Ecological niche modeling and principal component analysis of Krameria Loefl. (Krameriaceae)

Krameria plants are found in arid regions of the Americas and present a floral system that attracts oil-collecting bees. Niche modeling and multivariate tools were applied to examine ecological and geographical aspects of the 18 species of this genus, using occurrence data obtained from herbaria and literature. Niche modeling showed the potential areas of occurrence for each species and the analysis of climatic variables suggested that North American species occur mostly in deserted or xeric ecoregions with monthly precipitation below 140 mm and large temperature ranges. South American species are mainly found in deserted ecoregions and subtropical savannas where monthly precipitation often exceeds 150 mm and temperature ranges are smaller. Principal Component Analysis (PCA) performed with values of temperature and precipitation showed that the distribution limits of Krameria species are primarily associated with maximum and minimum temperatures. Modeling of Krameria species proved to be a useful tool for analyzing the influence of the ecological niche variables in the geographical distribution of species, providing new information to guide future investigations. (C) 2011 Elsevier Ltd. All rights reserved.

Chemotaxonomic relationships in Celastraceae inferred from principal component analysis (PCA) and partial least squares (PLS)

This paper describes a chemotaxonomic analysis of a database of triterpenoid compounds from the Celastraceae family using principal component analysis (PCA). The numbers of occurrences of thirty types of triterpene skeleton in different tribes of the family were used as variables. The study shows that PCA applied to chemical data can contribute to an intrafamilial classification of Celastraceae, once some questionable taxa affinity was observed, from chemotaxonomic inferences about genera and they are in agreement with the phylogeny previously proposed. The inclusion of Hippocrateaceae within Celastraceae is supported by the triterpene chemistry.

Reduction capability of soil humic substances from the Rio Negro basin, Brazil, towards Hg(II) studied by a multimethod approach and principal component analysis (PCA)

This paper characterizes humic substances (HS) extracted from soil samples collected in the Rio Negro basin in the state of Amazonas, Brazil, particularly investigating their reduction capabilities towards Hg(II) in order to elucidate potential mercury cycling/volatilization in this environment. For this reason, a multimethod approach was used, consisting of both instrumental methods (elemental analysis, EPR, solid-state NMR, FIA combined with cold-vapor AAS of Hg(0)) and statistical methods such as principal component analysis (PCA) and a central composite factorial planning method. The HS under study were divided into groups, complexing and reducing ones, owing to different distribution of their functionalities. The main functionalities (cor)related with reduction of Hg(II) were phenolic, carboxylic and amide groups, while the groups related with complexation of Hg(II) were ethers, hydroxyls, aldehydes and ketones. The HS extracted from floodable regions of the Rio Negro basin presented a greater capacity to retain (to complex, to adsorb physically and/or chemically) Hg(II), while nonfloodable regions showed a greater capacity to reduce Hg(II), indicating that HS extracted from different types of regions contribute in different ways to the biogeochemical mercury cycle in the basin of the mid-Rio Negro, AM, Brazil. (c) 2007 Published by Elsevier B.V.

Effect of Passive Fit Absence in the Prosthesis/Implant/Retaining Screw System: A Two-Dimensional Finite Element Analysis

The misfit between prostheses and implants is a clinical reality, but the level that can be accepted without causing mechanical or biologic problem is not well defined. This study investigates the effect of different levels of unilateral angular misfit prostheses in the prosthesis/implant/retaining screw system and in the surrounding bone using finite element analysis. Four models of a two-dimensional finite element were constructed: group I (control), prosthesis that fit the implant; groups 2 to 4, prostheses with unilateral angular misfit of 50, 100, and 200 mu m, respectively. A load of 133 N was applied with a 30-degree angulation and off-axis at 2 mm from the long axis of the implant at the opposite direction of misfit on the models. Taking into account the increase of the angular misfit, the stress maps showed a gradual increase of prosthesis stress and uniform stress in the implant and trabecular bone. Concerning the displacement, an inclination of the system due to loading and misfit was observed. The decrease of the unilateral contact between prosthesis and implant leads to the displacement of the entire system, and distribution and magnitude alterations of the stress also occurred.

Chemosystematic studies of natural compounds isolated from Asteraceae: characterization of tribes by principal component analysis

This work describes an application of principal component analysis (PCA) on a database of secondary metabolites from the Asteraceae family. The numbers of occurrences of metabolites in 11 chemical classes for the different vibes of the family were used as variables, PCA allows the identification of chemical classes that contribute most to the subgroups classification within the family. Relationships between chemical composition and botanical classification were made. (C) 2001 Elsevier B.V. B.V. All rights reserved.

Genetic parameter estimates and principal component analysis of breeding values of reproduction and growth traits in female Canchim cattle

Phenotypic data from female Canchim beef cattle were used to obtain estimates of genetic parameters for reproduction and growth traits using a linear animal mixed model. In addition, relationships among animal estimated breeding values (EBVs) for these traits were explored using principal component analysis. The traits studied in female Canchim cattle were age at first calving (AFC), age at second calving (ASC), calving interval (CI), and bodyweight at 420 days of age (BW420). The heritability estimates for AFC, ASC, CI and BW420 were 0.03±0.01, 0.07±0.01, 0.06±0.02, and 0.24±0.02, respectively. The genetic correlations for AFC with ASC, AFC with CI, AFC with BW420, ASC with CI, ASC with BW420, and CI with BW420 were 0.87±0.07, 0.23±0.02, -0.15±0.01, 0.67±0.13, -0.07±0.13, and 0.02±0.14, respectively. Standardised EBVs for AFC, ASC and CI exhibited a high association with the first principal component, whereas the standardised EBV for BW420 was closely associated with the second principal component. The heritability estimates for AFC, ASC and CI suggest that these traits would respond slowly to selection. However, selection response could be enhanced by constructing selection indices based on the principal components. © CSIRO 2013.

Genetic parameters and principal component analysis for egg production from White Leghorn hens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Evaluation of solvent effect on the extraction of phenolic compounds and antioxidant capacities from the berries: application of principal component analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genotype x location x feeding interactions in Nellore cattle calculated through three-mode principal component analysis

The main objective of this study was to apply three-mode principal component analysis to assess the triple interaction (genotype x location x feeding) on direct genetic value for weight at 205 days of age. We used 60 sires with offspring in three regions of northeastern Brazil (Maranhao, Mata and Agreste, and Reconcavo Baiano) and raised on a pasture regime or with supplementation. There was no interaction between genotype and location, but there was a correlation between genotype and direct effect of feeding. The use of sires should be dictated according to the system of rearing of their offspring.

Discrimination of Basal Cell Carcinoma and Melanoma from Normal Skin Biopsies in Vitro Through Raman Spectroscopy and Principal Component Analysis

Objective: Raman spectroscopy has been employed to discriminate between malignant (basal cell carcinoma [BCC] and melanoma [MEL]) and normal (N) skin tissues in vitro, aimed at developing a method for cancer diagnosis. Background data: Raman spectroscopy is an analytical tool that could be used to diagnose skin cancer rapidly and noninvasively. Methods: Skin biopsy fragments of similar to 2 mm(2) from excisional surgeries were scanned through a Raman spectrometer (830 nm excitation wavelength, 50 to 200 mW of power, and 20 sec exposure time) coupled to a fiber optic Raman probe. Principal component analysis (PCA) and Euclidean distance were employed to develop a discrimination model to classify samples according to histopathology. In this model, we used a set of 145 spectra from N (30 spectra), BCC (96 spectra), and MEL (19 spectra) skin tissues. Results: We demonstrated that principal components (PCs) 1 to 4 accounted for 95.4% of all spectral variation. These PCs have been spectrally correlated to the biochemicals present in tissues, such as proteins, lipids, and melanin. The scores of PC2 and PC3 revealed statistically significant differences among N, BCC, and MEL (ANOVA, p < 0.05) and were used in the discrimination model. A total of 28 out of 30 spectra were correctly diagnosed as N, 93 out of 96 as BCC, and 13 out of 19 as MEL, with an overall accuracy of 92.4%. Conclusions: This discrimination model based on PCA and Euclidean distance could differentiate N from malignant (BCC and MEL) with high sensitivity and specificity.

Two-dimensional relaxation-diffusion analysis to study water compartmentalization in cells by a single-sided NMR device

In questo lavoro di tesi è presentato un metodo per lo studio della compartimentalizzazione dell’acqua in cellule biologiche, mediante lo studio dell’autodiffusione delle molecole d’acqua tramite uno strumento NMR single-sided. Le misure sono state eseguite nel laboratorio NMR all’interno del DIFA di Bologna. Sono stati misurati i coefficienti di autodiffusione di tre campioni in condizione bulk, ottenendo risultati consistenti con la letteratura. È stato poi analizzato un sistema cellulare modello, Saccharomyces cerevisiae, allo stato solido, ottimizzando le procedure per l’ottenimento di mappe di correlazione 2D, aventi come assi il coefficiente di autodiffusione D e il tempo di rilassamento trasversale T2. In questo sistema l’acqua è confinata e l’autodiffusione è ristretta dalle pareti cellulari, si parla quindi di coefficiente di autodiffusione apparente, Dapp. Mediante le mappe sono state individuate due famiglie di nuclei 1H. Il campione è stato poi analizzato in diluizione in acqua distillata, confermando la separazione del segnale in due distinte famiglie. L’utilizzo di un composto chelato, il CuEDTA, ha permesso di affermare che la famiglia con il Dapp maggiore corrisponde all’acqua esterna alle cellule. L’analisi dei dati ottenuti sulle due famiglie al variare del tempo lasciato alle molecole d’acqua per la diffusione hanno portato alla stima del raggio dei due compartimenti: r=2.3±0.2µm per l’acqua extracellulare, r=0.9±0.1µm per quella intracellulare, che è probabilmente acqua scambiata tra gli organelli e il citoplasma. L’incertezza associata a tali stime tiene conto soltanto dell’errore nel calcolo dei parametri liberi del fit dei dati, è pertanto una sottostima, dovuta alle approssimazioni connesse all’utilizzo di equazioni valide per un sistema poroso costituito da pori sferici connessi non permeabili. Gli ordini di grandezza dei raggi calcolati sono invece consistenti con quelli osservabili dalle immagini ottenute con il microscopio ottico.