The concept of transfer function for organ performance (work output vs. biochemical input) is developed for skeletal and cardiac muscle under steady-state exercise conditions. For metabolic control by the ADP concentration, the transfer function approximates a Michaelis-Menten hyperbola. Variation of the work identifies metabolic operating points on the transfer function corresponding to ADP concentrations or to a ratio of inorganic phosphate to phosphocreatine that can be determined by phosphorus nuclear magnetic resonance. This operating point is characterized by the fraction (V/VJ) of maximal activity of oxidative metabolism in the steady state. This quantity appears to be useful in predicting the degree to which metabolic homeostasis is effective; poorly controlled metabolic states can readily be identified and are used in the diagnosis and therapy of metabolic disease in the organs of neonates and adults.Analytical biochemistry has great strengths in measuring the more stable components of cell bioenergetics, particularly ATP [as buffered by creatine kinase equilibrium in skeletal tissue, brain, and heart (1, 2)]. However, the more labile and indeed interesting components, phosphocreatine (PCr) and inorganic phosphate (Pi) are measured with significantly less accuracy for two reasons: (i) the breakdown of PCr during extraction in the interval between cessation of metabolism and assay and (ii) even more serious, the difficulty in distinguishing, by usual analytical techniques, the bound and free forms and the contents of different intracellular compartments (3).Phosphorus NMR (P NMR) is selectively sensitive to the unbound form of cell metabolites and affords a wholly noninvasive approach to the study of metabolic control in the cytoplasmic compartment of cells and tissues (4, 5). P NMR can be used to obtain the relative concentrations of PCr, Pi, and ATP with rapidity and with significant atcuracy (± 10% in a 1-min scan). These concentration ratios are of great usefulness and importance in the study of metabolic control in animal models, neonates, and adults. Additional information is available when the absolute values of tissue concentrations of PCr and Pi are calculated from the value of ATP, and also creatine, as determined by analytical biochemistry [or prospectively by proton NMR (6, 7)]. When ADP plays its usual role as a regulatory metabolite, its concentration is maintained too low to be directly determined by NMR but can be calculated from the PCr/P1 value with appropriate assumptions. Under these conditions, NMR becomes a very useful tool because the principal elements of energy metabolism are determined and thermodynamic values may be estimated. As we shall discuss here, rates of oxidative metabolism relative to their maximal rates for the particular tissue conditions may be determined with significant accuracy particularly when P NMR data are used to include the effect of pH. We shall show how P NMR can be used, particularly in tissues stressed with hypoxia, for the prediction of stabili...

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Three types of metabolic control of oxidative metabolism are observed in the various tissues that have been studied by phosphorous magnetic resonance spectroscopy. The principal control of oxidative metabolism in skeletal muscle is by ADP (or P1/phosphocreatine). This

Purpose To compare activity type classification rates of machine learning algorithms trained on laboratory versus free-living accelerometer data in older adults. Methods Thirty-five older adults (21F and 14M ; 70.8 ± 4.9 y) performed selected activities in the laboratory while wearing three ActiGraph GT3X+ activity monitors (dominant hip, wrist, and ankle). Monitors were initialized to collect raw acceleration data at a sampling rate of 80 Hz. Fifteen of the participants also wore the GT3X+ in free-living settings and were directly observed for 2-3 hours. Time- and frequency- domain features from acceleration signals of each monitor were used to train Random Forest (RF) and Support Vector Machine (SVM) models to classify five activity types: sedentary, standing, household, locomotion, and recreational activities. All algorithms were trained on lab data (RFLab and SVMLab) and free-living data (RFFL and SVMFL) using 20 s signal sampling windows. Classification accuracy rates of both types of algorithms were tested on free-living data using a leave-one-out technique. Results Overall classification accuracy rates for the algorithms developed from lab data were between 49% (wrist) to 55% (ankle) for the SVMLab algorithms, and 49% (wrist) to 54% (ankle) for RFLab algorithms. The classification accuracy rates for SVMFL and RFFL algorithms ranged from 58% (wrist) to 69% (ankle) and from 61% (wrist) to 67% (ankle), respectively. Conclusion Our algorithms developed on free-living accelerometer data were more accurate in classifying activity type in free-living older adults than our algorithms developed on laboratory accelerometer data. Future studies should consider using free-living accelerometer data to train machine-learning algorithms in older adults.

During maximal exercise, skeletal muscle metabolism and oxygen consumption remain elevated despite precipitous declines in power. Presently, it is unclear whether these responses are caused by an increased ATP cost of force generation (ATP COST) or mitochondrial uncoupling; a process that reduces the efficiency of oxidative ATP synthesis (ATP OX). r To address this gap, we used 31-phosphorus magnetic resonance spectroscopy to measure changes in ATP COST and ATP OX in human quadriceps during repeated trials of maximal intensity knee extensions lasting up to 4 min. r ATP COST remained unchanged. In contrast, ATP OX plateaued by ß2 min and then declined (ß15%) over the final 2 min. The maximal capacity for ATP OX (V max), as well as ADP-specific rates of ATP OX , were also significantly diminished. r Collectively, these results suggest that mitochondrial uncoupling, and not increased ATP COST , is responsible for altering the regulation of skeletal muscle metabolism and oxygen consumption during maximal exercise.

Deteriorating sleep quality and increased fatigue are common complaints of old age, and poor sleep is associated with decreased quality of life and increased mortality rates. To date, little attention has been given to the potential effects of physical activity on sleep quality and fatigue in aging. The purpose of this study was to examine the relationships between activity, sleep and fatigue across the adult lifespan. Sixty community-dwelling adults were studied; 22 younger (21–29 years), 16 middle-aged (36–64 years), and 22 older (65–81 years). Physical activity was measured by accelerometer. Sleep quality was assessed using the Pittsburg Sleep Quality Index. Self-reported fatigue was evaluated with the Patient-Reported Outcomes Measurement Information System (PROMIS). Regression analysis revealed a positive relationship between activity and sleep quality in the older (r2=0.18, p=0.05), but not the younger (r2=0.041, p=0.35) or middle-aged (r2=0.001, p=0.93) groups. This association was mainly established by the relationship between moderate-vigorous activity and sleep quality (r2=0.37, p=0.003) in older adults. No association was observed between physical activity and self-reported fatigue in any of the groups (r2≤0.14, p≥0.15). However, an inverse relationship was found between sleep quality and fatigue in the older (r2=0.29, p=0.05), but not the younger or middle-aged (r2≤0.13, p≥0.10) groups. These results support the hypothesis that physical activity may be associated with sleep quality in older adults, and suggest that improved sleep may mitigate self-reported fatigue in older adults in a manner that is independent of activity.

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https://mc06.manuscriptcentral.com/apnm-pubs Applied Physiology, Nutrition, and Metabolism D r a f t 2 ABSTRACTDespite intensive efforts to understand the extent to which skeletal muscle mitochondrial capacity changes in older humans, the answer to this important question remains unclear. To determine what the preponderance of evidence from in vivo studies suggests, we conducted a systematic review and meta-analysis of the effects of age on muscle oxidative capacity as measured noninvasively by magnetic resonance spectroscopy. A secondary aim was to examine potential moderators contributing to differences in results across studies, including: muscle group, physical activity status, and sex. Candidate papers were identified from PubMed searches (n=3,561 papers) and the reference lists of relevant papers. Standardized effects (Hedges' g) were calculated for age and each moderator using data from the 22 studies that met the inclusion criteria (n=28 effects). Effects were coded as positive when older (≥55 years) adults had higher muscle oxidative capacity than younger (20-45 years) adults. The overall effect of age on oxidative capacity was positive (g=0.171, p<0.001), indicating modestly greater oxidative capacity in old. Notably, there was significant heterogeneity in this result (Q=245.8, p<0.001; I 2 ~70-90%). Muscle group, physical activity, and sex were all significant moderators of oxidative capacity (p≤0.029). This analysis indicates that the current body of literature does not support a de facto decrease of in vivo muscle oxidative capacity in old age. The heterogeneity of study results and identification of significant moderators provide clarity regarding apparent discrepancies in the literature, and indicate the importance of accounting for these variables when examining purported age-related differences in muscle oxidative capacity.