adipose Tissue (SAT). Further, compared to Low-MetF, High-MetF individuals had an about 2-fold steeper slope for the relationship between SAT and fat mass index. Conclusion: Individuals with contrasting MetF to an OGTT had similar metabolic health. Yet High-MetF appears related to enhanced circulating TG clearance and enlarged subcutaneous fat.

Deciphering the constrained total energy expenditure model in humans by associating accelerometer-measured physical activity from wrist and hip.

The constrained total energy expenditure (TEE) model posits that progressive increases in physical activity (PA) lead to increases in TEE; but after certain PA threshold, TEE plateaus. Then, a compensatory reduction in the expenditure of non-essential activities constrains the TEE. We hypothesized that high PA levels as locomotion associate with a compensatory attenuation in arm movements. We included 209 adults (64% females, mean [SD] age 32.1 [15.0] years) and 105 children (40% females, age 10.0 [1.1] years). Subjects wore, simultaneously, one accelerometer in the non-dominant wrist and another in the hip for ≥ 4 days. We analyzed the association between wrist-measured (arm movements plus locomotion) and hip-measured PA (locomotion). We also analyzed how the capacity to dissociate arm movements from locomotion influences total PA. In adults, the association between wrist-measured and hip-measured PA was better described by a quadratic than a linear model (Quadratic-R2 = 0.54 vs. Linear-R2 = 0.52; P = 0.003). Above the 80th percentile of hip-measured PA, wrist-measured PA plateaued. In children, there was no evidence that a quadratic model fitted the association between wrist-measured and hip-measured PA better than a linear model (R2 = 0.58 in both models, P = 0.25). In adults and children, those with the highest capacity to dissociate arm movements from locomotion-i.e. higher arm movements for a given locomotion-reached the highest total PA. We conclude that, in adults, elevated locomotion associates with a compensatory reduction in arm movements (probably non-essential fidgeting) that partially explains the constrained TEE model. Subjects with the lowest arm compensation reach the highest total PA.

Pathophysiological role of metabolic flexibility on metabolic health.

Glucose, fatty acids, and amino acids among others are oxidized to generate adenosine triphosphate (ATP). These fuels are supplied from the environment (through food intake) and internal depots (through lipolysis, glycogenolysis, and proteolysis) at different rates throughout the day. Complex adaptive systems permit to accommodate fuel oxidation according to fuel availability. This capacity of a cell, tissue, or organism to adapt fuel oxidation to fuel availability is defined as metabolic flexibility (MetF). There are conditions, such as insulin resistance, diabetes, and obesity, in which MetF seems to be impaired. The observation that those conditions are accompanied by mitochondrial dysfunction has set the basis to propose a link between mitochondrial dysfunction, metabolic inflexibility, and metabolic health. We here highlight the evidence about the notion that MetF influences metabolic health.

PPARGC1A Gene Promoter Methylation as a Biomarker of Insulin Secretion and Sensitivity in Response to Glucose Challenges.

Methylation in CpG sites of the PPARGC1A gene (encoding PGC1-α) has been associated with adiposity, insulin secretion/sensitivity indexes and type 2 diabetes. We assessed the association between the methylation profile of the PPARGC1A gene promoter gene in leukocytes with insulin secretion/sensitivity indexes in normoglycemic women. A standard oral glucose tolerance test (OGTT) and an abbreviated version of the intravenous glucose tolerance test (IVGTT) were carried out in n = 57 Chilean nondiabetic women with measurements of plasma glucose, insulin, and C-peptide. Bisulfite-treated DNA from leukocytes was evaluated for methylation levels in six CpG sites of the proximal promoter of the PPARGC1A gene by pyrosequencing (positions -816, -783, -652, -617, -521 and -515). A strong correlation between the DNA methylation percentage of different CpG sites of the PPARGC1A promoter in leukocytes was found, suggesting an integrated epigenetic control of this region. We found a positive association between the methylation levels of the CpG site -783 with the insulin sensitivity Matsuda composite index (rho = 0.31; p = 0.02) derived from the OGTT. The CpG hypomethylation in the promoter position -783 of the PPARGC1A gene in leukocytes may represent a biomarker of reduced insulin sensitivity after the ingestion of glucose.

Hepatocyte expression of the micropeptide adropin regulates the liver fasting response and is enhanced by caloric restriction.

The micropeptide adropin encoded by the clock-controlled energy homeostasis-associated gene is implicated in the regulation of glucose metabolism. However, its links to rhythms of nutrient intake, energy balance, and metabolic control remain poorly defined. Using surveys of Gene Expression Omnibus data sets, we confirm that fasting suppresses liver adropin expression in lean C57BL/6J (B6) mice. However, circadian rhythm data are inconsistent. In lean mice, caloric restriction (CR) induces bouts of compulsive binge feeding separated by prolonged fasting intervals, increasing NAD-dependent deacetylase sirtuin-1 signaling important for glucose and lipid metabolism regulation. CR up-regulates adropin expression and induces rhythms correlating with cellular stress-response pathways. Furthermore, adropin expression correlates positively with phosphoenolpyruvate carboxokinase-1 (Pck1) expression, suggesting a link with gluconeogenesis. Our previous data suggest that adropin suppresses gluconeogenesis in hepatocytes. Liver-specific adropin knockout (LAdrKO) mice exhibit increased glucose excursions following pyruvate injections, indicating increased gluconeogenesis. Gluconeogenesis is also increased in primary cultured hepatocytes derived from LAdrKO mice. Analysis of circulating insulin levels and liver expression of fasting-responsive cAMP-dependent protein kinase A (PKA) signaling pathways also suggests enhanced responses in LAdrKO mice during a glucagon tolerance test (250 µg/kg intraperitoneally). Fasting-associated changes in PKA signaling are attenuated in transgenic mice constitutively expressing adropin and in fasting mice treated acutely with adropin peptide. In summary, hepatic adropin expression is regulated by nutrient- and clock-dependent extrahepatic signals. CR induces pronounced postprandial peaks in hepatic adropin expression. Rhythms of hepatic adropin expression appear to link energy balance and cellular stress to the intracellular signal transduction pathways that drive the liver fasting response.

Metabolic health and its association with lifestyle habits according to nutritional status in Chile: A cross-sectional study from the National Health Survey 2016-2017.

BACKGROUND: Lifestyle habits associate with metabolic health in overall populations. Whether such association is similar among subjects with a different nutritional status has been less studied. We aimed to (i) determine the prevalence of metabolic phenotypes in Chile, and (ii) determine the association between lifestyle habits and metabolic health according to the nutritional status. METHODS: The National Health Survey of Chile 2016-2017 was analyzed. A metabolically unhealthy phenotype was defined as manifesting ≥3 of the following risk factors: elevated blood pressure, elevated triglycerides, elevated glucose, elevated waist circumference, or reduced high-density lipoprotein cholesterol. Individuals manifesting <2 risk factors were considered as healthy. The nutritional status was defined as normal weight (18.5 to <25 kg/m2), overweight (25 to <30 kg/m2) or obesity (≥30 kg/m2). Questionnaires were used to estimate smoking habits, alcohol intake, sedentary behavior, moderate-vigorous physical activity, fruits/vegetables consumption, and fish/seafood consumption. The association (odds ratio [95%CI]) between lifestyle habits and metabolic health was determined within each nutritional status, adjusting for age, sex, BMI (in kg/m2), and education. RESULTS: The prevalence of a metabolically unhealthy phenotype was 36% in the overall sample. Such a prevalence was 7%, 33% and 58% among subjects with normal weight, overweight and obesity, respectively. In subjects with normal weight, the highest quartile of fruits/vegetables consumption was associated with reduced odds of having a metabolically unhealthy phenotype (0.09 [0.01-0.48]). In subjects with obesity, the highest quartile of moderate-vigorous physical activity was associated with reduced odds of having a metabolically unhealthy phenotype (0.29 [0.09-0.91]). CONCLUSION: One third of the Chilean population manifests an unhealthy phenotype. We identified associations between lifestyle habits and metabolic health that are specific to the nutritional status. Thus, emphasizing fruits/vegetables consumption in subjects with normal weight, and physical activity in subjects with obesity, may maximize the benefits of public health interventions.

Direct Relationship Between Metabolic Flexibility Measured During Glucose Clamp and Prolonged Fast in Men.

OBJECTIVE: This study aimed to determine the relationship between metabolic flexibility (MetFlex) measured during a euglycemic-hyperinsulinemic clamp and a prolonged fast. This study also analyzed the association between MetFlex and metabolic health. METHODS: Eighteen healthy men (mean [SD]: 22 [2] years old; BMI: 22 [1] kg/m2 ) performed two sessions: (1) euglycemic-hyperinsulinemic clamp (2 mIU/kg of insulin per minute) and (2) ~20-hour fast. Clamp MetFlex corresponded to the change in (Δ) respiratory quotient (RQ) (ΔRQ = postchallenge RQ - prechallenge RQ) adjusted for M value and prechallenge RQ. Prolonged fast MetFlex corresponded to the ΔRQ adjusted for the Δß-hydroxybutyrate and prechallenge RQ. RESULTS: MetFlex during the clamp related directly with MetFlex during prolonged fast (r = 0.59, P = 0.014). Using the median of MetFlex for each challenge, this study split participants into high or low MetFlex. Participants with high or low MetFlex to both challenges were identified. Participants with high MetFlex had 3% lower serum low-density lipoprotein cholesterol than participants with low MetFlex (P = 0.021). CONCLUSIONS: Measuring MetFlex during a clamp or a prolonged fast produces similar results, despite challenging the oxidation of different substrates. An impaired MetFlex in response to these challenges may be an early event in the development of abnormal lipid metabolism.

Impact of the Method Used to Select Gas Exchange Data for Estimating the Resting Metabolic Rate, as Supplied by Breath-by-Breath Metabolic Carts.

The method used to select representative gas exchange data from large datasets influences the resting metabolic rate (RMR) returned. This study determines which of three methods yields the lowest RMR (as recommended for use in human energy balance studies), and in which method the greatest variance in RMR is explained by classical determinants of this variable. A total of 107 young and 74 middle-aged adults underwent a 30 min RMR examination using a breath-by-breath metabolic cart. Three gas exchange data selection methods were used: (i) steady state (SSt) for 3, 4, 5, or 10 min, (ii) a pre-defined time interval (TI), i.e., 6-10, 11-15, 16-20, 21-25, 26-30, 6-25, or 6-30 min, and (iii) "filtering", setting thresholds depending on the mean RMR value obtained. In both cohorts, the RMRs yielded by the SSt and filtering methods were significantly lower (p < 0.021) than those yielded by the TI method. No differences in RMR were seen under the different conditions of the SSt method, or of the filtering method. No differences were seen between the methods in terms of the variance in RMR explained by its classical determinants. In conclusion, the SSt and filtering methods return the lowest RMRs and intra-measurement coefficients of variation when using breath-by-breath metabolic carts.