What is in the fish? Collaborative trial in suspect and non-target screening of organic micropollutants using LC- and GC-HRMS.

A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9-69 % of spiked compounds using LC-HRMS and 20-60 % of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants' own suspect lists led to putative identification of on average ∼145 and ∼20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ∼42 and ∼56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values from -9.9 to 16 and mass-to-charge ratios (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.

Fiber-orientation independent component of R2* obtained from single-orientation MRI measurements in simulations and a post-mortem human optic chiasm.

The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, ß1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted ß1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for ß1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects.

A Flexible Tool to Correct Superimposed Mass Isotopologue Distributions in GC-APCI-MS Flux Experiments.

The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.

Towards Unbiased Evaluation of Ionization Performance in LC-HRMS Metabolomics Method Development.

As metabolomics increasingly finds its way from basic science into applied and regulatory environments, analytical demands on nontargeted mass spectrometric detection methods continue to rise. In addition to improved chemical comprehensiveness, current developments aim at enhanced robustness and repeatability to allow long-term, inter-study, and meta-analyses. Comprehensive metabolomics relies on electrospray ionization (ESI) as the most versatile ionization technique, and recent liquid chromatography-high resolution mass spectrometry (LC-HRMS) instrumentation continues to overcome technical limitations that have hindered the adoption of ESI for applications in the past. Still, developing and standardizing nontargeted ESI methods and instrumental setups remains costly in terms of time and required chemicals, as large panels of metabolite standards are needed to reflect biochemical diversity. In this paper, we investigated in how far a nontargeted pilot experiment, consisting only of a few measurements of a test sample dilution series and comprehensive statistical analysis, can replace conventional targeted evaluation procedures. To examine this potential, two instrumental ESI ion source setups were compared, reflecting a common scenario in practical method development. Two types of feature evaluations were performed, (a) summary statistics solely involving feature intensity values, and (b) analyses additionally including chemical interpretation. Results were compared in detail to a targeted evaluation of a large metabolite standard panel. We reflect on the advantages and shortcomings of both strategies in the context of current harmonization initiatives in the metabolomics field.

Depletion of cardiac cardiolipin synthase alters systolic and diastolic function.

Cardiolipin (CL) is a major cardiac mitochondrial phospholipid maintaining regular mitochondrial morphology and function in cardiomyocytes. Cardiac CL production includes its biosynthesis and a CL remodeling process. Here we studied the impact of CL biosynthesis and the enzyme cardiolipin synthase (CLS) on cardiac function. CLS and cardiac CL species were significantly downregulated in cardiomyocytes following catecholamine-induced cardiac damage in mice, accompanied by increased oxygen consumption rates, signs of oxidative stress, and mitochondrial uncoupling. RNAi-mediated cardiomyocyte-specific knockdown of CLS in Drosophila melanogaster resulted in marked cardiac dilatation, severe impairment of systolic performance, and slower diastolic filling velocity assessed by fluorescence-based heart imaging. Finally, we showed that CL72:8 is significantly decreased in cardiac samples from patients with heart failure with reduced ejection fraction (HFrEF). In summary, we identified CLS as a regulator of cardiac function. Considering the cardiac depletion of CL species in HFrEF, pharmacological targeting of CLS may be a promising therapeutic approach.

Simulating Local Deformations in the Human Cortex Due to Blood Flow-Induced Changes in Mechanical Tissue Properties: Impact on Functional Magnetic Resonance Imaging.

Investigating human brain tissue is challenging due to the complexity and the manifold interactions between structures across different scales. Increasing evidence suggests that brain function and microstructural features including biomechanical features are related. More importantly, the relationship between tissue mechanics and its influence on brain imaging results remains poorly understood. As an important example, the study of the brain tissue response to blood flow could have important theoretical and experimental consequences for functional magnetic resonance imaging (fMRI) at high spatial resolutions. Computational simulations, using realistic mechanical models can predict and characterize the brain tissue behavior and give us insights into the consequent potential biases or limitations of in vivo, high-resolution fMRI. In this manuscript, we used a two dimensional biomechanical simulation of an exemplary human gyrus to investigate the relationship between mechanical tissue properties and the respective changes induced by focal blood flow changes. The model is based on the changes in the brain's stiffness and volume due to the vasodilation evoked by neural activity. Modeling an exemplary gyrus from a brain atlas we assessed the influence of different potential mechanisms: (i) a local increase in tissue stiffness (at the level of a single anatomical layer), (ii) an increase in local volume, and (iii) a combination of both effects. Our simulation results showed considerable tissue displacement because of these temporary changes in mechanical properties. We found that the local volume increase causes more deformation and consequently higher displacement of the gyrus. These displacements introduced considerable artifacts in our simulated fMRI measurements. Our results underline the necessity to consider and characterize the tissue displacement which could be responsible for fMRI artifacts.

Liver X Receptor Agonist AZ876 Induces Beneficial Endogenous Cardiac Lipid Reprogramming and Protects Against Isoproterenol-Induced Cardiac Damage.

Background It is known that dietary intake of polyunsaturated fatty acids may improve cardiac function. However, relatively high daily doses are required to achieve sufficient cardiac concentrations of beneficial omega-3 fatty acids. The liver X receptor (LXR) is a nuclear hormone receptor and a crucial regulator of lipid homeostasis in mammals. LXR activation has been shown to endogenously reprogram cellular lipid profiles toward increased polyunsaturated fatty acids levels. Here we studied whether LXR lipid reprogramming occurs in cardiac tissue and exerts cardioprotective actions. Methods and Results Male 129SV mice were treated with the LXR agonist AZ876 (20 µmol/kg per day) for 11 days. From day 6, the mice were injected with the nonselective ß-agonist isoproterenol for 4 consecutive days to induce diastolic dysfunction and subendocardial fibrosis while maintaining systolic function. Treatment with isoproterenol led to a marked impairment of global longitudinal strain and the E/e' ratio of transmitral flow to mitral annular velocity, which were both significantly improved by the LXR agonist. Histological examination showed a significant reduction in isoproterenol-induced subendocardial fibrosis by AZ876. Analysis of the cardiac lipid composition by liquid chromatography-high resolution mass spectrometry revealed a significant increase in cardiac polyunsaturated fatty acids levels and a significant reduction in saturated fatty acids by AZ876. Conclusions The present study provides evidence that the LXR agonist AZ876 prevents subendocardial damage, improves global longitudinal strain and E/e' in a mouse model of isoproterenol-induced cardiac damage, accompanied by an upregulation of cardiac polyunsaturated fatty acids levels. Cardiac LXR activation and beneficial endogenous cardiac lipid reprogramming may provide a new therapeutic strategy in cardiac disease with diastolic dysfunction.

Fat-body brummer lipase determines survival and cardiac function during starvation in Drosophila melanogaster.

The cross talk between adipose tissue and the heart has an increasing importance for cardiac function under physiological and pathological conditions. This study characterizes the role of fat body lipolysis for cardiac function in Drosophila melanogaster. Perturbation of the function of the key lipolytic enzyme, brummer (bmm), an ortholog of the mammalian ATGL (adipose triglyceride lipase) exclusively in the fly's fat body, protected the heart against starvation-induced dysfunction. We further provide evidence that this protection is caused by the preservation of glycerolipid stores, resulting in a starvation-resistant maintenance of energy supply and adequate cardiac ATP synthesis. Finally, we suggest that alterations of lipolysis are tightly coupled to lipogenic processes, participating in the preservation of lipid energy substrates during starvation. Thus, we identified the inhibition of adipose tissue lipolysis and subsequent energy preservation as a protective mechanism against cardiac dysfunction during catabolic stress.

Tailored Mobility in a Zeolite Imidazolate Framework (ZIF) Antibody Conjugate*.

Zeolitic imidazolate framework (ZIF) hybrid fluorescent nanoparticles and ZIF antibody conjugates have been synthesized, characterized, and employed in lateral-flow immunoassay (LFIA). The bright fluorescence of the conjugates and the possibility to tailor their mobility gives a huge potential for diagnostic assays. An enzyme-linked immunosorbent assay (ELISA) with horseradish peroxidase (HRP) as label, proved the integrity, stability, and dispersibility of the antibody conjugates, LC-MS/MS provided evidence that a covalent link was established between these metal-organic frameworks and lysine residues in IgG antibodies.

Systematic Identification of MACC1-Driven Metabolic Networks in Colorectal Cancer.

MACC1 is a prognostic and predictive metastasis biomarker for more than 20 solid cancer entities. However, its role in cancer metabolism is not sufficiently explored. Here, we report on how MACC1 impacts the use of glucose, glutamine, lactate, pyruvate and fatty acids and show the comprehensive analysis of MACC1-driven metabolic networks. We analyzed concentration-dependent changes in nutrient use, nutrient depletion, metabolic tracing employing 13C-labeled substrates, and in vivo studies. We found that MACC1 permits numerous effects on cancer metabolism. Most of those effects increased nutrient uptake. Furthermore, MACC1 alters metabolic pathways by affecting metabolite production or turnover from metabolic substrates. MACC1 supports use of glucose, glutamine and pyruvate via their increased depletion or altered distribution within metabolic pathways. In summary, we demonstrate that MACC1 is an important regulator of metabolism in cancer cells.

Abundance, fatty acid composition and saturation index of neutral lipids in colorectal cancer cell lines.

Lipid droplets, the dynamic organelles that store triglycerides (TG) and cholesterol esters (CE), are highly accumulated in colon cancer cells. This work studies the TG and CE subspecies profile in colon carcinoma cell lines, SW480 derived from primary tumor, and SW620 derived from a metastasis of the same tumor. It was previously reported that the total TG and CE content is dramatically higher in SW620 cells; however, TG and CE subspecies profile has not been investigated in detail. The work presented here confirms that the total TG and CE content is significantly higher in the SW620 cells. Moreover, the fatty acid (FA) composition of TG is significantly altered in the SW620 cells, with significant decrease in the abundance of saturated triglycerides. This resulted in a significantly decreased TG saturation index in the SW620 cells. The saturation index of CE was also significantly decreased in the SW620 cells.

Apparent thinning of human visual cortex during childhood is associated with myelination.

Human cortex appears to thin during childhood development. However, the underlying microstructural mechanisms are unknown. Using functional magnetic resonance imaging (fMRI), quantitative MRI (qMRI), and diffusion MRI (dMRI) in children and adults, we tested what quantitative changes occur to gray and white matter in ventral temporal cortex (VTC) from childhood to adulthood, and how these changes relate to cortical thinning. T1 relaxation time from qMRI and mean diffusivity (MD) from dMRI provide independent and complementary measurements of microstructural properties of gray and white matter tissue. In face- and character-selective regions in lateral VTC, T1 and MD decreased from age 5 to adulthood in mid and deep cortex, as well as in their adjacent white matter. T1 reduction also occurred longitudinally in children's brain regions. T1 and MD decreases 1) were consistent with tissue growth related to myelination, which we verified with adult histological myelin stains, and 2) were correlated with apparent cortical thinning. In contrast, in place-selective cortex in medial VTC, we found no development of T1 or MD after age 5, and thickness was related to cortical morphology. These findings suggest that lateral VTC likely becomes more myelinated from childhood to adulthood, affecting the contrast of MR images and, in turn, the apparent gray-white boundary. These findings are important because they suggest that VTC does not thin during childhood but instead gets more myelinated. Our data have broad ramifications for understanding both typical and atypical brain development using advanced in vivo quantitative measurements and clinical conditions implicating myelin.

Cancer cell lipid class homeostasis is altered under nutrient-deprivation but stable under hypoxia.

BACKGROUND: Cancer cells modify the balance between fatty acid (FA) synthesis and uptake under metabolic stress, induced by oxygen/nutrient deprivation. These modifications were shown to alter the levels of individual triglyceride (TG) or phospholipid sub-species. To attain a holistic overview of the lipidomic profiles of cancer cells under stress we performed a broad lipidomic assay, comprising 244 lipids from six major classes. This assay allowed us to perform robust analyses and assess the changes in averages of broader lipid-classes, stratified on the basis of saturation index of their fatty-acyl side chains. METHODS: Global lipidomic profiling using Liquid Chromatography-Mass Spectrometry was performed to assess lipidomic profiles of biologically diverse cancer cell lines cultivated under metabolically stressed conditions. RESULTS: Neutral lipid compositions were markedly modified under serum-deprived conditions and, strikingly, the cellular level of triglyceride subspecies decreased with increasing number of double bonds in their fatty acyl chains. In contrast and unexpectedly, no robust changes were observed in lipidomic profiles of hypoxic (2% O2) cancer cells despite concurrent changes in proliferation rates and metabolic gene expression. CONCLUSIONS: Serum-deprivation significantly affects lipidomic profiles of cancer cells. Although, the levels of individual lipid moieties alter under hypoxia (2% O2), the robust averages of broader lipid classes remain unchanged.

Pharmacokinetics of Daclatasvir, Sofosbuvir, and GS-331007 in a Prospective Cohort of Hepatitis C Virus-Positive Kidney Transplant Recipients.

BACKGROUND: Limited data exist on the pharmacokinetic profile of novel direct-acting antivirals in kidney transplant recipients. Daclatasvir is primarily eliminated through the biliary route and sofosbuvir through the renal route; here, we report the pharmacokinetic profile of combined treatment with these compounds in a prospective study of hepatitis C virus (HCV)-positive kidney transplant recipients (EudraCT: 2014-004551-32). METHODS: In this study, plasma samples of 16 HCV-positive kidney transplant recipients receiving daclatasvir and sofosbuvir were collected at 4 time points at days 1, 7, 14, 21, 56, and 84 after start of treatment. Inclusion criteria were stable graft function and an estimated glomerular filtration rate (eGFR) >30 mL/min/1.73 m. Daclatasvir, sofosbuvir, and GS-331007 (inactive metabolite of sofosbuvir) plasma concentrations were determined using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry. RESULTS: All patients showed a rapid virological response with HCV RNA below the detection limit 21 days after the start of therapy (medium time to viral clearance). No difference of the areas under the concentration-time curve (AUC) of daclatasvir, sofosbuvir, and GS-331007 was observed between patients with an eGFR below or ≥60 mL/min. For GS-331007, no relevant changes of trough levels were observed over time. Mean GS-331007 trough levels were 339.5 ± 174.9 ng/mL in patients with an eGFR ≥60 mL/min and 404.3 ± 226 ng/mL in patients with an eGFR <60 mL/min at day 7 (P = 0.52). At day 84, GS-331007 trough levels were 357.8 ± 200.8 and 404.2 ± 70.2 ng/mL in patients with an eGFR ≥60 mL/min and in patients with an eGFR <60 mL/min, respectively (P = 0.51). The accumulation ratios of renally eliminated GS-331007 for AUC and Cmax did not significantly differ between the 2 eGFR groups at day 7. CONCLUSIONS: An impaired eGFR (30-60 mL/min) does not lead to a dose accumulation of daclatasvir, sofosbuvir, and GS-331007. This study provides the rationale for future studies investigating the pharmacokinetic profile of sofosbuvir-based HCV treatment in kidney transplant recipients with an eGFR <30 mL/min.

Non-invasive metastasis prognosis from plasma metabolites in stage II colorectal cancer patients: The DACHS study.

Metastasis is the main cause of death from colorectal cancer (CRC). About 20% of stage II CRC patients develop metastasis during the course of disease. We performed metabolic profiling of plasma samples from non-metastasized and metachronously metastasized stage II CRC patients to assess the potential of plasma metabolites to serve as biomarkers for stratification of stage II CRC patients according to metastasis risk. We compared the metabolic profiles of plasma samples prospectively obtained prior to metastasis formation from non-metastasized vs. metachronously metastasized stage II CRC patients of the German population-based case-control multicenter DACHS study retrospectively. Plasma samples were analyzed from stage II CRC patients for whom follow-up data including the information on metachronous metastasis were available. To identify metabolites distinguishing non-metastasized from metachronously metastasized stage II CRC patients robust supervised classifications using decision trees and support vector machines were performed and verified by 10-fold cross-validation, by nested cross-validation and by traditional validation using training and test sets. We found that metabolic profiles distinguish non-metastasized from metachronously metastasized stage II CRC patients. Classification models from decision trees and support vector machines with 10-fold cross-validation gave average accuracy of 0.75 (sensitivity 0.79, specificity 0.7) and 0.82 (sensitivity 0.85, specificity 0.77), respectively, correctly predicting metachronous metastasis in stage II CRC patients. Taken together, plasma metabolic profiles distinguished non-metastasized and metachronously metastasized stage II CRC patients. The classification models consisting of few metabolites stratify non-invasively stage II CRC patients according to their risk for metachronous metastasis.

Statistical and Multivariate Analysis of MS-Based Plant Metabolomics Data.

Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.

Nontargeted Identification of Tracer Incorporation in High-Resolution Mass Spectrometry.

"Fluxomics" refers to the systematic analysis of metabolic fluxes in a biological system and may uncover novel dynamic properties of metabolism that remain undetected in conventional metabolomic approaches. In labeling experiments, tracer molecules are used to track changes in the isotopologue distribution of metabolites, which allows one to estimate fluxes in the metabolic network. Because unidentified compounds cannot be mapped on pathways, they are often neglected in labeling experiments. However, using recent developments in de novo annotation may allow to harvest the information present in these compounds if they can be identified. Here, we present a novel tool (HiResTEC) to detect tracer incorporation in high-resolution mass spectrometry data sets. The software automatically extracts a comprehensive, nonredundant list of all compounds showing more than 1% tracer incorporation in a nontargeted fashion. We explain and show in an example data set how mass precision and other filter heuristics, calculated on the raw data, can efficiently be used to reduce redundancy and noninformative signals by 95%. Ultimately, this allows to quickly investigate any labeling experiment for a complete set of labeled compounds (here 149) with acceptable false positive rates. We further re-evaluate a published data set from liquid chromatography-electrospray ionization (LC-ESI) to demonstrate broad applicability of our tool and emphasize importance of quality control (QC) tests. HiResTEC is provided as a package in the open source software framework R and is freely available on CRAN.

Compound annotation in liquid chromatography/high-resolution mass spectrometry based metabolomics: robust adduct ion determination as a prerequisite to structure prediction in electrospray ionization mass spectra.

RATIONALE: A bottleneck in metabolic profiling of complex biological extracts is confident, non-supervised annotation of ideally all contained, chemically highly diverse small molecules. Recent computational strategies combining sum formula prediction with in silico fragmentation achieve confident de novo annotation, once the correct neutral mass of a compound is known. Current software solutions for automated adduct ion assignment, however, are either publicly unavailable or have been validated against only few experimental electrospray ionization (ESI) mass spectra. METHODS: We here present findMAIN (find Main Adduct IoN), a new heuristic approach for interpreting ESI mass spectra. findMAIN scores MS1 spectra based on explained intensity, mass accuracy and isotope charge agreement of adducts and related ionization products and annotates peaks of the (de)protonated molecule and adduct ions. The approach was validated against 1141 ESI positive mode spectra of chemically diverse standard compounds acquired on different high-resolution mass spectrometric instruments (Orbitrap and time-of-flight). Robustness against impure spectra was evaluated. RESULTS: Correct adduct ion assignment was achieved for up to 83% of the spectra. Performance was independent of compound class and mass spectrometric platform. The algorithm proved highly tolerant against spectral contamination as demonstrated exemplarily for co-eluting compounds as well as systematically by pairwise mixing of spectra. When used in conjunction with MS-FINDER, a state-of-the-art sum formula tool, correct sum formulas were obtained for 77% of spectra. It outperformed both 'brute force' approaches and current state-of-the-art annotation packages tested as potential alternatives. Limitations of the heuristic pertained to poorly ionizing compounds and cationic compounds forming [M]+ ions. CONCLUSIONS: A new, validated approach for interpreting ESI mass spectra is presented, filling a gap in the nontargeted metabolomics workflow. It is freely available in the latest version of R package InterpretMSSpectrum.

Distribution pattern following systemic mesenchymal stem cell injection depends on the age of the recipient and neuronal health.

BACKGROUND: Mesenchymal stem cells (MSCs) show therapeutic efficacy in many different age-related degenerative diseases, including Alzheimer's disease. Very little is currently known about whether or not aging impacts the transplantation efficiency of MSCs. METHODS: In this study, we investigated the distribution of intravenously transplanted syngeneic MSCs derived from young and aged mice into young, aged, and transgenic APP/PS1 Alzheimer's disease mice. MSCs from male donors were transplanted into female mice and their distribution pattern was monitored by PCR using Y-chromosome specific probes. Biodistribution of transplanted MSCs in the brains of APP/PS1 mice was additionally confirmed by immunofluorescence and confocal microscopy. RESULTS: Four weeks after transplantation into young mice, young MSCs were found in the lung, axillary lymph nodes, blood, kidney, bone marrow, spleen, liver, heart, and brain cortex. In contrast, young MSCs that were transplanted into aged mice were only found in the brain cortex. In both young and aged mouse recipients, transplantation of aged MSCs showed biodistribution only in the blood and spleen. Although young transplanted MSCs only showed neuronal distribution in the brain cortex in young mice, they exhibited a wide neuronal distribution pattern in the brains of APP/PS1 mice and were found in the cortex, cerebellum, hippocampus, olfactory bulb, and brainstem. The immunofluorescent signal of both transplanted MSCs and resident microglia was robust in the brains of APP/PS1 mice. Monocyte chemoattractant-1 levels were lowest in the brain cortex of young mice and were significantly increased in APP/PS1 mice. Within the hippocampus, monocyte chemoattractant-1 levels were significantly higher in aged mice compared with younger and APP/PS1 mice. CONCLUSIONS: We demonstrate in vivo that MSC biodistribution post transplantation is detrimentally affected by aging and neuronal health. Aging of both the recipient and the donor MSCs used attenuates transplantation efficiency. Clinically, our data would suggest that aged MSCs should not be used for transplantation and that transplantation of MSCs into aged patients will be less efficacious.

Automated Annotation and Evaluation of In-Source Mass Spectra in GC/Atmospheric Pressure Chemical Ionization-MS-Based Metabolomics.

Gas chromatography using atmospheric pressure chemical ionization coupled to mass spectrometry (GC/APCI-MS) is an emerging metabolomics platform, providing much-enhanced capabilities for structural mass spectrometry as compared to traditional electron ionization (EI)-based techniques. To exploit the potential of GC/APCI-MS for more comprehensive metabolite annotation, a major bottleneck in metabolomics, we here present the novel R-based tool InterpretMSSpectrum assisting in the common task of annotating and evaluating in-source mass spectra as obtained from typical full-scan experiments. After passing a list of mass-intensity pairs, InterpretMSSpectrum locates the molecular ion (M0), fragment, and adduct peaks, calculates their most likely sum formula combination, and graphically summarizes results as an annotated mass spectrum. Using (modifiable) filter rules for the commonly used methoximated-trimethylsilylated (MeOx-TMS) derivatives, covering elemental composition, typical substructures, neutral losses, and adducts, InterpretMSSpectrum significantly reduces the number of sum formula candidates, minimizing manual effort for postprocessing candidate lists. We demonstrate the utility of InterpretMSSpectrum for 86 in-source spectra of derivatized standard compounds, in which rank-1 sum formula assignments were achieved in 84% of the cases, compared to only 63% when using mass and isotope information on the M0 alone. We further use, for the first time, automated annotation to evaluate the purity of pseudospectra generated by different metabolomics preprocessing tools, showing that automated annotation can serve as an integrative quality measure for peak picking/deconvolution methods. As an R package, InterpretMSSpectrum integrates flexibly into existing metabolomics pipelines and is freely available from CRAN ( https://cran.r-project.org/ ).