Inositol serves as a natural inhibitor of mitochondrial fission by directly targeting AMPK.

Mitochondrial dynamics regulated by mitochondrial fusion and fission maintain mitochondrial functions, whose alterations underline various human diseases. Here, we show that inositol is a critical metabolite directly restricting AMPK-dependent mitochondrial fission independently of its classical mode as a precursor for phosphoinositide generation. Inositol decline by IMPA1/2 deficiency elicits AMPK activation and mitochondrial fission without affecting ATP level, whereas inositol accumulation prevents AMPK-dependent mitochondrial fission. Metabolic stress or mitochondrial damage causes inositol decline in cells and mice to elicit AMPK-dependent mitochondrial fission. Inositol directly binds to AMPKγ and competes with AMP for AMPKγ binding, leading to restriction of AMPK activation and mitochondrial fission. Our study suggests that the AMP/inositol ratio is a critical determinant for AMPK activation and establishes a model in which AMPK activation requires inositol decline to release AMPKγ for AMP binding. Hence, AMPK is an inositol sensor, whose inactivation by inositol serves as a mechanism to restrict mitochondrial fission.

Impact of Plant-Based Dietary Fibers on Metabolic Homeostasis in High-Fat Diet Mice via Alterations in the Gut Microbiota and Metabolites.

BACKGROUND: The gut microbiota contributes to metabolic disease, and diet shapes the gut microbiota, emphasizing the need to better understand how diet impacts metabolic disease via gut microbiota alterations. Fiber intake is linked with improvements in metabolic homeostasis in rodents and humans, which is associated with changes in the gut microbiota. However, dietary fiber is extremely heterogeneous, and it is imperative to comprehensively analyze the impact of various plant-based fibers on metabolic homeostasis in an identical setting and compare the impact of alterations in the gut microbiota and bacterially derived metabolites from different fiber sources. OBJECTIVES: The objective of this study was to analyze the impact of different plant-based fibers (pectin, ß-glucan, wheat dextrin, resistant starch, and cellulose as a control) on metabolic homeostasis through alterations in the gut microbiota and its metabolites in high-fat diet (HFD)-fed mice. METHODS: HFD-fed mice were supplemented with 5 different fiber types (pectin, ß-glucan, wheat dextrin, resistant starch, or cellulose as a control) at 10% (wt/wt) for 18 wk (n = 12/group), measuring body weight, adiposity, indirect calorimetry, glucose tolerance, and the gut microbiota and metabolites. RESULTS: Only ß-glucan supplementation during HFD-feeding decreased adiposity and body weight gain and improved glucose tolerance compared with HFD-cellulose, whereas all other fibers had no effect. This was associated with increased energy expenditure and locomotor activity in mice compared with HFD-cellulose. All fibers supplemented into an HFD uniquely shifted the intestinal microbiota and cecal short-chain fatty acids; however, only ß-glucan supplementation increased cecal butyrate concentrations. Lastly, all fibers altered the small-intestinal microbiota and portal bile acid composition. CONCLUSIONS: These findings demonstrate that ß-glucan consumption is a promising dietary strategy for metabolic disease, possibly via increased energy expenditure through alterations in the gut microbiota and bacterial metabolites in mice.

Artificial Intelligence in Metabolomics: A Current Review.

Metabolomics and artificial intelligence (AI) form a synergistic partnership. Metabolomics generates large datasets comprising hundreds to thousands of metabolites with complex relationships. AI, aiming to mimic human intelligence through computational modeling, possesses extraordinary capabilities for big data analysis. In this review, we provide a recent overview of the methodologies and applications of AI in metabolomics studies in the context of systems biology and human health. We first introduce the AI concept, history, and key algorithms for machine learning and deep learning, summarizing their strengths and weaknesses. We then discuss studies that have successfully used AI across different aspects of metabolomic analysis, including analytical detection, data preprocessing, biomarker discovery, predictive modeling, and multi-omics data integration. Lastly, we discuss the existing challenges and future perspectives in this rapidly evolving field. Despite limitations and challenges, the combination of metabolomics and AI holds great promises for revolutionary advancements in enhancing human health.

The glucose-sensing transcription factor MLX balances metabolism and stress to suppress apoptosis and maintain spermatogenesis.

Male germ cell (GC) production is a metabolically driven and apoptosis-prone process. Here, we show that the glucose-sensing transcription factor (TF) MAX-Like protein X (MLX) and its binding partner MondoA are both required for male fertility in the mouse, as well as survival of human tumor cells derived from the male germ line. Loss of Mlx results in altered metabolism as well as activation of multiple stress pathways and GC apoptosis in the testes. This is concomitant with dysregulation of the expression of male-specific GC transcripts and proteins. Our genomic and functional analyses identify loci directly bound by MLX involved in these processes, including metabolic targets, obligate components of male-specific GC development, and apoptotic effectors. These in vivo and in vitro studies implicate MLX and other members of the proximal MYC network, such as MNT, in regulation of metabolism and differentiation, as well as in suppression of intrinsic and extrinsic death signaling pathways in both spermatogenesis and male germ cell tumors (MGCTs).

SOX17 Deficiency Mediates Pulmonary Hypertension: At the Crossroads of Sex, Metabolism, and Genetics.

Rationale: Genetic studies suggest that SOX17 (SRY-related HMG-box 17) deficiency increases pulmonary arterial hypertension (PAH) risk. Objectives: On the basis of pathological roles of estrogen and HIF2α (hypoxia-inducible factor 2α) signaling in pulmonary artery endothelial cells (PAECs), we hypothesized that SOX17 is a target of estrogen signaling that promotes mitochondrial function and attenuates PAH development via HIF2α inhibition. Methods: We used metabolic (Seahorse) and promoter luciferase assays in PAECs together with the chronic hypoxia murine model to test the hypothesis. Measurements and Main Results: Sox17 expression was reduced in PAH tissues (rodent models and from patients). Chronic hypoxic pulmonary hypertension was exacerbated by mice with conditional Tie2-Sox17 (Sox17EC-/-) deletion and attenuated by transgenic Tie2-Sox17 overexpression (Sox17Tg). On the basis of untargeted proteomics, metabolism was the top pathway altered by SOX17 deficiency in PAECs. Mechanistically, we found that HIF2α concentrations were increased in the lungs of Sox17EC-/- and reduced in those from Sox17Tg mice. Increased SOX17 promoted oxidative phosphorylation and mitochondrial function in PAECs, which were partly attenuated by HIF2α overexpression. Rat lungs in males displayed higher Sox17 expression versus females, suggesting repression by estrogen signaling. Supporting 16α-hydroxyestrone (16αOHE; a pathologic estrogen metabolite)-mediated repression of SOX17 promoter activity, Sox17Tg mice attenuated 16αOHE-mediated exacerbations of chronic hypoxic pulmonary hypertension. Finally, in adjusted analyses in patients with PAH, we report novel associations between a SOX17 risk variant, rs10103692, and reduced plasma citrate concentrations (n = 1,326). Conclusions: Cumulatively, SOX17 promotes mitochondrial bioenergetics and attenuates PAH, in part, via inhibition of HIF2α. 16αOHE mediates PAH development via downregulation of SOX17, linking sexual dimorphism and SOX17 genetics in PAH.

Biomass smoke inhalation promotes neuroinflammatory and metabolomic temporal changes in the hippocampus of female mice.

Smoke from wildland fires has been shown to produce neuroinflammation in preclinical models, characterized by neural infiltrations of neutrophils and monocytes, as well as altered neurovascular endothelial phenotypes. To address the longevity of such outcomes, the present study examined the temporal dynamics of neuroinflammation and metabolomics after inhalation exposures from biomass-derived smoke. 2-month-old female C57BL/6 J mice were exposed to wood smoke every other day for 2 weeks at an average exposure concentration of 0.5 mg/m3. Subsequent serial euthanasia occurred at 1-, 3-, 7-, 14-, and 28-day post-exposure. Flow cytometry of right hemispheres revealed two endothelial populations of CD31Hi and CD31Med expressors, with wood smoke inhalation causing an increased proportion of CD31Hi. These populations of CD31Hi and CD31Med were associated with an anti-inflammatory and pro-inflammatory response, respectively, and their inflammatory profiles were largely resolved by the 28-day mark. However, activated microglial populations (CD11b+/CD45low) remained higher in wood smoke-exposed mice than controls at day 28. Infiltrating neutrophil populations decreased to levels below controls by day 28. However, the MHC-II expression of the peripheral immune infiltrate remained high, and the population of neutrophils retained an increased expression of CD45, Ly6C, and MHC-II. Utilizing an unbiased approach examining the metabolomic alterations, we observed notable hippocampal perturbations in neurotransmitter and signaling molecules, such as glutamate, quinolinic acid, and 5-α-dihydroprogesterone. Utilizing a targeted panel designed to explore the aging-associated NAD+ metabolic pathway, wood smoke exposure drove fluctuations and compensations across the 28-day time course, ending with decreased hippocampal NAD+ abundance on day 28. Summarily, these results indicate a highly dynamic neuroinflammatory environment, with potential resolution extending past 28 days, the implications of which may include long-term behavioral changes, systemic and neurological sequalae directly associated with wildfire smoke exposure.

Multi-omic assessment shows dysregulation of pulmonary and systemic immunity to e-cigarette exposure.

Electronic cigarette (Ecig) use has become more common, gaining increasing acceptance as a safer alternative to tobacco smoking. However, the 2019 outbreak of Ecig and Vaping-Associated Lung Injury (EVALI) alerted the community to the potential for incorporation of deleterious ingredients such as vitamin E acetate into products without adequate safety testing. Understanding Ecig induced molecular changes in the lung and systemically can provide a path to safety assessment and protect consumers from unsafe formulations. While vitamin E acetate has been largely removed from commercial and illicit products, many Ecig products contain additives that remain largely uncharacterized. In this study, we determined the lung-specific effects as well as systemic immune effects in response to exposure to a common Ecig base, propylene glycol and vegetable glycerin (PGVG), with and without a 1% addition of phytol, a diterpene alcohol that has been found in commercial products. We exposed animals to PGVG with and without phytol and assessed metabolite, lipid, and transcriptional markers in the lung. We found both lung-specific as well as systemic effects in immune parameters, metabolites, and lipids. Phytol drove modest changes in lung function and increased splenic CD4 T cell populations. We also conducted multi-omic data integration to better understand early complex pulmonary responses, highlighting a central enhancement of acetylcholine responses and downregulation of palmitic acid connected with conventional flow cytometric assessments of lung, systemic inflammation, and pulmonary function. Our results demonstrate that Ecig exposure not only leads to changes in pulmonary function but also affects systemic immune and metabolic parameters.

Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome.

As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.

Aging influence on pulmonary and systemic inflammation and neural metabolomics arising from pulmonary multi-walled carbon nanotube exposure in apolipoprotein E-deficient and C57BL/6 female mice.

OBJECTIVE: Environmental exposures exacerbate age-related pathologies, such as cardiovascular and neurodegenerative diseases. Nanoparticulates, and specifically carbon nanomaterials, are a fast-growing contributor to the category of inhalable pollutants, whose risks to health are only now being unraveled. The current study assessed the exacerbating effect of age on multiwalled-carbon nanotube (MWCNT) exposure in young and old C57BL/6 and ApoE-/- mice. MATERIALS AND METHODS: Female C57BL/6 and apolipoprotein E-deficient (ApoE-/-) mice, aged 8 weeks and 15 months, were exposed to 0 or 40 µg MWCNT via oropharyngeal aspiration. Pulmonary inflammation, inflammatory bioactivity of serum, and neurometabolic changes were assessed at 24 h post-exposure. RESULTS: Pulmonary neutrophil infiltration was induced by MWCNT in bronchoalveolar lavage fluid in both C57BL/6 and ApoE-/-. Macrophage counts decreased with MWCNT exposure in ApoE-/- mice but were unaffected by exposure in C57BL/6 mice. Older mice appeared to have greater MWCNT-induced total protein in lavage fluid. BALF cytokines and chemokines were elevated with MWCNT exposure, but CCL2, CXCL1, and CXCL10 showed reduced responses to MWCNT in older mice. However, no significant serum inflammatory bioactivity was detected. Cerebellar metabolic changes in response to MWCNT were modest, but age and strain significantly influenced metabolite profiles assessed. ApoE-/- mice and older mice exhibited less robust metabolite changes in response to exposure, suggesting a reduced health reserve. CONCLUSIONS: Age influences the pulmonary and neurological responses to short-term MWCNT exposure. However, with only the model of moderate aging (15 months) in this study, the responses appeared modest compared to inhaled toxicant impacts in more advanced aging models.

An integrative cellular metabolomic study reveals downregulated tricarboxylic acid cycle and potential biomarkers induced by tetrabromobisphenol A in human lung A549 cells.

Tetrabromobisphenol A (TBBPA) is extensively utilized as a brominated flame retardant in numerous chemical products. As an environmental contaminant, the potential human toxicity of TBBPA has been attracting increasing attention. Nonetheless, the exact underlying mechanisms of toxicological effects caused by TBBPA remain uncertain. In this study, we investigated the potential mechanisms of TBBPA toxicity in vitro in the A549 cell line, one of the widely used type II pulmonary epithelial cell models in toxicology research. Cell viability was determined after treatment with varying concentrations of TBBPA. Liquid chromatography-mass spectrometry (LC-MS) metabolomics and metabolic flux approaches were utilized to evaluate metabolite and tricarboxylic acid (TCA) cycle oxidative flux changes. Our findings demonstrated that TBBPA significantly reduced the viability of cells and attenuated mitochondrial respiration in A549 cells. Additionally, LC-MS data showed significant reductions in TCA cycle metabolites including citrate, malate, fumarate, and alpha-ketoglutarate in 50 µM TBBPA-treated A549 cells. Metabolic flux analysis indicated reduced oxidative capacity in mitochondrial metabolism following TBBPA exposure. Moreover, diverse metabolic pathways, particularly alanine, aspartate, and glutamate metabolism and the TCA cycle, were found to be dysregulated. In total, 12 metabolites were significantly changed (p < .05) in response to 50 µM TBBPA exposure. Our results provide potential biomarkers of TBBPA toxicity in A549 cells and help elucidate the molecular mechanisms of pulmonary toxicity induced by TBBPA exposure.

Novel Relationship between Mitofusin 2-Mediated Mitochondrial Hyperfusion, Metabolic Remodeling, and Glycolysis in Pulmonary Arterial Endothelial Cells.

The disruption of mitochondrial dynamics has been identified in cardiovascular diseases, including pulmonary hypertension (PH), ischemia-reperfusion injury, heart failure, and cardiomyopathy. Mitofusin 2 (Mfn2) is abundantly expressed in heart and pulmonary vasculature cells at the outer mitochondrial membrane to modulate fusion. Previously, we have reported reduced levels of Mfn2 and fragmented mitochondria in pulmonary arterial endothelial cells (PAECs) isolated from a sheep model of PH induced by pulmonary over-circulation and restoring Mfn2 normalized mitochondrial function. In this study, we assessed the effect of increased expression of Mfn2 on mitochondrial metabolism, bioenergetics, reactive oxygen species production, and mitochondrial membrane potential in control PAECs. Using an adenoviral expression system to overexpress Mfn2 in PAECs and utilizing 13C labeled substrates, we assessed the levels of TCA cycle metabolites. We identified increased pyruvate and lactate production in cells, revealing a glycolytic phenotype (Warburg phenotype). Mfn2 overexpression decreased the mitochondrial ATP production rate, increased the rate of glycolytic ATP production, and disrupted mitochondrial bioenergetics. The increase in glycolysis was linked to increased hypoxia-inducible factor 1α (HIF-1α) protein levels, elevated mitochondrial reactive oxygen species (mt-ROS), and decreased mitochondrial membrane potential. Our data suggest that disrupting the mitochondrial fusion/fission balance to favor hyperfusion leads to a metabolic shift that promotes aerobic glycolysis. Thus, therapies designed to increase mitochondrial fusion should be approached with caution.

Metabolomics of oxidative stress: Nrf2 independent depletion of NAD or increases of sugar alcohols.

Nrf2 encodes a transcription factor best known for regulating the expression of antioxidant and detoxification genes. Recent evidence suggested that Nrf2 mediates metabolic reprogramming in cancer cells. However, the role of Nrf2 in the biochemical metabolism of cardiac cells has not been studied. Using LC-MS/MS-based metabolomics, we addressed whether knocking out the Nrf2 gene in AC16 human cardiomyocytes affects metabolic reprogramming by oxidative stress. Profiling the basal level metabolites showed an elevated pentose phosphate pathway and increased levels of sugar alcohols, sorbitol, L-arabitol, xylitol and xylonic acid, in Nrf2 KO cells. With sublethal levels of oxidative stress, depletion of NAD, an increase of GDP and elevation of sugar alcohols, sorbitol and dulcitol, were detected in parent wild type (WT) cells. Knocking out Nrf2 did not affect these changes. Biochemical assays confirmed depletion of NAD in WT and Nrf2 KO cells due to H2O2 treatment. These data support that although Nrf2 deficiency caused baseline activation of the pentose phosphate pathway and sugar alcohol synthesis, a brief exposure to none-lethal doses of H2O2 caused NAD depletion in an Nrf2 independent manner. Loss of NAD may contribute to oxidative stress associated cell degeneration as observed with aging, diabetes and heart failure.

Early Breast Cancer Detection Using Untargeted and Targeted Metabolomics.

Breast cancer (BC) is a common cause of morbidity and mortality, particularly in women. Moreover, the discovery of diagnostic biomarkers for early BC remains a challenging task. Previously, we [Jasbi et al. J. Chromatogr. B. 2019, 1105, 26-37] demonstrated a targeted metabolic profiling approach capable of identifying metabolite marker candidates that could enable highly sensitive and specific detection of BC. However, the coverage of this targeted method was limited and exhibited suboptimal classification of early BC (EBC). To expand the metabolome coverage and articulate a better panel of metabolites or mass spectral features for classification of EBC, we evaluated untargeted liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) data, both individually as well as in conjunction with previously published targeted LC-triple quadruple (QQQ)-MS data. Variable importance in projection scores were used to refine the biomarker panel, whereas orthogonal partial least squares-discriminant analysis was used to operationalize the enhanced biomarker panel for early diagnosis. In this approach, 33 altered metabolites/features were detected by LC-QTOF-MS from 124 BC patients and 86 healthy controls. For EBC diagnosis, significance testing and analysis of the area under receiver operating characteristic (AUROC) curve identified six metabolites/features [ethyl (R)-3-hydroxyhexanoate; caprylic acid; hypoxanthine; and m/z 358.0018, 354.0053, and 356.0037] with p < 0.05 and AUROC > 0.7. These metabolites informed the construction of EBC diagnostic models; evaluation of model performance for the prediction of EBC showed an AUROC = 0.938 (95% CI: 0.895-0.975), with sensitivity = 0.90 when specificity = 0.90. Using the combined untargeted and targeted data set, eight metabolic pathways of potential biological relevance were indicated to be significantly altered as a result of EBC. Metabolic pathway analysis showed fatty acid and aminoacyl-tRNA biosynthesis as well as inositol phosphate metabolism to be most impacted in response to the disease. The combination of untargeted and targeted metabolomics platforms has provided a highly predictive and accurate method for BC and EBC diagnosis from plasma samples. Furthermore, such a complementary approach yielded critical information regarding potential pathogenic mechanisms underlying EBC that, although critical to improved prognosis and enhanced survival, are understudied in the current literature. All mass spectrometry data and deidentified subject metadata analyzed in this study have been deposited to Mendeley Data and are publicly available (DOI: 10.17632/kcjg8ybk45.1).

Metabolic Profiling of Neocortical Tissue Discriminates Alzheimer's Disease from Mild Cognitive Impairment, High Pathology Controls, and Normal Controls.

Alzheimer's disease (AD) is the most common cause of dementia, accounting for an estimated 60-80% of cases, and is the sixth-leading cause of death in the United States. While considerable advancements have been made in the clinical care of AD, it remains a complicated disorder that can be difficult to identify definitively in its earliest stages. Recently, mass spectrometry (MS)-based metabolomics has shown significant potential for elucidation of disease mechanisms and identification of therapeutic targets as well diagnostic and prognostic markers that may be useful in resolving some of the difficulties affecting clinical AD studies, such as effective stratification. In this study, complementary gas chromatography- and liquid chromatography-MS platforms were used to detect and monitor 2080 metabolites and features in 48 postmortem tissue samples harvested from the superior frontal gyrus of male and female subjects. Samples were taken from four groups: 12 normal control (NC) patients, 12 cognitively normal subjects characterized as high pathology controls (HPC), 12 subjects with nonspecific mild cognitive impairment (MCI), and 12 subjects with AD. Multivariate statistics informed the construction and cross-validation (p < 0.01) of partial least squares-discriminant analysis (PLS-DA) models defined by a nine-metabolite panel of disease markers (lauric acid, stearic acid, myristic acid, palmitic acid, palmitoleic acid, and four unidentified mass spectral features). Receiver operating characteristic analysis showed high predictive accuracy of the resulting PLS-DA models for discrimination of NC (97%), HPC (92%), MCI (∼96%), and AD (∼96%) groups. Pathway analysis revealed significant disturbances in lysine degradation, fatty acid metabolism, and the degradation of branched-chain amino acids. Network analysis showed significant enrichment of 11 enzymes, predominantly within the mitochondria. The results expand basic knowledge of the metabolome related to AD and reveal pathways that can be targeted therapeutically. This study also provides a promising basis for the development of larger multisite projects to validate these candidate markers in readily available biospecimens such as blood to enable the effective screening, rapid diagnosis, accurate surveillance, and therapeutic monitoring of AD. All raw mass spectrometry data have been deposited to MassIVE (data set identifier MSV000087165).

Adsorption and Reductive Defluorination of Perfluorooctanoic Acid over Palladium Nanoparticles.

Per- and polyfluoroalkyl substances (PFASs) comprise a group of widespread and recalcitrant contaminants that are attracting increasing concern due to their persistence and adverse health effects. This study evaluated removal of one of the most prevalent PFAS, perfluorooctanoic acid (PFOA), in H2-based membrane catalyst-film reactors (H2-MCfRs) coated with palladium nanoparticles (Pd0NPs). Batch tests documented that Pd0NPs catalyzed hydrodefluorination of PFOA to partially fluorinated and nonfluorinated octanoic acids; the first-order rate constant for PFOA removal was 0.030 h-1, and a maximum defluorination rate was 16 µM/h in our bench-scale MCfR. Continuous-flow tests achieved stable long-term depletion of PFOA to below the EPA health advisory level (70 ng/L) for up to 70 days without catalyst loss or deactivation. Two distinct mechanisms for Pd0-based PFOA removal were identified based on insights from experimental results and density functional theory (DFT) calculations: (1) nonreactive chemisorption of PFOA in a perpendicular orientation on empty metallic surface sites and (2) reactive defluorination promoted by physiosorption of PFOA in a parallel orientation above surface sites populated with activated hydrogen atoms (Hads*). Pd0-based catalytic reduction chemistry and continuous-flow treatment may be broadly applicable to the ambient-temperature destruction of other PFAS compounds.

Hydrodefluorination of Perfluorooctanoic Acid in the H2-Based Membrane Catalyst-Film Reactor with Platinum Group Metal Nanoparticles: Pathways and Optimal Conditions.

PFAAs (perfluorinated alkyl acids) have become a concern because of their widespread pollution and persistence. A previous study introduced a novel approach for removing and hydrodefluorinating perfluorooctanoic acid (PFOA) using palladium nanoparticles (Pd0NPs) in situ synthesized on H2-gas-transfer membranes. This work focuses on the products, pathways, and optimal catalyst conditions. Kinetic tests tracking PFOA removal, F- release, and hydrodefluorination intermediates documented that PFOA was hydrodefluorinated by a mixture of parallel and stepwise reactions on the Pd0NP surfaces. Slow desorption of defluorination products lowered the catalyst's activity for hydrodefluorination. Of the platinum group metals studied, Pd was overall superior to Pt, Rh, and Ru for hydrodefluorinating PFOA. pH had a strong influence on performance: PFOA was more strongly adsorbed at higher pH, but lower pH promoted defluorination. A membrane catalyst-film reactor (MCfR), containing an optimum loading of 1.2 g/m2 Pd0 for a total Pd amount of 22 mg, removed 3 mg/L PFOA during continuous flow for 90 days, and the removal flux was as high as 4 mg PFOA/m2/d at a steady state. The EPA health advisory level (70 ng/L) also was achieved over the 90 days with the influent PFOA at an environmentally relevant concentration of 500 ng/L. The results document a sustainable catalytic method for the detoxification of PFOA-contaminated water.

Evaluation of potential metabolomic-based biomarkers of protein, carbohydrate and fat intakes using a controlled feeding study.

PURPOSE: Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-h urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). METHODS: A 2-week controlled feeding study mimicking the participants' habitual diets was conducted among 153 postmenopausal women from the Women's Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R2) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R2 reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Protocol of the Snuggle Bug/Acurrucadito Study: a longitudinal study investigating the influences of sleep-wake patterns and gut microbiome development in infancy on rapid weight gain, an early risk factor for obesity.

BACKGROUND: Overweight, obesity, and associated comorbidities are a pressing global issue among children of all ages, particularly among low-income populations. Rapid weight gain (RWG) in the first 6 months of infancy contributes to childhood obesity. Suboptimal sleep-wake patterns and gut microbiota (GM) have also been associated with childhood obesity, but little is known about their influences on early infant RWG. Sleep may alter the GM and infant metabolism, and ultimately impact obesity; however, data on the interaction between sleep-wake patterns and GM development on infant growth are scarce. In this study, we aim to investigate associations of infant sleep-wake patterns and GM development with RWG at 6 months and weight gain at 12 months. We also aim to evaluate whether temporal interactions exist between infant sleep-wake patterns and GM, and if these relations influence RWG. METHODS: The Snuggle Bug/ Acurrucadito study is an observational, longitudinal study investigating whether 24-h, actigraphy-assessed, sleep-wake patterns and GM development are associated with RWG among infants in their first year. Based on the Ecological Model of Growth, we propose a novel conceptual framework to incorporate sleep-wake patterns and the GM as metabolic contributors for RWG in the context of maternal-infant interactions, and familial and socio-physical environments. In total, 192 mother-infant pairs will be recruited, and sleep-wake patterns and GM development assessed at 3 and 8 weeks, and 3, 6, 9, and 12 months postpartum. Covariates including maternal and child characteristics, family and environmental factors, feeding practices and dietary intake of infants and mothers, and stool-derived metabolome and exfoliome data will be assessed. The study will apply machine learning techniques combined with logistic time-varying effect models to capture infant growth and aid in elucidating the dynamic associations between study variables and RWG. DISCUSSION: Repeated, valid, and objective assessment at clinically and developmentally meaningful intervals will provide robust measures of longitudinal sleep, GM, and growth. Project findings will provide evidence for future interventions to prevent RWG in infancy and subsequent obesity. The work also may spur the development of evidence-based guidelines to address modifiable factors that influence sleep-wake and GM development and prevent childhood obesity.

Pan-cancer transcriptional signatures predictive of oncogenic mutations reveal that Fbw7 regulates cancer cell oxidative metabolism.

The Fbw7 (F-box/WD repeat-containing protein 7) ubiquitin ligase targets multiple oncoproteins for degradation and is commonly mutated in cancers. Like other pleiotropic tumor suppressors, Fbw7's complex biology has impeded our understanding of how Fbw7 mutations promote tumorigenesis and hindered the development of targeted therapies. To address these needs, we employed a transfer learning approach to derive gene-expression signatures from The Cancer Gene Atlas datasets that predict Fbw7 mutational status across tumor types and identified the pathways enriched within these signatures. Genes involved in mitochondrial function were highly enriched in pan-cancer signatures that predict Fbw7 mutations. Studies in isogenic colorectal cancer cell lines that differed in Fbw7 mutational status confirmed that Fbw7 mutations increase mitochondrial gene expression. Surprisingly, Fbw7 mutations shifted cellular metabolism toward oxidative phosphorylation and caused context-specific metabolic vulnerabilities. Our approach revealed unexpected metabolic reprogramming and possible therapeutic targets in Fbw7-mutant cancers and provides a framework to study other complex, oncogenic mutations.

A four-week high fat diet does not alter plasma glucose or metabolic physiology in wild-caught mourning doves (Zenaida macroura).

The aim of this study was to determine the metabolic effects of a four-week 60% high-fat (HF) diet on mourning doves. Plasma glucose concentrations are, on average, 1.5-2 times higher in birds than in mammals of similar body mass, but birds have innate mechanisms that protect them from high blood glucose-associated pathologies normally developed in mammals. Elucidating these mechanisms may help develop therapeutics for treatment of human diabetes-related complications. A high fat (HF) diet is commonly used in rodents to investigate metabolic disease. We hypothesized that this diet in doves would elevate plasma glucose and alter metabolic physiology compared to the control (CON) diet. Following the four-week long diets, doves were euthanized, and we collected blood, liver, pectoralis muscles, and kidney samples. Contrary to the rodent-models, HF-fed birds did not have increased plasma glucose concentrations relative to CON-fed birds. Metabolomic analyses revealed no group differences in plasma, liver, pectoralis muscle, or kidney metabolites (FDR q-value>0.05 for all). Principal component analysis score plots of metabolites showed no separation between groups, and pathway analyses revealed no significantly altered metabolic pathways between groups (191 pathways across tissues, FDR q-value>0.05). Body mass, plasma uric acid, glucose, and insulin as well as liver and pectoralis muscle glycogen and triglycerides did not differ between groups (p > 0.05 for all). In conclusion, a four-week long high fat diet did not alter plasma glucose concentrations or metabolic physiology in mourning doves, indicating that these birds have mechanisms that allow them to avoid high fat diet-induced pathologies seen in mammals.