PubMed

Crocadepsins - Depsipeptides from the Myxobacterium Chondromyces crocatus found by a Genome Mining Approach. ACS Chem Biol. 2017 Dec 08;: Authors: Surup F, Viehrig K, Rachid S, Plaza A, Maurer CK, Hartmann RW, Müller R Abstract Analysis of the genome sequence of the myxobacterium Chondromyces crocatus Cm c5 revealed the presence of numerous cryptic megasynthetase gene clusters, one of which we here assign to two previously unknown chlorinated metabolites by a comparative gene inactivation and secondary metabolomics approach. Structure elucidation of these compounds revealed a unique cyclic depsipeptide skeleton featuring β- and δ-amide bonds of aspartic acid and 3-methyl ornithine moieties, respectively. Insights into their biosynthesis were obtained by targeted gene inactivation and feeding experiments employing isotope-labeled precursors. The compounds were produced ubiquitously by the species Chondromyces crocatus and were found to inhibit the carbon storage regulator-RNA interaction. PMID: 29220569 [PubMed - as supplied by publisher]

Mitochondrial metabolism and cancer. Cell Res. 2017 Dec 08;: Authors: Porporato PE, Filigheddu N, Pedro JMB, Kroemer G, Galluzzi L Abstract Glycolysis has long been considered as the major metabolic process for energy production and anabolic growth in cancer cells. Although such a view has been instrumental for the development of powerful imaging tools that are still used in the clinics, it is now clear that mitochondria play a key role in oncogenesis. Besides exerting central bioenergetic functions, mitochondria provide indeed building blocks for tumor anabolism, control redox and calcium homeostasis, participate in transcriptional regulation, and govern cell death. Thus, mitochondria constitute promising targets for the development of novel anticancer agents. However, tumors arise, progress, and respond to therapy in the context of an intimate crosstalk with the host immune system, and many immunological functions rely on intact mitochondrial metabolism. Here, we review the cancer cell-intrinsic and cell-extrinsic mechanisms through which mitochondria influence all steps of oncogenesis, with a focus on the therapeutic potential of targeting mitochondrial metabolism for cancer therapy.Cell Research advance online publication 8 December 2017; doi:10.1038/cr.2017.155. PMID: 29219147 [PubMed - as supplied by publisher]

Related Articles [Preliminary screening of biomarkers for curcumin's antidepressant effect based on metabonomics method]. Zhongguo Zhong Yao Za Zhi. 2017 Sep;42(18):3596-3601 Authors: Ma ZJ, Zhang W, Dong JM, Yu XH, Zhao XM, Pu SB Abstract To screen potential biomarkers of curcumin related to treating depression rats by using metabolomics means, so as to explore the antidepressant action mechanism of curcumin. The healthy male SD rats were randomly divided into four groups. Chronic unpredictable mild stress (CUMS) stimulation was conducted for modeling for 2 weeks, and then curcumin (200 mg•kg⁻¹) or venlafaxine (40 mg•kg⁻¹) was given by gavage administration. The blank group and model group rats were given with the same volume of 1% CMCNa normal saline, once per day for two weeks. The rats serum for each group was collected and LC/MS-IT-TOF method was used to characterize the metabolic differences. Also multivariate statistical analysis was used to screen possible potential biomarkers and analyze the possible metabolic pathways. After administration of curcumin and venlafaxine respectively, the depression indexes of CUMS model rats were all improved significantly (P<0.05), but there were no significant differences between curcumin and venlafaxine groups. In PCA and PLS-DA analysis after curcumin or venlafaxine intervention on CUMS model group rats, the small molecule metabolites level reflects a normal trend, and particularly for the curcumin group. Through metabonomics technology, 11 biomarkers associated with curcumin antidepressant effect were screened, and at the same time seven metabolic pathways were involved. The results showed that curcumin had antidepressant effects, which was evident in both macro and micro levels, comparable with positive drug of venlafaxine. The antidepressant effect of curcumin may be associated with the glycerol phospholipid metabolism, linoleic acid metabolism, pentose and glucuronic acid ester and ether lipid metabolism, but still need further exploration in the future. PMID: 29218948 [PubMed - in process]

Related Articles Analyzing metabolomics data for association with genotypes using two-component Gaussian mixture distributions. Pac Symp Biocomput. 2018;23:496-506 Authors: Westra J, Hartman N, Lake B, Shearer G, Tintle N Abstract Standard approaches to evaluate the impact of single nucleotide polymorphisms (SNP) on quantitative phenotypes use linear models. However, these normal-based approaches may not optimally model phenotypes which are better represented by Gaussian mixture distributions (e.g., some metabolomics data). We develop a likelihood ratio test on the mixing proportions of two-component Gaussian mixture distributions and consider more restrictive models to increase power in light of a priori biological knowledge. Data were simulated to validate the improved power of the likelihood ratio test and the restricted likelihood ratio test over a linear model and a log transformed linear model. Then, using real data from the Framingham Heart Study, we analyzed 20,315 SNPs on chromosome 11, demonstrating that the proposed likelihood ratio test identifies SNPs well known to participate in the desaturation of certain fatty acids. Our study both validates the approach of increasing power by using the likelihood ratio test that leverages Gaussian mixture models, and creates a model with improved sensitivity and interpretability. PMID: 29218908 [PubMed - in process]

Related Articles Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure. Pac Symp Biocomput. 2018;23:460-471 Authors: Orlenko A, Moore JH, Orzechowski P, Olson RS, Cairns J, Caraballo PJ, Weinshilboum RM, Wang L, Breitenstein MK Abstract With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide exciting opportunity to guide feature selection in agnostic metabolic profiling endeavors, where potentially thousands of independent data points must be evaluated. In previous research, AutoML using high-dimensional data of varying types has been demonstrably robust, outperforming traditional approaches. However, considerations for application in clinical metabolic profiling remain to be evaluated. Particularly, regarding the robustness of AutoML to identify and adjust for common clinical confounders. In this study, we present a focused case study regarding AutoML considerations for using the Tree-Based Optimization Tool (TPOT) in metabolic profiling of exposure to metformin in a biobank cohort. First, we propose a tandem rank-accuracy measure to guide agnostic feature selection and corresponding threshold determination in clinical metabolic profiling endeavors. Second, while AutoML, using default parameters, demonstrated potential to lack sensitivity to low-effect confounding clinical covariates, we demonstrated residual training and adjustment of metabolite features as an easily applicable approach to ensure AutoML adjustment for potential confounding characteristics. Finally, we present increased homocysteine with long-term exposure to metformin as a potentially novel, non-replicated metabolite association suggested by TPOT; an association not identified in parallel clinical metabolic profiling endeavors. While warranting independent replication, our tandem rank-accuracy measure suggests homocysteine to be the metabolite feature with largest effect, and corresponding priority for further translational clinical research. Residual training and adjustment for a potential confounding effect by BMI only slightly modified the suggested association. Increased homocysteine is thought to be associated with vitamin B12 deficiency - evaluation for potential clinical relevance is suggested. While considerations for clinical metabolic profiling are recommended, including adjustment approaches for clinical confounders, AutoML presents an exciting tool to enhance clinical metabolic profiling and advance translational research endeavors. PMID: 29218905 [PubMed - in process]

Related Articles Best practices and lessons learned from reuse of 4 patient-derived metabolomics datasets in Alzheimer's disease. Pac Symp Biocomput. 2018;23:280-291 Authors: Tenenbaum JD, Blach C Abstract The importance of open data has been increasingly recognized in recent years. Although the sharing and reuse of clinical data for translational research lags behind best practices in biological science, a number of patient-derived datasets exist and have been published enabling translational research spanning multiple scales from molecular to organ level, and from patients to populations. In seeking to replicate metabolomic biomarker results in Alzheimer's disease our team identified three independent cohorts in which to compare findings. Accessing the datasets associated with these cohorts, understanding their content and provenance, and comparing variables between studies was a valuable exercise in exploring the principles of open data in practice. It also helped inform steps taken to make the original datasets available for use by other researchers. In this paper we describe best practices and lessons learned in attempting to identify, access, understand, and analyze these additional datasets to advance research reproducibility, as well as steps taken to facilitate sharing of our own data. PMID: 29218889 [PubMed - in process]

Related Articles Temporal-Spatial Profiling of Pedunculopontine Galanin-Cholinergic Neurons in the Lactacystin Rat Model of Parkinson's Disease. Neurotox Res. 2017 Dec 07;: Authors: Elson JL, Kochaj R, Reynolds R, Pienaar IS Abstract Parkinson's disease (PD) is conventionally seen as resulting from single-system neurodegeneration affecting nigrostriatal dopaminergic neurons. However, accumulating evidence indicates multi-system degeneration and neurotransmitter deficiencies, including cholinergic neurons which degenerate in a brainstem nucleus, the pedunculopontine nucleus (PPN), resulting in motor and cognitive impairments. The neuropeptide galanin can inhibit cholinergic transmission, while being upregulated in degenerating brain regions associated with cognitive decline. Here we determined the temporal-spatial profile of progressive expression of endogenous galanin within degenerating cholinergic neurons, across the rostro-caudal axis of the PPN, by utilizing the lactacystin-induced rat model of PD. First, we show progressive neuronal death affecting nigral dopaminergic and PPN cholinergic neurons, reflecting that seen in PD patients, to facilitate use of this model for assessing the therapeutic potential of bioactive peptides. Next, stereological analyses of the lesioned brain hemisphere found that the number of PPN cholinergic neurons expressing galanin increased by 11%, compared to sham-lesioned controls, and increasing by a further 5% as the neurodegenerative process evolved. Galanin upregulation within cholinergic PPN neurons was most prevalent closest to the intra-nigral lesion site, suggesting that galanin upregulation in such neurons adapt intrinsically to neurodegeneration, to possibly neuroprotect. This is the first report on the extent and pattern of galanin expression in cholinergic neurons across distinct PPN subregions in both the intact rat CNS and lactacystin-lesioned rats. The findings pave the way for future work to target galanin signaling in the PPN, to determine the extent to which upregulated galanin expression could offer a viable treatment strategy for ameliorating PD symptoms associated with cholinergic degeneration. PMID: 29218504 [PubMed - as supplied by publisher]

Related Articles Panomics for Precision Medicine. Trends Mol Med. 2017 Dec 04;: Authors: Sandhu C, Qureshi A, Emili A Abstract Medicine is poised to undergo a digital transformation. High-throughput platforms are creating terabytes of genomic, transcriptomic, proteomic, and metabolomic data. The challenge is to interpret these data in a meaningful manner - to uncover relationships that are not readily apparent between molecular profiles and states of health or disease. This will require the development of novel data pipelines and computational tools. The combined analysis of multi-dimensional data is referred to as 'panomics'. The ultimate hope of integrative panomics is that it will lead to the discovery and application of novel markers and targeted therapeutics that drive forward a new era of 'precision medicine' where inter-individual variation is accounted for in the treatment of patients. PMID: 29217119 [PubMed - as supplied by publisher]

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/12/08PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/12/08PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

22 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/12/07PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

22 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/12/07PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Related Articles Phytochemical variation among the traditional Chinese medicine Mu Dan Pi from Paeonia suffruticosa (tree peony). Phytochemistry. 2017 Dec 02;146:16-24 Authors: Li SS, Wu Q, Yin DD, Feng CY, Liu ZA, Wang LS Abstract Mu Dan Pi is a traditional Chinese medicine used to treat inflammation, cancer, allergies, diabetes, angiocardiopathy, and neurodegenerative diseases. In this study, the metabolome variation within Mu Dan Pi collected from 372 tree peony cultivars was systematically investigated. In total, 42 metabolites were identified, comprising of 14 monoterpene glucosides, 11 tannins, 8 paeonols, 6 flavonoids, and 3 phenols. All cultivars revealed similar metabolite profiles, however, they were further classified into seven groups on the basis of their varying metabolite contents by hierarchical cluster analysis. Traditional cultivars for Mu Dan Pi were found to have very low metabolite contents, falling into clusters I and II. Cultivars with the highest amounts of metabolites were grouped in clusters VI and VII. Five potential cultivars, namely, 'Bai Yuan Qi Guan', 'Cao Zhou Hong', 'Da Zong Zi', 'Sheng Dan Lu', and 'Cheng Xin', with high contents of monoterpene glycosides, tannins, and paeonols, were further screened. Interestingly, the majority of investigated cultivars had relatively higher metabolite contents compared to the traditional medicinal tree peony cultivars. PMID: 29207319 [PubMed - as supplied by publisher]

Related Articles 8-oxoguanine DNA glycosylase (Ogg1) controls hepatic gluconeogenesis. DNA Repair (Amst). 2017 Nov 28;61:56-62 Authors: Scheffler K, Rachek L, You P, Rowe AD, Wang W, Kuśnierczyk A, Kittelsen L, Bjørås M, Eide L Abstract Mitochondrial DNA (mtDNA) resides in close proximity to metabolic reactions, and is maintained by the 8-oxoguanine DNA glycosylase (Ogg1) and other members of the base excision repair pathway. Here, we tested the hypothesis that changes in liver metabolism as under fasting/feeding conditions would be sensed by liver mtDNA, and that Ogg1 deficient mice might unravel a metabolic phenotype. Wild type (WT) and ogg1-/- mice were either fed ad libitum or subjected to fasting for 24h, and the corresponding effects on liver gene expression, DNA damage, as well as serum values were analyzed. Ogg1 deficient mice fed ad libitum exhibited hyperglycemia, elevated insulin levels and higher liver glycogen content as well as increased accumulation of 8oxoG in mtDNA compared to age- and gender matched WT mice. Interestingly, these phenotypes were absent in ogg1-/- mice during fasting. Gene expression and functional analyses suggest that the diabetogenic phenotype in the ogg1-/- mice is due to a failure to suppress gluconeogensis in the fed state. The ogg1-/- mice exhibited reduced mitochondrial electron transport chain (ETC) capacity and a combined low activity of the pyruvate dehydrogenase (PDH), alluding to inefficient channeling of glycolytic products into the citric acid cycle. Our data demonstrate a physiological role of base excision repair that goes beyond DNA maintenance, and implies that DNA repair is involved in regulating metabolism. PMID: 29207315 [PubMed - as supplied by publisher]

Related Articles High-resolution metabolomics determines the mode of onset of type 2 diabetes in a 3-year prospective cohort study. Int J Mol Med. 2017 Nov 21;: Authors: Lee Y, Pamungkas AD, Medriano CAD, Park J, Hong S, Jee SH, Park YH Abstract Type 2 diabetes mellitus (DM) is a progressive disease and the rate of progression from non-diabetes to DM varies considerably between individuals, ranging from a few months to many years. It is important to understand the mechanisms underlying the progression of diabetes. In the present study, a high-resolution metabolomics (HRM) analysis was performed to detect potential biomarkers and pathways regulating the mode of onset by comparing subjects who developed and did not develop type 2 DM at the second year in a 3-year prospective cohort study. Metabolic profiles correlated with progression to DM were examined. The subjects (n=98) were classified into four groups: Control (did not develop DM for 3 years), DM (diagnosed with DM at the start of the study), DM onset at the third year and DM onset at the second year. The focus was on the comparison of serum samples of the DM groups with onset at the second and third year from the first year, where these two groups had not developed DM, yet. Analyses involved sample examination using liquid chromatography-mass spectrometry-based HRM and multivariate statistical analysis of the data. Metabolic differences were identified across all analyses with the affected pathways involved in metabolism associated with steroid biosynthesis and bile acid biosynthesis. In the first year, higher levels of cholesterol {mass-to charge ratio (m/z) 369.35, (M+H-H2O)+}, 25-hydroxycholesterol [m/z 403.36, (M+H)+], 3α,7α-dihydroxy-5β-cholestane [m/z 443.33, (M+K)+], 4α-methylzymosterol-4-carboxylate [m/z 425.34, (M+H‑H2O)+], and lower levels of 24,25-dihydrolanosterol [m/z 429.40, (M+H)+] were evident in the group with DM onset at the second year compared with those in the group with DM onset at the third year. These results, with a focus on the cholesterol biosynthesis pathway, point to important aspects in the development of DM and may aid in the development of more effective means of treatment and prevention. PMID: 29207196 [PubMed - as supplied by publisher]

Related Articles Impact of intratumoral heterogeneity of breast cancer tissue on quantitative metabolomics using high-resolution magic angle spinning 1 H NMR spectroscopy. NMR Biomed. 2017 Dec 05;: Authors: Gogiashvili M, Horsch S, Marchan R, Gianmoena K, Cadenas C, Tanner B, Naumann S, Ersova D, Lippek F, Rahnenführer J, Andersson JT, Hergenröder R, Lambert J, Hengstler JG, Edlund K Abstract High-resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi-core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9- and 1.3-ppm signals) and metabolite quantification using HR MAS 1 H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16-0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one-way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue. PMID: 29206323 [PubMed - as supplied by publisher]

Related Articles Merging FT-IR and NGS for simultaneous phenotypic and genotypic identification of pathogenic Candida species. PLoS One. 2017;12(12):e0188104 Authors: Colabella C, Corte L, Roscini L, Shapaval V, Kohler A, Tafintseva V, Tascini C, Cardinali G Abstract The rapid and accurate identification of pathogen yeast species is crucial for clinical diagnosis due to the high level of mortality and morbidity induced, even after antifungal therapy. For this purpose, new rapid, high-throughput and reliable identification methods are required. In this work we described a combined approach based on two high-throughput techniques in order to improve the identification of pathogenic yeast strains. Next Generation Sequencing (NGS) of ITS and D1/D2 LSU marker regions together with FTIR spectroscopy were applied to identify 256 strains belonging to Candida genus isolated in nosocomial environments. Multivariate data analysis (MVA) was carried out on NGS and FT-IR data-sets, separately. Strains of Candida albicans, C. parapsilosis, C. glabrata and C. tropicalis, were identified with high-throughput NGS sequencing of ITS and LSU markers and then with FTIR. Inter- and intra-species variability was investigated by consensus principal component analysis (CPCA) which combines high-dimensional data of the two complementary analytical approaches in concatenated PCA blocks normalized to the same weight. The total percentage of correct identification reached around 97.4% for C. albicans and 74% for C. parapsilosis while the other two species showed lower identification rates. Results suggested that the identification success increases with the increasing number of strains actually used in the PLS analysis. The absence of reliable FT-IR libraries in the current scenario is the major limitation in FTIR-based identification of strains, although this metabolomics fingerprint represents a valid and affordable aid to rapid and high-throughput to clinical diagnosis. According to our data, FT-IR libraries should include some tens of certified strains per species, possibly over 50, deriving from diverse sources and collected over an extensive time period. This implies a multidisciplinary effort of specialists working in strain isolation and maintenance, molecular taxonomy, FT-IR technique and chemo-metrics, data management and data basing. PMID: 29206226 [PubMed - in process]

Related Articles Macroamidine Formation in Bottromycins Is Catalyzed by a Divergent YcaO Enzyme. J Am Chem Soc. 2017 Dec 05;: Authors: Franz L, Adam S, Santos-Aberturas J, Truman AW, Koehnke J Abstract The YcaO superfamily of proteins catalyzes the phosphorylation of peptide backbone amide bonds, which leads to the formation of azolines and azoles in ribosomally synthesized and post-translationally modified peptides (RiPPs). Bottromycins are RiPPs with potent antimicrobial activity, and their biosynthetic pathway contains two divergent, stand-alone YcaO enzymes, IpoC and PurCD. From an untargeted metabolomics approach, it had been suggested that PurCD acts with a partner protein to form the 12-membered macroamidine unique to bottromycins. Here we report the biochemical characterization of IpoC and PurCD. We demonstrate that IpoC installs a cysteine-derived thiazoline, whereas PurCD alone is sufficient to create the macroamidine structure. Both enzymes are catalytically promiscuous, and we generated 10 different macroamidines. Our data provide important insights into the versatility of YcaO enzymes, their ability to utilize different nucleophiles and provide a framework for the creation of novel bottromycin derivatives with enhanced bioactivity. PMID: 29206037 [PubMed - as supplied by publisher]

Related Articles [Research Progress on Estimation of Early Postmortem Interval]. Fa Yi Xue Za Zhi. 2016 Dec;32(6):444-447 Authors: Tao L, Ma JL, Chen L Abstract Estimation of postmortem interval （PMI） is very important for judging the nature of cases, restricting the scope of investigation and suspect, which is always the emphasis and difficulty for forensic pathology. Early postmortem interval is the time between 0 and 24 hours after death. Due to the shorter time after the case occurred, precisely estimating early postmortem interval can help solve crimes, which has important significance in forensic medicine. In recent years, series of advanced methods and technologies are used to estimate the early PMI by the internal and overseas scholars who work in the forensic area. This paper reviews the research progress on fluids biochemistry, supravital reactions, metabolomics, imageology and the degradation rule of genetic material to provide a new idea to the study and application for estimation of early PMI. PMID: 29205974 [PubMed - in process]

Related Articles Colon Ascendens Stent Peritonitis (CASP) Induces Excessive Inflammation and Systemic Metabolic Dysfunction in a Septic Rat Model. J Proteome Res. 2017 Dec 05;: Authors: Zhang L, Tian Y, Yang J, Li J, Tang H, Wang Y Abstract The colon ascendens stent peritonitis (CASP) surgery creates a leakage of intestinal contents, resulting in polymicrobial sepsis associated with a high risk for postoperative multiple organ failure and death in surgical patients. To evaluate the effects of CASP on multiple organs, we analyzed the systemic metabolic consequences in liver, kidney, lung and heart of rats after CASP by employing a combination of metabolomics, clinical chemistry and biological assays. We found that CASP surgery after 18 h caused significant elevations of lipid, amino acids, acetate, choline, PC and GPC in rat liver together with significant depletion of glucose and glycogen. Marked elevations of organic acids including lactate, acetate and creatine and amino acids accompanied with decline for glucose, betaine, TMAO, nucleotides and a range of organic osmolytes, such as myo-inositol, choline, PC and GPC are observed in the kidney of 18 h-postoperative rat. Furthermore, 18 h-postoperative rats exhibited accumulations of lipid, amino acids and depletions of taurine, myo-inositol, choline, PC and GPC, and some nucleotides including uridine, inosine and adenosine in the lung. In addition, significant elevations of some amino acids, uracil, betaine, choline metabolites, together with depletion of inosine-5'-monophosphate were only observed in the heart of 18 h-postoperative rats. These findings provide new insights into pathological consequences of CASP surgery, which are important for timely prognosis of sepsis. PMID: 29205045 [PubMed - as supplied by publisher]