Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0220723 (PCA)
 4,687 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The PACAPs have been shown to be potent vasodilators in different animal species. Data in humans are still lacking. Therefore we investigated the effects of PACAP 38, PACAP 27 and VIP on isolated human and porcine coronary arteries (HCA and PCA). Our data show, that the PACAPs are endothelium-independent vasorelaxants, which in HCA are slightly more potent than VIP. The N-terminal shortened peptides PACAP 6-38 and PACAP 6-27 also show relatively potent vasorelaxant effects, acting as partial agonists. Glibenclamide, a selective inhibitor of ATP-sensitive potassium channels, partially reverses the effects of the PACAPs, indicating an involvement of these channels in the mechanism of action.
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PMID:Pituitary adenylate cyclase activating peptides are endothelium-independent dilators of human and porcine coronary arteries. 771 91

Concentrations of metals (Al, Fe, Ti, Ni, Mn, Cr, Zn, Cu, Pb) were determined in surface sediments from Taranto gulf (Ionian Sea, Southern Italy) in order to assess the distribution and the bioavailability of metals. Total metal content and speciation of Fe, Ni, Mn, Zn, Cu and Pb were determined. Sediment cores were also sampled in some stations of particular interest. The analytical results show that metals distribution does not show significant variations in relation to depth. Metal distribution in the Taranto gulf is mainly influenced by industrial wastes from Taranto town, by rivers of the Basilicata region and by prevailing anticlockwise marine currents. These factors cause an accumulation of metals in the sediments near to the coasts of Calabria. The statistical analysis, effected by HCA and PCA methods, can be considered a good starting point in order to classify sediment samples and to locate accumulation areas. Metal speciation shows that Fe, Ni and Zn are present in sediments mainly as sulphides, Mn is present principally in an ion-exchange form or bound to carbonate, while Cu and Pb are mainly present in the fraction bounds to humic acids.
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PMID:Distribution and speciation of metals in surface sediments of Taranto [corrected] gulf (Ionian Sea, Southern Italy). 1534 94

Dietary restriction (DR)-induced changes in the serum metabolome may be biomarkers for physiological status (e.g., relative risk of developing age-related diseases such as cancer). Megavariate analysis (unsupervised hierarchical cluster analysis [HCA]; principal components analysis [PCA]) of serum metabolites reproducibly distinguish DR from ad libitum fed rats. Component-based approaches (i.e., PCA) consistently perform as well as or better than distance-based metrics (i.e., HCA). We therefore tested the following: (A) Do identified subsets of serum metabolites contain sufficient information to construct mathematical models of class membership (i.e., expert systems)? (B) Do component-based metrics out-perform distance-based metrics? Testing was conducted using KNN (k-nearest neighbors, supervised HCA) and SIMCA (soft independent modeling of class analogy, supervised PCA). Models were built with single cohorts, combined cohorts or mixed samples from previously studied cohorts as training sets. Both algorithms over-fit models based on single cohort training sets. KNN models had >85% accuracy within training/test sets, but were unstable (i.e., values of k could not be accurately set in advance). SIMCA models had 100% accuracy within all training sets, 89 % accuracy in test sets, did not appear to over-fit mixed cohort training sets, and did not require post-hoc modeling adjustments. These data indicate that (i) previously defined metabolites are robust enough to construct classification models (expert systems) with SIMCA that can predict unknowns by dietary category; (ii) component-based analyses outperformed distance-based metrics; (iii) use of over-fitting controls is essential; and (iv) subtle inter-cohort variability may be a critical issue for high data density biomarker studies that lack state markers.
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PMID:Development of biomarkers based on diet-dependent metabolic serotypes: practical issues in development of expert system-based classification models in metabolomic studies. 1566 13

This paper shows the results of a preliminary study of air monitoring in the province of Lecce (Apulia, Southern Italy). In particular, the attention has been focused on the determination of the PM-10 level and of the concentration of nine metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, V and Zn) present on the filters which were collected in two towns (Lecce and Campi Salentina) from 2002 until 2003. The metals have been chosen on the basis of their toxicity and of their possible use as chemical tracers. The results have proved that PM-10 values and metals concentrations did not show substantial difference between the two towns and that PM-10 level and lead concentration are below the limit established by Italian law in force. The experiments have demonstrated a high correlation between iron and manganese in both sampling sites; this could be attributed to pollution of metallurgical origin. Multivariate statistical analysis, carried out by HCA and PCA methods, has been used in order to differentiate samples in relation to sampling sites, sampling period and meteorological conditions.
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PMID:PM-10 and heavy metals in particulate matter of the province of Lecce (Apulia, Southern Italy). 1580 Nov 74

A study using two classification methods (SDA and SIMCA) was carried out in this work with the aim of investigating the relationship between the structure of flavonoid compounds and their free-radical-scavenging ability. In this work, we report the use of chemometric methods (SDA and SIMCA) able to select the most relevant variables (steric, electronic, and topological) responsible for this ability. The results obtained with the SDA and SIMCA methods agree perfectly with our previous model, in which we used other chemometric methods (PCA, HCA and KNN) and are also corroborated with experimental results from the literature. This is a strong indication of how reliable the selection of variables is.
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PMID:The use of classification methods for modeling the antioxidant activity of flavonoid compounds. 1660 67

Marine sediments from the Mar Grande and Gulf of Taranto were analysed for 17 parent PAHs, with molecular weight from 128 to 278 Daltons. The analyses were performed by gas chromatography coupled to mass spectrometry (GC-MS). Total PAHs content in sediments ranged from 464 to 12522 microg kg(-1) dry wt for Mar Grande and from 593 to 72275 microg kg(-1) dry wt for Gulf of Taranto. The analytical results were compared with the published results for other coastal areas in the Mediterranean Sea. PAHs levels in the Gulf of Taranto sediments were the highest in the Mediterranean sea, while PAHs concentrations in Mar Grande were higher than the ones reported in the Adriatic and Cretan Sea and with the same order of magnitude of the ones known for coastal areas of the Western and the Eastern Mediterranean Sea. PAHs concentration ratios were consistent with the main source of these compounds, in most areas, being pyrolysis. Based on the comparison of both the individual and the total PAHs concentrations with proposed sediment quality guidelines, the acute biological effects on the marine organisms were probable, especially for the Gulf of Taranto, in which almost all PAHs concentrations in sediments were higher than the guidelines limit values. The statistical analysis effected by HCA and PCA methods was used in order to classify sediment samples and to identify accumulation areas.
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PMID:Distribution and occurence of polycyclic aromatic hydrocarbons (PAHs) in sediments from the Mar Grande and Gulf of Taranto (Ionian Sea, southern Italy). 1673 22

Arylpiperazine compounds are promising 5-HT(1A) receptor ligands that can contribute for accelerating the onset of therapeutic effect of selective serotonin reuptake inhibitors. In the present work, the chemometric methods HCA, PCA, KNN, SIMCA and PLS were employed in order to obtain SAR and QSAR models relating the structures of arylpiperazine compounds to their 5-HT(1A) receptor affinities. A training set of 52 compounds was used to construct the models and the best ones were obtained with nine topological descriptors. The classification and regression models were externally validated by means of predictions for a test set of 14 compounds and have presented good quality, as verified by the correctness of classifications, in the case of pattern recognition studies, and by the high correlation coefficients (q(2)=0.76, r(2)=0.83) and small prediction errors for the PLS regression. Since the results are in good agreement with previous SAR studies, we can suggest that these findings can help in the search for 5-HT(1A) receptor ligands that are able to improve antidepressant treatment.
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PMID:A chemometric study of the 5-HT(1A) receptor affinities presented by arylpiperazine compounds. 1756 49

This work describes the use of a multi-LED photometer for discrimination of mineral water samples, employing chromogenic reagents and chemometric techniques. Forty-five water samples (including 7 different brands of mineral water and samples of deionised, distilled and tap waters) were analysed in a monosegmented flow system, using three different chromogenic reagents (murexide, PAR and eriochrome black T) in a pH 10.0 NH3/NH4(+) buffer in separate injections. Measurements were performed at 470, 500, 525, 562, 590, 612, 636 and 654 nm. Analyses were carried out using PCA, employing data sets including absorbance values obtained with one, two or all three reagents, which comprise 8, 16 or 24 variables, respectively. The best result was obtained with the data set from murexide and eriochrome black T, providing a clear distinction between 9 groups (distilled and deionised waters were classified in the same group). Based on the loading values, it was possible to select four wavelengths (470, 500, 590 and 654 nm) that provided a similar discrimination. With the use of these four LED, an HCA was performed, providing discrimination between 8 groups at a similarity level of 0.88. A model based on SIMCA allowed correctly classifying 94% of the samples. The discrimination between different groups is due to the metal ion contents in the water samples, mainly calcium and magnesium. Therefore, the use of common complexing reagents, such as murexide and erichrome black T, a multi-LED photometer and chemometric techniques provide an easy and simple method for water discrimination.
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PMID:A simple method for water discrimination based on an light emitting diode (LED) photometer. 1761 41

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.
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PMID:Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis. 1907 79

Extra virgin (EV), the finest and most expensive among all the olive oil grades, is often adulterated by the cheapest and lowest quality ordinary (ON) olive oil. A new methodology is described herein that provides a simple, rapid, and accurate way not only to detect such type of adulteration, but also to distinguish between these olive oil grades (EV and ON). This approach is based on the application of direct infusion electrospray ionization mass spectrometry in the positive ion mode, ESI(+)-MS, followed by the treatment of the MS data via exploratory statistical approaches, PCA (principal component analysis) and HCA (hierarchical clustering analysis). Ten distinct brands of each EV and ON olive oil, acquired at local stores, were analyzed by ESI(+)-MS and the results from HCA and PCA clearly indicated the formation of two distinct groups related to these two categories. For the adulteration study, one brand of each olive oil grade (EV and ON) was selected. The counterfeit samples (a total of 20) were then prepared by adding assorted proportions, from 1 to 20% w/w, with increments of 1% w/w, of the ON to the EV olive oil. The PCA and HCA methodologies, applied to the ESI(+)-MS data from the counterfeit (20) and authentic (10) EV samples, were able to readily detect adulteration, even at levels as low as 1% w/w.
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PMID:Extra virgin (EV) and ordinary (ON) olive oils: distinction and detection of adulteration (EV with ON) as determined by direct infusion electrospray ionization mass spectrometry and chemometric approaches. 2053 17


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