Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Rainwater major and trace element contents in Southeastern Brazil: an assessment of a sugar cane region in dry and wet period

The purpose of this study was to assess the composition of the rainwater in Araraquara City, Brazil, a region strongly influenced by pre-harvest burning of sugar cane crops. Chemical and mineralogical variables were measured in rainwater collected during the harvest, dry period of 2009 and the non-harvest, wet period of 2010. Ca2+ and NH4+ were responsible for 55% of cations and NO3- for 45% of anions in rainwater. Al and Fe along with K were the most abundant among trace elements in both soluble and insoluble fractions. High volume weighted mean concentration (VWM) for most of the analyzed species were observed in the harvest, dry period, mainly due to agricultural activities and meteorological conditions. The chemistry of the Araraquara rainwater and principal component analysis (PCA) quantification clearly indicate the concurrence of a diversity of sources from natural to anthropogenic especially related to agricultural activities.

Comparative analysis of shell occupation by two southern populations of the hermit crab Loxopagurus loxochelis (Decapoda, Diogenidae)

The present study aimed to comparatively verify the relation between the hermit crabs and the shells they use in two populations of Loxopagurus loxochelis. Samples were collected monthly from July 2002 to June 2003, at Caraguatatuba and Ubatuba Bay, São Paulo, Brazil. The animals sampled had their sex identified, were weighed and measured; their shells were identified, measured and weighed, and their internal volume determined. To relate the hermit crab's characteristics and the shells' variables, principal component analysis (PCA) and a regression tree were used. According to the PCA analysis, the three gastropod shells most frequently used by L. loxochelis varied in size. The regression tree successfully explained the relationship between the hermit crab's characteristics and the internal volume of the inhabited shell. It can be inferred that the relationship between the morphometry of an individual hermit crab and its shell is not straightforward and it is impossible to explain only on the basis of direct correlations between the body's and the shell's attributes. Several factors (such as the morphometry and the availability of the shell, environmental conditions and inter- and intraspecific competition) interact and seem to be taken into consideration by the hermit crabs when they choose a shell, resulting in the diversified pattern of shell occupancy shown here and elsewhere.

Pair approximation for a model of vertical and horizontal transmission of parasites.

We apply Stochastic Dynamics method for a differential equations model, proposed by Marc Lipsitch and collaborators (Proc. R. Soc. Lond. B 260, 321, 1995), for which the transmission dynamics of parasites occurs from a parent to its offspring (vertical transmission), and by contact with infected host (horizontal transmission). Herpes, Hepatitis and AIDS are examples of diseases for which both horizontal and vertical transmission occur simultaneously during the virus spreading. Understanding the role of each type of transmission in the infection prevalence on a susceptible host population may provide some information about the factors that contribute for the eradication and/or control of those diseases. We present a pair mean-field approximation obtained from the master equation of the model. The pair approximation is formed by the differential equations of the susceptible and infected population densities and the differential equations of pairs that contribute to the former ones. In terms of the model parameters, we obtain the conditions that lead to the disease eradication, and set up the phase diagram based on the local stability analysis of fixed points. We also perform Monte Carlo simulations of the model on complete graphs and Erdös-Rényi graphs in order to investigate the influence of population size and neighborhood on the previous mean-field results; by this way, we also expect to evaluate the contribution of vertical and horizontal transmission on the elimination of parasite. Pair Approximation for a Model of Vertical and Horizontal Transmission of Parasites.

Ornithodoros guaporensis (Acari, Ixodida: Argasidae), a new tick species from the Guaporé River Basin in the Bolivian Amazon

The soft tick Ornithodoros guaporensis n. sp. (Acari: Ixodida: Argasidae) is described from larvae and adults. Morphological analysis and 16S rDNA sequences are provided. Adults were collected from a rocky fissure inhabited by bats located in the Amazonian forest in north-eastern Bolivia (Beni Department) close to the Guaporé River. Larvae were obtained from eggs laid by females collected in the field, and which were fed on rabbits in the laboratory. Larvae of O. guaporensis are morphologically closely related to Ornithodoros rioplatensis, Ornithodoros puertoricensis and Orni-thodoros talaje. Larvae of O. guaporensis and O. rioplatensis can be separated from O. puertoricensis and O. talaje by the number of pairs of dorsal setae (20 in O. guaporensis and O. rioplatensis, 18 in O. puertoricensis and 17 in O. talaje). Larvae of O. guaporensis and O. rioplatensis can be differentiated by the medial dental formula (2/2 in O. guaporensis and 3/3 in O. rioplatensis) and the apex of the hypostome, which is more pointed in O. rioplatensis than in O. guaporensis. The Principal Component Analysis performed with morphometric characters of larvae showed a clear separation among O. guaporensis, O. rioplatensis, O. puertoricensis and O. talaje. Significant morphological differences among adults of these four species were not found. The analysis of the 16S rDNA sequences allowed for the differentiation between O. guaporensis and the remaining Neotropical species of the family Argasidae.

Computational methods for genome screening

Motivation An actual issue of great interest, both under a theoretical and an applicative perspective, is the analysis of biological sequences for disclosing the information that they encode. The development of new technologies for genome sequencing in the last years, opened new fundamental problems since huge amounts of biological data still deserve an interpretation. Indeed, the sequencing is only the first step of the genome annotation process that consists in the assignment of biological information to each sequence. Hence given the large amount of available data, in silico methods became useful and necessary in order to extract relevant information from sequences. The availability of data from Genome Projects gave rise to new strategies for tackling the basic problems of computational biology such as the determination of the tridimensional structures of proteins, their biological function and their reciprocal interactions. Results The aim of this work has been the implementation of predictive methods that allow the extraction of information on the properties of genomes and proteins starting from the nucleotide and aminoacidic sequences, by taking advantage of the information provided by the comparison of the genome sequences from different species. In the first part of the work a comprehensive large scale genome comparison of 599 organisms is described. 2,6 million of sequences coming from 551 prokaryotic and 48 eukaryotic genomes were aligned and clustered on the basis of their sequence identity. This procedure led to the identification of classes of proteins that are peculiar to the different groups of organisms. Moreover the adopted similarity threshold produced clusters that are homogeneous on the structural point of view and that can be used for structural annotation of uncharacterized sequences. The second part of the work focuses on the characterization of thermostable proteins and on the development of tools able to predict the thermostability of a protein starting from its sequence. By means of Principal Component Analysis the codon composition of a non redundant database comprising 116 prokaryotic genomes has been analyzed and it has been showed that a cross genomic approach can allow the extraction of common determinants of thermostability at the genome level, leading to an overall accuracy in discriminating thermophilic coding sequences equal to 95%. This result outperform those obtained in previous studies. Moreover, we investigated the effect of multiple mutations on protein thermostability. This issue is of great importance in the field of protein engineering, since thermostable proteins are generally more suitable than their mesostable counterparts in technological applications. A Support Vector Machine based method has been trained to predict if a set of mutations can enhance the thermostability of a given protein sequence. The developed predictor achieves 88% accuracy.

Monte-Carlo-Simulationen zum Phasenverhalten binärer Polymerbürsten

Diese Arbeit beschäftigt sich mit Strukturbildung im schlechten Lösungsmittel bei ein- und zweikomponentigen Polymerbürsten, bei denen Polymerketten durch Pfropfung am Substrat verankert sind. Solche Systeme zeigen laterale Strukturbildungen, aus denen sich interessante Anwendungen ergeben. Die Bewegung der Polymere erfolgt durch Monte Carlo-Simulationen im Kontinuum, die auf CBMC-Algorithmen sowie lokalen Monomerverschiebungen basieren. Eine neu entwickelte Variante des CBMC-Algorithmus erlaubt die Bewegung innerer Kettenteile, da der bisherige Algorithmus die Monomere in Nähe des Pfropfmonomers nicht gut relaxiert. Zur Untersuchung des Phasenverhaltens werden mehrere Analysemethoden entwickelt und angepasst: Dazu gehören die Minkowski-Maße zur Strukturuntersuchung binären Bürsten und die Pfropfkorrelationen zur Untersuchung des Einflusses von Pfropfmustern. Bei einkomponentigen Bürsten tritt die Strukturbildung nur beim schwach gepfropften System auf, dichte Pfropfungen führen zu geschlossenen Bürsten ohne laterale Struktur. Für den graduellen Übergang zwischen geschlossener und aufgerissener Bürste wird ein Temperaturbereich bestimmt, in dem der Übergang stattfindet. Der Einfluss des Pfropfmusters (Störung der Ausbildung einer langreichweitigen Ordnung) auf die Bürstenkonfiguration wird mit den Pfropfkorrelationen ausgewertet. Bei unregelmäßiger Pfropfung sind die gebildeten Strukturen größer als bei regelmäßiger Pfropfung und auch stabiler gegen höhere Temperaturen. Bei binären Systemen bilden sich Strukturen auch bei dichter Pfropfung aus. Zu den Parametern Temperatur, Pfropfdichte und Pfropfmuster kommt die Zusammensetzung der beiden Komponenten hinzu. So sind weitere Strukturen möglich, bei gleicher Häufigkeit der beiden Komponenten bilden sich streifenförmige, lamellare Muster, bei ungleicher Häufigkeit formt die Minoritätskomponente Cluster, die in der Majoritätskomponente eingebettet sind. Selbst bei gleichmäßig gepfropften Systemen bildet sich keine langreichweitige Ordnung aus. Auch bei binären Bürsten hat das Pfropfmuster großen Einfluss auf die Strukturbildung. Unregelmäßige Pfropfmuster führen schon bei höheren Temperaturen zur Trennung der Komponenten, die gebildeten Strukturen sind aber ungleichmäßiger und etwas größer als bei gleichmäßig gepfropften Systemen. Im Gegensatz zur self consistent field-Theorie berücksichtigen die Simulationen Fluktuationen in der Pfropfung und zeigen daher bessere Übereinstimmungen mit dem Experiment.

An Analysis of Living Conditions in Rural Villages in China. A New Geography of the Country.

Analysts, politicians and international players from all over the world look at China as one of the most powerful countries on the international scenario, and as a country whose economic development can significantly impact on the economies of the rest of the world. However many aspects of this country have still to be investigated. First the still fundamental role played by Chinese rural areas for the general development of the country from a political, economic and social point of view. In particular, the way in which the rural areas have influenced the social stability of the whole country has been widely discussed due to their strict relationship with the urban areas where most people from the countryside emigrate searching for a job and a better life. In recent years many studies have mostly focused on the urbanization phenomenon with little interest in the living conditions in rural areas and in the deep changes which have occurred in some, mainly agricultural provinces. An analysis of the level of infrastructure is one of the main aspects which highlights the principal differences in terms of living conditions between rural and urban areas. In this thesis, I first carried out the analysis through the multivariate statistics approach (Principal Component Analysis and Cluster Analysis) in order to define the new map of rural areas based on the analysis of living conditions. In the second part I elaborated an index (Living Conditions Index) through the Fuzzy Expert/Inference System. Finally I compared this index (LCI) to the results obtained from the cluster analysis drawing geographic maps. The data source is the second national agricultural census of China carried out in 2006. In particular, I analysed the data refer to villages but aggregated at province level.

Meta-analyses qualify metzincins and related genes as acute rejection markers in renal transplant patients

Definition of acute renal allograft rejection (AR) markers remains clinically relevant. Features of T-cell-mediated AR are tubulointerstitial and vascular inflammation associated with excessive extracellular matrix (ECM) remodeling, regulated by metzincins, including matrix metalloproteases (MMP). Our study focused on expression of metzincins (METS), and metzincins and related genes (MARGS) in renal allograft biopsies using four independent microarray data sets. Our own cases included normal histology (N, n = 20), borderline changes (BL, n = 4), AR (n = 10) and AR + IF/TA (n = 7). MARGS enriched in all data sets were further examined on mRNA and/or protein level in additional patients. METS and MARGS differentiated AR from BL, AR + IF/TA and N in a principal component analysis. Their expression changes correlated to Banff t- and i-scores. Two AR classifiers, based on METS (including MMP7, TIMP1), or on MARGS were established in our own and validated in the three additional data sets. Thirteen MARGS were significantly enriched in AR patients of all data sets comprising MMP7, -9, TIMP1, -2, thrombospondin2 (THBS2) and fibrillin1. RT-PCR using microdissected glomeruli/tubuli confirmed MMP7, -9 and THBS2 microarray results; immunohistochemistry showed augmentation of MMP2, -9 and TIMP1 in AR. TIMP1 and THBS2 were enriched in AR patient serum. Therefore, differentially expressed METS and MARGS especially TIMP1, MMP7/-9 represent potential molecular AR markers.

Proteome analysis in cardiovascular pathophysiology using Dahl rat model

Dahl salt-sensitive (DS) and salt-resistant (DR) inbred rat strains represent a well established animal model for cardiovascular research. Upon prolonged administration of high-salt-containing diet, DS rats develop systemic hypertension, and as a consequence they develop left ventricular hypertrophy, followed by heart failure. The aim of this work was to explore whether this animal model is suitable to identify biomarkers that characterize defined stages of cardiac pathophysiological conditions. The work had to be performed in two stages: in the first part proteomic differences that are attributable to the two separate rat lines (DS and DR) had to be established, and in the second part the process of development of heart failure due to feeding the rats with high-salt-containing diet has to be monitored. This work describes the results of the first stage, with the outcome of protein expression profiles of left ventricular tissues of DS and DR rats kept under low salt diet. Substantial extent of quantitative and qualitative expression differences between both strains of Dahl rats in heart tissue was detected. Using Principal Component Analysis, Linear Discriminant Analysis and other statistical means we have established sets of differentially expressed proteins, candidates for further molecular analysis of the heart failure mechanisms.

Exploring High-resolution Magic Angle Spinning (HR-MAS) NMR Spectroscopy for Metabonomic Analysis of Apples

Classical liquid-state high-resolution (HR) NMR spectroscopy has proved a powerful tool in the metabonomic analysis of liquid food samples like fruit juices. In this paper the application of (1)H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy to apple tissue is presented probing its potential for metabonomic studies. The (1)H HR-MAS NMR spectra are discussed in terms of the chemical composition of apple tissue and compared to liquid-state NMR spectra of apple juice. Differences indicate that specific metabolic changes are induced by juice preparation. The feasibility of HR-MAS NMR-based multivariate analysis is demonstrated by a study distinguishing three different apple cultivars by principal component analysis (PCA). Preliminary results are shown from subsequent studies comparing three different cultivation methods by means of PCA and partial least squares discriminant analysis (PLS-DA) of the HR-MAS NMR data. The compounds responsible for discriminating organically grown apples are discussed. Finally, an outlook of our ongoing work is given including a longitudinal study on apples.

Bulk Metallic Glasses Deform via Slip Avalanches

For the first time in metallic glasses, we extract both the exponents and scaling functions that describe the nature, statistics, and dynamics of slip events during slow deformation, according to a simple mean field model. We model the slips as avalanches of rearrangements of atoms in coupled shear transformation zones (STZs). Using high temporal resolution measurements, we find the predicted, different statistics and dynamics for small and large slips thereby excluding self-organized criticality. The agreement between model and data across numerous independent measures provides evidence for slip avalanches of STZs as the elementary mechanism of inhomogeneous deformation in metallic glasses.

Numerical study on the curling and warping of hardened rigid pavement slabs

In-service hardened concrete pavement suffers from environmental loadings caused by curling and warping of the slab. Traditionally, these loadings are computed on the basis of treating the slab as an elastic material, and of evaluating separately the curling and warping components. This dissertation simulates temperature distribution and moisture distribution through the slabs by use of a developed numerical model that couples the heat transfer and moisture transport. The computation of environmental loadings treats the slab as an elastic-viscous material, which considers the relaxation behavior and Pickett effect of the concrete. The heat transfer model considers the impacts of solar radiation, wind speed, air temperature, pavement slab albedo, etc. on the pavement temperature distribution. This dissertation assesses the difference between documented models that aim to predict pavement temperature, highlighting their pros and cons. The moisture transport model is unique for the documented models; it mimics the wetting and drying events occurring at the slab surface. These events are estimated by a proposed statistical algorithm, which is verified by field rainfall data. Analysis of the predicted results examines on the roles of the local air RH (relative humidity), wind speed, rainy pattern in the moisture distribution through the slab. The findings reveal that seasonal air RH plays a decisive role on the slab‘s moisture distribution; but wind speed and its daily variation, daily RH variation, and seasonal rainfall pattern plays only a secondary role. This dissertation sheds light on the computation of environmental loadings that in-service pavement slabs suffer from. Analysis of the computed stresses centers on the stress relaxation near the surface, stress evolution after the curing ends, and the impact of construction season on the stress‘s magnitude. An unexpected finding is that the total environmental loadings at the cyclically-stable state divert from the thermal stresses. At such a state, the total stress at the daytime is roughly equal to the thermal stress; whereas the total stress during the nighttime is far greater than the thermal stress. An explanation for this phenomenon is that during the night hours, the decline of the slab‘s near-surface temperature leads to a drop of the near-surface RH. This RH drop results in contraction therein and develops additional tensile stresses. The dissertation thus argues that estimating the environmental loadings by solely computing the thermally-induced stresses may reach delusive results. It recommends that the total environmental loadings of in-service slabs should be estimated by a sophisticated model coupling both moisture component and temperature component.

Are clustering effects accounted for in statistical analysis in leading dental specialty journals?

OBJECTIVES In dental research multiple site observations within patients or taken at various time intervals are commonplace. These clustered observations are not independent; statistical analysis should be amended accordingly. This study aimed to assess whether adjustment for clustering effects during statistical analysis was undertaken in five specialty dental journals. METHODS Thirty recent consecutive issues of Orthodontics (OJ), Periodontology (PJ), Endodontology (EJ), Maxillofacial (MJ) and Paediatric Dentristry (PDJ) journals were hand searched. Articles requiring adjustment accounting for clustering effects were identified and statistical techniques used were scrutinized. RESULTS Of 559 studies considered to have inherent clustering effects, adjustment for this was made in the statistical analysis in 223 (39.1%). Studies published in the Periodontology specialty accounted for clustering effects in the statistical analysis more often than articles published in other journals (OJ vs. PJ: OR=0.21, 95% CI: 0.12, 0.37, p<0.001; MJ vs. PJ: OR=0.02, 95% CI: 0.00, 0.07, p<0.001; PDJ vs. PJ: OR=0.14, 95% CI: 0.07, 0.28, p<0.001; EJ vs. PJ: OR=0.11, 95% CI: 0.06, 0.22, p<0.001). A positive correlation was found between increasing prevalence of clustering effects in individual specialty journals and correct statistical handling of clustering (r=0.89). CONCLUSIONS The majority of studies in 5 dental specialty journals (60.9%) examined failed to account for clustering effects in statistical analysis where indicated, raising the possibility of inappropriate decreases in p-values and the risk of inappropriate inferences.

THE ASSOCIATION BETWEEN CANCER-RELATED-FATIGUE, RESPONSE TO FATIGUE TREATMENT, AND CYTOKINES AND THEIR RECEPTORS, IN PATIENTS WITH ADVANCED CANCER

Background: Inflammation is implicated in the development of cancer related fatigue (CRF). However there is limited literature on the mediators of inflammation (namely), cytokines and their receptors, associated with clinically significant fatigue and response to treatment. Methods: We reviewed 37 advanced cancer patients with fatigue (≥4/10), who participated in two Randomized Controlled Trials, of anti-inflammatory agents (Thalidomide and Dexamethasone) for CRF. Responders showed improvement in FACIT-F subscale at the end of study (Day 15). Baseline patient characteristics and symptoms were assessed by FACIT-F, ESAS; serum cytokines [IL-1β and receptor antagonist (IL-1RA), IL-6, IL-6R, TNF-α and sTNF-R1 and R2, IL-8, IL-10, IL-17] levels measured by Luminex. Data were analyzed using principal component analysis (PCA) [reporting cumulative variance (variance) for the first four components] to determine their association with fatigue and response to treatment. Results: Females were 54%. Mean (SD) was as follows for age, 61(14); baseline FACIT (F) scores, 21.4(8.6); ESAS Fatigue item, 6.5(1.9); and FACIT-F change, 6.4(9.7); ESAS (fatigue) change, -2 (2.41). Baseline median in pg/mL for IL-6, TNF-α, IL-1β were 31.9; 18.9; 0.55, respectively. Change in IL-6 negatively correlated with change in FACIT-F scores (p=0.02). Baseline CRF (FACIT-F score) was associated with IL-6, IL-6R and IL-17, Variance = 78% whereas IL-10, IL-1RA, TNF-α and IL-1β were associated with improvement of CRF, Variance=74%. Conversely, IL-6 and IL-8 were associated with no improvement or worsening of CRF, Variance= 93%. Conclusions: Change in IL-6 negatively correlated with change in FACIT-F scores. IL-6, IL-6R and IL-17 are associated with CRF while IL-6 and IL-8 were associated with no improvement of CRF. Further studies are warranted confirm our findings.