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PubMedDate not supplied

Intact chemoreceptor-based biosensors.

A receptrode biosensor is presented that uses intact chemoreceptor-based molecular recognition from antennular structures of the Hawaiian swimming crab species Portunis sanguinolentus. The sensor is coupled to a learning, pattern recognition calculation for performing analytical chemistry. Action potential waveforms are used to establish the identity of individual action potential types that can be associated to particular analytes. The pattern recognition calculations used are referred to as cluster analysis (CA) and principal component analysis (PCA). Action potential similarities are determined by using a dendrogram plot of the cluster analysis results and further elucidated by using principal component scores plots. Quantitative analysis was performed after classification of analyte and background responses. Chemoresponses to salinity and trimethylamine N-oxide, two chemical constituents that are found in the crustacean living environment, were investigated and gave analytic responses over several orders of magnitude.

Action Potentials↗

PubMed2005

QSAR by LFER model of cytotoxicity data of anti-HIV 5-phenyl-1-phenylamino-1H-imidazole derivatives using principal component factor analysis and genetic function approximation.

Cytotoxicity data of anti-HIV 5-phenyl-1-phenylamino-1H-imidazole derivatives were subjected to quantitative structure-activity relationship (QSAR) study using linear free energy related (LFER) model of Hansch using electronic (Hammett sigma), hydrophobicity (pi) and steric (molar refractivity and STERIMOL L, B1, B2, B3 and B4) parameters of phenyl ring substituents of the compounds, along with appropriate indicator variables. Principal component factor analysis (FA) was used as the data-preprocessing step to identify the important predictor variables contributing to the response variable and to avoid collinearities among them. The generated multiple linear regression (MLR) equations were statistically validated using leave-one-out technique. Genetic function approximation (GFA) was also used on the same data set to develop QSAR equations, which produced the same best equation as obtained with FA-MLR. The final equation is of acceptable statistical quality (explained variance 80.2%) and predictive potential (leave-one-out predicted variance 74%). The analysis explores the structural and physicochemical contributions of the compounds for cytotoxicity. A thiol substituent at 2 position of the imidazole nucleus decreases cytotoxicity when compared to the corresponding unsubstituted congener. Presence of hydrogen bond donor group at meta position of the phenyl ring present at 5 position of the imidazole nucleus also reduces cytotoxicity. Additionally, absence of any substituent at 2 and 3 positions of the phenyl ring of 1-phenylamino fragment reduces the cytotoxicity. The negative coefficient of sigmap indicates that presence of electron-withdrawing substituents at the para position of the phenyl ring of the 1-phenylamino fragment is not favourable for the cytotoxicity. Again, lipophilicity of meta substituents of the 5-phenyl ring increases cytotoxicity. The coefficients of molar refractivity (MRm) and STERIMOL parameters for meta substituents (Lm, B1m and B4m) of the phenyl ring of 1-phenylamino fragment indicate that the length, width and overall size of meta substituents are conducive factors for the cytotoxicity.

Algorithms↗

PubMed2005

Foraminiferal responses to polluted sediments in the Montevideo coastal zone, Uruguay.

A study of foraminiferal assemblages was carried out in 24 sediment samples collected from the Montevideo coastal zone (south-eastern coastal region of South America) to assess the response of the benthic foraminifera to the polluted sediments. The area is affected by different pollutants such as sewage, hydrocarbons and heavy metals derived from different sources. Biological data were analyzed with multivariate techniques of cluster analysis and a principal component analysis (PCA) was performed for abiotic factors. The results allowed the recognition of different species assemblages corresponding to different sub-environments, which reflected the prevalent ecological conditions. The Montevideo Bay, particularly, its inner part showed an extremely poor foraminiferal fauna-including a totally azoic station-and high percentages of abnormal tests, when compared with the adjacent Punta Carretas and Punta Yeguas zones. Mean faunal density showed a strong relationship with organic matter, oxygen and heavy metal concentrations, as well as redox potential and pH values of each sub-environment. Although the adjacent zones presented a moderate pollution degree, it was noticed that a positive effect on the foraminiferal density specially on Ammonia tepida, caused by the sewage pipe located in Punta Carretas, a pure organic contamination. Differences among foraminiferal assemblages seemed to be related to the combined action of the several kinds of pollutants and the natural abiotic variables, like the rapid salinity changes that occurred in this area.

Animals↗

PubMed2005

Estimation of origins of polycyclic aromatic hydrocarbons in size-fractionated road dust in Tokyo with multivariate analysis.

This study aimed to estimate the origins of polycyclic aromatic hydrocarbons (PAHs) in size-fractionated road dust in Tokyo. First, seven categories of PAHs sources were defined: diesel vehicle exhaust, gasoline vehicle exhaust, tire, pavement, asphalt or bitumen, petroleum products excluding tire and asphalt, and combustion products except for those in vehicle engines. The 189 source data of 12-PAHs profiles were classified into 11 groups based on cluster analysis combined with principal component analysis. Next, 18 road dust samples were collected from eight streets in Tokyo and fractionated into four different particle-size-fractions: 0.1-45, 45-106, 106-250, and 250-2000 microm. In order to estimate the contributions of the classified source groups (S1-S11) to PAHs in the road dust, multiple regression analysis was performed with 12-PAH profile of the road dust as dependent variable and average 12-PAHs profiles of the 11 source groups as 11 explanatory variables. Diesel vehicle exhaust, tire and pavement were the major contributors of PAHs in the fractionated road dust. Although the estimated contributions of the 11 source groups varied among the particle-size-fractions, there was no clear and consistent relationship between particle size and the major PAH contributor.

Cluster Analysis↗

PubMed2005

Delusions in individuals with schizophrenia: factor structure, clinical correlates, and putative neurobiology.

BACKGROUND: Delusions are a central feature of schizophrenia, yet our understanding of their neurobiology is limited. Attempt to link dimensions of psychopathology to putative neurobiological mechanisms depends on careful delineation of symptoms. Previous factor analytic studies of delusions in schizophrenia were limited by several methodological problems, including the use of patients medicated with antipsychotics, inclusion of nondelusion symptoms in the analyses, and/or inclusion of patients with psychotic disorders other than schizophrenia. These problems may have possibly biased the resulting factor structure and contributed to the inconclusive findings regarding the neurobiology of positive symptoms. Our goal is to examine the factor structure of delusions in antipsychotic-free individuals with diagnoses of schizophrenia/schizoaffective disorder. SAMPLING AND METHODS: We assessed 83 antipsychotic-free individuals with DSM-IV diagnoses of schizophrenia/schizoaffective disorder. A principal component analysis was conducted on the delusions symptoms of the SAPS. RESULTS: The principal component analysis resulted in three distinct and interpretable factors explaining 58.3% of the variance. The Delusions of Influence factor was comprised by delusions of being controlled, thought withdrawal, thought broadcasting, thought insertion, and mind reading. The Self-Significance Delusions factor was comprised by delusions of grandeur, reference, religious, and delusions of guilt/sin. The Delusions of Persecution factor was comprised solely by persecutory delusions. The three factors displayed distinct associations with hallucinations, bizarre behavior, attention, positive formal thought disorder, and avolition/apathy. CONCLUSIONS: The results indicate that delusions are best described by three distinct subtypes. The authors propose a novel model linking the three delusion subtypes, attributions to self/other, and putative neurobiological mechanisms. Implications for future research are discussed, as well as links to cognitive-behavioral conceptualizations of delusions.

Adolescent↗

PubMed2006

Characterization of bacterial growth and the influence of antibiotics by means of UV resonance Raman spectroscopy.

In this work we monitor the bacterial growth of a Bacillus pumilus batch culture by means of UV resonance Raman spectroscopy. Excitation with a wavelength of 244 nm especially enhances the Raman scattering of the aromatic amino acids and the nucleic acid bases and therefore is a good method to track the metabolic changes that occur during bacterial growth. Furthermore, a drug from the fluoroquinolone group is added to the bacterial suspension at the beginning of the exponential growth phase. With the help of chemometrical methods such as hierarchical cluster analysis (HCA) and principal component analysis (PCA) it is possible to visualize the small changes that occur in the UV resonance Raman spectra due to the interaction of the drug with its biological targets DNA and the enzyme gyrase within the bacterial cell.

Anti-Bacterial Agents↗

PubMed2004

A genomic predictor of oral squamous cell carcinoma.

OBJECTIVES/HYPOTHESIS: The objective was to identify a genomic profile that predicts the likelihood of oral squamous cell carcinoma compared with normal oral mucosa in unknown tissue samples. STUDY DESIGN: Using a training set of tissue samples that were histologically classified as oral squamous cell carcinoma or normal mucosa, the authors used principal component analysis to develop a genomic predictor for oral squamous cell carcinoma. On a separate test set of unclassified samples, the authors used the predictor to classify the samples, then evaluated the performance of the predictor using histological diagnosis. METHODS: The authors used a data set consisting of messenger RNA extracted from 29 oral squamous cell carcinoma and 19 normal oral mucosa tissue samples and hybridized to Affymetrix oligonucleotide microarrays containing probe sets for 7070 genes and expressed sequence tags. The samples were divided into a training set of 15 oral squamous cell carcinoma and 10 normal samples and a test set consisting of the remaining samples. Using principal component analysis on the training set, the authors found a composite gene expression vector (principal component vector), which they used to compute likelihood ratios for oral squamous cell carcinoma on the test set. By calculating the contribution of each gene to the principal component vector, the authors identified genes with the greatest predictive value. RESULTS: Using the likelihood ratio, the authors correctly classified all 23 samples in the test set as either oral squamous cell carcinoma or normal. The authors found that many of the most predictive genes are known to be markers of squamous cell carcinoma or normal mucosa. CONCLUSION: Principal component analysis can be used with genomic microarray data to correctly predict the presence of oral squamous cell carcinoma in unknown tissue samples.

Biomarkers, Tumor↗

PubMed2006

Differentiation of faecal Escherichia coli from humans and animals by multiple antibiotic resistance analysis.

AIMS: Multiple antibiotic resistance (MAR) was performed on 128 Escherichia coli isolates, recovered from faecal samples of humans and animals (cattle, goat, sheep) to determine and compare their antibiotic resistance patterns and to evaluate them statistically in order to specify the source of the faecal material. METHODS AND RESULTS: Disk diffusion method was applied with a selection of antibiotics. Statistical approach was performed with hierarchical cluster analysis (CA), discriminant analysis (DA) and principal component analysis. Comparing human and animal isolates there was significant difference in levels of resistance to all antibiotics tested (P<0.05) with 46 and 24 distinct resistance patterns for human and animal isolates respectively. CA and DA separated human and animal isolates with a high average rate of correct classification (99.2%), when all animal isolates were pooled together. CONCLUSIONS: MAR analysis compared with appropriate statistical evaluation may provide a useful tool for differentiating the human or animal origin of E. coli isolates derived from environmental samples. Subsequently, determination of the source of faecal pollution becomes possible. SIGNIFICANCE AND IMPACT OF THE STUDY: Determining the source of faecal pollution enables the prediction of possible risk for public health and the application of appropriate management plans for prevention of further contamination.

Animals↗

PubMed2001

Effect of glutamate analogues on red-green opponent interaction in monkey electroretinograms.

The effect of glutamate analogues on red-green opponent interaction was electrophysiologically investigated in anesthetized cynomolgus monkeys (Macaca fascicularis). Two approaches were employed: amplitude measurement and principal component analysis. Electroretinograms were recorded for 23 monochromatic stimuli (400-700 nm) at an equal energy with white light adaptation before and after treatment with the glutamate analogues, 2-amino-4-phosphonobutyric acid, cis -2,3-piperidine-dicarboxylic acid, or both. Before treatment, although spectral amplitude curves of the a- and d-waves showed single, broad peaks at about 550 nm, the b-wave curve had three peaks at about 460, 540 and 600 nm, indicating the occurrence of the red-green opponent interaction. Principal component analysis performed on these waveforms extracted three components with short, middle, and long wavelength peaks, well defined characteristics of the red-green opponency. After vitreal injection of 2-amino-4-phosphonobutyric acid, the a- and d-wave amplitudes were enhanced while the b-wave amplitude was almost completely diminished. However, principal component analysis showed basically similar characteristics to those before drug, suggesting that the red-green opponency was not affected. In contrast, after application of cis -2,3-piperidine-dicarboxylic acid, the a- and d-waves were diminished and the b-wave was enhanced as expected, however the enhancement was observed only in the short and middle wavelengths. As a result of this partial enhancement, the b-wave spectral amplitude curve showed only a single peak, unlike in the control. In addition, principal component analysis revealed a quite different result from the control; only two components with short and middle wavelength peaks and the component with long wavelength peak disappeared. Similar two components were also separated after the conjunction of both drugs. These results demonstrate that red-green opponency is greatly inhibited by cis -2,3 piperidine-dicarboxylic acid, and thus suggest that horizontal cells are related to a generation of the red-green opponency through a cone type selective or nonselective negative feedback.

Animals↗

PubMed2003

Assessing the severity of migraine: development of the MIGSEV scale.

OBJECTIVES: To identify items that serve to assess the severity of migraine with a high level of clinical and psychometric relevance and to combine these into a unitary severity scale. BACKGROUND: Severity of migraine is an important determinant of patient quality of life and of health care resource utilization. Despite this, no validated method exists for measuring migraine severity. METHODS: After selection from the medical literature items of potential relevance to the severity of migraine, consensus meetings led to a choice of items which subsequently were refined further on the basis of patient interviews. The psychometric properties of those items then were assessed in a survey involving 287 migraineurs. The methods used to test reliability and validity included test-retest, calculation of Cronbach alpha coefficient, analysis of factorial structure using principal components analysis, a comparison of the agreement between doctors' and patients' assessments, and correlation with a validated quality-of-life questionnaire. The most pertinent items revealed by the factorial analysis were combined in a unitary scale. RESULTS: Seven items reflecting severity were identified by expert consensus. These were intensity of pain, tolerability, disability in daily activities, presence of nausea or vomiting, resistance to treatment, duration of attacks, and frequency of attacks. Principal components analysis identified 3 dimensions accounting for 65% of the overall variance related to intensity of attacks, resistance to treatment, and frequency of attacks. The internal consistency and the reproducibility of the items appeared quite satisfactory, and variations in these items were correlated with quality-of-life scores. The 4 items related to intensity of attacks were combined into a single scale with 3 response modalities. CONCLUSIONS: The 3 dimensions identified by this investigation appeared medically relevant and to have good psychometric properties. The items on the intensity dimension can be used to generate a simple scale for assessing migraine attack severity.

Adult↗

PubMed2002

Characterization of diet-dependent metabolic serotypes: primary validation of male and female serotypes in independent cohorts of rats.

Our research seeks to identify serum profiles, or serotypes, that reflect substantial changes in food intake in both male and female rats. This report validates previously defined subsets of redox-active low-molecular-weight metabolites using independent cohorts of ad libitum consumption (AL) and energy or dietary restricted (DR) 6-mo-old male and female rats. In the male study, both hierarchical cluster analysis (HCA) and principal component analysis (PCA) distinguished the dietary groups of origin in the second male cohort with >85% accuracy using 56 analytically and biologically valid metabolites. Further analysis revealed that 29 metabolites (nine previously unidentified metabolites + 20 chosen from the 56 metabolites) enabled HCA to distinguish dietary groups at 100% efficacy. In the female study, the 63 previously identified serum metabolites were sufficiently robust to enable classification of the dietary intake of two female cohorts (cohorts 2 and 3) that were independent of the cohort on which these markers were initially identified (cohort 1). Classification accuracy was 94 and 100% using HCA and PCA, respectively, in the female cohort 2. HCA and PCA revealed that the 63-metabolite profile distinguished AL and DR samples at 91 and 100% accuracy in the female cohort 3, establishing the 63-metabolite dataset as our baseline profile. These studies used independent cohorts to validate and potentially improve upon previously defined metabolic serotype in male and female rats and set the stage for pattern recognition-based approaches to establish metabolome-based categorical separations.

Animals↗

PubMed2005

Nasal biomarker profiles in acute and chronic rhinosinusitis.

BACKGROUND: Clinical manifestations of rhinosinusitis include acute rhinosinusitis, chronic rhinosinusitis (CRS) with nasal polyps and CRS without polyps. OBJECTIVE: Possible mechanisms defining these three forms of rhinosinusitis should be investigated assessing biomarker profiles in nasal secretions. METHODS: Fifteen cytokines, three cellular activation markers and total IgE were determined in nasal secretions of seven patients with acute rhinosinusitis, 12 patients with CRS without polyps, 13 patients with CRS with polyps and six healthy controls. Principal component analysis was used to extract relevant factors. RESULTS: Irrespective of the clinical manifestation, all biomarkers assessed were increased in patients with rhinosinusitis when compared with controls (P<0.001). Principal component analysis allowed the extraction of three factors explaining 83% of data variance. The general inflammatory activation was mainly reflected by the first factor. The second factor differentiated acute from CRS. This factor correlated with IL-12, which is involved in pathogen-related immune activation by antigen-presenting cells. It was also positively correlated with IL-4, IL-10 and IL-13, which play an important role in the resolution of infections. The third factor differentiated CRS with polyps from CRS without polyps (P=0.001). It represented IL-5 and nasal IgE (nIgE), whereas eosinophil cationic protein and tryptase were not specific for CRS with polyps. CONCLUSION: In mucosal infection, numerous inflammatory mediators are activated. Simple correlations of few biomarkers with a specific disease process bear the risk of overestimating a possibly unspecific effect. To assess biomarker profiles, more complex analytic tools may be more appropriate to delineate mechanisms underlying mucosal disease. Using principal component analysis, it was found that high nIgE and IL-5 levels are specific for CRS with nasal polyps.

Acute Disease↗

PubMed2005

Face recognition using laplacianfaces.

We propose an appearance-based face recognition method called the Laplacianface approach. By using Locality Preserving Projections (LPP), the face images are mapped into a face subspace for analysis. Different from Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) which effectively see only the Euclidean structure of face space, LPP finds an embedding that preserves local information, and obtains a face subspace that best detects the essential face manifold structure. The Laplacianfaces are the optimal linear approximations to the eigenfunctions of the Laplace Beltrami operator on the face manifold. In this way, the unwanted variations resulting from changes in lighting, facial expression, and pose may be eliminated or reduced. Theoretical analysis shows that PCA, LDA, and LPP can be obtained from different graph models. We compare the proposed Laplacianface approach with Eigenface and Fisherface methods on three different face data sets. Experimental results suggest that the proposed Laplacianface approach provides a better representation and achieves lower error rates in face recognition.

Algorithms↗

PubMed2006

Matrix metalloproteinase target family landscape: a chemometrical approach to ligand selectivity based on protein binding site analysis.

To gain insight into the structural determinants for the matrix metalloproteinase (MMP) family, we characterized the binding sites of 56 MMP structures and one TACE (tumor necrosis factor alpha converting enzyme) structure using molecular interaction fields (MIFs). These MIFs were produced by two approaches: the GRID force field and the knowledge-based potential DrugScore. The subsequent statistical analysis using consensus principal component analysis (CPCA) for the entire binding site and each subpockets revealed both approaches to encode similar information about discriminating regions. However, the relative importance of the probes varied between both approaches. The CPCA models provided the following ranking of the six subpockets based on the opportunity for selective interactions with different MMPs: S1' > S2, S3, S3' > S1, S2'. The interpretation of these models agreed with experimental binding modes inferred from crystal structures or docking.

ADAM Proteins↗

PubMed2005

Morphological variation of the thoracolumbar vertebrae in Macropodidae and its functional relevance.

The present study was designed to investigate how the form of the marsupial thoracolumbar vertebrae varies to cope with the particular demands of diverse loading and locomotor behaviors. The vertebral columns of 10 species of Macropodidae, with various body masses and modes of locomotion, together with two other arboreal marsupials, koala and cuscus, were selected. Seventy-four three-dimensional landmark coordinates were acquired on each of the 10 last presacral vertebrae of the 70 vertebral columns. The interspecific variations of the third lumbar vertebra (L3, which approximates the mean) and the transitional patterns of the thoracolumbar segments were examined using the combined approach of generalized Procrustes analysis (GPA) and principal components analysis (PCA). The results of analyses of an individual vertebra (L3) and of the transitional patterns indicate significant interspecific differences. In the L3 study the first PC shows allometric shape variation, while the second PC seems to relate to adaptation for terrestrial versus arboreal locomotion. When the L3 vertebrae of the common spotted cuscus and koala are included for comparison, the vertebra of the tree kangaroo occupies an intermediate position between the hopping kangaroo and these arboreal marsupials. The L3 vertebrae in the arboreal marsupials possess a distinct dorsoventrally expanded vertebral body, and perpendicularly orientated spinous and transverse processes. The results of the present study suggest that vertebral shape in the kangaroo and wallaroos provides a structural adaptation to hopping through a relatively enlarged loading area and powerful lever system. In contrast, the small-sized bettongs (or rat kangaroos) have a relatively flexible column and elongated levers for the action of back muscles that extend and laterally flex the spine. The complex pattern of vertebral shape transition in the last 10 presacral vertebrae was examined using PCAs that compare between species information about vertebral shape variation along the thoracolumbar column. The results reinforce and emphasize important aspects of the patterns of variation seen in the detailed analysis of the third lumbar vertebra. The results also imply that size, spinal loading pattern, and locomotor behavior exert an influence on shaping the vertebra. Further, the morphological adaptations are consistent within these marsupials and this opens up the possibility that this kind of analysis may be useful in making functional inferences from fossil material.

Animals↗

PubMed2004

Identification of the regulatory proteins in human pancreatic cancers treated with Trichostatin A by 2D-PAGE maps and multivariate statistical analysis.

In this paper, principal component analysis (PCA) is applied to a spot quantity dataset comprising 435 spots detected in 18 samples belonging to two different cell lines (Paca44 and T3M4) of control (untreated) and drug-treated pancreatic ductal carcinoma cells. The aim of the study was the identification of the differences occurring between the proteomic patterns of the two investigated cell lines and the evaluation of the effect of the drug Trichostatin A on the protein content of the cells. PCA turned out to be a successful tool for the identification of the classes of samples present in the dataset. Moreover, the loadings analysis allowed the identification of the differentially expressed spots, which characterise each group of samples. The treatment of both the cell lines with Trichostatin A therefore showed an appreciable effect on the proteomic pattern of the treated samples. Identification of some of the most relevant spots was also performed by mass spectrometry.

Analysis of Variance↗

PubMed2006

Distinguishing monosaccharide stereo- and structural isomers with TOF-SIMS and multivariate statistical analysis.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is utilized to examine the mass spectra and fragmentation patterns of seven isomeric monosaccharides. Multivariate statistical analysis techniques, including principal component analysis (PCA), allow discrimination of the extremely similar mass spectra of stereoisomers. Furthermore, PCA identifies those fragment peaks that vary significantly between spectra. Heavy isotope studies confirm that these peaks are indeed sugar fragments, allow identification of the fragments, and provide clues to the fragmentation pathways. Excellent reproducibility is shown by multiple experiments performed over time and on separate samples. This study demonstrates the combined selectivity and discrimination power of TOF-SIMS and PCA and suggests new applications of the technique including differentiation of subtle chemical changes in biological samples that may provide insights into cellular processes, disease progress, and disease diagnosis.

Mass Spectrometry↗

PubMed1988

[Morphometrical study of physical growth in infant cynomolgus monkeys using multivariate analysis].

We describe the relative growth in infant cynomolgus monkeys (Macaca fascicularis). The multivariate analyses using the principal component analysis and multivariate allometric analysis were applied to biometrical data of laboratory-bred cynomolgus monkeys aged from birth to 12 weeks. All the animals had been bred and reared under uniform environmental conditions at Tsukuba Primate Center for Medical Science, N. I. H., Japan. As the result of the principal component analysis, the cumulative contribution ratio of the 1st and 2nd principal components (PC1 and PC2) accounted for 88.2% and 85.7% in males and females, respectively. This indicates that the morphologic traits (15 traits) grow normally in size, but the analysis did not detect any differences in growth rate among the traits. So, the multivariate allometric analysis was applied to the same data. The traits concerning the face and truck showed relatively high growth rates compared to head breadth, whereas the limbs and arms grew slowly.

Analysis of Variance↗