Validation of a dual LC–HRMS platform for clinical metabolic diagnosis in serum,bridging quantitative analysis and untargeted metabolomics

Mass spectrometry-based metabolomics is a rapidly growing field in both research and diagnosis. Generally, the methodologies and types of instruments used for clinical and other absolute quantification experiments are different from those used for biomarkers discovery and untargeted analysis, as the former requires optimal sensitivity and dynamic range, while the latter requires high resolution and high mass accuracy. We used a Q-TOF mass spectrometer with two different types of pentafluorophenyl (PFP) stationary phases, employing both positive and negative ionization, to develop and validate a hybrid quantification and discovery platform using LC–HRMS. This dual-PFP LC–MS platform quantifies over 50 clinically relevant metabolites in serum (using both MS and MS/MS acquisitions) while simultaneously collecting high resolution and high mass accuracy full scans to monitor all other co-eluting non-targeted analytes. We demonstrate that the linearity, accuracy, and precision results for the quantification of a number of metabolites, including amino acids, organic acids, acylcarnitines and purines/pyrimidines, meets or exceeds normal bioanalytical standards over their respective physiological ranges. The chromatography resolved highly polar as well as hydrophobic analytes under reverse-phase conditions, enabling analysis of a wide range of chemicals, necessary for untargeted metabolomics experiments. Though previous LC–HRMS methods have demonstrated quantification capabilities for various drug and small molecule compounds, the present study provides an HRMS quant/qual platform tailored to metabolic disease; and covers a multitude of different metabolites including compounds normally quantified by a combination of separate instrumentation.     

Application of serum protein fingerprint in diagnosis of papillary thyroid carcinoma

To find new biomarkers and establish serum protein fingerprint models for early diagnosis and preoperative staging of papillary thyroid carcinoma, we employed SELDI-TOF-MS and bioinformatics tools. A total of 116 samples were analyzed in this study. The first 80 samples were analyzed by SELDI-TOF-MS and two biomarker patterns were identified. Pattern 1 distinguishes patients with papillary thyroid carcinoma from healthy individuals. Pattern 2 distinguishes papillary thyroid carcinoma from benign thyroid nodes. The remaining 29 samples were analyzed on the second day and served as an independent test set. The analysis of this independent test set yielded a specificity of 80.0% and a sensitivity of 88.9% for pattern 1 and a specificity of 80.0% and a sensitivity of 80.0% for pattern 2. Two additional biomarker patterns were identified to distinguish different stages of the papillary thyroid carcinoma (pattern 3) with an accuracy of 77.1% and different pathological types of thyroid carcinoma (pattern 4) with an accuracy of 88.1%. Taken together, the SELDI-TOF-MS technique combined with bioinformatics approaches can not only facilitate the discovery of better biomarkers for papillary thyroid carcinoma but also provide a useful tool for molecular diagnosis in the future.     

Evolution of intrahepatic carbon, nitrogen, and energy metabolism in a D-galactosamine-induced rat liver failure model

A clearer picture of the hepatic metabolic pathways affected by fulminant hepatic failure (FHF) would help develop nutritional support and nonsurgical therapies for FHF. We characterized the evolution of hepatic metabolism in a rat model of FHF using an isolated perfused liver system together with a mass-balance model of intermediary metabolism. Principal component analysis (PCA) was used to identify potential new sensitive markers for FHF. To induce FHF, rats were given two D-galactosamine injections under fasting conditions. Controls were fasted only. Livers were harvested 1, 4, 8, and 12 h later and perfused with Eagle minimal essential medium supplemented with amino acids and bovine serum albumin, and equilibrated with 95% O2/5% CO2. At the 1 h time point, lactate release increased concomitant with a decrease in gluconeogenesis, TCA cycle and mitochondrial electron transport fluxes. At 4 h, amino acid metabolism and urea cycle fluxes were significantly depressed. By 8 h, gluconeogenesis had switched to glycolysis. By 12 h, amino acid metabolism was broadly inhibited, and there was a net release of many amino acids. Mass-balance analysis shows that the main source of ATP production in the FHF liver gradually changed from mitochondrial oxidative phosphorylation to glycolysis. PCA suggests that a linear combination of glucose, lactate, and glutamine concentrations in arterial plasma is a sensitive marker for FHF. We conclude that D-galactosamine causes early mitochondrial dysfunction while glycolytic ATP synthesis remains functional. Markers that are indirectly linked to these pathways may be used to evaluate the progression of FHF.     

GPR120 induces regulatory dendritic cells by inhibiting HK2-dependent glycolysis to alleviate fulminant hepatic failure

Fulminant hepatic failure (FHF) is a potentially fatal liver disease that is associated with intrahepatic infiltration of inflammatory cells. As the receptor of polyunsaturated long chain fatty acids, GPR120 can regulate cell differentiation, proliferation, metabolism, and immune response. However, whether GPR120 is involved in FHF remains unknown. Using Propionibacterium acnes (P. acnes)-primed, LPS-induced FHF in mice, we found that interference with GPR120 activity using pharmacological agonist attenuated the severity of the liver injury and mortality of FHF in mice, while a lack of GPR120 exacerbated the disease. GPR120 activation potently alleviated FHF and led to decreased T helper (Th) 1 cell response and expansion of regulatory T cells (Tregs). Interestingly, GPR120 agonist didn’t directly target T cells, but dramatically induced a distinct population of CD11c⁺MHC II^lowCD80^lowCD86^low regulatory DCs in the livers of FHF mice. GPR120 was found to restrict HIF-1α-dependent glycolysis. The augmented HIF-1α stabilization caused by GPR120 antagonism or deletion could be attenuated by the inhibition of ERK or by the activation of AMPK. Through the analysis of the clinical FHF, we further confirmed the activation of GPR120 was negatively associated with the severity in patients. Our findings indicated that GPR120 activation has therapeutic potential in FHF. Strategies to target GPR120 using agonists or free fatty acids (FFAs) may represent a novel approach to FHF treatment.Subject terms: Inflammation, Hepatitis     

Dynamic metabolic transformation in tumor invasion and metastasis in mice with LM-8 osteosarcoma cell transplantation

While extensive evidence indicates that tumor cells shift their global metabolic programs, the molecular details of the metabolic transformation in tumor invasion, progression, and metastasis remain largely unknown. Characterization of the time-dependent metabolic shift during the tumor invasion, development, and metastasis will describe an important aspect of tumor phenotypes and potentially allow us to design therapies that inhibit tumor cell movement. In this study, a metabonomic study was performed to characterize the global metabolic changes during the process of tumor invasion and metastasis to lung in a mouse model with subcutaneous transplantation of murine osteosarcoma cell line (LM8). The serum metabolic profiling revealed that many key metabolites in glycolysis and tricarboxylic acid (TCA) cycle, as well as most of the amino acids were elevated at rapidly growing stage of tumor, presumably resulting from a high energy demand and turnover of anabolic metabolism during the tumor cell proliferation. Serum levels of succinic acid and proline significantly increased (with fold change FC = 10.75 and 4.43, relative to controls) among all the metabolites in the third week. The serum metabolic profile of lung metastasis at week 4 was different from that at week 3, in that most of previously increased serum metabolites were found decreased, except for cholesterol and several free fatty acids, suggesting lowered carbohydrate and amino acids metabolism, but an elevated lipid metabolism associated with tumor metastasis.     

Fibroblast growth factor homologous factor 1 stimulates Leydig cell regeneration from stem cells in male rats

Fibroblast growth factor homologous factor 1 (FHF1) is an intracellular protein that does not bind to cell surface fibroblast growth factor receptor. Here, we report that FHF1 is abundantly present in Leydig cells with up‐regulation during its development. Adult male Sprague Dawley rats were intraperitoneally injected with 75 mg/kg ethane dimethane sulphonate (EDS) to ablate Leydig cells to initiate their regeneration. Then, rats daily received intratesticular injection of FHF1 (0, 10 and 100 ng/testis) from post‐EDS day 14 for 14 days. FHF1 increased serum testosterone levels without affecting the levels of luteinizing hormone and follicle‐stimulating hormone. FHF1 increased the cell number staining with HSD11B1, a biomarker for Leydig cells at the advanced stage, without affecting the cell number staining with CYP11A1, a biomarker for all Leydig cells. FHF1 did not affect PCNA‐labelling index in Leydig cells. FHF1 increased Leydig cell mRNA (Lhcgr, Scarb1, Star, Cyp11a1, Hsd3b1, Cyp17a1, Hsd17b3, Insl3, Nr5a1 and Hsd11b1) and their protein levels in vivo. FHF1 increased preadipocyte biomarker Dlk1 mRNA level and decreased fully differentiated adipocyte biomarker (Fabp4 and Lpl) mRNA and their protein levels. In conclusion, FHF1 promotes Leydig cell regeneration from stem cells while inhibiting the differentiation of preadipocyte/stem cells into adipocytes in EDS‐treated testis.     

Improved protocols for quantitative determination of metabolites from biological samples using high performance ionic-exchange chromatography with conductimetric and pulsed amperometric detection

Simple and reliable protocols are described for an extensive analysis of metabolites in extracts from different biological sources. The separation was performed by high performance ionic-exchange chromatography (HPIC) at alkaline pH using two types of chromatography columns and two detection methods. Organic acids and inorganic anions were separated on an ionPac AS11 column using a 0.5 to 35 mM Na0H gradient. Detection limits in the range of milligrams per liter were achieved by use of a conductivity detector equipped with an anion self-regenerating suppressor. Twelve phosphorylated compounds belonging to the glycolytic and the pentose phosphate pathways could be resolved on a CarboPac PA1 column using a Na0H/Na-acetate gradient. Quantification was achieved by pulsed amperometry with detection limits in the micromolar range. Cell extracts obtained by extraction in boiling buffered ethanol described previously could be directly injected onto HPIC columns for the separation of metabolites because the extraction procedure affected neither the retention time nor the stability of most of the metabolites, and yielded very clean chromatograms. These improved protocols were applied for a dynamic analysis of intracellular metabolites in Saccharomyces cerevisiae in response to a glucose pulse.     

Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignancy in the world with high morbidity and mortality rate. Identification of novel biomarkers in HCC remains impeded primarily because of the heterogeneity of the disease in clinical presentations as well as the pathophysiological variations derived from underlying conditions such as cirrhosis and steatohepatitis. The aim of this study is to search for potential metabolite biomarkers of human HCC using serum and urine metabolomics approach. Sera and urine samples were collected from patients with HCC (n = 82), benign liver tumor patients (n = 24), and healthy controls (n = 71). Metabolite profiling was performed by gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography-quadrupole time of flight mass spectrometry in conjunction with univariate and multivariate statistical analyses. Forty three serum metabolites and 31 urinary metabolites were identified in HCC patients involving several key metabolic pathways such as bile acids, free fatty acids, glycolysis, urea cycle, and methionine metabolism. Differentially expressed metabolites in HCC subjects, such as bile acids, histidine, and inosine are of great statistical significance and high fold changes, which warrant further validation as potential biomarkers for HCC. However, alterations of several bile acids seem to be affected by the condition of liver cirrhosis and hepatitis. Quantitative measurement and comparison of seven bile acids among benign liver tumor patients with liver cirrhosis and hepatitis, HCC patients with liver cirrhosis and hepatitis, HCC patients without liver cirrhosis and hepatitis, and healthy controls revealed that the abnormal levels of glycochenodeoxycholic acid, glycocholic acid, taurocholic acid, and chenodeoxycholic acid are associated with liver cirrhosis and hepatitis. HCC patients with alpha fetoprotein values lower than 20 ng/ml was successfully differentiated from healthy controls with an accuracy of 100% using a panel of metabolite markers. Our work shows that metabolomic profiling approach is a promising screening tool for the diagnosis and stratification of HCC patients.     

Dose-related effects of low dose aspirin on hemostasis parameters and prostacyclin/thromboxane ratios in late pregnancy

Background: The purpose of this study was to determine which low dose of low dose aspirin (LDA) optimized the urinary prostacyclin (PGI₂)/thromboxane (TXA₂) ratio and minimized evidence of platelet aggregation during normal late pregnancy.Methods: Twelve women with uncomplicated singleton pregnancies between 28 and 34 weeks gestation participated in a randomized blinded study. Blood samples for salicylate levels were obtained pretreatment, 4 hours and 7 days after administration of placebo, 20mg, 40mg or 80mg of aspirin. Twenty-four hour urine specimens collected at the same intervals were assayed for PGI₂ and TXA₂ metabolites. In addition, bleeding time and platelet aggregation studies were performed prior to and after 7 days of LDA or placebo.Results: A dose-related increase in bleeding time occurred with 40 mg and 80 mg of LDA, but not with the 20 mg dose or placebo. Platelet aggregation studies changed progressively from a normal baseline to abnormal with an increasing dose of LDA. The ratio increased with aspirin doses as low as 20mg, with a decrease in TXA₂ metabolites but not in PGI₂ metabolites. Serum salicylate was not detectable in any sample from any patient.Conclusion: There are dose-related changes in platelet aggregation and bleeding times with progressively increasing doses of LDA. A lower dose of LDA, such as 20–40 mg per day, may be as efficacious as higher doses in the prophylaxis of pre-eclampsia in high risk populations.     

Metal Ions Catalytic for Free Radical Reactions in the Plasma of Patients with Fulminant Hepatic Failure

We propose that the frequency and severity of multi-organ failure (MOF) in fulminant hepatic failure (FHF) involves free radical damage caused by the presence of circulating iron and copper ions, catalytic for free radical reactions. The presence of such metal ions is demonstrated by using the sensitive bleomycin and phenanthroline assays. Antioxidant therapy, e.g., using chelating agents that prevent metal ions from stimulating free radical reactions, may have benefit in the treatment of FHF and its consequences.     

An inhibitor of c-Jun NH2-terminal kinase, SP600125, protects mice from D-galactosamine/lipopolysaccharide-induced hepatic failure by modulating BH3-only proteins

Fulminant hepatic failure (FHF) is a dramatic clinical syndrome characterized by massive hepatocyte apoptosis and very high mortality. The c-Jun-N-terminal kinase (JNK) pathway is an important stress-responsive kinase activated by several forms of liver injury. The aim of this study is to assess the role of JNK during D-galactosamine (GalN)/lipopolysaccharide (LPS)-induced liver injury, an experimental model of FHF, using SP600125, a small molecule JNK-specific inhibitor. Mice were given an intraperitoneal dose of GalN (800 microg/g body weight)/LPS (100 ng/g body weight) with and without subcutaneous SP600125 (50 mg/kg body weight) treatment (at 6 and 2 h before and 2 h after GalN/LPS administration). GalN/LPS treatment induced sustained JNK activation. Administration of SP600125 diminished JNK activity, suppressed lethality and the elevation of both serum alanine aminotransferase and aspartate aminotransferase, but had no effect on serum tumor necrosis factor-alpha, and reduced hepatocyte apoptosis after GalN/LPS administration. In support of the role of JNK in promoting the mitochondria-mediated apoptosis pathway, SP600125 prevented cytochrome c release, caspase-9 and caspase-3 activity. Moreover, SP600125 downregulated the mRNA and protein expression of Bad in the early periods following GalN/LPS injection and prevented Bid cleavage in the late periods. These results confirm the role of JNK as a critical apoptotic mediator in GalN/LPS-induced FHF. SP600125 has the potential to protect FHF by downregulating Bad and inhibiting Bid cleavage.     

Metabolomic analysis to discover candidate therapeutic agents against acute pancreatitis

Novel and effective drugs against acute pancreatitis are required. Therefore, we examined the changes in the metabolite levels in the serum and pancreatic tissue of mice with cerulein- and arginine-induced pancreatitis using gas-chromatography/mass-spectrometry (GC/MS) and investigated whether these alterations affected the severity of acute pancreatitis. In the cerulein-induced pancreatitis model, 93 and 129 metabolites were detected in the serum and pancreatic tissue, respectively. In the L-arginine-induced acute pancreatitis model, 120 and 133 metabolites were detected in the serum and pancreatic tissue, respectively. Among the metabolites, the concentrations of tricarboxylic acid (TCA) cycle intermediates and amino acids were altered in pancreatitis, and in pancreatic tissue, the levels of the intermediates involved in the initial part of the TCA cycle were increased and those of the intermediates involved in the latter part of the TCA cycle were decreased. Some metabolites exhibited similar changes in both pancreatitis mouse models, e.g., the levels of glutamic acid and O-phosphoethanolamine were significantly decreased in the pancreatic tissue. Supplementation with glutamic acid and O-phosphoethanolamine attenuated the severity of cerulein-induced acute pancreatitis. Our results suggest that GC/MS-based metabolomics is capable of accurately representing the status of acute pancreatitis, leading to the discovery of therapeutic agents for pancreatitis.     

Metabolomic analysis of a human oral glucose tolerance test reveals fatty acids as reliable indicators of regulated metabolism

Gas chromatography/mass spectrometry-based metabolomics was applied to investigate dynamic changes in the plasma metabolome upon an oral glucose tolerance test (OGTT). The OGTT is a frequently used diagnostic test of glucose homeostasis and diabetes. Diabetes is diagnosed either when glucose levels ≥7.0 mM in the fasting state or ≥11.0 mM at 2 h after oral glucose intake. The accuracy of the OGTT would, however, most likely improve if additional variables could be identified. In the present study, plasma samples were drawn every 15 min for 2 h after an oral glucose load of 75 g preceded by an overnight fast in healthy individuals. Blood plasma levels of more than 200 putative metabolites were measured. Multivariate modelling was used to distinguish metabolic regulation due to the glucose challenge from that of other variability. Two data scaling methods were applied, yielding similar results when evaluated by appropriate diagnostic tools. Fatty acid levels were found to be strongly decreased during the OGTT. Also, the levels of amino acids were shown to decrease. However, technical and uninduced biological variations were found to affect the amino acid levels to a greater extent than the fatty acid levels, making the fatty acids more reliable as indicators of metabolic regulation. Levels of several metabolites correlated with the quadratic glucose profile and two were found having an inverse correlation. Raw data plots of all identified significantly altered metabolites confirmed the excellent performance of the multivariate models. Using this approach, a better understanding of the metabolic response to an OGTT can be achieved, paving the way for inclusion of other variables describing appropriate metabolic control.     

Complement and the alternative pathway play an important role in LPS/D-GalN-induced fulminant hepatic failure

Fulminant hepatic failure (FHF) is a clinically severe type of liver injury with an extremely high mortality rate. Although the pathological mechanisms of FHF are not well understood, evidence suggests that the complement system is involved in the pathogenesis of a variety of liver disorders. In the present study, to investigate the role of complement in FHF, we examined groups of mice following intraperitoneal injection of LPS/D-GalN: wild-type C57BL/6 mice, wild-type mice treated with a C3aR antagonist, C5aR monoclonal antibody (C5aRmAb) or CR2-Factor H (CR2-fH, an inhibitor of the alternative pathway), and C3 deficient mice (C3^−/− mice). The animals were euthanized and samples analyzed at specific times after LPS/D-GalN injection. The results show that intraperitoneal administration of LPS/D-GalN activated the complement pathway, as evidenced by the hepatic deposition of C3 and C5b-9 and elevated serum levels of the complement activation product C3a, the level of which was associated with the severity of the liver damage. C3a receptor (C3aR) and C5a receptor (C5aR) expression was also upregulated. Compared with wild-type mice, C3^−/− mice survived significantly longer and displayed reduced liver inflammation and attenuated pathological damage following LPS/D-GalN injection. Similar levels of protection were seen in mice treated with C3aR antagonist,C5aRmAb or CR2-fH. These data indicate an important role for the C3a and C5a generated by the alternative pathway in LPS/D-GalN-induced FHF. The data further suggest that complement inhibition may be an effective strategy for the adjunctive treatment of fulminant hepatic failure.     

Metabolic profiling analysis of a D-galactosamine/lipopolysaccharide-induced mouse model of fulminant hepatic failure

The purpose of this study was to characterize the changes in metabolic intermediates and to investigate the metabolic profile of a mouse model of fulminant hepatic failure (FHF), induced by D-galactosamine/lipopolysaccharide (GalN/LPS). Plasma metabolite levels were detected using gas chromatography/time-of-flight mass spectrometry, and the acquired data were transferred into Simca-P and processed using principal components analysis (PCA). In total, 45 metabolites were identified from the 267 distinct compounds found in the study. Whereas significant differences were noted in the plasma levels of the control and FHF groups, no differences in gluconeogenesis or glycolysis were noted following GalN/LPS treatment. Our data also suggest that the production of ketone bodies, and the tricarboxylic acid and urea cycles, was inhibited. PCA data suggest that 5-hydroxyindoleacetic acid, glucose, beta-hydroxybutyrate, and phosphate parameters had the highest weights on each of the principal components, and that they were the most important metabolites contributing to the separation of groups. In conclusion, this metabonomic approach can be used as a powerful tool to characterize changes in metabolic intermediates and to search for metabolic markers under certain pathophysiological conditions, such as FHF. Our data also demonstrate that a combination of 5-hydroxyindoleacetic acid, glucose, beta-hydroxybutyrate, and phosphate concentrations in the plasma is a potential marker for FHF, as well as for the early prognosis of FHF.     

Diet-induced hyperinsulinemia differentially affects glucose and protein metabolism: a high-throughput metabolomic approach in rats

Metabolomics is a high-throughput tool that quantifies and identifies the complete set of biofluid metabolites. This “omics” science is playing an increasing role in understanding the mechanisms involved in disease progression. The aim of this study was to determine whether a nontargeted metabolomic approach could be applied to investigate metabolic differences between obese rats fed a high-fat sucrose (HFS) diet for 9 weeks and control diet-fed rats. Animals fed with the HFS diet became obese, hyperleptinemic, hyperglycemic, hyperinsulinemic, and resistant to insulin. Serum samples of overnight-fasted animals were analyzed by ¹H NMR technique, and 49 metabolites were identified and quantified. The biochemical changes observed suggest that major metabolic processes like carbohydrate metabolism, β-oxidation, tricarboxylic acid cycle, Kennedy pathway, and folate-mediated one-carbon metabolism were altered in obese rats. The circulating levels of most amino acids were lower in obese animals. Serum levels of docosahexaenoic acid, linoleic acid, unsaturated n-6 fatty acids, and total polyunsaturated fatty acids also decreased in HFS-fed rats. The circulating levels of urea, six water-soluble metabolites (creatine, creatinine, choline, acetyl carnitine, formate, and allantoin), and two lipid compounds (phosphatidylcholines and sphingomyelin) were also significantly reduced by the HFS diet intake. This study offers further insight of the possible mechanisms implicated in the development of diet-induced obesity. It suggests that the HFS diet-induced hyperinsulinemia is responsible for the decrease in the circulating levels of urea, creatinine, and many amino acids, despite an increase in serum glucose levels.     

Liquid chromatography–mass spectrometry-based metabolomics for authenticity assessment of fruit juices

High performance liquid chromatography?Cmass spectrometry (HPLC?CMS) technique, employing a hybrid triple quadrupole/linear ion trap (QqQ/LIT) mass analyzer, was used for comprehensive metabolomic fingerprinting of several fruit juices types, prepared from expensive (orange) or relatively low-priced (apple, grapefruit) fruits. Following the automated data mining and pre-treatment step, the suitability of the multivariate HPLC?CMS metabolomic data for authentication, i.e., classification of fruit juice and adulteration detection, was assessed with the use of advanced chemometric tools (principal component analysis, PCA, and linear discrimination analysis, LDA). The LDA classification model, constructed and validated employing a highly variable samples set, was able to reliably detect 15% addition of apple or grapefruit juice to orange juice. In the final stage of this study, high performance liquid chromatography?Cquadrupole?Cquadrupole-time-of-flight mass spectrometry (HPLC?CQqTOFMS) measurements were performed in order to obtain data for identification of pre-selected marker compounds using elemental formula calculation and online databases search.     

Gene expression profile analysis of the mouse liver during bacteria-induced fulminant hepatitis by a cDNA microarray system

Fulminant hepatic failure (FHF) is a disease characterized by sudden and severe impairment of liver function. To elucidate the mechanism involved in FHF, we adopted a murine model of FHF by administrating mice with heat-killed Propionibacterium acnes (P. acnes), followed by a low dose of lipopolysaccharide (LPS), and analyzed the dynamic change of gene expression profile of the murine liver using an in-house cDNA microarray system which contained most of the cDNAs encoding chemokines/cytokines and their receptors (33 chemokines/21 chemokine receptors, 28 cytokines/35 cytokine receptors) as well as 230 liver related proteins mostly selected by serial analysis of gene expression (SAGE). Among them, 335 genes were found to differ by more than 2-fold in at least one time point comparing with normal liver. Hierarchical cluster analysis revealed that except for a few genes, such as heme oxygenase (HO)-1 and nicotinamide N-methyltransferase (NNMT) of which expression increased, the expression of most of the genes encoding drug metabolizing enzymes decreased with the progress of the disease. The expression of the genes encoding chemokines/cytokines was dramatically changed, such as Mig, IP-10, RANTES, TNF-alpha, and IFN-gamma. In addition, the expression of those that were not previously linked to this murine model was also identified to be changed. These include endogenous IL-18 binding protein (IL-18BP), CXCL16 (the ligand of Bonzo, CXCR6) as well as ESTs. Taken together this study has shown the systemic and comprehensive gene expression profile during FHF and may contribute to better understanding of the mechanism of FHF.     

Application of neural computing methods for interpreting phospholipid fatty acid profiles of natural microbial communities

The microbial community compositions of surface and subsurface marine sediments and sediments lining burrows of marine polychaetes and hemichordates from the North Inlet estuary (near Georgetown, S.C. ) were analyzed by comparing ester-linked phospholipid fatty acid (PLFA) profiles with a back-propagating neural network (NN). The NNs were trained to relate PLFA inputs to sediment type outputs (e.g., surface, subsurface, and burrow lining) and worm species (e.g., Notomastus lobatus, Balanoglossus aurantiacus, and Branchyoasychus americana). Sensitivity analysis was used to determine which of the 60 PLFAs significantly contributed to training the NN. The NN architecture was optimized by changing the number of hidden neurons and calculating the cross-validation error between predicted and actual outputs of training and test data. The optimal NN architecture was found to be four hidden neurons with 60-input neurons representing the 60 PLFAs, and four output neurons coding for both sediment types and worm species. Comparison of cross-validation results using NNs and linear discriminant analysis (LDA) revealed that NNs had significantly fewer incorrect classifications (2.7%) than LDA (8.4%). For the NN cross-validation, both sediment type and worm species had 3 incorrect classifications out of 112. For the LDA cross-validation, sediment type and worm species had 7 and 12 incorrect classifications out of 112, respectively. Sensitivity analysis of the trained NNs revealed that 17 fatty acids explained 50% of variability in the data set. These PLFAs were highly different among sediments and burrow types, indicating significant differences in the microbiota.