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PubMed2004

Image fusion for dynamic contrast enhanced magnetic resonance imaging.

BACKGROUND: Multivariate imaging techniques such as dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been shown to provide valuable information for medical diagnosis. Even though these techniques provide new information, integrating and evaluating the much wider range of information is a challenging task for the human observer. This task may be assisted with the use of image fusion algorithms. METHODS: In this paper, image fusion based on Kernel Principal Component Analysis (KPCA) is proposed for the first time. It is demonstrated that a priori knowledge about the data domain can be easily incorporated into the parametrisation of the KPCA, leading to task-oriented visualisations of the multivariate data. The results of the fusion process are compared with those of the well-known and established standard linear Principal Component Analysis (PCA) by means of temporal sequences of 3D MRI volumes from six patients who took part in a breast cancer screening study. RESULTS: The PCA and KPCA algorithms are able to integrate information from a sequence of MRI volumes into informative gray value or colour images. By incorporating a priori knowledge, the fusion process can be automated and optimised in order to visualise suspicious lesions with high contrast to normal tissue. CONCLUSION: Our machine learning based image fusion approach maps the full signal space of a temporal DCE-MRI sequence to a single meaningful visualisation with good tissue/lesion contrast and thus supports the radiologist during manual image evaluation.

Algorithms↗

PubMed2005

Casein haplotype structure in five Italian goat breeds.

The aim of this work was to investigate the genetic structure of the casein gene cluster in 5 Italian goat breeds and to evaluate the haplotype variability within and among populations. A total of 430 goats from Vallesana, Roccaverano, Jonica, Garganica, and Maltese breeds were genotyped at alphas1-casein (CSN1S1), alphas2-casein, (CSN1S2), beta-casein (CSN2), and kappa-casein (CSN3) loci using several genomic techniques and milk protein analysis. Casein haplotype frequencies were estimated for each breed. Principal component analysis was carried out to highlight the relationship among breeds. Allele and haplotype distributions indicated considerable differences among breeds. The haplotype CSN1S1*F- CSN1S2*F-CSN3*D occurred in all breeds with frequencies >0.100 and was the most common haplotype in the Southern breeds. A high frequency of CSN1S1*0-CSN1S2*C-CSN3*A haplotype was found in Vallesana population (0.162). Principal component analysis clearly separated the Northern and Southern breeds by the first component. The variability of the caprine casein loci and variety of resulting haplotypes should be exploited in the future using specific breeding programs aiming to preserve biodiversity and to select goat genetic lines for specific protein production.

Animals↗

PubMed2005

Detection of lung cancer by sensor array analyses of exhaled breath.

RATIONALE: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry. OBJECTIVES: We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma. METHODS: In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer. MAIN RESULTS: Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively. CONCLUSION: The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer.

Adult↗

PubMed2004

Rumen odd and branched chain fatty acids in relation to in vitro rumen volatile fatty acid productions and dietary characteristics of incubated substrates.

A first aim of this batch in vitro experiment (21 h) was to use changes in odd and branched chain fatty acid (OBCFA) patterns to suggest shifts in microbial populations, associated with four types of incubated whole dairy cow diets. Principal component analysis suggested higher dietary starch increased the proportion of C15:0 and C17:0, whereas increased neutral detergent fibre content was positively related to anteiso C15:0 concentrations, which is in agreement with the importance of these fatty acids in respectively amylolytic and cellulolytic bacteria. A second aim of the experiment was to relate rumen volatile fatty acid proportions to OBCFA by principal component regression and to compare these relations with predictions based on diet proximate composition. The R2 values achieved for the regressions between acetate, propionate and butyrate, and OBCFA were 79.6%, 86.6% and 84.9% respectively. Moreover, in the current study, predictions of the rumen fermentation pattern showed higher R2 (p < 0.01) when based on OBCFA compared with proximate feed composition. If relations persist in vivo, there could be scope for milk OBCFA to predict the supply of specific rumen nutrients.

Animal Feed↗

PubMed2002

Interpretation of static time-of-flight secondary ion mass spectra of adsorbed protein films by multivariate pattern recognition.

Multivariate analysis has become increasingly common in the analysis of multidimensional spectral data. We previously showed that the multivariate analysis technique principal component analysis (PCA) is an excellent method for interpreting the static time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of adsorbed protein films. PCA is an unsupervised pattern recognition technique that loses resolution between spectra of different proteins as more proteins are added to the data set due to large within-group variation. The supervised pattern recognition techniques discriminant principal component analysis (DPCA) and linear discriminant analysis (LDA), which aim to control within-group variation while maximizing between-group separation to enhance discrimination between groups, were compared with PCA using data sets of TOF-SIMS spectra of proteins adsorbed onto mica and PTFE substrates. DPCA and LDA quantitatively improved discrimination between groups and provided different information about the data than PCA. LDA was able to classify unknown samples with a misclassification rate lower than PCA or DPCA. Both unsupervised and supervised pattern recognition techniques are useful for the interpretation and classification of static TOF-SIMS spectra of adsorbed protein films.

Adsorption↗

PubMed2005

Trends of dental arc variation in a young adult male population and their meaning in the concept of occlusion.

To describe the variation of shape and size of dental arcs the method of principal components was applied. 27 measurements of every dental cast made from 50 young adult males with good occlusion were made, and the following parameters were calculated: 7 widths, 5 left chords, 5 right chords, 5 sagittal lengths (calculated as orthogonal to corresponding width) and 5 angles. Different sets of features were analyzed for both arcs together and for each arc separately. Three independent analyses by the method of principal components show a good description of the main trend of dental arc shape and size variation and a difference between the growth and variation of frontal and distal parts of the arcs. They also describe the variations of occlusion. The trends of dental arc variation ascertained help us to understand the nature of malocclusions and the causes of their preservation in evolution.

Adult↗

PubMed2006

Size correction: comparing morphological traits among populations and environments.

Morphological relationships change with overall body size and body size often varies among populations. Therefore, quantitative analyses of individual traits from organisms in different populations or environments (e.g., in studies of phenotypic plasticity) often adjust for differences in body size to isolate changes in allometry. Most studies of among population variation in morphology either (1) use analysis of covariance (ANCOVA) with a univariate measure of body size as the covariate, or (2) compare residuals from ordinary least squares regression of each trait against body size or the first principal component of the pooled data (shearing). However, both approaches are problematic. ANCOVA depends on assumptions (small variance in the covariate) that are frequently violated in this context. Residuals analysis assumes that scaling relationships within groups are equal, but this assumption is rarely tested. Furthermore, scaling relationships obtained from pooled data typically mischaracterize within-group scaling relationships. We discuss potential biases imposed by the application of ANCOVA and residuals analysis for quantifying morphological differences, and elaborate and demonstrate a more effective alternative: common principal components analysis combined with Burnaby's back-projection method.

Biological Evolution↗

PubMed2006

Coordinative structure of manipulative hand-movements facilitates their recognition.

Manipulative hand movements involve coordinated movements of the fingers to manipulate an object within the hand, and are classified as either simultaneous or sequential. Simultaneous hand movements are characterized by single coordinated patterns of digit movements, while sequential hand movements involve sequences of such patterns. Here, we investigate the extent of the coordination among 15 hand-joints during simultaneous hand movements, and demonstrate that it leads to a concise representation that facilitates movement recognition. Principal component analysis (PCA), performed in the 15-dimensional (15-D) joint-space, indicates that the first principal-component captures more than 98% of the variability in individual hand movements. Consequently, the first principal direction provides a 15-D feature-vector that describes the underlying-coordination and can be used for automatic recognition. We evaluated this recognition strategy on a set of nine simultaneous hand-movements using a database of six users, each performing six sessions. A dedicated classifier for each user resulted in recognition rates of 97.0 +/- 4.7% during testing, while a single generic classifier achieved 95.2 +/- 2.5% recognition rates. We conclude that the suggested feature-vector captures the invariant structure of simultaneous hand-movements, facilitates their recognition, and may provide insight into motor planning.

Artificial Intelligence↗

PubMed1979

A multivariate analysis of fatness and relative fat patterning.

Skinfold measurements (triceps, subscapular, suprailiac and medial calf) in four samples (376 boys, 352 girs, 338 men and 380 women from rural Colombia) were subjected to principal components analysis to identify components of obesity and relative fat patterning. Three components emerged which were similar in the four samples: a first component of fatness explaining 70-80% of the variance and two fat pattern components each explaining 10-15% of the variance: trunk-extremity and upper-lower body. Fatness and the trunk-extremity pattern components changed with age in children (7-12 years), but none of the components changed with age in adults (25-60+). The fatter tended to be more patterned in both age groups. Canonical correlation analysis revealed that socioeconomic status was more related to fatness than to patterning. With the exception of brothers, all first degree relatives (sib, parent-off-spring) and spouses were correlated in fatness. Some of the correlations between relatives--usually sibs, but not spouses--were also significant for the pattern components, suggesting a genetic basis for the known stability of this characteristic (Garn, '55a). Principal components analysis is a useful multivariate alternative for quantitative studies of anthropometric patterning.

Adipose Tissue↗

PubMed2004

New background correction method for liquid chromatography with diode array detection, infrared spectroscopic detection and Raman spectroscopic detection.

A new method to eliminate the background spectrum (EBS) during analyte elution in column liquid chromatography (LC) coupled to spectroscopic techniques is proposed. This method takes into account the shape and also intensity differences of the background eluent spectrum. This allows the EBS method to make a better estimation of the background eluent spectrum during analyte elution. This is an advantage for quantification as well as for identification of analytes. The EBS method uses a two-step procedure. First, the baseline spectra are modeled using a limited number of principal components (PCs). Subsequently, an asymmetric least squares (asLS) regression method is applied using these principal components to correct the measured spectra during elution for the background contribution. The asymmetric least squares regression needs one parameter, the asymmetry factor p. This asymmetry factor determines relative weight of positive and negative residuals. Simulations are performed to test the EBS method in well-defined situations. The effect of spectral noise on the performance and the sensitivity of the EBS method for the value of the asymmetry factorp is tested. Two applications of the EBS method are discussed. In the first application, the goal is to extract the analyte spectrum from an LC-Raman analysis. In this case, the EBS method facilitates easy identification of unknown analytes using spectral libraries. In a second application, the EBS method is used for baseline correction in LC-diode array detection (DAD) analysis of polymeric standards during a gradient elution separation. It is shown that the EBS method yields a good baseline correction, without the need to perform a blank chromatographic run.

Spectrophotometry, Infrared↗

PubMed2006

Application of solid-phase microextraction to virgin olive oil quality control.

Volatiles of olive oils from 'tree-picked', 'ground-picked' and both mixed olives were analysed by solid-phase microextraction and gas chromatography with flame ionisation detection (FID). Headspace sampling was carried out for 30min of fibre exposition at 40 degrees C of sampling temperature by the selected 74 microm polydimethylsiloxane/divinylbenzene (PDMS/DVB) fibre. Chromatographic data were analysed by principal components analysis (PCA) and then selected 14 compounds from x-loading of first principal component that provides a differentiation of oils accord its sensorial characterisation. Compounds such as 4-ethylphenol and styrene were identified by gas chromatography-mass spectrometry (GC-MS) in 'ground-picked' olive oils.

Chromatography, Gas↗

PubMed2002

Dinitro and quinodimethane derivatives of terthiophene that can be both oxidized and reduced. Crystal structures, spectra, and a method for analyzing quinoid contributions to structure.

Two new oligothiophenes, the dinitro compound 3',4'-dibutyl-5,5' '-dinitro-2,2':5',2' '-terthiophene (1) and the quinodimethane 3',4'-dibutyl-5,5' '-bis(dicyanomethylene)-5,5' '-dihydro-2,2':5',2' '-terthiophene (2), have been synthesized and studied with electrochemistry, UV-vis-NIR-IR spectroscopy, ESR, and X-ray crystallography. These compounds, designed to be both electron and hole carriers, show redox properties that are unusual for oligothiophenes. Cyclic voltammetry and spectroelectrochemistry demonstrated that each compound could be oxidized to a cation radical and reduced to an anion radical and dianion. The spectra of 2 and its three redox partners were analyzed in terms of a limiting structure in which the neutral 2 has orbitals corresponding to those of a substituted-terthiophene dication. Compound 1 crystallizes with the thiophene rings held in an unusual nonplanar, cisoid configuration in face-to-face pi-stacks, with a spacing between molecules of 3.65 A. The C-C bond lengths of the outer nitro-substituted rings have quinoid character. Compound 2 crystallizes with the thiophene rings in a planar, transoid configuration. The molecules are held in pi-stacks formed from pi-dimers with a spacing between molecules of 3.47 and 3.63 A. The C-C bond distances of the thiophene rings of 1 and 2 and other oligomers were analyzed by a principal component analysis. The analysis found that 93% of the structural variance resided in one principal component related to the quinoid structure of the oligothiophene moiety. The analysis reliably demonstrated a quinoid contribution to the structure of 1. This method should be applicable to understanding the structure of other conjugated molecules in which quinoid structures contribute.

Journal Article↗

PubMed1978

Synthetic maps of human gene frequencies in Europeans.

Multivarate techniques can be used to condense the information for a large number of loci and alleles into one or a few synthetic variables. The geographic distribution of synthetic variables can be plotted by the same technique used in mapping the gene frequency of a single allele. Synthetic maps were constructed for Europe and the Near East, with the use of principal components to condense the information of 38 independent alleles from ten loci. The first principal component summarizes close to 30% of the total information and shows gradients. Maps thus constructed show clines in remarkable agreement with those expected on the basis of the spread of early farming in Europe, thus supporting the hypothesis that this spread was a demic spread rather than a cultural diffusion of farming technology.

Agriculture↗

PubMed1990

Temporal encoding of two-dimensional patterns by single units in primate primary visual cortex. II. Information transmission.

1. Previously, we studied how picture information was processed by neurons in inferior temporal cortex. We found that responses varying in both response strength and temporal waveform carried information about briefly flashed stationary black-and-white patterns. Now, we have applied that same paradigm to the study of striate cortical neurons. 2. In this approach the responses to a set of basic black and white pictures were quantified through use of a set of basic waveforms, the principal components (extracted from all the responses of each neuron). We found that the first principal component, which corresponds to the response strength, and others, which correspond to different basic temporal activity patterns, were significantly related to the stimuli, i.e., the stimulus drove both the response strength and its temporal pattern. 3. Our previous study had shown that, when information theory was used to quantify the stimulus-response relation, inferior temporal neurons convey over twice as much information in a response code that includes temporal modulation as in a response code that includes only the response strength. This study shows that striate cortical neurons also carry twice as much information in a temporal code as in a response strength code. Thus single visual neurons at both ends of a cortical processing chain for visual pattern use a multidimensional temporal code to carry stimulus-related information. 4. These results support our multiplex-filter hypothesis, which states that single visual system neurons can be regarded as several simultaneously active parallel channels, each of which conveys independent information about the stimulus.

Analysis of Variance↗

PubMed2003

Modeling and predicting hearing aid outcome.

Following a brief tutorial on the application of factor analysis to hearing aid outcome measures, three studies of hearing aid outcome measures in elderly adults are presented and analyzed. Two of the studies were completed at Indiana University (IU-1 and IU-2), and one was a collaborative multisite study by the Veterans Administration and the National Institute of Deafness and other Communication Disorders (NIDCD/VA). IU-1 measured hearing aid outcome in 173 elderly wearers of single-channel, linear, in-the-ear hearing aids with output-limiting compression, whereas IU-2 obtained the same extensive set of outcome measures from 53 elderly wearers of two-channel, wide-dynamic-range compression, in-the-canal hearing aids. In the NIDCD/VA study, 333 to 338 participants wore three single-channel circuits in succession, with each circuit housed within an in-the-ear shell. The three circuits included in that study and in this analysis were: (1) linear with peak clipping, (2) linear with output-limiting compression, and (3) single-channel, wide-dynamic-range compression. Evaluation of the many outcome measures completed in each study using principal components factor analysis revealed that from three (both IU studies) to five (NIDCD/VA study) principal components captured the individual differences in hearing aid outcome. This was independent of hearing aid type (in-the-ear or in-the-canal) and circuitry. Subsequent multiple regression analyses of individual differences in performance along each dimension of hearing aid outcome revealed that these individual differences could be accounted for reasonably well by various prefit variables for some dimensions of outcome, but not others. In general, measures of speech recognition performance were well accounted for by prefit measures, with the best predictors being hearing loss, cognitive performance, and age. Measures of hearing aid usage were less well accounted for by prefit measures, with the most accurate predictor of current hearing aid use being prior hearing aid use. The outcome dimension accounted for most poorly was that associated with hearing aid satisfaction, with subjective measures of aided sound quality being the best predictor of performance along this dimension of hearing aid outcome. Additional multicenter, large-scale studies are needed to develop more complete models of hearing aid outcome and to identify the variables that influence various aspects of hearing aid outcome. It is only through this additional research that it will be possible to optimize outcome for hearing aid wearers.

Journal Article↗

PubMed1996

Comparative evaluations of neuroperformance and clinical outcome assessments in chronic progressive multiple sclerosis: I. Reliability, validity and sensitivity to disease progression. Multiple Sclerosis Study Group.

There remains controversy regarding the most sensitive and valid outcome assessments to use in multiple sclerosis (MS) clinical trials. A double blind, placebo controlled, parallel group multicenter clinical trial to evaluate the clinical efficacy of cyclosporine A in chronic progressive MS incorporated several major clinical and performance outcome assessment modalities and a large sample size, both of which provide a unique opportunity to explore the relationship among MS disease status and the various outcome measures over time. The measures included a structured neurological examination, the Kurtzke Functional System scales and Expanded Disability Status Score, and the Incapacity Status Scale from the MS Minimal Record of Disability, the Harvard Ambulation Index, and neuroperformance testing. A test-retest reliability index, principal component analyses and a signal-to-noise ratio metric were used to comparatively evaluate the reliability, validity and sensitivity to disease progression of the various outcome assessments. The goal was to provide a rational basis for selection of behavioral outcome assessments in future MS clinical trials by identifying the primary dimensions of MS measured by the candidate outcome assessments and providing an objective basis for selecting tests that are most sensitive to MS disease and its progression over a two year trial period. We conclude that the components of the major clinical and performance measures show excellent reliability and cross validation. Principal component analyses of all outcome assessments yielded six primary underlying factors for describing disease status in chronic progressive MS that included lower extremity/pyramidal dysfunction, cerebellar/brainstem and upper extremity dysfunction, somatosensory dysfunction, visual dysfunction, mental or intellectual dysfunction and bowel/bladder problems. Signal-to-noise ratios indicated that upper and lower extremity composites of neuroperformance test items provided the most sensitive indicators of MS disease progression in the placebo group over the 2 year trial period.

Activities of Daily Living↗

PubMed2006

Chemical and biological pollution contribute to the immunological profiles of free-ranging harbor seals.

Polychlorinated biphenyls and other persistent organic pollutants have been associated with immunotoxicity and outbreaks of (infectious) disease in marine mammals by rendering them vulnerable to infection by pathogens such as viruses and bacteria. In an immunotoxicological study of free-ranging harbor seals (Phoca vitulina), we obtained samples of blood and blubber from seal pups that were live-captured from two remote and two near-urban sites in British Columbia, Canada, and Washington state, USA. Using these samples, we quantified hematology, innate immune function, adaptive immune function, and polychlorinated biphenyl accumulation. While controlling for confounding factors (age, sex, and condition), univariate correlations between phagocytosis (r2 = 0.30, p = 0.002), respiratory burst (r2 =0.45, p= 0.000), T-lymphocyte function (r2 = 0.16, p = 0.028), lymphocyte signaling (r2 = 0.17, p = 0.025), and lymphocyte counts (r2 = 0.29, p = 0.002), and polychlorinated biphenyl concentrations suggested chemical-associated immunotoxicity. Principal component analysis of immunological endpoints provided additional evidence of immunotoxic effects in seals. However, principal component analysis also identified a noncontaminant-related factor by distinguishing between seals inhabiting urban versus remote sites, with results being consistent with increased pathogen exposure. Elevated fecal coliform concentrations in water, and observations of terrestrial spill-over pathogens in local seals, further support the notion of biological pollution at these sites. Although our study highlights the role that environmental contaminants might play in rendering marine mammal populations vulnerable to disease through immunotoxicity, it also suggests that biological pollution represents an emerging conservation concern.

Animals↗

PubMed2000

Factor structure of the College Adjustment Scales.

The present study examined the underlying structure of the College Adjustment Scales via principal components analysis. A correlation matrix of the nine subscales showed significant multicolinearity. A subsequent principal components analysis demonstrated that one factor accounted for 57% of the total variance and that the majority of subscales were moderately correlated with this single factor. The results suggest that the College Adjustment Scales may measure the same underlying construct and that the clinical distinctions implied by subscale scores should be regarded with caution. Conclusions are constrained by sample size and demographic characteristics, but the results suggest the need for further empirical validation of the College Adjustment Scales, which may be useful in college counseling centers.

Adaptation, Psychological↗