Distribution of major, minor, and trace metals in lake environments of Antarctica

The concentrations of major, minor and trace metals were measured in water samples collected from five shallow Antarctic lakes (Carezza, Edmonson Point (No 14 and 15a), Inexpressible Island and Tarn Flat) found in Terra Nova Bay (northern Victoria Land, Antarctica) during the Italian Expeditions of 1993-2001. The total concentrations of a large suite of elements (Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Gd, K, La, Li, Mg, Mn, Mo, Na, Nd, Ni, Pb, Pr, Rb, Sc, Si, Sr, Ta, Ti, U, V, Y, W, Zn and Zr) were determined using spectroscopic techniques (ICP-AES, GF-AAS and ICP-MS). The results are similar to those obtained for the freshwater lakes of the Larsemann Hills, East Antarctica, and for the McMurdo Dry Valleys. Principal Component Analysis (PCA) and Cluster Analysis (CA) were performed to identify groups of samples with similar characteristics and to find correlations between the variables. The variability observed within the water samples is closely connected to the sea spray input; hence, it is primarily a consequence of geographical and meteorological factors, such as distance from the ocean and time of year. The trace element levels, in particular those of heavy metals, are very low, suggesting an origin from natural sources rather than from anthropogenic contamination.

Structure of a putative ancestral protein encoded by a single sequence repeat from a multidomain proteinase inhibitor gene from Nicotiana alata

Background: The ornamental tobacco Nicotiana alata produces a series of proteinase inhibitors (Pls) that are derived from a 43 kDa precursor protein, NaProPl. NaProPl contains six highly homologous repeats that fold to generate six separate structural domains, each corresponding to one of the native Pls. An unusual feature of NaProPl is that the structural domains lie across adjacent repeats and that the sixth Pl domain is generated from fragments of the first and sixth repeats. Although the homology of the repeats suggests that they may have arisen from gene duplication, the observed folding does not appear to support this. This study of the solution structure of a single NaProPl repeat (aPl1) forms a basis for unravelling the mechanism by which this protein may have evolved, Results: The three-dimensional structure of aPl1 closely resembles the triple-stranded antiparallel beta sheet observed in each of the native Pls. The five-residue sequence Glu-Glu-Lys-Lys-Asn, which forms the linker between the six structural domains in NaProPl, exists as a disordered loop in aPl1. The presence of this loop in aPl1 results in a loss of the characteristically flat and disc-like topography of the native inhibitors. Conclusions: A single repeat from NaProPl is capable of folding into a compact globular domain that displays native-like Pl activity. Consequently, it is possible that a similar single-domain inhibitor represents the ancestral protein from which NaProPl evolved.

Using biplots to interpret gene expression patterns in plants

Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments. Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact. Contact: scott.chapman@csiro.au.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Progressive dysgraphia in a case of posterior cortical atrophy

Dysgraphia (agraphia) is a common feature of posterior cortical atrophy (PCA). However, detailed analyses of these spelling and writing impairments are infrequently conducted. LM is a 59-year-old woman with dysgraphia associated with PCA. She presented with a two-year history of decline in her writing and dressmaking skills. A 3D T-1-weighted MRI scan confirmed selective bi-parietal atrophy, with relative sparing of the hippocampi and other cortical regions. Analyses of LM's preserved and impaired spelling abilities indicated mild physical letter distortions and a significant spelling deficit characterised by letter substitutions, insertions, omissions, and transpositions that was systematically sensitive to word length while insensitive to real word versus nonword category, word frequency, regularity, imagery, grammatical class and ambiguity. Our findings suggest a primary graphemic buffer disorder underlies LM's spelling errors, possibly originating from disruption to the operation of a fronto-parietal network implicated in verbal working memory.

Limited ecoclinal variation found in Malva parviflora (small-flowered mallow) across the Mediterranean-climatic agricultural region of Western Australia

Malva parviflora L. populations were collected from 24 locations across the Mediterranean-climatic agricultural region of Western Australia and grown in Perth in a common garden experiment. Seventeen morphometric and taxonomic measurements were taken and genetic variation was investigated by performing principal components analysis (PCA). Taxonomic measurements confirmed that all plants used in the study were M. parviflora. Greater variation occurred within populations than between populations. Separation between populations was only evident between northern and southern populations along principal components 2 (PC2), which was due mainly to flowering time. Flowering time and consequently photoperiod were highly correlated with latitude and regression analysis revealed a close relationship (r(2) = 0.6). Additionally, the pollination system of M. parviflora was examined. Plants were able to self-pollinate without the need for external vectors and the pollen ovule ratio (31 +/- 1.3) revealed that M. parviflora is most likely to be an obligate inbreeder with a slight potential for outcrossing. The limited variation of M. parviflora enhances the likelihood of suitable control strategies being effective across a broad area.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

A microbiological study of Papillon-LeFevre syndrome in two patients

Aim-To analyse the microflora of subgingival plaque from patients with Papillon-Lefevre syndrome (PLS), which is a very rare disease characterised by palmar-plantar hyperkeratosis with precocious periodontal destruction. Methods-Bacterial isolates were identified using a combination of commercial identification kits, traditional laboratory tests, and gas liquid chromatography. Some isolates were also subjected to partial 16S rDNA sequencing. Plaque samples were also assayed for the presence of Porphyromonas gingivalis, Prevotella intermedia, and Actinobacillus actinomycetemcomitans in a quantitative enzyme linked immunosorbent assay (ELISA) using monoclonal antibodies. Results-The culture results showed that most isolates were capnophilic and facultatively anaerobic species-mainly Capnocytophaga spp and Streptococcus spp. The latter included S constellatus, S oralis, and S sanguis. Other facultative bacteria belonged to the genera gemella, kingella, leuconostoc, and stomatococcus. The aerobic bacteria isolated were species of neisseria and bacillus. Anaerobic species included Prevotella intermedia, P melaninogenica, and P nigrescens, as well as Peptostreptococcus spp. ELISA detected P gingivalis in one patient in all sites sampled, whereas A actinomycetemcomitans was detected in only one site from the other patient. Prevotella intermedia was present in low numbers. Conclusions-Patients with PLS have a very complex subgingival flora including recognised periodontal pathogens. However, no particular periodontopathogen is invariably associated with PLS.

Aetiology of Papillon LeFevre Syndrome

Papillon LeFevre Syndrome, or PLS, was first described over 70 years ago. It is characterised by severe periodontal disease, typically leading to loss of teeth by adolescence, combined with palmoplantar hyperkeratosis. The fact that it is associated with consanguinity in particular ethnic groups suggests that genotype may contribute to the aetiology of this syndrome. Microbiological studies have been hampered by the rareness of the condition which makes prospective studies virtually impossible to perform. Numerous studies on small groups of patients, sometimes single cases, together suggest an association of recognised periodontal pathogens with PLS. Actinobacillus actinomycetemcomitans has been especially linked to PLS and raised levels of antibody to A.a. have been measured in some PLS patients, though not others. Porphyromonas gingivalis and Prevotella intermedia have also been detected in plaque samples from PLS, using monoclonal antibodies. Many other species have also been associated with PLS following culture and identification, as well as use of probes. Treatment has been attempted by eradication of periodontal pathogens so that teeth can erupt into a 'safe' environment. Successful treatment has needed intensive treatment and monitoring and good oral hygiene as well as thorough antibiotic therapy of patient, family members and even pets. Recently a Cathepsin C genotype has been strongly linked to PLS. However, this gene cannot account for all features of PLS and we can speculate that additional genes must be involved. It is concluded that PLS results from a combination of host and bacterial factors, including recessive human gene(s) associated with consanguinity, specific periodontal pathogens and lack of thorough oral hygiene. It is also believed that the human genetic component may merit examination as a 'host factor' in other bacterial infections. (C) 2001 Academic Press.

Genetic variability in Australian isolates of Puccinia coronata f. sp avenae assessed with molecular and pathogenicity markers

In a preliminary survey of genetic variability among 12 Australian isolates of Puccinia coronata f. sp. avenae Fraser and Led (Pca) collected from 1966 to 1993, two relatively diverse (

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.