Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry.

Dysregulated lipid metabolism underpins many chronic diseases including cardiometabolic diseases. Mass spectrometry-based lipidomics is an important tool for understanding mechanisms of lipid dysfunction and is widely applied in epidemiology and clinical studies. With ever-increasing sample numbers, single batch acquisition is often unfeasible, requiring advanced methods that are accurate and robust to batch-to-batch and interday analytical variation. Herein, an optimized comprehensive targeted workflow for plasma and serum lipid quantification is presented, combining stable isotope internal standard dilution, automated sample preparation, and ultrahigh performance liquid chromatography-tandem mass spectrometry with rapid polarity switching to target 1163 lipid species spanning 20 subclasses. The resultant method is robust to common sources of analytical variation including blood collection tubes, hemolysis, freeze-thaw cycles, storage stability, analyte extraction technique, interinstrument variation, and batch-to-batch variation with 820 lipids reporting a relative standard deviation of <30% in 1048 replicate quality control plasma samples acquired across 16 independent batches (total injection count = 6142). However, sample hemolysis of ≥0.4% impacted lipid concentrations, specifically for phosphatidylethanolamines (PEs). Low interinstrument variability across two identical LC-MS systems indicated feasibility for intra/inter-lab parallelization of the assay. In summary, we have optimized a comprehensive lipidomic protocol to support rigorous analysis for large-scale, multibatch applications in precision medicine. The mass spectrometry lipidomics data have been deposited to massIVE: data set identifiers MSV000090952 and 10.25345/C5NP1WQ4S.

Nonsevere Burn Induces a Prolonged Systemic Metabolic Phenotype Indicative of a Persistent Inflammatory Response Postinjury.

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic comorbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on the impact of nonsevere injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of a nonsevere burn injury, longitudinal plasma was collected from adults (n = 35) who presented at hospital with a nonsevere burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from nonburn control participants (n = 14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoprotein signatures and 852 lipid species from across 20 subclasses. Multivariate data modeling (orthogonal projections to latent structures-discriminate analysis; OPLS-DA) revealed alterations in lipoprotein and lipid metabolism when comparing the baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value < 1.0e-4), low density lipoprotein-2 subfractions (variable importance in projection score; VIP > 6.83e-1) and monoacyglyceride (20:4) (p-value < 1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP > 7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols, and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of a nonsevere burn injury. The phenotype is indicative of an acute inflammatory profile that continues to be sustained postinjury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have an elevated incidence postburn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalize intervention strategies, and improve acute care, reducing the risk of chronic comorbidity.

Characterizing the plasma metabolome during 14 days of live-high, train-low simulated altitude: A metabolomic approach.

NEW FINDINGS: What is the central question of this study? Does 14 days of live-high, train-low simulated altitude alter an individual's metabolomic/metabolic profile? What is the main finding and its importance? This study demonstrated that ∼200 h of moderate simulated altitude exposure resulted in greater variance in measured metabolites between subject than within subject, which indicates individual variability during the adaptive phase to altitude exposure. In addition, metabolomics results indicate that altitude alters multiple metabolic pathways, and the time course of these pathways is different over 14 days of altitude exposure. These findings support previous literature and provide new information on the acute adaptation response to altitude. ABSTRACT: The purpose of this study was to determine the influence of 14 days of normobaric hypoxic simulated altitude exposure at 3000 m on the human plasma metabolomic profile. For 14 days, 10 well-trained endurance runners (six men and four women; 29 ± 7 years of age) lived at 3000 m simulated altitude, accumulating 196.4 ± 25.6 h of hypoxic exposure, and trained at ∼600 m. Resting plasma samples were collected at baseline and on days 3 and 14 of altitude exposure and stored at -80°C. Plasma samples were analysed using liquid chromatography-high-resolution mass spectrometry to construct a metabolite profile of altitude exposure. Mass spectrometry of plasma identified 36 metabolites, of which eight were statistically significant (false discovery rate probability 0.1) from baseline to either day 3 or day 14. Specifically, changes in plasma metabolites relating to amino acid metabolism (tyrosine and proline), glycolysis (adenosine) and purine metabolism (adenosine) were observed during altitude exposure. Principal component canonical variate analysis showed significant discrimination between group means (P < 0.05), with canonical variate 1 describing a non-linear recovery trajectory from baseline to day 3 and then back to baseline by day 14. Conversely, canonical variate 2 described a weaker non-recovery trajectory and increase from baseline to day 3, with a further increase from day 3 to 14. The present study demonstrates that metabolomics can be a useful tool to monitor metabolic changes associated with altitude exposure. Furthermore, it is apparent that altitude exposure alters multiple metabolic pathways, and the time course of these changes is different over 14 days of altitude exposure.

Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Untargeted metabolomics of neuronal cell culture: A model system for the toxicity testing of insecticide chemical exposure.

Toxicity testing is essential for the protection of human health from exposure to toxic environmental chemicals. As traditional toxicity testing is carried out using animal models, mammalian cell culture models are becoming an increasingly attractive alternative to animal testing. Combining the use of mammalian cell culture models with screening-style molecular profiling technologies, such as metabolomics, can uncover previously unknown biochemical bases of toxicity. We have used a mass spectrometry-based untargeted metabolomics approach to characterize for the first time the changes in the metabolome of the B50 cell line, an immortalised rat neuronal cell line, following acute exposure to two known neurotoxic chemicals that are common environmental contaminants; the pyrethroid insecticide permethrin and the organophosphate insecticide malathion. B50 cells were exposed to either the dosing vehicle (methanol) or an acute dose of either permethrin or malathion for 6 and 24 hours. Intracellular metabolites were profiled by gas chromatography-mass spectrometry. Using principal components analysis, we selected the key metabolites whose abundance was altered by chemical exposure. By considering the major fold changes in abundance (>2.0 or <0.5 from control) across these metabolites, we were able to elucidate important cellular events associated with toxic exposure including disrupted energy metabolism and attempted protective mechanisms from excitotoxicity. Our findings illustrate the ability of mammalian cell culture metabolomics to detect finer metabolic effects of acute exposure to known toxic chemicals, and validate the need for further development of this process in the application of trace-level dose and chronic toxicity studies, and toxicity testing of unknown chemicals.

Gas chromatography-mass spectrometry-based metabolite profiling of Salmonella enterica serovar Typhimurium differentiates between biofilm and planktonic phenotypes.

The aim of this study was to utilize gas chromatography coupled with mass spectrometry (GC-MS) to compare and identify patterns of biochemical change between Salmonella cells grown in planktonic and biofilm phases and Salmonella biofilms of different ages. Our results showed a clear separation between planktonic and biofilm modes of growth. The majority of metabolites contributing to variance between planktonic and biofilm supernatants were identified as amino acids, including alanine, glutamic acid, glycine, and ornithine. Metabolites contributing to variance in intracellular profiles were identified as succinic acid, putrescine, pyroglutamic acid, and N-acetylglutamic acid. Principal-component analysis revealed no significant differences between the various ages of intracellular profiles, which would otherwise allow differentiation of biofilm cells on the basis of age. A shifting pattern across the score plot was illustrated when analyzing extracellular metabolites sampled from different days of biofilm growth, and amino acids were again identified as the metabolites contributing most to variance. An understanding of biofilm-specific metabolic responses to perturbations, especially antibiotics, can lead to the identification of novel drug targets and potential therapies for combating biofilm-associated diseases. We concluded that under the conditions of this study, GC-MS can be successfully applied as a high-throughput technique for "bottom-up" metabolomic biofilm research.

Influence of glucocorticoids, neuregulin-1ß, and sex on surfactant phospholipid secretion from type II cells.

Glucocorticoids induce lung fibroblasts to produce fibroblast-pneumocyte factor, a peptide that stimulates type II cells to synthesize pulmonary surfactant. This effect is known to be more apparent in cells derived from female fetuses, a characteristic that has been attributed to sex-linked differences in the fibroblasts. In the current study, it has been shown that dexamethasone enhances both ß-adrenergic receptor (ß-AR) activity (1.3- to 1.6-fold increase) and (-)-isoproterenol-induced secretion of surfactant (1.8- to 1.9-fold increase) in type II cells. However, fibroblast-conditioned media (FCM), prepared in the presence of dexamethasone, generates a much greater response to (-)-isoproterenol (3.1- to 3.8-fold increase). Furthermore, each of these effects is more pronounced if both cell types are female-derived. It is hypothesized that the enhanced response to glucocorticoids is the result of a synergistic effect between the steroid and a component of FCM. Neuregulin-1ß (NRG1ß), which is elevated in FCM generated in the presence of dexamethasone, influences not only the rate of surfactant secretion and the ß-AR activity in type II cells, but also enhances in both sexes the cellular response to (-)-isoproterenol. These results suggest that NRG1ß might be more effective than glucocorticoids in treating prematurely born male infants, which are known to respond poorly to glucocorticoids. Given that glucocorticoids are known to induce higher levels of ß-AR mRNA, the effect of NRG1ß, alone and in combination with dexamethasone, on ß-AR gene expression was measured using qRT-PCR. Whereas NRG1ß had no effect alone, in combination with dexamethasone it produced up to a 4.2-fold elevation in the level of ß-AR mRNA.

1H NMR spectroscopic characterisation of HepG2 cells as a model metabolic system for toxicology studies.

The immortalised human hepatocellular HepG2 cell line is commonly used for toxicology studies as an alternative to animal testing due to its characteristic liver-distinctive functions. However, little is known about the baseline metabolic changes within these cells upon toxin exposure. We have applied high-resolution 1H Nuclear Magnetic Resonance (NMR) spectroscopy to characterise the biochemical composition of HepG2 cells at baseline and post-exposure to hydrogen peroxide (H2O2). Metabolic profiles of live cells, cell extracts, and their spent media supernatants were obtained using 1H high-resolution magic angle spinning (HR-MAS) NMR and 1H NMR spectroscopic techniques. Orthogonal partial least squares discriminant analysis (O-PLS-DA) was used to characterise the metabolites that differed between the baseline and H2O2 treated groups. The results showed that H2O2 caused alterations to 10 metabolites, including acetate, glutamate, lipids, phosphocholine, and creatine in the live cells; 25 metabolites, including acetate, alanine, adenosine diphosphate (ADP), aspartate, citrate, creatine, glucose, glutamine, glutathione, and lactate in the cell extracts, and 22 metabolites, including acetate, alanine, formate, glucose, pyruvate, phenylalanine, threonine, tryptophan, tyrosine, and valine in the cell supernatants. At least 10 biochemical pathways associated with these metabolites were disrupted upon toxin exposure, including those involved in energy, lipid, and amino acid metabolism. Our findings illustrate the ability of NMR-based metabolic profiling of immortalised human cells to detect metabolic effects on central metabolism due to toxin exposure. The established data sets will enable more subtle biochemical changes in the HepG2 model cell system to be identified in future toxicity testing.

Pharmacokinetics and safety of deferasirox in subjects with chronic kidney disease undergoing haemodialysis.

AIM: Treatment of chronic kidney disease (CKD) includes parenteral iron therapy, and these infusions can lead to iron overload. Secondary iron overload is typically treated with iron chelators, of which deferasirox is one of the most promising. However, it has not been studied in patients with CKD and iron overload. METHODS: A pilot study was conducted to evaluate the pharmacokinetics and safety of deferasirox in eight haemodialysis-dependent patients, who were receiving intravenous iron for treatment of anaemia of CKD. Deferasirox was administered at two doses (10 mg/kg and 15 mg/kg), either acute (once daily for 2 days) or steady-state (once daily for 2 weeks). RESULTS: A dose of 10 mg/kg in either protocol was not sufficient to achieve a plasma concentration in the therapeutic range (acute peak 14.1 and steady-state 22.8 µmol/L), while 15 mg/kg in either protocol maintained plasma concentration well above this range (acute peak 216 and steady-state 171 µmol/L). Plasma concentration observed at 15 mg/kg was well above that expected for this dose (40-50 µmol/L), although no adverse clinical events were observed. CONCLUSION: This study highlights the need to profile drugs such as deferasirox in specific patient groups, such as those with CKD and iron overload.

Development of a non-targeted metabolomics method to investigate urine in a rat model of polycystic kidney disease.

AIM: The purpose of this research was to use metabolomics to investigate the cystic phenotype in the Lewis polycystic kidney rat. METHODS: Spot urine samples were collected from four male Lewis control and five male Lewis polycystic kidney rats aged 5 weeks, before kidney function was significantly impaired. Metabolites were extracted from urine and analysed using gas chromatography-mass spectrometry. Principal component analysis was used to determine key metabolites contributing to the variance observed between sample groups. RESULTS: With the development of a metabolomics method to analyse Lewis and Lewis polycystic kidney rat urine, 2-ketoglutaric acid, allantoin, uric acid and hippuric acid were identified as potential biomarkers of cystic disease in the rat model. CONCLUSION: The findings of this study demonstrate the potential of metabolomics to further investigate kidney disease.

Liquid chromatography tandem mass spectrometry for the simultaneous quantitative analysis of ketamine and medetomidine in ovine plasma.

Ketamine and medetomidine are commonly combined to sedate or anaesthetize a wide range of animal species. Despite this, there are few methods for the simultaneous quantitative analysis of the two drugs. This study describes the use of solid-phase extraction sample preparation followed by liquid chromatography-tandem mass spectrometry for the quantitative analysis of both drugs in ovine plasma. Extraction recovery was 93% for ketamine and 95% for medetomidine. The lowest limit of detection for ketamine was 1 ng/mL and for medetomidine 2 ng/mL, with linearity greater than 0.99 for both. Intra-day and inter-day precisions for both drugs were less than 10 and 7%, respectively. Application of the method to samples obtained from pregnant ewes and their fetuses showed placental transfer of the drugs over time such that there was no significant difference in plasma concentration at delivery. In summary, a validated method has been developed for the simultaneous quantification of ketamine and medetomidine in ovine plasma samples which can be used to study the pharmacokinetics of these drugs.

Branched-chain amino acid supplementation improves cycling performance in untrained cyclists.

OBJECTIVES: To investigate the effects of acute branched-chain amino acid (BCAA) supplementation on cycling performance and neuromuscular fatigue during a prolonged, self-paced cycling time-trial. DESIGN: Randomised double-blind counterbalanced crossover. METHODS: Eighteen recreationally active men (mean±SD; age: 24.7±4.8 years old; body-weight, BW: 67.1±6.1kg; height: 171.7±4.9cm) performed a cycling time-trial on an electromagnetically-braked cycle ergometer. Participants were instructed to complete the individualised total work in the shortest time possible, while ingesting either BCAAs (pre-exercise: 0.084gkg-1 BW; during exercise: 0.056gkg-1h-1) or a non-caloric placebo solution. Rating of perceived exertion, power, cadence and heart rate were recorded throughout, while maximal voluntary contraction, muscle voluntary activation level and electrically evoked torque using single and doublet stimulations were assessed at baseline, immediately post-exercise and 20-min post-exercise. RESULTS: Supplementation with BCAA reduced (287.9±549.7s; p=0.04) time-to-completion and ratings of perceived exertion (p≤0.01), while concomitantly increasing heart rate (p=0.02). There were no between-group differences (BCAA vs placebo) in any of the neuromuscular parameters, but significant decreases (All p≤0.01) in maximal voluntary contraction, muscle voluntary activation level and electrically evoked torque (single and doublet stimulations) were recorded immediately following the trial, and these did not recover to pre-exercise values by the 20min recovery time-point. CONCLUSIONS: Compared to a non-caloric placebo, acute BCAA supplementation significantly improved performance in cycling time-trial among recreationally active individuals without any notable changes in either central or peripheral factors. This improved performance with acute BCAA supplementation was associated with a reduced rating of perceived exertion.

Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases.

Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

Sample Preparation and Reporting Standards for Metabolomics of Adherent Mammalian Cells.

Metabolomics is an analytical technique that investigates the small molecules present within a biological system. Metabolomics of cultured cells allows profiling of the metabolic chemicals involved in a cell type-specific system and the response of that metabolome to external challenges, such as change in environment or exposure to drugs or toxins. The numerous benefits of in vitro metabolomics include a much greater control of external variables and reduced ethical concerns. There is potential for metabolomics of mammalian cells to uncover new information on mechanisms of action for drugs or toxins or to provide a more sensitive, human-specific early risk assessment in drug development or toxicology investigations. One way to achieve stronger biological outcomes from metabolomic data is via the use of these mammalian cultured cell models, particularly in a high-throughput context. With the sensitivity and quantity of data that metabolomics is able to provide, it is important to ensure that the sampling techniques have minimal interference when it comes to interpretation of any observed shifts in the metabolite profile. Here we describe a sampling procedure designed to ensure that the effects seen in metabolomic analyses are explained fully by the experimental factor and not other routine culture-specific activities.

Untargeted gas chromatography-mass spectrometry-based metabolomics analysis of kidney and liver tissue from the Lewis Polycystic Kidney rat.

Polycystic kidney disease (PKD) encompasses a spectrum of inherited disorders that lead to end-stage renal disease (ESRD). There is no cure for PKD and current treatment options are limited to renal replacement therapy and transplantation. A better understanding of the pathobiology of PKD is needed for the development of new, less invasive treatments. The Lewis Polycystic Kidney (LPK) rat phenotype has been characterized and classified as a model of nephronophthisis (NPHP9, caused by mutation of the Nek8 gene) for which polycystic kidneys are one of the main pathologic features. The aim of this study was to use a GC-MS-based untargeted metabolomics approach to determine key biochemical changes in kidney and liver tissue of the LPK rat. Tissues from 16-week old LPK (n = 10) and Lewis age- and sex-matched control animals (n = 11) were used. Principal component analysis (PCA) distinguished signal corrected metabolite profiles from Lewis and LPK rats for kidney (PC-1 77%) and liver (PC-1 46%) tissue. There were marked differences in the metabolite profiles of the kidney tissues with 122 deconvoluted features significantly different between the LPK and Lewis strains. The metabolite profiles were less marked between strains for liver samples with 30 features significantly different. Five biochemical pathways showed three or more significantly altered metabolites: transcription/translation, arginine and proline metabolism, alpha-linolenic and linoleic acid metabolism, the citric acid cycle, and the urea cycle. The results of this study validate and complement the current literature and are consistent with the understood pathobiology of PKD.

Untargeted Metabolomic Analysis of Rat Neuroblastoma Cells as a Model System to Study the Biochemical Effects of the Acute Administration of Methamphetamine.

Methamphetamine is an illicit psychostimulant drug that is linked to a number of diseases of the nervous system. The downstream biochemical effects of its primary mechanisms are not well understood, and the objective of this study was to investigate whether untargeted metabolomic analysis of an in vitro model could generate data relevant to what is already known about this drug. Rat B50 neuroblastoma cells were treated with 1 mM methamphetamine for 48 h, and both intracellular and extracellular metabolites were profiled using gas chromatography⁻mass spectrometry. Principal component analysis of the data identified 35 metabolites that contributed most to the difference in metabolite profiles. Of these metabolites, the most notable changes were in amino acids, with significant increases observed in glutamate, aspartate and methionine, and decreases in phenylalanine and serine. The data demonstrated that glutamate release and, subsequently, excitotoxicity and oxidative stress were important in the response of the neuronal cell to methamphetamine. Following this, the cells appeared to engage amino acid-based mechanisms to reduce glutamate levels. The potential of untargeted metabolomic analysis has been highlighted, as it has generated biochemically relevant data and identified pathways significantly affected by methamphetamine. This combination of technologies has clear uses as a model for the study of neuronal toxicology.

Characterizing the plasma metabolome during and following a maximal exercise cycling test.

Although complex in nature, a number of metabolites have been implicated in the onset of exercise-induced fatigue. The purpose of this study was to identify changes in the plasma metabolome and specifically, to identify candidate metabolites associated with the onset of fatigue during prolonged cycling. Eighteen healthy and recreationally active men (mean ± SD; age: 24.7 ± 4.8 yr; mass 67.1 ± 6.1 kg; body mass index: 22.8 ± 2.2; peak oxygen uptake: 40.9 ± 6.1 ml·kg-1·min-1) were recruited to this study. Participants performed a prolonged cycling time-to-exhaustion (TTE) test at an intensity corresponding to a fixed blood lactate concentration (3 mmol/l). Plasma samples collected at 10 min of exercise, before fatigue (last sample before fatigue <10 min before fatigue), immediately after fatigue (point of exhaustion), and 20 min after fatigue were assessed using a liquid chromatography-mass spectrometry-based metabolomic approach. Eighty metabolites were putatively identified, with 68 metabolites demonstrating a significant change during the cycling task (duration: ~80.9 ± 13.6 min). A clear multivariate structure in the data was revealed, with the first principal component (36% total variance) describing a continuous increase in metabolite concentration throughout the TTE trial and recovery, whereas the second principal component (14% total variance) showed an increase in metabolite concentration followed by a recovery trajectory, peaking at the point of fatigue. Six clusters of correlated metabolites demonstrating unique metabolite trajectories were identified, including significant separation in the metabolome between prefatigue and postfatigue time points. In accordance with our hypothesis, free-fatty acids and tryptophan contributed to differences in the plasma metabolome at fatigue.NEW & NOTEWORTHY Metabolites have long been implicated in the onset of fatigue. This study applied a metabolomic approach to track 80 plasma-borne metabolites during a cycle to fatigue task. Of these, 68 metabolites demonstrated significant change, with the plasma metabolome at fatigue being clearly distinguishable from other time points. Six unique clusters of metabolites were identified, and free fatty acids were strongly associated with fatigue onset therein lending support to the central fatigue hypothesis.

The Influence of Blood Removal on Pacing During a 4-Minute Cycling Time Trial.

PURPOSE: To examine the influence of manipulating aerobic contribution after whole-blood removal on pacing patterns, performance, and energy contribution during self-paced middle-distance cycling. METHODS: Seven male cyclists (33 ± 8 y) completed an incremental cycling test followed 20 min later by a 4-min self-paced cycling time trial (4MMP) on 6 separate occasions over 42 d. The initial 2 sessions acted as familiarization and baseline testing, after which 470 mL of blood was removed, with the remaining sessions performed 24 h, 7 d, 21 d, and 42 d after blood removal. During all 4MMP trials, power output, oxygen uptake, and aerobic and anaerobic contribution to power were determined. RESULTS: 4MMP average power output significantly decreased by 7% ± 6%, 6% ± 8%, and 4% ± 6% at 24 h, 7 d, and 21 d after blood removal, respectively. Compared with baseline, aerobic contribution during the 4MMP was significantly reduced by 5% ± 4%, 4% ± 5%, and 4% ± 10% at 24 h, 7 d, and 21 d, respectively. The rate of decline in power output on commencement of the 4MMP was significantly attenuated and was 76% ± 20%, 72% ± 24%, and 75% ± 35% lower than baseline at 24 h, 21 d, and 42 d, respectively. CONCLUSION: Removal of 470 mL of blood reduces aerobic energy contribution, alters pacing patterns, and decreases performance during self-paced cycling. These findings indicate the importance of aerobic energy distribution during self-paced middle-distance events.

The potential of metabolomic analysis techniques for the characterisation of α1-adrenergic receptors in cultured N1E-115 mouse neuroblastoma cells.

Several studies of neuropathic pain have linked abnormal adrenergic signalling to the development and maintenance of pain, although the mechanisms underlying this are not yet fully understood. Metabolomic analysis is a technique that can be used to give a snapshot of biochemical status, and can aid in the identification of the mechanisms behind pathological changes identified in cells, tissues and biological fluids. This study aimed to use gas chromatography-mass spectrometry-based metabolomic profiling in combination with reverse transcriptase-polymerase chain reaction and immunocytochemistry to identify functional α1-adrenergic receptors on cultured N1E-115 mouse neuroblastoma cells. The study was able to confirm the presence of mRNA for the α1D subtype, as well as protein expression of the α1-adrenergic receptor. Furthermore, metabolomic data revealed changes to the metabolite profile of cells when exposed to adrenergic pharmacological intervention. Agonist treatment with phenylephrine hydrochloride (10 µM) resulted in altered levels of several metabolites including myo-inositol, glucose, fructose, alanine, leucine, phenylalanine, valine, and n-acetylglutamic acid. Many of the changes observed in N1E-115 cells by agonist treatment were modulated by additional antagonist treatment (prazosin hydrochloride, 100 µM). A number of these changes reflected what is known about the biochemistry of α1-adrenergic receptor activation. This preliminary study therefore demonstrates the potential of metabolomic profiling to confirm the presence of functional receptors on cultured cells.

The bioavailability of medetomidine in eight sheep following oesophageal administration.

There is sound evidence that medetomidine is an effective analgesic for acute pain in sheep. In this study, 15 µg kg(-1) of medetomidine was administered intravenously, and into the oesophagus, in a cross-over study, using eight sheep. Following intravenous administration, medetomidine could be detected in the plasma of these sheep for 120-180 min but following oesophageal administration, medetomidine could not be detected in the plasma of any sheep at any of 17 time points over four days. It is suspected that this is due to high first pass metabolism in the liver. Consequently, we conclude that future studies investigating the use of analgesics in orally-administered osmotic pumps in sheep should consider higher doses of medetomidine (e.g. >100 µg kg(-1)), further investigations into the barriers of medetomidine bioavailability from the sheep gut, liver-bypass drug delivery systems, or other α2-adrenergic agonists (e.g. clonidine or xylazine).