Seeding multivariate algorithms for spectral analysis, a data augmentation approach to enhance analytical performance.

Adenovirus 5 serotype vector-specific immunity and HIV-1 infection: a tale of T cells and antibodies

Breast cancer is a malignant tumor which threat to women's physical and mental health. Delphinidin, one of the main anthocyanidins, has potent anti-cancer properties. In previous study, we found that delphinidin has the preventive role in MNU-induced breast carcinogenesis of rats, but the molecular mechanism by which delphinidin combats breast cancer has not been completely elucidated.The aim of the present study was to identify metabolic profile that account for delphinidin on the preventive effect on 1-methyl-1-nitrosourea (MNU)-induced breast carcinogenesis of rats. In the present study, liquid chromatography-mass spectrometry (LC-MS) was conducted to identify metabolic profiles of rat tissues collected from normal mammary glands (normal group), breast tumors derived from MNU-induced breast carcinogenesis models (control group) and delphinidin administration models (delphinidin group). Principal component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) were employed to identify biochemical patterns. The values of variable importance in the projection (VIP) in PLS-DA model combined with the P value of Student's t-test were used to determine important metabolites. An orthogonal partial least square discriminant analysis (OPLS-DA) was used to conduct the supervised analysis. The fitness and prediction capabilities of PCA modes were measured by R 2 and Q 2 value respectively. Potential biomarkers were subjected to pathway analysis with Metaboanalyst 3.0 based on the KEGG Pathway Database to identify related metabolic pathways. The PCA and PLS-DA analysis indicated that the proposed method were satisfactory for metabolomic analysis. Metabolites from the obtained features were further filtered by PLS-DA analysis with VIP>1.0 and P<0.05. The significant difference was appeared in 190 metabolites between normal group and control group (P<0.05). Eight most significant metabolic pathways were obtained on the basis of the results of P<0.05 data analysis between control and normal group, embodying in aminoacyl-tRNA biosynthesis, arginine biosynthesis, biosynthesis of unsaturated fatty acids, valine, leucine and isoleucine biosynthesis, purine metabolism, alanine, aspartate and glutamate metabolism, glycerophospholipid metabolism, histidine metabolism. A total of 48 metabolites were identified to be associated with protective effects of delphinidin on MNU-induced rats significantly(P<0.05). Compared with control group, a total of 5 metabolic pathways were significantly perturbed in response to delphinidin administration (p<0.05), including in taurine and hypotaurine metabolism, Glycerophospholipid metabolism, arachidonic acid metabolism, aminoacyl-tRNA biosynthesis and primary bile acid biosynthesis. Metabolites and metabolic pathways were identified to be associated with protective effects of delphinidin on MNU-induced rats. The findings provided new insights into the precise mechanism of delphinidin in preventing breast carcinogenesis.

Remote sensing technology provides an unprecedented tool for the continuous and real-time monitoring of atmospheric SO2 from volcanic eruption and anthropogenic emission. The Global Ozone Monitoring Experiment (GOME), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), and Ozone Monitoring Instrument (OMI) have high SO2 monitoring capability. The OMI, which was launched on the EOS/Aura platform in July 2004, has the same hyperspectral measurements as the GOME and SCIAMACHY, but offers the improved spatial resolution at nadir (1324 km2) and daily global coverage for short-lifetime SO2. For OMI operational SO2 planetary boundary layer (PBL) retrieval, the previous band residual difference (BRD) algorithm has been replaced by principal component analysis (PCA) algorithm, which effectively reduces the systematic biases in SO2 column retrievals. However, there are few studies on the evaluations and validations of PCA SO2 retrievals over China, and the long-term comparisons with BRD SO2 retrievals also need to be conducted. In this study, the accuracies of PCA and BRD SO2 retrievals are validated by using ground-based multi axis differential optical absorption spectroscopy (MAX-DOAS) located in Beijing, and regional atmospheric modeling system, community multi-scale air quality (RAMS-CMAQ) modeling system model which can simulate the vertical distribution of atmospheric SO2. Moreover, BRD and PCA SO2 retrievals from oceanic area, eastern China and Reunion volcanic eruption are compared to find the long-term trend and spatiotemporal differences between SO2 columns. Finally, the uncertainty of SO2 retrieval, caused by measurement errors, band selection and input parameter errors in radiative transfer model, are analysed to understand the limitations of BRD and PCA algorithms. Results show that both PCA and BRD SO2 retrievals over Beijing are lower than ground-based MAX-DOAS measurements of SO2. PCA and BRD SO2 retrievals over eastern China are lower than the simulated SO2 columns from RAMS-CMAQ in winter 2008, but in July and August BRD SO2 columns are higher than RAMS-CMAQ simulations. The values of SO2 columns from BRD over China are more consistent with those from ground-based MAX-DOAS and RAMS-CMAQ model than from PCA. Although PCA algorithm effectively reduces the noise in SO2 column retrieval, SO2 columns from PCA over China are lower than those from BRD. For oceanic area where SO2 amount is nearly zero, the standard deviation of PCA results is lower than that of BRD, but the absolute value of averaged PCA SO2 column is larger than that of BRD. In the case of Reunion volcanic eruption with SO2 columns larger than 25 DU, the BRD SO2 columns are lower than PCA retrievals. Meanwhile, with the increase of SO2 column, the difference between BRD and PCA SO2 retrievals increases. Detailed uncertainty analysis shows the influences of measurement errors, band selection and inputs of radiative transfer model on the retrieval results. This study is important for developing the retrieval algorithm, and can also improve the application of OMI SO2 products.

In the present work, we have attempted a comprehensive analysis of cytosolic and microsomal proteomes to elucidate the signaling pathways impaired in human hepatoma (Huh7) cells upon herpes simplex virus type 1 (HSV-1; Cgal(+)) infection. Using a combination of differential in-gel electrophoresis and nano liquid chromatography/tandem mass spectrometry, 18 spots corresponding to 16 unique deregulated cellular proteins were unambiguously identified, which were involved in the regulation of essential processes such as apoptosis, mRNA processing, cellular structure and integrity, signal transduction, and endoplasmic-reticulum-associated degradation pathway. Based on our proteomic data and additional functional studies target proteins were identified indicating a late activation of apoptotic pathways in Huh7 cells upon HSV-1 Cgal(+) infection. Additionally to changes on RuvB-like 2 and Bif-1, down-regulation of Erlin-2 suggests stimulation of Ca(2+)-dependent apoptosis. Moreover, activation of the mitochondrial apoptotic pathway results from a time-dependent multi-factorial impairment as inferred from the stepwise characterization of constitutive pro- and anti-apoptotic factors. Activation of serine-threonine protein phosphatase 2A (PP2A) was also found in Huh7 cells upon HSV-1 Cgal(+) infection. In addition, PP2A activation paralleled dephosphorylation and inactivation of downstream mitogen-activated protein (MAP) kinase pathway (MEK(1/2), ERK(1/2)) critical to cell survival and activation of proapoptotic Bad by dephosphorylation of Ser-112. Taken together, our results provide novel molecular information that contributes to define in detail the apoptotic mechanisms triggered by HSV-1 Cgal(+) in the host cell and lead to the implication of PP2A in the transduction of cell death signals and cell survival pathway arrest.

Background: Key pathogenetic mechanisms underlying renal disease progression are unaffected by current treatment. Metabolite profiling has significantly contributed to a deeper understanding of the biochemical metabolic networks and pathways in disease, but the biochemical details in maintenance hemodialysis (MHD) patients remain largely undefined. Methods: The metabolic fingerprinting of plasma samples from 19 MHD patients and 12 healthy controls was characterized using liquid chromatography quadrupole time-of-flight mass spectrometry. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied to analyze the metabolic data. Results: The plasma metabolite profile distinguished the MHD patients from the healthy controls successfully by using both PCA and OPLS-DA models. Sixty-three metabolites were identified as the key metabolites to discriminate the MHD patients from healthy controls, involving several metabolic pathways (all p < 0.05). An increase in plasma levels of D-glucose, hippuric acid, androsterone glucuronide, indolelactic acid, and a reduction in plasma levels of glycerophosphocholine, serotonin, L-lactic acid, phytosphingosine, and several lysophosphatidylcholine were observed in MHD patients compared to healthy subjects. Metabolomics analysis combined with KEGG pathway enrichment analysis revealed that non-alcoholic fatty liver disease, choline metabolism in cancer, the forkhead box O signaling pathway, and the hypoxia-inducible factor-1 signaling pathway in MHD patients were significantly changed (p < 0.05). Conclusion: The identification of a novel signaling pathway and key metabolite markers in MHD patients provides insights into potential pathogenesis and valuable pharmacological targets for end-stage renal disease.

The increase of urban impervious surface has significant influence on the urban ecological environment, also contributes to urban waterlogging and urban heat island (UHI). Therefore, the remote sensing extraction of urban impervious surface becomes a hotspot. The widely used sub-pixel approach - Linear Spectral Mixture Analysis (LSMA) estimates the impervious surface by adding the high albedo (the bright impervious surface) and the low albedo (the dark impervious surface) from the solving percentage of different objects from mixed pixels. However for the approach, the selection of end members is difficult and some misclassifications will occur, which causes a large area error, and low accuracy of the impervious surface area. For these issue, in this study, a modified LSMA is explored combining with high-resolution image (Google earth image, 2 meters), the Principal Component Analysis (PCA) and the Normalized Difference Building Index (NDBI) to extract the impervious surface of Guangzhou city with Landsat 8 OLI, October 2015. Based on the PCA, and high resolution image are employed to accurate the selection of end members. The LSMA based on the PCA, the modified LSMA based on the PCA and NDBI are taken to extract the impervious surface of the research area. And the Google earth image is for screening the end members and testing the accuracy estimation by sample area. The result shows that after the accurate topographic correction, the modified LSMA based on the PCA and NDBI is better than the conventional LSMA based on the PCA. The area precision of impervious surface in research area by the modified LSMA is improved with the correlation coefficient is 0.947. The study indicates that taking the high resolution images, the PCA and NDBI to improve the LSMA can raise the un-mix accuracy to a certain degree.

Polynuclear platinum(II) complexes represent a class of potential anticancer agents that have shown promising pharmacological properties in preclinical studies. The nature of cellular responses induced by these complexes, however, is poorly understood. In this research, the cellular responses of human ovarian cancer COC1 cells to dinuclear platinum(II) complexes {[cis-Pt(NH₃)₂Cl]₂L¹}(NO₃)₂ (1) and {[cis-Pt(NH₃)₂Cl]₂L²}(NO₃)₂ (2) (L¹ = α,α'-diamino-p-xylene, L² = 4,4'-methylenedianiline) has been studied using cisplatin as a reference. The effect of platinum complexes on the proliferation, death mode, mitochondrial membrane potential, and cell cycle progression has been examined by MTT assay and flow cytometry. The activation of cell cycle checkpoint kinases (CHK1/2), extracellular signal-regulated kinases (ERK1/2), and p38 mitogen-activated protein kinase (p38 MAPK) of the cells by the complexes has also been analyzed using phospho-specific flow cytometry. Complex 1 is more cytotoxic than complex 2 and cisplatin at most concentrations; complex 2 and cisplatin are comparably cytotoxic. These complexes kill the cells through an apoptotic or apoptosis-like pathway characterized by exposure of phosphatidylserine and dissipation of mitochondrial membrane potential. Complex 1 shows the strongest inductive effect on the morphological changes of the cells, followed by cisplatin and complex 2. Complexes 1 and 2 arrest the cell cycle in G2 or M phase, while cisplatin arrests the cell cycle in S phase. The influence of these complexes on CHK1/2, ERK1/2, and p38 MAPK varies with the dose of the drugs or reaction time. Activation of phospho-ERK1/2 and phospho-p38 MAPK by these complexes is closely related to the cytostatic activity. The results demonstrate that dinuclear platinum(II) complexes can induce some cellular responses different from those caused by cisplatin.

Chronic Ethanol Consumption Impairs Cellular Immune Responses Against HCV NS5 Protein Due to Dendritic Cell Dysfunction

Imaging mass spectrometry is an innovative technique that combines high-resolution microscopic imaging tools with analytical capabilities of spectrometry. It is a powerful tool to determine the spatial distribution of chemical compounds on complex surfaces, for example, for microscale analysis of cells and tissue in biological samples. The result is a large spectral datacube: a three-dimensional (3D) dataset in which surface position and mass spectral distribution are represented. Analysts try to discover ‘features’: correlations in spectral profiles with a recognizable spatial distribution. Techniques for feature extraction and visualization are developed to improve the exploratory analysis of spectral datacubes. The topic of this work is the design and implementation of feature extraction and visualization techniques in high-resolution imaging spectrometry data. Principal Component Analysis (PCA) is interactively used as a governing approach for feature detection. A wide range of visualization techniques are implemented based on extracted features. The thesis is organized as follows. In Chapter 2 (Spectral analysis: a survey), we provide a brief background survey on spectral analysis. The analysis in the proposed approach is divided into three stages: data acquisition, feature extraction and feature visualization. For each stage, a detailed description of currently applied methods is given. The methods most appropriate for this qualitative approach of analysis are chosen as a specific subset. PCA in combination with a binning function is most suited for extracting features from imaging mass spectral data. Both methods increase the signal-to-noise ratio and reduce the amount of data from imaging mass spectrometry. Chapter 3 (PCA-based feature extraction) compares the quality of three different PCA-based methods for detecting and extracting features from spectral datacubes. We discuss preprocessing of mass spectral data, PCA, additional rotational optimization by VARIMAX, and the PARAFAC method for factor regression. The results are compared quantitatively and qualitatively, together with some performance characteristics. For the quantitative comparison, we used a RMSE metric to compare the methods with ground truth spectra under various noise conditions. For the qualitative comparison, we used three criteria to judge the quality of features in the resulting visualizations. These criteria were applied to interpret the visualizations of features. In Chapter 4 (Feature-based registration), a robust method for automatic featurebased registration is developed. The reduction of uncorrelated noise provided by PCA allows high-resolution imaging mass spectrometry datasets to be automatically aligned and combined for high-resolution analysis of large areas. The results clearly show that the entropy-weighted, mean squared error landscape of chemically matched component images can be used to automatically align high-resolution imaging mass spectrometry datasets. Several spectral datacubes are combined to provide better detection and extraction of features. In Chapter 5 (Feature visualization), a visualization technique is described that utilizes principal components to create transfer functions for volume rendering of a spectral datacube. Two types of spectral datacubes are visualized in 3D by direct volume rendering with these transfer functions to control opacity and highlight extracted features. This enables us to visualize the link between the spectral and spatial characteristics of a feature within the spectral datacube. Applications demonstrate the additional value of these visualizations. Chapter 6 (Feature zooming) presents a technique for spectral and/or spatial zooming of extracted features. This technique is especially useful for spatially extended datasets. The combined spectral datasets are too large in size to be explored and visualized using commonly feature extraction and visualization techniques. Analysts are able to select important features or deselect unimportant features for further analysis on different levels of detail. Moreover, features with unwanted artifacts can be removed to reduce noise. Chapter 7 (High-resolution feature visualization) provides an approach to parametrically visualize features in 3D and at the highest resolution possible. Three parameters control the spectral contribution, the level of detail and the level of density on which an extracted feature is represented. This visualization has feature shapes with well-defined borders and provides more insight into the influences of noise on a mass spectral measurement. It is possible to distinguish different peaks according to their difference in density and spatial position, which would not be possible in a separate spectral or spatial view. An application shows how resulting features are visualized and interpreted. The developed tools generate new possibilities to handle, explore, and visualize the large imaging mass spectrometry datasets. A sensitive, selective, and robust approach for feature extraction enables detection and classification of features in different proteomics applications. Multiple feature shapes with high-resolution characteristics can be compared and examined on different levels of detail. These visualizations can provide more detailed molecular insight in the biochemistry of surfaces and improve classification of peptides and proteins.

Varicella-zoster virus (VZV) causes both primary varicella, and through reactivation of the virus, herpes zoster. It is hypothesized that VZV-immune adults may reduce the probability of developing herpes zoster through exposure to varicella. In this study we examine the existence of immunological boosting in VZV-immune adults after close contact with primary varicella. We followed-up 18 parents with household exposure to primary varicella for 1 y. Fifteen age-matched healthy and 20 older volunteers served as control groups. Cellular (IFN-γ ELISPOT) and humoral responses were measured. Data analyses were performed by t-tests and linear mixed models. The young control group only showed higher cellular responses than the older control group and the exposed group 1 mo after exposure. The exposed group had a strong tendency toward higher cellular responses compared to the older control group, reaching significance 1 y post-exposure. The best fitting linear mixed model predicts a decline in cellular response of 50% between 1 wk and 1 mo post-exposure, followed by an increase to attain an 80% higher level at 1 y compared to the first week post-exposure. No significant results emerged based on the humoral response of the individual parents in the exposed group, despite a general tendency toward higher antibody concentrations in the exposed versus the control groups. No significant difference in humoral immunity was found between the control groups. One year after initial re-exposure to VZV, VZV-immune adults showed a rise in cellular response as assessed by IFN-γ ELISPOT, and steady-state levels for the humoral response.

BackgroundOxylipins and endocannabinoids are low molecular weight bioactive lipids that are crucial for initiation and resolution of inflammation during microbial infections. Metabolic complications in malaria are recognized contributors to severe and fatal malaria, but the impact of malaria infection on the production of small lipid derived signalling molecules is unknown. Knowledge of immunoregulatory patterns of these molecules in malaria is of great value for better understanding of the disease and improvement of treatment regimes, since the action of these classes of molecules is directly connected to the inflammatory response of the organism.MethodsDetection of oxylipins and endocannabinoids from plasma samples from forty children with uncomplicated and severe malaria as well as twenty controls was done after solid phase extraction followed by chromatography mass spectrometry analysis. The stable isotope dilution method was used for compound quantification. Data analysis was done with multivariate (principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA®) and univariate approaches (receiver operating characteristic (ROC) curves, t tests, correlation analysis).ResultsForty different oxylipin and thirteen endocannabinoid metabolites were detected in the studied samples, with one oxylipin (thromboxane B2, TXB2) in significantly lower levels and four endocannabinoids (OEA, PEA, DEA and EPEA) at significantly higher levels in infected individuals as compared to controls according to t test analysis with Bonferroni correction. Three oxylipins (13-HODE, 9-HODE and 13-oxo-ODE) were higher in severe compared to uncomplicated malaria cases according to the results from multivariate analysis. Observed changes in oxylipin levels can be connected to activation of cytochrome P450 (CYP) and 5-lipoxygenase (5-LOX) metabolic pathways in malaria infected individuals compared to controls, and related to increased levels of all linoleic acid oxylipins in severe patients compared to uncomplicated ones. The endocannabinoids were extremely responsive to malaria infection with majority of this class of molecules found at higher levels in infected individuals compared to controls.ConclusionsIt was possible to detect oxylipin and endocannabinoid molecules that can be potential biomarkers for differentiation between malaria infected individuals and controls and between different classes of malaria. Metabolic pathways that could be targeted towards an adjunctive therapy in the treatment of malaria were also pinpointed.

The fatty acid binding protein (FABP) family of proteins plays a role in multiple myeloma cell survival and disease progression in vitro and in silico, and thus blocking the FABPs could have anti-cancer effects and prove beneficial for myeloma patients.

BackgroundProstate cancer (PCa) tumors harboring translocations of ETS family genes with the androgen responsive TMPRSS2 gene (ETS+ tumors) provide a robust biomarker for detecting PCa in approximately 70% of patients. ETS+ PCa express high levels of the androgen receptor (AR), yet PCa tumors lacking ETS fusions (ETS−) also express AR and demonstrate androgen-regulated growth. In this study, we evaluate the differences in the AR-regulated transcriptomes between ETS+ and ETS− PCa tumors.Methods10,608 patient tumors from three independent PCa datasets classified as ETS+ (samples overexpressing ERG or other ETS family members) or ETS− (all other PCa) were analyzed for differential gene expression using false-discovery-rate adjusted methods and gene-set enrichment analysis (GSEA).ResultsBased on the expression of AR-dependent genes and an unsupervised Principal Component Analysis (PCA) model, AR-regulated gene expression alone was able to separate PCa samples into groups based on ETS status in all PCa databases. ETS status distinguished several differentially expressed genes in both TCGA (6.9%) and GRID (6.6%) databases, with 413 genes overlapping in both databases. Importantly, GSEA showed enrichment of distinct androgen-responsive genes in both ETS− and ETS+ tumors, and AR ChIP-seq data identified 131 direct AR-target genes that are regulated in an ETS-specific fashion. Notably, dysregulation of ETS-dependent AR-target genes within the metabolic and non-canonical WNT pathways was associated with clinical outcomes.ConclusionsETS status influences the transcriptional repertoire of the AR, and ETS− PCa tumors appear to rely on distinctly different AR-dependent transcriptional programs to drive and sustain tumorigenesis.

Voreloxin is a first-in-class anticancer quinolone derivative that intercalates DNA and poisons topoisomerase II (Stockett et al. and Hawtin et al., AACR 2008). This leads to replication-dependent, site-selective DNA double strand breaks (DSB) targeting G/C-rich sequences that are characteristic sites of quinolone-induced DNA cleavage (Noble et al, 2003, Richter et al 2007, Stockett et al, AACR 2008). A consequence of this DNA damage is G2 arrest and cell death by apoptosis. Voreloxin is under clinical investigation in acute myeloid leukemia (AML) and ovarian cancer. Clinical responses have been observed in these indications (Lancet et al., ASCO 2009; Maris et al., ASCO 2009; McGuire et al., SGO 2008), as well as in NSCLC and SCLC (Burris et al., ECCO 2007). The current analysis was performed in support of the ongoing phase 1b/2 study clinical study (SPO-0012) of voreloxin in combination with cytarabine in relapsed or refractory AML. The purposes were to; (1) characterize voreloxin-induced biomarkers of mechanism-based pharmacodynamic (PD) activity in cell lines and peripheral blood mononuclear cells (PBMC) from AML patients; (2) differentiate between the cellular PD DNA damage responses to voreloxin and cytarabine; (3) profile patient PBMC before and following the combination treatment with voreloxin and cytarabine in SPO-0012, to evaluate PD markers of cellular response; (4) investigate potential correlations between cellular PD markers of DNA damage and clinical outcome. Based on our understanding of voreloxin's mechanism of action, pharmacodynamic (PD) markers of S phase delay, G2 arrest and DNA damage following treatment with voreloxin were profiled in cell lines and then evaluated in primary AML cells. These included markers of stalled replication forks (pRPA-32, pCHK1) and DNA DSB (DNA-PKcs, p53, and pCHK2). Cellular response to cytarabine was also characterized in these in vitro model systems. Cytarabine is a mainstay of treatment in AML, administered for 7 days per treatment cycle in combination with daunorubicin on days 1–3 (the “7+3” treatment schedule). Cytarabine is incorporated into DNA and causes inhibition of DNA polymerase resulting in decreased DNA synthesis and repair. DNA damage responses were observed with cytarabine, but these occurred later than with voreloxin treatment. Voreloxin induction of pDNA-PKcs and pCHK2 were chosen for PD assessments in the ongoing phase 1b/2 study of voreloxin in combination with cytarabine in relapsed or refractory AML. PBMC were purified from blood samples collected from patients at time points pre- and post-dosing. Upregulation of pDNA-PKcs and pCHK2 was detected within 2 hours post-dose, providing evidence of mechanism-based PD responses to voreloxin. Inconsistent quality of PBMC preparation at individual sites precluded correlation of PD response with clinical outcome. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C226.

Lipid phosphate phosphatases: more than one way to put the brakes on LPA signaling?