Deep data analysis of conductive phenomena on complex oxide interfaces: physics from data mining.

Erratum to “Multivariate statistical analysis of atom probe tomography data” [Ultramicroscopy 110 (2010) 1362

Multivariate statistical analysis of sediment data (information matrix 123 × 16) from the Gulf of Mexico, USA shows that the data structure is defined by four latent factors conditionally called “inorganic natural”, “inorganic anthropogenic”, “bioorganic” and “organic anthropogenic” explaining 39.24%, 23.17%, 10.77% and 10.67% of the total variance of the data system, respectively. The receptor model obtained by the application of the PCR approach makes it possible to apportion the contribution of each chemical component for the latent factor formation. A separation of the contribution of each chemical parameter is achieved within the frames of “natural” and “anthropogenic” origin of the respective heavy metal or organic matter to the sediment formation process. This is a new approach as compared to the traditional “one dimensional” search with a limited number of preliminary selected tracer components. The model suggested divides natural from anthropogenic influences and allows in this way each participant in the sediment formation process to be used as marker of either natural or anthropogenic effects.

Fingerprint data from swine manure microbial community rRNAs and rRNA genes were treated by multivariate statistical and diversity analyses to differentiate swine manures. Microbial communities from finishing pig manure and from a mixture of manure slurries from maternity confinement and finishing pigs were characterized using a combination of amplicon length heterogeneity PCR (LH-PCR) and terminal restriction fragment length polymorphism (T-RFLP), using PCR primers targeting Bacteria and Archaea, respectively. Unweighted pair group method with arithmetic mean clustering, principal components analysis (PCA), indicator species analysis (ISA), and diversity analyses showed that rRNA-based fingerprinting methods [reverse transcription (RT)-LH-PCR and RT-T-RFLP] were more effective than rDNA-based fingerprinting methods for distinguishing the manure samples. Multiresponse permutation procedure from fingerprint data showed that all manure samples had distinct microbial communities. PCA and ISA showed that the major phylotypes differentiating the LH-PCR or the RT-LH-PCR profiles were distributed differently between manures, suggesting that the bacterial community structure was different from the metabolically active bacterial community. The detection of minor archaeal populations was greater using RT-T-RFLP instead of T-RFLP. The findings indicated that the analysis of microbial community rRNAs could differentiate each manure sample from the others and would be appropriate for the monitoring of metabolically active populations.

Classification of torbanite and cannel coal: II. Insights from pyrolysis-GC/MS and multivariate statistical analysis

Metabolic composition of healthy and infected Grüner Veltliner grapes and wine assessed by high resolution mass spectrometry

Extraction methods are critical in the production and success of an extra virgin olive oil ready for consumption. The first step of olive oil extraction procedure produces an olive paste, which is subsequently processed by separation of the liquid phases (oil and vegetable water) from the pomace. Profiles of Apulian extra virgin olive oils and the deuterated chloroform extracts of its paste and pomace were studied by 1D and 2D NMR (NMR) spectroscopy without separation and pre‐treatment of samples. In order to study the metabolic profiles variation in the paste and pomace extracts with respect to the corresponding EVOOs, multivariate statistical analyses (PCA and OPLS DA) of the1H NMR data were performed. As expected, a different minor components profile, in particular for the presence of higher content of secoiridoids, lignans and phenolic compounds in olive paste and pomace extracts with respect to the EVOOs, was observed.Practical applications:Amount of extractable oil from olive paste and pomace after the production processes of EVOO was measured by1H NMR spectroscopy. Identification of metabolites in olive paste and pomace was performed by 1D and 2D NMR spectroscopy without separation and pre‐treatment of samples. The chemical composition of major and minor components (in particular secoiridoids, lignans, and phenolic compounds) present in olive paste and pomace chloroform extracts could be used for extraction process trimming purposes as well as in fingerprint analyses for cultivar and/or geographical origin certification of olive oil production. Moreover, determination of the entire metabolic content of different materials of the olive oil production process could be exploited in other applications such as recycling on agricultural land, studies of the health benefits on human nutrition and alternative dietary lipid source in animals. In fact, it is worth noting that the olive paste and pomace extracts could be even healthier than other vegetable oils.The extraction processes are critical in the extra virgin olive oil production. The chemical composition of EVOOs and its paste and pomace extracts have been investigated by Nuclear Magnetic Resonance Spectroscopy (NMR).

Three-dimensional geological modelling and multivariate statistical analysis of water chemistry data to analyse and visualise aquifer structure and groundwater composition in the Wairau Plain, Marlborough District, New Zealand

Water containing high concentrations of nitrate is unfit for human consumption and, if discharging to freshwater or marine habitats, can contribute to algal blooms and eutrophication. The level of nitrate contamination in groundwater of two densely populated, agro-industrial areas of the Cameroon Volcanic Line (CVL) (Banana Plain and Mount Cameroon area) was evaluated. A total of 100 samples from boreholes, open wells and springs (67 from the Banana Plain; 33 from springs only, in the Mount Cameroon area) were collected in April 2009 and January 2010 and analyzed for chemical constituents, including nitrates. The average groundwater nitrate concentrations for the studied areas are: 17.28 mg/l for the Banana Plain and 2.90 mg/l for the Mount Cameroon area. Overall, groundwaters are relatively free from excessive nitrate contamination, with nitrate concentrations in only 6 % of groundwater resources in the Banana Plain exceeding the maximum admissible concentration for drinking water (50 mg/l). Sources of NO3− in groundwater of this region may be mainly anthropogenic (N-fertilizers, sewerage, animal waste, organic manure, pit latrines, etc.). Multivariate statistical analyses of the hydrochemical data revealed that three factors were responsible for the groundwater chemistry (especially, degree of nitrate contamination): (1) a geogenic factor; (2) nitrate contamination factor; (3) ionic enrichment factor. The impact of anthropogenic activities, especially groundwater nitrate contamination, is more accentuated in the Banana Plain than in the Mount Cameroon area. This study also demonstrates the usefulness of multivariate statistical analysis in groundwater study as a supplementary tool for interpretation of complex hydrochemical data sets.

Monitoring water quality of surface water resources is the key concern in determining the potable water quality in high-altitude region. Therefore, there is a need to evaluate different parameters affecting water quality of river and identify the most important variables and factors significantly affecting water quality. In the present study, multivariate statistical methods including cluster analysis and principal component analysis/factor analysis were applied to analyze the Indus River water quality in the Trans-Himalayan region of India. For this total 25 no. of physicochemical parameters were analyzed in water samples taken from seven different monitoring sites in summer and winter season. All the physical, microbial, chemical, and mineral parameters were analyzed by using the standard methods of American Public Health Association, whereas minerals were determined with the inductively coupled plasma optical emission of spectroscopy method. Thereafter, experimental two-season (28 samples × 25 parameters) matrices of both the seasons were run through the multivariate statistical data analysis. The varifactors obtained from the FA of both the seasons and results indicate that the parameters responsible for water quality variations are mainly related to discharge and temperature (natural), organic pollution (point source: domestic sanitary waste), and nutrients (non-point sources: agriculture) in the summer season. However, in the winter seasons, results showed that the river water was less affected by anthropogenic activities and natural weathering process. Therefore, it is concluded that quality of Indus River water is affected by agricultural, domestic, and hydrogeochemical sources in the summer season. These findings corroborate suitability of multivariate statistical techniques in the elucidation of various parameters for water quality monitoring and determination of different contamination sources.

To investigate the gene regulation of tumor cells in the process of different organ metastasis on a xenograft mouse model and screen the genes involved in the organ-target metastasis of tumor cells. A multi-organ metastasis model was constructed with a human ovarian clear cell carcinoma cell line (ES-2) based on a severe immunodeficiency mouse strain (NCG). Differentially expressed tumor proteins among multi-organ metastases were successfully characterized by microliter liquid chromatography-high-resolution mass spectrometry, sequence-specific data analysis and multivariate statistical data analysis. Liver metastases were selected as typical for subsequent bioinformatic analysis. Selected liver metastasis-specific genes in ES-2 cells were validated by sequence-specific quantitation including high resolution-multiple reaction monitoring quantification at protein level and quantitative real-time polymerase chain reaction at mRNA level. From the mass spectrometry data, a total of 4503 human proteins were identified using the sequence-specific data analysis strategy. Of them, 158 proteins were selected as specifically regulated genes in liver metastases for subsequent bioinformatics studies. Based on Ingenuity Pathway Analysis (IPA) pathway analysis and sequence-specific quantitation, Ferritin light chain (FTL), lactate dehydrogenase A (LDHA) and long-chain-fatty-acid-CoA ligase 1 (ACSL1) were finally validated as specifically upregulated proteins in liver metastases. Our work provides a new approach to analyze gene regulation in tumor metastasis in xenograft mouse model. In presence of a large number of mouse protein interference, we validated the up-regulation of human ACSL1, FTL and LDHA in ES-2 liver metastases, which reflects the adaptive regulation of tumor cells to the liver microenvironment through metabolic reprogramming.

In accordance with data provided from Mathematics Modeling Competition for National University students in 2012, it can be found whether grapes are high-quality or not as well as the direct relationship between the grape and wine quality by means of SPSS and other statistical softwares, through multivariate statistical analysis and data analysis, and by verifying the credibility what comments made on wine quality by members of liquor, additionally, quality classification on grapes is made through factor analysis.The physical and chemical indicators detected from wine and grapes reflect their quality to a certain extent.Through analysis of relationship between physical and chemical indicators concerning grapes and wine, a mathematical model used for evaluating wine quality with the help of physical and chemical indicators concerning grapes and wine is established, providing references for accurately evaluating wine quality.

The 10 species of Galaxias in Tasmania, G. olidus from mainland Australia and the four species of Paragalaxias were studied using principal co‐ordinates analysis (PCOA) and cluster analysis of a standardized Euclidean distance matrix based upon variate means, and by canonical variate analysis (CVA) conducted as a stepwise multiple discriminant analysis. Thirty‐five variables comprising 30 morphometric and five meristic characters were analysed. The meristic characters were not included in the CVA. Excellent separation of the two genera was achieved in all analyses. The multivariate analyses were repeated on each genus separately to see if relationships suggested by the overall analysis remain stable. When the resultant groupings of species are compared for the different analyses, no consistent, distinct groupings of species within each genus are apparent. Despite the absence of distinct groupings, some trends in the affinities of some species are evident. In particular, species affinities as indicated by the CVA are more consistent with established opinions of species relationships. From the results of the study it is suggested that caution be exercised in the application of multivariate statistical analyses of morphological data to ichthyological systematics and phylogeny.

This study aimed to investigate the metabolic profile of gestational diabetes mellitus (GDM) at both antepartum and postpartum periods. Seventy pregnant women were divided into three groups: the normal glucose-tolerant group (NGT, n=35), the abnormal glucose-tolerant groups without insulin therapy (A1GDM, n=24) or with insulin therapy (A2GDM, n=11). Metabolic profiles of the plasma were acquired by proton nuclear magnetic resonance (1H-NMR) spectroscopy and analyzed by multivariate statistical data analysis. The relationship between demographic parameters and the potential metabolite biomarkers was further explored. Group antepartum or postpartum showed similar metabolic trends. Compare with those of the NGT group, the levels of 2-hydroxybutyrate, lysine, acetate, glutamine, succinate, tyrosine, formate, and all three BCAAs (leucine, valine, isoleucine) in the A2GDM group were increased dramatically, and the levels of lysine, acetate, and formate in the A1GDM group were elevated significantly. The dramatically decreased levels of 3-methyl-2-oxovalerate and methanol were observed both in the A1GDM group and A2GDM group. Compare to the A1GDM group, the branched-chain amino acids (BCAAs) of leucine, valine, and isoleucine were increased dramatically in the A2GDM group. The levels of aromatic amino acids (AAAs), tyrosine and phenylalanine, were significantly increased in GDM women, consistent with the severity of GDM. Interference of amino acid metabolism and disturbance in energy metabolism occurred in women with different grades of GDM. Metabolic profiles could reflect the severity of GDM. Plasma BCAA concentrations showing strong positive correlations with weight and pre-delivery BMI. This study provides a new perspective to understand the pathogenesis and etiology of GDM, which may help the clinical management and treatment of GDM.

Lipopolysaccharides (LPSs), as MAMP molecules, trigger the activation of signal transduction pathways involved in defence. Currently, plant metabolomics is providing new dimensions into understanding the intracellular adaptive responses to external stimuli. The effect of LPS on the metabolomes of Arabidopsis thaliana cells and leaf tissue was investigated over a 24 h period. Cellular metabolites and those secreted into the medium were extracted with methanol and liquid chromatography coupled to mass spectrometry was used for quantitative and qualitative analyses. Multivariate statistical data analyses were used to extract interpretable information from the generated multidimensional LC-MS data. The results show that LPS perception triggered differential changes in the metabolomes of cells and leaves, leading to variation in the biosynthesis of specialised secondary metabolites. Time-dependent changes in metabolite profiles were observed and biomarkers associated with the LPS-induced response were tentatively identified. These include the phytohormones salicylic acid and jasmonic acid, and also the associated methyl esters and sugar conjugates. The induced defensive state resulted in increases in indole—and other glucosinolates, indole derivatives, camalexin as well as cinnamic acid derivatives and other phenylpropanoids. These annotated metabolites indicate dynamic reprogramming of metabolic pathways that are functionally related towards creating an enhanced defensive capacity. The results reveal new insights into the mode of action of LPS as an activator of plant innate immunity, broadens knowledge about the defence metabolite pathways involved in Arabidopsis responses to LPS, and identifies specialised metabolites of functional importance that can be employed to enhance immunity against pathogen infection.

Uncomplicated healing of grafts for tendon reconstruction remains an unsolved problem in hand surgery. Results are limited by adhesion formation and decreased strength properties, especially within the tight fibro-osseous sheath of the digits. This is especially problematic when an extra synovial tendon graft is used to replace an intra synovial flexor tendon. Compositional differences are likely to play an important role in these processes. The aim of this study was, therefore, to compare protein expression in pair-matched intra synovial tendon grafts with extra synovial tendon grafts, using a rabbit tendon injury model. We hypothesized that there would be significant differences in proteins critical for response to tensile loading and adhesion formation between the two groups. Using mass spectrometry and multivariate statistical data analysis, we found tissue-specific differences in 22 proteins, where 7 explained 93% (R2) of the variation, with a prediction of 81% (Q2). Among the highest discriminating proteins were Galectin, Histone H2A, and Periostin, which were found in a substantially larger amount in the extra synovial tendons compared to the intra synovial tendons. These findings may contribute to improved understanding of the differences in outcome seen after tendon reconstruction using tendon grafts with intra synovial and extra synovial grafts.