Bed-rest and exercise remobilization: Concurrent adaptations in muscle glucose and protein metabolism

BACKGROUND

Bed-rest (BR) of only a few days duration reduces muscle protein synthesis and induces skeletal muscle atrophy and insulin resistance, but the scale and juxtaposition of these events have not been investigated concurrently in the same individuals. Moreover, the impact of short-term exercise-supplemented remobilization (ESR) on muscle volume, protein turnover and leg glucose uptake (LGU) in humans is unknown.

METHODS

Ten healthy males (24 ± 1 years, body mass index 22.7 ± 0.6 kg/m2) underwent 3 days of BR, followed immediately by 3 days of ESR consisting of 5 × 30 maximal voluntary single-leg isokinetic knee extensions at 90°/s each day. An isoenergetic diet was maintained throughout the study (30% fat, 15% protein and 55% carbohydrate). Resting LGU was calculated from arterialized-venous versus venous difference across the leg and leg blood flow during the steady-state of a 3-h hyperinsulinaemic-euglycaemic clamp (60 mU/m2/min) measured before BR, after BR and after remobilization. Glycogen content was measured in vastus lateralis muscle biopsy samples obtained before and after each clamp. Leg muscle volume (LMV) was measured using magnetic resonance imaging before BR, after BR and after remobilization. Cumulative myofibrillar protein fractional synthetic rate (FSR) and whole-body muscle protein breakdown (MPB) were measured over the course of BR and remobilization using deuterium oxide and 3-methylhistidine stable isotope tracers that were administered orally.

RESULTS

Compared with before BR, there was a 45% decline in insulin-stimulated LGU (P < 0.05) after BR, which was paralleled by a reduction in insulin-stimulated leg blood flow (P < 0.01) and removal of insulin-stimulated muscle glycogen storage. These events were accompanied by a 43% reduction in myofibrillar protein FSR (P < 0.05) and a 2.5% decrease in LMV (P < 0.01) during BR, along with a 30% decline in whole-body MPB after 2 days of BR (P < 0.05). Myofibrillar protein FSR and LMV were restored by 3 days of ESR (P < 0.01 and P < 0.01, respectively) but not by ambulation alone. However, insulin-stimulated LGU and muscle glycogen storage were not restored by ESR.

CONCLUSIONS

Three days of BR caused concurrent reductions in LMV, myofibrillar protein FSR, myofibrillar protein breakdown and insulin-stimulated LGU, leg blood flow and muscle glycogen storage in healthy, young volunteers. Resistance ESR restored LMV and myofibrillar protein FSR, but LGU and muscle glycogen storage remained depressed, highlighting divergences in muscle fuel and protein metabolism. Furthermore, ambulation alone did not restore LMV and myofibrillar protein FSR in the non-exercised contralateral limb, emphasizing the importance of exercise rehabilitation following even short-term BR.

Human Metabolism and Excretion of Kawakawa (Piper excelsum) Leaf Chemicals

SCOPE

Piper excelsum (kawakawa) has a history of therapeutic use by Māori in Aotearoa New Zealand. It is currently widely consumed as a beverage and included as an ingredient in "functional" food product. Leaves contain compounds that are also found in a wide range of other spices, foods, and medicinal plants. This study investigates the human metabolism and excretion of kawakawa leaf chemicals.

METHODS AND RESULTS

Six healthy male volunteers in one study (Bioavailability of Kawakawa Tea metabolites in human volunteers [BOKA-T]) and 30 volunteers (15 male and 15 female) in a second study (Impact of acute Kawakawa Tea ingestion on postprandial glucose metabolism in healthy human volunteers [TOAST]) consume a hot water infusion of dried kawakawa leaves (kawakawa tea [KT]). Untargeted Liquid Chromatography-Tandem Mass spectrometry (LC-MS/MS) analyses of urine samples from BOKA-T identified 26 urinary metabolites that are significantly associated with KT consumption, confirmed by the analysis of samples from the independent TOAST study. Seven of the 26 metabolites are also detected in plasma. Thirteen of the 26 urinary compounds are provisionally identified as metabolites of specific compounds in KT, eight metabolites are identified as being derived from specific compounds in KT but without resolution of chemical structure, and five are of unknown origin.

CONCLUSIONS

Several kawakawa compounds that are also widely found in other plants are bioavailable and are modified by phase 1 and 2 metabolism.

From Microcosm to Macrocosm: The -Omics, Multiomics, and Sportomics Approaches in Exercise and Sports

This article explores the progressive integration of -omics methods, including genomics, metabolomics, and proteomics, into sports research, highlighting the development of the concept of "sportomics." We discuss how sportomics can be used to comprehend the multilevel metabolism during exercise in real-life conditions faced by athletes, enabling potential personalized interventions to improve performance and recovery and reduce injuries, all with a minimally invasive approach and reduced time. Sportomics may also support highly personalized investigations, including the implementation of n-of-1 clinical trials and the curation of extensive datasets through long-term follow-up of athletes, enabling tailored interventions for athletes based on their unique physiological responses to different conditions. Beyond its immediate sport-related applications, we delve into the potential of utilizing the sportomics approach to translate Big Data regarding top-level athletes into studying different human diseases, especially with nontargeted analysis. Furthermore, we present how the amalgamation of bioinformatics, artificial intelligence, and integrative computational analysis aids in investigating biochemical pathways, and facilitates the search for various biomarkers. We also highlight how sportomics can offer relevant information about doping control analysis. Overall, sportomics offers a comprehensive approach providing novel insights into human metabolism during metabolic stress, leveraging cutting-edge systems science techniques and technologies.

Integrating Omics Data in Genome-Scale Metabolic Modeling: A Methodological Perspective for Precision Medicine

Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.

A Protocol for the Automatic Construction of Highly Curated Genome-Scale Models of Human Metabolism

Genome-scale metabolic models (GEMs) have emerged as a tool to understand human metabolism from a holistic perspective with high relevance in the study of many diseases and in the metabolic engineering of human cell lines. GEM building relies on either automated processes that lack manual refinement and result in inaccurate models or manual curation, which is a time-consuming process that limits the continuous update of reliable GEMs. Here, we present a novel algorithm-aided protocol that overcomes these limitations and facilitates the continuous updating of highly curated GEMs. The algorithm enables the automatic curation and/or expansion of existing GEMs or generates a highly curated metabolic network based on current information retrieved from multiple databases in real time. This tool was applied to the latest reconstruction of human metabolism (Human1), generating a series of the human GEMs that improve and expand the reference model and generating the most extensive and comprehensive general reconstruction of human metabolism to date. The tool presented here goes beyond the current state of the art and paves the way for the automatic reconstruction of a highly curated, up-to-date GEM with high potential in computational biology as well as in multiple fields of biological science where metabolism is relevant.

Lipopolysaccharide induces placental mitochondrial dysfunction in murine and human systems by reducing MNRR1 levels via a TLR4-independent pathway

Mitochondria play a key role in placental growth and development, and mitochondrial dysfunction is associated with inflammation in pregnancy pathologies. However, the mechanisms whereby placental mitochondria sense inflammatory signals are unknown. Mitochondrial nuclear retrograde regulator 1 (MNRR1) is a bi-organellar protein responsible for mitochondrial function, including optimal induction of cellular stress-responsive signaling pathways. Here, in a lipopolysaccharide-induced model of systemic placental inflammation, we show that MNRR1 levels are reduced both in mouse placental tissues in vivo and in human trophoblastic cell lines in vitro. MNRR1 reduction is associated with mitochondrial dysfunction, enhanced oxidative stress, and activation of pro-inflammatory signaling. Mechanistically, we uncover a non-conventional pathway independent of Toll-like receptor 4 (TLR4) that results in ATM kinase-dependent threonine phosphorylation that stabilizes mitochondrial protease YME1L1, which targets MNRR1. Enhancing MNRR1 levels abrogates the bioenergetic defect and induces an anti-inflammatory phenotype. We therefore propose MNRR1 as an anti-inflammatory therapeutic in placental inflammation.

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MNRR1 levels are reduced in mouse and human models of placental inflammation

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MNRR1 reduction occurs in mitochondria via a TLR4-independent NOX2-ATM-YME1L1 axis

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Activation of MNRR1 prevents placental inflammation

A multifunctional study of naturally occurring pyrazines in biological systems; formation mechanisms, metabolism, food applications and functional properties

Natural pyrazines, mainly methyl- or ethyl-substituted forms, are commonly applied as flavor ingredients in raw and roasted food. Meanwhile alkylpyrazines are used as food preservatives due to their effective antimicrobial action. These natural pyrazines are widely distributed in several biological systems such as plants, animals, and insects; each with respective physiological role. Besides, pyrazines are formed in food via thermal treatment and fermentation. This review presents the most comprehensive overview of pyrazines with correlation to their chemical structures and different applications with emphasis on their food applications. The major part deals with pyrazines generated in thermally treated food, reaction mechanisms highlighting factors and optimum conditions affecting their production. Additionally, the several metabolic reactions mediating for pyrazines metabolism in humans and excretion via the kidney are discussed and on context to their effects. Lastly, a review of the different techniques applied for pyrazines isolation, detection and quantitation is presented. The study provides future considerations and direction of research on this important dietary component and their applications. Pyrazines multifunctional chemistry is of value to the food sector, by presenting the best practices for their production whilst the detrimental effects are minimized.

Empirico-inductive and/or hypothetico-deductive methods in food science and nutrition research: which one to favor for a better global health?

Scientific research generally follows two main methods: empirico-inductive (EI), gathering scattered, real-world qualitative/quantitative data to elaborate holistic theories, and the hypothetico-deductive (HD) approach, testing the validity of hypothesized theory in specific conditions, generally according to reductionist methodologies or designs, with the risk of over simplifying the initial complexity empirically perceived in its holistic view. However, in current food and nutrition research, new hypotheses are often elaborated from reductionist data obtained with the HD approach, and aggregated to form (ultra)reductionist theories, with no application of EI observations, limiting the applicability of these hypotheses in real life. This trend and the application of the EI method are illustrated as regards with the global health issue through the examples of food classifications/scoring, clinical studies, the definition of a sustainable diet, the "matrix effect"-related hypothesis, the concept of healthy core metabolism, and obesity prevention within the perspective of social sciences. To be efficient for producing food and nutritional data appropriable by the society, it finally appears that not only both approaches are necessary, starting with the EI method then the HD one, but also a back and forth between the two, this being not always realized, potentially leading to confusion and misunderstanding in society.

Programmed PPAR-α downregulation induces inflammaging by suppressing fatty acid catabolism in monocytes

Inflammaging is associated with an increased risk of chronic disease. Monocytes are the principal immune cells for the production of inflammatory cytokines and contribute to inflammaging in the elderly. However, the underlying mechanisms remain largely unknown. Here, we found that monocytes from aged individuals contained high levels of lipid droplets (LDs), and this increase was correlated with impaired fatty acid oxidation. Downregulated peroxisome proliferator-activated receptor (PPAR)-α may be responsible for the pro-inflammatory phenotype of monocytes in aged individuals, as it was positively correlated with LD accumulation and increasing TNF-α concentration. Interestingly, interventions that result in PPAR-α upregulation, such as fenofibrate treatment, TNF-α neutralization, or calorie restriction, reversed the effect of aging on monocytes. Thus the downregulation of PPAR-α and LD levels in monocytes represents a novel biomarker for inflammaging. Furthermore, PPAR-α activation in the elderly may also alleviate long-term inflammaging, preventing the development of life-limiting chronic diseases.

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Monocytes from aged individuals contained high levels of lipid droplets (LDs)

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Downregulated PPAR-α is responsible for the aged monocytes profiles

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TNF-α might accelerate monocyte aging by downregulating PPAR-α expression

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PPAR-α activation in the elderly may also alleviate long-term inflammaging

Personalized whole-body models integrate metabolism, physiology, and the gut microbiome

Comprehensive molecular‐level models of human metabolism have been generated on a cellular level. However, models of whole‐body metabolism have not been established as they require new methodological approaches to integrate molecular and physiological data. We developed a new metabolic network reconstruction approach that used organ‐specific information from literature and omics data to generate two sex‐specific whole‐body metabolic (WBM) reconstructions. These reconstructions capture the metabolism of 26 organs and six blood cell types. Each WBM reconstruction represents whole‐body organ‐resolved metabolism with over 80,000 biochemical reactions in an anatomically and physiologically consistent manner. We parameterized the WBM reconstructions with physiological, dietary, and metabolomic data. The resulting WBM models could recapitulate known inter‐organ metabolic cycles and energy use. We also illustrate that the WBM models can predict known biomarkers of inherited metabolic diseases in different biofluids. Predictions of basal metabolic rates, by WBM models personalized with physiological data, outperformed current phenomenological models. Finally, integrating microbiome data allowed the exploration of host–microbiome co‐metabolism. Overall, the WBM reconstructions, and their derived computational models, represent an important step toward virtual physiological humans.

The long-term genetic stability and individual specificity of the human gut microbiome

By following up the gut microbiome, 51 human phenotypes and plasma levels of 1,183 metabolites in 338 individuals after 4 years, we characterize microbial stability and variation in relation to host physiology. Using these individual-specific and temporally stable microbial profiles, including bacterial SNPs and structural variations, we develop a microbial fingerprinting method that shows up to 85% accuracy in classifying metagenomic samples taken 4 years apart. Application of our fingerprinting method to the independent HMP cohort results in 95% accuracy for samples taken 1 year apart. We further observe temporal changes in the abundance of multiple bacterial species, metabolic pathways, and structural variation, as well as strain replacement. We report 190 longitudinal microbial associations with host phenotypes and 519 associations with plasma metabolites. These associations are enriched for cardiometabolic traits, vitamin B, and uremic toxins. Finally, mediation analysis suggests that the gut microbiome may influence cardiometabolic health through its metabolites.

How ancestral subsistence strategies solve salmon starvation and the "protein problem" of Pacific Rim resources

This article provides a theoretical treatment of hunter-gatherer diet and physiology. Through a synthesis of nutritional studies, informed by ethno-archaeological data, we examine the risk of protein-rich diets for human survival, and how societies circumvent "salmon starvation" in the northeastern Pacific Rim. Fundamental nutritional constraints associated with salmon storage and consumption counter long-standing assumptions about the engine of cultural evolution in the region. Excess consumption of lean meat can lead to protein poisoning, termed by early explorers "rabbit starvation." While consumption of fats and carbohydrates is widely portrayed as a pathway to "offsetting" protein thresholds, there are true limits to the amount of protein individuals can consume, and constraints are most extreme for smaller individuals, children, and pregnant/nursing mothers. While this problem is not usually perceived as associated with fish, the risk of protein poisoning limits the amount of low-fat fish that people can eat safely. Compared with smaller, mass-harvested species (e.g., eulachon), dried salmon are exceedingly lean. Under certain circumstances fattier foods (small forage fish, marine mammals, whales, and even bears) or carbohydrate-rich plants may have been preferred not just for taste but to circumvent this "dietary protein ceiling." Simply put, "salmon specialization" cannot evolve without access to complimentary caloric energy through fat-rich or carbohydrate-rich resources. By extension, the evolution of storage-based societies requires this problem be solved prior to or in tandem with-salmon intensification. Without such solutions, increased mortality and reproductive rates would have made salmon reliance unsustainable. This insight is in line with genomic research suggesting protein toxicity avoidance was a powerful evolutionary force, possibly linked to genetic adaptations among First Americans. It is also relevant to evaluating the plausibility of other purportedly "focal" economies and informs understanding of the many solutions varied global societies have engineered to overcome physiological protein limits.

GSK3 inhibitor ameliorates steatosis through the modulation of mitochondrial dysfunction in hepatocytes of obese patients

Obesity is an important risk factor and a potential treatment target for hepatic steatosis. The maladaptation of hepatic mitochondrial flexibility plays a key role in the hepatic steatosis. Herein, we found that hepatocyte-like cells derived from human adipose stem cell of obese patients exhibited the characteristics of hepatic steatosis and accompanied with lower expression of the subunits of mitochondrial complex I and lower oxidative phosphorylation levels. The GSK3 inhibitor CHIR-99021 promoted the expression of NDUFB8, NDUFB9, the subunits of mitochondrial complex I, the basal oxygen consumption rate, and the fatty acid oxidation of the hepatocytes of obese patients by upregulating the expression of the transcription factor PGC-1α, TFAM, and NRF1 involved in mitochondrial biogenesis. Moreover, CHIR-99021 decreased the lipid droplets size and the triglyceride levels in hepatocytes of obese patients. The results demonstrate that GSK3 inhibition ameliorates hepatic steatosis by elevating the mitochondrial function in hepatocytes of obese patients.

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Obese patients’ adipose-stem-cell-derived hepatocytes reveal hepatic steatosis

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Hepatic steatosis is accompanied the mitochondrial dysfunction

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The mitochondrial dysfunction is governed by the low expression PGC-1α, TFAM, and NRF1

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GSK3 inhibitor ameliorates hepatic steatosis via mitochondrial dysfunction modulation

Chemical Oxygen Demand Can Be Converted to Gross Energy for Food Items Using a Linear Regression Model

BACKGROUND

Human and microbial metabolism are distinct disciplines. Terminology, metrics, and methodologies have been developed separately. Therefore, combining the 2 fields to study energetic processes simultaneously is difficult.

OBJECTIVES

When developing a mechanistic framework describing gut microbiome and human metabolism interactions, energy values of food and digestive materials that use consistent and compatible metrics are required. As an initial step toward this goal, we developed and validated a model to convert between chemical oxygen demand (COD) and gross energy (${E_g}$) for >100 food items and ingredients.

METHODS

We developed linear regression models to relate (and be able to convert between) theoretical gross energy (${E_g}^{\prime}$) and chemical oxygen demand (COD'); the latter is a measure of electron equivalents in the food's carbon. We developed an overall regression model for the food items as a whole and separate regression models for the carbohydrate, protein, and fat components. The models were validated using a sample set of computed ${E_g}^{\prime}$ and COD' values, an experimental sample set using measured ${E_g}$ and COD values, and robust statistical methods.

RESULTS

The overall linear regression model and the carbohydrate, protein, and fat regression models accurately converted between COD and ${E_g}$, and the component models had smaller error. Because the ratios of COD per gram dry weight were greatest for fats and smallest for carbohydrates, foods with a high fat content also had higher ${E_g}$ values in terms of kcal · g dry weight-1.

CONCLUSION

Our models make it possible to analyze human and microbial energetic processes in concert using a single unit of measure, which fills an important need in the food-nutrition-metabolism-microbiome field. In addition, measuring COD and using the regressions to calculate ${E_g}$ can be used instead of measuring ${E_g}$ directly using bomb calorimetry, which saves time and money.

The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk

Metabolism is loosely defined as the set of physical and chemical interactions associated with the processes responsible for sustaining life. Two evident features arise whenever one looks at metabolism: first, metabolism is conformed as a very complex and intertwined construct of the many associated biomolecular processes. Second, metabolism is characterized by a high degree of stability reflected by the organisms resilience to either environmental changes or pathogenic conditions. Here we will investigate the relationship between these two features. By having access to the full set of human metabolic interactions as reported in the highly curated KEGG database, we built an integrated human metabolic network comprising metabolic, transcriptional regulation, and protein-protein interaction networks. We hypothesized that a metabolic process may exhibit resilience if it can recover from perturbations at the pathway level; in other words, metabolic resilience could be due to pathway crosstalk which may implicate that a metabolic process could proceed even when a perturbation has occurred. By analyzing the topological structure of the integrated network, as well as the hierarchical structure of its main modules or subnetworks, we observed that behind biological resilience lies an intricate communication structure at the topological and functional level with pathway crosstalk as the main component. The present findings, alongside the advent of large biomolecular databases, such as KEGG may allow the study of the consequences of this redundancy and resilience for the study of healthy and pathological phenotypes with many potential applications in biomedical science.

Identification of Trenbolone Metabolites Using Hydrogen Isotope Ratio Mass Spectrometry and Liquid Chromatography/High Accuracy/High Resolution Mass Spectrometry for Doping Control Analysis

Trenbolone is a synthetic anabolic-androgenic steroid, which has been misused for performance enhancement in sports. The detection of trenbolone doping in routine sports drug testing programs is complex as methods utilizing gas chromatography/mass spectrometry are complicated by unspecific derivatization products and artifacts, and liquid chromatography/mass spectrometry-based assays have shown to allow for comparably high limits-of-detection only. The number of previously reported metabolites in human urine is limited, and most analytical methods rely on targeting epitrenbolone, trenbolone glucuronide, and epitrenbolone glucuronide. In order to probe for the presence of additional trenbolone metabolites and to re-investigate the metabolism, an elimination study was conducted. One single dose of 10 mg of 5-fold deuterated trenbolone was administered to a healthy male volunteer and urine samples were collected for 30 days. For sample processing, published protocols were combined considering unconjugated, glucuronic acid-, sulfo- and alkaline-labile conjugated steroid metabolites. The sample preparation strategy consisted of solid-phase extractions, liquid-liquid extractions, metabolite de-conjugation, HPLC fractionation, and derivatization. Analytical methods included gas chromatography/thermal conversion/hydrogen isotope ratio mass spectrometry combined with single quadrupole mass spectrometry as well as liquid chromatography/high accuracy/high resolution mass spectrometry of the hydrolyzed and non-hydrolyzed samples. Twenty deuterium-labeled metabolites were identified including glucuronic acid-, sulfo- and potential cysteine-conjugates, and characterized by parallel reaction monitoring experiments yielding corresponding product ion mass spectra. Main metabolites were attributed to trenbolone-diol and potential trenbolone-diketone derivatives excreted as glucuronic acid and sulfo-conjugated analytes with detection windows of 5, respectively 6 days. Further characterization was conducted with pseudo MS3 experiments of the intact conjugates and by comparison of resulting product ion mass spectra with reference material.

Absorption, Biokinetics, and Metabolism of the Dopamine D2 Receptor Agonist Hordenine (N,N-Dimethyltyramine) after Beer Consumption in Humans

Hordenine, a natural constituent of germinated barley, is a biased agonist of the dopamine D2 receptor. This pilot study investigated the biokinetics of hordenine and its metabolites in four volunteers consuming beer equal to 0.075 mg hordenine/kg body weight. A new ultrahigh-performance liquid chromatography method coupled to electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) method determined maximum plasma concentrations of 12.0-17.3 nM free hordenine after 0-60 min. Hordenine phase-II metabolism was first dominated by sulfation, but later by glucuronidation. The elimination half-lives in plasma were 52.7-66.4 min for free hordenine and about 60/80 min longer for hordenine sulfate and hordenine glucuronide. Urinary excretion peaked 2-3.5 h after consumption and accumulated to 3.78 μmol within 24 h, corresponding to 9.9% of the ingested dose. The observed hordenine levels in plasma seem too low to provoke direct interaction with the dopamine D2 receptor related to food reward, but synergistic or additive effects with alcohol or N-methyltyramine may occur.

The Effects of Anthocyanins and Their Microbial Metabolites on the Expression and Enzyme Activities of Paraoxonase 1, an Important Marker of HDL Function

High circulating HDL concentrations and measures of various HDL functions are inversely associated with cardiovascular disease (CVD) risk. Paraoxonase 1 (PON1) contributes to many of the athero-protective functions of HDL, such as promoting the reverse cholesterol transport process and reducing the levels of oxidized LDL. PON1 activities are influenced by several factors, the most important being diet and genetic polymorphisms. Reported data from randomized controlled trials have shown that anthocyanin consumption increased PON1 activity. However, the underlying molecular mechanisms by which anthocyanins increase PON1 activity are not understood. Therefore, the aim of this research was to investigate the ability of anthocyanins and their metabolites to increase PON1 gene expression and/or enzyme activities as potential mechanisms. The effect of the two predominant dietary anthocyanins and 18 of their recently identified microbial metabolites including their phase-II conjugates on PON1 gene expression was studied using a PON1-Huh7 stably-transfected cell line and reporter gene assay. The effects of these compounds on PON1 arylesterase and lactonase activities were investigated using two isoforms of the PON1 enzyme that are the phenotypes of the 192Q/R polymorphism. None of the compounds caused even modest changes in PON1 promoter activity (p ≥ 0.05). Further, none of the compounds at physiological concentrations caused any significant changes in the arylesterase or lactonase activity of either of the iso-enzymes. Cyanidin reduced the lactonase activity of the PON1-R192R enzyme at high concentrations (−22%, p < 0.001), but not at physiologically achievable concentrations. In conclusion, none of the data reported here support the notion that anthocyanins or their metabolites affect PON1 transactivation or enzyme activities.

Evaluating human basal metabolism: the erroneous and misleading use of so-called "prediction equations"

Prediction (regression) equations are widely used, but their reliability as predictive tools is questionable as they provide contradicting results. The key point is that values calculated by regression equations are not precisely defined numbers but lie within a range of possible values in the standard deviation interval, none of which can be considered as the most probable. Ignoring this point leads to illicit/improper calculations, generating wrong results, which may have adverse consequences for human health. To demonstrate this, we applied the equations of Harris and Benedict in a reverse method, i.e. calculating (predicting) the daily energy expenditure in the same subjects used to obtain the equations and comparing values with the original measured data. We used the Bland-Altman and frequency distribution analyses. We found large differences in both individual data and population characteristics, showing that prediction equations are not predictive tools.

Rapid structure identification of nineteen metabolites of ondansetron in human urine using LC/MSn

Ondansetron, a 5-hydroxytryptamine type 3 (5-HT₃ ) receptor antagonist, is regarded as an excellent candidate to treat chemotherapy- and radiotherapy-induced nausea and vomiting. To better understand the metabolic profiles of ondansetron in human urine, the metabolites were analyzed using liquid chromatography/mass spectrometry (LC/MSⁿ ). Urine samples were collected after oral administration of 8 mg ondansetron to healthy volunteers. Then samples were treated by solid-phase extraction and detected with LC/MSⁿ . Besides ondansetron, in human urine, a total of 19 metabolites including 13 new metabolites were detected and identified via comparing the retention time and product ion spectra with those of reference standards isolated and characterized. The results showed that ondansetron was metabolized via hydroxylation, glucuronidation, sulfation and minor N-demethylation in human. LC/MSⁿ was demonstrated to be useful and sensitive in the metabolic study of ondansetron.

Improved control of non-communicable diseases (NCDs) requires an additional advanced concept for public health - a perspective from a middle-income country

A major consequence of all elements of the 'epidemiological transition' is the rapid emergence of non-communicable diseases (NCDs) in low- and middle-income countries. In contrast to the outcomes of the 'Alma Ata Conference for Primary Health Care', it has not yet been possible to introduce an equally powerful health policy for the prevention and control of NCDs. Major strategies so far are to advise individuals not to smoke and drink alcohol in excess. Additionally, 'healthy' nutrition and increased physical activity are also advocated. Policy for preventing and working against NCDs is now part of the Sustainable Development Goals, specifically target 3.4. So far, attempts to soften the influence of NCDs on the health of the people in low- and middle-income countries have been unsuccessful. It is argued here that additional concepts on how public health could operate against NCDs are needed.  Major risk factors for NCDs interfere with and alter complex steps within the human metabolism.  This paper explores how human metabolism works by assessing advances in molecular biology and research in genetics, epigenetics and gerontology. Recent developments in these scientific disciplines shed light on the complexity of how human health is maintained and diseases are invoked. Public health bodies should be aware, interested and possibly contribute to the aforementioned areas of interest, as far as NCDs are concerned, and translate major developments in a way, that could be useful in improving population health.

Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Endocrine Disrupting Chemicals: An Occult Mediator of Metabolic Disease

Endocrine disrupting chemicals (EDCs), a heterogeneous group of exogenous chemicals that can interfere with any aspect of endogenous hormones, represent an emerging global threat for human metabolism. There is now considerable evidence that the observed upsurge of metabolic disease cannot be fully attributed to increased caloric intake, physical inactivity, sleep deficit, and ageing. Among environmental factors implicated in the global deterioration of metabolic health, EDCs have drawn the biggest attention of scientific community, and not unjustifiably. EDCs unleash a coordinated attack toward multiple components of human metabolism, including crucial, metabolically-active organs such as hypothalamus, adipose tissue, pancreatic beta cells, skeletal muscle, and liver. Specifically, EDCs' impact during critical developmental windows can promote the disruption of individual or multiple systems involved in metabolism, via inducing epigenetic changes that can permanently alter the epigenome in the germline, enabling changes to be transmitted to the subsequent generations. The clear effect of this multifaceted attack is the manifestation of metabolic disease, clinically expressed as obesity, metabolic syndrome, diabetes mellitus, and non-alcoholic fatty liver disease. Although limitations of EDCs research do exist, there is no doubt that EDCs constitute a crucial parameter of the global deterioration of metabolic health we currently encounter.

A Model Integration Pipeline for the Improvement of Human Genome-Scale Metabolic Reconstructions

Metabolism has been a major field of study in the last years, mainly due to its importance in understanding cell physiology and certain disease phenotypes due to its deregulation. Genome-scale metabolic models (GSMMs) have been established as important tools to help achieve a better understanding of human metabolism. Towards this aim, advances in systems biology and bioinformatics have allowed the reconstruction of several human GSMMs, although some limitations and challenges remain, such as the lack of external identifiers for both metabolites and reactions. A pipeline was developed to integrate multiple GSMMs, starting by retrieving information from the main human GSMMs and evaluating the presence of external database identifiers and annotations for both metabolites and reactions. Information from metabolites was included into a graph database with omics data repositories, allowing clustering of metabolites through their similarity regarding database cross-referencing. Metabolite annotation of several older GSMMs was enriched, allowing the identification and integration of common entities. Using this information, as well as other metrics, we successfully integrated reactions from these models. These methods can be leveraged towards the creation of a unified consensus model of human metabolism.

Carbon dioxide generation rates for building occupants

Indoor carbon dioxide (CO2 ) concentrations have been used for decades to characterize building ventilation and indoor air quality. Many of these applications require rates of CO2 generation from the building occupants, which are currently based on approaches and data that are several decades old. However, CO2 generation rates can be derived from well-established concepts within the fields of human metabolism and exercise physiology, which relate these rates to body size and composition, diet, and level of physical activity. This paper reviews how CO2 generation rates have been estimated in the past and discusses how they can be characterized more accurately. Based on this information, a new approach to estimating CO2 generation rates is presented, which is based on the described concepts from the fields of human metabolism and exercise physiology. Using this approach and more recent data on body mass and physical activity, values of CO2 generation rates from building occupants are presented along with the variability that may occur based on body mass and activity data.

Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival

Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly. As experimental genome-wide SDL screens are still scarce, here we introduce a network-level computational modeling framework that quantitatively predicts human SDLs in metabolism. For each enzyme pair (A, B) we systematically knock out the flux through A combined with a stepwise flux increase through B and search for pairs that reduce cellular growth more than when either enzyme is perturbed individually. The predictive signal of the emerging network of 12,000 SDLs is demonstrated in five different ways. (i) It can be successfully used to predict gene essentiality in shRNA cancer cell line screens. Moving to clinical tumors, we show that (ii) SDLs are significantly underrepresented in tumors. Furthermore, breast cancer tumors with SDLs active (iii) have smaller sizes and (iv) result in increased patient survival, indicating that activation of SDLs increases cancer vulnerability. Finally, (v) patient survival improves when multiple SDLs are present, pointing to a cumulative effect. This study lays the basis for quantitative identification of cancer SDLs in a model-based mechanistic manner. The approach presented can be used to identify SDLs in species and cell types in which "omics" data necessary for data-driven identification are missing.

Genetic versus Non-Genetic Regulation of miR-103, miR-143 and miR-483-3p Expression in Adipose Tissue and Their Metabolic Implications-A Twin Study

Murine models suggest that the microRNAs miR-103 and miR-143 may play central roles in the regulation of subcutaneous adipose tissue (SAT) and development of type 2 diabetes (T2D). The microRNA miR-483-3p may reduce adipose tissue expandability and cause ectopic lipid accumulation, insulin resistance and T2D. We aimed to explore the genetic and non-genetic factors that regulate these microRNAs in human SAT, and to investigate their impact on metabolism in humans. Levels of miR-103, miR-143 and miR-483-3p were measured in SAT biopsies from 244 elderly monozygotic and dizygotic twins using real-time PCR. Heritability estimates were calculated and multiple regression analyses were performed to study associations between these microRNAs and measures of metabolism, as well as between these microRNAs and possible regulating factors. We found that increased BMI was associated with increased miR-103 expression levels. In addition, the miR-103 levels were positively associated with 2 h plasma glucose levels and hemoglobin A1c independently of BMI. Heritability estimates for all three microRNAs were low. In conclusion, the expression levels of miR-103, miR-143 and miR-483-3p in adipose tissue are primarily influenced by non-genetic factors, and miR-103 may be involved in the development of adiposity and control of glucose metabolism in humans.

Extensive changes in the transcriptional profile of human adipose tissue including genes involved in oxidative phosphorylation after a 6-month exercise intervention

AIM

Adipose tissue has an important function in total energy homeostasis, and its dysregulation may contribute to lifestyle-related diseases such as type 2 diabetes, cancer and cardiovascular diseases. The aim of this study was to investigate genome-wide mRNA expression in adipose tissue in healthy men before and after an exercise intervention to identify genes or pathways that mediate the beneficial effect of regular exercise. We also investigated the difference in adipose tissue mRNA expression between individuals with or without a family history of type 2 diabetes.

METHODS

The 6-month supervised exercise intervention was conducted in 47 healthy men (age 37.8 ± 4.3 years, BMI 28.5 ± 3.6 kg m(-2) ) with a previous low level of physical activity. RNA was analysed using GeneChip Human Gene 1.0 ST arrays (Affymetrix) before and after the exercise.

RESULTS

We identified 2,560 significant transcripts differentially expressed before vs. after exercise with a false discovery rate (FDR) < 0.1%, including genes encoding the respiratory chain, histone subunits, small nucleolar RNAs and ribosomal proteins. Additionally, pathways enriched in response to exercise include the ribosome, oxidative phosphorylation, proteasome and many metabolic pathways, whereas the WNT and MAPK signalling pathways were down-regulated (FDR < 5%) after exercise. There were no significant differences in mRNA expression between individuals with or without a family history of type 2 diabetes.

CONCLUSION

Exercise increased the expression of genes involved in oxidative phosphorylation, which is the opposite of what has been seen in adipose tissue from elderly or obese individuals with low physical fitness, and our study thereby demonstrates a mechanism for the beneficial effect of exercise.

Membrane transporters in a human genome-scale metabolic knowledgebase and their implications for disease

Membrane transporters enable efficient cellular metabolism, aid in nutrient sensing, and have been associated with various diseases, such as obesity and cancer. Genome-scale metabolic network reconstructions capture genomic, physiological, and biochemical knowledge of a target organism, along with a detailed representation of the cellular metabolite transport mechanisms. Since the first reconstruction of human metabolism, Recon 1, published in 2007, progress has been made in the field of metabolite transport. Recently, we published an updated reconstruction, Recon 2, which significantly improved the metabolic coverage and functionality. Human metabolic reconstructions have been used to investigate the role of metabolism in disease and to predict biomarkers and drug targets. Given the importance of cellular transport systems in understanding human metabolism in health and disease, we analyzed the coverage of transport systems for various metabolite classes in Recon 2. We will review the current knowledge on transporters (i.e., their preferred substrates, transport mechanisms, metabolic relevance, and disease association for each metabolite class). We will assess missing coverage and propose modifications and additions through a transport module that is functional when combined with Recon 2. This information will be valuable for further refinements. These data will also provide starting points for further experiments by highlighting areas of incomplete knowledge. This review represents the first comprehensive overview of the transporters involved in central metabolism and their transport mechanisms, thus serving as a compendium of metabolite transporters specific for human metabolic reconstructions.

Using the reconstructed genome-scale human metabolic network to study physiology and pathology

Metabolism plays a key role in many major human diseases. Generation of high-throughput omics data has ushered in a new era of systems biology. Genome-scale metabolic network reconstructions provide a platform to interpret omics data in a biochemically meaningful manner. The release of the global human metabolic network, Recon 1, in 2007 has enabled new systems biology approaches to study human physiology, pathology and pharmacology. There are currently more than 20 publications that utilize Recon 1, including studies of cancer, diabetes, host-pathogen interactions, heritable metabolic disorders and off-target drug binding effects. In this mini-review, we focus on the reconstruction of the global human metabolic network and four classes of its application. We show that computational simulations for numerous pathologies have yielded clinically relevant results, many corroborated by existing or newly generated experimental data.

New evidence on variations of human body burden of methylmercury from fish consumption

Epidemiologic studies commonly use mercury (Hg) level in hair as a valid proxy to estimate human exposure to methylmercury (MeHg) through fish consumption. This study presents the results yielded by a complete data set on fish consumption habits, Hg levels in edible fish resources, and corresponding Hg accumulation in hair, gathered in three distinct communities of eastern Canada. For one of these communities, the average hair Hg concentration was 14 times less than the expected value based on calculated daily oral exposure and current knowledge of MeHg metabolism. This finding could be explained by differences in specific genetic characteristics and/or interactive effects of other dietary components.

Pharmacokinetics and metabolism of brotizolam in humans

Pharmacokinetic studies were performed in healthy young volunteers and in elderly patients after oral administration of single doses (0.5 mg), increasing doses (0.5-1.5 mg), and multiple doses (1.0 mg) of brotizolam. Brotizolam was absorbed quickly from the gastro-intestinal tract. Elimination half-lives were in the range of 3.6-7.9 h. In healthy young volunteers as well as in elderly patients, there was neither a tendency for brotizolam to accumulate nor was there any indication of enzyme induction. Brotizolam was metabolized almost completely into hydroxylated compounds which were conjugated prior to renal excretion. After oral administration of [14C]-brotizolam, two-thirds of excretion of radioactivity was renal and was completed within 4 days.