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PubMed1994

Application of the exploratory data analysis for evaluating the toxicity of chlorinated phenol derivatives by various cell models.

Exploratory data analysis based on multivariate statistical analysis techniques was introduced as a new approach to expressing the toxicity of chemical substances at the simultaneous acceptance of various cell models. Using principal component analysis and cluster analysis methods the toxicity of chlorinated phenol derivatives on employing some of the cell models (chlorococcal algae, cyanobacteria, bacteria, micromycetes, plant and animal cells) was characterized. The previous empirical experience that the toxicity of chlorinated phenol derivatives will increase with a growing degree of chlorination and that the presence of the methoxy group will cause a lowering of the toxic effect was demonstrated. The relationship between groups of tests used was presented.

Allium↗

PubMedDate not supplied

Mining and visualizing large anticancer drug discovery databases.

In order to find more effective anticancer drugs, the U.S. National Cancer Institute (NCI) screens a large number of compounds in vitro against 60 human cancer cell lines from different organs of origin. About 70,000 compounds have been tested in the program since 1990, and each tested compound can be characterized by a vector (i.e., "fingerprint") of 60 anticancer activity, or -[log(GI50)], values. GI50 is the concentration required to inhibit cell growth by 50% compared with untreated controls. Although cell growth inhibitory activity for a single cell line is not very informative, activity patterns across the 60 cell lines can provide incisive information on the mechanisms of action of screened compounds and also on molecular targets and modulators of activity within the cancer cells. Various statistical and artificial intelligence methods, including principal component analysis, hierarchical cluster analysis, stepwise linear regression, multidimensional scaling, neural network modeling, and genetic function approximation, among others, can be used to analyze this large activity database. Mining the database can provide useful information: (a) for the development of anticancer drugs; (b) for a better understanding of the molecular pharmacology of cancer; and (c) for improvement of the drug discovery process.

Algorithms↗

PubMed1993

Are oppositional and conduct disorders of adolescents separate conditions?

This study explores the factor structure of behaviours that correspond to symptoms of DSM-III-R oppositional defiant (OD) and conduct disorder (CD). It also seeks to clarify how those hypothetical factors may relate to diagnoses of OD and CD. Using exploratory factor analysis and cluster analysis of parent questionnaire data from a group of referred adolescents (N = 528) diagnosed according to DSM-III criteria the authors extracted four factors. One of them corresponded closely to DSM-III-R OD, while the others comprised different aspects of the CD construct. The findings suggest there are subtypes of conduct problems in adolescents, and give some support to the distinction between conduct and oppositional disorders.

Adolescent↗

PubMed2004

The effect of urbanisation on Laajalahti Bay, Helsinki City, as reflected by sediment geochemistry.

Sediment geochemical techniques were used to assess how the sediment record reflects the loading and land use history of Laajalahti Bay, a semi-enclosed bay adjacent to the city of Helsinki, Finland. A dated sediment core was analysed for concentrations of Al, Ca, K, Mg, Na, Fe, Mn, Cu and Zn and total concentrations of C, N and P together with P fractions and biogenic silica (BSi) at intervals of 1 cm to a depth of 88 cm. Furthermore, five phases of development were identified in the sediment record by using principal components analysis and cluster analysis. The lithology of the core indicates sharp changes in the sedimentation environment in the earlier history of the embayment that are most likely due to isostatic uplift and changes in salinity. The most prominent recent trends were the increasing sedimentation rates and nutrient concentrations towards present. In addition, significant increases were observed in the concentrations of anthropogenic indicators Cu and Zn. In spite of decreased nutrient loading to Laajalahti Bay no significant signs of improvement were observed in the sediment record yet.

Cluster Analysis↗

PubMed1997

Is neural network better than statistical methods in diagnosis of acute appendicitis?

Three statistical classification methods: discriminant analysis, logistic regression analysis and cluster analysis were compared with the back-propagation neural network algorithm in the diagnosis of acute appendicitis. The differences in the classification accuracy, which were evaluated with the receiver operating characteristic (ROC) curve were small, though discriminant analysis and back-propagation showed slightly better results than the other methods. The agreement of the methods on the diagnosis increased the accuracy of the classification, so that the number of misclassified cases reduced. The back-propagation neural network offers a good choice for statistical classification methods, but it was not found to be better than them. The use of several methods and their agreement as the basis of the diagnosis seems to give the best results for this diagnostic classification problem.

Appendicitis↗

PubMed2003

A reassessment of living hominoid postcranial variability: implications for ape evolution.

In an analysis of hominoid postcranial variation, 'Evol. Anthrop. 6 (1998) 87' argued that many purportedly unique features of the hominoid postcranium are actually much more variable than previously reported and in many instances overlap with both suspensory (Ateles) and non-suspensory primates. Based on these results, it was concluded that parallelism in the living ape postcranium was a plausible and even likely possibility given the Miocene hominoid postcranial record. However, this analysis did not distinguish whether within-hominoid variability or overlap with non-hominoids involved one or all ape taxa, a distinction which has potentially important effects on the interpretation of results. To address this issue, primate postcranial morphometric data from the trunk and forelimb were reanalyzed using three techniques: cladistic analysis, principle components analysis, and cluster analysis. Results reveal that these postcranial characters distinguish not only suspensory and quadrupedal primates but also discriminate hominoids and Ateles from all other taxa, great apes from lesser apes and Ateles, cercopithecines from colobines, and cercopithecoids from platyrrhines. The majority of hominoid variability and overlap with Ateles occurs with Hylobates humeral head and shoulder joint characters related to brachiation. This suggests that Hylobates' specializations may skew analyses of hominoid postcranial uniqueness and variability, and that great apes are relatively similar in their postcranium.

Anatomy, Comparative↗

PubMed1996

Size and location of the human temporomandibular joint.

The literature abounds with conflicting data on various morphometric aspects of the temporomandibular joint (TMJ). The purpose of this study was to observe the effects of sex, ethnic group, and edentulism on TMJ osseous morphology and to define possible factors which might influence variation in this structure. TMJs and related craniofacial structures were measured directly on 229 dry skulls and matching mandibles. Analysis of variance, principal component analysis, and cluster analysis were performed. Our results indicate that 1) the anteroposterior-related TMJ dimensions are independent of sex, ethnic group, and edentulism; 2) the transverse TMJ dimension is related to cranial breadth measures; and 3) the projected distance, along a midsagittal plane, between the TMJ and foramen magnum is independent of sex, ethnicity, and edentulism. It is our assertion that the TMJ must not be considered as a single morphological structure but rather viewed as a functional unit with component parts which are subordinate to completely different sets of influences.

Africa↗

PubMed2005

Application of TOF-SIMS with chemometrics to discriminate between four different yeast strains from the species Candida glabrata and Saccharomyces cerevisiae.

We present a TOF-SIMS analysis of the cell surface differences between four yeast strains from two species, Candida glabrata and Saccharomyces cerevisiae (haploid strains BY4742 and BY4741 and the derived diploid BY4743). The study assesses the suitability of TOF-SIMS analysis in combination with statistical methods (principal component analysis, Fisher's discriminant analysis, and cluster analysis) for the discrimination between the four yeast strains. We demonstrate that a combination of these statistical methods identifies 34 ions, from a total data set of 1200, which can be used to distinguish between the four yeasts. The study discusses the assignments of surface cell membrane phospholipids for the identified ions and the resulting differences in the phospholipid pattern between the four yeasts, particularly in relation to ploidy and budding pattern. The method shows that fatty acids, phosphatidylglycerols, phosphatidylethanolamines, phosphatidylserines, and phosphatidylcholines, as well as cardiolipins, are of diagnostic importance.

Candida glabrata↗

PubMed1999

An exploratory attempt to distinguish subgroups among crack-abusing African-American women.

Despite the significant emergence of research on female addiction over the last two decades, specific research on African-American women substance abusers, particularly crack cocaine users, is limited. The identification of meaningful subgroups of substance abusing populations, particularly minority women is important both clinically, and because of their over-representation in the epidemiological data on crack cocaine use in many urban centers across this country. An extensive battery of instruments was administered to 110 women entering treatment in an intensive outpatient substance abuse treatment program in Philadelphia, serving women who are primarily indigent, African-American, and whose primary substance of abuse is crack cocaine. Factor analysis and cluster analysis procedures were utilized to classify women into subgroups across relevant clinical, behavioral, and background concerns relevant to studying substance abusing populations. Five conceptually meaningful subgroups emerged which classified women across various indicators such as HIV sex risk factors, personality traits/Axis II dimensions, clinical syndromes, psychological symptomatology, lifetime and recent drug and alcohol use, prior physical and sexual abuse, and social context variables such as parental addiction, and whether they live with a substance abuser. Attempts to classify women into identifiable clinical subtypes is essential in order to better inform treatment initiatives designed to serve this group, as well as prevention and community outreach intervention strategies which attempt to bring them into treatment.

Adult↗

PubMed1998

[Classification of measles control situation in different areas of China].

Based on initial description of measles epidemiology, principal component analysis and cluster analysis were applied to analyze the epidemiological pattern of measles in China. Several indicators of socioeconomic status, epidemiological characteristics of measles, as well as status of EPI performance were selected as creteria for classification. It was demonstrated that four groups could be identified as undercontrol, moderate, less advanced and poor areas in terms of the status of measles controlled program. Different strategies were recommanded for different groups. For the undercontrol areas, establishment of measles surveillance system should be prioritized. For the moderate epidemic areas, supplemental immunization should be considered while measles surveillance system is initiated. In the less advanced areas, supplemental immunization and strengthening outbreak response activities should be considered. For poor areas, routine measles immunization needs further improvement to reduce outbreaks.

Adolescent↗

PubMed1994

Quantitative modeling and biology: the multivariate approach.

Even though elegant examples of mathematical modeling of biological problems exist, such approaches still remain outside the domain of most biologists. It is proposed that, for a wider and more systematic use of mathematical models in biology, the soft modeling approaches, which are applicable to phenomena with a limited level of definition, should be investigated and preferred. In particular, multivariate data analysis (MDA) is indicated as an important tool toward fulfilling this goal. This paper reviews the general principles of MDA and examines in detail principal component analysis and cluster analysis, which are two of the most important MDA techniques. A number of applications to real biological problems are presented. These examples show how the construction of classifications corresponds to the generation of new knowledge and new concepts, which are hierarchically on a higher level than the initial information. This new form of knowledge is obtained without superimposing a priori theories on the data. It is demonstrated how the MDA can lead to the identification of biological systems; also shown is their ability to describe multiple scale phenomena, a typical feature of biological systems. Moreover, the multivariate analyses provide new descriptors for a given biological system; these descriptors are quantitative, thus allowing the system to be described in a "metric space," where it then becomes possible to use any other mathematical tool.

Animals↗

PubMedDate not supplied

[Social inequalities in health in the city of Málaga].

Social inequalities and health inequalities are closely related, and their reduction is the goal of international organizations and governments as well. In order to better understand the territorial distribution of social inequalities in the city of Málaga (Spain) and compare them with measured health differences, a descriptive study was done using different sources of information. Using the city's neighbourhoods as the unit of analysis, a cluster analysis was carried out based on a set of demographic, socioeconomic and standard of living indicators. This led to the configuration of six social areas within the city. In these areas, as defined by socially homogeneous criteria, diverse health indicators have been measured, leading the verification of important health differences among them. For example, clear differences in mortality rates between Area IV (socioeconomically deprived) and Area III (with a higher standard of living) are observed: the ratio between their respective "years of potential life lost" was 1.79, and between standardized mortality rates, 1.42. A similar disadvantage in low birth weight was confirmed notably so in adolescent pregnancies (five times higher). In conclusion, those areas of the city with a lower socio-economic status also had the lowest health levels.

Cluster Analysis↗

PubMed2005

Spatial variations in selected metal contents and particle size distribution in an urban and rural atmosphere of Islamabad, Pakistan.

Spatial variations in total suspended particulate matter (TSP) were investigated for distribution of metals and particle size fractions in the urban and rural atmosphere of Islamabad, Pakistan. The metals Na, K, Fe, Mn, Pb, Cd, Cr, Zn, Ni and Co, and the particle fractions <2.5, 2.5-10, 10-100 and >100 microm were included in the study. TSP samples were trapped on glass fibre filters using high volume samplers and quantification of metals was done using Atomic Absorption Spectrometry employing HNO(3) based wet digestion. At the urban site, Na was dominant at 2.384 microg/m(3) followed by K, Fe and Zn with 0.778, 0.667 and 0.567 microg/m(3) as mean concentrations, respectively. The metal levels for the rural site ranged from 0.002 microg/m(3) for Cd to 1.077 microg/m(3) for Na. However, compared with the urban site, mean Pb concentration showed an almost two-fold enhancement, i.e., 0.163 Vs. 0.327 microg/m(3). Metals and particle size source identification was done using Principal Component Analysis and Cluster Analysis. Five sources were traced out for the urban site: industrial, soil, automobile emissions, metallurgical industries and excavation activities. For the rural site, four sources were recorded: agricultural, automotive emissions, excavation activities and metallurgical units. Collectively, for both the sites, PM(10-100) emerged as a major contributor to TSP, followed by PM(2.5-10), PM(<2.5) and PM(>100) in that order. The metals showed in general positive relationship with fine particulate fractions (PM(2.5-10), PM(<2.5)), and negative correlation with coarse fractions (PM(10-100), PM(>100)). Comparison with the corresponding data from various Asian sites revealed that the levels of Na, K, Fe, Mn, Co and Ni for the present study were lower than those reported for grossly polluted cities of the world.

Agriculture↗

PubMed2003

Genetic diversity of a germplasm collection of Cucurbita pepo using SRAP and AFLP markers.

Cucurbita pepo is a highly polymorphic species. The cultivars can be grouped into eight morphotypes in two subspecies, ssp. pepo and ssp. ovifera. A collection of 69 accessions representative of the morphotypes and some unclassified types was used for analysing the morphological and molecular diversity of this species. This collection includes commercial cultivars and Spanish landraces, which represent the great diversification of types that have arisen in Europe after this species arrived from America. For the molecular variability studies, two PCR-based systems were employed, AFLP and SRAP, which preferentially amplify ORFs. Principal coordinates analysis and cluster analysis using the UPGMA method clearly separate the accessions into the two subspecies through the use of both markers. However, the gene diversity and the genetic identity values among morphotypes and subspecies varied between the two marker systems. The information given by SRAP markers was more concordant to the morphological variability and to the evolutionary history of the morphotypes than that of AFLP markers. In ssp. ovifera, the accessions of the different morphotypes were basically grouped according to the fruit colour. This may indicate different times of development and also the extent of breeding in the accessions used. This study has allowed identification of new types that can be employed for the development of new cultivars. The landraces of the spp. ovifera, used as ornamental in Europe, have proved to be of great interest for preserving the diversity of C. pepo.

Cluster Analysis↗

PubMed2004

Relationship between stimulus complexity and neuronal activity in the inferotemporal cortex of the macaque monkey.

The single-unit activity of 217 cells was recorded from the inferotemporal cortex (IT) of two awake macaque monkeys while they performed a fixation task. The stimuli were coloured geometrical shapes or coloured representations of natural or artificial objects. To determine whether the stimuli could be separated into groups on the basis on neuronal population behaviour, the responses to the images were analysed by factor analysis and cluster analysis. It was a common result of each analysis that, on the basis of neuronal responses, the stimulus set could be separated into two groups, despite the lack of difference in mean response rate to them. Similar groups were formed when only the first half of the responses was analysed. The results suggest a differential coding of the images of simple geometrical shapes and of the images of complex, real (photographic) objects. We found significant differences between the two stimulus groups in physical features, other than size or luminance. Our results suggest that the same neurone population might respond differently to simple and complex images in the first 150 ms of their responses. The differences might be attributed to "non-obvious" physical features of the stimuli, such as the amount of internal lines in the images, colourfulness and the length of perimeter of the stimuli.

Action Potentials↗

PubMed2005

Distribution patterns of particulate trace metals in the water column and nepheloid layer of the Gulf of Riga.

The dynamics (fate) of trace metals in suspended particulate matter within the Gulf of Riga has not yet been adequately addressed in the scientific literature. Therefore, during a two year period (2001-2002) samples of suspended particulate matter and surface sediments for trace metal analysis were collected in the Gulf of Riga and the Daugava river, and these data were combined with background information from the national marine monitoring program in Latvia. This paper presents a descriptive study of solid phase trace metals (aluminium, iron, cadmium, chromium, copper, manganese, nickel, lead and zinc) dynamics and their spatial distribution within the Gulf of Riga based on Principal Component Analysis and Cluster analysis. Fluvial particulate matter and particulate Al, Fe, Cr and Ni were brought into the Gulf of Riga mainly during spring flood and thereafter quickly diluted by the water masses of the Gulf of Riga. Fine-grained suspended material and particulate Al and Fe were well mixed and evenly distributed through all deepwater basins of the Gulf of Riga. The increase of particulate Mn below the thermocline in August and a strong negative correlation with dissolved oxygen concentrations suggested that particulate Mn in the water column and the sediments were regulated mainly by changing oxic-anoxic conditions in the sediments of the Gulf of Riga. The observed correlation between Al and Fe in the water column is in contrast to that observed in the nepheloid layer where Fe correlated with Mn, obviously due to fast diagenetic processes on sediment surface. The observed negative correlation of Cd and Zn with total carbon and total nitrogen in the nepheloid layer might indicate different sedimentation mechanisms of these elements, however, this assumption is still inconclusive.

Carbon↗

PubMed2003

An objective definition of air mass types affecting Athens, Greece; the corresponding atmospheric pressure patterns and air pollution levels.

This work aims at defining characteristic air mass types that dominate in the region of Athens, Greece during the cold (November-March) and the warm (May-September) period of the year and also at evaluating the corresponding concentration levels of the main air pollutants. For each air mass type, the mean atmospheric pressure distribution (composite maps) over Europe and the Mediterranean is estimated in order to reveal the association of atmospheric circulation with air pollution levels in Athens. The data basis for this work consists of daily values of thirteen meteorological and six pollutant parameters covering the period 1993-97. The definition of the characteristic air mass types is attempted objectively by using the methods of Factor Analysis and Cluster Analysis. The results show that during the cold period of the year there are six prevailing air mass types (at least 3% of the total number of days) and six infrequent ones. The examination of the corresponding air pollution concentration levels shows that the primary air pollutants appear with increased concentrations when light or southerly winds prevail. This is usually the case when a high pressure system is located over the central Mediterranean or a low pressure system lays over south Italy, respectively. Low levels of the primary pollutants are recorded under northeasterly winds, mainly caused by a high pressure system over Ukraine. During the warm period of the year, the southwestern Asia thermal low and the subtropical anticyclone of the Atlantic Ocean affect Greece. Though these synoptic systems cause almost stagnant conditions, four main air mass types are dominant and ten others, associated with extreme weather, are infrequent. Despite the large amounts of total solar radiation characterizing this period, ozone concentrations remain at low levels in central Athens because of its destruction by nitric oxide.

Air Movements↗

PubMed2005

Water and food consumption patterns of U.S. adults from 1999 to 2001.

OBJECTIVE: High water consumption has been proposed as an aid to weight control and as a means of reducing the energy density of the diet. This study examines the relationship between water consumption and other drinking and eating patterns. RESEARCH METHODS AND PROCEDURES: The National Health and Nutrition Examination Survey 1999 to 2001, with responses from 4755 individuals > or =18 years of age, provides the data for this cross-sectional analysis. A cluster analysis was performed using z-scores of specific food and beverage consumption to examine patterns. A multinomial logit analysis was used to examine sociodemographic characteristics of each dietary pattern and to examine the effects of water consumption on the likelihood of consuming a non-dairy caloric beverage. All results were weighted to be nationally representative and controlled for design effects. RESULTS: Within the sample, 87% consumed water, with an average daily consumption of 51.9 oz (1.53 liters) per consumer. Water consumers drank fewer soft/fruit drinks and consumed 194 fewer calories per day. Water consumers (potentially a self-selected sample) consumed more fruits, vegetables, and low- and medium-fat dairy products. Four distinct unhealthy dietary patterns were found that included little or no water consumption. Older and more educated persons used healthier food patterns. Mexican dietary patterns were much healthier than dietary patterns of blacks. DISCUSSION: Water consumption potentially is a dietary component to be promoted, but much more must be understood about its role in a healthy diet. Because high water consumption is linked with healthier eating patterns-patterns more likely to be followed by higher-educated, older adults-the target of water promotion and healthy diet options should focus on younger and less educated adults.

Adult↗