Additional file 1: of Is the presence of HCMV components in CNS tumors a glioma-specific phenomenon?

Table S1. Expression of HCMV proteins and DNA in glioma and non glial tumors of CNS. Figure S1. Nested PCR analysis of HCMV DNA from peripheral blood samples. No HCMV DNA was detected in benign meningioma (lane 1), malignant meningioma(lane 2), PRL pituitary adenoma(lane 3), GH pituitary adenoma(lane 4), ACTH pituitary adenoma(lane 5), cavernous hemangioma(lane 6) and metastatic carcinoma samples(lane 7) (DOCX 41 kb

Image1_Integrated untargeted and targeted metabolomics to reveal therapeutic effect and mechanism of Alpiniae oxyphyllae fructus on Alzheimer’s disease in APP/PS1 mice.tif

Introduction:Alpiniae oxyphyllae Fructus (AOF) has been abundantly utilized for the treatment of diarrhea, dyspepsia, kidney asthenia, and abdominal pain in China. AOF is effective for treating AD in clinical trials, but its exact mode of action is yet unknown.Methods: In this study, metabolomics was combined to ascertain the alterations in plasma metabolism in APP/PS1 transgenic mice, the therapy of AOF on model mice, and the dynamic variations in 15 bile acids (BAs) concentration.Results: 31 differential biomarkers were finally identified in APP/PS1 group vs. the WT group. The levels of 16 metabolites like sphinganine (Sa), lyso PE (20:2), lysoPC (17:0), glycocholic acid (GCA), deoxycholicacid (DCA) were increased in APP/PS1 group, and those of 15 metabolites like phytosphingosine, cer (d18:0/14:0), and fumaric acid were reduced in APP/PS1 group. After AOF treatment, 29 of the 31 differential metabolites showed a tendency to be back-regulated, and 15 metabolites were significantly back-regulated, including sphinganine (Sa), lyso PE (20:2), glycocholic acid (GCA), deoxycholic acid (DCA). The relationship between BAs level and AD had been received increasing attention in recent years, and we also found notable differences between DCA and GCA in different groups. Therefore, a BAs-targeted metabonomic way was established to determine the level of 15 bile acids in different groups. The consequence demonstrated that primary BAs (CA, CDCA) declined in APP/PS1 model mice. After 3 months of AOF administration, CA and CDCA levels showed an upward trend. Conjugated primary bile acids (TCA, GCA, TCDCA, GCDCA), and secondary bile acids (DCA, LCA, GDCA, TDCA, TLCA GLCA) ascended in APP/PS1 group. After 3 months of AOF treatment, the levels of most BAs decreased to varying degrees. Notably, the metabolic performance of DCA and GCA in different groups was consistent with the predictions of untargeted metabolomics, validating the correctness of untargeted metabolomics.Discussion: According to metabolic pathways of regulated metabolites, it was prompted that AOF ameliorated the symptom of AD mice probably by regulating bile acids metabolism. This study offers a solid foundation for further research into the AOF mechanism for the therapy of AD.</p

Differential metabolites identified in brain between M group vs. S group.

Differential metabolites identified in brain between M group vs. S group.</p

Table1_Integrated untargeted and targeted metabolomics to reveal therapeutic effect and mechanism of Alpiniae oxyphyllae fructus on Alzheimer’s disease in APP/PS1 mice.docx

Introduction:Alpiniae oxyphyllae Fructus (AOF) has been abundantly utilized for the treatment of diarrhea, dyspepsia, kidney asthenia, and abdominal pain in China. AOF is effective for treating AD in clinical trials, but its exact mode of action is yet unknown.Methods: In this study, metabolomics was combined to ascertain the alterations in plasma metabolism in APP/PS1 transgenic mice, the therapy of AOF on model mice, and the dynamic variations in 15 bile acids (BAs) concentration.Results: 31 differential biomarkers were finally identified in APP/PS1 group vs. the WT group. The levels of 16 metabolites like sphinganine (Sa), lyso PE (20:2), lysoPC (17:0), glycocholic acid (GCA), deoxycholicacid (DCA) were increased in APP/PS1 group, and those of 15 metabolites like phytosphingosine, cer (d18:0/14:0), and fumaric acid were reduced in APP/PS1 group. After AOF treatment, 29 of the 31 differential metabolites showed a tendency to be back-regulated, and 15 metabolites were significantly back-regulated, including sphinganine (Sa), lyso PE (20:2), glycocholic acid (GCA), deoxycholic acid (DCA). The relationship between BAs level and AD had been received increasing attention in recent years, and we also found notable differences between DCA and GCA in different groups. Therefore, a BAs-targeted metabonomic way was established to determine the level of 15 bile acids in different groups. The consequence demonstrated that primary BAs (CA, CDCA) declined in APP/PS1 model mice. After 3 months of AOF administration, CA and CDCA levels showed an upward trend. Conjugated primary bile acids (TCA, GCA, TCDCA, GCDCA), and secondary bile acids (DCA, LCA, GDCA, TDCA, TLCA GLCA) ascended in APP/PS1 group. After 3 months of AOF treatment, the levels of most BAs decreased to varying degrees. Notably, the metabolic performance of DCA and GCA in different groups was consistent with the predictions of untargeted metabolomics, validating the correctness of untargeted metabolomics.Discussion: According to metabolic pathways of regulated metabolites, it was prompted that AOF ameliorated the symptom of AD mice probably by regulating bile acids metabolism. This study offers a solid foundation for further research into the AOF mechanism for the therapy of AD.</p

Effect of AOF on AD model rats in MWM.

(A) Escape latency required for the rats to find the hidden platform over 5 consecutive training days; (B) Average swimming speeds of the rats during 5 training days; (C) Time in target quadrant in space exploration test (%). (D) Crossover times in previous platform location in space exploration test. Each column represents the mean ± SD for each group (n = 6 per group, * P < 0.05 versus sham group, ** P < 0.01 versus sham group; # P < 0.05 versus AD model group, ## P < 0.01 versus AD model group). S, sham group; M, AD model group; T, AOF group.</p

The experiment schedule.

Alpinia oxyphylla Fructus, called Yizhi in Chinese, is the dried fruit of Alpinia oxyphylla Miquel. It has been used in traditional Chinese medicine to treat dementia and memory defects of Alzheimer’s disease for many years. However, the underlying mechanism is still unclear. In this study, we used a rat Alzheimer’s disease model on intrahippocampal injection of aggregated Aβ1–42 to study the effects of Alpinia oxyphylla Fructus. A brain and plasma dual-channel metabolomics approach combined with multivariate statistical analysis was further performed to determine the effects of Alpinia oxyphylla Fructus on Alzheimer’s disease animals. As a result, in the Morris water maze test, Alpinia oxyphylla Fructus had a clear ability to ameliorate the impaired learning and memory of Alzheimer’s disease rats. 11 differential biomarkers were detected in AD rats’ brains. The compounds mainly included amino acids and phospholipids; after Alpinia oxyphylla Fructus administration, 9 regulated biomarkers were detected compared with the AD model group. In the plasma of AD rats, 29 differential biomarkers, primarily amino acids, phospholipids and fatty acids, were identified; After administration, 23 regulated biomarkers were detected. The metabolic pathways of regulated metabolites suggest that Alpinia oxyphylla Fructus ameliorates memory and learning deficits in AD rats principally by regulating amino acid metabolism, lipids metabolism, and energy metabolism. In conclusion, our results confirm and enhance our current understanding of the therapeutic effects of Alpinia oxyphylla Fructus on Alzheimer’s disease. Meanwhile, our work provides new insight into the potential intervention mechanism of Alpinia oxyphylla Fructus for Alzheimer’s disease treatment.</div

S6 Fig -

The OPLS-DA score plots from M group and T group in positive (A) and negative (C) ion mode in the brain. The permutations test of M vs. T group in positive (B) and negative (D) ion mode in the brain. M, AD model group; T, AOF group. (TIF)</p

Differential biomarkers and regulated biomarkers identified in plasma.

Differential biomarkers and regulated biomarkers identified in plasma.</p

Multivariate data analyses of plasma samples.

PCA score plots of different groups in positive (A) and negative (D) ion mode; The OPLS-DA score plots from M group and S group in positive (B) and negative (E) ion mode; The permutations test of M vs. S group in positive (D) and negative (F) ion mode. S, sham group; M, AD model group; T, AOF group.</p

DataSheet_1_Association of Coronary Artery Disease and Metabolic Syndrome: Usefulness of Serum Metabolomics Approach.docx

IntroductionIndividuals with metabolic syndrome (MetS) are at increasing risk of coronary artery disease (CAD). We investigated the common metabolic perturbations of CAD and MetS via serum metabolomics to provide insight into potential associations.MethodsNon-targeted serum metabolomics analyses were performed using ultra high-performance liquid chromatography coupled with Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap HRMS) in samples from 492 participants (272 CAD vs. 121 healthy controls (HCs) as cohort 1, 55 MetS vs. 44 HCs as cohort 2). Cross-sectional data were obtained when the participants were recruited from the First Affiliated Hospital of Zhengzhou University. Multivariate statistics and Student’s t test were applied to obtain the significant metabolites [with variable importance in the projection (VIP) values >1.0 and p values ResultsThirty metabolites were identified for CAD, mainly including amino acids, lipid, fatty acids, pseudouridine, niacinamide; 26 metabolites were identified for MetS, mainly including amino acids, lipid, fatty acids, steroid hormone, and paraxanthine. The logistic regression results showed that all of the 30 metabolites for CAD, and 15 metabolites for MetS remained significant after adjustments of clinical risk factors. In the common metabolic signature association analysis between CAD and MetS, 11 serum metabolites were significant and common to CAD and MetS outcomes. Out of this, nine followed similar trends while two had differing directionalities. The nine common metabolites exhibiting same change trend improved risk prediction for CAD (86.4%) and MetS (90.9%) using the ROC analysis.ConclusionSerum metabolomics analysis might provide a new insight into the potential mechanisms underlying the common metabolic perturbations of CAD and MetS.</p