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At least 685 records · Page 38Linked to original sources
PubMed2001

Regional cerebral blood flow as assessed by principal component analysis and (99m)Tc-HMPAO SPET in healthy subjects at rest: normal distribution and effect of age and gender.

The increasing implementation of standardisation techniques in brain research and clinical diagnosis has highlighted the importance of reliable baseline data from normal control subjects for inter-subject analysis. In this context, knowledge of the regional cerebral blood flow (rCBF) distribution in normal ageing is a factor of the utmost importance. In the present study, rCBF was investigated in 50 healthy volunteers (25 men, 25 women), aged 31-78 years, who were examined at rest by means of single-photon emission tomography (SPET) using technetium-99m d, l-hexamethylpropylene amine oxime (HMPAO). After normalising the CBF data, 27 left and 27 right volumes of interest (VOIs) were selected and automatically outlined by standardisation software (computerised brain atlas). The heavy load of flow data thus obtained was reduced in number and grouped in factors by means of principal component analysis (PCA). PCA extracted 12 components explaining 81% of the variance and including the vast majority of cortical and subcortical regions. Analysis of variance and regression analyses were performed for rCBF, age and gender before PCA was applied and subsequently for each single extracted factor. There was a significantly higher CBF on the right side than on the left side ( P<0.001). In the overall analysis, a significant decrease was found in CBF ( P=0.05) with increasing age, and this decrease was particularly evident in the left hemisphere ( P=0.006). When gender was specifically analysed, CBF was found to decrease significantly with increasing age in females ( P=0.037) but not in males. Furthermore, a significant decrease in rCBF with increasing age was found in the brain vertex ( P=0.05), left frontotemporal cortex ( P=0.012) and temporocingulate cortex ( P=0.003). By contrast, relative rCBF in central structures increased with age ( P=0.001). The ability of standardisation software and PCA to identify functionally connected brain regions might contribute to a better understanding of the relationships between rCBF at rest, anatomically defined brain structures, ageing and gender.

Adult↗
PubMed2001

Application of ICP sector field MS and principal component analysis for studying interdependences among 23 trace elements in Polish beers.

Twenty-three metallic elements, including almost all essential and toxic metals such as lead, cadmium, mercury, arsenic, silver, and thallium, have been quantified in 35 types of bottled and canned Polish beer by using double-focusing sector field inductively coupled plasma mass spectrometry (ICP-MS) with ultrasonic nebulization. The samples were digested using concentrated HNO3 in closed PTFE vessels and applying microwave energy under pressure. The means and medians of the concentrations of Rb, Mn, and Fe were on the order of 200 ng/mL; Cu, Zn, V, Cr, Sn, As, Pb, and Ni were detected at 1-5 ng/mL; Ag, Ga, Cd, Co, Cs, Hg, U, and Sb were found at < 1 ng/mL; and In, Tl, Bi, and Th were present at < 0.1 ng/mL. The concentrations of Hg, Cd, As, Pb, and Zn were 1-3 orders of magnitude lower than proposed tolerance limits. The interdependences among determined trace elements were examined using the principal component analysis (PCA) method. The PCA model explained 74% of the total variance. The metals tend to cluster together (As, Tl, Cs, Sn, Th, Bi, and Hg; Cd and Co; Cs and Cr; Fe and Zn; Mn and V).

Beer↗
PubMed2001

Evaluation of peptide electropherograms by multivariate mathematical-statistical methods. I. Principal component analysis.

Depository effects in slowly metabolised proteins, typically glycation or the estimation of products arising from the reaction of unsaturated long-chain-fatty acid metabolites (possessing aldehydic groups) are very difficult to assess owing to their extremely low concentration in the protein matrix. In order to reveal such alterations we applied deep enzymatic fragmentation resulting in a set of small peptides, which, if modified, are likely to change their electrophoretic properties and can be visualised on the resulting profile. Peptide maps of collagen (a mixture of collagen types I and III digested by bacterial collagenase) were applied as the model protein structure for detecting the nonenzymatic posttranslational changes originating during various physiological conditions like high fructose diet and hypertriglyceridemic state. Capillary electrophoresis in acidic media (sodium phosphate buffer, pH 2.5) was used as the separation method capable of (partial) separation of over 60 peptide peaks. Two to 13 changes were revealed in the profiles obtained reflecting the physiological conditions of the animals tested. Combination of peptide profiling with subsequent t-test evaluation of individual peak areas and principal component analysis based on cumulative peak areas of individual sections of the electropherograms allowed to determine in which section (part) of the electropherogram the physiological state indicating changes occurred. Simultaneously it was possible to reveal the qualitative differences between the four physiological regimes investigated (i.e., which regime affects the collagen molecules most and which affects them least). The approach can be used as guidance for targeted preseparation of the very complex peptide mixture.

Animals↗
PubMed1998

Nuclear magnetic resonance spectroscopic and principal components analysis investigations into biochemical effects of three model hepatotoxins.

1H NMR spectroscopy of urine combined with pattern recognition (PR) methods of data analysis has been used to investigate the time-related biochemical changes induced in Sprague-Dawley rats by three model hepatotoxins: alpha-naphthyl isothiocyanate (ANIT), d-(+)-galactosamine (GalN), and butylated hydroxytoluene (BHT). The development of hepatic lesions was monitored by conventional plasma analysis and liver histopathology. Urine was collected continuously postdosing up to 144 h and analyzed by 600-MHz 1H NMR spectroscopy. NMR spectra of the urine samples showed a number of time-dependent perturbations of endogenous metabolite levels that were characteristic for each hepatotoxin. Biochemical changes common to all three hepatotoxins included a reduction in the urinary excretion of citrate and 2-oxoglutarate and an increased excretion of taurine and creatine. Increased urinary excretion of betaine, urocanic acid, tyrosine, threonine, and glutamate was characteristic of GalN toxicity. Both GalN and ANIT caused increased urinary excretion of bile acids, while glycosuria was evident in BHT- and ANIT-treated rats. Data reduction of the NMR spectra into 256 integrated regions was used to further analyze the data. Mean values of each integrated region were analyzed by principal components analysis (PCA). Each toxin gave a unique time-related metabolic trajectory that could be visualized in two-dimensional PCA maps and in which the maximum distance from the control point corresponded to the time of greatest cellular injury (confirmed by conventional toxicological tests). Thereafter, the metabolic trajectories changed direction and moved back toward the control region of the PR map during the postdose recovery phase. The combination of urinary metabolites which were significantly altered at various time points allowed for differentiation between biliary and parenchymal injury. This NMR-PR approach to the noninvasive detection of liver lesions will be of value in furthering the understanding of hepatotoxic mechanisms and assisting in the discovery of novel biomarkers of hepatotoxicity.

1-Naphthylisothiocyanate↗
PubMed2003

Chemometric investigation of the efficiency of different TiO(2)-based catalysts as principal components of TOC photochemical sensors under development.

There is an increasing demand for measurement of organic carbon in solutions both in industry and in environmental research for the purpose of continuous water-quality monitoring. Practically all the methods used are based on a catalytic system in which metal oxides play a major role. The development of a new TOC/DOC measurement system, in our work, uses a mixed anatase-rutile form of TiO(2 )as catalyst of the mineralisation process, and direct measurement of the CO(2) produced, by a gaseous diffusion electrode. The entire research is based on heterogeneous catalysis using an immobilised catalyst, which can offer considerable advantages over other methods of catalysis. Four different catalytic systems were analysed. Three involved thermal immobilisation of TiO(2) on glass supports (glass spheres and glassy particulates) or on an Al metal grid. One further system consisted of direct oxidation of a Ti grid at high temperatures. The system was illuminated using a 350 nm UV source (350 mW cm(-2)) contained in a home-made measurement cell. Five molecules-malic acid, pentachlorophenol, sodium dodecylsulfate, hydroquinone, and citric acid-which were deemed to be representative and had been investigated in several previous studies, were used as photodegradation targets. However, it was not possible to obtain a direct expression of "catalytic efficiency" simply by reading the data obtained, nor any indirect molecular "recalcitrancy" scale. Chemometric analysis, by principal components analysis, allows the five used catalytic systems to be easily compared each other and a single PC component is able to perform classification.

Journal Article↗
PubMed2005

Principal component analysis calibration method for dual-luminophore oxygen and temperature sensor films: application to luminescence imaging.

Oxygen sensor films are frequently used to image air-pressure distributions on surfaces in aerodynamic wind tunnels. In this application, the sensor film is referred to as a pressure-sensitive paint (PSP). A Stern-Volmer calibration is used to relate the emission intensity ratio of a long-lifetime luminescent dye (the pressure-sensitive luminophore, PSL) to surface air pressure. A major problem in PSP measurements arises because the Stern-Volmer calibration of the PSL's emission varies with temperature. To correct for the temperature dependence, a second luminescent dye that has an emission that varies with temperature (the temperature-sensitive luminophore, TSL) is incorporated into the sensor film. With such a dual-luminophore PSP (DL-PSP), it is possible to measure the surface-temperature distribution with the TSL emission, and this information is then used to correct the temperature dependence of the PSL's pressure response. In the present article, we report the application of a DL-PSP to obtain high-resolution air-pressure distributions on a surface that is subjected to a 20 degrees C temperature gradient. Two different calibration methods are used to generate surface-temperature and air-pressure distributions from the luminescence imaging data, and a quantitative comparison of the results obtained from the two methods is provided. The first method is based on an intensity-ratio calibration that uses luminescence images collected at two wavelengths, one corresponding to the TSL emission and the second corresponding to the PSL emission. The second method is based on principal component analysis (PCA) of luminescence images obtained at four wavelengths throughout the spectral region of the TSL and PSL emission (hyperspectral imaging, 550-750 nm). The results demonstrate that the PCA method allows the measurement of surface air pressure with higher accuracy and precision compared to those of the intensity-ratio method. The improvement is especially significant at pressures near 1 atm, where the temperature interference is most pronounced. Surface-pressure distributions are measured with comparable accuracy and precision with the two methods.

Journal Article↗
PubMed2005

Comparison of type I error for multiple test corrections in large single-nucleotide polymorphism studies using principal components versus haplotype blocking algorithms.

Although permutation testing has been the gold standard for assessing significance levels in studies using multiple markers, it is time-consuming. A Bonferroni correction to the nominal p-value that uses the underlying pair-wise linkage disequilibrium (LD) structure among the markers to determine the number of effectively independent tests has recently been proposed. We propose using the number of independent LD blocks plus the number of independent single-nucleotide polymorphisms for correction. Using the Collaborative Study on the Genetics of Alcoholism LD data for chromosome 21, we simulated 1,000 replicates of parent-child trio data under the null hypothesis with two levels of LD: moderate and high. Assuming haplotype blocks were independent, we calculated the number of independent statistical tests using 3 haplotype blocking algorithms. We then compared the type I error rates using a principal components-based method, the three blocking methods, a traditional Bonferroni correction, and the unadjusted p-values obtained from FBAT. Under high LD conditions, the PC method and one of the blocking methods were slightly conservative, whereas the 2 other blocking methods exceeded the target type I error rate. Under conditions of moderate LD, we show that the blocking algorithm corrections are closest to the desired type I error, although still slightly conservative, with the principal components-based method being almost as conservative as the traditional Bonferroni correction.

Algorithms↗
PubMed2003

A robust subspace algorithm for principal component analysis.

We present a noise robust PCA algorithm which is an extension of the Oja subspace algorithm and allows tuning the noise sensitivity. We derive a loss function which is minimized by this algorithm and interpret it in a noisy PCA setting. Results on the local stability analysis of this algorithm are given and it is shown that the locally stable equilibria are those which minimize the loss function.

Algorithms↗
PubMed2006

Approaching PM(2.5) and PM(2.5-10) source apportionment by mass balance analysis, principal component analysis and particle size distribution.

A chemical characterization was carried out for PM(2.5) and PM(2.5-10) samples collected in a suburban area and the concentrations of 12 elements were determined in 8 size segregated fractions using a Berner Impactor. Two main objectives were proposed in this work: 1) to test for closure among chemical and gravimetric measurements of PM(2.5) and PM(2.5-10) and 2) evaluate the performance of Multilinear Regression Analysis (MLRA) and Mass Balance Analysis (MBA) in the determination of source contribution to Particulate Matter (PM) concentrations. The fraction unaccounted for by chemical analysis comprised on average 17% and 34% of gravimetric PM(2.5) and PM(2.5-10), respectively. The lack of closure in PM(2.5) and PM(2.5-10) mass (i.e., constituent concentrations not adding up to gravimetrically measured) could partly result from the presence of water associated with particles and errors in the estimation of unmeasured species. MLRA and MBA showed very similar results for the temporal variation of the source contributions. However, quantitatively important discrepancies could be observed, principally due to the lack of mass closure in PM(2.5) and PM(2.5-10). Both methods indicated that the major PM(2.5) aerosol mass contributors included secondary aerosol and vehicle exhaust. In the coarse fraction, marine and mineral aerosol contributions were predominant.

Aerosols↗
PubMedDate not supplied

Comparison between neural networks (NN) and principal component analysis (PCA): structure activity relationships of 1,4-dihydropyridine calcium channel antagonists (nifedipine analogues).

The applicability of the neural network computer package PSDD (Perceptron Simulator for Drug Design/Perceptron-type Neural Network Simulator) in structure-activity relationship (SAR) studies was investigated. A group of 1,4-dihydropyridine derivatives was used in order to compare the PSDD results with those obtained previously with PCA. Calculated atomic and molecular descriptors using the semiempirical AM1 method were mainly used. It was shown that the predictive capability demonstrated by PSDD in SAR analysis were almost equivalent to that of PCA.

Algorithms↗