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At least 865 records · Page 48Linked to original sources
PubMed2005

Fibroblast-like synoviocytes derived from patients with rheumatoid arthritis show the imprint of synovial tissue heterogeneity: evidence of a link between an increased myofibroblast-like phenotype and high-inflammation synovitis.

OBJECTIVE: Given the heterogeneity of gene expression patterns and cellular distribution between rheumatoid arthritis (RA) synovial tissues, we sought to determine whether this variability was also reflected at the level of the fibroblast-like synoviocyte (FLS) cultured from RA synovial tissues. METHODS: Gene expression profiles in FLS cultured from synovial tissues obtained from 19 RA patients were analyzed using complementary DNA microarrays and hierarchical cluster analysis. To validate the subclassification, we performed prediction analysis and principal components analysis. Genes that differed significantly in their expression between FLS cultures were selected using Statistical Analysis of Microarrays software. Real-time quantitative polymerase chain reaction was performed to validate the microarray data. Immunocytochemistry was applied to study the expression of the genes of interest in FLS and synovial tissues. RESULTS: Hierarchical clustering identified 2 main groups of FLS characterized by distinctive gene expression profiles. FLS from high-inflammation synovial tissues revealed increased expression of a transforming growth factor beta/activin A-inducible gene profile that is characteristic of myofibroblasts, a cell type considered to be involved in wound healing, whereas increased production of growth factor (insulin-like growth factor 2/insulin-like growth factor binding protein 5) appeared to constitute a characteristic feature of FLS derived from low-inflammation synovial tissues. The molecular feature that defines the myofibroblast-like phenotype was reflected as an increased proportion of myofibroblast-like cells in the heterogeneous FLS population. Myofibroblast-like cells were also found upon immunohistochemical analysis of synovial tissue. CONCLUSION: Our findings support the notion that heterogeneity between synovial tissues is reflected in FLS as a stable trait, and provide evidence of a possible link between the behavior of FLS and the inflammation status of RA synovium.

Arthritis, Rheumatoid↗
PubMed2007

Towards a detailed understanding of bacterial metabolism--spectroscopic characterization of Staphylococcus epidermidis.

Bacteria are a major cause of infection. To fight disease and growing resistance, research interest is focused on understanding bacterial metabolism. For a detailed evaluation of the involved mechanisms, a precise knowledge of the molecular composition of the bacteria is required. In this article, various vibrational spectroscopic techniques are applied to comprehensively characterize, on a molecular level, bacteria of the strain Staphylococcus epidermidis, an opportunistic pathogen which has evolved to become a major cause of nosocomial infections. IR absorption spectroscopy reflects the overall chemical composition of the cells, with major focus on the protein vibrations. Smaller sample volumes-down to a single cell-are sufficient to probe the overall chemical composition by means of micro-Raman spectroscopy. The nucleic-acid and aromatic amino-acid moieties are almost exclusively explored by UV resonance Raman spectroscopy. In combination with statistical evaluation methods [hierarchical cluster analysis (HCA), principal component analysis (PCA), linear discriminant analysis (LDA)], the protein and nucleic-acid components that change during the different bacterial growth phases can be identified from the in vivo vibrational spectra. Furthermore, tip-enhanced Raman spectroscopy (TERS) provides insight into the surface structures and follows the dynamics of the polysaccharide and peptide components on the bacterial cells with a spatial resolution below the diffraction limit. This might open new ways for the elucidation of host-bacteria and drug-bacteria interactions.

Bacterial Proteins↗
PubMedDate not supplied

Global analysis of lymphocyte gene expression: perturbation of H-9 cells by infection with distinct isolates of human immunodeficiency virus--an exposition by multivariate analysis of a host-parasite interface.

AIDS is a progressive disease associated with steady loss of helper T cells and several other functions. As the disease evolves, cytopathogenic human immunodeficiency (HIV) variants of increasing virulence can be isolated from the host. The HIV is an unusually variable genome by virtue of a low replication fidelity. In this report we describe our effort to test the hypothesis that there is a correlation between virus variability and cytopathogenicity, and further, that there is an "impact" of the virus infection on the expression of host cellular genes. To search for such a relationship, we infected H-9 cells (human CD4+ lymphoblastoid cell line) with each of 5 isolates of HIV of distinct origin and cytopathogenicity. To measure the influence of the virus infection on the expression of host cellular genes, shortly after infection, (3 h or 13 h), cells were radiolabeled and the radioactive polypeptides separated by two-dimensional gel electrophoresis. Radiofluorographs were prepared and analyzed to determine relative rates of biosynthesis of cellular polypeptides. To organize the large amounts of data found, cluster analysis and principal component analysis were used to expose the data in formats that allowed a model construction. The rates of biosynthesis of many cellular polypeptides were altered upon viral infection in terms of both enhancements and impairment of biosynthesis. Some of the variation in polypeptide synthesis was isolate-specific, while most alterations were of modest magnitude. There appears to be no "overall effect" associated with infection by a cytopathic variant of the virus. Polypeptides affected by the cytopathic variants were determined as targets for further investigation. The method used promotes the measurement of "ensemble" information that is characteristic of the process and it promotes the creation of models of virus action.

Acquired Immunodeficiency Syndrome↗
PubMed2004

Agitated behaviours among the institutionalized elderly with dementia: validation of the Korean version of the Cohen-Mansfield Agitation Inventory.

OBJECTIVES: To analyze the factor structure, the criterion validity, the internal consistency, inter-rater reliability and test-retest reliability of the Korean version of Cohen-Mansfield Agitation Inventory, to provide data on the frequency and distribution of agitated behaviours, and to compare patterns of agitated behaviours among the institutionalized elderly with Alzheimer's disease (AD) or Vascular dementia (VaD). METHODS: The Korean version of the Cohen-Mansfield Agitation Inventory (CMAI-K) was administered to a total of 257 elderly with AD or VaD in a nursing home in Seoul, Korea. Three kinds of reliability and criterion validity were tested. Factor analysis using principal component analysis with the varimax rotation was performed. To identify different patterns of agitated behaviours, multiple logistic regression analysis was used. RESULTS: This study demonstrated satisfactory reliability and validity for the CMAI-K as an instrument measuring agitation in Korean dementia sufferers in nursing homes. Eighty-three percent of the subjects manifested one or more agitated behaviours at least once a week. Factor analysis yielded four subtypes of agitation: physically aggressive behaviours, physically nonaggressive behaviours, verbally agitated behaviours, and hiding/hoarding behaviours. CONCLUSION: These results indicate that the CMAI-K is a reliable and valid instrument to measure agitated behaviours in Korean elderly with AD or VaD. These results validate and expand previous research on the agitation in dementia, and guide in the development of interventions.

Aged↗
PubMed2003

Characteristics of hydroxypropyl methylcellulose influencing compactibility and prediction of particle and tablet properties by infrared spectroscopy.

Particle characteristics, chemical substitution, compaction behavior, and tablet properties of hydroxypropyl methylcellulose powders from two different suppliers were related using multivariate data analysis. By Principal Component Analysis it was shown that the the degree of substitution of the HPMC powders did not correlate to the particle and compaction properties as strongly as anticipated. Particle shape and powder surface area seem to be more important for the compaction behaviour of the powders than the degree of substitution. In addition, particle and tablet properties were predicted from infrared spectral data. Fourier transform infrared (FTIR) and near infrared (NIR) spectral data of the powders were combined with measured values of the particle characteristics, compaction behavior, and tablet properties using the multivariate data analysis program SIMCA 7.1. Properties like density, particle shape, tablet tensile strength, and drug release characteristics of the HPMC powders and corresponding tablets in this study could be predicted using Partial Least Squares models. In conclusion, the particle shape and powder surface area of HPMC powders seem to be important factors for the quality of tablet attained. Further, this study confirms that NIR and FTIR analysis used in combination with multivariate analysis are powerful tools for predicting the properties of materials and the quality of the end product.

Compressive Strength↗
PubMed2005

Hunting the primary: novel strategies for defining the origin of tumours.

In 1995, two methods of genome-wide expression profiling were first described: expression microarrays and serial analysis of gene expression (SAGE). In the subsequent 10 years, many hundreds of papers have been published describing the application of these technologies to a wide spectrum of biological and clinical questions. Common to all of this research is a basic process of data gathering and analysis. The techniques and statistical and bio-informatic tools involved in this process are reviewed. The processes of class discovery (using clustering and self-organizing maps), class prediction (weighted voting, k nearest neighbour, support vector machines, and artificial neural networks), target identification (fold change, discriminant analysis, and principal component analysis), and target validation (RT-PCR and tissue microarrays) are described. Finally, the diagnostic problem of adenocarcinomas that present as metastases of unknown origin is reviewed, and it is demonstrated how integration of expression profiling techniques promises to throw new light on this important clinical challenge.

Adenocarcinoma↗
PubMed2004

Proteomic signature of human cancer cells.

We assessed proteomic profiles as biomarkers for monitoring cell phenotypes. Protein expression profiles were obtained by fluorescence two-dimensional difference gel electrophoresis (2-D-DIGE), in which quantitative ability is improved by labeling proteins with fluorescent dyes prior to electrophoresis. Integrated protein spot intensities were analyzed by a statistical approach. The proteomic data of two groups of cell lines: (1) adenocarcinoma (AC) cell lines derived from lung, pancreas and colon tissues and (2) lung cancer cell lines with different histological backgrounds, including AC, squamous cell carcinoma and small cell carcinoma, were assessed on the basis of prior biological information. Hierarchical clustering analysis and principal component analysis were used to divide the cell lines into subgroups on the basis of similarities between their protein expression profiles. The majority of cell lines were grouped according to their organ of origin or histological background. A machine-learning algorithm selected 32 protein spots that were responsible for the classification. The results indicate that proteomic data generated by 2-D-DIGE can provide a signature of essential cell phenotypes, suggesting that it might be possible to apply this technique to developing tumor markers that could identify the organ of origin of metastatic tumors and contribute to the differential diagnosis of lung cancer.

Cell Line, Tumor↗
PubMed2005

Proteomic signatures for histological types of lung cancer.

We performed proteomic studies on lung cancer cells to elucidate the mechanisms that determine histological phenotype. Thirty lung cancer cell lines with three different histological backgrounds (squamous cell carcinoma, small cell lung carcinoma and adenocarcinoma) were subjected to two-dimensional difference gel electrophoresis (2-D DIGE) and grouped by multivariate analyses on the basis of their protein expression profiles. 2-D DIGE achieves more accurate quantification of protein expression by using highly sensitive fluorescence dyes to label the cysteine residues of proteins prior to two-dimensional polyacrylamide gel electrophoresis. We found that hierarchical clustering analysis and principal component analysis divided the cell lines according to their original histology. Spot ranking analysis using a support vector machine algorithm and unsupervised classification methods identified 32 protein spots essential for the classification. The proteins corresponding to the spots were identified by mass spectrometry. Next, lung cancer cells isolated from tumor tissue by laser microdissection were classified on the basis of the expression pattern of these 32 protein spots. Based on the expression profile of the 32 spots, the isolated cancer cells were categorized into three histological groups: the squamous cell carcinoma group, the adenocarcinoma group, and a group of carcinomas with other histological types. In conclusion, our results demonstrate the utility of quantitative proteomic analysis for molecular diagnosis and classification of lung cancer cells.

Adenocarcinoma↗
PubMed1999

Influences of copper forms on the toxicity to microorganisms in soils.

Soil samples with wide ranges of pH (4.9 to 8.1), organic carbon (0.1 to 77%), and total Cu contents from 32 to 11700 mg kg(-1), collected near a copper mine, were used to investigate the relationships between microbial features and Cu speciation in order to clarify the form(s) of Cu adversely affecting microorganisms. The effects of Cu on soil microorganisms were evaluated by two indicators: the ratio of microbial biomass carbon to soil organic carbon (Cmic/Org-C) and Cu tolerance level of bacterial community (IC50). The sequential extraction scheme of McLaren and Crawford (1973) was used to quantify the different Cu forms (soluble and exchangeable, specifically adsorbed, and organically bound). These influences were investigated using simple correlation analysis, multiple regression analysis, and principal component analysis. The IC50 was positively correlated with the log concentration of soluble and exchangeable Cu (Ex-Cu) (r = 0.757, P<0.01). The IC50 value was also influenced by the amount of specifically adsorbed Cu. The Cmic/Org-C ratio was not significantly correlated with any Cu forms. Thus, other soil properties had more influence on the size of microbial biomass carbon in the soils used. The amount of Ex-Cu exerting high toxicity was affected by pH and the amount of total Cu.

Carbon↗
PubMed1993

Coplanar polychlorinated biphenyl congener levels and patterns and the identification of separate populations of harbor seals (Phoca vitulina) in Denmark.

Blubber samples from 21 harbor seals (Phoca vitulina), found dead on Danish beaches during the morbilli virus epidemic in 1988, have been analyzed for toxic coplanar chlorinated biphenyl (CB) congeners. The 21 samples consist of seven samples from 1-2-year-old animals (both males and females) from each of three geographical separate locations: The Limfjord, the Kattegat, and the Wadden Sea. The level of the CBs, defined as the sum of all the measured CB congeners, were highest in the samples from the Wadden Sea and lowest in the Limfjord samples. The quotient between highest level and lowest level was 4. Toxic equivalency factors given by Safe (1990) was used for calculation of the contribution to dioxin-like toxicity from the coplanar CB congeners, and the result was compared to literature data on polychlorinated dibenzo-p-dioxins and -dibenzofurans in harbor seal. CB congeners CB-118, CB-156, CB-157, and CB-105 were major contributors to sigma TEQ in all samples. The patterns of polychlorinated biphenyl congeners in harbor seals from the three locations were compared by principal component analysis. The two first principal components could separate the samples in groups corresponding to each of the three geographical locations. The geographical and biological variations were estimated from the data. It was shown, that the geographical variation was the largest. Possible reasons behind the geographical variation in CB congener patterns are discussed.

Adipose Tissue↗
PubMed1992

Frequency domain models of the EEG.

The structure of the normal resting EEG crosspectrum SVV(omega) is analyzed using complex multivariate statistics. Exploratory data analysis with Principal Component Analysis (PCA) is followed by hypothesis testing and computer simulations related to possible neural generators. The SVV(omega) of 211 normal individuals (ages 5 to 97) may be decomposed into two types of processes: the xi process with spatial isotropicity reflecting diffuse, correlated cortical generators with radial symmetry, and processes that seem to be generated by more spatially concentrated, correlated sources. The latter are reflected as spectral peaks such as the process. The eigenvectors of the xi process are the Spherical Harmonic Functions which explains the recurring pattern of maps characteristic of the spatial PCA of qEEG data. A new method for estimating sources in the frequency domain which fits dipoles to the whole crosspectrum is applied to explain the characteristics of the localized sources.

Age Factors↗
PubMed1992

Growth of the cranial bones in human fetuses (2nd and 3rd trimesters).

The increase of the weight of some cranial bones was studied in 30 human fetuses (from 17 to 41 weeks of gestation, both sexes together) by multivariate allometry. The study was performed with a covariance matrix of the log-transformed bony weights and the Principal Components Analysis (PCA). The first principal component in PCA accounted for 92.12% of the total variance, and all characters were positively correlated with this component. PCA scaled the growth of the bones in the following sequence: a) with negative allometry: vomer, palatine, mandible and maxillae; b) with isometry (p less than 0.05): zygomatic bone; c) with positive allometry: sphenoid, ethmoid, frontal, occipital, temporal and parietal. During the 2nd and 3rd trimesters of gestation the skull exhibited two different growth rates, i.e., the bony group of the facial skeleton presented lower eigenvalues than the bony group of the calvaria, including the base of the skull. These bones of the calvaria certainly are affected by the high increase in volume of the fetal brain during the prenatal life. The knowledge of the cranial growth is a useful information for the anatomy, anthropology, orthodontics, and several medical specialties: radiology, obstetrics, pediatrics, orthopedics and reconstructive surgery.

Cephalometry↗
PubMed2002

Analysis of river pollution data from low-flow period by means of multivariate techniques: a case study from the oil-shale industry region, northeastern Estonia.

The oil-shale industry has created serious pollution problems in northeastern Estonia. Untreated, phenol-rich leachate from semi-coke mounds formed as a by-product of oil-shale processing is discharged into the Baltic Sea via channels and rivers. An exploratory analysis of water chemical and microbiological data sets from the low-flow period was carried out using different multivariate analysis techniques. Principal component analysis allowed us to distinguish different locations in the river system. The riverine microbial community response to water chemical parameters was assessed by co-inertia analysis. Water pH, COD and total nitrogen were negatively related to the number of biodegradative bacteria, while oxygen concentration promoted the abundance of these bacteria. The results demonstrate the utility of multivariate statistical techniques as tools for estimating the magnitude and extent of pollution based on river water chemical and microbiological parameters. An evaluation of river chemical and microbiological data suggests that the ambient natural attenuation mechanisms only partly eliminate pollutants from river water, and that a sufficient reduction of more recalcitrant compounds could be achieved through the reduction of wastewater discharge from the oil-shale chemical industry into the rivers.

Biodegradation, Environmental↗
PubMed2000

Cardiovascular risk factors clustering with endogenous hyperinsulinaemia predict death from coronary heart disease in patients with Type II diabetes.

AIMS/HYPOTHESIS: Information on the association of hyperinsulinaemia with coronary heart disease (CHD) in patients with Type II (non-insulin-dependent) diabetes is limited and controversial. Therefore, we carried out a prospective study to examine the predictive value of fasting plasma insulin and "hyperinsulinaemia cluster" with regard to the risk of CHD mortality. METHODS: At baseline risk factors for CHD were determined in 902 patients aged 45 to 64 years with Type II diabetes not treated by insulin (499 men and 403 women). These patients were followed up to 7 years for CHD mortality. RESULTS: Coronary heart disease mortality (16.2% in men, 9.2% in women) increased significantly in men with increasing plasma insulin tertiles (p = 0.006) and in both sexes combined (p = 0.010) but not in women (p = 0.090). The predictive value of hyperinsulinaemia with regard to death from CHD was independent of conventional cardiovascular risk factors but not of risk factors clustering with hyperinsulinaemia. By applying factor analysis and principal component analysis we showed that "hyperinsulinaemia cluster" (a factor having high positive loadings for body mass index, triglycerides and insulin; and a high negative loading for high-density lipoprotein cholesterol) was predictive of death from CHD in patients with Type II diabetes (hazard ratio with 95% confidence intervals 1.43 (1.18, 1.73), p < 0.001). CONCLUSION/INTERPRETATION: Our results support the notion that cardiovascular risk factors clustering with endogenous hyperinsulinaemia increase the risk of death from CHD in patients with Type II diabetes not treated with insulin.

Age Factors↗
PubMed2004

Chemometric characterisation of Basque and French ciders according to their polyphenolic profiles.

Polyphenolic compositions of Basque and French ciders were determined by HPLC-DAD following thiolysis, in order to characterise and differentiate these beverages and then develop a classification system capable of confirming the authenticities of both kinds of cider. A data set consisting of 165 cider samples and 27 measured features was evaluated using multivariate chemometric techniques, such as cluster analysis and principal component analysis, in order to perform a preliminary study of data structure. Supervised pattern recognition techniques such as linear discriminant analysis (LDA), K-nearest neighbours (KNN), soft independent modelling of class analogy (SIMCA), and multilayer feed-forward artificial neural networks (MLF-ANN) attained classification rules for the two categories using the chemical data, which produced satisfactory results. Authentication systems obtained by combining two of these techniques were proposed. We found that SIMCA and LDA or KNN models achieved 100% hit-rates, since LDA and KNN permit the detection of every Basque cider and SIMCA provides a model for Basque cider that excludes all French ciders. Polyphenolic profiles of the ciders provided enough information to be able to develop classification rules for identifying ciders according to their geographical origin (Basque or French regions). Chemical and organoleptic differences between these two types of cider are probably due to the original and distinctive cidermaking technologies used for their elaboration. Using polyphenic profiles, about 80% of French ciders could be distinguished according to their region of origin (Brittany or Normandy). Although their polyphenolic profiles did not provide enough information to achieve an authentication system for Breton and Norman ciders.

Journal Article↗
PubMed2006

Chemometrical investigation of the presence and distribution of organochlorine and polyaromatic compounds in sediments of the Ebro River Basin.

A multivariate statistical data analysis, using principal component analysis, of historical data from 1996 to 2003 concerning the concentration of different polycyclic aromatic hydrocarbons and organochlorine compounds in sediment samples from different sampling sites of the Ebro River Basin was performed under the UE funded project AQUATERRA. Three major contamination sources were identified and their composition and distribution profiles were resolved. The first contamination profile was mostly loaded by polycyclic aromatic hydrocarbons, the second contamination profile was loaded by some organochlorine compounds and the third contamination profile was more specifically loaded by naphthalene. Samples from the different geographical regions of the Ebro River Basin were grouped according to the contamination described by these three major profiles.

Europe↗
PubMed1999

Comparison of Parental and Transgenic Alfalfa Rhizosphere Bacterial Communities Using Biolog GN Metabolic Fingerprinting and Enterobacterial Repetitive Intergenic Consensus Sequence-PCR (ERIC-PCR).

> Abstract Rhizosphere bacterial communities of parental and two transgenic alfalfa (Medicago sativa L.) of isogenic background were compared based on metabolic fingerprinting using Biolog GN microplates and DNA fingerprinting of bacterial communities present in Biolog GN substrate wells by enterobacterial repetitive intergenic consensus sequence-PCR (ERIC-PCR). The two transgenic alfalfa expressed either bacterial (Bacillus licheniformis) genes for alpha-amylase or fungal (Phanerochaete chrysosporium) genes for Mn-dependent lignin peroxidase (Austin S, Bingham ET, Matthews DE, Shahan MN, Will J, Burgess RR, Euphytica 85:381-393). Cluster analysis and principal components analysis (PCA) of the Biolog GN metabolic fingerprints indicated consistent differences in substrate utilization between the parental and lignin peroxidase transgenic alfalfa rhizosphere bacterial communities. Cluster analysis of ERIC-PCR fingerprints of the bacterial communities in Biolog GN substrate wells revealed consistent differences in the types of bacteria (substrate-specific populations) enriched from the rhizospheres of each alfalfa genotype. Comparison of ERIC-PCR fingerprints of bacterial strains obtained from substrate wells to substrate community ERIC-PCR fingerprints suggested that a limited number of populations were responsible for substrate oxidation in these wells. Results of this study suggest that transgenic plant genotype may affect rhizosphere microorganisms and that the methodology used in this study may prove a useful approach for the comparison of bacterial communities.

Journal Article↗