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PubMed2003

[Clinical investigation on characteristics of traditional Chinese medical syndrome of hepatocirrhosis].

OBJECTIVE: To explore the characteristics of traditional Chinese medical syndrome (TCM syndrome) of hepatocirrhosis. METHODS: Clinical information from the four diagnosis methods of traditional Chinese medicine (TCM) and related laboratorial indexes were systematically collected from 223 hepatocirrhosis cases, and the multi-statistical methods including systematic cluster analysis, principal component analysis, stepwise discrimination and variance analysis were made with the software SAS 6.11. RESULTS: Multi-analysis showed that there were 3 categories of syndrome characteristics. Type 1 (134 cases): damp heat, blood stasis, deficiency of liver and spleen Qi; Type 2 (62 cases): deficiency of both Qi and Yin with severe deficiency of Qi, heat with severe dampness, blood stasis; Type 3 (27 cases): deficiency of both Qi and Yin with severe deficiency of Yin, stasis and heat or dampness. Analysis of the changes of the related laboratorial indexes among the three types of syndrome showed that Type 1 mainly manifested asthenia syndrome with sthenia syndrome, and its indexes of AST, ALT, GGT levels were markedly higher than those of Type 2 and Type 3, both of which mainly showed sthenia syndrome with asthenia syndrome, and that Type 3 was in active inflammation, deficiency of both Qi and Yin (deficiency of Yin > deficiency of Qi), and its FN, Alb, FV, FVII, PLT, PCT levels were obviously reduced. CONCLUSION: The multi-statistical methods can reveal the characteristics and regularity of TCM syndrome of hepatocirrhosis, and the 3 categories of syndrome characteristics basically conform to clinical manifestations. The result of TCM syndrome distribution and laboratorial indexes infer that damp heat is the pathological basis of hepatocirrhosis, and the degree of liver function disorder and liver damage may be the pathological basis of deficiency of Yin of both liver and kidney.

Adult↗

PubMed2002

Metabonomic assessment of toxicity of 4-fluoroaniline, 3,5-difluoroaniline and 2-fluoro-4-methylaniline to the earthworm Eisenia veneta (Rosa): identification of new endogenous biomarkers.

High-resolution 1H nuclear magnetic resonance (NMR) spectroscopy can be used to produce a biochemical fingerprint of low-molecular-weight metabolites from complex biological mixtures such as tissue extracts and biofluids. Changes in such fingerprint profiles can be used to characterize the effects of toxic insult in in vivo systems. The technique is nonselective and requires little sample preparation or derivatization. In the present study, earthworms (Eisenia veneta) were exposed to three different model xenobiotics by a standard filter paper contact test, and toxicant-induced biochemical changes were then investigated by characterizing the changes in endogenous metabolites visible in 600-MHz 1H NMR spectra of tissue extracts. The NMR spectral intensities were converted to discrete numerical values and tabulated in order to provide data matrices suitable for multivariate analysis. Principal component analysis showed that changes had occurred in the biochemical profiles relative to the undosed controls. The 2-fluoro-4-methylaniline-treated worms showed a decrease in a resonance from a compound identified as 2-hexyl-5-ethyl-3-furansulfonate using a combination of high-performance liquid chromatography (HPLC)-Fourier transform mass spectrometry (IonSpec, Lake Forest, CA, USA) and 1H and 13C NMR spectroscopy. An increase in inosine monophosphate was also observed. The 4-fluoroaniline-treated worms showed a decrease in maltose concentrations, and 3,5-difluoroaniline exerted the same effect as 2-fluoro-4-methylaniline but to a lesser extent. These changes could potentially be used as novel biomarkers of xenobiotic toxicity and could be used to determine the mechanism of action of other toxic chemicals.

Aniline Compounds↗

PubMed2003

[The 'Soarchmjitter'. The use of a Frisian lingual measurement instrument in care of the elderly].

In this article a research has been described funded by the province Fryslân. The aim of this research project is bipartite. First, to determine the reliability and the validity of the instrument and, secondly, to inquire the involved residents living in old people's homes after the valuation of the use of the Frisian language in the care. The research is conducted among 73 residents living in nine old people's homes in the province Fryslân. On two moments in time residents of the old people's homes are asked to fill in a questionnaire with regard to their own care (in)dependency and once with regard to the use of the Frisian language in the care. Reliability analysis shows with regard to internal consistency high Cronbach's alpha values. Test-retest reliability (Cohen's kappa and Spearman Correlation) reveals fair to moderate values. Factor analysis (principal components analysis) results in a one-factor solution. According to the residents, the 'Soarchmjitter' gives a good picture of their care dependency and its questions and answers join their needs. It can be concluded that the 'Soarchmjitter' is a useful instrument to communicate in the own spoken language of the resident and to come in this way to an agreement with nurses about their care demands.

Aged↗

PubMed2004

Evaluation of a simple carrier molecule to enhance drug penetration of dermal layers by utilizing multivariate methods, structure property correlations, and continuous system modeling.

Nicotinic acid is shown to be comparable to dihydropyridine in its capacity to facilitate penetration of an attached antibacterial drug through dermal layers. Antibacterial drugs examined with nicotinic acid or dihydropyridine carriers were beta-lactam antibiotics: methicillin, oxacillin, benzylpenicillin, penicillin F, penicillin dihydro F, propicillin, carbenicillin, penicillin K, penicillin X, and ampicillin. An oxymethyl (-O-CH2-) group is inserted as the linker between the antibiotic and the carrier group. Structure Property Correlations and multivariate methods such as regression analysis, cluster analysis, principal component analysis, discriminate analysis, self-organizing tree algorithm, and factor analysis clearly showed that nicotinic acid performs as an effective carrier drug and is comparable to dihydropyridine. The skin penetration constant Kp was calculated for all 10 antibiotics having either dihydropyridine or nicotinic acid as carrier, and was found to have a mean of 5.13E-05 cm/hour and 1.83E-05 cm/hour, respectively. The standard deviation for each group showed the numerical values overlap as did the 90% confidence interval for each group. A hierarchical tree organization of skin shows the overlapped dermal layers as they exist in normal skin and for the model utilized in this work. A Deming-Regression analysis also shows the nicotinic acid and dihydropyridine structures to have similar and correlated water solubility. Plotting Kp of the dihydropyridine structures as independent variable versus Kp of the nicotinic acid structures show good correlation (Pearson correlation r = 0.6606) and no significant departure from linearity. Connected box plots showed the majority of Kp values for each group of modified antibiotics to exist in a tight cluster. Polar graph of the Log Kow values showed the two groups of modified antibiotics to be correlated and numerically adjacent in trend. ChemSketch property calculations and modeling demonstrates the affects of structural oxygens, nitrogens, carbonyl groups, amide groups, and aromatic rings that are important in understanding the pervasiveness through dermal layers. Continuous model analysis by acslXtreme is utilized and demonstrates three models of the dispersion of drugs through dermal layers based on diffusivity constant (D), Log Kp from Log Kow and formula weight, and Kp as a function of time.

Administration, Topical↗

PubMed1991

Statistical tools in the clinical laboratory.

Method evaluation, control of data and transformation of laboratory results into diagnoses all involve a decision step. A survey of the statistical tools available to organize the information and check the congruity of decision making is provided is focused on: (a) the use of classical statistical tools (including computer based simulation and replication techniques) which enable theoretical distributions to be obtained and their optimal limits to be defined for classification purposes; (b) the analysis of multivariate distributions, which evidences the relationships among the variables involved, whatever they might be: e.g. results obtained on the same specimens with different methods (in test evaluation), different laboratory data related to the same pathophysiological situations (in making diagnoses), etc. As for the latter, the most common techniques of statistical analysis of data (discriminant and cluster analysis, principal components analysis) are also illustrated by general examples.

Analysis of Variance↗

PubMed1988

Applications of multivariate analysis in diagnostic cytology.

Three multivariate methods for structure simplification (cluster analysis, principal component analysis and factor analysis) and three multivariate methods for prediction (discriminant analysis, analysis of variance and regression analysis) are discussed and contrasted, along with basic descriptive statistics for multivariate data. These methods are only a subset of the multivariate methods currently in use, but include those that have thus far been applied in diagnostic cytology. Multivariate analyses provide a basis for describing and analyzing large complex data sets and, with the enormous amounts of data becoming available, their applications in many areas of diagnostic cytology must surely increase.

Cytological Techniques↗

PubMed1987

Multivariate statistical analysis of L-dopa esters as potential anti-parkinsonian prodrugs.

This paper reports a QSAR study of thirteen L-DOPA esters previously synthesised and examined for their physicochemical, biochemical and behavioural properties. Multivariate statistical analysis (principal component analysis, cluster analysis, simple and multiple linear regression) reveals favourable and unfavourable structural features of L-DOPA prodrugs. Some of the many biochemical and behavioural activities investigated are shown to be redundant. These indications may contribute to the design of novel L-DOPA prodrugs.

Analysis of Variance↗

PubMed1980

A multivariate analysis of the infrared spectra of drugs of abuse.

The infrared (IR) spectra of 15 drugs of abuse were analyzed for similarity by using techniques of numerical taxonomy. The study included six barbiturates (amobarbital, barbital, butabarbital, phentobarbital, phenobarbital, and secobarbital), four amphetamine-related compounds (amphetamine, ephedrine, methamphetamine, and phentermine), and five other drugs (cocaine, heroin, phencyclidine, phendimetrazine, and diazepam). Three character sets were based on increasing numbers (10, 24, and 36) of IR peaks. The cluster analysis, principal component analysis, and nonmetric multidimensional scaling elements of the program system NT-SYS were used to structure taxonomic distances between drugs. Best results were obtained from the 36-peak data set; ordination diagrams proved to be more visually informative than phenograms. Preliminary results from our analysis of this set of drugs indicate that an expanded multivariate approach to drug classification may be useful.

Amphetamines↗

PubMed1980

Application of two multi-dimensional analytical methods to histological study of the aorta in dietary atherosclerosis of the rabbit.

Multivariate analysis (principal component analysis, discriminant analysis) have been applied to the histological data of arterial lesions in experimental atherosclerosis of the rabbit. We carried out a comparative study of: 1. the lesion observed at three levels of the aortas; origin of the aorta, thoracic aorta and abdominal aorta, and 2. the lesions according to the type of fat ingested during the experimental period. Five edible fats were studied: butter, olive oil, arachid oil, rapeseed oil rich in erucic acid, and rapeseed oil poor in erucic acid (Primor). This study re-affirms the possible importance of the above mentioned methods in evaluation by histology of lesions induced in the arteries by the different hyperlipidic regimens. Indeed these methods are complementary and enable the introduction of statistical methods in the quantitative evaluation of morphological lesions.

Animals↗

PubMedDate not supplied

Prognostic significance of routine clinical and laboratory data in advanced head and neck cancers.

Predictive factors for toxicity and response to chemotherapy in patients with advanced head and neck cancer are seldom reported. Therefore, from a short series of patients with a histologically proven cancer, who were treated by a neo-adjuvant protocol with cisplatin and fluorouracil, routine clinical and laboratory data were investigated. ALT (alanine aminotransferase) and Hb (hemoglobin) appeared to be predictive for efficacy. By multivariate analysis (principal component analysis), these laboratory data were involved in two independent axes: one which was considered as "inflammatory" and the other as "hepatic". Initial obesity indices were associated with the former. The predictive variables for toxicity (i.e. age, serum creatinine level, weight loss and plasma cisplatin) were probably biased in this series. Nevertheless cisplatin concentration regularly increased in each cycle. Hence it was dependent on the rank of the course. According to this preliminary study, it would be of interest to conduct future investigations on acquired protein-energy malnutrition, as well as on selected soluble mediators of cellular and humoral immune response.

Adult↗

PubMed1997

A diagnostic index of vertical problems for Class III malocclusions.

A cephalometric investigation was undertaken to derive a vertical indicator--a single value derived from a series of cephalometric variables that can be used in the differential diagnosis of Class III patients. The subjects consisted of 76 Japanese female patients whose chief complaint was anterior crossbite and who presented with either open bite or anterior deep overbite. All the data were derived from the initial lateral cephalometric radiographs. The main skeletal measurements that characterize vertical problems were selected using cluster analysis, principal component analysis, and discriminant analysis. As a result, a Class III vertical indicator was derived. The vertical indicator score for deep overbite was -2.5 +/- 2.2, whereas the vertical indicator score for open bite was +2.5 +/- 2.3. This vertical indicator may be used in diagnosing the nature of vertical problems and determining the appropriate treatment and prognosis for the individual Class III female patient.

Adult↗

PubMed1998

FT-IR microspectroscopic imaging of human carcinoma thin sections based on pattern recognition techniques.

FT-IR microspectroscopic maps of unstained thin sections from human melanoma and colon carcinoma tissues were obtained on a conventional infrared microscope equipped with an automatic x, y stage. Mapped infrared data were analyzed by different image re-assembling techniques, namely functional group mapping ("chemical mapping") and, for the first time by cluster analysis, principal component analysis and artificial neural networks. The output values of the different classifiers were recombined with the original spatial information to construct IR-images whose color or gray tones were based on the spatial distribution of individual spectral patterns. While the functional group mapping technique could not reliably differentiate between the different tissue regions, the approach based on pattern recognition yielded images with a high contrast that confirmed standard histopathological techniques. The new technique turned out to be particularly helpful to improve discrimination between different types of tissue structures in general, and to increase image contrast between normal and cancerous regions of a given tissue sample.

Biomarkers, Tumor↗

PubMed2002

Validation of a pediatric voice quality-of-life instrument: the pediatric voice outcome survey.

OBJECTIVE: To validate a parent proxy instrument to study the voice-related quality of life (VR-QOL) for the pediatric population. METHODS: The voice outcome survey (VOS) was administered to 108 caregivers of children aged 2 to 18 years, who either had a tracheotomy or had achieved surgical decannulation. The VOS was altered so that each item was addressed to the parent proxy as opposed to the child. A scoring paradigm was developed to report the scores on a range of 0 to 100. Structural properties of the instrument examined include validity, reliability, and principal component analysis. The VOS was then revised to suit the results of this analysis. RESULTS: The mean +/- SD (range) score for the pediatric VOS was 49.8 +/- 27.1 (0-100). Reliability analysis and principal component analysis supported the reduction of 1 item from the final pediatric VOS. The revised instrument demonstrated an overall Cronbach alpha value of.86. Substratification by age revealed robust Cronbach alpha values from ages 2 to 18 years. Construct validity analysis also supported statistical significance (P =.004). Principal component analysis of the revised instrument supports its internal structure and design. CONCLUSIONS: The pediatric VOS is a simple, short, health status instrument designed to measure the VR-QOL in the pediatric population. Cross-sectional analysis suggests that children and adolescents with tracheotomies have a poorer VR-QOL than do those who have achieved decannulation.

Adolescent↗

PubMed2006

Source apportionment of PM2.5 in urban area of Hong Kong.

A monitoring program for PM(2.5) had been performed at two urban monitoring stations in Hong Kong from November 2000 to February 2001 and June 2001 to August 2001. PM(2.5) samples were collected once every 6 days at PolyU and KT stations with the sampling duration of 24-h. A sum of 25 chemical species in PM(2.5) were determined and selected for receptor models. Enrichment factors relative to earth crust abundances were evaluated and it was noted that most crustal elements including Al, Ti, Mg, Ca and K have small enrichment factors. Correlation and multivariate analysis technique, such as principal components analysis (PCA)/absolute principal components analysis (APCA) and cluster analysis (CA) are used for source apportionment to identify the possible sources of PM(2.5) and to determine their contribution. Six factors at each site were isolated by using PCA/APCA and cluster analysis. Similar sources (crustal matter, automobile emission, diesel emission, secondary aerosols, tire wear, and non-ferrous smelter) are identified by the PCA/APCA and cluster analysis.

Aerosols↗

PubMed2006

Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation.

The multi-yeast strain composition of wine fermentations has been well established. However, the effect of multiple strains of Saccharomyces spp. on wine flavour is unknown. Here, we demonstrate that multiple strains of Saccharomyces grown together in grape juice can affect the profile of aroma compounds that accumulate during fermentation. A metabolic footprint of each yeast in monoculture, mixed cultures or blended wines was derived by gas chromatography - mass spectrometry measurement of volatiles accumulated during fermentation. The resultant ion spectrograms were transformed and compared by principal-component analysis. The principal-component analysis showed that the profiles of compounds present in wines made by mixed-culture fermentation were different from those where yeasts were grown in monoculture fermentation, and these differences could not be produced by blending wines. Blending of monoculture wines to mimic the population composition of mixed-culture wines showed that yeast metabolic interactions could account for these differences. Additionally, the yeast strain contribution of volatiles to a mixed fermentation cannot be predicted by the population of that yeast. This study provides a novel way to measure the population status of wine fermentations by metabolic footprinting.

Culture Media↗

PubMed2004

Protein designability analysis in sequence principal component space using 2D lattice model.

The number of proteins that fold into a certain structure differs drastically. The designability of a protein structure, which is defined as the number of sequences that have that structure as their unique lowest energy state, is studied in this paper using a simplified lattice model. The two-letter (HP) code and the pair-contact energy model are employed in the formulation of the relationship between the protein sequences and the compact structures. Due to the correlations between different dimensions, principal component analysis (PCA) is carried out to remove these correlations and develop reliable approximations of probability density functions of the protein sequences and the compact structures. An estimation of designability is derived using these probability density functions. Good correlation between estimated designabilities and those obtained through enumerative calculations is successfully achieved.

Algorithms↗

PubMed2006

Morphometric analysis of face in dysmorphology.

Dysmorphology refers to study of human congenital malformations (birth defects). Most of the case reporting in dysmorphology is subjective and is based on experience of the reporting clinician. We have used the methods of geometric morphometrics to analyze the variation in faces of normal individuals and those with dysmorphic syndrome. We obtained photographs of 20 individuals with Rubinstein Taybi syndrome and 30 normal, age and sex matched individuals. The photographs were digitized with 16 landmarks on the face to obtain 32 "x" and "y" co-ordinates. These co-ordinates were then subjected to generalized procrustes superimposition in order to normalize for effects of size, rotation and position of image. The procrustes residuals thus obtained were then subjected to principal component analysis. The principal component analysis resulted in extraction of three important principal components explaining 41%, 17% and 14% of variance, respectively. Discriminant analysis could differentiate the two groups using first two principal component scores for each individual, with a predictive accuracy of 76% (Wilks lambda=0.725, chi2=15.09, d.f.=2, p=0.001). Binary logistic regression analysis showed predictive accuracy of 78% based on this model. The utility of the subjective evaluation of facial characteristics is multifold. The results of the analysis can be used as representatives of the facial dysmorphism for any genotype-phenotype association study. We conclude that application of the principles of geometric morphometrics to study of shape variation in facies of patients with dysmorphic syndromes appears to be a promising new area of research.

Adolescent↗

PubMed2006

Use of factor analysis in Journal of Advanced Nursing: literature review.

AIM: This paper reports a review analysing the use of factor analysis in papers in Journal of Advanced Nursing. BACKGROUND: Factor analysis is a multivariate statistical method for reducing large numbers of variables to fewer underlying dimensions. There are several methods of factor analysis with principal components analysis being the most commonly applied. Factor analysis has been used by researchers in nursing for many years but the standards for use and reporting are variable. METHOD: Papers using factor analysis in Journal of Advanced Nursing were retrieved from 1982 to the end of 2004. The search term 'factor analysis' was used in the CINAHL database and applied specifically to Journal of Advanced Nursing in December 2004. Retrieved papers were included in the review if they came from Journal of Advanced Nursing and used factor analysis as part of the method of the reported study. RESULTS: One hundred and twenty-four papers were retrieved as a result of the initial search criteria of which 116 were from Journal of Advanced Nursing. Screening of papers for the use of factor analysis left 100 papers for review. Principal components analysis was the most commonly used method of factor analysis; Eigenvalues greater than one was the most commonly applied criterion for selecting the number of factors followed by orthogonal rotation to achieve simple structure. The majority of papers did not report the whole factor solution and there were papers that did not specify anything beyond the fact that they carried out factor analysis. Confirmatory factor analysis was rarely used and exploratory methods other than principal components analysis were also rarely used. CONCLUSIONS: Factor analysis is quite commonly used in nursing research reported in Journal of Advanced Nursing. While some papers are exemplary there is room for improvement in the reporting of all aspects of factor analysis.

Bibliometrics↗